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Soft, Biocompatible Optoelectronic Interfaces to the Brain
08 Jun 2017 | | Contributor(s):: John A. Rogers
In this talk, we will describe foundational concepts in physics and materials science for these types of technologies, in 1D, 2D and 3D architectures. Examples in system level demonstrations include experiments on freely moving animals with ‘cellular-scale’, injectable optofluidic...
Saeyoung Macx Kim
Sep 18 2014
8th Neurodegenerative Conditions Research & Development Conference
[Illinois] MCB 529 BRH Reproductive Rhythms
07 Jan 2014 | | Contributor(s):: Megan Mahoney, Martha U. Gillette
[Illinois] MCB 529 BRH Biological Rhythms in Health and Disease
30 Dec 2013 | | Contributor(s):: Martha U. Gillette
Our major research thrusts are to understand: 1) signals that engage the circadian clockwork in the brain, 2) sub-cellular micro-environments that shape neuronal dendrites in development and repair, and 3) emergent behaviors of integrated neuronal systems.
[Illinois] MCB 529 BRH Circadian Control of Liver Function
30 Dec 2013 | | Contributor(s):: Shelley Tischkau, Martha U. Gillette
[Illinois] MCB 529 BRH Drugs of Abuse and Circadian Rhythms
30 Dec 2013 | | Contributor(s):: Joshua M Gulley, Martha U. Gillette
[Illinois] MCB 529 BRH Nocturnal and Diurnal Adaptations
30 Dec 2013 | | Contributor(s):: Rhanor Gillette, Martha U. Gillette
[Illinois] MCB 493 Lecture 14: Future Directions in Neural Systems Modeling
30 Oct 2013 | | Contributor(s):: Thomas J. Anastasio
In the future, neural systems models will become increasingly complex and will span levels from molecular interactions within neurons to interactions between networks
[Illinois] MCB 493 Lecture 9: Probability Estimation and Supervised Learning
Supervised learning algorithms can train neural units and networks to estimate probabilities and simulate the responses of neurons to multisensory stimulation.
[Illinois] MCB 493 Lecture 11: Temporal-Difference Learning and Reward Prediction
29 Oct 2013 | | Contributor(s):: Thomas J. Anastasio
Temporal-difference learning can train neural networks to estimate the future value of a current state and simulate the responses of neurons involved in reward processing.
[Illinois] MCB 493 Neural Systems Modeling
The purpose of this independent study is to give students hands-on experience in using computers to model neural systems. A neural system is a system of interconnected neural elements, or units. Students will use existing computer programs which will simulate real neural systems. They will...
[Illinois]: Posterior target probability given single-sensory input (delta rule)
02 Jul 2013 | | Contributor(s):: Lisa Sproat, Jessica S Johnson, NanoBio Node
Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of one modality (i.e., visual)
[Illinois]: Posterior probability of a target given single-sensory input (Bayes')
28 Jun 2013 | | Contributor(s):: Lisa Sproat, Jessica S Johnson, NanoBio Node
Computes the posterior probability of a target given sensory input of one modality (i.e., visual)