Gamma oscillations in V1 are correlated with GABAA receptor density: A multi-modal MEG and Flumazenil-PET study

Abstract

High-frequency oscillations in the gamma-band reflect rhythmic synchronization of spike timing in active neural networks. The modulation of gamma oscillations is a widely established mechanism in a variety of neurobiological processes, yet its neurochemical basis is not fully understood. Modeling, in-vitro and in-vivo animal studies suggest that gamma oscillation properties depend on GABAergic inhibition. In humans, search for evidence linking total GABA concentration to gamma oscillations has led to promising -but also to partly diverging- observations. Here, we provide the first evidence of a direct relationship between the density of GABAA receptors and gamma oscillatory gamma responses in human primary visual cortex (V1). By combining Flumazenil-PET (to measure resting-levels of GABAA receptor density) and MEG (to measure visually-induced gamma oscillations), we found that GABAA receptor densities correlated positively with the frequency and negatively with amplitude of visually-induced gamma oscillations in V1. Our findings demonstrate that gamma-band response profiles of primary visual cortex across healthy individuals are shaped by GABAA-receptor-mediated inhibitory neurotransmission. These results bridge the gap with in-vitro and animal studies and may have future clinical implications given that altered GABAergic function, including dysregulation of GABAA receptors, has been related to psychiatric disorders including schizophrenia and depression.

Significant reductions in human visual gamma frequency by the gaba reuptake inhibitor tiagabine revealed by robust peak frequency estimation

“…The latter measure has been proposed as an index of local GABA concentration [Muthukumaraswamy et al, 2009] and GABA A receptor density [Kujala et al, 2015], two factors that could potentially influence the variability of our peak frequency reliability estimates. We used Pearson's r coefficient to correlate peak gamma frequency, in each experimental session, with peak frequency reliability, as measured by the percentage of bootstrap iterations within ±1.2 Hz of the bootstrap distribution mode.…”

“…Cousijn et al, 2014; Muthukumaraswamy et al, 2009]. Invigorating this debate, a very recent flumazenil‐positron emission tomography (PET) study demonstrated a positive correlation between the frequency of visually induced gamma oscillations and the density of GABA A receptors in early visual areas [Kujala et al, 2015]. Further contribution to the translation of animal models to humans has come from studies combining MEG, to record cortical activity, with the use of pharmacological agents, to modulate neurotransmission [Hall et al, 2010; Muthukumaraswamy, 2014].…”

“…Although inter‐individual differences in visual gamma frequency have been related to the structural properties of visual cortical areas [e.g., Muthukumaraswamy et al, 2010; Schwarzkopf et al, 2012], other studies do not show a clear dependence [c.f. Kujala et al, 2015; Robson et al, 2015]. Gamma frequency in visual cortex is modulated by sensory input strength, increasing monotonically with respect to stimulus contrast [Perry, 2015; Perry et al, 2015; Ray and Maunsell, 2010].…”

Neuromagnetic investigations of mechanisms and effects of STN-DBS and medication in Parkinson's disease

“…However, it is still difficult to fully interpret many of the obtained measures due to the complexity of the underlying neural sources. In this respect, multimodal approaches combining MEG (or EEG) with imaging of the dopamine or GABA neurotransmitter systems (using PET) may help improve our interpretation of the observed changes in oscillatory dynamics (Muthukumaraswamy et al, 2013;Kujala et al, 2015). While we found in our studies that DBS and medication affected cortical gamma oscillations, their functional and behavioral implications are not easily discernable.…”

“…While we found in our studies that DBS and medication affected cortical gamma oscillations, their functional and behavioral implications are not easily discernable. Hence, combining MEG experimentation similar to the one adopted in this thesis with behavioral measures as well as imaging techniques mapping out relevant details on relevant neuroreceptors, such as GABA receptor density (Kujala et al, 2015), may improve the neurophysiological basis for interpreting our current results, and thus our understanding of the impact of treatments on particular neuronal elements, and their relation to behavioral effects and the possible underlying mechanisms.…”