Data driven multiscale modelling of paroxysmal brain transitions using DC-coupled electrophysiological data.

Overview

1. MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
2. Research Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
3. Centre for Nanotechnology in Medicine & Division of Neuroscience, University of Manchester, Manchester, United Kingdom

Abstract

We introduce a novel parameter estimation framework for a slow-fast neuronal model using DC-coupled electrophysiological data recorded from the WAG-Rij rat model of generalised seizures. In this animal model, fluctuations in extracellular potassium concentrations are hypothesised to drive infra-slow oscillations (ISO) that precede spike-wave discharges. We construct a biophysically motivated slow-fast dynamical system in which seizures are triggered by fluctuations in extracellular potassium concentrations to model the in vivo observations. Specifically, we interpret ISOs dynamics (mathematically) as the integral transform (or low-pass filter) of extracellular potassium concentrations, facilitating real time tracking of physiological states. Model parameters are estimated from empirical data, using an expectation-maximisation approach that optimises a regularised likelihood function, while biological states are inferred through the unscented Kalman filter. The inferred model allows tracking changes in latent proxy of extracellular potassium concentrations from DC-coupled electrophysiological recordings (exhibiting paroxysmal transitions) under the assumption that in our preclinical model extracellular potassium dynamics contribute to seizure generation. We validate the consistency of inferred hidden biological states across longer datasets containing multiple seizure events that were not utilised during parameter estimation. The results demonstrate that ISOs provide sufficient information to infer latent ionic dynamics and support the conceptualisation of seizure onset as bifurcation-driven transitions modulated by the ionic changes.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data, not to its authors' code: see the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Datasets cited

• zenodo:5655535, at Zenodo; found in “Data Availability”

Data Availability

All data used in this paper are freely available in Zenodo at the following address: https://doi.org/10.5281/zenodo.5655535.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 9 MeSH terms, 55 references.

Cite

This paper

Jafarian, A., & Wykes, R. C. (2026). Data driven multiscale modelling of paroxysmal brain transitions using DC-coupled electrophysiological data. PloS one, 21(7), e0353399. https://doi.org/10.1371/journal.pone.0353399

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1038/s41467-026-73790-x [code]

An artefact-resilient wide bandwidth bidirectional graphene neural interface.

Journal: Nature communications

In common: 2 references, author Rob C Wykes

[2] doi:10.1162/netn.a.543 [code]

High-resolution Bayesian Virtual Epileptic Patient using neural field models.

Journal: Network neuroscience (Cambridge, Mass.)

In common: epilepsy, 3 references

[3] doi:10.1371/journal.pcbi.1014222 [code]

Neural population models for EEG: From Canonical models to alternative model structures.

Journal: PLoS computational biology

In common: 3 references

[4] doi:10.1093/braincomms/fcag130 [code]

Sleep increases firing rate modulation during interictal epileptiform discharges in mesial temporal structures.

Journal: Brain communications

In common: epilepsy, 2 references

[5] doi:10.1038/s41598-026-44063-w [code]

Neuronal silence as a predictive biomarker and target for epileptic seizures suppression.

Journal: Scientific reports

In common: epilepsy, 2 references

[6] doi:10.1038/s42003-026-09988-y

Thalamic involvement defines distinct slow-wave subtypes in NREM sleep.

Journal: Communications biology

In common: 2 references

[7] doi:10.3389/fphar.2026.1881525

Pentylenetetrazole kindling impairs place recognition memory associated with suppressing proBDNF-mediated neural information flows at the hippocampal CA3-CA1 synapses.

Journal: Frontiers in pharmacology

In common: epilepsy, rat, 1 reference

[8] doi:10.1002/epi.70252

Dual role of spreading depolarization in an epileptic focus.

Journal: Epilepsia

In common: epilepsy, rat, 1 reference

[9] doi:10.1371/journal.pdig.0001445 [code]

A digital twin approach for simultaneous reconstruction of brain anatomy and dynamics from neural data.

Journal: PLOS digital health

In common: 2 references

[10] doi:10.1371/journal.pcbi.1013463 [code]

A multi-frequency whole-brain neural mass model with homeostatic feedback inhibition.

Journal: PLoS computational biology

In common: 2 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.