Schizophrenia | EPFL Graph Search

Schizophrenia is a mental disorder characterized by continuous or relapsing episodes of psychosis. Major symptoms include hallucinations (typically hearing voices), delusions, and disorganized thinking. Other symptoms include social withdrawal, and flat affect. Symptoms typically develop gradually, begin during young adulthood, and in many cases never become resolved. There is no objective diagnostic test; diagnosis is based on observed behavior, a psychiatric history that includes the person's reported experiences, and reports of others familiar with the person. To be diagnosed with schizophrenia, the described symptoms need to have been present for at least six months (according to the DSM-5) or one month (according to the ICD-11). Many people with schizophrenia have other mental disorders, especially substance use disorders, depressive disorders, anx

The EEG multiverse of schizophrenia

Ophélie Gladys Favrod, Patricia Figueiredo, Dario Alejandro Gordillo Lopez, Michael Herzog, Wei-Hsiang Lin, Janir Nuno Ramos Antunes Da Cruz, Maya Roinishvili

Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which eventually may explain the clinical outcome. One tacit assumption of these "deep rooting" approaches is that paradigms tap into common and representative aspects of the disorder. Here, we analyzed the resting-state electroencephalogram (EEG) of 121 schizophrenia patients and 75 controls. Using multiple signal processing methods, we extracted 194 EEG features. Sixty-nine out of the 194 EEG features showed a significant difference between patients and controls, indicating that these features detect an important aspect of schizophrenia. Surprisingly, the correlations between these features were very low. We discuss several explanations to our results and propose that complementing "deep" with "shallow" rooting approaches might help in understanding the underlying mechanisms of the disorder.

OXFORD UNIV PRESS INC2022

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

Erick Jorge Canales Rodriguez, Wenhao Jiang

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.

2020

EEG signatures of schizophrenia: visual backward masking and microstates

Janir Nuno Ramos Antunes Da Cruz

Schizophrenia is a complex and devastating mental disorder that influences how one behaves, feels, and thinks. It affects a little less than 1 % of the world population and it is understood to be partly genetically mediated. Several genetic risk factors of schizophrenia have been identified. However, efforts to functionally characterize the genetic risk of schizophrenia have not been successful. To link the genetic risk to schizophrenia phenotype, schizophrenia research has turned to quantifiable stable trait markers with a clear genetic connection, so-called endo-phenotypes. Endophenotypes research in schizophrenia has heavily relied on the use of electroencephalogram (EEG) to identify endophenotypes and to better understand the neural mechanisms of neuropsychological candidate endophenotypes for schizophrenia. Here, I used high-density EEG to study two promising candidate endophenotypes of schizophrenia: visual backward masking (VBM) and EEG microstates. To cope with the heterogeneity of schizophrenia, I analyzed data from more than 300 participants (including schizophrenia patients, their unaffected siblings, healthy students scoring either high or low in schizotypal traits, patients with a first episode of psychosis, and healthy controls) performing a masking task or at rest. To deal with undesired signals that may affect the measurements and change the EEG signals of interest in a time-efficient manner and to minimize experts' subjectivity, I first proposed and validated an automatic pre-processing pipeline. This pipeline was subsequently used to pre-process all the analyzed EEG data. In a VBM study, performance of siblings was in between the ones of patients and controls (endophenotype concept). In patients, masking deficits were associated with decreased EEG amplitudes. In siblings, contrary to expectation, EEG amplitudes were even higher than in controls, which I interpret as a compensation signal. Based on EEG source localization, I propose that siblings over-activate a network of brain areas, including the right insula as a key player, to compensate for the deficits. In an EEG microstates study, schizophrenia patients, their siblings, and patients with a first episode of psychosis showed abnormal microstate dynamics compared to controls (endophenotype concept). Interestingly, siblings showed atypical dynamics of a particular microstate compared to patients, which I interpret also as a compensation signal. A similar result was also found in high schizotypes. My findings suggest that, even if there are genetic risks for developing schizophrenia, the brain is somehow capable of compensating for them. A better understanding of these compensation mechanisms and their commonalities might help to explain why some siblings develop schizophrenia, while others do not, which might open new avenues for characterization of schizophrenia and possible treatments of the disorder.

EPFL2019

EEG signatures of schizophrenia: visual backward masking and microstates

Janir Nuno Ramos Antunes Da Cruz

EPFL2019