Multi-frequency phase locking in human somatosensory cortex

作者:Langdon Angela J*; Boonstra Tjeerd W; Breakspear Michael
来源:Progress in Biophysics and Molecular Biology, 2011, 105(1-2): 58-66.
DOI:10.1016/j.pbiomolbio.2010.09.015

摘要

Cortical population responses to sensory input arise from the interaction between external stimuli and the intrinsic dynamics of the densely interconnected neuronal population. Although there is a large body of knowledge regarding single neuron responses to periodic stimuli, responses at the scale of cortical populations are incompletely understood. The characteristics of large-scale neuronal activity during periodic stimulation speak directly to the mechanisms underlying collective neuronal activity. Their accurate elucidation is hence a vital prelude to constructing and evaluating large-scale computational and biophysical models of the brain. Electroencephalographic data was recorded from eight human subjects while periodic vibrotactile stimuli were applied to the fingertip. Time frequency decomposition was performed on the multi-channel data in order to investigate relative changes in the power and phase distributions at stimulus-related frequencies. We observed phase locked oscillatory activity at multiple stimulus-specific frequencies, in particular at ratios of 1:1, 2:1 and 2:3 to the stimulus frequency. These phase locked components were found to be modulated differently across the range of stimulus frequencies, with oscillatory responses most robustly sustained around 30 Hz. In contrast, no robust frequency-locked responses were apparent in the power changes. These results demonstrate n:m phase synchronization between cortical oscillations in the somatosensory system and an external periodic signal. We argue that neuronal populations evidence a collective nonlinear response to periodic sensory input. The existence of n:m phase synchronization demonstrates the contribution of intrinsic cortical dynamics to stimulus encoding and provides a novel phenomenological criteria for the validation of large-scale models of the brain.