Literature DB >> 19761522

Resource allocation and fluid intelligence: insights from pupillometry.

Elke van der Meer1, Reinhard Beyer, Judith Horn, Manja Foth, Boris Bornemann, Jan Ries, Juerg Kramer, Elke Warmuth, Hauke R Heekeren, Isabell Wartenburger.   

Abstract

Thinking is biological work and involves the allocation of cognitive resources. The aim of this study was to investigate the impact of fluid intelligence on the allocation of cognitive resources while one is processing low-level and high-level cognitive tasks. Individuals with high versus average fluid intelligence performed low-level choice reaction time tasks and high-level geometric analogy tasks. We combined behavioral measures to examine speed and accuracy of processing with pupillary measures that indicate resource allocation. Individuals with high fluid intelligence processed the low-level choice reaction time tasks faster than normal controls. The task-evoked pupillary responses did not differ between groups. Furthermore, individuals with high fluid intelligence processed the high-level geometric analogies faster, more accurately, and showed greater pupil dilations than normal controls. This was only true, however, for the most difficult analogy tasks. In addition, individuals with high fluid intelligence showed greater preexperimental pupil baseline diameters than normal controls. These results indicate that individuals with high fluid intelligence have more resources available and thus can solve more demanding tasks. Moreover, high fluid intelligence appears to be accompanied by more task-free exploration.

Mesh:

Year:  2009        PMID: 19761522     DOI: 10.1111/j.1469-8986.2009.00884.x

Source DB:  PubMed          Journal:  Psychophysiology        ISSN: 0048-5772            Impact factor:   4.016


  43 in total

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2.  Insulin resistance is associated with poorer verbal fluency performance in women.

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3.  Pupillary Responses as a Biomarker of Early Risk for Alzheimer's Disease.

Authors:  Eric L Granholm; Matthew S Panizzon; Jeremy A Elman; Amy J Jak; Richard L Hauger; Mark W Bondi; Michael J Lyons; Carol E Franz; William S Kremen
Journal:  J Alzheimers Dis       Date:  2017       Impact factor: 4.472

4.  Individual differences in baseline oculometrics: Examining variation in baseline pupil diameter, spontaneous eye blink rate, and fixation stability.

Authors:  Nash Unsworth; Matthew K Robison; Ashley L Miller
Journal:  Cogn Affect Behav Neurosci       Date:  2019-08       Impact factor: 3.282

5.  Pupillary responses during a joint attention task are associated with nonverbal cognitive abilities and sub-clinical symptoms of autism.

Authors:  Valentyna Erstenyuk; Meghan R Swanson; Michael Siller
Journal:  Res Autism Spectr Disord       Date:  2014-06-01

6.  Task-evoked pupillary responses track effort exertion: Evidence from task-switching.

Authors:  Kevin da Silva Castanheira; Sophia LoParco; A Ross Otto
Journal:  Cogn Affect Behav Neurosci       Date:  2020-10-20       Impact factor: 3.282

7.  How to Build a Dichoptic Presentation System That Includes an Eye Tracker.

Authors:  Cheng S Qian; Jan W Brascamp
Journal:  J Vis Exp       Date:  2017-09-06       Impact factor: 1.355

8.  Speech-perception training for older adults with hearing loss impacts word recognition and effort.

Authors:  Stefanie E Kuchinsky; Jayne B Ahlstrom; Stephanie L Cute; Larry E Humes; Judy R Dubno; Mark A Eckert
Journal:  Psychophysiology       Date:  2014-06-09       Impact factor: 4.016

9.  Pupillary dilation responses as a midlife indicator of risk for Alzheimer's disease: association with Alzheimer's disease polygenic risk.

Authors:  William S Kremen; Matthew S Panizzon; Jeremy A Elman; Eric L Granholm; Ole A Andreassen; Anders M Dale; Nathan A Gillespie; Daniel E Gustavson; Mark W Logue; Michael J Lyons; Michael C Neale; Chandra A Reynolds; Nathan Whitsel; Carol E Franz
Journal:  Neurobiol Aging       Date:  2019-09-09       Impact factor: 4.673

10.  Neuromelanin marks the spot: identifying a locus coeruleus biomarker of cognitive reserve in healthy aging.

Authors:  David V Clewett; Tae-Ho Lee; Steven Greening; Allison Ponzio; Eshed Margalit; Mara Mather
Journal:  Neurobiol Aging       Date:  2015-10-29       Impact factor: 4.673

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