Oscillations in neural activity play a critical role in neural computation and communication. There is intriguing new evidence that the nonsinusoidal features of the oscillatory waveforms may inform underlying physiological and pathophysiological characteristics. Time-domain waveform analysis approaches stand in contrast to traditional Fourier-based methods, which alter or destroy subtle waveform features. Recently it has been shown that the waveform features of oscillatory beta (13-30 Hz) events—a prominent motor cortical oscillation—may reflect near-synchronous excitatory synaptic inputs onto cortical pyramidal neurons. Here we analyze data from invasive human primary motor cortex (M1) recordings from patients with Parkinson's disease (PD) implanted with a deep brain stimulator (DBS) to test the hypothesis that the beta waveform becomes less sharp with DBS, suggesting that M1 input synchrony may be decreased. We find that, in PD, M1 beta oscillations have sharp, asymmetric, nonsinusoidal features, specifically asymmetries in the ratio between the sharpness of the beta peaks compared to the troughs. This waveform feature is nearly perfectly correlated with beta-high gamma phase-amplitude coupling (r = 0.94)—a neural index previously shown to track PD-related motor deficit. Our results suggest that the pathophysiological beta generator is altered by DBS, smoothing out the beta waveform. This has implications not only for the interpretation of the physiological mechanism by which DBS reduces PD-related motor symptoms, but more broadly for our analytic toolkit in general. That is, the often-overlooked time-domain features of oscillatory waveforms may carry critical physiological information about neural processes and dynamics.
To better understand the neural basis of cognition and disease we need to understand how groups of neurons interact to communicate with one another. For example, there is evidence that parkinsonian bradykinesia and rigidity may arise from an oversynchronization of afferents to the motor cortex, and that these symptoms are treatable using deep brain stimulation (DBS). Here we show that the waveform shape of beta (13-30 Hz) oscillations, which may reflect input synchrony onto the cortex, is altered by DBS. This suggests that mechanistic inferences regarding physiological and pathophysiological neural communication may be made from the temporal dynamics of oscillatory waveform shape.
The authors declare that no competing financial interests.
We thank T. Donoghue, R. Gao, T. Noto, B. Postle, T. Tran, and A. Watrous for invaluable discussion and comments. S.R.C. is supported by the National Science Foundation Graduate Research Fellowship Program. B.V. is supported by the University of California, San Diego, Qualcomm Institute, California Institute for Telecommunications and Information Technology, Strategic Research Opportunities Program, and a Sloan Research Fellowship. B.V. and R.v.d.M. are further supported by US National Institutes of Health grant NIH MH095984 to B.R. Postle. Data collection by P.A.S. and C.d.H. was supported by a grant from the Michael J. Fox foundation and by US National Institutes of Health grant R01 NS069779.; S.R.C. performed the research, S.R.C., E.J.P., R.v.d.M. and B.V. designed the research, C.d.H. and P.A.S designed and performed the original PD study; all authors wrote the paper.