Abstract
Intrinsic functional brain networks (INs) are regions showing temporal coherence with one another. These INs are present in the context of a task (as opposed to an undirected task such as rest), albeit modulated to a degree both spatially and temporally. Prominent networks include the default mode, attentional fronto-parietal, executive control, bilateral temporal lobe, and motor networks. The characterization of INs has recently gained considerable momentum, however; most previous studies evaluate only a small subset of the INs (e.g., default mode). In this paper we use independent component analysis to study INs decomposed from functional magnetic resonance imaging data collected in a large group of schizophrenia patients, healthy controls, and individuals with bipolar disorder, while performing an auditory oddball task. Schizophrenia and bipolar disorder share significant overlap in clinical symptoms, brain characteristics, and risk genes which motivates our goal of identifying whether functional imaging data can differentiate the two disorders. We tested for group differences in properties of all identified INs including spatial maps, spectra, and functional network connectivity. A small set of default mode, temporal lobe, and frontal networks with default mode regions appearing to play a key role in all comparisons. Bipolar subjects showed more prominent changes in ventromedial and prefrontal default mode regions whereas schizophrenia patients showed changes in posterior default mode regions. Anti-correlations between left parietal areas and dorsolateral prefrontal cortical areas were different in bipolar and schizophrenia patients and amplitude was significantly different from healthy controls in both patient groups. Patients exhibited similar frequency behavior across multiple networks with decreased low frequency power. In summary, a comprehensive analysis of INs reveals a key role for the default mode in both schizophrenia and bipolar disorder.
Highlights
Schizophrenia (SZ) is a psychotic disorder characterized by altered perception, cognition, thought processes, and behaviors whereas bipolar (BP) illness is a mood disorder involving prolonged states of depression and mania (Goodwin and Jamison, 2007)
Following application of group independent component analysis (ICA) to functional magnetic resonance imaging (fMRI) data from all subjects, we identify all plausible Intrinsic functional brain networks (INs) and use a comprehensive approach to test for group differences in all identified INs
In the following we summarize each set of results, starting with the spatial maps (SMs)
Summary
Schizophrenia (SZ) is a psychotic disorder characterized by altered perception, cognition, thought processes, and behaviors whereas bipolar (BP) illness is a mood disorder involving prolonged states of depression and mania (Goodwin and Jamison, 2007). Two of the more widely used methods include seed-based approaches (Greicius et al, 2004) and investigations based on independent component analysis (ICA; Calhoun et al, 2004, 2009a). These approaches both capitalize on underlying temporal coherence in the functional magnetic resonance imaging (fMRI) timecourses (TCs) which appears to reflect functionally relevant activity and is present both at rest and during a task (Biswal et al, 1995; Calhoun et al, 2008a). Numerous INs have been identified consistently by many groups, such as the default mode network, the attentional fronto-parietal networks, www.frontiersin.org
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