Helping Humans: Neuroprosthetics

Related lectures (32)

Page 2 of 4

Covers the optimization of neuron models for coding and decoding in computational neuroscience.

Explores parameter estimation in neuron models, focusing on quadratic optimization and linear fit.

Explores interspike intervals, renewal processes, and escape noise experiments in neuronal dynamics.

Explores neural signal recording methods using various electrode types for in-vivo and in-vitro studies.

Explores modeling in vitro data for computational neuroscience, including predicting subthreshold voltage and spike times.

Explores the dynamics of neuronal populations, emphasizing random networks and mean-field arguments for connectivity.

Explores the evolution of vision systems, retinal ganglion cells, LGN organization, and visual cortex processing.

Covers the Generalized Linear Model (GLM) in computational neuroscience.

Explores the reconstruction of a full-scale mouse striatal cellular level model to integrate and interpret striatal data.

Explores the concept of separation of time scales in computational neuroscience and the reduction of detail in two-dimensional neuron models.