Literature DB >> 26806290

Representational dynamics of object recognition: Feedforward and feedback information flows.

Erin Goddard1, Thomas A Carlson2, Nadene Dermody3, Alexandra Woolgar2.   

Abstract

Object perception involves a range of visual and cognitive processes, and is known to include both a feedfoward flow of information from early visual cortical areas to higher cortical areas, along with feedback from areas such as prefrontal cortex. Previous studies have found that low and high spatial frequency information regarding object identity may be processed over different timescales. Here we used the high temporal resolution of magnetoencephalography (MEG) combined with multivariate pattern analysis to measure information specifically related to object identity in peri-frontal and peri-occipital areas. Using stimuli closely matched in their low-level visual content, we found that activity in peri-occipital cortex could be used to decode object identity from ~80ms post stimulus onset, and activity in peri-frontal cortex could also be used to decode object identity from a later time (~265ms post stimulus onset). Low spatial frequency information related to object identity was present in the MEG signal at an earlier time than high spatial frequency information for peri-occipital cortex, but not for peri-frontal cortex. We additionally used Granger causality analysis to compare feedforward and feedback influences on representational content, and found evidence of both an early feedfoward flow and later feedback flow of information related to object identity. We discuss our findings in relation to existing theories of object processing and propose how the methods we use here could be used to address further questions of the neural substrates underlying object perception.
Copyright © 2016 Elsevier Inc. All rights reserved.

Keywords:  Coarse-to-fine; Feedback; Granger causality; Magnetoencephalography; Pattern classifier analysis; Visual perception

Mesh:

Year:  2016        PMID: 26806290     DOI: 10.1016/j.neuroimage.2016.01.006

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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