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Rethinking Statistical Learning as a Dynamic Stochastic Process, from The Motor Systems Perspective
[article]
2022
bioRxiv
pre-print
The brain integrates streams of sensory input and builds accurate predictions, while arriving at stable percepts under disparate time scales. This stochastic process bears different dynamics for different people, yet statistical learning (SL) currently averages out, as noise, individual fluctuations in data streams registered from the brain as the person learns. We here adopt the motor systems perspective to reframe SL. Specifically, we rethink this problem using the demands that the person's
doi:10.1101/2022.01.18.476831
fatcat:5c2vb7gtibbp5ijtam6ipzgse4