Results demonstrate that GABA concentration can be successfully resolved from cortical motor areas and, as hypothesized, that motor cortex GABA is associated with specific aspects of motor cortex beta and gamma oscillations. More specifically, recent studies have shown that MEG measures of VI gamma activity are associated with GABA concentration (Muthukumaraswamy et al., 2009
), and based on these previous findings, we hypothesized that motor cortex GABA levels would correlate positively with motor cortex gamma frequency . Although MI cortical gamma responses differ from VI gamma responses in many respects (e.g., method of activation, duration, bandwidth, etc.), -like VI gamma oscillations, present findings show that the frequency
of MI gamma varies with in vivo
MI GABA concentration. Present results thus suggest a common GABA-related mechanism governing VI and MI gamma networks.
The literature provides some information about the properties of these networks. Neural network models based on hippocampus CA1 field-potential recordings suggest that the synaptic release of GABA generates inhibitory postsynaptic potentials (IPSPs) that briefly and rhythmically attenuate random axonal activity. This attenuation modulates excitatory inputs and thus promotes the gamma field oscillation (Traub et al., 2003
). In the case of MI gamma, these modulating signals may arise briefly in relation to movement initiated proprioceptive signals (Muthukumaraswamy, 2010
), or possibly from sub-cortical structures such as the sub-thalamic nucleus, also known to exhibit coherent gamma bursts in relation to transient movement (Lalo et al., 2008
As shown in , the peak MRGS frequency was inversely correlated with age. A previous developmental MEG study (Gaetz et al., 2010
) compared MRGS across healthy controls from three age groups (4-6 yrs, 11-13 yrs, and Adults), and observed no group MRGS frequency differences. Given the Gaetz et al. (2010)
finding, the present observation of a significant relation between age and MRGS frequency (p
= 0.03) is somewhat surprising. Post hoc analysis of the previously published findings (Gaetz et al., 2010
), however, did show the same pattern of decreased MRGS with increasing age, but only in the adult group. The above argues for the possibility of a non-linear relation of MRGS frequency and age over the lifespan. Overall, larger N studies are needed to assess the degree to which age predicts MI GABA concentration and MRGS frequency over the lifespan.
A marginally significant negative correlation of GABA/NAA decrease with increasing age was also observed. A small number of studies have noted similar relationships. For example, a plastic down-regulation of normal adult inhibitory GABA neurotransmission has long been reported in the rat auditory system (Caspary et al., 1999
; Ling et al., 2005
), and in humans, region specific in vivo GABA decreases as a function of age have also been reported (Grachev and Apkarian, 2001
). A weakness of the present study is that GABA measures were obtained from only a single MRS voxel. Future studies examining associations between GABA concentration and gamma cortical oscillations from additional ROI locations are needed to determine whether the age associations observed in the present study are system specific or a ubiquitous feature of the aging brain.
With regard to beta activity, present results provide support for the theory that post-movement “beta rebound” represents a period of GABAergic inhibition. Numerous studies have observed a transient increase in MI beta amplitude following transient motor movements (Jurkiewicz et al., 2006
) and transient tactile stimulation (Gaetz and Cheyne, 2006
). This post-movement/stimulus rebound in beta amplitude has been associated with a state of reduced
motor cortex excitability. For example, Chen et al. (Chen et al., 1999
) reported decreased Motor Evoked Potential (MEPs) amplitudes from an intrinsic hand muscle when stimulating the contralateral MI with transcranial magnetic stimulation (TMS) during a period of post-stimulus beta synchrony. Although this inferred period of beta synchrony was not due to movement per se, the report of decreased MI excitability during a period known to be associated with increased beta synchrony is important – especially as GABA is the leading candidate signal for MI inhibition and known through pharmacology studies to directly augment beta power (Hall et al., 2010
; Jensen et al., 2005
; Wanquier, 1998
). Early reports of PMBR in the MEG literature (Pfurtscheller and Neuper, 1997
; Salmelin et al., 1995
) have speculated that this rebound period represents a time of increased motor inhibition. Findings from the present study, the first to show associations between in vivo
GABA concentration with beta rebound amplitude, support the hypothesis that PMBR is associated with GABAergic inhibition. Additional studies are needed to replicate these novel findings. In addition, the current study compared resting
GABA concentration with beta and gamma band measures obtained using a simple motor task. The relationship between GABA and resting-state
cortical oscillations (from MI and other cortical locations) is also an interesting topic for future studies.
Present findings suggest a common GABAergic mechanism underlying gamma and beta oscillations. The blockade of motor cortical beta oscillations by the gap-junction inhibitor carbenoxolone has been observed (Yamawaki et al., 2008
). These data suggest that the mechanism underlying beta oscillations in layer V of MI is similar to that mediating gamma oscillations via GABAergic output at the level of gap-junction connections at the axonal plexus (Traub et al., 2003
). Although similar in this respect, Yamawaki et al., (2008)
has shown that, unlike gamma cortical oscillations, excitatory synaptic drive is not neededfor MI beta oscillatory activity to occur (Yamawaki et al., 2008
). The present study has also shown that proximal but spatially distinct regions of MI cortex can exhibit different oscillatory frequencies. Whether these rhythms arise from different interneuronal groups or whether a single interneuron can participate in the generation of multiple rhythms simultaneously remains an interesting question for future research.
In the current study, PMBR was observed to be highest (greatest % change) in participants with relatively high MI GABA levels (see ). This finding is supported indirectly by recent observations where Autistic adult participants were shown to exhibit significantly reduced PMBR in an action observation task (Honaga et al., 2010
). Moreover, children with Autism have been shown to exhibit less GABA from motor / frontal lobe ROIs than age matched controls (Harada et al., 2010
) . Together, these findings help strengthen the inferred relation between GABA and PMBR and provide a clear prediction for GABA/PMBR studies involving clinical populations where GABA downregulation may be implicated (such as Autism, Schizophrenia and Epilepsy).
In conclusion, present findings show that non-invasive multimodal imaging can assess associations between brain oscillations and brain chemistry. It is hoped that continued work in this area will led to a better understanding of the mechanisms influencing the generation and modulation of endogenous and exogenous rhythmic brain activity. Such insights may help explain the underlying functional mechanisms as they relate to normal development of the motor system. It is also likely that work in this area will provide insight to the neural mechanisms underlying the abnormal oscillatory activity frequently observed patient populations (e.g., schizophrenia and autism), with work in this area helping to create treatments that targets very specific neurotransmitters and, by extension, specific cortical network abnormalities in these patient populations.