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Dynamic control of sequential retrieval speed in networks with heterogeneous learning rules.

Publication ,  Journal Article
Gillett, M; Brunel, N
Published in: Elife
August 28, 2024

Temporal rescaling of sequential neural activity has been observed in multiple brain areas during behaviors involving time estimation and motor execution at variable speeds. Temporally asymmetric Hebbian rules have been used in network models to learn and retrieve sequential activity, with characteristics that are qualitatively consistent with experimental observations. However, in these models sequential activity is retrieved at a fixed speed. Here, we investigate the effects of a heterogeneity of plasticity rules on network dynamics. In a model in which neurons differ by the degree of temporal symmetry of their plasticity rule, we find that retrieval speed can be controlled by varying external inputs to the network. Neurons with temporally symmetric plasticity rules act as brakes and tend to slow down the dynamics, while neurons with temporally asymmetric rules act as accelerators of the dynamics. We also find that such networks can naturally generate separate 'preparatory' and 'execution' activity patterns with appropriate external inputs.

Duke Scholars

Published In

Elife

DOI

EISSN

2050-084X

Publication Date

August 28, 2024

Volume

12

Location

England

Related Subject Headings

  • Neurons
  • Neuronal Plasticity
  • Nerve Net
  • Models, Neurological
  • Learning
  • Humans
  • Brain
  • Animals
  • 42 Health sciences
  • 32 Biomedical and clinical sciences
 

Citation

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Gillett, M., & Brunel, N. (2024). Dynamic control of sequential retrieval speed in networks with heterogeneous learning rules. Elife, 12. https://doi.org/10.7554/eLife.88805
Gillett, Maxwell, and Nicolas Brunel. “Dynamic control of sequential retrieval speed in networks with heterogeneous learning rules.Elife 12 (August 28, 2024). https://doi.org/10.7554/eLife.88805.
Gillett, Maxwell, and Nicolas Brunel. “Dynamic control of sequential retrieval speed in networks with heterogeneous learning rules.Elife, vol. 12, Aug. 2024. Pubmed, doi:10.7554/eLife.88805.

Published In

Elife

DOI

EISSN

2050-084X

Publication Date

August 28, 2024

Volume

12

Location

England

Related Subject Headings

  • Neurons
  • Neuronal Plasticity
  • Nerve Net
  • Models, Neurological
  • Learning
  • Humans
  • Brain
  • Animals
  • 42 Health sciences
  • 32 Biomedical and clinical sciences