2009
DOI: 10.1002/hbm.20749
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Increased inferior frontal activation during word generation: A marker of genetic risk for schizophrenia but not bipolar disorder?

Abstract: During verbal-fluency tasks, impairments in performance and functional abnormalities in the inferior frontal cortex have been observed in both schizophrenia patients and their unaffected relatives. We sought to examine whether such functional abnormalities are a specific marker of genetic vulnerability to schizophrenia. We studied a sample of 132 subjects, comprising 39 patients with schizophrenia, 10 unaffected monozygotic (MZ) cotwins of schizophrenia probands, 28 patients with bipolar disorder, 7 unaffected… Show more

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Cited by 37 publications
(41 citation statements)
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References 80 publications
(105 reference statements)
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“…Distinguishing people with schizophrenia from those with BD and healthy control subjects has been achieved with a sensitivity and specificity of over 90% based on functional abnormalities in prefrontal and temporal cortices and within default neural networks. [49][50][51] Neuroimaging-based prediction has also shown promising results in classifying subjects with obsessive-compulsive disorder, 52 autism spectrum disorders, 53 BD, 46,54 and substance abuse. 55 Most of these studies have found abnormalities that were regionally distributed but of relatively small magnitudes, and therefore with much overlap between patients and control subjects for any given region, which machine learning approaches were able to integrate leading to accurate classification.…”
Section: Figure 2 Training and Testing Of Classification Modelsmentioning
confidence: 99%
“…Distinguishing people with schizophrenia from those with BD and healthy control subjects has been achieved with a sensitivity and specificity of over 90% based on functional abnormalities in prefrontal and temporal cortices and within default neural networks. [49][50][51] Neuroimaging-based prediction has also shown promising results in classifying subjects with obsessive-compulsive disorder, 52 autism spectrum disorders, 53 BD, 46,54 and substance abuse. 55 Most of these studies have found abnormalities that were regionally distributed but of relatively small magnitudes, and therefore with much overlap between patients and control subjects for any given region, which machine learning approaches were able to integrate leading to accurate classification.…”
Section: Figure 2 Training and Testing Of Classification Modelsmentioning
confidence: 99%
“…However, another verbal fluency study reported there were no significant differences between the HR and control groups, suggesting that hyperactivity during cognitive functioning is not a marker of genetic risk for bipolar disorder. 57 …”
Section: Functional Mrimentioning
confidence: 99%
“…Our findings can be interpreted in a similar fashion. 57 Abnormalities in prefrontal regions can be associated with suppression of task-induced negative emotion, leading to abnormal activation in regions associated with emotional arousal (e.g., insula), and further interfere with cognition in the HR group. 58 However, the neurochemical basis of the functional abnormalities in HR individuals is unclear.…”
Section: Functional Alterations and Genetic Risk For Bipolar Disordermentioning
confidence: 99%
“…This study also shows that striatal subdivision is negatively related to verbal fluency performance, but this is not the case for the limbic subdivision. Verbal fluency depends on prefrontal function [48]. The associative striatum regulates information flow to and from the prefrontal cortex [49,50].…”
Section: Discussionmentioning
confidence: 99%