Characterisation of cortical activity in response to deep brain stimulation of ventral-lateral nucleus: Modelling and experiment

M.H. Adhikari, J.H. Heeroma, M. di Bernardo, B. Krauskopf, M.P. Richardson, M.C. Walker, J.R. Terry

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Motivated by its success as a therapeutic treatment in other neurological disorders, most notably Parkinson’s disease, Deep Brain Stimulation (DBS) is currently being trialled in a number of patients with drug unresponsive epilepsies. However, the mechanisms by which DBS interferes with neuronal activity linked to the disorder are not well understood. Furthermore, there is a need to identify optimized values of parameters (for example in amplitude/frequency space) of the stimulation protocol with which one aims to achieve the desired outcome.

In this paper we characterise the system response to stimulation, to gain an understanding of the role different brain regions play in generating the output observed in EEG. We perform a number of experiments in healthy rats, where the ventral–lateral thalamic nucleus is stimulated using a train of square-waves with different frequency and amplitudes. The response to stimulation in the motor cortex is recorded and the drive–response relationship over frequency/amplitude space is considered. Subsequently, we compare the experimental data with simulations of a mean-field model, finding good agreement between the output of the model and the experimental data – both in the time and frequency domains – when considering a transition to oscillatory activity in the cortex as the frequency of stimulation is increased.

Overall, our study suggests that mean-field models can appropriately characterise the stimulus–response relationship of DBS in healthy animals. In this way, it constitutes a first step towards the goal of developing a closed-loop feedback control protocol for suppressing epileptic activity, by adaptively adjusting the stimulation protocol in response to EEG activity.
Original languageEnglish
Pages (from-to)77-85
JournalJournal of Neuroscience Methods
Volume183
Issue number1
DOIs
Publication statusPublished - 30 Sept 2009

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