Intelligence describes the general cognitive ability level of a person. It is one of the most fundamental concepts in psychological science and is crucial for the effective adaption of behavior to varying environmental demands. Changing external task demands have been shown to induce reconfiguration of functional brain networks. However, whether neural reconfiguration between different tasks is associated with intelligence has not yet been investigated. We used functional magnetic resonance imaging data from 812 subjects to show that higher scores of general intelligence are related to less brain network reconfiguration between resting state and seven different task states as well as to network reconfiguration between tasks. This association holds for all functional brain networks except the motor system and replicates in two independent samples (n = 138 and n = 184). Our findings suggest that the intrinsic network architecture of individuals with higher intelligence scores is closer to the network architecture as required by various cognitive demands. Multitask brain network reconfiguration may, therefore, represent a neural reflection of the behavioral positive manifold – the essence of the concept of general intelligence. Finally, our results support neural efficiency theories of cognitive ability and reveal insights into human intelligence as an emergent property from a distributed multitask brain network.
more » « less- NSF-PAR ID:
- 10372941
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Cerebral Cortex
- Volume:
- 32
- Issue:
- 19
- ISSN:
- 1047-3211
- Page Range / eLocation ID:
- p. 4172-4182
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Introduction Working memory is a critical cognitive ability that affects our daily functioning and relates to many cognitive processes and clinical conditions. Episodic memory is vital because it enables individuals to form and maintain their self‐identities. Our study analyzes the extent to which whole‐brain functional connectivity observed during completion of an
N ‐back memory task, a common measure of working memory, can predict both working memory and episodic memory.Methods We used connectome‐based predictive models (CPMs) to predict 502 Human Connectome Project (HCP) participants' in‐scanner 2‐back memory test scores and out‐of‐scanner working memory test (List Sorting) and episodic memory test (Picture Sequence and Penn Word) scores based on functional magnetic resonance imaging (fMRI) data collected both during rest and
N ‐back task performance. We also analyzed the functional brain connections that contributed to prediction for each of these models.Results Functional connectivity observed during
N ‐back task performance predicted out‐of‐scanner List Sorting scores and to a lesser extent out‐of‐scanner Picture Sequence scores, but did not predict out‐of‐scanner Penn Word scores. Additionally, the functional connections predicting 2‐back scores overlapped to a greater degree with those predicting List Sorting scores than with those predicting Picture Sequence or Penn Word scores. Functional connections with the insula, including connections between insular and parietal regions, predicted scores across the 2‐back, List Sorting, and Picture Sequence tasks.Conclusions Our findings validate functional connectivity observed during the
N ‐back task as a measure of working memory, which generalizes to predict episodic memory to a lesser extent. By building on our understanding of the predictive power ofN ‐back task functional connectivity, this work enhances our knowledge of relationships between working memory and episodic memory.
