Recent developments in multivariate pattern analysis for functional MRI

Multivariate pattern analysis (MVPA) is a recently-developed approach for functional magnetic resonance imaging (fMRI) data analyses. Compared with the traditional univariate methods, MVPA is more sensitive to subtle changes in multivariate patterns in fMRI data. In this review, we introduce several significant advances in MVPA applications and summarize various combinations of algorithms and parameters in different problem settings. The limitations of MVPA and some critical questions that need to be addressed in future research are also discussed

Altered Negative Unconscious Processing in Major Depressive Disorder: An Exploratory Neuropsychological Study

Objective: Major depressive disorder (MDD) has been characterized by abnormalities in emotional processing. However, what remains unclear is whether MDD also shows deficits in the unconscious processing of either positive or negative emotions. We conducted a psychological study in healthy and MDD subjects to investigate unconscious emotion processing and its valence-specific alterations in MDD patients

Abnormal baseline brain activity in bipolar depression: A resting state functional magnetic resonance imaging study

We examined resting state brain activity in the depressive phase of bipolar disorder (BD) by measuring the amplitude of low-frequency fluctuations (ALFF) in the functional magnetic resonance imaging (fMRI) signal. Unlike functional connectivity, the ALFF approach reflects local properties in specific regions and provides direct information about impaired foci. Groups of 26 patients with BD depression and 26 gender-, age-, and education-matched healthy subjects participated in fMRI scans. We examined group differences in ALFF findings as well as correlations between clinical measurements and ALFF in the regions showing significant group differences. Our results showed that patients with BD depression had significantly increased ALFF in the left insula, the right caudate nucleus, the temporal gyrus, the bilateral inferior frontal gyrus, and the posterior lobe of the cerebellum. They also had decreased ALFF in the left postcentral gyrus, the left parahippocampal gyrus, and the cerebellum. Moderate negative correlations were found between the Hamilton Depression Rating Scale score and ALFF in the left insular cortex in the patient group. These results support a model of BD that involves dysfunction in the prefrontal-limbic networks and associated striatal systems. We also demonstrated the feasibility of ALFF as a technique to investigate persistent cerebral dysfunction in BD. (C) 2012 Elsevier Ireland Ltd. All rights reserved