S J Iwabuchi1, L Palaniyappan2. 1. Translational Neuroimaging for Mental Health,Division of Psychiatry and Applied Psychology,University of Nottingham,Nottingham,UK. 2. Departments of Psychiatry & Medical Biophysics,University of Western Ontario,London,Ontario,Canada.
Abstract
BACKGROUND: Sensory-processing deficits appear crucial to the clinical expression of symptoms of schizophrenia. The visual cortex displays both dysconnectivity and aberrant spontaneous activity in patients with persistent symptoms and cognitive deficits. In this paper, we examine visual cortex in the context of the remerging notion of thalamic dysfunction in schizophrenia. We examined specific regional and longer-range abnormalities in sensory and thalamic circuits in schizophrenia, and whether these patterns are strong enough to discriminate symptomatic patients from controls. METHOD: Using publicly available resting fMRI data of 71 controls and 62 schizophrenia patients, we derived conjunction maps of regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) to inform further seed-based Granger causality analysis (GCA) to study effective connectivity patterns. ReHo, fALFF and GCA maps were entered into a multiple kernel learning classifier, to determine whether patterns of local and effective connectivity can differentiate controls from patients. RESULTS: Visual cortex shows both ReHo and fALFF reductions in patients. Visuothalamic effective connectivity in patients was significantly reduced. Local connectivity (ReHo) patterns discriminated patients from controls with the highest level of accuracy of 80.32%. CONCLUSIONS: Both the inflow and outflow of Granger causal information between visual cortex and thalamus is affected in schizophrenia; this occurs in conjunction with highly discriminatory but localized dysconnectivity and reduced neural activity within the visual cortex. This may explain the visual-processing deficits that are present despite symptomatic remission in schizophrenia.
BACKGROUND: Sensory-processing deficits appear crucial to the clinical expression of symptoms of schizophrenia. The visual cortex displays both dysconnectivity and aberrant spontaneous activity in patients with persistent symptoms and cognitive deficits. In this paper, we examine visual cortex in the context of the remerging notion of thalamic dysfunction in schizophrenia. We examined specific regional and longer-range abnormalities in sensory and thalamic circuits in schizophrenia, and whether these patterns are strong enough to discriminate symptomatic patients from controls. METHOD: Using publicly available resting fMRI data of 71 controls and 62 schizophreniapatients, we derived conjunction maps of regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) to inform further seed-based Granger causality analysis (GCA) to study effective connectivity patterns. ReHo, fALFF and GCA maps were entered into a multiple kernel learning classifier, to determine whether patterns of local and effective connectivity can differentiate controls from patients. RESULTS: Visual cortex shows both ReHo and fALFF reductions in patients. Visuothalamic effective connectivity in patients was significantly reduced. Local connectivity (ReHo) patterns discriminated patients from controls with the highest level of accuracy of 80.32%. CONCLUSIONS: Both the inflow and outflow of Granger causal information between visual cortex and thalamus is affected in schizophrenia; this occurs in conjunction with highly discriminatory but localized dysconnectivity and reduced neural activity within the visual cortex. This may explain the visual-processing deficits that are present despite symptomatic remission in schizophrenia.
Entities:
Keywords:
Effective connectivity; fractional amplitutude of low frequency fluctuations; machine learning; regional homogeneity; schizophrenia; visuothalamic.
Authors: Avyarthana Dey; Kara Dempster; Michael MacKinley; Peter Jeon; Tushar Das; Ali Khan; Joe Gati; Lena Palaniyappan Journal: NPJ Schizophr Date: 2021-01-26
Authors: Joel Weijia Lai; Candice Ke En Ang; U Rajendra Acharya; Kang Hao Cheong Journal: Int J Environ Res Public Health Date: 2021-06-05 Impact factor: 3.390