NEW TEAM: Neuro-markers of Expertise
GOALS: "Automaticity is central to the development of expertise, and practice is the means to automaticity. The key challenge for aspiring expert performers is to avoid the arrested development associated with automaticity (and mere practice) and to acquire cognitive skills to support their continued learning and improvement”. ~ Anders Ericsson, p694
Our team’s motivation is to explore the neural signatures associated with the development of the fundamental cognitive skills required for an expert performance (e.g., decision making, anticipation, error-detection and correction, and more). The goal for the team is to monitor the evolution of those cognitive skills across the skill level and to register the relevant structural and functional changes in the brain that are developed over the years of practice.
METHODS & TECHNOLOGIES: Imaging techniques such as fMRI and EEG, Performance recording technics such as eye-tracker, and motion analyzer, Brain simulation, Multivariate data analyses, Signal processing, Task design, Python and MATLAB programming, Machine Learning.
RESEARCH & DESIGN ISSUES: Monitoring and recording behavioral (e.g., outcome performance, reaction time) and neural features of the brain activation patterns when cognitive tasks are performed. Evaluating and contrasting the recorded changes among performers who vary in skill levels. Detecting activation of neural networks involved in cognitive skills. Simulating and modeling the cognitive functioning of the brain regions in response to the practive effect. Use of machines in automaticity and expertise.
MEETING TIME: Tues, 3:00-3:50
ADVISORS: Mark Wheeler (PSYCH), Shamsi Monfared (PSYCH)
PARTNERS & SPONSORS: Georgia Tech, National Science Foundation (NSF)
MAJORS, PREPARATION AND INTERESTS:
Human-Computer Interaction, Music, Bioengineering, Computational Science & Engineering, Neuroscience, Psychology, Statistics, Applied Physics, Medical Physics, Health Systems, Human Performance, Cognitive Neuroscience