Integrity of the Prefronto-striato-thalamo-prefrontal Loop Predicts Tai Chi Chuan Training Effects on Cognitive Task-switching in Middle-aged and Older Adults

Tai Chi Chuan evidence related to impulsivity and impulse related disorders: A scoping review

BACKGROUND

The purpose of this study was to review the evidence for the potential of Tai Chi Chuan (TCC) as a model of meditative movement in benefiting people with impulsivity related disorders and provide guidance for future research.

METHODS

A scoping review of the literature was conducted in five databases. Eligibility criteria were original articles reporting TCC based interventions or included TCC techniques and provided any assessment on impulsivity or related measures, impulse control disorders, or other psychiatric disorders related to impulsivity (e.g., addictive disorders, ADHD, and other conduct disorders). Twenty-eight out of 304 studies initially retrieved were reviewed. The reports concentrated mostly on neurodegenerative conditions, cognitive decline, and substance use disorders (SUD).

RESULTS

TCC had several positive effects in cognitive domains resulting in improvements in memory, executive functions, inhibitory control, attention, and verbal fluency. These improvements in memory, executive function, including inhibitory control and attention, and verbal fluency were associated with changes in the brain plasticity, resting activity, and other neurobiological markers.

CONCLUSION

Albeit no study was found on the use of TCC in impulse control disorders or impulse related conditions, other than SUD, the findings suggest that considering the behavioral impact of TCC, especially the improvement of executive functions, it could be a valuable therapeutic tool for approaching impulse control related disorders.

Brain white matter correlates of learning ankle tracking using a wearable device: importance of the superior longitudinal fasciculus II

Background

Wearable devices have been found effective in training ankle control in patients with neurological diseases. However, the neural mechanisms associated with using wearable devices for ankle training remain largely unexplored. This study aimed to investigate the ankle tracking performance and brain white matter changes associated with ankle tracking learning using a wearable-device system and the behavior–brain structure relationships in middle-aged and older adults.

Methods

Twenty-six middle-aged and older adults (48–75 years) participated in this study. Participants underwent 5-day ankle tracking learning with their non-dominant foot using a custom-built ankle tracking system equipped with a wearable sensor and a sensor-computer interface for real-time visual feedback and data acquisition. Repeated and random sequences of target tracking trajectories were both used for learning and testing. Ankle tracking performance, calculated as the root-mean-squared-error (RMSE) between the target and actual ankle trajectories, and brain diffusion spectrum MR images were acquired at baseline and retention tests. The general fractional anisotropy (GFA) values of eight brain white matter tracts of interest were calculated to indicate their integrity. Two-way (Sex × Time) mixed repeated measures ANOVA procedures were used to investigate Sex and Time effects on RMSE and GFA. Correlations between changes in RMSE and those in GFA were analyzed, controlling for age and sex.

Results

After learning, both male and female participants reduced the RMSE of tracking repeated and random sequences (both p < 0.001). Among the eight fiber tracts, the right superior longitudinal fasciculus II (R SLF II) was the only one which showed both increased GFA (p = 0.039) after learning and predictive power of reductions in RMSE for random sequence tracking with its changes in GFA [β = 0.514, R² change = 0.259, p = 0.008].

Conclusions

Our findings implied that interactive tracking movement learning using wearable sensors may place high demands on the attention, sensory feedback integration, and sensorimotor transformation functions of the brain. Therefore, the SLF II, which is known to perform these brain functions, showed corresponding neural plasticity after such learning, and its plasticity also predicted the behavioral gains. The SLF II appears to be a very important anatomical neural correlate involved in such learning paradigms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-022-01042-2.