
Gregor Kovacic
Gregor Kovacic received his undergraduate degrees in Physics and Mathematics from the University of Ljubljana, Slovenia, in 1985, and his PhD in Applied Mathematics from California Institute of...
http://nanohub.org/members/173301

Soft, Biocompatible Optoelectronic Interfaces to the Brain
08 Jun 2017  Online Presentations  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...
http://nanohub.org/resources/26702

Janae
http://nanohub.org/members/134905

Nikhil Khinchi
http://nanohub.org/members/127261

Saeyoung Macx Kim
http://nanohub.org/members/119055

Sep 18 2014
8th Neurodegenerative Conditions Research & Development Conference
It is our pleasure to announce the 8th Neurodegenerative Conditions Research & Development Conference, to be held on September 1819, 2014 in San Francisco, CA to discuss the latest scientific...
http://nanohub.org/events/details/994

AJAY RAJAK
http://nanohub.org/members/94009

[Illinois] MCB 529 BRH Reproductive Rhythms
07 Jan 2014  Online Presentations  Contributor(s): Megan Mahoney, Martha U. Gillette
http://nanohub.org/resources/20121

[Illinois] MCB 529 BRH Biological Rhythms in Health and Disease
30 Dec 2013  Courses  Contributor(s): Martha U. Gillette
Our major research thrusts are to understand: 1) signals that engage the circadian clockwork in the brain, 2) subcellular microenvironments that shape neuronal dendrites in development and...
http://nanohub.org/resources/20114

[Illinois] MCB 529 BRH Circadian Control of Liver Function
30 Dec 2013  Online Presentations  Contributor(s): Shelley Tischkau, Martha U. Gillette
http://nanohub.org/resources/20118

[Illinois] MCB 529 BRH Drugs of Abuse and Circadian Rhythms
30 Dec 2013  Online Presentations  Contributor(s): Joshua M Gulley, Martha U. Gillette
http://nanohub.org/resources/20119

[Illinois] MCB 529 BRH Nocturnal and Diurnal Adaptations
30 Dec 2013  Online Presentations  Contributor(s): Rhanor Gillette, Martha U. Gillette
http://nanohub.org/resources/20117

[Illinois] MCB 493 Lecture 14: Future Directions in Neural Systems Modeling
30 Oct 2013  Online Presentations  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
http://nanohub.org/resources/18948

[Illinois] MCB 493 Lecture 9: Probability Estimation and Supervised Learning
30 Oct 2013  Online Presentations  Contributor(s): Thomas J. Anastasio
Supervised learning algorithms can train neural units and networks to estimate probabilities and simulate the responses of neurons to multisensory stimulation.
http://nanohub.org/resources/18834

[Illinois] MCB 493 Lecture 11: TemporalDifference Learning and Reward Prediction
29 Oct 2013  Online Presentations  Contributor(s): Thomas J. Anastasio
Temporaldifference learning can train neural networks to estimate the future value of a current state and simulate the responses of neurons involved in reward processing.
http://nanohub.org/resources/18947

[Illinois] MCB 493 Neural Systems Modeling
29 Oct 2013  Courses  Contributor(s): Thomas J. Anastasio
The purpose of this independent study is to give students handson experience in using computers to model neural systems. A neural system is a system of interconnected neural elements, or units....
http://nanohub.org/resources/16704

[Illinois]: Posterior target probability given singlesensory input (delta rule)
02 Jul 2013  Tools  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)
http://nanohub.org/resources/unisensorydelta

[Illinois]: Posterior probability of a target given singlesensory input (Bayes')
01 Jul 2013  Tools  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)
http://nanohub.org/resources/unisensorybayes

[Illinois]: Posterior probability of a target given input for two senses (Bayes')
01 Jul 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Computes the posterior probability of a target given sensory input of two modalities (i.e., visual and auditory)
http://nanohub.org/resources/bisensorybayes

[Illinois]: Posterior probability of a target given input for two senses (delta)
01 Jul 2013  Tools  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 two modalities (i.e., visual and auditory)
http://nanohub.org/resources/bisensorydelta