 the periodic features of neural time series data, such as local field potentials, LFPs, can be quantified by calculating their power spectrum. This power spectrum is typically discounted, but recent research suggests that it may contain information about the excitatory inhibitory balance of neuronal populations. In this study, the authors tested this hypothesis in the context of experimental and idiopathic Parkinson's disease. They found that the power spectrum of the subthalamic nucleus, STN, LFPs in dopamine-depleted rats reflected changes in basal ganglia network activity which were associated with different levels of STN neuron firing and a balance between excitation and inhibition. The same relationship was observed in Parkinson's patients where higher power spectrum exponents corresponded to increased inhibition and decreased excitability of the STN. Furthermore, these findings were consistent with the effects of deep brain stimulation, DBS, on Parkinson's patients, suggesting that the power spectrum of STN LFPs could be used as a biomarker for adaptive DBS. This article was authored by Christoph Wiest, Flavie Torosillos, Alec Pagossian, and others.