Computation embodied in population geometry

Yuanhang Zhang; Massimiliano Di Ventra

doi:10.1038/s41467-026-76139-6

August 5, 2026Nature CommunicationsOpen Access

Computation embodied in population geometry

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Key Points

This research focuses on understanding the shapes formed by populations of spiking neurons and how they can be emulated.
Emulated intrinsic population geometry using electronic devices.
Analyzed low-dimensional shapes formed by spiking neurons.
Investigated energy-efficient forecasting capabilities.
Demonstrated that electronic devices can replicate neural manifold shapes effectively.
Achieved near-training-free forecasting using this emulation.
Highlighted significant energy efficiency in the process.

Abstract

Neural manifolds refer to the low-dimensional shapes formed by populations of spiking neurons. This intrinsic population geometry can be physically emulated by electronic devices, facilitating near-training-free forecasting with exceptional energy efficiency.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a758c3d847ab6d26c0203b7 https://doi.org/10.1038/s41467-026-76139-6

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Computation embodied in population geometry

Key Points

Abstract

Discussion

Cite This Study

Computation embodied in population geometry

Key Points

Abstract

Discussion

Cite This Study

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