Multimodal neuroimaging as a window into the pathological physiology of schizophrenia: Current trends and issues

Isobe, Masanori; Miyata, Jun; Hazama, Masatoshi; Fukuyama, Hidenao; Murai, Toshiya; Takahashi, Hidehiko

doi:10.1016/j.neures.2015.07.009

Cited by 28 publications

(16 citation statements)

References 63 publications

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“…Multimodal MRI can reveal insightful information about key clinical aspects of schizophrenia(69,70). As the most widely studied psychosis, schizophrenia has served as the test bed for almost all above mentioned fusion approaches(71).…”

Section: Review Of Fusion Studies Focused On Psychopathologymentioning

confidence: 99%

Multimodal Fusion of Brain Imaging Data: A Key to Finding the Missing Link(s) in Complex Mental Illness

Calhoun

Sui

2016

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

316

283

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It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

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Section: Review Of Fusion Studies Focused On Psychopathologymentioning

confidence: 99%

Multimodal Fusion of Brain Imaging Data: A Key to Finding the Missing Link(s) in Complex Mental Illness

Calhoun

Sui

2016

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

316

283

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“…The corpus callosum (CC), the largest commissural fiber bundle in the brain, connects the left and the right hemispheres and serves an essential role of relaying sensory, motor, and cognitive information between the homologous regions (Huang et al, 2005;Ribolsi, Daskalakis, Siracusano, & Koch, 2014). Many studies have investigated abnormalities of the CC in schizophrenia with an aim of studying the disconnection between the two hemispheres (Isobe et al, 2016;Ribolsi et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Microstructural abnormalities in callosal fibers and their relationship with cognitive function in schizophrenia: A tract‐specific analysis study

et al. 2019

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Introduction The corpus callosum serves the essential role of relaying cognitive information between the homologous regions in the left and the right hemispheres of the brain. Cognitive impairment is a core dysfunction of schizophrenia, but much of its pathophysiology is unknown. The aim of this study was to elucidate the association between microstructural abnormalities of the corpus callosum and cognitive dysfunction in schizophrenia. Methods We examined stepwise multiple regression analysis to investigate the relationship of the fractional anisotropy (FA) of callosal fibers in each segment with z ‐scores of each brief assessment of cognition in schizophrenia subtest and cognitive composite score in all subjects (19 patients with schizophrenia [SZ group] and 19 healthy controls [HC group]). Callosal fibers were separated into seven segments based on their cortical projection using tract‐specific analysis of diffusion tensor imaging. Results The FA of callosal fibers in the temporal segment was significantly associated with z ‐scores of token motor test, Tower of London test, and the composite score. In the SZ group, the FA of callosal fibers in the temporal segment was significantly associated with the z ‐score of the Tower of London test. In addition, the FA of callosal fibers in temporal segment showed significant negative association with the positive and negative syndrome scale negative score in the SZ group. Compared to the HC group, the FA in temporal segment was significantly decreased in the SZ group. Conclusion Our results suggest that microstructural abnormalities in the callosal white matter fibers connecting bilateral temporal lobe cortices contribute to poor executive function and severe negative symptom in patients with schizophrenia.

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“…Structural and functional magnetic resonance neuroimaging studies have shown that schizophrenia and schizoaffective disorder share cerebral gray and white matter reductions and altered activation patterns relative to control values (Madre et al, 2016). Regions most affected include several frontal, cingulate and temporal lobe structures implicated in the SBN (Isobe et al, 2016). However, it is not known whether SBN abnormalities occur preferentially or more severely in people with schizophrenia relative to schizoaffective disorder or whether they are common neurobiological features in patients with psychosis.…”

Section: Introductionmentioning

confidence: 99%

The continuing story of schizophrenia and schizoaffective disorder: One condition or two?

Hartman

Heinrichs

Mashhadi

2019

Schizophrenia Research: Cognition

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Although schizophrenia and schizoaffective disorder remain separable in diagnostic systems, the validity of the distinction is uncertain. This study asked whether schizophrenia and schizoaffective disorder are distinguishable on selected cognitive, social cognitive and structural social brain measures. Outpatients with a diagnosis of schizophrenia (n = 44) or schizoaffective disorder (n = 29) and non-psychiatric control participants (n = 62) were studied. Patients were assessed clinically (Positive and Negative Syndrome Scale) and all participants were administered a battery of cognitive (MATRICS Consensus Cognitive Battery; Wechsler Abbreviated Scale of Intelligence, Wide Range Achievement Reading) and social cognitive (Reading the Mind in the Eyes, Mayer-Salovey-Caruso Emotional Intelligence Test; MSCEIT) tasks. In addition, participants underwent structural magnetic resonance imaging (MRI) to yield cortical thickness data for 42 regions associated with the social brain network. Results showed no significant differences between patient groups on 17/18 cognitive/social cognitive and social brain cortical thickness measures. In contrast, schizophrenia and schizoaffective disorder patients differed from controls on 16/18 and 11/18 measures respectively. Schizoaffective disorder patients outperformed schizophrenia patients on an emotion regulation task (MSCEIT). Schizophrenia and schizoaffective disorder are largely indistinguishable on key cognitive, social cognitive and neural measures. The continuing separation of these syndromes in diagnostic systems and disease models requires is questionable and requires further attention.

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Multimodal neuroimaging as a window into the pathological physiology of schizophrenia: Current trends and issues

Cited by 28 publications

References 63 publications

Multimodal Fusion of Brain Imaging Data: A Key to Finding the Missing Link(s) in Complex Mental Illness

Multimodal Fusion of Brain Imaging Data: A Key to Finding the Missing Link(s) in Complex Mental Illness

Microstructural abnormalities in callosal fibers and their relationship with cognitive function in schizophrenia: A tract‐specific analysis study

The continuing story of schizophrenia and schizoaffective disorder: One condition or two?

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