Work

State and parameter estimation for a neural model of local field potentials

Year: 2026

Type: article

Abstract: The study of cortical dynamics during different states such as decision making, sleep and movement, is an important topic in Neuroscience. Modelling efforts aim to relate the neural rhythms present in cortical recordings to the underlying dynamics responsible for their emergence. We present an effort to capture certain features of the neural activity from the cortex of a mouse during natural sleep, obtained through local field potential measurements. Our approach relies on using a discretized Wilson-Cowan Amari neural field model for neural activity, along with a data assimilation method that allows the Bayesian joint estimation of the state and parameters. We demonstrate the feasibility of our approach on synthetic measurements before applying it to a dataset available in literature. Our findings suggest the potential of our approach to characterize the parameters of the external forcing in the neural activity model, while simultaneously inferring a state that aligns with the observed signal.

Source: Journal of Mathematical Biology

DOI: 10.1007/s00285-026-02451-w

Authors: Daniele Avitabile, Gabriel J. Lord, Khadija Meddouni

Institutions: Institut national de recherche en sciences et technologies du numérique, Academic Center for Dentistry Amsterdam, Radboud University Nijmegen

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,090

OpenAlex ID: W7114809393

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