Brain Functional Connectivity Changes During Learning of Time Discrimination.

Abstract

Introduction: The human brain is a complex system consisting of connected nerve cells that adapt to and learn from the environment by changing its regional activities. The synchrony between these regional activities is called functional network changes during life and results in the learning of new skills. Time perception and interval discrimination are among the most necessary skills for the human being to perceive motions, coordinate motor functions, speak, and perform many cognitive functions. Despite its importance, the underlying mechanism of changes in brain functional connectivity patterns during learning time intervals still need to be well understood.

Methods: This study aimed to show how electroencephalography (EEG) functional connectivity changes are associated with learning temporal intervals. In this regard, 12 healthy volunteers were trained with an auditory time-interval discrimination task over six days while their brain activities were recorded via EEG signals during the first and the last sessions. Then, changes in regional phase synchronization were calculated using the weighted/phase lag index (WPLI) approach, the most effective EEG functional connections at the temporal and prefrontal regions, and in the theta and beta bands frequency. In addition, the WPLI reported more accurate values.

Results: The results showed that learning interval discrimination significantly changed functional connectivity in the prefrontal and temporal regions.

Conclusion: These findings could shed light on a better understanding of the brain mechanism involved in time perception.

Highlights: Accuracy of auditory interval discrimination improved by a six-day learning process.Most established connections were formed in the temporal, occipital and middle regions of brain.Creation of new significant connection was observed at the theta and gamma frequency bands.New neural networks are constructed between regions of the brain during interval learning.

Plain language summary: The time perception is a vital challenge that human beings face in various aspects of their lives. Researchers have always been challenged in how to calculate it and understand its mechanism for each individual. In the present study, which is based on the temporal perception, by comparing the timing of auditory stimuli, we seek to show the functional relationships of neural network formation related to learning temporal perception. Our aim was to understand how the hidden information of auditory stimuli (time intervals) is encoded in the content of the brain signals.