학술논문

Brain network modularity predicts cognitive training-related gains in young adults
Document Type
article
Source
Subject
Biological Psychology
Psychology
Behavioral and Social Science
Brain Disorders
Neurosciences
Clinical Research
Underpinning research
1.1 Normal biological development and functioning
1.2 Psychological and socioeconomic processes
Mental health
Neurological
Adolescent
Adult
Attention
Brain
Cognition
Female
Humans
Image Processing
Computer-Assisted
Magnetic Resonance Imaging
Male
Memory
Short-Term
Nerve Net
Neuropsychological Tests
Problem Solving
Video Games
Young Adult
Functional connectivity
Brain network modularity
Cognitive training
Working memory
Reasoning
Cognitive Sciences
Experimental Psychology
Biological psychology
Cognitive and computational psychology
Language
Abstract
The brain operates via networked activity in separable groups of regions called modules. The quantification of modularity compares the number of connections within and between modules, with high modularity indicating greater segregation, or dense connections within sub-networks and sparse connections between sub-networks. Previous work has demonstrated that baseline brain network modularity predicts executive function outcomes in older adults and patients with traumatic brain injury after cognitive and exercise interventions. In healthy young adults, however, the functional significance of brain modularity in predicting training-related cognitive improvements is not fully understood. Here, we quantified brain network modularity in young adults who underwent cognitive training with casual video games that engaged working memory and reasoning processes. Network modularity assessed at baseline was positively correlated with training-related improvements on untrained tasks. The relationship between baseline modularity and training gain was especially evident in initially lower performing individuals and was not present in a group of control participants that did not show training-related gains. These results suggest that a more modular brain network organization may allow for greater training responsiveness. On a broader scale, these findings suggest that, particularly in low-performing individuals, global network properties can capture aspects of brain function that are important in understanding individual differences in learning.