Physiological and harmonic components in neural and muscular coherence in Parkinsonian tremor Shouyan Wang a,b , Tipu Z. Aziz b , John F. Stein a , Peter G. Bain c , Xuguang Liu c, * a Department of Physiology, Anatomy, and Genetics, University of Oxford, Parks Road, Oxford OX1 3PT, UK b Department of Neurosurgery, Radcliffe Infirmary, Woodstock Road, Oxford OX2 6HE, UK c The Movement Disorders and Neurostimulation Unit, Department of Neuroscience, Charing Cross Hospital & Division of Neuroscience and Mental Health, Imperial College London, Fulham Palace Road, London W6 8RF,UK Accepted 29 March 2006 Abstract Objective: To differentiate physiological from harmonic components in coherence analysis of the tremor-related neural and muscular signals by comparing power, cross-power and coherence spectra. Methods: Influences of waveform, burst-width and additional noise on generating harmonic peaks in the power, cross-power and coherence spectra were studied using simulated signals. The local field potentials (LFPs) of the subthalamic nucleus (STN) and the EMGs of the contralateral forearm muscles in PD patients with rest tremor were analysed. Results: (1) Waveform had significant effect on generating harmonics; (2) noise significantly decreased the coherence values in a frequency- dependent fashion; and (3) cross-spectrum showed high resistance to harmonics. Among six examples of paired LFP–EMG signals, significant coherence appeared at the tremor frequency only, both the tremor and double tremor frequencies and the double-tremor frequency only. Conclusions: In coherence analysis of neural and muscular signals, distortion in waveform generates significant harmonic peaks in the coherence spectra and the coherence values of both physiological and harmonic components are modulated by extra noise or non-tremor related activity. Significance: The physiological or harmonic nature of a coherence peak at the double tremor frequency may be differentiated when the coherence spectra are compared with the power and in particular the cross-power spectra. q 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. Keywords: Local field potential; Electromyograms; Spectral analysis; Coherence; Harmonics; Tremor 1. Introduction The extensive networks in the central nervous system contributing to the generation of tremor have been a focus for neurophysiological study in both physiological and pathological tremor. One of the most common approaches is to physiologically detect the tremor related signals at different sites of the sensorimotor system, and the simultaneously recorded signals are subsequently analysed to reveal the functional interconnections among them so that a functionally linked network can be identified in spatial and temporal domains. There have been recent advances in physiological recording techniques such as magnetoence- phalography (MEG) (Halliday et al., 2000; Marsden et al., 2001a; Timmermann et al., 2003; Volkmann et al., 1996) and depth local field potentials (LFPs) (Brown, 2003; Liu et al., 2002; Marsden et al., 2000, 2001b) that have taken the field beyond conventional electroencephalograhpy (EEG) and electromyography (EMG) (Mima and Hallett, 1999). Recently, there are rapid developments in signal processing techniques such as coherence (Halliday et al., 1995, 2000; Clinical Neurophysiology 117 (2006) 1487–1498 www.elsevier.com/locate/clinph 1388-2457/$30.00 q 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2006.03.027 * Corresponding author. Address: The Movement Disorders and Neurostimulation Group, Division of Neurosciences and Mental Health, Department of Neuroscience, Imperial College London, Charing Cross Hospital, Fulham Palace Road, London W6 8RF, UK. Tel.: C44 2088467631; fax: C44 2083830663. E-mail address: x.liu@ic.ac.uk (X. Liu).