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

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.

OBJECTIVE-Although electrophysiological measures of functional connectivity between brain areas are widely used, the spatial distribution of functional interactions as well as the disturbance introduced by focal brain lesions remains poorly understood. Based on the rationale that damaged brain tissue can be expected to be disconnected from the physiological interactions among healthy areas, this study aimed to map the functionality of brain areas according to their connectivity with other areas. METHODS-Magnetoencephalographic(MEG) recordings of spontaneous cortical activity during resting state were obtained from 15 consecutive patients with focal brain lesions and from 14 healthy controls. Neural activity at each volume element (voxel) in the brain was estimated using an adaptive spatial filtering technique. For each brain voxel, the mean imaginary coherence of all its connections with other brain voxels was then caluculated as an index of functional connectivity, and the results compared across brain regions and between subjects.RESULTS-The magnitude of the mean imaginary coherence of all voxels and subjects was greatest in the alpha frequency range corresponding to the human cortical idling rhythm. In healthy subjects, functionally critical brain areas such as the somatosensory and language cortices had the highest alpha coherence. When compared to healthy controls, all lesion patients had diffuse or scattered brain areas with decreased coherence. Patients with lesion-induced neurological deficits displayed decreased connectivity estimates in the corresponding brain area compared to intact contralateral regions. In tumor patients without preoperative neurological deficits, brain areas showing decreased coherence could be surgically resected without the occurrence of post-surgical deficits.CONCLUSION-Resting state coherence measured with MEG is capable of mapping the functional connectivity of the brain, and can therefore offer valuable information for use in planning resective surgeries in patients with brain lesions, as well as investigations into structuralfunctional relationships in normal subjects.

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.