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Decoding the Mental States of Focus and Distraction in a Real Life Setting of Tibetan Monastic Debates Using EEG and Machine Learning

Authors
Ms. Pallavi Kaushik
University of Groningen
Dr. Marieke Van Vugt
University of Groningen ~ Cognitive Modeling Group
Partha Pratim Roy
Indian Institute of Technology, Roorkee, India
Abstract

Cognitive science has started to make more and more use of techniques from machine learning to disentangle the neural correlates of cognitive processes. It can be particularly useful for complex situations in which many things are happening at the same time. Here we apply machine learning to investigate the cognitive processes in a rather novel situation: Tibetan monastic debate. Monastic debate is a core practice used in Tibetan monasteries to train preciseness of reasoning and memorization. In the work presented here we distinguish between the occurrence of attentional states, focus and distraction. This gives insight into the cognitive effect of debate training.

Discussion
New

This is really interesting work! Such a unique data set and application. I can imagine there are numerous reasons why a trainee was marked 'distracted' or 'focused'. I'm curious if you've identified subcategories of what may drive distraction or focus in this type of scenario and whether or not there are unique neural patterns that may diagnose the...

Dr. Elizabeth Fox 1 comment
Cite this as:

Kaushik, P., Van Vugt, M., & Roy, P. (2020, July). Decoding the Mental States of Focus and Distraction in a Real Life Setting of Tibetan Monastic Debates Using EEG and Machine Learning. Paper presented at Virtual MathPsych/ICCM 2020. Via mathpsych.org/presentation/174.