Objective: Apply signal processing methods for more robust Bereitschaftspotential detection

Background: The Bereitschaftspotential (readiness potential, BP) is a small, slow rising negative scalp EEG potential beginning 1-2 seconds before voluntary movement [1, 2]. The BP is a positive finding used to support clinical diagnoses of functional myoclonus, formerly known as ‘psychogenic’ [3]. Reliably detecting the BP requires capturing a large number of events for EEG back averaging in a relaxed patient with distinct EMG bursts against a relative paucity of artefact, especially eye movements. This is challenging in the clinical context where there may be too few events, or myoclonic jerks may be clustered or coincide with other movements. Artefact Subspace Reconstruction (ASR) [4] and Independent Component Analysis (ICA) [5] are artefact correction methods best used on high-density EEG. This retrospective study assesses the applicability of these methods for detecting the BP in functional myoclonus investigations with the reduced montage EEG used in clinical routine.

Method: Thirty-three patients were included who polygraphic recordings with back-averaging analysis on a Micromed system. Recordings were deemed as either having BP present (22) or absent (11) BP by an expert reviewer. The raw recordings were imported to Python and the EEG processed with either ASR or ICA, back-averaged, and the BP at FC3, FC4 and Cz electrodes compared between the two processed methods and the unprocessed EEG back-average. As a heuristic of how well the preprocessing supports a more robust analysis, myoclonic events were randomly dropped from analysis and the variation in the averaged pre-event EEG gradients were compared.

Results: Overall averages did not significantly differ between processing methods. ICA processing led to a lower variation with randomly dropped epochs than did the raw data (Wilcoxon signed rank, W=400, p=0.016). When looking only at those studies with BP present, there was a significant improvement in between event variation with both ASR and ICA (Wilcoxon signed rank, W=179, p=0.046; W=181, p=0.040, respectively).

Conclusion: ASR and manual ICA potentially provide methods for reliable clinical BP studies with relatively fewer events, or in situations with more artefact. Addition of electro-oculography leads may facilitate this preprocessing, as might extra scalp EEG electrodes.

References: [1] Kornhuber, H.H. and Deecke, L., 1965. Hirnpotentialänderungen bei Willkürbewegungen und passiven Bewegungen des Menschen: Bereitschaftspotential und reafferente Potentiale. Pflüger’s Archiv für die gesamte Physiologie des Menschen und der Tiere, 284, pp.1-17.
[2] Libet, B. and Gleason, C., 1983. a., Wright, EW, & Pearl, DK (1983). Time of conscious intention to act in relation to onset of cerebral activity (readiness-potential). Brain, 106(3), pp.623-642.
[3] Perez, D.L., Edwards, M.J., Nielsen, G., Kozlowska, K., Hallett, M. and LaFrance Jr, W.C., 2021. Decade of progress in motor functional neurological disorder: continuing the momentum. Journal of Neurology, Neurosurgery & Psychiatry, 92(6), pp.668-677.
[4] Mullen, Tim R., Christian AE Kothe, Yu Mike Chi, Alejandro Ojeda, Trevor Kerth, Scott Makeig, Tzyy-Ping Jung, and Gert Cauwenberghs. “Real-time neuroimaging and cognitive monitoring using wearable dry EEG.” IEEE transactions on biomedical engineering 62, no. 11 (2015): 2553-2567.
[5] Jung, T.P., Makeig, S., Westerfield, M., Townsend, J., Courchesne, E. and Sejnowski, T.J., 2000. Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects. Clinical neurophysiology, 111(10), pp.1745-1758.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/optimizing-bereitschaftspotential-detection-using-signal-processing-techniques/