Handling MEG Data Corrupted with Deep Brain Stimulation Artifacts - Some Pointers

TY - GEN

T1 - Handling MEG Data Corrupted with Deep Brain Stimulation Artifacts - Some Pointers

AU - Ganguly, Suranjita

AU - Jain, Ankita

AU - Koppula, Aditya

AU - Sasidharan, Sreedev

AU - Dattada, Vamsi Vijay Mohan

AU - Hojlund, Andreas

AU - Sridharan, Kousik Sarathy

N1 - Publisher Copyright: © 2023 IEEE.

PY - 2023

Y1 - 2023

N2 - Deep brain stimulation (DBS) is a therapeutic treatment used in pathological conditions, which is known to improve clinical state, but the effect-mechanisms are unclear. The electrophysiological study of effect-mechanisms is complicated by strong artifactual components blurring the boundary between brain activity and DBS-induced noise. To study the artifactual signatures and the effect of pre-processing steps such as spatiotemporal signal space separation (tSSS) and normalization on the DBS-corrupted MEG data, we deployed a watermelon-based phantom 'implanted' with DBS leads and stimulated the phantom with various DBS stimulation settings. We observe that tSSS can lead to a 'spillover' of artifacts between sensor types and bipolar stimulation leads to lower sub-harmonic (20 Hz) artifacts compared to monopolar stimulation. Normalized spectra, we show here, can be biased if artifactual spectral bins are chosen as the normalizing factor. Alternatively, artifact-free bins can be visually chosen or an unbiased approach such as the FOOOF method can be used.

AB - Deep brain stimulation (DBS) is a therapeutic treatment used in pathological conditions, which is known to improve clinical state, but the effect-mechanisms are unclear. The electrophysiological study of effect-mechanisms is complicated by strong artifactual components blurring the boundary between brain activity and DBS-induced noise. To study the artifactual signatures and the effect of pre-processing steps such as spatiotemporal signal space separation (tSSS) and normalization on the DBS-corrupted MEG data, we deployed a watermelon-based phantom 'implanted' with DBS leads and stimulated the phantom with various DBS stimulation settings. We observe that tSSS can lead to a 'spillover' of artifacts between sensor types and bipolar stimulation leads to lower sub-harmonic (20 Hz) artifacts compared to monopolar stimulation. Normalized spectra, we show here, can be biased if artifactual spectral bins are chosen as the normalizing factor. Alternatively, artifact-free bins can be visually chosen or an unbiased approach such as the FOOOF method can be used.

KW - artifcact handling

KW - Deep Brain Stimulation

KW - MEG

KW - Parkinson's disease

KW - Phantom

UR - http://www.scopus.com/inward/record.url?scp=85183535351&partnerID=8YFLogxK

U2 - 10.1109/ICAEECI58247.2023.10370869

DO - 10.1109/ICAEECI58247.2023.10370869

M3 - Article in proceedings

AN - SCOPUS:85183535351

SN - 979-8-3503-4280-2

BT - 2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI)

PB - IEEE

T2 - 1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

Y2 - 19 October 2023 through 20 October 2023

ER -