Cognitive Science Research on Mathematical Model of Memory Published in Nature

November 25, 2021

Co-authored by Máté Lengyel, PhD, a Senior Research Fellow at Central European Universitys (CEU) Department of Cognitive Science and Center for Cognitive Computation, and Professor of Computational Neuroscience at the University of Cambridge, and co-funded by a grant from the European Research Council hosted by CEU, the research Contextual inference underlies the learning of sensorimotor repertoires” appeared on November 24 in Nature.

"This research tells us something very fundamental about how memory works,” said Professor Lengyel. "The traditional view has been that when you show improvement in a skill (a so-called learning curve), it must be because you are laying down a new memory, or perhaps modifying an existing one. We show that there may be an entirely different mechanism at play: you may simply be changing how much you rely on any one of the huge repertoire of memories your brain has already stored over your life time."

Contextual inference underlies the learning of sensorimotor repertoires

Heald, J.B., Lengyel, M. & Wolpert, D.M.

Nature, 46, Published: 24 November 2021.

Humans spend a lifetime learning, storing and refining a repertoire of motor

memories. For example, through experience, we become proficient at manipulating a

large range of objects with distinct dynamical properties. However, it is unknown

what principle underlies how our continuous stream of sensorimotor experience is

segmented into separate memories and how we adapt and use this growing

repertoire. Here we develop a theory of motor learning based on the key principle that

memory creation, updating and expression are all controlled by a single

computation—contextual inference. Our theory reveals that adaptation can arise both

by creating and updating memories (proper learning) and by changing how existing

memories are differentially expressed (apparent learning). This insight enables us to

account for key features of motor learning that had no unified explanation:

spontaneous recovery1, savings2, anterograde interference3, how environmental

consistency affects learning rate4,5 and the distinction between explicit and implicit

learning6. Critically, our theory also predicts previously undescribed phenomena—

evoked recovery and context-dependent single-trial learning—which we confirm

experimentally. These results suggest that contextual inference, rather than classical

single-context mechanisms1,4,7–9, is the key principle underlying how a diverse set of

experiences is reflected in our motor behaviour.

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