Our group has begun development of MEG data analysis methods to better describe neural mechanisms involved in the deficits in recognition of emotional facial expressions in schizophrenia. Our model is derived from the existing literature, and from pilot work done in our lab using MEG neuroimaging techniques in both patients with schizophrenia and normal controls performing facial affect recognition tasks. We hypothesize (1) between-group differences in MEG-assessed brain activation in specific brain regions and (2) a critical role for those deficits in the cognitive and social dysfunction seen in schizophrenia. Our lab has successfully localized three distinct dipolar sources during facial affect processing. We propose to further investigate MEG-assessed face emotion information processing abnormalities and their relation to behavioral measures. We will test for differences between groups on MEG measures in a brain region associated with general visual processing general (V1, calcarine cortex), a brain region specialized for processing faces (fusiform gyrus), a brain region implicated in assessment of emotional content (amygdala), and a brain region that attends to salient environmental features (anterior cingulate gyrus). MEG analysis will be done concurrently using Neuromag software for comparison with the existing literature and with our Multi Start Spatio-Temporal dipole modeling to develop new techniques. We will also generate a method for assessing the connectivity between these brain areas using a mutual information exchange calculation. MEG analyses will be related to (1) an affect processing battery, (2) standard symptom scales, and (3) measures of quality of life for subjects with schizophrenia.
| Huang, Ming-Xiong; Dale, Anders M; Song, Tao et al. (2006) Vector-based spatial-temporal minimum L1-norm solution for MEG. Neuroimage 31:1025-37 |
