Nina P. Azari

The Role of Diaschisis in Stroke Recovery

BACKGROUND AND PURPOSE Recovery from hemiparesis after stroke has been shown to involve reorganization in motor and premotor cortical areas. However, whether poststroke recovery also depends on changes in remote brain structures, ie, diaschisis, is as yet unresolved. To address this question, we studied regional cerebral blood flow in 7 patients (mean+/-SD age, 54+/-8 years) after their first hemiparetic stroke. METHODS We analyzed imaging data voxel by voxel using a principal component analysis by which coherent changes in functional networks could be disclosed. Performance was assessed by a motor score and by the finger movement rate during the regional cerebral blood flow measurements. RESULTS The patients had recovered (P<0. 001) from severe hemiparesis after on average 6 months and were able to perform sequential finger movements with the recovered hand. Regional cerebral blood flow at rest differentiated patients and controls (P<0.05) by a network that was affected by the stroke lesion. During blindfolded performance of sequential finger movements, patients were differentiated from controls (P<0.05) by a recovery-related network and a movement-control network. These networks were spatially incongruent, involving motor, sensory, and visual cortex of both cerebral hemispheres, the basal ganglia, thalamus, and cerebellum. The lesion-affected and recovery-related networks overlapped in the contralesional thalamus and extrastriate occipital cortex. CONCLUSIONS Motor recovery after hemiparetic brain infarction is subserved by brain structures in locations remote from the stroke lesion. The topographic overlap of the lesion-affected and recovery-related networks suggests that diaschisis may play a critical role in stroke recovery.

Neural correlates of religious experience.

The commonsense view of religious experience is that it is a preconceptual, immediate affective event. Work in philosophy and psychology, however, suggest that religious experience is an attributional cognitive phenomenon. Here the neural correlates of a religious experience are investigated using functional neuroimaging. During religious recitation, self‐identified religious subjects activated a frontal–parietal circuit, composed of the dorsolateral prefrontal, dorsomedial frontal and medial parietal cortex. Prior studies indicate that these areas play a profound role in sustaining reflexive evaluation of thought. Thus, religious experience may be a cognitive process which, nonetheless, feels immediate.

RESEARCH: "Religious Experience and Emotion: Evidence for Distinctive Cognitive Neural Patterns"

Categorical comparisons of neuroimaging data suggest that religious experience is cognitively mediated. Cognition involves coordinated integration of large-scale networks. The aim of this study was to distinguish neural networks mediating religious experience. A principal component analysis (PCA) was applied to cerebral blood flow data of a Christian religious experience and a happy emotion. Differences in variance patterns (PCs) were assessed. The religious experience and the emotion were distinguished by PC9, a neural network that evidenced two forms of expression: One involved prefrontal structures, which participate in social-relational cognition and which were shown previously to correlate with the religious state. Another involved cortical areas important for emotion-related language processing, reward, and action preparation. The results suggest that an essential dimension of religious experience involves social-relational cognition, mediated by a specific neocortical network.

Cerebral networks in sensorimotor disturbances

Increasing evidence suggests that the human brain employs multiple, interconnected brain areas for information processing and control of behavior, including the performance of laboratory tasks. Brain diseases are expected to affect these networks directly by interference and indirectly as a consequence of deficit compensation. Covariance analyses applied to functional brain imaging data open the opportunity to study neural networks and their disease-related changes in the human brain. Here, we review our analytic approach based on principal component analysis (PCA) to address such questions. We will discuss its methodological foundations and applications in patients with sensorimotor disorders. We will show that PCA in combination with, both, hypothesis-driven testing and correlation statistics provides a powerful tool for elucidating disease-related abnormalities and postlesional reorganization of neural networks in the human brain.