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Front Neurosci. 2014 Oct 31;8:339. doi: 10.3389/fnins.2014.00339. eCollection 2014.

Cortical connective field estimates from resting state fMRI activity.

Author information

1
Laboratory of Experimental Ophthalmology, University Medical Center Groningen, University of Groningen Groningen, Netherlands ; Laboratorio de Circuitos Neuronales, Centro Interdisciplinario de Neurociencia, Pontificia Universidad Católica de Chile Santiago, Chile ; NeuroImaging Center, University Medical Center Groningen, University of Groningen Netherlands.
2
Experimental Psychology, Helmholtz Institute, Utrecht University Utrecht, Netherlands.
3
Laboratory of Experimental Ophthalmology, University Medical Center Groningen, University of Groningen Groningen, Netherlands.
4
Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Netherlands.
5
NeuroImaging Center, University Medical Center Groningen, University of Groningen Netherlands.
6
Laboratory of Experimental Ophthalmology, University Medical Center Groningen, University of Groningen Groningen, Netherlands ; NeuroImaging Center, University Medical Center Groningen, University of Groningen Netherlands.

Abstract

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 (pRF) 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.

KEYWORDS:

RS-fMRI; connective field modeling; connectivity mapping; population receptive fields; visuotopic maps

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