Heidi E. Kirsch

High Gamma Power Is Phase-Locked to Theta Oscillations in Human Neocortex

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.

De novo mutations in epileptic encephalopathies

Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown. Here we report a screen for de novo mutations in patients with two classical epileptic encephalopathies: infantile spasms (n = 149) and Lennox–Gastaut syndrome (n = 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the ∼4,000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 × 10−3). Among these are GABRB3, with de novo mutations in four patients, and ALG13, with the same de novo mutation in two patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P = 4.1 × 10−10 and P = 7.8 × 10−12, respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P < 10−8), as has been reported previously for autism spectrum disorders.

Seizures and epileptiform activity in the early stages of Alzheimer disease.

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 are instructive for clinical practice and highlight similarities between AD and transgenic animal models of the disease. OBJECTIVE To describe common clinical characteristics and treatment outcomes of patients with amnestic mild cognitive impairment (aMCI) or early AD who also have epilepsy or subclinical epileptiform activity. DESIGN Retrospective observational study from 2007 to 2012. SETTING Memory and Aging Center, University of California, San Francisco. PATIENTS We studied 54 patients with a diagnosis of aMCI plus epilepsy (n = 12), AD plus epilepsy (n = 35), and AD plus subclinical epileptiform activity (n = 7). MAIN OUTCOMES AND MEASURES Clinical and demographic data, electroencephalogram (EEG) readings, and treatment responses to antiepileptic medications. RESULTS Patients with aMCI who had epilepsy presented with symptoms of cognitive decline 6.8 years earlier than patients with aMCI who did not have epilepsy (64.3 vs 71.1 years; P = .02). Patients with AD who had epilepsy presented with cognitive decline 5.5 years earlier than patients with AD who did not have epilepsy (64.8 vs 70.3 years; P = .001). Patients with AD who had subclinical epileptiform activity also had an early onset of cognitive decline (58.9 years). The timing of seizure onset in patients with aMCI and AD was nonuniform (P < .001), clustering near the onset of cognitive decline. Epilepsies were most often complex partial seizures (47%) and more than half were nonconvulsive (55%). Serial or extended EEG monitoring appeared to be more effective than routine EEG at detecting interictal and subclinical epileptiform activity. Epileptic foci were predominantly unilateral and temporal. Of the most commonly prescribed antiepileptics, treatment outcomes appeared to be better for lamotrigine and levetiracetam than for phenytoin. CONCLUSIONS AND RELEVANCE Common clinical features of patients with aMCI- or AD-associated epilepsy at our center included early age at onset of cognitive decline, early incidence of seizures in the disease course, unilateral temporal epileptic foci detected by serial/extended EEG, transient cognitive dysfunction, and good seizure control and tolerability with lamotrigine and levetiracetam. Careful identification and treatment of epilepsy in such patients may improve their clinical course.

Five-dimensional neuroimaging : localization of the time–frequency dynamics of cortical activity

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, although 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.

Spatiotemporal dynamics of word processing in the human brain

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.

Emergent network topology at seizure onset in humans

Epilepsy - the worlds 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 compute a simple measure of linear coupling between all electrode pairs (more than 2400) to define networks of interdependent electrodes during preictal and ictal time intervals. We analyze these networks by applying traditional measures from network analysis and identify statistically significant global and local changes in network topology. We find at seizure onset a diffuse breakdown in global coupling, and local changes indicative of increased throughput of specific cortical and subcortical regions. We conclude that network analysis yields measures to summarize the complicated coupling topology emergent at seizure onset. Using these measures, we can identify spatially localized brain regions that may facilitate seizures and may be potential targets for focal therapies.

Mapping Functional Connectivity in Patients with Brain Lesions

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 connectivity with other areas.

The howling cortex: seizures and general anesthetic drugs.

The true incidence of seizures caused by general anesthetic drugs is unknown. Abnormal movements are common during induction of anesthesia, but they may not be indicative of true seizures. Conversely, epileptiform electrocortical activity is commonly induced by enflurane, etomidate, sevoflurane and, to a lesser extent, propofol, but it rarely progresses to generalized tonic-clonic seizures. Even “nonconvulsant” anesthetic drugs occasionally cause seizures in subjects with preexisting epilepsy. These seizures most commonly occur during induction or emergence from anesthesia, when the anesthetic drug concentration is relatively low. There is no unifying neural mechanism of anesthetic drug-related seizurogenesis. However, there is a growing body of experimental work suggesting that seizures are not caused simply by “too much excitation,” but rather by excitation applied to a mass of neurons which are primed to react to the excitation by going into an oscillatory seizure state. Increased &ggr;-amino-butyric acid (GABA)ergic inhibition can sensitize the cortex so that only a small amount of excitation is required to cause seizures. This has been postulated to occur 1) at the network level by increasing the propensity for reverberation (e.g., by prolongation of the “inhibitory lag”), or 2) via different effects on subpopulations of interneurons (“inhibiting-the-inhibitors”) or 3) at the synaptic level by changing the chloride reversal potential (“excitatory GABA”). On the basis of applied neuropharmacology, prevention of anesthetic-drug related seizures would include 1) avoiding sevoflurane and etomidate, 2) considering prophylaxis with adjunctive benzodiazepines (&agr;-subunit GABAA agonists), or drugs that impair calcium entry into neurons, and 3) using electroencephalogram monitoring to detect early signs of cortical instability and epileptiform activity. Seizures may falsely elevate electroencephalogram indices of depth of anesthesia.

Neocortical hyperexcitability in a human case of tuberous sclerosis complex and mice lacking neuronal expression of TSC1

To identify brain regions, cell types, or both that generate abnormal electrical discharge in tuberous sclerosis complex (TSC). Here we examined excitatory and inhibitory synaptic currents in human tissue samples obtained from a TSC patient with no discernible cortical tubers and acute neocortical brain slices from a mouse featuring synapsin‐driven conditional deletion of a TSC1 gene. These studies were designed to assess whether TSC gene inactivation alters excitability.

Resting Functional Connectivity in Patients with Brain Tumors in Eloquent Areas

Resection of brain tumors adjacent to eloquent areas represents a challenge in neurosurgery. If maximal resection is desired without inducing postoperative neurological deficits, a detailed knowledge of the functional topography in and around the tumor is crucial. The aim of the present work is to evaluate the value of preoperative magnetoencephalography (MEG) imaging of functional connectivity to predict the results of intraoperative electrical stimulation (IES) mapping, the clinical gold standard for neurosurgical localization of functional areas.