Recent advances in brain imaging techniques, measurement approaches, and storage
capacities have provided an unprecedented supply of high temporal resolution neural data. …

Deep brain stimulation is a promising treatment for neuropsychiatric conditions such as
major depression. It could be optimized by identifying neural biomarkers that trigger therapy …

In recent years there has been increasing interest in applying network science tools to EEG
data. At the 2018 American Epilepsy Society conference in New Orleans, LA, the yearly …

Responsive neurostimulation (RNS) devices, able to detect imminent seizures and to rapidly
deliver electrical stimulation to the brain, are effective in reducing seizures in some patients …

Neuroengineering is faced with unique challenges in repairing or replacing complex neural
systems that are composed of many interacting parts. These interactions form intricate …

In ∼20 million people with drug-resistant epilepsy, focal seizures originating in dysfunctional
brain networks will often evolve and spread to surrounding tissue, disrupting function in …

The epileptic network is characterized by pathologic, seizure-generating ‘foci’ embedded in
a web of structural and functional connections. Clinically, seizure foci are considered optimal …

There exist significant clinical and basic research needs for accurate, automated seizure
detection algorithms. These algorithms have translational potential in responsive …

Optimizing direct electrical stimulation for the treatment of neurological disease remains
difficult due to an incomplete understanding of its physical propagation through brain tissue. …

Patients with drug-resistant epilepsy often require surgery to become seizure-free. While
laser ablation and implantable stimulation devices have lowered the morbidity of these …