Behavioural Relevance of Neural Dynamics

Our interests in the relations between cognition and brain signal variability have been broad to date, spanning simple and complex perceptual decision-making (e.g., Kloosterman et al., 2019, eLife), internal vs. externally modulated states (e.g., Grady and Garrett, 2018, NeuroImage), working (e.g., Garrett et al., 2015, PNAS) and long-term memory (Kloosterman et al., in prep), and reinforcement learning (Skowron et al., in prep) using a variety of stimuli types, cognitive performance metrics, and model parameterizations. Broadly, we find that better performers have higher brain signal variability, and that within-person signal variability can parametrically tune with changes in task difficulty (Garrett et al., 2013a,b, Cerebral Cortex; 2013, NBR; 2015 PNAS). We also continue to examine whether variability may be an expression of the flexible modulation of brain states that allows a probabilistic search for an optimal state, given either unexpected or anticipated changes in the environment (see Garrett et al., 2013, NBR).

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