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Related Experiment Video

Updated: May 29, 2025

A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments
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Separating cognitive and motor processes in the behaving mouse.

Munib A Hasnain1,2, Jaclyn E Birnbaum2,3, Juan Luis Ugarte Nunez1

  • 1Department of Biomedical Engineering, Boston University, Boston, MA, USA.

Nature Neuroscience
|February 5, 2025
PubMed
Summary

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A. J. Major et al. reply.

Nature neuroscience·2025
This summary is machine-generated.

Cognitive processes in animals are linked to movements, but a new study shows they are distinct. Researchers isolated cognitive and motor neural dynamics, revealing separate cell populations encode each process.

Area of Science:

  • Neuroscience
  • Animal Behavior
  • Cognitive Science

Background:

  • Complex animal behaviors involve cognitive processes and movements, which are strongly correlated with neural activity.
  • A key question is whether cognitive and motor processes share neural mechanisms or are separable.

Purpose of the Study:

  • To develop methods for assessing the separability of cognitive and motor processes.
  • To isolate and characterize the neural dynamics associated with distinct cognitive and motor components.

Main Methods:

  • Designed a novel behavioral task in mice involving multiple cognitive processes.
  • Applied a subspace decomposition technique to isolate cognitive and motor neural dynamics.
  • Analyzed neural population activity to identify cell populations encoding each component.

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Main Results:

  • Neural dynamics previously attributed to cognition were found to be contaminated by movement-related activity.
  • Isolated cognitive and motor components exhibited distinct dynamical trajectories.
  • Largely separate neuronal populations were identified for encoding cognitive versus motor processes.

Conclusions:

  • Cognitive and motor processes in complex behaviors are largely separable at the neural level.
  • Accurate isolation of cognitive and motor dynamics is crucial for understanding neural circuit function.
  • Findings inform the development of conceptual and computational models of the brain.