Mitigating Mismatch Compression in Differential Local Field Potentials

Vineet Tiruvadi, Samuel James, Bryan Howell, Mosadoluwa Obatusin, Andrea Crowell, Patricio Riva-Posse, Robert E Gross, Cameron C McIntyre, Helen S Mayberg, Robert Butera, Vineet Tiruvadi, Samuel James, Bryan Howell, Mosadoluwa Obatusin, Andrea Crowell, Patricio Riva-Posse, Robert E Gross, Cameron C McIntyre, Helen S Mayberg, Robert Butera

Abstract

Deep brain stimulation (DBS) devices capable of measuring differential local field potentials ( ∂ LFP) enable neural recordings alongside clinical therapy. Efforts to identify oscillatory correlates of various brain disorders, or disease readouts, are growing but must proceed carefully to ensure readouts are not distorted by brain environment. In this report we identified, characterized, and mitigated a major source of distortion in ∂ LFP that we introduce as mismatch compression (MC). Using in vivo, in silico, and in vitro models of MC, we showed that impedance mismatches in the two recording electrodes can yield incomplete rejection of stimulation artifact and subsequent gain compression that distorts oscillatory power. We then developed and validated an opensource mitigation pipeline that mitigates the distortions arising from MC. This work enables more reliable oscillatory readouts for adaptive DBS applications.

Conflict of interest statement

Conflicts of Interest

Cameron C. McIntyre is a paid consultant for Boston Scientific Neuromodulation, receives royalties from Hologram Consultants, Neuros Medical, Qr8 Health, and is a shareholder in the following companies: Hologram Consultants, Surgical Information Sciences, CereGate, Autonomic Technologies, Cardionomic, Enspire DBS. Helen S. Mayberg has a consulting agreement with Abbott Labs (previously St Jude Medical, Neuromodulation), which has licensed her intellectual property to develop SCC DBS for the treatment of severe depression (US 2005/0033379A1). Robert E. Gross serves as a consultant to and receives research support from Medtronic, and serves as a consultant to Abbott Labs. The terms of these arrangements have been approved by Emory University, Icahn School of Medicine, and Duke University in accordance with policies to manage conflict of interest. All other authors have no COI to declare.

Figures

Fig. 1.. Mismatch Compression in ∂LFPs.
Fig. 1.. Mismatch Compression in ∂LFPs.
a, Clinical DBS leads have four electrodes, each of which can be in either gray or white matter. ∂LFP records from two electrodes around the stimulation electrode. b, An in vitro model introduces differences in resistivity to test whether impedance mismatches in the two electrodes causes gain compression in amplifiers. c, Amplifier transfer function shows how inputs are transformed into outputs. Three models are simulated here. d, Time domain output from the different amplifier models demonstrate the effects of gain compression, both hard-clipping and soft-clipping. e, Schematic of the focused MC model consists of brain, lead, amplifier layers. f, Simulated ∂LFP is analysed with the same approaches used for empirical measurements.
Fig. 2.. Empirical ∂LFPs.
Fig. 2.. Empirical ∂LFPs.
a, in vitro agar construct with two distinct phases - saline (clear) and agar (blue). DBS lead is placed in saline phase. b, DBS lead is fixed at either uniform saline or interface conditions with microactuator rig. c, A 15 s in vivo recording from Activa PC+S™ without active stimulation. d, A 15 s in vivo recording with active stimulation. Recording settling time was seen in first few seconds. e, Stimulation onset during voltage sweep shows stimulation transient.
Fig. 3.. MC Mitigation Steps -
Fig. 3.. MC Mitigation Steps -
a, MC mitigation pipeline for ∂LFP recordings remove frequency features that can be distorted. b, Empirical PSD in saline at two stimulation voltages demonstrates mismatch compression. c, Adjustments to the frequency windows for oscillatory bands to avoid mismatch compression artifacts. In this illustration, no polynomial subtraction is performed. d, Comparison of mean and median power calculation within standard and adjusted bands. Calculations are performed in both 0V and 8V stimulation.
Fig. 4.. In vivo measurement variability.
Fig. 4.. In vivo measurement variability.
a, Spectrogram of in vivo voltage sweep from 2V to 8V demonstrates significant changes locked to stimulation. b, Weekly averaged ∂LFP PSDs over seven months in a single patient demonstrate significant variability across months of recording. Each bold color curve (translucent) is a fourth-order polynomial fit to the weekly average (thin color curve). c, Impedance mismatches in recording electrodes of all patients demonstrate large, dynamic mismatches in left and (d) right DBS leads. e, An over-range marker (ORM) power was calculated across recordings from all weeks to assess presence of overt gain compression (saturation), demonstrating variability over the weeks in both left and (f) right channels.
Fig. 5.. Simulation generates gain compression distortions…
Fig. 5.. Simulation generates gain compression distortions with impedance mismatch.
a, Simulated ∂LFP at a low impedance mismatch (ZΔ) shows artifacts during simulated 130 Hz stimulation. Before stimulation (blue box and line) is compared to during stimulation (green box and line). b, Power spectral density (PSD) for the before and during stimulation time periods. c,d, Simulated ∂LFP at a high impedance. e, Simulated PSD at various stimulation voltages. Aliased simulation harmonics (ASH) and intermodulation harmonics (IMH) are labeled. f, Empirical recording in saline shows an observed peak at all simulated peaks. Additional peaks are present and not attributed to MC due to their insensitivity to impedance mismatches.
Fig. 6.. In vitro Mismatch Compression.
Fig. 6.. In vitro Mismatch Compression.
∂LFP recordings were captured in two configurations: a, uniform saline medium and b, interface of saline-agar. c, Uniform-medium PSDs at various voltages demonstrate distinct peaks, with 32 Hz, 64 Hz, and 66 Hz being highlighted for their voltage-dependence. d, Interface-media PSDs demonstrate more voltage-dependence. e, Oscillatory power calculated in uniform-medium at various stimulation voltages compared to f, interface-medium. g, Recordings taken at both interface (solid dot) and uniform (empty dot), with a range of stimulation voltages 0V to 8V. h, Aliased stimulation harmonic (ASH) arise from suboptimally sampled stimulation shaping harmonics (SSH), while intermodulation hamornics (IMH) arise directly from amplifier gain compression. i, Gain compression ratio (GCr) calculated from ASH and IMH reflect both stimulation voltage and impedance mismatch.
Fig. 7.. Applied MC Mitigations.
Fig. 7.. Applied MC Mitigations.
a, Raw PSDs recorded in agar at stimulation voltages between 0V to 8V. b, Oscillatory power calculated in each band for each tested stimulation voltage. c, Corrected PSDs remove features that are corrupted by mismatch compression. d, Oscillatory power calculated converges to the no-stimulation condition across all stimulation voltages. e,f, PSDs from chronic recordings across 7 months in two patients. Thin lines are weekly averaged PSDs, bold lines are polynomial fits to highlight weekly variability. g,h, MC pipeline applied to all weekly PSDs shows removal of features distorted by MC. Significant inter-patient variability is observed; differences in oscillatory power can more confidently be ascribed to neural sources.

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