Literature DB >> 31222630

Validating the relation-monitoring task as a measure of relational integration and predictor of fluid intelligence.

Joel E Bateman1, Kate A Thompson2, Damian P Birney2.   

Abstract

The relation-monitoring task (RMT) has demonstrated a remarkable ability to predict higher-order cognitive abilities such as fluid intelligence, despite its apparent simplicity: It requires no storage over time and no advanced mental manipulation. Instead, the task is theorized to measure relational integration: the process of constructing mental relations between independent elements. Although several studies have established a link between the RMT and fluid intelligence, few studies have investigated the task parameters that contribute to the task's ability to predict higher-order performance. In the present experiment, we manipulated relational complexity and attentional-control demands by varying visual interference and the amount of new information presented on each trial. Even the most basic version of the task (loading primarily on relational integration) explained substantial variance in fluid intelligence, above and beyond the variance already predicted by traditional working memory tasks. We extended prior results by suggesting an incremental effect of attentional-control demands that contributes (but is not imperative) to the RMT's relationship with fluid intelligence. These findings support the relational integration hypothesis, the theory that what fundamentally limits fluid intelligence is the capacity for relational integration.

Keywords:  Attention; Fluid intelligence; Reasoning; Relational integration; Working memory

Year:  2019        PMID: 31222630     DOI: 10.3758/s13421-019-00952-2

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


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Authors:  Joel E Bateman; Damian P Birney
Journal:  Acta Psychol (Amst)       Date:  2019-08-30

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Journal:  Behav Brain Sci       Date:  1998-12       Impact factor: 12.579

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Journal:  Acta Psychol (Amst)       Date:  1967

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Authors:  Jiachen Lu; Lili Tian; Jiafeng Zhang; Jing Wang; Chaoxiong Ye; Qiang Liu
Journal:  Sci Rep       Date:  2017-11-24       Impact factor: 4.379

10.  The relational integration task explains fluid reasoning above and beyond other working memory tasks.

Authors:  Adam Chuderski
Journal:  Mem Cognit       Date:  2014-04
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  2 in total

1.  Fluid Intelligence Emerges from Representing Relations.

Authors:  Adam Chuderski
Journal:  J Intell       Date:  2022-08-02

2.  Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This.

Authors:  Damian P Birney; Jens F Beckmann
Journal:  J Intell       Date:  2022-08-01
  2 in total

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