Towards the next generation of recurrent network models for cognitive neuroscience

GR Yang, M Molano-Mazón - Current opinion in neurobiology, 2021 - Elsevier
Recurrent neural networks (RNNs) trained with machine learning techniques on cognitive
tasks have become a widely accepted tool for neuroscientists. In this short opinion piece, we …

Neural mechanisms underlying the temporal organization of naturalistic animal behavior

L Mazzucato - Elife, 2022 - elifesciences.org
Naturalistic animal behavior exhibits a strikingly complex organization in the temporal
domain, with variability arising from at least three sources: hierarchical, contextual, and …

Contextual inference underlies the learning of sensorimotor repertoires

JB Heald, M Lengyel, DM Wolpert - Nature, 2021 - nature.com
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 …

Thalamic control of cortical dynamics in a model of flexible motor sequencing

L Logiaco, LF Abbott, S Escola - Cell reports, 2021 - cell.com
The neural mechanisms that generate an extensible library of motor motifs and flexibly string
them into arbitrary sequences are unclear. We developed a model in which inhibitory basal …

Optimal anticipatory control as a theory of motor preparation: A thalamo-cortical circuit model

TC Kao, MS Sadabadi, G Hennequin - Neuron, 2021 - cell.com
Across a range of motor and cognitive tasks, cortical activity can be accurately described by
low-dimensional dynamics unfolding from specific initial conditions on every trial. These" …

De novo motor learning creates structure in neural activity space that shapes adaptation

JC Chang, MG Perich, LE Miller, JA Gallego… - …, 2023 - pmc.ncbi.nlm.nih.gov
Animals can quickly adapt learned movements in response to external perturbations. Motor
adaptation is likely influenced by an animal's existing movement repertoire, but the nature of …