Epstein Secrets

al. 2003). Signals from each EEG electrode were decimated by a 149 factor of 5 (to 100 liz), then filtered with a zero-phase, 3rd order, band-pass Butterworth filter 150 (0.1 — 2 Hz) and normalized by subtracting their mean and dividing by their standard deviation 151 (Bradbeny et al. 2010). Kinematic d

ographic signals during tool use Conf Proc IEEE Eng Med Biol Soc; 5306:5309, 678 2008 679 25 EFTA_R1_02036222 EFTA02693143 680 Bradberry TJ, Rong F and Contreras-Vidal JL. Decoding center-out hand velocity from MEG 681 signals during visuomotor adaptation Neuroimage 47: 1691:1700, 2009a 682 6

mployed in this study has been previously described (Bradberry et a! 2010) so will only briefly be described here. First, a fourth-order, low-pass Butterworth filter with a cutoff frequency of I Hz was applied to the kinematic and EEG data. Very low frequencies have previously been shown to possess kinema

al J L 2010 Reconstructing three-dimensional hand movements from noninvasive electroencephalographic signals J. Neurosci. 30 31:2 7 Bradherry Ti, Rong F and Contreras-Vidal J L 2009 Decoding center-out hand velocity from MEG signals during visuomotor adaptation Neurointage 47 1691 700 Cisek P and K

t al. 2003). Signals from each EEG electrode were decimated by a 149 factor of 5 (to 100 Hz), then filtered with a zero-phase, 3rd order, band-pass Butterworth filter 150 (0.1 - 2 Hz) and normalized by subtracting their mean and dividing by their standard deviation 151 (Bradberry et al. 2010). Kinematic

7 magnetoencephalographic signals during tool use Conf Proe IEEE Eng Med Biol Soc; 5306:5309, 678 2008 679 25 EFTA00304392 680 Bradberry TJ, Rong F and Contreras-Vidal JL. Decoding center-out hand velocity from MEG 681 signals during visuomotor adaptation Netwoimage 47: 1691:1700, 2009a 682 6