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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,(More)
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(More)
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(More)
OBJECTIVE The spatial distribution of functional connectivity between brain areas and the disturbance introduced by focal brain lesions are poorly understood. Based on the rationale that damaged brain tissue is disconnected from the physiological interactions among healthy areas, this study aimed to map the functionality of brain areas according to their(More)
Intracranial electroencephalography (iEEG) is clinically indicated for medically refractory epilepsy and is a promising approach for developing neural prosthetics. These recordings also provide valuable data for cognitive neuroscience research. Accurate localization of iEEG electrodes is essential for evaluating specific brain regions underlying the(More)
IMPORTANCE Epileptic activity associated with Alzheimer disease (AD) deserves increased attention because it has a harmful impact on these patients, can easily go unrecognized and untreated, and may reflect pathogenic processes that also contribute to other aspects of the illness. We report key features of AD-related seizures and epileptiform activity that(More)
SAM(g2) is an automated analysis that transforms the MEG data into a functional image of spike-like activity, giving the source waveforms for those locations. Since the source waveforms estimated by SAM have higher signal-to-noise ratio (SNR) than does the raw MEG data, it is possible to automatically mark the location and timing of each spike for(More)
Epilepsy - the world's most common serious brain disorder - is defined by recurrent unprovoked seizures that result from complex interactions between distributed neural populations. We explore some macroscopic characteristics of emergent ictal networks by considering intracranial recordings from human subjects with intractable epilepsy. For each seizure, we(More)
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(More)