ArticleProceedings of the National Academy of Sciences of the United States of America2022
Heterogeneous stochastic bifurcations explain intrinsic oscillatory patterns in entorhinal cortical stellate cells.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 16 citations in OpenAlex.
- Intrinsic Excitability of Rat Hippocampal Granule Cells Increases Along the Dorsal-to-Ventral Axis.Hippocampus · 2026Article
- The biological role of local and global fMRI BOLD signal variability in multiscale human brain organization.Nature communications · 2026Article
- 3D pattern formation of a protein-membrane suspension.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Degeneracy Explains Diversity in Interneuronal Regulation of Pattern Separation in Heterogeneous Dentate Gyrus Networks.Function (Oxford, England) · 2025Article
- Review
- The Brain's Best Kept Secret Is Its Degenerate Structure.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Review
- The biological role of local and global fMRI BOLD signal variability in human brain organization.bioRxiv : the preprint server for biology · 2023Article
- Heterogeneous off-target impact of ion-channel deletion on intrinsic properties of hippocampal model neurons that self-regulate calcium.Frontiers in cellular neuroscience · 2023Article
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2 authors at 1 institution in 1 country.
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Abstract
Stellate cells (SC) in the medial entorhinal cortex manifest intrinsic membrane potential oscillatory patterns. Although different theoretical frameworks have been proposed to explain these patterns, a robust unifying framework that jointly accounts for intrinsic heterogeneities and stochasticity is missing. Here, we first performed in vitro patch-clamp electrophysiological recordings from rat SCs and found pronounced cell-to-cell variability in their characteristic physiological properties, including peri-threshold oscillatory patterns. We demonstrate that noise introduced into two independent populations (endowed with deterministic or stochastic ion-channel gating kinetics) of heterogeneous biophysical models yielded activity patterns that were qualitatively similar to electrophysiological peri-threshold oscillatory activity in SCs. We developed spectrogram-based quantitative metrics for the identification of valid oscillations and confirmed that these metrics reliably captured the variable-amplitude and arhythmic oscillatory patterns observed in electrophysiological recordings. Using these quantitative metrics, we validated activity patterns from both heterogeneous populations of SC models, with each model assessed with multiple trials of different levels of noise at distinct membrane depolarizations. Our analyses unveiled the manifestation of stochastic resonance (detection of the highest number of valid oscillatory traces at an optimal level of noise) in both heterogeneous populations of SC models. Finally, we show that a generalized network motif comprised of a slow negative feedback loop amplified by a fast positive feedback loop manifested stochastic bifurcations and stochastic resonance in the emergence of oscillations. Together, through a unique convergence of the degeneracy and stochastic resonance frameworks, our unifying framework centered on heterogeneous stochastic bifurcations argues for state-dependent emergence of SC oscillations.
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