Publications by authors named "Anton Albajes-Eizagirre"

20 Publications

  • Page 1 of 1

Structural Brain Correlates in Major Depression, Anxiety Disorders and Post-traumatic Stress Disorder: A Voxel-Based Morphometry Meta-analysis.

Neurosci Biobehav Rev 2021 Jul 10. Epub 2021 Jul 10.

Mental Health Department, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí (I3PT), Spain; Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Spain; Carlos III Health Institute, Mental Health Networking Biomedical Research Centre (CIBERSAM), Spain. Electronic address:

The high comorbidity of Major Depressive Disorder (MDD), Anxiety Disorders (ANX), and Posttraumatic Stress Disorder (PTSD) has hindered the study of their structural neural correlates. The authors analyzed specific and common grey matter volume (GMV) characteristics by comparing them with healthy controls (HC). The meta-analysis of voxel-based morphometry (VBM) studies showed unique GMV diminutions for each disorder (p < 0.05, corrected) and less robust smaller GMV across diagnostics (p < 0.01, uncorrected). Pairwise comparison between the disorders showed GMV differences in MDD versus ANX and in ANX versus PTSD. These results endorse the hypothesis that unique clinical features characterizing MDD, ANX, and PTSD are also reflected by disorder specific GMV correlates.
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http://dx.doi.org/10.1016/j.neubiorev.2021.07.002DOI Listing
July 2021

Cortical gray matter reduction precedes transition to psychosis in individuals at clinical high-risk for psychosis: A voxel-based meta-analysis.

Schizophr Res 2021 06 22;232:98-106. Epub 2021 May 22.

Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neuroscience, Hospital Clínic, Villarroel 170, 08036 Barcelona, Spain; Fundació Clínic per a la Recerca Biomèdica (FCRB), Esther Koplowitz Centre, Rosselló 153, 08036 Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Rosselló 149, 08036 Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain. Electronic address:

Gray matter and cortical thickness reductions have been documented in individuals at clinical high-risk for psychosis and may be more pronounced in those who transition to psychosis. However, these findings rely on small samples and are inconsistent across studies. In this review and meta-analysis we aimed to investigate neuroanatomical correlates of clinical high-risk for psychosis and potential predictors of transition, using a novel meta-analytic method (Seed-based d Mapping with Permutation of Subject Images) and cortical mask, combining data from surface-based and voxel-based morphometry studies. Individuals at clinical high-risk for psychosis who later transitioned to psychosis were compared to those who did not and to controls, and included three statistical maps. Overall, individuals at clinical high-risk for psychosis did not differ from controls, however, within the clinical high-risk for psychosis group, transition to psychosis was associated with less cortical gray matter in the right temporal lobe (Hedges' g = -0.377), anterior cingulate and paracingulate (Hedges' g = -0.391). These findings have the potential to help refine prognostic and etiopathological research in early psychosis.
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http://dx.doi.org/10.1016/j.schres.2021.05.008DOI Listing
June 2021

Corrigendum to 'Voxel-based meta-analysis via permutation of subject images (PSI): Theory and implementation for SDM' [Neuroimage 186 (2019) 174-184/YNIMG_15396].

Neuroimage 2021 May 17;231:117859. Epub 2021 Feb 17.

FIDMAG Germanes Hospitalàries, Sant Boi de Llobregat, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. Electronic address:

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http://dx.doi.org/10.1016/j.neuroimage.2021.117859DOI Listing
May 2021

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 17. Epub 2021 Feb 17.

Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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http://dx.doi.org/10.1002/hbm.25364DOI Listing
February 2021

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 11. Epub 2021 Feb 11.

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
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http://dx.doi.org/10.1002/hbm.25320DOI Listing
February 2021

Can we increase the subjective well-being of the general population? An umbrella review of the evidence.

Rev Psiquiatr Salud Ment (Engl Ed) 2021 Jan-Mar;14(1):50-64. Epub 2020 Nov 5.

Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain; Early Psychosis: Interventions and Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden. Electronic address:

Introduction: Subjective well-being (SWB) refers to being satisfied with one's life, having positive affect and having little negative affect. We may understand it as a subjective definition of good life, or in colloquial terms "happiness", and it has been associated with several important benefits such as lower mortality. In the last decades, several randomized controlled trials (RCT) have investigated the efficacy of several interventions in increasing SWB in the general population but results from different disciplines have not been integrated.

Methods: We conducted an umbrella review of systematic reviews and meta-analyses of RCT that assess the efficacy of any kind of interventions in increasing SWB in the general population, including both positive psychology interventions (PPI) and other interventions. We (re)calculated the meta-analytic statistics needed to objectively assess the quality of the evidence of the efficacy of each type of intervention in improving each component of SWB according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

Results: There was moderate-quality evidence that PPI might induce small decreases of negative affect, and low-quality evidence that they might induce moderate increases of positive affect. We found similar results for those PPI specifically consisting in conducting acts of kindness (especially spending money on or giving items to others), for which there was low-quality evidence that they might induces small increases of life satisfaction, but not for PPI specifically consisting in practicing gratitude. Quality of the evidence of the efficacy for the other interventions included in the umbrella review (yoga, resilience training, physical activity, leisure, control enhancement, psychoeducation, and miscellaneous) was very low.

Conclusion: There is some evidence that PPI, and specially conducting acts of kindness such as spending money on others, may increase the SWB of the general population. The quality of the evidence of the efficacy for other interventions (e.g., yoga, physical activity, or leisure) is still very low. Registration number: PROSPERO CRD42020111681.
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http://dx.doi.org/10.1016/j.rpsm.2020.08.002DOI Listing
November 2020

Greater male than female variability in regional brain structure across the lifespan.

Hum Brain Mapp 2020 Oct 12. Epub 2020 Oct 12.

FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
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http://dx.doi.org/10.1002/hbm.25204DOI Listing
October 2020

Precuneus and insular hypoactivation during cognitive processing in first-episode psychosis: Systematic review and meta-analysis of fMRI studies.

Rev Psiquiatr Salud Ment (Engl Ed) 2020 Sep 25. Epub 2020 Sep 25.

Research Institute of the Hospital Clínic Universitari of Valencia (INCLIVA), Valencia, Spain; Center for Networking Biomedical Research in Mental Health (CIBERSAM), Spain; Department of Psychiatric, University of Valencia, School of Medicine, Valencia, Spain.

Introduction: The neural correlates of the cognitive dysfunction in first-episode psychosis (FEP) are still unclear. The present review and meta-analysis provide an update of the location of the abnormalities in the fMRI-measured brain response to cognitive processes in individuals with FEP.

Methods: Systematic review and voxel-based meta-analysis of cross-sectional fMRI studies comparing neural responses to cognitive tasks between individuals with FEP and healthy controls (HC) according to PRISMA guidelines.

Results: Twenty-six studies were included, comprising 598 individuals with FEP and 567 HC. Individual studies reported statistically significant hypoactivation in the dorsolateral prefrontal cortex (6 studies), frontal lobe (8 studies), cingulate (6 studies) and insula (5 studies). The meta-analysis showed statistically significant hypoactivation in the left anterior insula, precuneus and bilateral striatum.

Conclusions: While the studies tend to highlight frontal hypoactivation during cognitive tasks in FEP, our meta-analytic results show that the left precuneus and insula primarily display aberrant activation in FEP that may be associated with salience attribution to external stimuli and related to deficits in perception and regulation.
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http://dx.doi.org/10.1016/j.rpsm.2020.08.001DOI Listing
September 2020

Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA.

Neuroimage 2020 09 26;218:116956. Epub 2020 May 26.

CIBERSAM, Madrid, Spain; FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).
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http://dx.doi.org/10.1016/j.neuroimage.2020.116956DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7524039PMC
September 2020

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI).

J Vis Exp 2019 11 27(153). Epub 2019 Nov 27.

Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS); Mental Health Research Networking Center (CIBERSAM); Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London; Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet;

Most methods for conducting meta-analysis of voxel-based neuroimaging studies do not assess whether effects are not null, but whether there is a convergence of peaks of statistical significance, and reduce the assessment of the evidence to a binary classification exclusively based on p-values (i.e., voxels can only be "statistically significant" or "non-statistically significant"). Here, we detail how to conduct a meta-analysis using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI), a novel method that uses a standard permutation test to assess whether effects are not null. We also show how to grade the strength of the evidence according to a set of criteria that considers a range of statistical significance levels (from more liberal to more conservative), the amount of data or the detection of potential biases (e.g., small-study effect and excess of significance). To exemplify the procedure, we detail the conduction of a meta-analysis of voxel-based morphometry studies in obsessive-compulsive disorder, and we provide all the data already extracted from the manuscripts to allow the reader to replicate the meta-analysis easily. SDM-PSI can also be used for meta-analyses of functional magnetic resonance imaging, diffusion tensor imaging, position emission tomography and surface-based morphometry studies.
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http://dx.doi.org/10.3791/59841DOI Listing
November 2019

An overlapping pattern of cerebral cortical thinning is associated with both positive symptoms and aggression in schizophrenia via the ENIGMA consortium.

Psychol Med 2020 09 16;50(12):2034-2045. Epub 2019 Oct 16.

Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital Aachen, RWTH Aachen University, Aachen, Germany.

Background: Positive symptoms are a useful predictor of aggression in schizophrenia. Although a similar pattern of abnormal brain structures related to both positive symptoms and aggression has been reported, this observation has not yet been confirmed in a single sample.

Method: To study the association between positive symptoms and aggression in schizophrenia on a neurobiological level, a prospective meta-analytic approach was employed to analyze harmonized structural neuroimaging data from 10 research centers worldwide. We analyzed brain MRI scans from 902 individuals with a primary diagnosis of schizophrenia and 952 healthy controls.

Results: The result identified a widespread cortical thickness reduction in schizophrenia compared to their controls. Two separate meta-regression analyses revealed that a common pattern of reduced cortical gray matter thickness within the left lateral temporal lobe and right midcingulate cortex was significantly associated with both positive symptoms and aggression.

Conclusion: These findings suggested that positive symptoms such as formal thought disorder and auditory misperception, combined with cognitive impairments reflecting difficulties in deploying an adaptive control toward perceived threats, could escalate the likelihood of aggression in schizophrenia.
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http://dx.doi.org/10.1017/S0033291719002149DOI Listing
September 2020

Neural signatures of conditioning, extinction learning, and extinction recall in posttraumatic stress disorder: a meta-analysis of functional magnetic resonance imaging studies.

Psychol Med 2020 07 1;50(9):1442-1451. Epub 2019 Jul 1.

FIDMAG Germanes Hospitalàries, CIBERSAM, Sant Boi de Llobregat, Barcelona, Spain.

Background: Establishing neurobiological markers of posttraumatic stress disorder (PTSD) is essential to aid in diagnosis and treatment development. Fear processing deficits are central to PTSD, and their neural signatures may be used as such markers.

Methods: Here, we conducted a meta-analysis of seven Pavlovian fear conditioning fMRI studies comparing 156 patients with PTSD and 148 trauma-exposed healthy controls (TEHC) using seed-based d-mapping, to contrast neural correlates of experimental phases, namely conditioning, extinction learning, and extinction recall.

Results: Patients with PTSD, as compared to TEHCs, exhibited increased activation in the anterior hippocampus (extending to the amygdala) and medial prefrontal cortex during conditioning; in the anterior hippocampus-amygdala regions during extinction learning; and in the anterior hippocampus-amygdala and medial prefrontal areas during extinction recall. Yet, patients with PTSD have shown an overall decreased activation in the thalamus during all phases in this meta-analysis.

Conclusion: Findings from this metanalysis suggest that PTSD is characterized by increased activation in areas related to salience and threat, and lower activation in the thalamus, a key relay hub between subcortical areas. If replicated, these fear network alterations may serve as objective diagnostic markers for PTSD, and potential targets for novel treatment development, including pharmacological and brain stimulation interventions. Future longitudinal studies are needed to examine whether these observed network alteration in PTSD are the cause or the consequence of PTSD.
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http://dx.doi.org/10.1017/S0033291719001387DOI Listing
July 2020

Shared and differential default-mode related patterns of activity in an autobiographical, a self-referential and an attentional task.

PLoS One 2019 4;14(1):e0209376. Epub 2019 Jan 4.

FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.

The default-mode network (DMN) comprises a set of brain regions that show deactivations during performance of attentionally demanding tasks, but also activation during certain processes including recall of autobiographical memories and processing information about oneself, among others. However, the DMN is not activated in a homogeneous manner during performance of such tasks, so it is not clear to what extent its activation patterns correspond to deactivation patterns seen during attention-demanding tasks. In this fMRI study we compared patterns of activation in response to an autobiographical memory task to those observed in a self/other-reflection task, and compared both to deactivations observed during the n-back working memory task. Autobiographical recall and self-reflection activated several common DMN areas, which were also deactivated below baseline levels by the n-back task. Activation in the medial temporal lobe was seen during autobiographical recall but not the self/other task, and right angular gyrus activity was specifically linked to other-reflection. ROI analysis showed that most, but not all DMN regions were activated above baseline levels during the autobiographical memory and self-reflection tasks. Our results provide evidence for the usefulness of the autobiographical memory task to study DMN activity and support the notion of interacting subsystems within this network.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0209376PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6319771PMC
September 2019

Meta-analysis of non-statistically significant unreported effects.

Stat Methods Med Res 2019 12 4;28(12):3741-3754. Epub 2018 Dec 4.

FIDMAG Germanes Hospitalàries, Barcelona, Spain.

Published studies in Medicine (and virtually any other discipline) sometimes report that a difference or correlation did not reach statistical significance but do not report its effect size or any statistic from which the latter may be derived. Unfortunately, meta-analysts should not exclude these studies because their exclusion would bias the meta-analytic outcome, but also they cannot be included as null effect sizes because this strategy is also associated to bias. To overcome this problem, we have developed MetaNSUE, a novel method based on multiple imputations of the censored information. We also provide an R package and an easy-to-use Graphical User Interface for non-R meta-analysts.
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http://dx.doi.org/10.1177/0962280218811349DOI Listing
December 2019

Voxel-based meta-analysis via permutation of subject images (PSI): Theory and implementation for SDM.

Neuroimage 2019 02 30;186:174-184. Epub 2018 Oct 30.

FIDMAG Germanes Hospitalàries, Sant Boi de Llobregat, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. Electronic address:

Coordinate-based meta-analyses (CBMA) are very useful for summarizing the large number of voxel-based neuroimaging studies of normal brain functions and brain abnormalities in neuropsychiatric disorders. However, current CBMA methods do not conduct common voxelwise tests, but rather a test of convergence, which relies on some spatial assumptions that data may seldom meet, and has lower statistical power when there are multiple effects. Here we present a new algorithm that can use standard voxelwise tests and, importantly, conducts a standard permutation of subject images (PSI). Its main steps are: a) multiple imputation of study images; b) imputation of subject images; and c) subject-based permutation test to control the familywise error rate (FWER). The PSI algorithm is general and we believe that developers might implement it for several CBMA methods. We present here an implementation of PSI for seed-based d mapping (SDM) method, which additionally benefits from the use of effect sizes, random-effects models, Freedman-Lane-based permutations and threshold-free cluster enhancement (TFCE) statistics, among others. Finally, we also provide an empirical validation of the control of the FWER in SDM-PSI, which showed that it might be too conservative. We hope that the neuroimaging meta-analytic community will welcome this new algorithm and method.
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http://dx.doi.org/10.1016/j.neuroimage.2018.10.077DOI Listing
February 2019

Amygdala where art thou?

Neurosci Biobehav Rev 2019 07 7;102:430-431. Epub 2018 Jun 7.

Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Victoria, Australia. Electronic address:

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http://dx.doi.org/10.1016/j.neubiorev.2018.06.003DOI Listing
July 2019

What do results from coordinate-based meta-analyses tell us?

Neuroimage 2018 08 3;176:550-553. Epub 2018 May 3.

FIDMAG Germanes Hospitalàries, Sant Boi de Llobregat, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain; Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. Electronic address:

Coordinate-based meta-analyses (CBMA) methods, such as Activation Likelihood Estimation (ALE) and Seed-based d Mapping (SDM), have become an invaluable tool for summarizing the findings of voxel-based neuroimaging studies. However, the progressive sophistication of these methods may have concealed two particularities of their statistical tests. Common univariate voxelwise tests (such as the t/z-tests used in SPM and FSL) detect voxels that activate, or voxels that show differences between groups. Conversely, the tests conducted in CBMA test for "spatial convergence" of findings, i.e., they detect regions where studies report "more peaks than in most regions", regions that activate "more than most regions do", or regions that show "larger differences between groups than most regions do". The first particularity is that these tests rely on two spatial assumptions (voxels are independent and have the same probability to have a "false" peak), whose violation may make their results either conservative or liberal, though fortunately current versions of ALE, SDM and some other methods consider these assumptions. The second particularity is that the use of these tests involves an important paradox: the statistical power to detect a given effect is higher if there are no other effects in the brain, whereas lower in presence of multiple effects.
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http://dx.doi.org/10.1016/j.neuroimage.2018.04.065DOI Listing
August 2018

Fear extinction in the human brain: A meta-analysis of fMRI studies in healthy participants.

Neurosci Biobehav Rev 2018 05 10;88:16-25. Epub 2018 Mar 10.

Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Level 3, 161 Barry Street, Melbourne, Victoria, Australia. Electronic address:

The study of fear extinction represents an important example of translational neuroscience in psychiatry and promises to improve the understanding and treatment of anxiety and fear-related disorders. We present the results of a set of meta-analyses of human fear extinction studies in healthy participants, conducted with functional magnetic resonance imaging (fMRI) and reporting whole-brain results. Meta-analyses of fear extinction learning primarily implicate consistent activation of brain regions linked to threat appraisal and experience, including the dorsal anterior cingulate and anterior insular cortices. An overlapping anatomical result was obtained from the meta-analysis of extinction recall studies, except when studies directly compared an extinguished threat stimulus to an unextinguished threat stimulus (instead of a safety stimulus). In this latter instance, more consistent activation was observed in dorsolateral and ventromedial prefrontal cortex regions, together with other areas including the hippocampus. While our results partially support the notion of a shared neuroanatomy between human and rodent models of extinction processes, they also encourage an expanded account of the neural basis of human fear extinction.
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http://dx.doi.org/10.1016/j.neubiorev.2018.03.002DOI Listing
May 2018

Meta-Analysis of Functional Neuroimaging and Cognitive Control Studies in Schizophrenia: Preliminary Elucidation of a Core Dysfunctional Timing Network.

Front Psychol 2016 17;7:192. Epub 2016 Feb 17.

Department of Psychiatry and Clinical Psychology, Clínica Universidad de NavarraPamplona, Spain; Instituto de Investigación Sanitaria de NavarraNavarra, Spain.

Timing and other cognitive processes demanding cognitive control become interlinked when there is an increase in the level of difficulty or effort required. Both functions are interrelated and share neuroanatomical bases. A previous meta-analysis of neuroimaging studies found that people with schizophrenia had significantly lower activation, relative to normal controls, of most right hemisphere regions of the time circuit. This finding suggests that a pattern of disconnectivity of this circuit, particularly in the supplementary motor area, is a trait of this mental disease. We hypothesize that a dysfunctional temporal/cognitive control network underlies both cognitive and psychiatric symptoms of schizophrenia and that timing dysfunction is at the root of the cognitive deficits observed. The goal of our study was to look, in schizophrenia patients, for brain structures activated both by execution of cognitive tasks requiring increased effort and by performance of time perception tasks. We conducted a signed differential mapping (SDM) meta-analysis of functional neuroimaging studies in schizophrenia patients assessing the brain response to increasing levels of cognitive difficulty. Then, we performed a multimodal meta-analysis to identify common brain regions in the findings of that SDM meta-analysis and our previously-published activation likelihood estimate (ALE) meta-analysis of neuroimaging of time perception in schizophrenia patients. The current study supports the hypothesis that there exists an overlap between neural structures engaged by both timing tasks and non-temporal cognitive tasks of escalating difficulty in schizophrenia. The implication is that a deficit in timing can be considered as a trait marker of the schizophrenia cognitive profile.
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http://dx.doi.org/10.3389/fpsyg.2016.00192DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4756542PMC
February 2016

Electro-physiological data fusion for stress detection.

Stud Health Technol Inform 2012 ;181:228-32

Starlab Barcelona, Spain.

In this work we describe the performance evaluation of a system for stress detection. The analysed data is acquired by following an experimental protocol designed to induce cognitive stress to the subjects. The experimental set-up included the recording of electroencephalography (EEG) and facial (corrugator and zygomatic) electromyography (EMG). In a preliminary analysis we are able to correlate EEG features (alpha asymmetry and alpha/beta ratio using only 3 channels) with the stress level of the subjects statistically (by using averages over subjects) but also on a subject-to-subject basis by using computational intelligence techniques reaching classification rates up to 79% when classifying 3 minutes takes. On a second step, we apply fusion techniques to the overall multi-modal feature set fusing the formerly mentioned EEG features with EMG energy. We show that the results improve significantly providing a more robust stress index every second. Given the achieved performance the system described in this work can be successfully applied for stress therapy when combined with virtual reality.
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January 2013
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