Neural correlates of probabilistic category learning in patients with schizophrenia.
Functional neuroimaging studies of probabilistic category learning in healthy adults report activation of cortical-striatal circuitry. Based on previous findings of normal learning rate concurrent with an overall performance deficit in patients with schizophrenia, we hypothesized that relative to healthy adults, patients with schizophrenia would display preserved caudate nucleus and abnormal prefrontal cortex activation during probabilistic category learning. Forty patients with schizophrenia receiving antipsychotic medication and 25 healthy participants were assessed on interleaved blocks of probabilistic category learning and control tasks while undergoing blood oxygenation level-dependent functional magnetic resonance imaging. In addition to the whole sample of patients with schizophrenia and healthy adults, a subset of patients and healthy adults matched for good learning was also compared. In the whole sample analysis, patients with schizophrenia displayed impaired performance in conjunction with normal learning rate relative to healthy adults. The matched comparison of patients and healthy adults classified as good learners revealed greater caudate and dorsolateral prefrontal cortex activity in the healthy adults and greater activation in a more rostral region of the dorsolateral prefrontal, cingulate, parahippocampal and parietal cortex in patients. These results demonstrate that successful probabilistic category learning can occur in the absence of normal frontal-striatal function. Based on analyses of the patients and healthy adults matched on learning and performance, a minority of patients with schizophrenia achieve successful probabilistic category learning and performance levels through differential activation of a circumscribed neural network which suggests a compensatory mechanism in patients showing successful learning.
Weickert
Thomas W
TW
Genes, Cognition and Psychosis Program, Clinical Brain Disorders Branch, National Institute of Mental Health-National Institutes of Health, Bethesda, Maryland 20892, USA. t.weickert@unsw.edu.au
Goldberg
Terry E
TE
Callicott
Joseph H
JH
Chen
Qiang
Q
Apud
Jose A
JA
Das
Sumitra
S
Zoltick
Brad J
BJ
Egan
Michael F
MF
Meeter
Martijn
M
Myers
Catherine
C
Gluck
Mark A
MA
Weinberger
Daniel R
DR
Mattay
Venkata S
VS
D000328:Adult; D000704:Analysis of Variance; D001921:Brain / Q000098:blood supply / Q000473:pathology*; D001931:Brain Mapping; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D007858:Learning / Q000502:physiology*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D009483:Neuropsychological Tests; D010100:Oxygen / Q000097:blood; D010775:Photic Stimulation; D011337:Probability Learning; D011597:Psychomotor Performance; D011930:Reaction Time / Q000502:physiology; D012559:Schizophrenia / Q000473:pathology* / Q000503:physiopathology*; D012565:Schizophrenic Psychology; D055815:Young Adult
D010100:Oxygen