Longitudinal multitask wireless electrocorticography data from two fully implanted nonhuman primates

Area of Science:

• Neuroscience
• Biomedical Engineering
• Data Science

Background:

• Chronic electrocorticography (ECoG) recordings are crucial for understanding long-term brain dynamics.
• Existing datasets often lack the duration or wireless capabilities needed for comprehensive research.
• Nonhuman primate models offer valuable insights into sensorimotor cortical functions.

Purpose of the Study:

• To present a unique, high-quality dataset of chronic wireless ECoG recordings.
• To facilitate research into long-term cortical dynamics and brain-computer interfaces (BCI).
• To ensure data interoperability and reusability through adherence to the Brain Imaging Data Structure (BIDS).

Main Methods:

• Utilized bilateral subdural ECoG arrays in two Japanese macaques (Macaca fuscata).
• Employed fully implantable wireless transmission units for data acquisition over hundreds of days.
• Recorded data during resting-state, auditory, motor tasks, and somatosensory evoked potential paradigms.
• Organized all data, including raw signals, annotations, and metadata, according to the BIDS extension for intracranial electrophysiology.

Main Results:

• Confirmed data quality and signal stability through impedance monitoring and spectral analyses.
• Demonstrated reliability and consistency of ECoG signals across the extensive recording period.
• Provided a comprehensive dataset covering diverse behavioral and stimulus conditions.

Conclusions:

• The open-access longitudinal wireless ECoG dataset is a valuable resource for neuroscience research.
• This data will advance the understanding of chronic cortical dynamics.
• The dataset is expected to accelerate progress in brain-computer interface (BCI) development and applications.