330 Electrophysiologically-defined Parameterization of Intracranial Neuromodulation to Define DBS Settings for Treatment-resistant Depression. (1st April 2022)

• Record Type: Journal Article
• Authors: Metzger, Brian; Adkinson, Joshua; Oswalt, Denise; Xiao, Jiayang; Allawala, Anusha; Goodman, Wayne; Pouratian, Nader; Sheth, Sameer A.; Bijanki, Kelly R.
• Is Part Of: Neurosurgery. Volume 68(2022)Supplement 1
• Page Start: 75
• Page End: 75
• Publication Date: 2022-04-01
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1227/NEU.0000000000001880_330
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract : INTRODUCTION: Deep brain stimulation settings for treatment resistant depression are typically selected through a process of behaviorally-defined trial-and-error, which is prone to substantial variability in treatment response. METHODS: Intracranial EEG (iEEG) was collected concurrently with 426 unique DBS configurations varied along 5 dimensions: DBS target, segmented DBS configuration, frequency, amplitude, pulse width. Multiple sessions of baseline resting-state iEEG were also recorded, from which sessions associated with the lowest and highest depression scores were selected as desired and undesired target patterns, respectively. After decomposing iEEG data into frequency bands of interest, we created correlation matrices across the spatial/spectral space of stimulation-evoked changes in power, and rank-ordered the output in terms of similarity for each stimulation configuration to the template patterns. Iterative model fitting then determined which parameter components contributed most to the matching score. RESULTS: To validate the approach, we compared rank-order for desired state to undesired state and found a negative correlation between them (r = -0.45, p < 0.0001), suggesting that high-ranking stimulation parameters matched to the desired state are low-ranking when matched to the undesired state. In application of these stimulation settings for therapeutic stimulation, we saw a substantial reduction in depressive symptoms compared with the patient's pre-DBS baselines (pre-DBS vs template-matching defined stimulation: MADRS 36 vs. 9; HAM-D 24 vs. 6). CONCLUSION: We have implemented spatiotemporal template matching by searching a set of 426 unique stimulation parameter sets for evoked neural states recapitulating the neural signature of a desired state in a patient with TRD. Preliminary data demonstrate that particular spatiotemporal neural signatures can be defined and matched to stimulation-evoked states.