Tags: neuroscience

All Categories (1-20 of 32)

  1. 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

  2. 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

  3. Janae

    http://nanohub.org/members/134905

  4. Nikhil Khinchi

    http://nanohub.org/members/127261

  5. Saeyoung Macx Kim

    http://nanohub.org/members/119055

  6. 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 18-19, 2014 in San Francisco, CA to discuss the latest scientific...

    http://nanohub.org/events/details/994

  7. AJAY RAJAK

    http://nanohub.org/members/94009

  8. [Illinois] MCB 529 BRH Reproductive Rhythms

    07 Jan 2014 | Online Presentations | Contributor(s): Megan Mahoney, Martha U. Gillette

    http://nanohub.org/resources/20121

  9. [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) sub-cellular micro-environments that shape neuronal dendrites in development and...

    http://nanohub.org/resources/20114

  10. [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

  11. [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

  12. [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

  13. [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

  14. [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

  15. [Illinois] MCB 493 Lecture 11: Temporal-Difference Learning and Reward Prediction

    29 Oct 2013 | Online Presentations | 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.

    http://nanohub.org/resources/18947

  16. [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 hands-on 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

  17. [Illinois]: Posterior target probability given single-sensory 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

  18. [Illinois]: Posterior probability of a target given single-sensory 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

  19. [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

  20. [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