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Published on: March 3, 2023
Perceptual Learning of Multiple Object Tracking Is Not Enhanced by Transcranial Random Noise Stimulation of hMT
Xiaoxin Chen1, Renhao Ye2, Arijit Chakraborty3,4,5
1Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.
Purpose:
Multiple object tracking (MOT) assesses the ability to attentively track multiple moving targets. We investigated whether perceptual learning enhances MOT performance in adults with normal vision and whether this effect can be enhanced by high-frequency transcranial random noise stimulation (hf-tRNS) of the human middle temporal complex (hMT+).
Methods:
Nineteen adults with normal vision were recruited. The experimental protocol comprised two baseline measurements (10 days apart), 8 days of 25-minute MOT training (days 1-8), and a postintervention measurement. During training, nine participants received 25-minute hf-tRNS (1 mA) to hMT+, while the other 10 participants received sham stimulation.
Results:
A mixed-design analysis of variance indicated that training significantly improved MOT performance (main effect of time: F(9, 153) = 24.82, P < 0.001). Post hoc analysis shows that a significant difference from baseline occurred from day 2 to posttraining, indicating a clear MOT improvement. Posttraining performance was significantly different from baseline up to day 4, suggesting that training effects plateaued on day 5. There was no significant interaction between time and stimulation (F(9, 153) = 0.631, P = 0.438) and no significant main effect of stimulation (F(9, 153) = 1.402, P = 0.192), indicating hf-tRNS did not modulate the effect of training.
Conclusions:
Perceptual learning significantly improved MOT performance in adults with normal vision. However, hf-tRNS over the hMT+ area did not further enhance MOT performance.
Translational Relevance:
This research confirms the perceptual learning effect on multiple object tracking, highlighting its potential for future rehabilitation of MOT performance in patients with MOT deficits.
