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...

Beta oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of healthy and abnormal behaviors, including perception, attention and motor action. In non-averaged signals, beta can emerge as transient high-power 'events'. As such, functionally relevant differences in averaged power across time and trials can reflect changes in event number, power, duration, and/or frequency span. We show that functionally relevant differences in averaged beta power in primary somatosensory neocortex reflect a difference in the number of high-power beta events per trial, i.e. event rate. Further, beta events occurring close to the stimulus were more likely to impair perception. These results are consistent across detection and attention tasks in human magnetoencephalography, and in local field potentials from mice performing a detection task. These results imply that an increased propensity of beta events predicts the failure to effectively transmit information through specific neocortical representations.

BackgroundBrain-machine interfaces (BMIs) involving electrodes implanted into the human cerebral cortex have recently been developed in an attempt to restore function to profoundly paralyzed individuals. Current BMIs for restoring communication can provide important capabilities via a typing process, but unfortunately they are only capable of slow communication rates. In the current study we use a novel approach to speech restoration in which we decode continuous auditory parameters for a real-time speech synthesizer from neuronal activity in motor cortex during attempted speech.Methodology/Principal FindingsNeural signals recorded by a Neurotrophic Electrode implanted in a speech-related region of the left precentral gyrus of a human volunteer suffering from locked-in syndrome, characterized by near-total paralysis with spared cognition, were transmitted wirelessly across the scalp and used to drive a speech synthesizer. A Kalman filter-based decoder translated the neural signals generated during attempted speech into continuous parameters for controlling a synthesizer that provided immediate (within 50 ms) auditory feedback of the decoded sound. Accuracy of the volunteer's vowel productions with the synthesizer improved quickly with practice, with a 25% improvement in average hit rate (from 45% to 70%) and 46% decrease in average endpoint error from the first to the last block of a three-vowel task.Conclusions/SignificanceOur results support the feasibility of neural prostheses that may have the potential to provide near-conversational synthetic speech output for individuals with severely impaired speech motor control. They also provide an initial glimpse into the functional properties of neurons in speech motor cortical areas.

BackgroundBioelectric gradients among all cells, not just within excitable nerve and muscle, play instructive roles in developmental and regenerative pattern formation. Plasma membrane resting potential gradients regulate cell behaviors by regulating downstream transcriptional and epigenetic events. Unlike neurons, which fire rapidly and typically return to the same polarized state, developmental bioelectric signaling involves many cell types stably maintaining various levels of resting potential during morphogenetic events. It is important to begin to quantitatively model the stability of bioelectric states in cells, to understand computation and pattern maintenance during regeneration and remodeling.MethodTo facilitate the analysis of endogenous bioelectric signaling and the exploitation of voltage-based cellular controls in synthetic bioengineering applications, we sought to understand the conditions under which somatic cells can stably maintain distinct resting potential values (a type of state memory). Using the Channelpedia ion channel database, we generated an array of amphibian oocyte and mammalian membrane models for voltage evolution. These models were analyzed and searched, by simulation, for a simple dynamical property, multistability, which forms a type of voltage memory.ResultsWe find that typical mammalian models and amphibian oocyte models exhibit bistability when expressing different ion channel subsets, with either persistent sodium or inward-rectifying potassium, respectively, playing a facilitative role in bistable memory formation. We illustrate this difference using fast sodium channel dynamics for which a comprehensive theory exists, where the same model exhibits bistability under mammalian conditions but not amphibian conditions. In amphibians, potassium channels from the Kv1.x and Kv2.x families tend to disrupt this bistable memory formation. We also identify some common principles under which physiological memory emerges, which suggest specific strategies for implementing memories in bioengineering contexts.ConclusionOur results reveal conditions under which cells can stably maintain one of several resting voltage potential values. These models suggest testable predictions for experiments in developmental bioelectricity, and illustrate how cells can be used as versatile physiological memory elements in synthetic biology, and unconventional computation contexts.Electronic supplementary materialThe online version of this article (doi:10.1186/s12976-015-0019-9) contains supplementary material, which is available to authorized users.

Transient neocortical events with high spectral power in the 15–29 Hz beta band are among the most reliable predictors of sensory perception. Prestimulus beta event rates in primary somatosensory cortex correlate with sensory suppression, most effectively 100–300 ms before stimulus onset. However, the neural mechanisms underlying this perceptual association are unknown. We combined human magnetoencephalography (MEG) measurements with biophysical neural modeling to test potential cellular and circuit mechanisms that underlie observed correlations between prestimulus beta events and tactile detection. Extending prior studies, we found that simulated bursts from higher-order, nonlemniscal thalamus were sufficient to drive beta event generation and to recruit slow supragranular inhibition acting on a 300 ms timescale to suppress sensory information. Further analysis showed that the same beta-generating mechanism can lead to facilitated perception for a brief period when beta events occur simultaneously with tactile stimulation before inhibition is recruited. These findings were supported by close agreement between model-derived predictions and empirical MEG data. The postevent suppressive mechanism explains an array of studies that associate beta with decreased processing, whereas the during-event facilitatory mechanism may demand a reinterpretation of the role of beta events in the context of coincident timing.

Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key non-rapid eye movement (NREM) sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 72 schizophrenia (SCZ) patients and 58 controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that fast and slow spindle properties were largely uncorrelated. We also describe a novel measure of slow oscillation and spindle interaction that was attenuated in SCZ. The main sleep findings were replicated in a demographically distinct sample, and a joint model, based on multiple NREM components, statistically predicted disease status in the replication cohort. Although also altered in patients, auditory event-related potentials elicited during wake were unrelated to NREM metrics. Consistent with a growing literature implicating thalamocortical dysfunction in SCZ, our characterization identifies independent NREM and wake EEG biomarkers that may index distinct aspects of SCZ pathophysiology and point to multiple neural mechanisms underlying disease heterogeneity. This study lays the groundwork for evaluating these neurophysiological markers, individually or in combination, to guide efforts at treatment and prevention as well as identifying individuals most likely to benefit from specific interventions.

Beta frequency oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of many healthy and abnormal behaviors, including perception, attention and motor action. Recent evidence shows that in non-averaged signals, beta can emerge as transient high-power "events". As such, functionally relevant differences in averaged power across time and trials can reflect accumulated changes in the number, power, duration, and/or frequency span of the events. We show for the first time that functionally relevant differences in averaged prestimulus beta power in human sensory neocortex reflects a difference in the number of high-power beta events per trial, i.e., the rate of events. Further, high power beta events close to the time of the stimulus were more likely to impair perception. This result is consistent across detection and attention tasks in human magnetoencephalography (MEG) and is conserved in local field potential (LFP) recordings of mice performing a detection task. Our findings suggest transient brain rhythms are best viewed as a "rate metric" in their impact on function, and provides a new framework for understanding and manipulating functionally relevant rhythmic events.

Transient neocortical events with high spectral power in the 15-29Hz beta band are among the most reliable predictors of sensory perception: High prestimulus beta event rates in primary somatosensory lead to sensory suppression, most effective at 100-300ms prestimulus latency. However, the synaptic and neuronal mechanisms inducing beta's perceptual effects have not been completely localized. We combined human MEG with neural modeling designed to account for these macroscale signals to interpret the cellular and circuit mechanisms that underlie the influence of beta on tactile detection. Extending prior studies, we modeled the hypothesis that higher-order thalamic bursts, sufficient for beta event generation in cortex, recruit supragranular GABAB inhibition acting on a 300ms time scale to suppress sensory information. Consistency between model and MEG data supported this hypothesis and led to a further prediction, validated in our data, that stimuli are perceived when beta events occur simultaneously with tactile stimulation. The post-event suppressive mechanism explains an array of studies that associate beta with decreased processing, while the during-event mechanism may demand a reinterpretation of the role of beta events in the context of coincident timing. Significance statementSomatosensory beta events -transient 15-29Hz oscillations in electromagnetic recordings -are thought to be generated when "top-down" bursts of spikes presumably originating in higher-order thalamus arrive in upper layers of somatosensory cortex. Physiological evidence had shown that the immediate action of these top-down projections should be excitatory; however, after a beta event, sensory perception is noticeably inhibited for approximately 300ms. The source of this post-event sensory suppression, in particular, had been unresolved. Using a detailed computational model of somatosensory cortex, we find evidence for the hypothesis that these bursts couple indirectly to GABAB inhibition in upper layers of cortex, and that beta events first briefly disinhibit sensory relay before a longer period of inhibition. * Here, we use "event" rather than "burst" so as not to confuse events with their mechanistic generators, which we believe to be bursts in upstream sources. Our interpretation of events is as "sequences of bursts", viz. "bursts of bursts" where the length of the sequence can be as low as one.