Literature DB >> 25583612

Attention enhances multi-voxel representation of novel objects in frontal, parietal and visual cortices.

Alexandra Woolgar1, Mark A Williams2, Anina N Rich2.   

Abstract

Selective attention is fundamental for human activity, but the details of its neural implementation remain elusive. One influential theory, the adaptive coding hypothesis (Duncan, 2001, An adaptive coding model of neural function in prefrontal cortex, Nature Reviews Neuroscience 2:820-829), proposes that single neurons in certain frontal and parietal regions dynamically adjust their responses to selectively encode relevant information. This selective representation may in turn support selective processing in more specialized brain regions such as the visual cortices. Here, we use multi-voxel decoding of functional magnetic resonance images to demonstrate selective representation of attended--and not distractor--objects in frontal, parietal, and visual cortices. In addition, we highlight a critical role for task demands in determining which brain regions exhibit selective coding. Strikingly, representation of attended objects in frontoparietal cortex was highest under conditions of high perceptual demand, when stimuli were hard to perceive and coding in early visual cortex was weak. Coding in early visual cortex varied as a function of attention and perceptual demand, while coding in higher visual areas was sensitive to the allocation of attention but robust to changes in perceptual difficulty. Consistent with high-profile reports, peripherally presented objects could also be decoded from activity at the occipital pole, a region which corresponds to the fovea. Our results emphasize the flexibility of frontoparietal and visual systems. They support the hypothesis that attention enhances the multi-voxel representation of information in the brain, and suggest that the engagement of this attentional mechanism depends critically on current task demands.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Attention; Frontoparietal; Multi-voxel coding; Pattern analysis; Visual objects; fMRI

Mesh:

Year:  2015        PMID: 25583612     DOI: 10.1016/j.neuroimage.2014.12.083

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


  13 in total

1.  Multisensory coding in the multiple-demand regions: vibrotactile task information is coded in frontoparietal cortex.

Authors:  Alexandra Woolgar; Regine Zopf
Journal:  J Neurophysiol       Date:  2017-04-12       Impact factor: 2.714

2.  Bottom-Up and Top-Down Factors Differentially Influence Stimulus Representations Across Large-Scale Attentional Networks.

Authors:  Nicole M Long; Brice A Kuhl
Journal:  J Neurosci       Date:  2018-02-02       Impact factor: 6.167

3.  An Information-Driven 2-Pathway Characterization of Occipitotemporal and Posterior Parietal Visual Object Representations.

Authors:  Maryam Vaziri-Pashkam; Yaoda Xu
Journal:  Cereb Cortex       Date:  2019-05-01       Impact factor: 5.357

Review 4.  The Posterior Parietal Cortex in Adaptive Visual Processing.

Authors:  Yaoda Xu
Journal:  Trends Neurosci       Date:  2018-08-14       Impact factor: 13.837

5.  Discrimination of Visual Categories Based on Behavioral Relevance in Widespread Regions of Frontoparietal Cortex.

Authors:  Yaara Erez; John Duncan
Journal:  J Neurosci       Date:  2015-09-09       Impact factor: 6.167

6.  Neural signatures of vigilance decrements predict behavioural errors before they occur.

Authors:  Alexandra Woolgar; Anina N Rich; Hamid Karimi-Rouzbahani
Journal:  Elife       Date:  2021-04-08       Impact factor: 8.140

7.  Concurrent neuroimaging and neurostimulation reveals a causal role for dlPFC in coding of task-relevant information.

Authors:  Jade B Jackson; Eva Feredoes; Anina N Rich; Michael Lindner; Alexandra Woolgar
Journal:  Commun Biol       Date:  2021-05-17

8.  Task Context Overrules Object- and Category-Related Representational Content in the Human Parietal Cortex.

Authors:  Stefania Bracci; Nicky Daniels; Hans Op de Beeck
Journal:  Cereb Cortex       Date:  2017-01-01       Impact factor: 5.357

Review 9.  Integrated Intelligence from Distributed Brain Activity.

Authors:  John Duncan; Moataz Assem; Sneha Shashidhara
Journal:  Trends Cogn Sci       Date:  2020-08-05       Impact factor: 20.229

10.  Response of the multiple-demand network during simple stimulus discriminations.

Authors:  Tanya Wen; Daniel J Mitchell; John Duncan
Journal:  Neuroimage       Date:  2018-05-10       Impact factor: 6.556

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