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Monday, July 20 • 8:00pm - 9:00pm
P204: Stabilization of spiking neural networks using stochastic and high-frequency neurostimulation disrupts seizure-like transitions

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Teaser Video: https://youtu.be/XpifsmyHopY

Google Meet Link: https://meet.google.com/mgo-fdvw-pvb

Want to discuss "asynchronously"? E-mail me (sbrich@umich.edu), find me on Twitter, or find me on LinkedIn.

Authors: Scott Rich
, Axel Hutt, Frances Skinner, Jeremie Lefebvre, Taufik Valiante


Epilepsy is one of the most common serious neurological disorders in the world, typified by repeated unprovoked seizures. Such seizures are characterized by an abrupt transition to a hyper-active, and often hyper- synchronous, brain state [1]. These in vivo transitions share noted similarities to mathematical transitions occurring through bifurcations, suggesting that the study of seizure onset is fertile ground for interdisciplinary research [2]. Neuromodulation represents a promising avenue for clinical intervention in patients with epilepsy, although the field is still wanting for principled understandings of how such devices mitigate seizure onset [3]. Such understanding of neuromodulatory mechanisms may allow for better stimulation strategies to reduce the burden of seizures.

Here, we use a network model to probe how sudden transitions into oscillatory dynamics, which share clear parallels with seizure onset, are influenced by both intrinsic and extrinsic inputs. These extrinsic inputs can be viewed as a model of a neuromodulatory intervention. Building on a previous model of cortical gamma activity [4], the model consists of 500 excitatory and 500 inhibitory all-to-all connected Poisson neurons with heterogeneity implemented in their rheobase analogues.

A combination of numerical simulations and mean-field analyses revealed that high variance and/or high frequency stimulation waveforms were most efficient in preventing multi-stability in these networks, where multi-stability serves as a mathematical harbinger of the sudden transition between asynchronous and oscillatory network dynamics. Furthermore, our analysis showed that stabilization of neural activity is via a selective recruitment of inhibitory cells, providing a theoretical undergird for the known key role these cells play in both the healthy and diseased brain. Interestingly, this effect occurred without the need to precisely “target” the inhibitory population, highlighting that neuromodulatory devices utilizing these stimulation paradigms may not need to be excessively “precise” in order to elicit the desired response. While deep brain stimulation systems have long been thought to affect neural circuits via the creation of a “functional” or “informational” lesion [5], potentially through depolarization blockade [6], these findings provide theoretical support for a distinct mechanism of action through selective interneuronal activation. Taken together, these results provide new vistas on the underlying mechanisms through which neuromodulatory approaches stabilize neural microcircuit activity, utilizing a variety of computational tools including numerical simulation, mean-field reduction, and stochastic stability analysis.


[1] Reynolds, EH. Introduction: epilepsy in the world. Epilepsia. 2002, 43, 1-3.

[2] Wending, F et. al. Computational models of epileptiform activity. J Neuroscience Methods. 2016, 260, 233-251.

[3] Salanova, V. Deep brain stimulation for epilepsy. Epilepsy & Behav. 2018, 18.6, 514-532.

[4] Herrmann, C et. al. Shaping neural oscillations with periodic stimulation. J. Neuroscience. 2016, 36.19, 5328-5337.

[5] Grill, WM et. al. Deep brain stimulation creates an informational lesion of the stimulated nucleus. Neuroreport. 2004, 15.7, 1137-1140.

[6] McIntyre, CC et. al. Uncovering the mechanism(s) of action of deep brain stimulation: activation, inhibition, or both. Clinical Neurophys. 2004, 115.6, 1239-1248.

avatar for Scott Rich

Scott Rich

Postdoctoral Research Fellow, Division of Clinical and Computational Neuroscience, Krembil Research Institute
I'm currently a Postdoctoral Research Fellow at the Krembil Research Institute (part of the University Health Network and affiliated with the University of Toronto), working under the co-supervision of Drs. Frances Skinner, Taufik Valiante, and Jeremie Lefebvre. My research is focused... Read More →

Monday July 20, 2020 8:00pm - 9:00pm
Slot 07

Attendees (41)