Deep brain stimulation (DBS) of the ventral intermediate nucleus (Vim) of the thalamus may be used to treat medication refractory essential tremor. Using recordings from in vivo human Vim neurons, our previous work has suggested that evoked potentials (that we termed quasi-evoked inhibition) ∼2 ms following high frequency microstimulation pulses may be related to inhibitory synapses onto the Vim. Here, we investigate whether (i) quasi-evoked inhibition is related to clinical tremor reduction, and (ii) if quasi-evoked inhibition is dependent on the stimulation location within the Vim. By developing an objective determination of the presence or absence of quasi-evoked inhibition and utilizing accelerometer recordings, we showed that recordings with quasi-evoked inhibition at 100 Hz microstimulation exhibit greater tremor reduction than those without (P < 0.05, BF > 30). The number of stimulation pulses with quasi-evoked inhibition is also correlated with tremor reduction (rho = 0.18, P < 0.05) at all stimulation frequencies >=100 Hz. Furthermore, by analyzing microelectrode trajectories reconstructed from structural MRIs, we found that proximity to the ventral caudal border (P < 0.005) and to a previously established sweet spot (P < 0.05) are anti-correlated with the number of stimulation pulses with quasi-evoked inhibition. Our findings suggest that quasi-evoked inhibition is a potential biomarker of tremor reduction by means of network inhibition, and the more posterior regions of the Vim may allow for better recruitment of inhibition. This may be useful for closed-loop stimulation design.
Zoe Paraskevopoulos, D. Crompton, Sarah Iskin et al.· bioRxiv· 0 citations
Deep Brain Stimulation (DBS) is an established clinical treatment for a variety of neurological disorders, including Parkinson’s Disease where it has been shown to reduce motor symptoms as well as disrupt pathological beta oscillations in the basal ganglia. The mechanisms of action of DBS on the collective activity of neuronal circuits is not fully understood. We use a recurrently-connected excitatory-inhbitory network based on the Brunel network architecture that can produce activity in a variety of states. Using a model of DBS that can reproduce observed effects such as antidromic activation, local somatic suppression, and axonal activation, we characterize the effect of stimulation across the entire parameter space of the network. We show that the effects of stimulation are dependent on the baseline state of the network, with the level of beta suppression dependent on the level of inhibition and the external drive. Specifically, networks with higher inhibition and lower drive show greater disruption of beta oscillations. We further show that networks in different states are preferentially sensitive to different frequencies of stimulation, suggesting that alternative protocols to the clinically standard high-frequency stimulation may have therapeutic efficacy.
Spandan Sengupta, Shervin Safavi, T. Knösche et al.· bioRxiv· 0 citations
A comprehensive phenomenological computational model is proposed that accounts for the impact of electrical stimulation parameters on neuronal circuits while incorporating experimentally-validated synaptic and cellular constraints and provides a mechanistic framework for understanding DBS representation and propagation in neuronal networks.
D. Crompton, L. Milosevic, M. Lankarany· bioRxiv· 0 citations