Ivan Mindlin

🔗 fastDMF-powered implementation: github.com/Picardian14/...
pure Python version by Carlos :) github.com/carlosmig/Ho...

Thanks to all co-authors for the collaboration, and my colleague and friend @rherzoga.bsky.social for leading this work.

Feedback, reuse, and extensions are very welcome.
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Because inhibitory control is local and homeostatic, adaptiveness can be heterogeneous across regions while remaining stable. This enables coexisting SW and asynchronous regimes—chimeric-like—suggesting a potential mechanism to cognitive states such as local-sleep–related attentional lapses. 4/5

In a high-coupling regime, the adaptive inhibitory feedback gives rise to bistable UP–DOWN dynamics (delta-range slow waves (SW) ), while faster adaptation supports asynchronous activity.
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In the DMF, resting-state activity emerges from noisy firing rates stabilized by feedback inhibitory control (FIC).
Previous implementations (e.g. fastDMF) use static inhibition. Here, we introduce a local plastic inhibitory rule that can dynamically self adjust toward homeostasis.

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The impact of homeostatic inhibitory plasticity in a generative biophysical model A main characteristic of biological systems is their capacity to dynamically adapt to environmental changes. In the brain, synaptic plasticity enables the strengthening or weakening of connections bet...

📄Very happy to share our new pre-print!! 🧠

We introduce a homeostatic inhibitory plasticity rule into the Dynamic Mean Field (DMF) model which stabilizes firing rates and expands the model’s dynamical repertoire—for example, enabling slow-wave activity.

www.biorxiv.org/content/10.6...
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