ArticleBiological cybernetics2020
Analysis of neural clusters due to deep brain stimulation pulses.
Article in Biological cybernetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 0 citations in OpenAlex.
- How to entrain a selected neuronal rhythm but not others: open-loop dithered brain stimulation for selective entrainment.Journal of neural engineering · 2023Article
- Phase response approaches to neural activity models with distributed delay.Biological cybernetics · 2022Review
- Deep brain stimulation for movement disorder treatment: exploring frequency-dependent efficacy in a computational network model.Biological cybernetics · 2022Article
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Authors and funding
4 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Deep brain stimulation (DBS) is an established method for treating pathological conditions such as Parkinson's disease, dystonia, Tourette syndrome, and essential tremor. While the precise mechanisms which underly the effectiveness of DBS are not fully understood, several theoretical studies of populations of neural oscillators stimulated by periodic pulses have suggested that this may be related to clustering, in which subpopulations of the neurons are synchronized, but the subpopulations are desynchronized with respect to each other. The details of the clustering behavior depend on the frequency and amplitude of the stimulation in a complicated way. In the present study, we investigate how the number of clusters and their stability properties, bifurcations, and basins of attraction can be understood in terms of one-dimensional maps defined on the circle. Moreover, we generalize this analysis to stimuli that consist of pulses with alternating properties, which provide additional degrees of freedom in the design of DBS stimuli. Our results illustrate how the complicated properties of clustering behavior for periodically forced neural oscillator populations can be understood in terms of a much simpler dynamical system.
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