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A standardized protocol and software framework for synchronized acquisition, processing, and sharing of multimodal brain imaging data streams.

A piece of information attached to a data sample that identifies its class or category, providing the ground truth for machine learning algorithms to learn from and use for future predictions.

The process of identifying raw data (such as neural signals or images) and adding one or more relevant labels to provide context, enabling supervised machine learning models to learn from the data and make accurate predictions.

The aggregate electrical signal generated by the summed synaptic and other electrical activity of a local population of neurons in a small volume of brain tissue.[20] LFPs reflect the synchronized input to a neural area and are a primary signal source measured by both intracortical and ECoG electrodes.[28]

A measure of brain activity recorded from a small group of neurons in a specific area of the brain, capturing the collective electric potentials generated by local neuronal activity.

A type of RNN capable of capturing long-term dependencies in neural signals, such as EEG time series.

Study design in which the same subjects are followed and measured across multiple sessions or points in time.

A filter that allows frequencies below a certain cutoff to pass and attenuates higher frequencies.