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Related Experiment Video

Updated: Jan 7, 2026

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array
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Backpropagation through space, time and the brain.

Benjamin Ellenberger1, Paul Haider2, Federico Benitez1

  • 1Department of Physiology, University of Bern, Bern, Switzerland.

Nature Communications
|December 26, 2025
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Summary
This summary is machine-generated.

Generalized Latent Equilibrium (GLE) enables physical neuronal networks to perform efficient credit assignment locally. This framework allows for online approximation of backpropagation in deep networks, overcoming spatio-temporal locality constraints.

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Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array
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Area of Science:

  • Computational Neuroscience
  • Artificial Intelligence

Background:

  • Neuronal networks face challenges in credit assignment due to spatio-temporal locality constraints.
  • Existing backpropagation algorithms often violate these locality principles.

Purpose of the Study:

  • Introduce Generalized Latent Equilibrium (GLE) for fully local spatio-temporal credit assignment.
  • Develop a framework for efficient learning in physical, dynamical neuronal networks.

Main Methods:

  • Derived neuronal dynamics from an energy function based on local mismatches.
  • Utilized stationarity and gradient descent for parameter dynamics.
  • Exploited dendritic morphology for information processing and prospective coding.

Main Results:

  • Developed an online approximation of backpropagation through space and time.
  • Demonstrated computation of spatio-temporal convolutions in the forward direction.
  • Showcased approximation of adjoint variables in the backward stream.

Conclusions:

  • GLE provides a biologically plausible mechanism for credit assignment in neuronal networks.
  • This framework supports continuous learning with local synaptic plasticity.
  • Prospective coding enhances computational capabilities within single neurons.