# CRCNS: Collaborative Research: State-Dependent Control for Brain Modulation

> **NIH NIH R01** · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · 2020 · $346,533

## Abstract

Abstract
There is a several decade history demonstrating that electrical polarization of neurons can modulate
neuronal firing, and that such polarization can suppress (or excite) spiking activity and seizures. We have
demonstrated seizure control using both open- and closed-loop stimulation strategies (J Neurophysiol,
76:4202-4205,1996; J Neurosci, 21:590-600, 2001). With past NIMH and CRCNS support (R01MH50006,
1R01EB014641) – we discovered a unification in the computational biophysics of spikes, seizures, and
spreading depression (J Neurosci, 34:11733-11743, 2014). These findings demonstrate that the repertoire
of the dynamics of the neuronal membrane encompasses a broad range of dynamics ranging from normal
to pathological, and that seizures and spreading depression are manifestations of the inherent properties of
those membranes. Recently we achieved a major experimental verification of key predictions from the
unification predictions in in vivo epilepsy. Most recently, we achieved the experimental goal of the most
recent CRCNS project, “Model-Based Control of Spreading Depression”, by demonstrating that neuronal
polarization can suppress (or enhance), block, or prevent spreading depression, the physiological
underpinning of migraine auras. Remarkably, this suppression requires the opposite polarity as that
required to suppress spikes and seizures, and is fully consistent with the computational biophysical models
of spreading depression. Further surprising findings from these experiments was that suppression of
spreading depression does not appear to generate seizures, and vice versa, that when the brain is in
seizure activity suppression does not generate spreading depression. The implications of the above is that
in controlling brain dynamics from different states of the brain, that there can be state dependent control
which is qualitatively very different from that required in other states. Furthermore, the control algorithms
required to maintain a given steady state (e.g. normal spiking) may differ from that required to guide a
system from a pathological state back into a steady state. We propose the hypothesis that there is an
entirely new framework for feedback control of neuronal circuitry – State Dependent Control. This is a
model-based framework, wherein neuronal systems are sensed through electrical or optical sensors, and
the data assimilated into a biophysical computational model of the possible states. Feedback control is then
applied based upon the state, and the trajectory of the system through state space is continually observed.
Working out state dependent control for brain activity has health implications for not only epilepsy and
migraine, but more broadly in intensive care settings because of the harmful effects of spreading depression
waves in traumatic brain injury, stroke, and subarachnoid hemorrhage.

## Key facts

- **NIH application ID:** 10003278
- **Project number:** 5R01EB014641-05
- **Recipient organization:** PENNSYLVANIA STATE UNIV HERSHEY MED CTR
- **Principal Investigator:** Bruce J Gluckman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $346,533
- **Award type:** 5
- **Project period:** 2011-08-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10003278

## Citation

> US National Institutes of Health, RePORTER application 10003278, CRCNS: Collaborative Research: State-Dependent Control for Brain Modulation (5R01EB014641-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10003278. Licensed CC0.

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