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dc.contributor.authorYousif, N
dc.contributor.authorBain, PG
dc.contributor.authorNandi, D
dc.contributor.authorBorisyuk, R
dc.date.accessioned2020-03-20T13:58:56Z
dc.date.issued2020-03-05
dc.description.abstractFor more than 30 years, deep brain stimulation (DBS) has been used to target the symptoms of a number of neurological disorders and in particular movement disorders such as Parkinson’s disease (PD) and essential tremor (ET). It is known that the loss of dopaminergic neurons in the substantia nigra leads to PD, while the exact impact of this on the brain dynamics is not fully understood, the presence of beta-band oscillatory activity is thought to be pathological. The cause of ET, however, remains uncertain, however pathological oscillations in the thalamocortical-cerebellar network have been linked to tremor. Both of these movement disorders are treated with DBS, which entails the surgical implantation of electrodes into a patient’s brain. While DBS leads to an improvement in symptoms for many patients, the mechanisms underlying this improvement is not clearly understood, and computational modeling has been used extensively to improve this. Many of the models used to study DBS and its effect on the human brain have mainly utilized single neuron and single axon biophysical models. We have previously shown in separate models however, that the use of population models can shed much light on the mechanisms of the underlying pathological neural activity in PD and ET in turn, and on the mechanisms underlying DBS. Together, this work suggested that the dynamics of the cerebellar-basal ganglia thalamocortical network support oscillations at frequency range relevant to movement disorders. Here, we propose a new combined model of this network and present new results that demonstrate that both Parkinsonian oscillations in the beta band and oscillations in the tremor frequency range arise from the dynamics of such a network. We find regions in the parameter space demonstrating the different dynamics and go on to examine the transition from one oscillatory regime to another as well as the impact of DBS on these different types of pathological activity. This work will allow us to better understand the changes in brain activity induced by DBS, and allow us to optimize this clinical therapy, particularly in terms of target selection and parameter setting.en_GB
dc.identifier.citationVol. 14, article no. 55en_GB
dc.identifier.doi10.3389/fnhum.2020.00055
dc.identifier.urihttp://hdl.handle.net/10871/120354
dc.language.isoenen_GB
dc.publisherFrontiers Mediaen_GB
dc.rightsCopyright © 2020 Yousif, Bain, Nandi and Borisyuk. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_GB
dc.subjectParkinson’s diseaseen_GB
dc.subjectessential tremoren_GB
dc.subjectoscillationsen_GB
dc.subjectcomputational modelingen_GB
dc.subjectbeta banden_GB
dc.subjectgamma banden_GB
dc.titleA population model of deep brain stimulation in movement disorders From circuits to cellsen_GB
dc.typeArticleen_GB
dc.date.available2020-03-20T13:58:56Z
dc.descriptionThis is the final version. Available from Frontiers Media via the DOI in this record. en_GB
dc.identifier.eissn1662-5161
dc.identifier.journalFrontiers in Human Neuroscienceen_GB
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-02-05
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-02-05
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-03-20T13:52:14Z
refterms.versionFCDVoR
refterms.dateFOA2020-03-20T13:58:59Z
refterms.panelBen_GB


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Copyright © 2020 Yousif, Bain, Nandi and Borisyuk. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Except where otherwise noted, this item's licence is described as Copyright © 2020 Yousif, Bain, Nandi and Borisyuk. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.