Human motor cortical gamma activity relates to GABAergic signalling and to behaviour

Gamma activity (γ, >30 Hz) is universally demonstrated across brain regions and species. However, the physiological basis and functional role of γ sub-bands (slow-γ, mid-γ, fast-γ) have been predominantly studied in rodent hippocampus; γ activity in the human neocortex is much less well understood. Here we combined neuroimaging and non-invasive brain stimulation to examine the properties of γ activity sub-bands in the primary motor cortex (M1), and their relationship to both local GABAergic activity and to motor learning. In 33 healthy individuals, we quantified movement-related γ activity in M1 using magnetoencephalography, assessed GABAergic signaling using transcranial magnetic stimulation (TMS), and estimated motor learning via a serial reaction time task. We characterised two distinct γ sub-bands (slow-γ, mid-γ) which show movement-related increase in activity during unilateral index finger movements and are characterised by distinct temporal-spectral-spatial profiles. Bayesian correlation analysis revealed strong evidence for a positive relationship between slow-γ (∼30-60Hz) peak frequency and endogenous GABA signalling during movement preparation (as assessed using the TMS-metric short interval intracortical inhibition). There was also moderate evidence for a relationship between power of the movement-related mid-γ activity (60-90Hz) and motor learning. These relationships were neurochemically- and frequency-specific. These data provide new insights into the neurophysiological basis and functional roles of γ activity in human M1 and allow the development of a new theoretical framework for γ activity in the human neocortex. Significance Statement Gamma (γ) activity is ubiquitous in the brain, yet our understanding of the mechanisms and function of γ activity in the human neocortex, and particularly in the human motor cortex, is limited. Using a multimodal approach, we characterised two patterns of movement-related γ activity in the human motor cortex (slow-γ and mid-γ), with different spatial, temporal and spectral properties. Slow-γ peak frequency was correlated to local GABA-A activity, whereas mid-gamma power predicted performance in a subsequent motor learning task. Based on these findings and previous research, we propose a theoretical framework to explain how human motor cortical γ activities may arise and their potential role in plasticity and motor learning, providing new hypotheses to be tested in future studies. Key Points ### Competing Interest Statement The authors have declared no competing interest.