Neurocritical care patients are at risk of developing secondary brain injury from inflammation, ischemia, and edema that follows the primary insult. Recognizing clinical deterioration due to secondary injury is frequently challenging in comatose patients. Multimodality monitoring (MMM) encompasses various tools to monitor cerebral metabolism, perfusion, and oxygenation aimed at detecting these ...

Accurate localization of the epileptic seizure onset zones (SOZs) is crucial for successful surgery, which usually depends on the information obtained from intracranial electroencephalography (IEEG) recordings. The visual criteria and univariate methods of analyzing IEEG recordings have not always produced clarity on the SOZs for resection and ultimate seizure freedom for patients. Here, to con...

Human faces transmit multiple valuable signals, and neuroimaging studies have shown that the amygdala is active in response to facial stimuli. However, little has been known about the temporal profile of amygdala activation during facial signal processing until recently. Here we review three recent studies conducted by our group in which we recorded amygdala intracranial electroencephalography ...

Functional imaging studies complement structural magnetic resonance imaging (MRI) in the assessment of patients with brain tumor-associated focal epilepsy. (11)C-Methionine (MET) and (18) F-fluoro-ethyl-L-tyrosine (FET) are amino acid analogues that highlight metabolically active areas in positron emission tomography (PET). Ictal single photon emission computed tomography (SPECT) can provide in...

This research focuses on the development of a machine learning technique based on Time-Delay Neural Networks (TDNN) and Independent Component Analysis (ICA), to analyze EEG signal dynamics related to the initiation and propagation of epileptic seizures. We aim at designing a generative model to simulate EEG time-series after alteration of specific localized channels (electrodes) in order to exp...

Environmental cues often trigger memories of past events (associative retrieval), and these memories are a form of prediction about imminent experience. Learning is driven by the detection of prediction violations, when the past and present diverge. Using intracranial electroencephalography (iEEG), we show that associative prediction violations elicit increased low-frequency power (in the slow-...

A brain-computer interface (BCI) is a device that enables severely disabled people to communicate and interact with their environments using their brain waves. Most research investigating BCI in humans has used scalp-recorded electroencephalography or intracranial electrocorticography. The use of brain signals obtained directly from stereotactic depth electrodes to control a BCI has not previou...

Magnetoencephalography (MEG), which acquires neuromagnetic fields in the brain, is a useful diagnostic tool in presurgical evaluation of epilepsy. Previous studies have shown that MEG affects the planning intracranial electroencephalography placement and correlates with surgical outcomes by using a single dipole model. Spatiotemporal source analysis using distributed source models is an advance...

Episodic memory encoding refers to the cognitive process by which items and their associated contexts are stored in memory. To investigate changes directly attributed to the formation of explicit associations, we examined oscillatory power captured through intracranial electroencephalography (iEEG) as 27 neurosurgical patients receiving subdural and depth electrodes for seizure monitoring parti...