Journal of Neural EngineeringNeurosciencePeer-reviewed journal article
Quantifying a Frequency Modulation Response Biomarker in Responsive Neurostimulation
Praveen VenkateshiD, Daniel Sneider, Mohammed Danish, Nathaniel D. SistersoniD, Naoir Zaher, Alexandra UrbaniD, Pulkit GroveriD, Robert Mark RichardsoniD, Vasileios KokkinosiD
Abstract
ObjectiveResponsive Neurostimulation (RNS) is an effective treatment for controlling seizures in patients with drug-resistant focal epilepsy who are not suitable candidates for resection surgery. A lack of tools for detecting and characterizing potential response biomarkers, however, contributes to a limited understanding of mechanisms by which RNS improves seizure control. We developed a method to quantify ictal frequency modulation, previously identified as a biomarker of clinical responsiveness to RNS. ApproachFrequency modulation is characterized by shifts in power across spectral bands during ictal events, over several months of neurostimulation. This effect was quantified by partitioning each seizure pattern into segments with distinct spectral content and measuring the extent change from the baseline distribution of spectral content using the squared Earthmovers distance. Main resultsWe analyzed intracranial electroencephalography data from 13 patients who received RNS therapy, six of whom exhibited frequency modulation on expert evaluation. Subjects in the frequency modulation group had, on average, significantly larger and more sustained changes in their Earthmovers distances (mean = 13.97x10-3 {+/-} 1.197x10-3). In contrast, those subjects without expert-identified frequency modulation exhibited statistically insignificant or negligible distances (mean = 4.994x10-3 {+/-} 0.732x10-3). SignificanceThis method is the first step towards a quantitative, feedback-driven system for systematically optimizing RNS stimulation parameters, with an ultimate goal of truly personalized closed-loop therapy for epilepsy.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 13
- FWCI
- 1.61
- Field percentile
- top 19%
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