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A Minimally Invasive Neurostimulation Method for Controlling Abnormal Synchronisation in the Neuronal Activity

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Specialty Biology
Date 2018 Jul 20
PMID 30024878
Citations 6
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Abstract

Many collective phenomena in Nature emerge from the -partial- synchronisation of the units comprising a system. In the case of the brain, this self-organised process allows groups of neurons to fire in highly intricate partially synchronised patterns and eventually lead to high level cognitive outputs and control over the human body. However, when the synchronisation patterns are altered and hypersynchronisation occurs, undesirable effects can occur. This is particularly striking and well documented in the case of epileptic seizures and tremors in neurodegenerative diseases such as Parkinson's disease. In this paper, we propose an innovative, minimally invasive, control method that can effectively desynchronise misfiring brain regions and thus mitigate and even eliminate the symptoms of the diseases. The control strategy, grounded in the Hamiltonian control theory, is applied to ensembles of neurons modelled via the Kuramoto or the Stuart-Landau models and allows for heterogeneous coupling among the interacting unities. The theory has been complemented with dedicated numerical simulations performed using the small-world Newman-Watts network and the random Erdős-Rényi network. Finally the method has been compared with the gold-standard Proportional-Differential Feedback control technique. Our method is shown to achieve equivalent levels of desynchronisation using lesser control strength and/or fewer controllers, being thus minimally invasive.

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References
1.
Deco G, Kringelbach M, Jirsa V, Ritter P . The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core. Sci Rep. 2017; 7(1):3095. PMC: 5465179. DOI: 10.1038/s41598-017-03073-5. View

2.
Popovych O, Tass P . Control of abnormal synchronization in neurological disorders. Front Neurol. 2015; 5:268. PMC: 4267271. DOI: 10.3389/fneur.2014.00268. View

3.
Lyons M . Deep brain stimulation: current and future clinical applications. Mayo Clin Proc. 2011; 86(7):662-72. PMC: 3127561. DOI: 10.4065/mcp.2011.0045. View

4.
Wendling F, Bartolomei F, Mina F, Huneau C, Benquet P . Interictal spikes, fast ripples and seizures in partial epilepsies--combining multi-level computational models with experimental data. Eur J Neurosci. 2012; 36(2):2164-77. DOI: 10.1111/j.1460-9568.2012.08039.x. View

5.
Hallett M . Transcranial magnetic stimulation and the human brain. Nature. 2000; 406(6792):147-50. DOI: 10.1038/35018000. View