William S. Anderson

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The neurophysiological mechanisms by which anesthetic drugs cause loss of consciousness are poorly understood. Anesthetic actions at the molecular, cellular, and systems levels have been studied in detail at steady states of deep general anesthesia. However, little is known about how anesthetics alter neural activity during the transition into(More)
Epileptic seizures are traditionally characterized as the ultimate expression of monolithic, hypersynchronous neuronal activity arising from unbalanced runaway excitation. Here we report the first examination of spike train patterns in large ensembles of single neurons during seizures in persons with epilepsy. Contrary to the traditional view, neuronal(More)
Intracranial recording is an important diagnostic method routinely used in a number of neurological monitoring scenarios. In recent years, advancements in such recordings have been extended to include unit activity of an ensemble of neurons. However, a detailed functional characterization of excitatory and inhibitory cells has not been attempted in human(More)
A large scale neural network simulation with realistic cortical architecture has been undertaken to investigate the effects of external electrical stimulation on the propagation and evolution of ongoing seizure activity. This is an effort to explore the parameter space of stimulation variables to uncover promising avenues of research for this therapeutic(More)
PURPOSE A neural network simulation with realistic cortical architecture has been used to study synchronized bursting as a seizure representation. This model has the property that bursting epochs arise and cease spontaneously, and bursting epochs can be induced by external stimulation. We have used this simulation to study the time-frequency properties of(More)
Epilepsy affects 50 million people worldwide, and seizures in 30% of the cases remain drug resistant. This has increased interest in responsive neurostimulation, which is most effective when administered during seizure onset. We propose a novel framework for seizure onset detection that involves (i) constructing statistics from multichannel intracranial EEG(More)
Seizures are events that spread through the brain's network of connections and create pathological activity. To understand what is occurring in the brain during seizure we investigated the time progression of the brain's state from seizure onset to seizure suppression. Knowledge of a seizure's dynamics and the associated spatial structure is important for(More)
The human brain is a dynamic networked system. Patients with partial epileptic seizures have focal regions that periodically diverge from normal brain network dynamics during seizures. We studied the evolution of brain connectivity before, during, and after seizures with graph-theoretic techniques on continuous electrocorticographic (ECoG) recordings (5.4 ±(More)
Seizure prediction has proven to be difficult in clinically realistic environments. Is it possible that fluctuations in cortical firing could influence the onset of seizures in an ictal zone? To test this, we have now used neural network simulations in a computational model of cortex having a total of 65,536 neurons with intercellular wiring patterned after(More)
Over the past two decades, deep brain stimulation (DBS) has supplanted lesioning techniques for the treatment of movement disorders, and has been shown to be safe and efficacious. The primary therapeutic indications for DBS are essential tremor, dystonia and Parkinson's disease. In the case of Parkinson's disease, DBS is effective for treating the primary(More)