Passive functional mapping of receptive language cortex during general anesthesia using electrocorticography.

Objective: To investigate the feasibility of passive functional mapping in the receptive language cortex during general anesthesia using electrocorticographic (ECoG) signals.

Methods: We used subdurally placed ECoG grids to record cortical responses to speech stimuli during awake and anesthesia conditions. We identified the cortical areas with significant responses to the stimuli using the spectro-temporal consistency of the brain signal in the broadband gamma (BBG) frequency band (70-170 Hz).

Electrocorticographic mapping of expressive language function without requiring the patient to speak: A report of three cases.

Objective: Patients requiring resective brain surgery often undergo functional brain mapping during perioperative planning to localize expressive language areas. Currently, all established protocols to perform such mapping require substantial time and patient participation during verb generation or similar tasks. These issues can make language mapping impractical in certain clinical circumstances (e.

Intraoperative mapping of expressive language cortex using passive real-time electrocorticography.

In this case report, we investigated the utility and practicality of passive intraoperative functional mapping of expressive language cortex using high-resolution electrocorticography (ECoG). The patient presented here experienced new-onset seizures caused by a medium-grade tumor in very close proximity to expressive language regions. In preparation of tumor resection, the patient underwent multiple functional language mapping procedures.

Asynchronous decoding of finger movements from ECoG signals using long-range dependencies conditional random fields.

Objective: In this work we propose the use of conditional random fields with long-range dependencies for the classification of finger movements from electrocorticographic recordings.

Approach: The proposed method uses long-range dependencies taking into consideration time-lags between the brain activity and the execution of the motor task. In addition, the proposed method models the dynamics of the task executed by the subject and uses information about these dynamics as prior information during the classification stage.

Alpha power indexes task-related networks on large and small scales: A multimodal ECoG study in humans and a non-human primate.

Performing different tasks, such as generating motor movements or processing sensory input, requires the recruitment of specific networks of neuronal populations. Previous studies suggested that power variations in the alpha band (8-12Hz) may implement such recruitment of task-specific populations by increasing cortical excitability in task-related areas while inhibiting population-level cortical activity in task-unrelated areas (Klimesch et al., 2007; Jensen and Mazaheri, 2010).