No evidence that working memory training alters gray matter structure: A MRI surface -based analysis

Relational Integration Training Modulated the Frontoparietal Network for Fluid Intelligence: An EEG Microstates Study

Relational integration is a key subcomponent of working memory and a strong predictor of fluid intelligence. Both relational integration and fluid intelligence share a common neural foundation, particularly involving the frontoparietal network. This study utilized a randomized controlled experiment to examine the effect of relational integration training on brain networks using electroencephalogram (EEG) and microstate analysis. Participants were randomly assigned to either a relational integration training group (n = 29) or an active control group (n = 28) for one month. The Sandia matrices task assessed fluid intelligence, while rest-EEG was recorded during pre- and post-tests. Microstate analysis revealed that, for microstate D, the training group demonstrated a significant increase in occurrence and contribution following the intervention compared to the control group. Additionally, microstate D occurrence was negatively correlated with reaction times (RTs). Post-training, the training group showed a lower occurrence and contribution of microstate C compared to the control group. Regarding transfer probability, the training group exhibited a decrease between microstates A and B, and an increase between microstates C and D. In contrast, the control group showed increased transfer probability between microstates A, B, and C, and a decrease between microstate D and other microstates (B and A). These findings indicate that relational integration training influences frontoparietal networks associated with fluid intelligence. The current study suggests that relational integration training is an effective intervention for enhancing fluid intelligence.

Cortical Thickness Changes After Computerized Working Memory Training in Patients With Mild Cognitive Impairment

Background

Adaptive computerized working memory (WM) training has shown favorable effects on cerebral cortical thickness as compared to non-adaptive training in healthy individuals. However, knowledge of WM training-related morphological changes in mild cognitive impairment (MCI) is limited.

Objective

The primary objective of this double-blind randomized study was to investigate differences in longitudinal cortical thickness trajectories after adaptive and non-adaptive WM training in patients with MCI. We also investigated the genotype effects on cortical thickness trajectories after WM training combining these two training groups using longitudinal structural magnetic resonance imaging (MRI) analysis in Freesurfer.

Method

Magnetic resonance imaging acquisition at 1.5 T were performed at baseline, and after four- and 16-weeks post training. A total of 81 individuals with MCI accepted invitations to undergo 25 training sessions over 5 weeks. Longitudinal Linear Mixed effect models investigated the effect of adaptive vs. non-adaptive WM training. The LME model was fitted for each location (vertex). On all statistical analyzes, a threshold was applied to yield an expected false discovery rate (FDR) of 5%. A secondary LME model investigated the effects of LMX1A and APOE-ε4 on cortical thickness trajectories after WM training.

Results

A total of 62 participants/patients completed the 25 training sessions. Structural MRI showed no group difference between the two training regimes in our MCI patients, contrary to previous reports in cognitively healthy adults. No significant structural cortical changes were found after training, regardless of training type, across all participants. However, LMX1A-AA carriers displayed increased cortical thickness trajectories or lack of decrease in two regions post-training compared to those with LMX1A-GG/GA. No training or training type effects were found in relation to the APOE-ε4 gene variants.

Conclusion

The MCI patients in our study, did not have improved cortical thickness after WM training with either adaptive or non-adaptive training. These results were derived from a heterogeneous population of MCI participants. The lack of changes in the cortical thickness trajectory after WM training may also suggest the lack of atrophy during this follow-up period. Our promising results of increased cortical thickness trajectory, suggesting greater neuroplasticity, in those with LMX1A-AA genotype need to be validated in future trials.

Brain bases of recovery following cognitive rehabilitation for traumatic brain injury: a preliminary study

Many patients with traumatic brain injury (TBI) have persistent cognitive deficits, including decreased attention and working memory. This preliminary study examined fMRI data from a clinical trial implementing a 4-week virtual reality driving intervention to assess how sustained training can improve deficits related to traumatic brain injury. Previously-reported behavioral findings showed improvements in working memory and processing speed in those who received the intervention; this report explores the brain bases of these effects by comparing neural activity related to working memory (n-back task) and resting state connectivity before and after the intervention. In the baseline visit (n = 24), working memory activity was prominent in bilateral DLPFC and prefrontal cortex, anterior insula, medial superior frontal gyrus, left thalamus, bilateral supramarginal / angular gyrus, precuneus, and left posterior middle temporal gyrus. Following intervention, participants showed less global activation on the n-back task, with regions of activity only in the bilateral middle frontal cortex, posterior middle frontal gyrus, and supramarginal gyrus. Activity related to working memory load was reduced for the group that went through the intervention (n = 7) compared to the waitlist control group (n = 4). These results suggest that successful cognitive rehabilitation of working memory in TBI may be associated with increased efficiency of brain networks, evidenced by reduced activation of brain activity during cognitive processing. These results highlight the importance of examining brain activity related to cognitive rehabilitation of attention and working memory after brain injury.

Cortical and subcortical responsiveness to intensive adaptive working memory training: An MRI surface-based analysis

Working memory training (WMT) has been shown to have effects on cognitive performance, the precise effects and the underlying neurobiological mechanisms are, however, still a matter of debate. In particular, the impact of WMT on gray matter morphology is still rather unclear. In the present study, 59 healthy middle‐aged participants (age range 50–65 years) were pseudo‐randomly single‐blinded allocated to an 8‐week adaptive WMT or an 8‐week nonadaptive intervention. Before and after the intervention, high resolution magnetic resonance imaging (MRI) was performed and cognitive test performance was assessed in all participants. Vertex‐wise cortical volume, thickness, surface area, and cortical folding was calculated. Seven subcortical volumes of interest and global mean cortical thickness were also measured. Comparisons of symmetrized percent change (SPC) between groups were conducted to identify group by time interactions. Greater increases in cortical gyrification in bilateral parietal regions, including superior parietal cortex and inferior parietal lobule as well as precuneus, greater increases in cortical volume and thickness in bilateral primary motor cortex, and changes in surface area in bilateral occipital cortex (medial and lateral occipital cortex) were detected in WMT group after training compared to active controls. Structural training‐induced changes in WM‐related regions, especially parietal regions, might provide a better brain processing environment for higher WM load.

Sustained and transient gray matter volume changes after n-back training: A VBM study

Working memory training causes functional adaptations in the brain, which include changes in activation and functional connectivity that remain stable over time. Few studies have investigated gray matter (GM) changes after working memory training, and they have produced heterogeneous results without clarifying the stable effects of training. The present study was designed to test for sustained and transient anatomic changes after only 200 min of working memory training. The voxel-based morphometry technique was used in order to investigate the GM changes produced by a brief single n-back training, immediately and 5 weeks after finishing it. The sample was composed by 59 human participants who underwent MRI scanning and were assigned to either a training group or a passive control group. Results showed sustained GM volume enlargement in the right superior parietal cortex and a transient GM decrease in the right putamen. The brain adaptation in the right superior parietal cortex was stronger in individuals who showed greater improvements in performance. The results provide further evidence that a brief working memory training is able to produce brain plasticity in structures related to the trained task.

Working memory training effects across the lifespan: Evidence from human and experimental animal studies

Working memory refers to a cognitive function that provides temporary storage and manipulation of the information necessary for complex cognitive tasks. Due to its central role in general cognition, several studies have investigated the possibility that training on working memory tasks could improve not only working memory function but also increase other cognitive abilities or modulate other behaviors. This possibility is still highly controversial, with prior studies providing contradictory findings. The lack of systematic approaches and methodological shortcomings complicates this debate even more. This review highlights the impact of working memory training at different ages on humans. Finally, it demonstrates several findings about the neural substrate of training in both humans and experimental animals, including non-human primates and rodents.