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Individual-specific functional connectivity markers track dimensional and categorical features of psychotic illness
by
Brady, Roscoe O
, Chen Huafu
, Dost, Öngür
, Liu, Hesheng
, Schoeppe Franziska
, Li, Meiling
, Wang, Danhong
, Wang, Meiyun
, Baker, Justin T
, Ren Jianxun
in
Anatomy
/ Bipolar disorder
/ Brain architecture
/ Emotional behavior
/ Etiology
/ Medical imaging
/ Mental disorders
/ Neural networks
/ Neuroimaging
/ Patients
/ Psychosis
/ Schizoaffective disorder
/ Schizophrenia
/ Structure-function relationships
2020
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Individual-specific functional connectivity markers track dimensional and categorical features of psychotic illness
by
Brady, Roscoe O
, Chen Huafu
, Dost, Öngür
, Liu, Hesheng
, Schoeppe Franziska
, Li, Meiling
, Wang, Danhong
, Wang, Meiyun
, Baker, Justin T
, Ren Jianxun
in
Anatomy
/ Bipolar disorder
/ Brain architecture
/ Emotional behavior
/ Etiology
/ Medical imaging
/ Mental disorders
/ Neural networks
/ Neuroimaging
/ Patients
/ Psychosis
/ Schizoaffective disorder
/ Schizophrenia
/ Structure-function relationships
2020
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Individual-specific functional connectivity markers track dimensional and categorical features of psychotic illness
by
Brady, Roscoe O
, Chen Huafu
, Dost, Öngür
, Liu, Hesheng
, Schoeppe Franziska
, Li, Meiling
, Wang, Danhong
, Wang, Meiyun
, Baker, Justin T
, Ren Jianxun
in
Anatomy
/ Bipolar disorder
/ Brain architecture
/ Emotional behavior
/ Etiology
/ Medical imaging
/ Mental disorders
/ Neural networks
/ Neuroimaging
/ Patients
/ Psychosis
/ Schizoaffective disorder
/ Schizophrenia
/ Structure-function relationships
2020
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Individual-specific functional connectivity markers track dimensional and categorical features of psychotic illness
Journal Article
Individual-specific functional connectivity markers track dimensional and categorical features of psychotic illness
2020
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Overview
Neuroimaging studies of psychotic disorders have demonstrated abnormalities in structural and functional connectivity involving widespread brain networks. However, these group-level observations have failed to yield any biomarkers that can provide confirmatory evidence of a patient’s current symptoms, predict future symptoms, or predict a treatment response. Lack of precision in both neuroanatomical and clinical boundaries have likely contributed to the inability of even well-powered studies to resolve these key relationships. Here, we employed a novel approach to defining individual-specific functional connectivity in 158 patients diagnosed with schizophrenia (n = 49), schizoaffective disorder (n = 37), or bipolar disorder with psychosis (n = 72), and identified neuroimaging features that track psychotic symptoms in a dimension- or disorder-specific fashion. Using individually specified functional connectivity, we were able to estimate positive, negative, and manic symptoms that showed correlations ranging from r = 0.35 to r = 0.51 with the observed symptom scores. Comparing optimized estimation models among schizophrenia spectrum patients, positive and negative symptoms were associated with largely non-overlapping sets of cortical connections. Comparing between schizophrenia spectrum and bipolar disorder patients, the models for positive symptoms were largely non-overlapping between the two disorder classes. Finally, models derived using conventional region definition strategies performed at chance levels for most symptom domains. Individual-specific functional connectivity analyses revealed important new distinctions among cortical circuits responsible for the positive and negative symptoms, as well as key new information about how circuits underlying symptom expressions may vary depending on the underlying etiology and illness syndrome from which they manifest.
Publisher
Nature Publishing Group
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