On the human sensorimotor-cortex beta rhythm: Sources and modeling

Jensen, Ole; Goel, Prem K.; Kopell, Nancy; Pohja, Mikko; Hari, Riitta; Ermentrout, Bard

doi:10.1016/j.neuroimage.2005.02.008

Cited by 394 publications

(332 citation statements)

References 34 publications

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“…For example, it has been shown that gamma oscillations across the cortex are modulated by a variety of drug preparations, including a morphine-induced decrease in inhibition (38). Although studies in humans looking at changes in stimulusinduced visual gamma oscillations and their relationship to GABAergic compounds have yet to be performed, the GABAergic agonist diazepam has been shown to increase rolandic beta amplitude and decrease the frequency of oscillation measured using MEG (39). In terms of pharmacological studies, MEG provides added opportunities over MRS in that it is a time-resolved technique that could assess changes in oscillation frequency over relatively short periods of time (tens of…”

Section: Discussionmentioning

confidence: 99%

Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans

Muthukumaraswamy

Edden

Jones

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

529

490

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Functional imaging of the human brain is an increasingly important technique for clinical and cognitive neuroscience research, with functional MRI (fMRI) of the blood oxygen level-dependent (BOLD) response and electroencephalography or magnetoencephalography (MEG) recordings of neural oscillations being 2 of the most popular approaches. However, the neural and physiological mechanisms that generate these responses are only partially understood and sources of interparticipant variability in these measures are rarely investigated. Here, we test the hypothesis that the properties of these neuroimaging metrics are related to individual levels of cortical inhibition by combining magnetic resonance spectroscopy to quantify resting GABA concentration in the visual cortex, MEG to measure stimulus-induced visual gamma oscillations and fMRI to measure the BOLD response to a simple visual grating stimulus. Our results demonstrate that across individuals gamma oscillation frequency is positively correlated with resting GABA concentration in visual cortex (R ‫؍‬ 0.68; P < 0.02), BOLD magnitude is inversely correlated with resting GABA (R ‫؍‬ ؊0.64; P < 0.05) and that gamma oscillation frequency is strongly inversely correlated with the magnitude of the BOLD response (R ‫؍‬ ؊0.88; P < 0.001). Our results are therefore supportive of recent theories suggesting that these functional neuroimaging metrics are dependent on the excitation/inhibition balance in an individual's cortex and have important implications for the interpretation of functional imaging results, particularly when making between-group comparisons in clinical research.functional magnetic resonance imaging ͉ magnetic resonance spectroscopy ͉ magnetoencephalography ͉ oscillations T he high spatial resolution and noninvasive nature of blood oxygen level-dependent (BOLD) functional MRI (fMRI) (1) have led to it becoming one of the most popular tools for measuring brain function in human neuroscience. However, fMRI provides only an indirect measure of neural activity by measuring task-related changes in cerebral haemodynamics that are coupled by a complex and only partially understood mechanism to changes in underlying neural activity. Recent evidence suggests that oscillations in the gamma frequency range, loosely defined as approximately 30-100 Hz, are well correlated temporally, spatially, and functionally with haemodynamic changes in cortex, suggesting a close relationship with the BOLD response (2-6). There is also increasing evidence that the most plausible mechanism for the generation of gamma oscillations is a neuronal network containing a mixture of interconnected pyramidal cells and GABAergic inhibitory interneurons (7-10) with the balance of excitation-inhibition setting the peak gamma oscillation frequency of the network (11). Similarly, it has recently been argued that the magnitude of the BOLD response is also sensitive to this excitation-inhibition balance (12, 13).In the current study, we tested the hypothesis that the local level of inhibition in an i...

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Section: Discussionmentioning

confidence: 99%

Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans

Muthukumaraswamy

Edden

Jones

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

529

490

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“…Likewise, it is unclear whether the GABAergic influences on oscillatory dynamics are specific to visual areas or extend to other cortices. In sensorimotor regions, administration of a benzodiazepine GABA A positive allosteric modulator produced an alteration of the beta rhythm consisting of decreased frequency and increased amplitude [Jensen et al, 2005]. In other studies, no differences in gamma frequency were observed over motor regions using alcohol [Campbell et al, 2014], lorazepam [Lozano‐Soldevilla et al, 2014], ketamine [Shaw et al, 2015], or tiagabine [Muthukumaraswamy et al, 2013b].…”

Section: Discussionmentioning

confidence: 99%

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

Magazzini

Muthukumaraswamy

Campbell

et al. 2016

Human Brain Mapping

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The frequency of visual gamma oscillations is determined by both the neuronal excitation–inhibition balance and the time constants of GABAergic processes. The gamma peak frequency has been linked to sensory processing, cognitive function, cortical structure, and may have a genetic contribution. To disentangle the intricate relationship among these factors, accurate and reliable estimates of peak frequency are required. Here, a bootstrapping approach that provides estimates of peak frequency reliability, thereby increasing the robustness of the inferences made on this parameter was developed. The method using both simulated data and real data from two previous pharmacological MEG studies of visual gamma with alcohol and tiagabine was validated. In particular, the study by Muthukumaraswamy et al. [2013a] (Neuropsychopharmacology 38(6):1105–1112), in which GABAergic enhancement by tiagabine had previously demonstrated a null effect on visual gamma oscillations, contrasting with strong evidence from both animal models and very recent human studies was re‐evaluated. After improved peak frequency estimation and additional exclusion of unreliably measured data, it was found that the GABA reuptake inhibitor tiagabine did produce, as predicted, a marked decrease in visual gamma oscillation frequency. This result demonstrates the potential impact of objective approaches to data quality control, and provides additional translational evidence for the mechanisms of GABAergic transmission generating gamma oscillations in humans. Hum Brain Mapp 37:3882–3896, 2016. © 2016 Wiley Periodicals, Inc.

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“…In contrast, several prior studies have shown that the neocortex can generate beta rhythms locally from the spiking interactions of local cortical circuits. More specifically, prior in vitro experiments and models have established that networks of PNs and inhibitory neurons whose spiking is reciprocally coupled through fast excitation (AMPAergic) and inhibition (GABAergic) can produce beta rhythms, provided that the PNs contain a voltage-dependent M-type potassium current, which gates the rhythmic firing time of the cells to a beta period (22)(23)(24)(25).…”

Section: Detailed Neocortical Modeling Provides a Specific Explanatiomentioning

confidence: 99%

“…Consistent with the first view, beta has been robustly observed in LFP signals from basal ganglia nuclei including the subthalamic nucleus, striatum, and globus pallidus (18,19), and computational models have proposed mechanisms by which beta rhythms can emerge via interactions within and between these circuits (20, 21). Other studies have suggested that the neocortex itself has unique properties that generate beta rhythms through spike-mediated synaptic and electrical interactions within local circuits (22)(23)(24)(25) or that beta in early-sensory neocortical areas could be driven in a top-down manner from frontal cortex during attentive states (26).…”

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confidence: 99%

“…These findings make several predictions about optimal states for perceptual and motor performance and guide causal interventions to modulate beta for optimal function. beta rhythm | magnetoencephalography | computational modeling | sensorimotor processing | Parkinson's disease B eta band rhythms (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29) are a commonly observed activity pattern in the brain. They are found with magnetoencephalography (MEG) (1)(2)(3)(4), EEG (5,6), and local field potential (LFP) recordings from neocortex (7)(8)(9) and are preserved across species (10).…”

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confidence: 99%

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Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice

Sherman

Lee

Law

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

415

510

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Human neocortical 15-29-Hz beta oscillations are strong predictors of perceptual and motor performance. However, the mechanistic origin of beta in vivo is unknown, hindering understanding of its functional role. Combining human magnetoencephalography (MEG), computational modeling, and laminar recordings in animals, we present a new theory that accounts for the origin of spontaneous neocortical beta. In our MEG data, spontaneous beta activity from somatosensory and frontal cortex emerged as noncontinuous beta events typically lasting <150 ms with a stereotypical waveform. Computational modeling uniquely designed to infer the electrical currents underlying these signals showed that beta events could emerge from the integration of nearly synchronous bursts of excitatory synaptic drive targeting proximal and distal dendrites of pyramidal neurons, where the defining feature of a beta event was a strong distal drive that lasted one beta period (∼50 ms). This beta mechanism rigorously accounted for the beta event profiles; several other mechanisms did not. The spatial location of synaptic drive in the model to supragranular and infragranular layers was critical to the emergence of beta events and led to the prediction that beta events should be associated with a specific laminar current profile. Laminar recordings in somatosensory neocortex from anesthetized mice and awake monkeys supported these predictions, suggesting this beta mechanism is conserved across species and recording modalities. These findings make several predictions about optimal states for perceptual and motor performance and guide causal interventions to modulate beta for optimal function. beta rhythm | magnetoencephalography | computational modeling | sensorimotor processing | Parkinson's disease B eta band rhythms (15-29 Hz) are a commonly observed activity pattern in the brain. They are found with magnetoencephalography (MEG) (1-4), EEG (5, 6), and local field potential (LFP) recordings from neocortex (7-9) and are preserved across species (10). Local beta oscillations and their coordination between regions are implicated in numerous functions, including sensory perception, selective attention, and motor planning and initiation (2,3,6,7,9,(11)(12)(13)(14)(15). Neocortical beta oscillations are disrupted in various neuropathologies, most notably Parkinson's disease (PD), in which treatments that alleviate motor symptoms also reverse the neocortical beta disruption (16,17). Although associations between beta and performance suggest a crucial role in brain function, beta rhythmicity might not be important per se but instead may be an epiphenomenal consequence of other important processes. Discovering how beta emerges at the cellular and network levels is crucial to understanding why beta is such a clear predictor of performance in many domains.A major, unresolved point of debate concerns the locus of beta generation. One prominent view is that beta is generated in basal ganglia and thalamic structures and that neocortical beta is an entrained reflecti...

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On the human sensorimotor-cortex beta rhythm: Sources and modeling

Cited by 394 publications

References 34 publications

Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans

Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans

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

Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice

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