Literature DB >> 24879865

Contour extracting networks in early extrastriate cortex.

Serge O Dumoulin1, Robert F Hess2, Keith A May3, Ben M Harvey1, Bas Rokers4, Martijn Barendregt4.   

Abstract

Neurons in the visual cortex process a local region of visual space, but in order to adequately analyze natural images, neurons need to interact. The notion of an ‘‘association field’’ proposes that neurons interact to extract extended contours. Here, we identify the site and properties of contour integration mechanisms. We used functional magnetic resonance imaging (fMRI) and population receptive field (pRF) analyses. We devised pRF mapping stimuli consisting of contours. We isolated the contribution of contour integration mechanisms to the pRF by manipulating the contour content. This stimulus manipulation led to systematic changes in pRF size. Whereas a bank of Gabor filters quantitatively explains pRF size changes in V1, only V2/V3 pRF sizes match the predictions of the association field. pRF size changes in later visual field maps, hV4, LO-1, and LO-2 do not follow either prediction and are probably driven by distinct classical receptive field properties or other extraclassical integration mechanisms. These pRF changes do not follow conventional fMRI signal strength measures. Therefore, analyses of pRF changes provide a novel computational neuroimaging approach to investigating neural interactions. We interpreted these results as evidence for neural interactions along cooriented, cocircular receptive fields in the early extrastriate visual cortex (V2/V3), consistent with the notion of a contour association field.
© 2014 ARVO.

Entities:  

Keywords:  Gabor filter; association field; functional magnetic resonance imaging; population receptive fields; visual cortex

Mesh:

Year:  2014        PMID: 24879865     DOI: 10.1167/14.5.18

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  5 in total

1.  Evaluating population receptive field estimation frameworks in terms of robustness and reproducibility.

Authors:  Mario Senden; Joel Reithler; Sven Gijsen; Rainer Goebel
Journal:  PLoS One       Date:  2014-12-02       Impact factor: 3.240

2.  Comparing different stimulus configurations for population receptive field mapping in human fMRI.

Authors:  Ivan Alvarez; Benjamin de Haas; Chris A Clark; Geraint Rees; D Samuel Schwarzkopf
Journal:  Front Hum Neurosci       Date:  2015-02-20       Impact factor: 3.169

3.  Population receptive field estimates for motion-defined stimuli.

Authors:  Anna E Hughes; John A Greenwood; Nonie J Finlayson; D Samuel Schwarzkopf
Journal:  Neuroimage       Date:  2019-05-31       Impact factor: 6.556

Review 4.  Studying Cortical Plasticity in Ophthalmic and Neurological Disorders: From Stimulus-Driven to Cortical Circuitry Modeling Approaches.

Authors:  Joana Carvalho; Remco J Renken; Frans W Cornelissen
Journal:  Neural Plast       Date:  2019-11-03       Impact factor: 3.599

5.  Comparison of human population receptive field estimates between scanners and the effect of temporal filtering.

Authors:  Catherine Morgan; D Samuel Schwarzkopf
Journal:  F1000Res       Date:  2019-09-24
  5 in total

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