Journal
FRONTIERS IN NEUROSCIENCE
Volume 8, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fnins.2014.00339
Keywords
RS-fMRI; population receptive fields; connective field modeling; connectivity mapping; visuotopic maps
Categories
Funding
- (Chilean) National Commission for Scientific and Technological Research (BECAS CHILE)
- (Chilean) National Commission for Scientific and Technological Research (millennium center for neuroscience CENEM) [NC10 001 F]
- Netherlands Organization for Scientific Research (NWO Brain and Cognition grant) [433-09-233]
- ERC [StG 2012-312787_DRASTIC]
Ask authors/readers for more resources
One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (PR F) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 -> V2 and V1 -> V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that-despite some variability in CF estimates between RS scans-neural properties such as CF maps and CF size can be derived from resting state data.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available