Pharmacologically induced and stimulus evoked rhythmic neuronal oscillatory activity in the primary motor cortex in vitro

Yamawaki, Naoki; Stanford, Ian M.; Hall, Stephen D.; Woodhall, Gavin L.

doi:10.1016/j.neuroscience.2007.10.021

Cited by 170 publications

(174 citation statements)

References 49 publications

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“…This drive effectively turned on a transient bout of rhythmic spiking activity in the network over a 150-ms window. As in prior studies (22)(23)(24)(25), the network parameters were Table S3), as did the PK1 and PK5 troughs and the rising endpoints of the beta event waveform observed in the average human data (Fig. 1B).…”

Section: Detailed Neocortical Modeling Provides a Specific Explanatiomentioning

confidence: 79%

“…This mechanism may not account for beta at different recording scales or behavioral states [e.g., motor hold conditions (27,28) or up-states (47)] or in other brain networks, particularly those without spatially aligned PNs such as inhibitory networks in the striatum, where other mechanisms have been proposed (21). Prior modeling and experiments, primarily from slice recordings, have established that neocortical beta rhythms can emerge from the spiking interactions of local excitatory and inhibitory populations (22)(23)(24)(25)(26). Beta in the LFP of slice preparations, including those from somatosensory (22) and motor neocortex (24), operates in a similar 20-to 30-Hz range, dominated by the activity of layer V PNs.…”

Section: Discussionmentioning

confidence: 99%

“…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).…”

mentioning

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.

401

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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Section: Detailed Neocortical Modeling Provides a Specific Explanatiomentioning

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Section: Detailed Neocortical Modeling Provides a Specific Explanatiomentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

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.

401

510

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Practice changes beta power at rest and its modulation during movement in healthy subjects but not in patients with Parkinson's disease

et al. 2015

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Background PD (Parkinson's disease) is characterized by impairments in cortical plasticity, in beta frequency at rest and in beta power modulation during movement (i.e., event‐related ERS [synchronization] and ERD [desynchronization]). Recent results with experimental protocols inducing long‐term potentiation in healthy subjects suggest that cortical plasticity phenomena might be reflected by changes of beta power recorded with EEG during rest. Here, we determined whether motor practice produces changes in beta power at rest and during movements in both healthy subjects and patients with PD. We hypothesized that such changes would be reduced in PD.MethodsWe thus recorded EEG in patients with PD and age‐matched controls before, during and after a 40‐minute reaching task. We determined posttask changes of beta power at rest and assessed the progressive changes of beta ERD and ERS during the task over frontal and sensorimotor regions.ResultsWe found that beta ERS and ERD changed significantly with practice in controls but not in PD. In PD compared to controls, beta power at rest was greater over frontal sensors but posttask changes, like those during movements, were far less evident. In both groups, kinematic characteristics improved with practice; however, there was no correlation between such improvements and the changes in beta power.ConclusionsWe conclude that prolonged practice in a motor task produces use‐dependent modifications that are reflected in changes of beta power at rest and during movement. In PD, such changes are significantly reduced; such a reduction might represent, at least partially, impairment of cortical plasticity.

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Neuronal network pharmacodynamics of GABAergic modulation in the human cortex determined using pharmaco‐magnetoencephalography

Hall

Barnes

Furlong

et al. 2010

Human Brain Mapping

143

132

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Neuronal network oscillations are a unifying phenomenon in neuroscience research, with comparable measurements across scales and species. Cortical oscillations are of central importance in the characterization of neuronal network function in health and disease and are influential in effective drug development. Whilst animal in vitro and in vivo electrophysiology is able to characterize pharmacologically induced modulations in neuronal activity, present human counterparts have spatial and temporal limitations. Consequently, the potential applications for a human equivalent are extensive. Here, we demonstrate a novel implementation of contemporary neuroimaging methods called pharmaco-magnetoencephalography. This approach determines the spatial profile of neuronal network oscillatory power change across the cortex following drug administration and reconstructs the time course of these modulations at focal regions of interest. As a proof of concept, we characterize the nonspecific GABAergic modulator diazepam, which has a broad range of therapeutic applications. We demonstrate that diazepam variously modulates θ (4–7 Hz), α (7–14 Hz), β (15–25 Hz), and γ (30–80 Hz) frequency oscillations in specific regions of the cortex, with a pharmacodynamic profile consistent with that of drug uptake. We examine the relevance of these results with regard to the spatial and temporal observations from other modalities and the various therapeutic consequences of diazepam and discuss the potential applications of such an approach in terms of drug development and translational neuroscience. Hum Brain Mapp, 2010. © 2009 Wiley-Liss, Inc.

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Pharmacologically induced and stimulus evoked rhythmic neuronal oscillatory activity in the primary motor cortex in vitro

Cited by 170 publications

References 49 publications

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

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

Practice changes beta power at rest and its modulation during movement in healthy subjects but not in patients with Parkinson's disease

Neuronal network pharmacodynamics of GABAergic modulation in the human cortex determined using pharmaco‐magnetoencephalography

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