Changes in resting‐state functionally connected parietofrontal networks after videogame practice

Abstract

Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test-retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test-retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions.

Strengthening Connections: Functional Connectivity and Brain Plasticity

“…In the trained group, increased frontoparietal, parietostriatal and frontostriatal iFC was observed, with increases in frontoparietal and parietostriatal iFC being associated with improvements in LSAT performance (though it should be noted that the brain-behavior correlations were uncorrected for multiple comparisons). Another study (Martinez et al, 2013) also observed increased iFC within frontoparietal and lateral and medial temporal networks (also at uncorrected thresholds) following 4 weeks of practice on a puzzle-solving game. As in the study by Jolles et al (2013), it is possible that the increased iFC within higher-level cognitive networks observed in these two studies reflects the fact that even after practice performance was not asymptotic, and required the continued scaffolding support of widespread increases in iFC.…”

Altered brain rhythms and functional network disruptions involved in patients with generalized fixation-off epilepsy

“…We obtained a statistical map (p values) per band (5) and condition (3), which were used as gold standard for finding potential disruptions in patients 1 and 2. We considered statistically significant the uncorrected p<0.005 (cluster size 10), since any statistical contrast passed TFCE-based permutations to correct for multiple comparisons, probably due to the high intra-subject variability of this EEG-informed fMRI relationships Mantini et al 2007) and the small sample size (Martinez et al 2013).…”

“…T h e i n p u t m a t r i x h a d n voxels *(n conditions *n subjects *n Volumes ) dimensions equals to n voxels * (2 conditions *7 subjects *120 Volumes ) dimensions in our case. The outputs from this TC-GICA were 25 Independent Component (IC) spatial maps, which were used to identify large-scale resting state networks (Damoiseaux et al 2006;Martinez et al 2013;Smith et al 2009). …”

“…In both fMRI analyses, the 25 ICs were sorted into two broad classes: biologically relevant components, and scanner/physiological artifactual components following the criteria purposed by Kelly et al (Kelly et al 2010;Martinez et al 2013).…”

“…Independent Component Analyses on the resting-state fMRI series were computed using Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) (Beckmann and Smith 2004;Martinez et al 2013) toolbox in FSL. Here, two types of fMRI standalone analysis were performed, which differed in the initial input data matrix.…”