An online dynamic experimental framework to study single neuron responses in humans

Abstract

Single-neuron activity can be recorded from patients being evaluated for neurosurgical treatment of drug-resistant epilepsy who volunteer to have microwires implanted for single cell research that aims to study various aspects of the human brain. These recordings provide an unprecedented window into the human brain to observe how information is encoded and retrieved at the cellular level. Current single cell research paradigms require laborious offline analysis to identify stimuli eliciting neuronal responses and introduce new relevant stimuli in a follow up task. Any delays due to patient availability can compromise the follow up task, risking loss of experimental progress as recording electrodes may move away from previously recorded neurons. This paper introduces a novel experimental framework for online single cell data analysis and dynamic sampling of the stimulus space. It allows for real-time data acquisition and analysis to identify response-eliciting stimuli, introduce new relevant stimuli, and discard those that fail to elicit responses.