Analysis of the functional EEG network in an Ecuadorian schizophrenia sample

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"apellidos" => "Shahsavand-Ananloo" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0213616321000264?idApp=UINPBA00004N" "url" => "/02136163/0000003500000004/v3_202112100830/S0213616321000264/v3_202112100830/en/main.assets" ] "en" => array:20 [ "idiomaDefecto" => true "cabecera" => "ORIGINAL ARTICLE" "titulo" => "Analysis of the functional EEG network in an Ecuadorian schizophrenia sample" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "216" "paginaFinal" => "224" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Alberto Rodríguez-Lorenzana, Mabel Torres-Tapia, Cesar Parra, Álvaro Díez, Antonio Arjona, Javier Gomez-Pilar, Erika Pasquel, Diego Granizo, Vicente Molina" "autores" => array:9 [ 0 => array:3 [ "nombre" => "Alberto" "apellidos" => "Rodríguez-Lorenzana" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0001" ] ] ] 1 => array:3 [ "nombre" => "Mabel" "apellidos" => "Torres-Tapia" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0001" ] ] ] 2 => array:3 [ "nombre" => "Cesar" "apellidos" => "Parra" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0001" ] ] ] 3 => array:3 [ "nombre" => "Álvaro" "apellidos" => "Díez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0002" ] ] ] 4 => array:3 [ "nombre" => "Antonio" "apellidos" => "Arjona" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0002" ] ] ] 5 => array:3 [ "nombre" => "Javier" "apellidos" => "Gomez-Pilar" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "c" "identificador" => "aff0003" ] ] ] 6 => array:3 [ "nombre" => "Erika" "apellidos" => "Pasquel" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "d" "identificador" => "aff0004" ] ] ] 7 => array:3 [ "nombre" => "Diego" "apellidos" => "Granizo" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "e" "identificador" => "aff0005" ] ] ] 8 => array:4 [ "nombre" => "Vicente" "apellidos" => "Molina" "email" => array:1 [ 0 => "vicente.molina@uva.es" ] "referencia" => array:4 [ 0 => array:2 [ "etiqueta" => "f" "identificador" => "aff0006" ] 1 => array:2 [ "etiqueta" => "g" "identificador" => "aff0007" ] 2 => array:2 [ "etiqueta" => "h" "identificador" => "aff0008" ] 3 => array:2 [ "etiqueta" => "*" "identificador" => "cor0001" ] ] ] ] "afiliaciones" => array:8 [ 0 => array:3 [ "entidad" => "Escuela de Psicología, Universidad de Las Américas, Av. de los Granados E12-41 y Colimes esq., Quito, Ecuador" "etiqueta" => "a" "identificador" => "aff0001" ] 1 => array:3 [ "entidad" => "Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain" "etiqueta" => "b" "identificador" => "aff0002" ] 2 => array:3 [ "entidad" => "Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain" "etiqueta" => "c" "identificador" => "aff0003" ] 3 => array:3 [ "entidad" => "San juan de dios specialized hospital, Calle San Juan de Dios S2 – 209, Quito,Ecuador" "etiqueta" => "d" "identificador" => "aff0004" ] 4 => array:3 [ "entidad" => "Sacred Heart Psychiatric Institute, Av. Manuel Córdova Galarza, km1, Quito, Ecuador" "etiqueta" => "e" "identificador" => "aff0005" ] 5 => array:3 [ "entidad" => "Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain" "etiqueta" => "f" "identificador" => "aff0006" ] 6 => array:3 [ "entidad" => "Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain" "etiqueta" => "g" "identificador" => "aff0007" ] 7 => array:3 [ "entidad" => "Neurosciences Institute of Castilla y León (INCYL), School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain" "etiqueta" => "h" "identificador" => "aff0008" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0001" "etiqueta" => "⁎" "correspondencia" => "Corresponding author at: Dept. of Psychiatry, University Hospital of Valladolid; Av. Ramón y Cajal, 7, Valladolid 48005, Spain." ] ] ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0002" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 3243 "Ancho" => 3000 "Tamanyo" => 610813 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0004" "detalle" => "Fig " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "a. Scatter plot depicting the association between connective parameters and cognitive scores in patients with schizophrenia and controls in the study sample. b. Scatter plot representing the association between connective parameters and cognitive scores in patients with schizophrenia and controls in the Ecuador cohort." ] ] ] "textoCompleto" => "IntroductionThe synchronization of oscillatory patterns is fundamental to the understanding of brain activity underlying cognitive processes, which require the integration of dispersed neuronal activity through short- and long-distance communication established by structural and functional connections. Perception, cognition, emotion and behavior seem to be determined more by the interaction between different neuronal assemblies distributed in the brain than by the local activation of an area.<a class="elsevierStyleCrossRef" href="#bib0001">1</a> For this reason, the study of the functioning of oscillatory patterns is central to the understanding of mental activity.<a class="elsevierStyleCrossRef" href="#bib0002">2</a>One of the connective parameters used in the analysis of the organization of oscillatory processes is the Small World (SW) properties of the functional connective network they form. This type of configuration is characterized by presenting a high degree of local clustering, which facilitates regional specialization, and a short average path length, which facilitates the integration of the activity of different neuronal populations.<a class="elsevierStyleCrossRef" href="#bib0003">3</a>,<a class="elsevierStyleCrossRef" href="#bib0004">4</a> Graph theory analyses applied to electrophysiological measurements<a class="elsevierStyleCrossRef" href="#bib0005">5</a>,<a class="elsevierStyleCrossRef" href="#bib0006">6</a> allow to identify this type of configuration. It has been proposed that the presence of higher values in this type of brain network properties translates into a greater capacity for integration and specialization and favors the efficient distribution of information.<a class="elsevierStyleCrossRef" href="#bib0007">7</a>,<a class="elsevierStyleCrossRef" href="#bib0008">8</a> The SW measure is defined as the ratio between the clustering coefficient (CLC), i.e., how interconnected a node is with adjacent nodes (and these with each other) and the characteristic path length (PL), the proximity with which a node is connected to each of the other nodes in the network.<a class="elsevierStyleCrossRef" href="#bib0009">9</a> Thus, the local CLC index represents an indicator of segregation and local efficiency of information transfer, probably related to regional specialization. The PL is interpreted as a metric of information integration in all areas,<a class="elsevierStyleCrossRef" href="#bib0010">10</a> this being more efficient the shorter the PL is. Since one of the conditions observed in some patients diagnosed with schizophrenia is the abnormal integration and segregation of neural networks,<a class="elsevierStyleCrossRef" href="#bib0011">11</a>,<a class="elsevierStyleCrossRef" href="#bib0012">12</a>,<a class="elsevierStyleCrossRef" href="#bib0013">13</a> the study of these parameters could be important for the better understanding of the etiopathogenic mechanisms of the syndrome.<a class="elsevierStyleCrossRef" href="#bib0014">14</a>Another type of parameter relevant to functional alterations in schizophrenia is the Connectivity Strength (CS) measure. CS measures the relationships between a given voxel and the whole brain connectivity matrix rather than relationships with individual regions or networks.<a class="elsevierStyleCrossRef" href="#bib0015">15</a> For this purpose, this measure summarizes the average connection value of all nodes in the network and can be calculated from phase-locking values (PLV), which in the case of EEG indicate the degree of synchronization between sensors.<a class="elsevierStyleCrossRef" href="#bib0016">16</a>Associations between alteration in the described parameters and cognitive performance have been reported.<a class="elsevierStyleCrossRef" href="#bib0017">17</a>,<a class="elsevierStyleCrossRef" href="#bib0018">18</a>,<a class="elsevierStyleCrossRef" href="#bib0019">19</a> Previous work based on both graph theory applied to EEG parameters<a class="elsevierStyleCrossRef" href="#bib0020">20</a>,<a class="elsevierStyleCrossRef" href="#bib0021">21</a> and functional magnetic resonance imaging (fMRI)<a class="elsevierStyleCrossRef" href="#bib0011">11</a>,<a class="elsevierStyleCrossRef" href="#bib0022">22</a> identify these types of networks as determinants in cognitive functioning, because a change in their pattern is observed between the resting state and during the performance of cognitive tasks in both schizophrenic patients and healthy individuals. Some results point to dysfunction of these networks in schizophrenia,<a class="elsevierStyleCrossRef" href="#bib0009">9</a>,<a class="elsevierStyleCrossRef" href="#bib0023">23</a>,<a class="elsevierStyleCrossRef" href="#bib0024">24</a> however in others no correlation is demonstrated between the clinical severity of psychosis and the disorganization of these networks.<a class="elsevierStyleCrossRef" href="#bib0025">25</a>,<a class="elsevierStyleCrossRef" href="#bib0026">26</a>The study of brain connectivity in schizophrenia and its relationship with cognitive performance has a long tradition in developed countries; however, in the Andean region (Ecuador, Peru, Bolivia and Colombia) no research of this type has been conducted to date in schizophrenia, so it is necessary to analyze the possible role of functional network organization in these populations and whether there is any particularity that could be linked to genetics or other environmental and cultural conditions.Material and methodsSubjetsTwenty-four patients diagnosed with schizophrenia (17 men) and thirty-two healthy controls (22 men) were included. Written informed consent was obtained from all participants after full printed information. The ethical committees of the Universidad San Francisco de Quito approved the study.Patients were diagnosed by the psychiatrists in charge of their treatment according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 5th edition, based on complete interviews and all available evidence. Healthy controls were recruited through contacts of university research staff. Sociodemographic and clinical characteristics are presented in <a class="elsevierStyleCrossRef" href="#tbl0001">Table 1</a>.<elsevierMultimedia ident="tbl0001"></elsevierMultimedia>Current treatment dose was converted to mg/d in chlorpromazine equivalents.Exclusion criteria for patients and controls included history of neurological disease (including head trauma with loss of consciousness), past or present substance dependence (except nicotine and caffeine), not having completed elementary school. In addition, controls with any current psychiatric diagnosis or treatment were excluded.All patients with schizophrenia were receiving stable doses of atypical antipsychotics.Cognitive assessmentThe following tests was used in the cognitive assessment process:Brief Assessment in Cognition in Schizophrenia (BACS)<a class="elsevierStyleCrossRef" href="#bib0027">27</a> using the Spanish adaptation of the battery.<a class="elsevierStyleCrossRef" href="#bib0028">28</a>EEG recordingEEG data acquisition and preprocessingEEG recordings were obtained using Brain Recorder® software (Brain Products Gmbh; Munich, Germany), a 64-channel BrainAmp® amplifier (Brain Products Gmbh; Munich, Germany).The International System 10-20 was used for electrode placement, in addition to a ground electrode at the AFz site. During recording, the reference was taken over the Cz electrode, allowing the final inclusion in the study of a total of 62 recording channels. The impedance of the electrodes was kept below 5 KΩ at all times. The sampling rate was 250 Hz and the signal was recorded continuously.Two electrodes were extracted to record the possible noise source derived from eye movements.Odd-ball paradigmElectrophysiological evaluation in the presence of cognitive stimulation was performed using an auditory odd-ball paradigm (with unexpected target stimulus). All participants listened to 600 binaural tones presented in random order with an inter-stimulus interval that fluctuated randomly between 1.16 and 1.44 s; the paradigm extended for 13 min. Three types of tones were presented: target tone (500 Hz tone; probability; 0.2), distractor tone (1000 Hz tone; probability; 0.2), and standard tone (2000 Hz tone; probability; 0.6).Subjects who responded correctly to at least 50% of the stimuli included in the paradigm were included in the study. Only the response to correctly attended target tones was used for subsequent EEG analyses.EEG processingThe time-frequency representation of the EEG was calculated using the continuous wavelet transform (CWT), including frequencies from 1 to 70 Hz. In this way, two windows derived from the division of the 1s evoked responses [(-300-700) ms] were generated: 1) pre-stimulus [(-3000) ms before the onset of the target stimulus]; and 2) response [(300) ms centered around the response peak].In order to systematize artifact rejection, a three-step approach developed by the group in previous studies<a class="elsevierStyleCrossRef" href="#bib0029">29</a>,<a class="elsevierStyleCrossRef" href="#bib0030">30</a> was used.The parameters included in the analyses were the following; 1) path length, 2) clustering coefficient, 3) small world and 4) connectivity strength and their respective modulations upon realization of the odd-ball paradigm.For the construction of graphs derived from the EEG analysis, the measurements recorded at the 62 electrodes used in the study were taken. The activity of each electrode was interpreted as representing a node of the network, while the links were calculated based on the phase-locking between each pair of electrodes.<a class="elsevierStyleCrossRef" href="#bib0031">31</a> To estimate the signal synchrony between electrodes, the phase-locking values (PLV) in successive trials were used.<a class="elsevierStyleCrossRef" href="#bib0032">32</a> CWT was used in the PLV calculation,<a class="elsevierStyleCrossRef" href="#bib0033">33</a> using the analyses developed by the research group in previous studies,<a class="elsevierStyleCrossRef" href="#bib0016">16</a>,<a class="elsevierStyleCrossRef" href="#bib0034">34</a> represented in the following formula:<elsevierMultimedia ident="ueqn0001"></elsevierMultimedia>where N is the number of attempts, ∆φxy is the phase difference between the x and y signals, k is the time interval and s is the wavelet scaling factor.The network segregation was analyzed using the CLC parameter.<a class="elsevierStyleCrossRef" href="#bib0035">35</a> This analysis is expressed as follows:<elsevierMultimedia ident="ueqn0002"></elsevierMultimedia>where wxy denotes the weight of the connection between electrodes i and j. The task-associated CLC modulation was defined as the change in CLC values between the prestimulus and response windows.For the analysis of network integration, the PL parameter<a class="elsevierStyleCrossRef" href="#bib0035">35</a> was used. The following equation was used for this purpose:<elsevierMultimedia ident="ueqn0003"></elsevierMultimedia>where dij indicates the minimum distance between electrodes i and j. The PL modulation associated with the task was defined as the change in PL values between the prestimulus and response windows.The balance between segregation and integration was calculated using the SW parameter.<a class="elsevierStyleCrossRef" href="#bib0035">35</a> The SW modulation associated with the task was defined as the change in SW values between the pre-stimulus and response windows.<elsevierMultimedia ident="ueqn0004"></elsevierMultimedia>The CS was calculated using the following formula:<elsevierMultimedia ident="ueqn0005"></elsevierMultimedia>where Wij refers to PLV between nodes i and j, and N is the total number of nodes in the network.<a class="elsevierStyleCrossRef" href="#bib0034">34</a> Task-associated CS modulation was defined as the change in CS values between the pre-stimulus and response windows.<a class="elsevierStyleCrossRef" href="#bib0016">16</a>The EEG recording and analysis equipment and procedures were identical to those used in,<a class="elsevierStyleCrossRef" href="#bib0009">9</a>,<a class="elsevierStyleCrossRef" href="#bib0036">36</a> in order to be able to compare the results in the corresponding samples.Statistical analysesDemographic, cognitive, clinical and neurophysiological data were compared between the groups into which the sample was divided using Kruskal-Wallis tests; in cases where a significant group effect was identified, the Mann-Whitney test was used to make comparisons between pairs of groups. Analyses were also performed to assess the effects of drug treatment on altered connective parameters in patients using Spearman's Rho.Analysis of connective parametersThe parameters; Small World, Path Length, clustering coefficient, connectivity Strength, modulation in path length, modulation in small world parameter, modulation in clustering coefficient parameter and modulation in connectivity strength parameter were included in the analyses. The Kruskal-Wallis test was used for overall sample comparison and the Mann-Withney test for pairwise comparison when a significant effect was detected for the group.Comparison of connective parameters between Ecuadorian and Spanish clinical populationWe analyzed whether the alterations in the functional connective network were similar between patients with schizophrenia in the Ecuadorian and Spanish samples. For this purpose, comparisons were made using U-Mann Whitney tests for the altered parameters.Relationship between connective disorders and cognitive performanceMultiple stepwise linear regressions were performed using as dependent variables the scores obtained in the cognitive battery by all participants in the study sample and as independent variables the connective parameters that showed a significant alteration in the previous analyses were taken into account. (see <a class="elsevierStyleCrossRef" href="#fig0002">Figure 2</a>a). These same analyses were performed in the Ecuadorian cohort (see <a class="elsevierStyleCrossRef" href="#fig0002">Figure 2</a>b).ResultsThe age and sex of the patients were balanced in both samples. No significant differences were found in the sex distribution between the group of patients diagnosed with schizophrenia and the controls, (x2=4.93, df=2, p=0.09) x2 and age (K=0.831, df=2, p=0.66).Shapiro-Wilk test was performed to test the normality of the connective parameters found that the variables PL (modulation), (W=0.96, p=0.02), SW (pre-stimulus), (W=0.94, p<0.001), CLC (pre-stimulus) (W=0. 88, p<0.001), PL (pre-stimulus) (W=0.92, p<0.001), and CS (pre-stimulus), (W=0.96, p=0.02) do not exhibit normality so nonparametric tests were used for statistical analyses.No significant correlations were found between antipsychotic treatment dose and the studied parameters: CLC (pre-stimulus), (rho= -0.247, S=1921, p=0.279); PL (pre-stimulus), (rho=-0.179, S=1816.4, p=0.284); CS (pre-stimulus), (rho=- 0.157, S=1782.3, p=0.496); SW (pre-stimulus), (rho=0.151, S=1307.8, p=0.514), CLC modulation (rho= 0.08, S=1410.3, p=0.717); PL modulation (rho=-0.019, S=1569.2, p=0.935); CS modulation (rho=- 0.086, S=1408.3, p=0.713); SW modulation (rho=0.039, S=1480.7,p=0.868)Brain connectivity patternsFor the calculation of connectivity metrics the mean number of segments used in patients was 80.79 (sd 20.96) and 88.88(sd 13.78) in controls.Significantly higher values were found in schizophrenia patients than in controls in the parameters Clustering coefficient (U=239, p<0.008); Path Length (U=223, p<0.003; Connectivity Strength (U=270, p<0.029); connectivity strength modulation (U=280, p<0.043 and lower values of Small World (U=226, p<0.004). See <a class="elsevierStyleCrossRef" href="#tbl0002">Table 2</a>.<elsevierMultimedia ident="tbl0002"></elsevierMultimedia>Comparison of connective parameters between the Spanish and Ecuadorian clinical populationThe experimental protocol was applied identically in the Spanish and Ecuadorian samples.No differences were found in sex (x2=0.034,df=1,p=0.853) or age (K=0.28, df=1,p=0.6) between the Spanish and Ecuadorian populations. Ecuadorian patients showed higher values compared to Spanish patients in the Clustering Coefficient (U=134, p=0.004) and Path Length (U=138, p=0.006) parameters and lower values in the Small World parameter (U=142, p=0.007). These results are illustrated in <a class="elsevierStyleCrossRef" href="#fig0001">Figure 1</a>.<elsevierMultimedia ident="fig0001"></elsevierMultimedia>Relationship between connective parameters and cognitive performanceThe basal CS parameter is a good predictor of performance inversely in the variables working memory (R2=0.07;B=-290;T=4.971;p=0.03)and motor speed (R2=0.24;B=-272;T=9.44;p=0.03). The SW parameter directly predicted performance in the domains processing speed (R2=0.13;B=377;T=8.947;p=0.004) and Tower of London (R2=0.08;B=310;T=5.746;p=0.02). The basal PL parameter inversely predicted performance in the motor speed variable (R2=0.24;B=-361;T=9.44;p=0.005). Finally, the resting state clustering coefficient inversely predicted performance in the verbal memory sub-category (R2=0.08;B=-315;T=5.936;p=0.02). The model showed no predictive ability of any of the connective parameters on the verbal fluency sub-category of the BACS test. See <a class="elsevierStyleCrossRef" href="#fig0002">Figure 2</a>a.<elsevierMultimedia ident="fig0002"></elsevierMultimedia>DiscussionHigher CS values were identified in patients diagnosed with schizophrenia compared to healthy controls as well as a significantly higher deficit in the modulation of this parameter. In addition, SW values (in the pre-stimulated condition) were lower in the schizophrenia group. Patients also showed higher PL and CLC values in this condition than controls. Finally, the alteration of CS, SW, CLC and PL parameters was related to performance in neuropsychological tests.The findings identified in our sample are in line with those reported in other populations such as Spain. A study conducted in a sample with schizophrenia in Spain identified higher CS values at baseline and during an attentional task versus controls.<a class="elsevierStyleCrossRef" href="#bib0016">16</a>,<a class="elsevierStyleCrossRef" href="#bib0037">37</a> For its part, the lower SW index in Ecuadorian patients has been described in a Spanish sample.<a class="elsevierStyleCrossRef" href="#bib0038">38</a> Finally, in a Spanish sample it was observed that patients showed higher baseline recordings than controls in CLC and PL parameters.<a class="elsevierStyleCrossRef" href="#bib0034">34</a>However, significant differences are observed in some of these parameters between both populations (see <a class="elsevierStyleCrossRef" href="#fig0001">Figure 1</a>). A possible explanation for the differences found may be determined by the heterogeneity inherent to the condition studied. This heterogeneity may also manifest itself in measures of brain connectivity.<a class="elsevierStyleCrossRef" href="#bib0039">39</a>To our knowledge, no previous research had performed a comparative analysis of the presence of these alterations in two populations with different genetic, socioeconomic, and cultural conditions. One of the strengths of this study is that the results were compared with the results of investigations that applied the same methodology of data processing and analysis, which guarantees the homogeneity of the protocols and allows reinforcing the starting hypothesis regarding the universality of the disease in terms of functional connective alterations.The results obtained at baseline in the CS parameter by patients diagnosed with schizophrenia could be reflecting a connective condition contributing to the overload of the neural ensembles. The presence of higher resting-state density values found in patients diagnosed with schizophrenia could hinder the modulatory capacity of neural ensembles in this group.<a class="elsevierStyleCrossRef" href="#bib0040">40</a> This is consistent with reports of a GABAergic deficit identified in schizophrenia.<a class="elsevierStyleCrossRef" href="#bib0041">41</a> Dysregulation in the excitatory/inhibitory balance<a class="elsevierStyleCrossRef" href="#bib0042">42</a> could cause the basal hyper-synchronization present in some patients diagnosed with schizophrenia and be reflected through higher CS values.An increased modulation of the CS parameter was also identified in the group of patients diagnosed with schizophrenia. In the literature we can find several studies that using different imaging techniques in their analysis,<a class="elsevierStyleCrossRef" href="#bib0043">43</a>,<a class="elsevierStyleCrossRef" href="#bib0044">44</a>,<a class="elsevierStyleCrossRef" href="#bib0045">45</a> have reported the presence of an increased activity of the default neural network in schizophrenia. The activation of neural mechanisms not associated with the performance of a simple attentional task could be behind the inefficiency shown by some patients to perform such tasks.Thus, difficulties in modulation could mean that while in controls there is a decrease in global activation before a task (which probably responds to the need to activate more networks involved in cognitive processing), patients increase their activity even more, thus producing a failure in specialization.The presence of lower values in the SW parameter in basal state with respect to controls identified in the group of patients diagnosed with schizophrenia could be linked to worse processing reflected in cognitive tests. Small-world organization has been shown to be fundamental in information transfer in terms of functional integration and segregation,<a class="elsevierStyleCrossRef" href="#bib0046">46</a>,<a class="elsevierStyleCrossRef" href="#bib0008">8</a>,<a class="elsevierStyleCrossRef" href="#bib0047">47</a> efficient levels of information segregation and integration with low energy and wiring costs are linked to a number of benefits for connective functioning, such as, a high degree of short global communication with relatively few connections.<a class="elsevierStyleCrossRef" href="#bib0048">48</a>In the cognitive section, our results indicate a predictive relationship linking a higher CS index to worse results in motor speed, which is in line with previous studies suggesting that performance in this cognitive function would depend on the functional hyperactivation shown by patients' networks.<a class="elsevierStyleCrossRef" href="#bib0049">49</a> Motor speed was also inversely associated with the PL index. This association could reflect the importance of network integration for the correct performance of cognitive tasks that require the activation of different processing levels. From a theoretical point of view, these signs could be a consequence of oscillatory alterations mediated by inhibitory dysregulations identified in the disease.<a class="elsevierStyleCrossRef" href="#bib0042">42</a>On the other hand, participants who performed worse in the processing speed domain presented lower resting state SW levels. Slower processing speed could therefore be associated with a less globally integrated and less clustered resting functional organization. This is consistent with evidence reported in preceding studies indicating a reduction in processing speed in patients diagnosed with schizophrenia.<a class="elsevierStyleCrossRef" href="#bib0050">50</a>,<a class="elsevierStyleCrossRef" href="#bib0051">51</a>A relationship was also found between performance on the verbal memory task and the CLC index. As the clustering values increased the worse the participants' performance was this domain. Previous studies have reported this same relationship<a class="elsevierStyleCrossRef" href="#bib0052">52</a> which could reflect the dependence of verbal memory on the level of functional segregation shown by the networks in the basal state.It has been proposed that an excess of cortical activation may result in an overload of working memory processes beyond their capacity.<a class="elsevierStyleCrossRef" href="#bib0053">53</a>,<a class="elsevierStyleCrossRef" href="#bib0054">54</a>,<a class="elsevierStyleCrossRef" href="#bib0055">55</a> Our results point in the same line, higher indexes in the CLC parameter are related to worse performance in working memory.Finally, the magnitude of SW predicted better scores in executive function. The relationship identified in the results between SW measures and this domain could be indicative of the dependence of executive function on the small-world configuration of the networks in the basal state.Our study has limitations, most of them related to the small sample size. This limitation may have had a special incidence in the comparisons made between the groups of patients diagnosed with schizophrenia from Ecuador and Spain (n=24) and (n=22) respectively, and may have been one of the circumstances that contributed to the differences found between the connective parameters of both populations. On the other hand, significant differences were found in the years of schooling of patients and controls, so we cannot rule out that this factor may explain, at least in part, the differences in the connective patterns of both groups. Nevertheless, the overall pattern of the data in the Ecuadorian population was consistent with that identified in previous studies of similar populations in other countries. The inherent heterogeneity of the syndrome, which has been discussed previously, could also have contributed to the presence of these differences. Moreover, these results should be replicated in samples without neuroleptic treatment.ConclusionsEcuadorian patients diagnosed with schizophrenia present connective alterations similar to those found in other samples with different genetic, environmental and cultural conditions. Moreover, these alterations were related to worse performance in several cognitive domains.Ethical considerationsThe study protocol was accepted by the ethical committees of the Universidad San Francisco de Quito (2017-042E).FundingThis study is part of a research programme investigating funded by the Universidad de Las Américas." "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres1626078" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abss0001" "titulo" => "Background and objectives" ] 1 => array:2 [ "identificador" => "abss0002" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abss0005" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abss0006" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1451322" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "sec0001" "titulo" => "Introduction" ] 3 => array:3 [ "identificador" => "sec0002" "titulo" => "Material and methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0003" "titulo" => "Subjets" ] 1 => array:2 [ "identificador" => "sec0004" "titulo" => "Cognitive assessment" ] 2 => array:3 [ "identificador" => "sec0005" "titulo" => "EEG recording" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0006" "titulo" => "EEG data acquisition and preprocessing" ] 1 => array:2 [ "identificador" => "sec0007" "titulo" => "Odd-ball paradigm" ] ] ] 3 => array:2 [ "identificador" => "sec0008" "titulo" => "EEG processing" ] 4 => array:3 [ "identificador" => "sec0009" "titulo" => "Statistical analyses" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0010" "titulo" => "Analysis of connective parameters" ] 1 => array:2 [ "identificador" => "sec0011" "titulo" => "Comparison of connective parameters between Ecuadorian and Spanish clinical population" ] 2 => array:2 [ "identificador" => "sec0012" "titulo" => "Relationship between connective disorders and cognitive performance" ] ] ] ] ] 4 => array:3 [ "identificador" => "sec0013" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0014" "titulo" => "Brain connectivity patterns" ] 1 => array:2 [ "identificador" => "sec0015" "titulo" => "Comparison of connective parameters between the Spanish and Ecuadorian clinical population" ] 2 => array:2 [ "identificador" => "sec0016" "titulo" => "Relationship between connective parameters and cognitive performance" ] ] ] 5 => array:2 [ "identificador" => "sec0017" "titulo" => "Discussion" ] 6 => array:2 [ "identificador" => "sec0018" "titulo" => "Conclusions" ] 7 => array:2 [ "identificador" => "sec0019" "titulo" => "Ethical considerations" ] 8 => array:2 [ "identificador" => "sec0020" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "xack573809" "titulo" => "Acknowledgements" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2021-02-26" "fechaAceptado" => "2021-06-30" "PalabrasClave" => array:1 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1451322" "palabras" => array:4 [ 0 => "Functional network" 1 => "Graph-theory" 2 => "Schizophrenia" 3 => "Electroencephalography" ] ] ] ] "tieneResumen" => true "resumen" => array:1 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "Background and objectivesHigher mental functions depend on global functional coordination of the brain. Our aim was to study the baseline condition and modulation of functional networks in a previously unevaluated clinical population, compare the results with a population from another country, and analyze their relationship with cognitive functioning. MethodsWe evaluated the functioning of brain networks by EEG in 24 patients with schizophrenia and 32 healthy Ecuadorian controls. EEG recordings were made at rest and while performing a P300 task. Small world (SW), Path Length (PL), clustering coefficient (CLC) and connective strength (CS) values were calculated in both conditions. The values obtained were compared between groups, with the results of Spanish patients, and the relationship between the connective parameters and the cognitive performance of the participants was analyzed. ResultsHigher PL, CLC and CS values were identified in patients diagnosed with schizophrenia compared to controls (in basal condition) and lower SW values in this same condition. Ecuadorian patients obtained higher values than Spanish patients in the PL and CLC parameters and lower values for the SW parameter, despite these differences, the pattern of alteration in both samples followed the same trend. Finally, the alteration of CS, SW, CLC and PL parameters at baseline was related to cognitive performance. ConclusionThe connective alterations identified in Ecuadorian schizophrenic patients are consistent with those found in another sample with different genetic, environmental and cultural conditions. In addition, these alterations were associated with worse performance in different cognitive domains." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abss0001" "titulo" => "Background and objectives" ] 1 => array:2 [ "identificador" => "abss0002" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abss0005" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abss0006" "titulo" => "Conclusion" ] ] ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<elsevierMultimedia ident="ecom0001"></elsevierMultimedia>" "etiqueta" => "Appendix" "titulo" => "Supplementary materials" "identificador" => "sec0022" ] ] ] ] "multimedia" => array:10 [ 0 => array:8 [ "identificador" => "fig0001" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1602 "Ancho" => 3000 "Tamanyo" => 300147 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0003" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Differences between Spanish and Ecuadorian patient groups in connective parameters." ] ] 1 => array:8 [ "identificador" => "fig0002" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 3243 "Ancho" => 3000 "Tamanyo" => 610813 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0004" "detalle" => "Fig " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "a. Scatter plot depicting the association between connective parameters and cognitive scores in patients with schizophrenia and controls in the study sample. b. Scatter plot representing the association between connective parameters and cognitive scores in patients with schizophrenia and controls in the Ecuador cohort." ] ] 2 => array:8 [ "identificador" => "tbl0001" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0001" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "Note: T= student's T, X2=Chi-square used for M:F Ratio only," "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0001"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0002"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Ecuador</th><a name="en0003"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Schizophrenia patients</th><a name="en0004"></a><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Healthy controls</th></tr><tr title="table-row"><a name="en0005"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0006"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Schizophrenia patients \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0007"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Healthy controls \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0008"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">T/X2 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0009"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">España \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0010"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Ecuador \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0011"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">T/X2 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0012"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">España \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0013"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Ecuador \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0014"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">T/X2 \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0015"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">M:F Ratio \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0016"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17:07 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0017"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">22:12 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0018"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.24 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0019"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">13:07 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0020"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17:07 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0021"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.17 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0022"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17:11 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0023"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12:05 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0024"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.45 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0025"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0026"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">37.96(1.76) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0027"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">36.56(11.48) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0028"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.44 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0029"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">38.4(13.09) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0030"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">37.95(12.76) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0031"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.11 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0032"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">36.71(11.83) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0033"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">37.82(9.23) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0034"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-0.33 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0035"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Education (years) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0036"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12.75(3.19) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0037"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.55(3.44) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0038"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-3.79<a class="elsevierStyleCrossRef" href="#tb1fn3">⁎⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0039"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">13.85(4.04) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0040"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12.75(3.19) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0041"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.91 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0042"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16(2.2) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0043"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.53(3.73) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0044"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-0.37 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0045"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Positive PANSS \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0046"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">15.64(6.32) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0047"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">NA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0048"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.11 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0049"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">12.44(4.59 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0050"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">15.63(6.32) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0051"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-1.72 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0052"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">NA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0053"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">NA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0054"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0055"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Negative PANSS \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0056"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17.95(7.01) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0057"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">NA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0058"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.27 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0059"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">18.56(7.99) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0060"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17.95(7.01) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0061"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.25 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0062"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">NA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0063"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">NA \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0064"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0065"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Verbal memory \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0066"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">32.83(7.39) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0067"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">45(11.19) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0068"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-4.62<a class="elsevierStyleCrossRef" href="#tb1fn3">⁎⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0069"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">36.67(9.21) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0070"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">32.83(7.39) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0071"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.43 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0072"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">49.21(9.38) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0073"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">41.56(10.86) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0074"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.46<a class="elsevierStyleCrossRef" href="#tb1fn1">*</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0075"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Working memory \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0076"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">14.57(4.23) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0077"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">19.63(3.52) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0078"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-4.79<a class="elsevierStyleCrossRef" href="#tb1fn3">⁎⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0079"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">15.87(4.09) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0080"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">14.66(4.22) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0081"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.87 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0082"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">21.78(3.52) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0083"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">17.81(3.05) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0084"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.77<a class="elsevierStyleCrossRef" href="#tb1fn3">⁎⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0085"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Motor speed \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0086"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">35.04(13.26) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0087"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">65.31(11.72) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0088"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-9.04<a class="elsevierStyleCrossRef" href="#tb1fn3">⁎⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0089"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">44.2(14.75) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0090"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">35.04(13.26) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0091"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">2.01 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0092"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">66.46(14.28) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0093"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">61.5(7.65) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0094"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.284 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0095"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Verbal Fluency \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0096"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.96(5.47) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0097"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">21.40(9.59) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0098"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-2.03<a class="elsevierStyleCrossRef" href="#tb1fn1">*</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0099"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">18.61(8) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0100"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.95(5.47) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0101"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.76 \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0102"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">23.93(11.45) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0103"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">22.71(3.77) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0104"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.41 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0105"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Processing speed \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0106"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">46.58(14.46) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0107"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">67.25(10.58) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0108"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-6.18<a class="elsevierStyleCrossRef" href="#tb1fn3">⁎⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0109"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">65.67(13.51) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0110"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">46.58(14.46) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0111"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">4.11<a class="elsevierStyleCrossRef" href="#tb1fn3">⁎⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0112"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">68.64(14.12) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0113"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">68.62(9.7) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0114"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0115"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Tower of London \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0116"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">11.38(4.55) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0117"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.94(3) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0118"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-5.51<a class="elsevierStyleCrossRef" href="#tb1fn3">⁎⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0119"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">15.87(3.66) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0120"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">11.37(4.54) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0121"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">3.22<a class="elsevierStyleCrossRef" href="#tb1fn2">⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0122"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.92(3.38) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0123"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">16.37(3.22) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0124"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.53 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2768869.png" ] ] ] "notaPie" => array:3 [ 0 => array:3 [ "identificador" => "tb1fn1" "etiqueta" => "⁎" "nota" => "=p<0.05," ] 1 => array:3 [ "identificador" => "tb1fn2" "etiqueta" => "⁎⁎" "nota" => "=p<0.01," ] 2 => array:3 [ "identificador" => "tb1fn3" "etiqueta" => "⁎⁎⁎" "nota" => "=p<0.001" ] ] ] "descripcion" => array:1 [ "en" => "Sociodemographic, clinical, and cognitive data of patient and controls." ] ] 3 => array:8 [ "identificador" => "tbl0002" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0002" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "Significant differences:" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0125"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0126"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Healthy controls \t\t\t\t\t\t\n \t\t\t\t\t\t</th><a name="en0127"></a><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Schizophrenia patients \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0128"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">SW (pre-stimulus) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0129"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.9281 (0.014) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0130"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.9082 (0.025)<a class="elsevierStyleCrossRef" href="#tb2fn2">⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0131"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">SW (modulation) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0132"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-0.0004 (0.005) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0133"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">-0.0005 (0.01) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0134"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">CS (pre-stimulus) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0135"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.3141 (0.020) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0136"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.3226 (0.043)<a class="elsevierStyleCrossRef" href="#tb2fn1">*</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0137"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">CS (modulation) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0138"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.0021 (0.007) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0139"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0,0020 (0.009)<a class="elsevierStyleCrossRef" href="#tb2fn1">*</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0140"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">CLC (pre-stimulus) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0141"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.0061 (0.002) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0142"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.0086 (0.004)<a class="elsevierStyleCrossRef" href="#tb2fn2">⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0143"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">CLC (modulation) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0144"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.0003 (0.001) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0145"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.0003 (0.002) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0146"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">PL (pre-stimulus) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0147"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.0845 (0.015) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0148"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">1.1126 (0.035)<a class="elsevierStyleCrossRef" href="#tb2fn2">⁎⁎</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><a name="en0149"></a><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">PL (modulation) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0150"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.0002 (0.007) \t\t\t\t\t\t\n \t\t\t\t</td><a name="en0151"></a><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="top">0.0011 (0.015) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2768868.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tb2fn1" "etiqueta" => "⁎" "nota" => "p <0.05 in the schizophrenia group compared to the control group." ] 1 => array:3 [ "identificador" => "tb2fn2" "etiqueta" => "⁎⁎" "nota" => "p <0.01 in the schizophrenia groups compared to the control group." ] ] ] "descripcion" => array:1 [ "en" => "Values of connective parameters in basal state and modulation for Ecuadorian patients and controls." ] ] 4 => array:6 [ "identificador" => "ecom0001" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "detalles" => array:1 [ 0 => array:3 [ "identificador" => "alt0005" "detalle" => "Image, application " "rol" => "short" ] ] "Ecomponente" => array:2 [ "fichero" => "mmc1.doc" "ficheroTamanyo" => 78336 ] ] 5 => array:5 [ "identificador" => "ueqn0001" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "PLVxy(k,s)=1N|∑n=1NeΔφxy(k,s,n)|," "Fichero" => "STRIPIN_si3.jpeg" "Tamanyo" => 191 "Alto" => 40 "Ancho" => 188 ] ] 6 => array:5 [ "identificador" => "ueqn0002" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "CLC=(N3)∑i,j,h∈ni≠j,i≠h,j≠h(wijwihwjh)1/3" "Fichero" => "STRIPIN_si4.jpeg" "Tamanyo" => 215 "Alto" => 53 "Ancho" => 241 ] ] 7 => array:5 [ "identificador" => "ueqn0003" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "PL=1N·(N−1)∑i,j∈ni≠jdij" "Fichero" => "STRIPIN_si5.jpeg" "Tamanyo" => 194 "Alto" => 53 "Ancho" => 145 ] ] 8 => array:5 [ "identificador" => "ueqn0004" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "SW=CLCPL" "Fichero" => "STRIPIN_si6.jpeg" "Tamanyo" => 169 "Alto" => 31 "Ancho" => 62 ] ] 9 => array:5 [ "identificador" => "ueqn0005" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "CS=∑i=1N∑j>iwijN(N−1)/2" "Fichero" => "STRIPIN_si7.jpeg" "Tamanyo" => 179 "Alto" => 40 "Ancho" => 119 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "cebibsec1" "bibliografiaReferencia" => array:55 [ 0 => array:3 [ "identificador" => "bib0001" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "MA Lindquist" 1 => "J Meng Loh" 2 => "LY Atlas" 3 => "TD Wager" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:6 [ "tituloSerie" => "Neuroimage" "fecha" => "2009" "volumen" => "45" "numero" => "1" "paginaInicial" => "187" "paginaFinal" => "198" ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0002" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Neural synchrony in cortical networks: history, concept and current status" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:7 [ 0 => "PJ Uhlhaas" 1 => "G Pipa" 2 => "B Lima" 3 => "L Melloni" 4 => "S Neuenschwander" 5 => "D Nikolić" 6 => "W. 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ORIGINAL ARTICLE

Alberto Rodríguez-Lorenzanaa, Mabel Torres-Tapiaa, Cesar Parraa, Álvaro Díezb, Antonio Arjonab, Javier Gomez-Pilarc, Erika Pasqueld, Diego Granizoe, Vicente Molinaf,g,h,

Corresponding author

vicente.molina@uva.es

Corresponding author at: Dept. of Psychiatry, University Hospital of Valladolid; Av. Ramón y Cajal, 7, Valladolid 48005, Spain.

a Escuela de Psicología, Universidad de Las Américas, Av. de los Granados E12-41 y Colimes esq., Quito, Ecuador

b Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain

c Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain

d San juan de dios specialized hospital, Calle San Juan de Dios S2 – 209, Quito,Ecuador

e Sacred Heart Psychiatric Institute, Av. Manuel Córdova Galarza, km1, Quito, Ecuador

f Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain

g Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain

h Neurosciences Institute of Castilla y León (INCYL), School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain

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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0001" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0007">Introduction</span><p id="para0005" class="elsevierStylePara elsevierViewall">The synchronization of oscillatory patterns is fundamental to the understanding of brain activity underlying cognitive processes&#44; which require the integration of dispersed neuronal activity through short- and long-distance communication established by structural and functional connections&#46; Perception&#44; cognition&#44; emotion and behavior seem to be determined more by the interaction between different neuronal assemblies distributed in the brain than by the local activation of an area&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a> For this reason&#44; the study of the functioning of oscillatory patterns is central to the understanding of mental activity<span class="elsevierStyleInf">&#46;</span><a class="elsevierStyleCrossRef" href="#bib0002"><span class="elsevierStyleSup">2</span></a></p><p id="para0006" class="elsevierStylePara elsevierViewall">One of the connective parameters used in the analysis of the organization of oscillatory processes is the Small World &#40;SW&#41; properties of the functional connective network they form&#46; This type of configuration is characterized by presenting a high degree of local clustering&#44; which facilitates regional specialization&#44; and a short average path length&#44; which facilitates the integration of the activity of different neuronal populations<span class="elsevierStyleInf">&#46;</span><a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0004"><span class="elsevierStyleSup">4</span></a> Graph theory analyses applied to electrophysiological measurements<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">5</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0006"><span class="elsevierStyleSup">6</span></a> allow to identify this type of configuration&#46; It has been proposed that the presence of higher values in this type of brain network properties translates into a greater capacity for integration and specialization and favors the efficient distribution of information<span class="elsevierStyleInf">&#46;</span><a class="elsevierStyleCrossRef" href="#bib0007"><span class="elsevierStyleSup">7</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0008"><span class="elsevierStyleSup">8</span></a> The SW measure is defined as the ratio between the clustering coefficient &#40;CLC&#41;&#44; i&#46;e&#46;&#44; how interconnected a node is with adjacent nodes &#40;and these with each other&#41; and the characteristic path length &#40;PL&#41;&#44; the proximity with which a node is connected to each of the other nodes in the network<span class="elsevierStyleInf">&#46;</span><a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a> Thus&#44; the local CLC index represents an indicator of segregation and local efficiency of information transfer&#44; probably related to regional specialization&#46; The PL is interpreted as a metric of information integration in all areas&#44;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">10</span></a> this being more efficient the shorter the PL is&#46; Since one of the conditions observed in some patients diagnosed with schizophrenia is the abnormal integration and segregation of neural networks&#44;<a class="elsevierStyleCrossRef" href="#bib0011"><span class="elsevierStyleSup">11</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0012"><span class="elsevierStyleSup">12</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0013"><span class="elsevierStyleSup">13</span></a> the study of these parameters could be important for the better understanding of the etiopathogenic mechanisms of the syndrome&#46;<a class="elsevierStyleCrossRef" href="#bib0014"><span class="elsevierStyleSup">14</span></a></p><p id="para0007" class="elsevierStylePara elsevierViewall">Another type of parameter relevant to functional alterations in schizophrenia is the Connectivity Strength &#40;CS&#41; measure&#46; CS measures the relationships between a given voxel and the whole brain connectivity matrix rather than relationships with individual regions or networks&#46;<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">15</span></a> For this purpose&#44; this measure summarizes the average connection value of all nodes in the network and can be calculated from phase-locking values &#40;PLV&#41;&#44; which in the case of EEG indicate the degree of synchronization between sensors&#46;<a class="elsevierStyleCrossRef" href="#bib0016"><span class="elsevierStyleSup">16</span></a></p><p id="para0008" class="elsevierStylePara elsevierViewall">Associations between alteration in the described parameters and cognitive performance have been reported&#46;<a class="elsevierStyleCrossRef" href="#bib0017"><span class="elsevierStyleSup">17</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0018"><span class="elsevierStyleSup">18</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0019"><span class="elsevierStyleSup">19</span></a> Previous work based on both graph theory applied to EEG parameters<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">20</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0021"><span class="elsevierStyleSup">21</span></a> and functional magnetic resonance imaging &#40;fMRI&#41;<a class="elsevierStyleCrossRef" href="#bib0011"><span class="elsevierStyleSup">11</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0022"><span class="elsevierStyleSup">22</span></a> identify these types of networks as determinants in cognitive functioning&#44; because a change in their pattern is observed between the resting state and during the performance of cognitive tasks in both schizophrenic patients and healthy individuals&#46; Some results point to dysfunction of these networks in schizophrenia&#44;<a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0023"><span class="elsevierStyleSup">23</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0024"><span class="elsevierStyleSup">24</span></a> however in others no correlation is demonstrated between the clinical severity of psychosis and the disorganization of these networks&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">25</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0026"><span class="elsevierStyleSup">26</span></a></p><p id="para0009" class="elsevierStylePara elsevierViewall">The study of brain connectivity in schizophrenia and its relationship with cognitive performance has a long tradition in developed countries&#59; however&#44; in the Andean region &#40;Ecuador&#44; Peru&#44; Bolivia and Colombia&#41; no research of this type has been conducted to date in schizophrenia&#44; so it is necessary to analyze the possible role of functional network organization in these populations and whether there is any particularity that could be linked to genetics or other environmental and cultural conditions&#46;</p></span><span id="sec0002" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0008">Material and methods</span><span id="sec0003" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0009">Subjets</span><p id="para0010" class="elsevierStylePara elsevierViewall">Twenty-four patients diagnosed with schizophrenia &#40;17 men&#41; and thirty-two healthy controls &#40;22 men&#41; were included&#46; Written informed consent was obtained from all participants after full printed information&#46; The ethical committees of the Universidad San Francisco de Quito approved the study&#46;</p><p id="para0011" class="elsevierStylePara elsevierViewall">Patients were diagnosed by the psychiatrists in charge of their treatment according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders&#44; 5th edition&#44; based on complete interviews and all available evidence&#46; Healthy controls were recruited through contacts of university research staff&#46; Sociodemographic and clinical characteristics are presented in <a class="elsevierStyleCrossRef" href="#tbl0001">Table 1</a>&#46;</p><elsevierMultimedia ident="tbl0001"></elsevierMultimedia><p id="para0012" class="elsevierStylePara elsevierViewall">Current treatment dose was converted to mg&#47;d in chlorpromazine equivalents&#46;</p><p id="para0017" class="elsevierStylePara elsevierViewall">Exclusion criteria for patients and controls included history of neurological disease &#40;including head trauma with loss of consciousness&#41;&#44; past or present substance dependence &#40;except nicotine and caffeine&#41;&#44; not having completed elementary school&#46; In addition&#44; controls with any current psychiatric diagnosis or treatment were excluded&#46;</p><p id="para0018" class="elsevierStylePara elsevierViewall">All patients with schizophrenia were receiving stable doses of atypical antipsychotics&#46;</p></span><span id="sec0004" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0010">Cognitive assessment</span><p id="para0019" class="elsevierStylePara elsevierViewall">The following tests was used in the cognitive assessment process&#58;</p><p id="para0020" class="elsevierStylePara elsevierViewall">Brief Assessment in Cognition in Schizophrenia &#40;BACS&#41;<a class="elsevierStyleCrossRef" href="#bib0027"><span class="elsevierStyleSup">27</span></a> using the Spanish adaptation of the battery<span class="elsevierStyleInf">&#46;</span><a class="elsevierStyleCrossRef" href="#bib0028"><span class="elsevierStyleSup">28</span></a></p></span><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0011">EEG recording</span><span id="sec0006" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0012">EEG data acquisition and preprocessing</span><p id="para0021" class="elsevierStylePara elsevierViewall">EEG recordings were obtained using Brain Recorder&#174; software &#40;Brain Products Gmbh&#59; Munich&#44; Germany&#41;&#44; a 64-channel BrainAmp&#174; amplifier &#40;Brain Products Gmbh&#59; Munich&#44; Germany&#41;&#46;</p><p id="para0022" class="elsevierStylePara elsevierViewall">The International System 10-20 was used for electrode placement&#44; in addition to a ground electrode at the AFz site&#46; During recording&#44; the reference was taken over the Cz electrode&#44; allowing the final inclusion in the study of a total of 62 recording channels&#46; The impedance of the electrodes was kept below 5 K&#937; at all times&#46; The sampling rate was 250 Hz and the signal was recorded continuously&#46;</p><p id="para0023" class="elsevierStylePara elsevierViewall">Two electrodes were extracted to record the possible noise source derived from eye movements&#46;</p></span><span id="sec0007" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0013">Odd-ball paradigm</span><p id="para0024" class="elsevierStylePara elsevierViewall">Electrophysiological evaluation in the presence of cognitive stimulation was performed using an auditory odd-ball paradigm &#40;with unexpected target stimulus&#41;&#46; All participants listened to 600 binaural tones presented in random order with an inter-stimulus interval that fluctuated randomly between 1&#46;16 and 1&#46;44 s&#59; the paradigm extended for 13 min&#46; Three types of tones were presented&#58; target tone &#40;500 Hz tone&#59; probability&#59; 0&#46;2&#41;&#44; distractor tone &#40;1000 Hz tone&#59; probability&#59; 0&#46;2&#41;&#44; and standard tone &#40;2000 Hz tone&#59; probability&#59; 0&#46;6&#41;&#46;</p><p id="para0025" class="elsevierStylePara elsevierViewall">Subjects who responded correctly to at least 50&#37; of the stimuli included in the paradigm were included in the study&#46; Only the response to correctly attended target tones was used for subsequent EEG analyses&#46;</p></span></span><span id="sec0008" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0014">EEG processing</span><p id="para0026" class="elsevierStylePara elsevierViewall">The time-frequency representation of the EEG was calculated using the continuous wavelet transform &#40;CWT&#41;&#44; including frequencies from 1 to 70 Hz&#46; In this way&#44; two windows derived from the division of the 1s evoked responses &#91;&#40;-300-700&#41; ms&#93; were generated&#58; 1&#41; pre-stimulus &#91;&#40;-3000&#41; ms before the onset of the target stimulus&#93;&#59; and 2&#41; response &#91;&#40;300&#41; ms centered around the response peak&#93;&#46;</p><p id="para0027" class="elsevierStylePara elsevierViewall">In order to systematize artifact rejection&#44; a three-step approach developed by the group in previous studies<a class="elsevierStyleCrossRef" href="#bib0029"><span class="elsevierStyleSup">29</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">30</span></a> was used&#46;</p><p id="para0028" class="elsevierStylePara elsevierViewall">The parameters included in the analyses were the following&#59; 1&#41; path length&#44; 2&#41; clustering coefficient&#44; 3&#41; small world and 4&#41; connectivity strength and their respective modulations upon realization of the odd-ball paradigm&#46;</p><p id="para0029" class="elsevierStylePara elsevierViewall">For the construction of graphs derived from the EEG analysis&#44; the measurements recorded at the 62 electrodes used in the study were taken&#46; The activity of each electrode was interpreted as representing a node of the network&#44; while the links were calculated based on the phase-locking between each pair of electrodes&#46;<a class="elsevierStyleCrossRef" href="#bib0031"><span class="elsevierStyleSup">31</span></a> To estimate the signal synchrony between electrodes&#44; the phase-locking values &#40;PLV&#41; in successive trials were used<span class="elsevierStyleInf">&#46;</span><a class="elsevierStyleCrossRef" href="#bib0032"><span class="elsevierStyleSup">32</span></a> CWT was used in the PLV calculation<span class="elsevierStyleInf">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0033"><span class="elsevierStyleSup">33</span></a> using the analyses developed by the research group in previous studies&#44;<a class="elsevierStyleCrossRef" href="#bib0016"><span class="elsevierStyleSup">16</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0034"><span class="elsevierStyleSup">34</span></a> represented in the following formula&#58;<elsevierMultimedia ident="ueqn0001"></elsevierMultimedia>where N is the number of attempts&#44; &#8710;&#966;<span class="elsevierStyleInf">xy</span> is the phase difference between the x and y signals&#44; k is the time interval and s is the wavelet scaling factor&#46;</p><p id="para0030" class="elsevierStylePara elsevierViewall">The network segregation was analyzed using the CLC parameter&#46;<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">35</span></a> This analysis is expressed as follows&#58;<elsevierMultimedia ident="ueqn0002"></elsevierMultimedia>where wxy denotes the weight of the connection between electrodes i and j&#46; The task-associated CLC modulation was defined as the change in CLC values between the prestimulus and response windows&#46;</p><p id="para0031" class="elsevierStylePara elsevierViewall">For the analysis of network integration&#44; the PL parameter<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">35</span></a> was used&#46; The following equation was used for this purpose&#58;<elsevierMultimedia ident="ueqn0003"></elsevierMultimedia>where dij indicates the minimum distance between electrodes i and j&#46; The PL modulation associated with the task was defined as the change in PL values between the prestimulus and response windows&#46;</p><p id="para0032" class="elsevierStylePara elsevierViewall">The balance between segregation and integration was calculated using the SW parameter<span class="elsevierStyleInf">&#46;</span><a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">35</span></a> The SW modulation associated with the task was defined as the change in SW values between the pre-stimulus and response windows&#46;<elsevierMultimedia ident="ueqn0004"></elsevierMultimedia></p><p id="para0033" class="elsevierStylePara elsevierViewall">The CS was calculated using the following formula&#58;<elsevierMultimedia ident="ueqn0005"></elsevierMultimedia>where Wij refers to PLV between nodes i and j&#44; and N is the total number of nodes in the network&#46;<a class="elsevierStyleCrossRef" href="#bib0034"><span class="elsevierStyleSup">34</span></a> Task-associated CS modulation was defined as the change in CS values between the pre-stimulus and response windows&#46;<a class="elsevierStyleCrossRef" href="#bib0016"><span class="elsevierStyleSup">16</span></a></p><p id="para0034" class="elsevierStylePara elsevierViewall">The EEG recording and analysis equipment and procedures were identical to those used in&#44;<a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0036"><span class="elsevierStyleSup">36</span></a> in order to be able to compare the results in the corresponding samples&#46;</p></span><span id="sec0009" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0015">Statistical analyses</span><p id="para0035" class="elsevierStylePara elsevierViewall">Demographic&#44; cognitive&#44; clinical and neurophysiological data were compared between the groups into which the sample was divided using Kruskal-Wallis tests&#59; in cases where a significant group effect was identified&#44; the Mann-Whitney test was used to make comparisons between pairs of groups&#46; Analyses were also performed to assess the effects of drug treatment on altered connective parameters in patients using Spearman&#39;s Rho&#46;</p><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0016">Analysis of connective parameters</span><p id="para0036" class="elsevierStylePara elsevierViewall">The parameters&#59; Small World&#44; Path Length&#44; clustering coefficient&#44; connectivity Strength&#44; modulation in path length&#44; modulation in small world parameter&#44; modulation in clustering coefficient parameter and modulation in connectivity strength parameter were included in the analyses&#46; The Kruskal-Wallis test was used for overall sample comparison and the Mann-Withney test for pairwise comparison when a significant effect was detected for the group&#46;</p></span><span id="sec0011" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0017">Comparison of connective parameters between Ecuadorian and Spanish clinical population</span><p id="para0037" class="elsevierStylePara elsevierViewall">We analyzed whether the alterations in the functional connective network were similar between patients with schizophrenia in the Ecuadorian and Spanish samples&#46; For this purpose&#44; comparisons were made using U-Mann Whitney tests for the altered parameters&#46;</p></span><span id="sec0012" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0018">Relationship between connective disorders and cognitive performance</span><p id="para0038" class="elsevierStylePara elsevierViewall">Multiple stepwise linear regressions were performed using as dependent variables the scores obtained in the cognitive battery by all participants in the study sample and as independent variables the connective parameters that showed a significant alteration in the previous analyses were taken into account&#46; &#40;see <a class="elsevierStyleCrossRef" href="#fig0002">Figure 2</a>a&#41;&#46; These same analyses were performed in the Ecuadorian cohort &#40;see <a class="elsevierStyleCrossRef" href="#fig0002">Figure 2</a>b&#41;&#46;</p></span></span></span><span id="sec0013" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0019">Results</span><p id="para0039" class="elsevierStylePara elsevierViewall">The age and sex of the patients were balanced in both samples&#46; No significant differences were found in the sex distribution between the group of patients diagnosed with schizophrenia and the controls&#44; &#40;x<span class="elsevierStyleSup">2</span>&#61;4&#46;93&#44; df&#61;2&#44; p&#61;0&#46;09&#41; x<span class="elsevierStyleSup">2</span> and age &#40;K&#61;0&#46;831&#44; df&#61;2&#44; p&#61;0&#46;66&#41;&#46;</p><p id="para0040" class="elsevierStylePara elsevierViewall">Shapiro-Wilk test was performed to test the normality of the connective parameters found that the variables PL &#40;modulation&#41;&#44; &#40;W&#61;0&#46;96&#44; p&#61;0&#46;02&#41;&#44; SW &#40;pre-stimulus&#41;&#44; &#40;W&#61;0&#46;94&#44; p&#60;0&#46;001&#41;&#44; CLC &#40;pre-stimulus&#41; &#40;W&#61;0&#46; 88&#44; p&#60;0&#46;001&#41;&#44; PL &#40;pre-stimulus&#41; &#40;W&#61;0&#46;92&#44; p&#60;0&#46;001&#41;&#44; and CS &#40;pre-stimulus&#41;&#44; &#40;W&#61;0&#46;96&#44; p&#61;0&#46;02&#41; do not exhibit normality so nonparametric tests were used for statistical analyses&#46;</p><p id="para0041" class="elsevierStylePara elsevierViewall">No significant correlations were found between antipsychotic treatment dose and the studied parameters&#58; CLC &#40;pre-stimulus&#41;&#44; &#40;rho&#61; -0&#46;247&#44; S&#61;1921&#44; p&#61;0&#46;279&#41;&#59; PL &#40;pre-stimulus&#41;&#44; &#40;rho&#61;-0&#46;179&#44; S&#61;1816&#46;4&#44; p&#61;0&#46;284&#41;&#59; CS &#40;pre-stimulus&#41;&#44; &#40;rho&#61;- 0&#46;157&#44; S&#61;1782&#46;3&#44; p&#61;0&#46;496&#41;&#59; SW &#40;pre-stimulus&#41;&#44; &#40;rho&#61;0&#46;151&#44; S&#61;1307&#46;8&#44; p&#61;0&#46;514&#41;&#44; CLC modulation &#40;rho&#61; 0&#46;08&#44; S&#61;1410&#46;3&#44; p&#61;0&#46;717&#41;&#59; PL modulation &#40;rho&#61;-0&#46;019&#44; S&#61;1569&#46;2&#44; p&#61;0&#46;935&#41;&#59; CS modulation &#40;rho&#61;- 0&#46;086&#44; S&#61;1408&#46;3&#44; p&#61;0&#46;713&#41;&#59; SW modulation &#40;rho&#61;0&#46;039&#44; S&#61;1480&#46;7&#44;p&#61;0&#46;868&#41;</p><span id="sec0014" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0020">Brain connectivity patterns</span><p id="para0042" class="elsevierStylePara elsevierViewall">For the calculation of connectivity metrics the mean number of segments used in patients was 80&#46;79 &#40;sd 20&#46;96&#41; and 88&#46;88&#40;sd 13&#46;78&#41; in controls&#46;</p><p id="para0043" class="elsevierStylePara elsevierViewall">Significantly higher values were found in schizophrenia patients than in controls in the parameters Clustering coefficient &#40;U&#61;239&#44; p&#60;0&#46;008&#41;&#59; Path Length &#40;U&#61;223&#44; p&#60;0&#46;003&#59; Connectivity Strength &#40;U&#61;270&#44; p&#60;0&#46;029&#41;&#59; connectivity strength modulation &#40;U&#61;280&#44; p&#60;0&#46;043 and lower values of Small World &#40;U&#61;226&#44; p&#60;0&#46;004&#41;&#46; See <a class="elsevierStyleCrossRef" href="#tbl0002">Table 2</a>&#46;</p><elsevierMultimedia ident="tbl0002"></elsevierMultimedia></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0021">Comparison of connective parameters between the Spanish and Ecuadorian clinical population</span><p id="para0047" class="elsevierStylePara elsevierViewall">The experimental protocol was applied identically in the Spanish and Ecuadorian samples&#46;</p><p id="para0048" class="elsevierStylePara elsevierViewall">No differences were found in sex &#40;x<span class="elsevierStyleSup">2</span>&#61;0&#46;034&#44;df&#61;1&#44;p&#61;0&#46;853&#41; or age &#40;K&#61;0&#46;28&#44; df&#61;1&#44;p&#61;0&#46;6&#41; between the Spanish and Ecuadorian populations&#46; Ecuadorian patients showed higher values compared to Spanish patients in the Clustering Coefficient &#40;U&#61;134&#44; p&#61;0&#46;004&#41; and Path Length &#40;U&#61;138&#44; p&#61;0&#46;006&#41; parameters and lower values in the Small World parameter &#40;U&#61;142&#44; p&#61;0&#46;007&#41;&#46; These results are illustrated in <a class="elsevierStyleCrossRef" href="#fig0001">Figure 1</a>&#46;</p><elsevierMultimedia ident="fig0001"></elsevierMultimedia></span><span id="sec0016" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0022">Relationship between connective parameters and cognitive performance</span><p id="para0049" class="elsevierStylePara elsevierViewall">The basal CS parameter is a good predictor of performance inversely in the variables working memory &#40;R<span class="elsevierStyleSup">2</span>&#61;0&#46;07&#59;B&#61;-290&#59;T&#61;4&#46;971&#59;p&#61;0&#46;03&#41;and motor speed &#40;R<span class="elsevierStyleSup">2</span>&#61;0&#46;24&#59;B&#61;-272&#59;T&#61;9&#46;44&#59;p&#61;0&#46;03&#41;&#46; The SW parameter directly predicted performance in the domains processing speed &#40;R<span class="elsevierStyleSup">2</span>&#61;0&#46;13&#59;B&#61;377&#59;T&#61;8&#46;947&#59;p&#61;0&#46;004&#41; and Tower of London &#40;R<span class="elsevierStyleSup">2</span>&#61;0&#46;08&#59;B&#61;310&#59;T&#61;5&#46;746&#59;p&#61;0&#46;02&#41;&#46; The basal PL parameter inversely predicted performance in the motor speed variable &#40;R<span class="elsevierStyleSup">2</span>&#61;0&#46;24&#59;B&#61;-361&#59;T&#61;9&#46;44&#59;p&#61;0&#46;005&#41;&#46; Finally&#44; the resting state clustering coefficient inversely predicted performance in the verbal memory sub-category &#40;R<span class="elsevierStyleSup">2</span>&#61;0&#46;08&#59;B&#61;-315&#59;T&#61;5&#46;936&#59;p&#61;0&#46;02&#41;&#46; The model showed no predictive ability of any of the connective parameters on the verbal fluency sub-category of the BACS test&#46; See <a class="elsevierStyleCrossRef" href="#fig0002">Figure 2</a>a&#46;</p><elsevierMultimedia ident="fig0002"></elsevierMultimedia></span></span><span id="sec0017" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0023">Discussion</span><p id="para0050" class="elsevierStylePara elsevierViewall">Higher CS values were identified in patients diagnosed with schizophrenia compared to healthy controls as well as a significantly higher deficit in the modulation of this parameter&#46; In addition&#44; SW values &#40;in the pre-stimulated condition&#41; were lower in the schizophrenia group&#46; Patients also showed higher PL and CLC values in this condition than controls&#46; Finally&#44; the alteration of CS&#44; SW&#44; CLC and PL parameters was related to performance in neuropsychological tests&#46;</p><p id="para0051" class="elsevierStylePara elsevierViewall">The findings identified in our sample are in line with those reported in other populations such as Spain&#46; A study conducted in a sample with schizophrenia in Spain identified higher CS values at baseline and during an attentional task versus controls&#46;<a class="elsevierStyleCrossRef" href="#bib0016"><span class="elsevierStyleSup">16</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0037"><span class="elsevierStyleSup">37</span></a> For its part&#44; the lower SW index in Ecuadorian patients has been described in a Spanish sample&#46;<a class="elsevierStyleCrossRef" href="#bib0038"><span class="elsevierStyleSup">38</span></a> Finally&#44; in a Spanish sample it was observed that patients showed higher baseline recordings than controls in CLC and PL parameters&#46;<a class="elsevierStyleCrossRef" href="#bib0034"><span class="elsevierStyleSup">34</span></a></p><p id="para0052" class="elsevierStylePara elsevierViewall">However&#44; significant differences are observed in some of these parameters between both populations &#40;see <a class="elsevierStyleCrossRef" href="#fig0001">Figure 1</a>&#41;&#46; A possible explanation for the differences found may be determined by the heterogeneity inherent to the condition studied&#46; This heterogeneity may also manifest itself in measures of brain connectivity&#46;<a class="elsevierStyleCrossRef" href="#bib0039"><span class="elsevierStyleSup">39</span></a></p><p id="para0053" class="elsevierStylePara elsevierViewall">To our knowledge&#44; no previous research had performed a comparative analysis of the presence of these alterations in two populations with different genetic&#44; socioeconomic&#44; and cultural conditions&#46; One of the strengths of this study is that the results were compared with the results of investigations that applied the same methodology of data processing and analysis&#44; which guarantees the homogeneity of the protocols and allows reinforcing the starting hypothesis regarding the universality of the disease in terms of functional connective alterations&#46;</p><p id="para0054" class="elsevierStylePara elsevierViewall">The results obtained at baseline in the CS parameter by patients diagnosed with schizophrenia could be reflecting a connective condition contributing to the overload of the neural ensembles&#46; The presence of higher resting-state density values found in patients diagnosed with schizophrenia could hinder the modulatory capacity of neural ensembles in this group&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">40</span></a> This is consistent with reports of a GABAergic deficit identified in schizophrenia&#46;<a class="elsevierStyleCrossRef" href="#bib0041"><span class="elsevierStyleSup">41</span></a> Dysregulation in the excitatory&#47;inhibitory balance<a class="elsevierStyleCrossRef" href="#bib0042"><span class="elsevierStyleSup">42</span></a> could cause the basal hyper-synchronization present in some patients diagnosed with schizophrenia and be reflected through higher CS values&#46;</p><p id="para0055" class="elsevierStylePara elsevierViewall">An increased modulation of the CS parameter was also identified in the group of patients diagnosed with schizophrenia&#46; In the literature we can find several studies that using different imaging techniques in their analysis&#44;<a class="elsevierStyleCrossRef" href="#bib0043"><span class="elsevierStyleSup">43</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0044"><span class="elsevierStyleSup">44</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">45</span></a> have reported the presence of an increased activity of the default neural network in schizophrenia&#46; The activation of neural mechanisms not associated with the performance of a simple attentional task could be behind the inefficiency shown by some patients to perform such tasks&#46;</p><p id="para0056" class="elsevierStylePara elsevierViewall">Thus&#44; difficulties in modulation could mean that while in controls there is a decrease in global activation before a task &#40;which probably responds to the need to activate more networks involved in cognitive processing&#41;&#44; patients increase their activity even more&#44; thus producing a failure in specialization&#46;</p><p id="para0057" class="elsevierStylePara elsevierViewall">The presence of lower values in the SW parameter in basal state with respect to controls identified in the group of patients diagnosed with schizophrenia could be linked to worse processing reflected in cognitive tests&#46; Small-world organization has been shown to be fundamental in information transfer in terms of functional integration and segregation&#44;<a class="elsevierStyleCrossRef" href="#bib0046"><span class="elsevierStyleSup">46</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0008"><span class="elsevierStyleSup">8</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0047"><span class="elsevierStyleSup">47</span></a> efficient levels of information segregation and integration with low energy and wiring costs are linked to a number of benefits for connective functioning&#44; such as&#44; a high degree of short global communication with relatively few connections&#46;<a class="elsevierStyleCrossRef" href="#bib0048"><span class="elsevierStyleSup">48</span></a></p><p id="para0058" class="elsevierStylePara elsevierViewall">In the cognitive section&#44; our results indicate a predictive relationship linking a higher CS index to worse results in motor speed&#44; which is in line with previous studies suggesting that performance in this cognitive function would depend on the functional hyperactivation shown by patients&#39; networks&#46;<a class="elsevierStyleCrossRef" href="#bib0049"><span class="elsevierStyleSup">49</span></a> Motor speed was also inversely associated with the PL index&#46; This association could reflect the importance of network integration for the correct performance of cognitive tasks that require the activation of different processing levels&#46; From a theoretical point of view&#44; these signs could be a consequence of oscillatory alterations mediated by inhibitory dysregulations identified in the disease&#46;<a class="elsevierStyleCrossRef" href="#bib0042"><span class="elsevierStyleSup">42</span></a></p><p id="para0059" class="elsevierStylePara elsevierViewall">On the other hand&#44; participants who performed worse in the processing speed domain presented lower resting state SW levels&#46; Slower processing speed could therefore be associated with a less globally integrated and less clustered resting functional organization&#46; This is consistent with evidence reported in preceding studies indicating a reduction in processing speed in patients diagnosed with schizophrenia&#46;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">50</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0051"><span class="elsevierStyleSup">51</span></a></p><p id="para0060" class="elsevierStylePara elsevierViewall">A relationship was also found between performance on the verbal memory task and the CLC index&#46; As the clustering values increased the worse the participants&#39; performance was this domain&#46; Previous studies have reported this same relationship<a class="elsevierStyleCrossRef" href="#bib0052"><span class="elsevierStyleSup">52</span></a> which could reflect the dependence of verbal memory on the level of functional segregation shown by the networks in the basal state&#46;</p><p id="para0061" class="elsevierStylePara elsevierViewall">It has been proposed that an excess of cortical activation may result in an overload of working memory processes beyond their capacity&#46;<a class="elsevierStyleCrossRef" href="#bib0053"><span class="elsevierStyleSup">53</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0054"><span class="elsevierStyleSup">54</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">55</span></a> Our results point in the same line&#44; higher indexes in the CLC parameter are related to worse performance in working memory&#46;</p><p id="para0062" class="elsevierStylePara elsevierViewall">Finally&#44; the magnitude of SW predicted better scores in executive function&#46; The relationship identified in the results between SW measures and this domain could be indicative of the dependence of executive function on the small-world configuration of the networks in the basal state&#46;</p><p id="para0063" class="elsevierStylePara elsevierViewall">Our study has limitations&#44; most of them related to the small sample size&#46; This limitation may have had a special incidence in the comparisons made between the groups of patients diagnosed with schizophrenia from Ecuador and Spain &#40;n&#61;24&#41; and &#40;n&#61;22&#41; respectively&#44; and may have been one of the circumstances that contributed to the differences found between the connective parameters of both populations&#46; On the other hand&#44; significant differences were found in the years of schooling of patients and controls&#44; so we cannot rule out that this factor may explain&#44; at least in part&#44; the differences in the connective patterns of both groups&#46; Nevertheless&#44; the overall pattern of the data in the Ecuadorian population was consistent with that identified in previous studies of similar populations in other countries&#46; The inherent heterogeneity of the syndrome&#44; which has been discussed previously&#44; could also have contributed to the presence of these differences&#46; Moreover&#44; these results should be replicated in samples without neuroleptic treatment&#46;</p></span><span id="sec0018" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0024">Conclusions</span><p id="para0064" class="elsevierStylePara elsevierViewall">Ecuadorian patients diagnosed with schizophrenia present connective alterations similar to those found in other samples with different genetic&#44; environmental and cultural conditions&#46; Moreover&#44; these alterations were related to worse performance in several cognitive domains&#46;</p></span><span id="sec0019" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0025">Ethical considerations</span><p id="para0065" class="elsevierStylePara elsevierViewall">The study protocol was accepted by the ethical committees of the Universidad San Francisco de Quito &#40;2017-042E&#41;&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0026">Funding</span><p id="para0066" class="elsevierStylePara elsevierViewall">This study is part of a research programme investigating funded by the <span class="elsevierStyleGrantSponsor" id="gs0001">Universidad de Las Am&#233;ricas</span>&#46;</p></span></span>"
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              "titulo" => "Cognitive assessment"
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              "titulo" => "EEG recording"
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                  "titulo" => "Odd-ball paradigm"
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                  "titulo" => "Analysis of connective parameters"
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                1 => array:2 [
                  "identificador" => "sec0011"
                  "titulo" => "Comparison of connective parameters between Ecuadorian and Spanish clinical population"
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                2 => array:2 [
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              "titulo" => "Brain connectivity patterns"
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            1 => array:2 [
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              "titulo" => "Comparison of connective parameters between the Spanish and Ecuadorian clinical population"
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            2 => array:2 [
              "identificador" => "sec0016"
              "titulo" => "Relationship between connective parameters and cognitive performance"
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          "titulo" => "Acknowledgements"
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    "pdfFichero" => "main.pdf"
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    "fechaRecibido" => "2021-02-26"
    "fechaAceptado" => "2021-06-30"
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          "clase" => "keyword"
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          "palabras" => array:4 [
            0 => "Functional network"
            1 => "Graph-theory"
            2 => "Schizophrenia"
            3 => "Electroencephalography"
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    "resumen" => array:1 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abss0001" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0002">Background and objectives</span><p id="spara007" class="elsevierStyleSimplePara elsevierViewall">Higher mental functions depend on global functional coordination of the brain&#46; Our aim was to study the baseline condition and modulation of functional networks in a previously unevaluated clinical population&#44; compare the results with a population from another country&#44; and analyze their relationship with cognitive functioning&#46;</p></span> <span id="abss0002" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0003">Methods</span><p id="spara008" class="elsevierStyleSimplePara elsevierViewall">We evaluated the functioning of brain networks by EEG in 24 patients with schizophrenia and 32 healthy Ecuadorian controls&#46; EEG recordings were made at rest and while performing a P300 task&#46; Small world &#40;SW&#41;&#44; Path Length &#40;PL&#41;&#44; clustering coefficient &#40;CLC&#41; and connective strength &#40;CS&#41; values were calculated in both conditions&#46; The values obtained were compared between groups&#44; with the results of Spanish patients&#44; and the relationship between the connective parameters and the cognitive performance of the participants was analyzed&#46;</p></span> <span id="abss0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0004">Results</span><p id="spara010" class="elsevierStyleSimplePara elsevierViewall">Higher PL&#44; CLC and CS values were identified in patients diagnosed with schizophrenia compared to controls &#40;in basal condition&#41; and lower SW values in this same condition&#46; Ecuadorian patients obtained higher values than Spanish patients in the PL and CLC parameters and lower values for the SW parameter&#44; despite these differences&#44; the pattern of alteration in both samples followed the same trend&#46; Finally&#44; the alteration of CS&#44; SW&#44; CLC and PL parameters at baseline was related to cognitive performance&#46;</p></span> <span id="abss0006" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0005">Conclusion</span><p id="spara011" class="elsevierStyleSimplePara elsevierViewall">The connective alterations identified in Ecuadorian schizophrenic patients are consistent with those found in another sample with different genetic&#44; environmental and cultural conditions&#46; In addition&#44; these alterations were associated with worse performance in different cognitive domains&#46;</p></span>"
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          "en" => "<p id="spara002" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleBold">a</span>&#46; Scatter plot depicting the association between connective parameters and cognitive scores in patients with schizophrenia and controls in the study sample&#46; <span class="elsevierStyleBold">b&#46;</span> Scatter plot representing the association between connective parameters and cognitive scores in patients with schizophrenia and controls in the Ecuador cohort&#46;</p>"
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                  \t\t\t\t</td><a name="en0036"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">12&#46;75&#40;3&#46;19&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0037"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">16&#46;55&#40;3&#46;44&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0038"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-3&#46;79<a class="elsevierStyleCrossRef" href="#tb1fn3"><span class="elsevierStyleSup">&#8270;&#8270;&#8270;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0039"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">13&#46;85&#40;4&#46;04&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0040"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">12&#46;75&#40;3&#46;19&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0041"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;91&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0042"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">16&#40;2&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0043"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">16&#46;53&#40;3&#46;73&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0044"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-0&#46;37&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0045"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Positive PANSS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0046"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">15&#46;64&#40;6&#46;32&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0047"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">NA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0048"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;11&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0049"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">12&#46;44&#40;4&#46;59&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0050"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">15&#46;63&#40;6&#46;32&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0051"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-1&#46;72&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0052"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">NA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0053"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">NA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0054"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0055"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Negative PANSS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0056"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">17&#46;95&#40;7&#46;01&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0057"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">NA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0058"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;27&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0059"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">18&#46;56&#40;7&#46;99&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0060"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">17&#46;95&#40;7&#46;01&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0061"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;25&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0062"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">NA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0063"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">NA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0064"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0065"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Verbal memory&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0066"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">32&#46;83&#40;7&#46;39&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0067"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">45&#40;11&#46;19&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0068"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-4&#46;62<a class="elsevierStyleCrossRef" href="#tb1fn3"><span class="elsevierStyleSup">&#8270;&#8270;&#8270;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0069"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">36&#46;67&#40;9&#46;21&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0070"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">32&#46;83&#40;7&#46;39&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0071"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;43&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0072"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">49&#46;21&#40;9&#46;38&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0073"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">41&#46;56&#40;10&#46;86&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0074"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2&#46;46<a class="elsevierStyleCrossRef" href="#tb1fn1">&#42;</a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0075"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Working memory&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0076"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">14&#46;57&#40;4&#46;23&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0077"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">19&#46;63&#40;3&#46;52&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0078"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-4&#46;79<a class="elsevierStyleCrossRef" href="#tb1fn3"><span class="elsevierStyleSup">&#8270;&#8270;&#8270;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0079"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">15&#46;87&#40;4&#46;09&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0080"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">14&#46;66&#40;4&#46;22&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0081"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;87&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0082"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">21&#46;78&#40;3&#46;52&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0083"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">17&#46;81&#40;3&#46;05&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0084"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">3&#46;77<a class="elsevierStyleCrossRef" href="#tb1fn3"><span class="elsevierStyleSup">&#8270;&#8270;&#8270;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0085"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Motor speed&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0086"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">35&#46;04&#40;13&#46;26&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0087"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">65&#46;31&#40;11&#46;72&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0088"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-9&#46;04<a class="elsevierStyleCrossRef" href="#tb1fn3"><span class="elsevierStyleSup">&#8270;&#8270;&#8270;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0089"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">44&#46;2&#40;14&#46;75&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0090"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">35&#46;04&#40;13&#46;26&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0091"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0092"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">66&#46;46&#40;14&#46;28&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0093"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">61&#46;5&#40;7&#46;65&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0094"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;284&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0095"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Verbal Fluency&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0096"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">16&#46;96&#40;5&#46;47&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0097"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">21&#46;40&#40;9&#46;59&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0098"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-2&#46;03<a class="elsevierStyleCrossRef" href="#tb1fn1">&#42;</a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0099"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">18&#46;61&#40;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0100"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">16&#46;95&#40;5&#46;47&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0101"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;76&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0102"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">23&#46;93&#40;11&#46;45&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0103"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">22&#46;71&#40;3&#46;77&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0104"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;41&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0105"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Processing speed&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0106"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">46&#46;58&#40;14&#46;46&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0107"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">67&#46;25&#40;10&#46;58&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0108"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">-6&#46;18<a class="elsevierStyleCrossRef" href="#tb1fn3"><span class="elsevierStyleSup">&#8270;&#8270;&#8270;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0109"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">65&#46;67&#40;13&#46;51&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0110"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">46&#46;58&#40;14&#46;46&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0111"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">4&#46;11<a class="elsevierStyleCrossRef" href="#tb1fn3"><span class="elsevierStyleSup">&#8270;&#8270;&#8270;</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0112"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">68&#46;64&#40;14&#46;12&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0113"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">68&#46;62&#40;9&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0114"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0115"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Tower of London&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0116"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">11&#46;38&#40;4&#46;55&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0117"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">16&#46;94&#40;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0118"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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        "texto" => "<p id="para0068" class="elsevierStylePara elsevierViewall">We would like to acknowledge the contributions of the Departments of Psychiatry and Psychology of the Sagrado Coraz&#243;n Psychiatric Institute and the San Juan de Dios Hospital in Quito for their help in developing the search and data collection strategy&#46;</p>"
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Article information

ISSN: 02136163
Original language: English

DOI:10.1016/j.ejpsy.2021.06.004

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Year/Month	Html	Pdf	Total

2024 November	6	1	7
2024 October	34	8	42
2024 September	48	15	63
2024 August	34	19	53
2024 July	34	7	41
2024 June	38	12	50
2024 May	42	32	74
2024 April	46	18	64
2024 March	73	7	80
2024 February	59	21	80
2024 January	48	16	64
2023 December	34	11	45
2023 November	68	17	85
2023 October	61	19	80
2023 September	52	9	61
2023 August	40	14	54
2023 July	23	9	32
2023 June	58	20	78
2023 May	99	27	126
2023 April	32	8	40
2023 March	19	8	27
2023 February	19	16	35
2023 January	21	27	48
2022 December	93	57	150
2022 November	101	64	165
2022 October	17	24	41
2022 September	16	16	32
2022 August	24	14	38
2022 July	17	11	28
2022 June	18	5	23
2022 May	31	14	45
2022 April	21	17	38
2022 March	28	25	53
2022 February	38	16	54
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2021 December	26	19	45
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2021 September	1	0	1

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