Topic: multi-electrode arrays

My laboratory studies how the retina processes visual scenes and transmits this information to the brain. We use multi-electrode arrays to record the activity of hundreds of retina neurons simultaneously in conjunction with transgenic mouse lines and chemogenetics to manipulate neural circuit function. We are interested in three major areas. First, we work to understand how neurons in the retina are functionally connected. Second we are studying how light-adaptation and circadian rhythms alter visual processing in the retina. Finally, we are working to understand the mechanisms of retinal deg

Reliably identifying cell types is crucial for understanding neural systems (1). However, classifying the neurons recorded in large-scale population recordings into well-defined types remains a challenge. While some methods rely on genetic targeting or anatomy for classification, a functional approach used in sensory systems is to analyze neuronal responses to stimuli that elicit distinguishable responses across different types (2, 3, 4). Yet, previous approaches of this nature have been limited by a restricted set of stimuli and scalability issues, thus preventing comprehensive characterizati

Eliciting percepts akin to natural vision using brain computer interfaces is the holy grail of vision prosthetics. However, progress has been slowed by our lack of understanding of how the human visual cortex processes and encodes information as well as how external perturbations, such as electrical stimulation via multi-electrode arrays, might perturb the recurrent cortical dynamics. Furthermore, investigating these questions directly remains difficult as we rarely have the opportunity to probe the human cortex in-vivo. From this limitation and thanks to the current exponential increase in

The human language system comprises a series of processing stages across multiple brain regions typically lateralized to the left cerebral hemisphere. In the event of stroke or other injury to these systems, neural circuits reorganize in an attempt to restore lost function. However, the neural processes and learned representations underlying language network reorganization remain unclear. Here, we present data from a first-of-its-kind human case study involving chronic intracortical recordings from the right cerebral hemisphere of a patient with non-fluent aphasia with severe left-hemispheric