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  • Open Access

Revealing Stimulus-Dependent Dynamics Through Statistical Complexity

Edson V. de Paula1, Rafael M. Jungmann2,3, Antonio J. Fontenele4, Leandro A. A. Aguiar1,2,3, Pedro V. Carelli1, Fernanda S. Matias5, Mauro Copelli1,*, and Nivaldo A. P. de Vasconcelos6,†

  • *Contact author: mauro.copelli@ufpe.br
  • †Contact author: nivaldo.vasconcelos@ufpe.br
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PRX Life 4, 023018 – Published 22 May, 2026

DOI: https://doi.org/10.1103/wndc-k654

Abstract

Advances in large-scale neural recordings have expanded our ability to describe the activity of distributed brain circuits. However, understanding how neural population dynamics differ across regions and behavioral contexts remains challenging. Here, we surveyed neuronal population dynamics across multiple mouse brain areas (visual cortex, hippocampus, thalamus, and midbrain) using spike data from local ensembles. Two complementary measures were used to characterize these dynamics: the coefficient of variation (CV), a classical indicator of spike-time variability, and statistical complexity, an information-theoretic quantifier of organizational structure. To probe stimulus-dependent activity, we segmented and concatenated recordings from behavioral experiments into distinct time series corresponding to natural image presentations, blank screens during visual task, and spontaneous activity. While the CV failed to discriminate between these conditions, statistical complexity revealed clear, stimulus-specific motifs in population activity. These results indicate that information-theoretic measures can uncover structured, stimulus-dependent patterns in neural population dynamics that remain unobserved in traditional variability metrics.

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Corrections

22 July, 2026

Correction: A minor error in Eq. (9) has been fixed.

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Outline

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PRX Life 4, 023018– Published 22 May, 2026
  • Received 28 November 2025
  • Accepted 15 April 2026
  • Corrected 22 July 2026
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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