Tracking cognitive strategies using EEG signals Health & Human Sciences Academic Year 2024 Accepted Cognitive Neuroscience/Psychology How does cognitive processing evolve across time? Humans thrive to exhibit cognitive flexibility and to do so, we engage in both top-down and bottom-up processing strategies when confronted with information. Some of us adopt proactive strategies that rely on top-down expectations and working memory capacity to achieve better performance. Others rely on reactive strategies and deal with information as it is presented to us. We have collected a set of EEG data (N = 80) from human participants while they were engaged in tasks requiring them to be cognitively flexible. The task was designed in a way that afforded either strategy and our goal is to use this dataset and construct a model that can predict across time everyone’s strategy (proactive vs. reactive) across time. Preprocessing of the EEG data has been completed. The student will be responsible for conducting additional time-frequency analyses and constructing the prediction model. The student will further use feature tracking algorithm to backward identify the components in the winning model that is responsible for predicting real-time unfolding of strategies supporting human cognitive flexibility. Yu-Chin Chiu Yu-Chin Chiu Literature search; Applying machine-learning algorithms on existing EEG data; Statistical analyses; Scientific writing/reporting Programming skills (matlab, or python). Motivation to learn through problem solving. Desired - Some knowledge about signal processing, machine learning methods and cognitive psychology. 6 20 (estimated)