Local GABA concentration is related to network-level resting functional connectivity

Charlotte J Stagg,Stephen M Smith,Mark Woolrich,Christel A Gudberg,Cassandra Sampaio-Baptista,Velicia Bachtiar,Jacinta O’Shea,Ugwechi Amadi,Jamie Near,Andrei S Ilie,Nicola Filippini,Heidi Johansen-Berg

doi:10.7554/elife.01465

Charlotte J Stagg, Stephen M Smith + Show 10 more

Open Access

https://doi.org/10.7554/elife.01465

Copy DOI

Abstract

Anatomically plausible networks of functionally inter-connected regions have been reliably demonstrated at rest, although the neurochemical basis of these 'resting state networks' is not well understood. In this study, we combined magnetic resonance spectroscopy (MRS) and resting state fMRI and demonstrated an inverse relationship between levels of the inhibitory neurotransmitter GABA within the primary motor cortex (M1) and the strength of functional connectivity across the resting motor network. This relationship was both neurochemically and anatomically specific. We then went on to show that anodal transcranial direct current stimulation (tDCS), an intervention previously shown to decrease GABA levels within M1, increased resting motor network connectivity. We therefore suggest that network-level functional connectivity within the motor system is related to the degree of inhibition in M1, a major node within the motor network, a finding in line with converging evidence from both simulation and empirical studies. DOI: http://dx.doi.org/10.7554/eLife.01465.001.

Highlights

There has been a surge of recent interest in so-called ‘resting state networks’ (RSNs) in the human brain
If correlated activity spontaneously emerges through attractor dynamics in distant cortical regions, extent of these functional correlations should be best predicted by local GABA concentrations
MR Spectroscopy data were acquired from the hand region of left primary motor cortex (M1) and all neurochemicals of interest were expressed as a ratio to N-acetyl aspartate (NAA) (Stagg et al, 2009; see Figure 1 for representative spectra)

Summary

Introduction

There has been a surge of recent interest in so-called ‘resting state networks’ (RSNs) in the human brain. Recent simulation studies have predicted that patterns of local oscillatory activity can emerge spontaneously in a coherent fashion across large networks with specific connectional architectures (Cabral et al, 2011). Such local neuronal dynamics depend on neurochemical inhibitory tone, as shown, for example, by changes in local activity within the primary motor cortices (M1s) caused by pharmacological manipulations (Hall et al, 2011). If correlated activity spontaneously emerges through attractor dynamics in distant cortical regions, extent of these functional correlations should be best predicted by local GABA concentrations

Methods

Results

Conclusion