Work

Aberrant processing of deviant stimuli in schizophrenia revealed by fusion of fMRI and EEG data

Year: 2010

Type: article

Abstract: BACKGROUND: Aberrant electrophysiological and hemodynamic processing of auditory oddball stimuli is among the most robustly documented findings in patients with schizophrenia. However, no study to date has directly examined linked patterns of electrical and hemodynamic differences in patients and controls. METHODS: In a recent paper we demonstrated a data-driven approach, joint independent component analysis (jICA) to fuse together functional magnetic resonance imaging (fMRI) and event-related potential (ERP) data and elucidated the chronometry of auditory oddball target detection in healthy control subjects. In this paper we extend our fusion method to identify specific differences in the neuronal chronometry of target detection for chronic schizophrenia patients compared to healthy controls. RESULTS: We found one linked source, consistent with the N2 response, known to be related to cognitive processing of deviant stimuli, spatially localized to bilateral fronto-temporal regions. This source showed significant between-group differences both in amplitude response and in the fMRI/ERP distribution pattern. These findings are consistent with previous work showing N2 amplitude and latency abnormalities in schizophrenia, and provide new information about the linkage between the two. CONCLUSIONS: In summary, we use a novel approach to isolate and identify a linked fMRI/ERP component which shows marked differences in chronic schizophrenia patients. We also demonstrate that jointly using both fMRI and ERP measures provides a fully picture of the underlying hemodynamic and electrical changes which are present in patients. Our approach also has broad applicability to other diseases such as autism, Alzheimer's disease, or bipolar disorder.

Source: Acta Neuropsychiatrica

DOI: 10.1111/j.1601-5215.2010.00467.x

Authors: Vince D. Calhoun, Lei Wu, Kent A. Kiehl, Tom Eichele, Godfrey D. Pearlson

Institutions: Mind Research Network, University of New Mexico, Yale University, University of Bergen

Language: English

Topic: Schizophrenia research and treatment

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute of Mental Health, National Institute of Biomedical Imaging and Bioengineering