We observed robust coupling between the high-and low-frequency bands of ongoing electrical activity in the human brain. In particular, the phase of the low-frequency theta (4 to 8 hertz) rhythm modulates power in the high gamma (80 to 150 hertz) band of the electrocorticogram, with stronger modulation occurring at higher theta amplitudes. Furthermore, different behavioral tasks evoke distinct patterns of theta/high gamma coupling across the cortex. The results indicate that transient coupling between low-and high-frequency brain rhythms coordinates activity in distributed cortical areas, providing a mechanism for effective communication during cognitive processing in humans.Neuronal oscillations facilitate synaptic plasticity (1), influence reaction time (2), correlate with attention (3) and perceptual binding (4), and are proposed to play a role in transient, longrange coordination of distinct brain regions (5). Direct cortical recordings reveal that ongoing rhythms encompass a wide range of spatial and temporal scales-ultraslow rhythms less than 0.05 Hz coexist with fast transient oscillations 500 Hz or greater (1), with spatial coherence between these oscillations extending from several centimeters for the corticospinal tract (6) to the micrometer scale for subthreshold membrane oscillations in a single neuron (7). Exactly how these transient oscillations influence each other and coordinate processing at both the single-neuron and population levels remains unknown.Evidence for cross-frequency coupling, where one frequency band modulates the activity of a different frequency band, is more abundant in animal than human data. For example, the theta rhythm can modulate the firing rate and spike timing of a single neuron (8-11) as well as the gamma power of the intracortical local field potential (8,12,13). Task-related changes in theta power have been observed in humans (14-16), and cross-frequency coupling at frequencies up to 40 Hz has been detected at the scalp (17,18). However, given the difficulty in localizing electrical sources from scalp recordings alone (19), subdural electrodes that record directly from the human cortex are needed to address this question. Furthermore, subdural electrodes are ideal for studying activity in the recently described human high gamma band (HG) at 80 to 150 Hz. HG activity is modulated by sensory, motor, and cognitive events (20), is

Recent studies suggest that cross-frequency coupling (CFC) may serve a functional role in neuronal computation, communication, and learning. In particular, the strength of phase-amplitude CFC differs across brain areas in a task-relevant manner, changes quickly in response to sensory, motor, and cognitive events, and correlates with performance in learning tasks. Importantly, while high-frequency brain activity reflects local domains of cortical processing, low-frequency brain rhythms are dynamically entrained across distributed brain regions by both external sensory input and internal cognitive events. CFC may thus serve as a mechanism to transfer information from large-scale brain networks operating at behavioral timescales to the fast, local cortical processing required for effective computation and synaptic modification, thus integrating functional systems across multiple spatiotemporal scales.

Inappropriate response tendencies may be stopped via a specific fronto/basal ganglia/primary motor cortical network. We sought to characterize the functional role of two regions in this putative stopping network, the right inferior frontal gyrus (IFG) and the primary motor cortex (M1), using electocorticography from subdural electrodes in four patients while they performed a stop-signal task. On each trial, a motor response was initiated, and on a minority of trials a stop signal instructed the patient to try to stop the response. For each patient, there was a greater right IFG response in the beta frequency band (ϳ16 Hz) for successful versus unsuccessful stop trials. This finding adds to evidence for a functional network for stopping because changes in beta frequency activity have also been observed in the basal ganglia in association with behavioral stopping. In addition, the right IFG response occurred 100 -250 ms after the stop signal, a time range consistent with a putative inhibitory control process rather than with stop-signal processing or feedback regarding success. A downstream target of inhibitory control is M1. In each patient, there was alpha/beta band desynchronization in M1 for stop trials. However, the degree of desynchronization in M1 was less for successfully than unsuccessfully stopped trials. This reduced desynchronization on successful stop trials could relate to increased GABA inhibition in M1. Together with other findings, the results suggest that behavioral stopping is implemented via synchronized activity in the beta frequency band in a right IFG/basal ganglia network, with downstream effects on M1.

The phase of ongoing theta (4–8 Hz) and alpha (8–12 Hz) electrophysiological oscillations is coupled to high gamma (80–150 Hz) amplitude, which suggests that low-frequency oscillations modulate local cortical activity. While this phase–amplitude coupling (PAC) has been demonstrated in a variety of tasks and cortical regions, it has not been shown whether task demands differentially affect the regional distribution of the preferred low-frequency coupling to high gamma. To address this issue we investigated multiple-rhythm theta/alpha to high gamma PAC in two subjects with implanted subdural electrocorticographic grids. We show that high gamma amplitude couples to the theta and alpha troughs and demonstrate that, during visual tasks, alpha/high gamma coupling preferentially increases in visual cortical regions. These results suggest that low-frequency phase to high-frequency amplitude coupling is modulated by behavioral task and may reflect a mechanism for selection between communicating neuronal networks.

The spatiotemporal dynamics of cortical oscillations across human brain regions remain poorly understood because of a lack of adequately validated methods for reconstructing such activity from noninvasive electrophysiological data. In this paper, we present a novel adaptive spatial filtering algorithm optimized for robust source time-frequency reconstruction from magnetoencephalography (MEG) and electroencephalography (EEG) data. The efficacy of the method is demonstrated with simulated sources and is also applied to real MEG data from a self-paced finger movement task. The algorithm reliably reveals modulations both in the beta band (12-30 Hz) and high gamma band (65-90 Hz) in sensorimotor cortex. The performance is validated by both across-subjects statistical comparisons and by intracranial electrocorticography (ECoG) data from two epilepsy patients. Interestingly, we also reliably observed high frequency activity (30-300 Hz) in the cerebellum, though with variable locations and frequencies across subjects. The proposed algorithm is highly parallelizable and runs efficiently on modern high performance computing clusters. This method enables the ultimate promise of MEG and EEG for five-dimensional imaging of space, time, and frequency activity in the brain and renders it applicable for widespread studies of human cortical dynamics during cognition.

Hebb proposed that neuronal cell assemblies are critical for effective perception, cognition, and action. However, evidence for brain mechanisms that coordinate multiple coactive assemblies remains lacking. Neuronal oscillations have been suggested as one possible mechanism for cell assembly coordination. Prior studies have shown that spike timing depends upon local field potential (LFP) phase proximal to the cell body, but few studies have examined the dependence of spiking on distal LFP phases in other brain areas far from the neuron or the influence of LFP-LFP phase coupling between distal areas on spiking. We investigated these interactions by recording LFPs and single-unit activity using multiple microelectrode arrays in several brain areas and then used a unique probabilistic multivariate phase distribution to model the dependence of spike timing on the full pattern of proximal LFP phases, distal LFP phases, and LFP-LFP phase coupling between electrodes. Here we show that spiking activity in single neurons and neuronal ensembles depends on dynamic patterns of oscillatory phase coupling between multiple brain areas, in addition to the effects of proximal LFP phase. Neurons that prefer similar patterns of phase coupling exhibit similar changes in spike rates, whereas neurons with different preferences show divergent responses, providing a basic mechanism to bind different neurons together into coordinated cell assemblies. Surprisingly, phasecoupling-based rate correlations are independent of interneuron distance. Phase-coupling preferences correlate with behavior and neural function and remain stable over multiple days. These findings suggest that neuronal oscillations enable selective and dynamic control of distributed functional cell assemblies.neuronal oscillations | neuronal ensembles | spike timing | local field potentials | brain rhythms S ignificant progress has been made in understanding the dynamics and response properties of single nerve cells (1, 2) and how they interconnect to form cortical microcircuits (3, 4). More than 60 y ago, however, Donald Hebb hypothesized that the fundamental unit of brain operation is not the single neuron but rather the cell assembly-an anatomically dispersed but functionally integrated ensemble of neurons (5). The individual neurons that compose an assembly may reside in widely separated brain areas but act as a single functional unit through coordinated network activity. Dynamic interactions between multiple assemblies may then give rise to the large-scale functional networks found in mammalian brains (6-8). Despite the theoretical appeal of Hebb's idea (9) and growing empirical evidence of assemblies (10-12), it remains unclear how diverse groups of neurons spanning several cortical regions transiently coordinate their activity to form cell assemblies or how multiple coactive assemblies regulate their interactions to form larger functional networks.Brain rhythms may play a key role in coordinating neuronal ensembles (13-15), with a dynamic hierarchy of neuronal osc...

One hundred and fifty years of neurolinguistic research has identified the key structures in the human brain that support language. However, neither the classic neuropsychological approaches introduced by Broca (1861) and Wernicke (1874), nor modern neuroimaging employing PET and fMRI has been able to delineate the temporal flow of language processing in the human brain. We recorded the electrocorticogram (ECoG) from indwelling electrodes over left hemisphere language cortices during two common language tasks, verb generation and picture naming. We observed that the very high frequencies of the ECoG (high-gamma, 70-160 Hz) track language processing with spatial and temporal precision. Serial progression of activations is seen at a larger timescale, showing distinct stages of perception, semantic association/selection, and speech production. Within the areas supporting each of these larger processing stages, parallel (or "incremental") processing is observed. In addition to the traditional posterior vs. anterior localization for speech perception vs. production, we provide novel evidence for the role of premotor cortex in speech perception and of Wernicke's and surrounding cortex in speech production. The data are discussed with regards to current leading models of speech perception and production, and a "dual ventral stream" hybrid of leading speech perception models is given.

We examined the spatiotemporal dynamics of word processing by recording the electrocorticogram (ECoG) from the lateral frontotemporal cortex of neurosurgical patients chronically implanted with subdural electrode grids. Subjects engaged in a target detection task where proper names served as infrequent targets embedded in a stream of task-irrelevant verbs and nonwords. Verbs described actions related to the hand (e.g, throw) or mouth (e.g., blow), while unintelligible nonwords were sounds which matched the verbs in duration, intensity, temporal modulation, and power spectrum. Complex oscillatory dynamics were observed in the delta, theta, alpha, beta, low, and high gamma (HG) bands in response to presentation of all stimulus types. HG activity (80-200 Hz) in the ECoG tracked the spatiotemporal dynamics of word processing and identified a network of cortical structures involved in early word processing. HG was used to determine the relative onset, peak, and offset times of local cortical activation during word processing. Listening to verbs compared to nonwords sequentially activates first the posterior superior temporal gyrus (post-STG), then the middle superior temporal gyrus (mid-STG), followed by the superior temporal sulcus (STS). We also observed strong phase-locking between pairs of electrodes in the theta band, with weaker phase-locking occurring in the delta, alpha, and beta frequency ranges. These results provide details on the first few hundred milliseconds of the spatiotemporal evolution of cortical activity during word processing and provide evidence consistent with the hypothesis that an oscillatory hierarchy coordinates the flow of information between distinct cortical regions during goal-directed behavior.