Topic: Cortical regions

To uncover the neural mechanisms of stimulus perception, experimenters commonly use tasks in which subjects are repeatedly presented with a weak stimulus and instructed to report, via movement, if they perceived the stimulus. The difference in neural activity between reported stimulus (hit) and unreported stimulus (miss) trials is then seen as potentially perception-related. However, recent studies found that activity related to the report spreads throughout the brain, calling into question to what extent such tasks may be conflating activity that is perception-related with activity that is re

Understanding how tasks are processed across the entire brain is a central yet complex question in neuroscience. Recently, the release of brainwide electrophysiological recordings in a standardized behavior task offers an unprecedented opportunity to approach this question. In this paper, we characterize the signal activity of all the cortical regions systematically, and correlate the resulting functional properties with their corresponding anatomical positions. Taking advantage of the proposed brainwide reduced-rank regression encoding model that is unified and well-performing, we measured tw

Normal brain function results from directed causal interactions between brain regions. However, the large-scale spatial and temporal structure of these interactions remains unclear. Lagged correlations between the activity of different brain regions may reflect their directed causal interactions. Thus, we combined magnetoencephalography (MEG) and machine learning approaches to characterize and disentangle the structure of lagged correlations in the human brain. We computed lagged correlations between all pairs of cortical regions and frequencies of neural activity. We employed curvature-regul