Literature DB >> 31476428

Individual differences in parietal and frontal cortex structure predict dissociable capacities for perception and cognitive control.

Joshua O Eayrs1, Nilli Lavie2.   

Abstract

Capacity limits in perception can lead to failures of awareness in situations that overload capacity, resulting in various phenomena of 'inattentional blindness'. In contrast, capacity limits in cognitive control over attention by working memory lead to increased processing of irrelevant distractors (reduced inattentional blindness). Here, using Voxel-Based Morphometry combined with Principal Components Analysis, we establish distinct brain-structural correlates of perceptual capacity, dissociable from those of cognitive control. Perceptual capacity was measured as the principal component accounting for variance across tasks of multiple object tracking, change blindness and rapid visual enumeration (i.e. 'subitizing'). Cognitive control capacity was measured as the principal component underlying performance of three different complex working memory span tasks (involving spatial, semantic and numerical domains). Volumetric differences in the right Inferior Parietal Lobule (IPL) were predictive of individual differences in perceptual capacity, while volumetric differences in left Middle Frontal Gyrus (MFG) (as well as lateral frontal and posterior cingulate cortex in a non-parametric analysis) were predictive of individual differences in cognitive control capacity. IPL remained a significant predictor of perceptual capacity when controlling for variance accounted for by cognitive control capacity and vice versa for the neural correlates of cognitive control. These results suggest that perceptual and cognitive control capacities represent dissociable and lasting, trait-like attributes which can be predicted from distinct signatures in regional grey matter.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cognitive control; Individual differences; Perceptual capacity; Voxel based morphometry

Year:  2019        PMID: 31476428     DOI: 10.1016/j.neuroimage.2019.116148

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


  3 in total

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Authors:  Melissa Newton; Savannah L Cookson; Mark D'Esposito; Andrew Kayser
Journal:  J Neurosci       Date:  2022-08-29       Impact factor: 6.709

2.  Neural representation of phonological information during Chinese character reading.

Authors:  Aqian Li; Rui Yang; Jing Qu; Jie Dong; Lala Gu; Leilei Mei
Journal:  Hum Brain Mapp       Date:  2022-05-12       Impact factor: 5.399

3.  Social media 'addiction': The absence of an attentional bias to social media stimuli.

Authors:  Katie Thomson; Simon C Hunter; Stephen H Butler; David J Robertson
Journal:  J Behav Addict       Date:  2021-04-13       Impact factor: 6.756

  3 in total

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