Literature DB >> 29371834

An Interactive Simulation Program for Exploring Computational Models of Auto-Associative Memory.

Christian G Fink1.   

Abstract

While neuroscience students typically learn about activity-dependent plasticity early in their education, they often struggle to conceptually connect modification at the synaptic scale with network-level neuronal dynamics, not to mention with their own everyday experience of recalling a memory. We have developed an interactive simulation program (based on the Hopfield model of auto-associative memory) that enables the user to visualize the connections generated by any pattern of neural activity, as well as to simulate the network dynamics resulting from such connectivity. An accompanying set of student exercises introduces the concepts of pattern completion, pattern separation, and sparse versus distributed neural representations. Results from a conceptual assessment administered before and after students worked through these exercises indicate that the simulation program is a useful pedagogical tool for illustrating fundamental concepts of computational models of memory.

Entities:  

Keywords:  Hebbian plasticity; Hopfield networks; computational neuroscience; memory; neural networks

Year:  2017        PMID: 29371834      PMCID: PMC5777830     

Source DB:  PubMed          Journal:  J Undergrad Neurosci Educ        ISSN: 1544-2896


  5 in total

1.  Selection of intrinsic horizontal connections in the visual cortex by correlated neuronal activity.

Authors:  S Löwel; W Singer
Journal:  Science       Date:  1992-01-10       Impact factor: 47.728

2.  Pencil-and-Paper Neural Networks: An Undergraduate Laboratory Exercise in Computational Neuroscience.

Authors:  Kevin M Crisp; Ellen N Sutter; Jacob A Westerberg
Journal:  J Undergrad Neurosci Educ       Date:  2015-10-15

3.  An Algebra-Based Introductory Computational Neuroscience Course with Lab.

Authors:  Christian G Fink
Journal:  J Undergrad Neurosci Educ       Date:  2017-06-15

4.  Neural networks and physical systems with emergent collective computational abilities.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1982-04       Impact factor: 11.205

5.  Demonstrations of neural network computations involving students.

Authors:  Christopher J May
Journal:  J Undergrad Neurosci Educ       Date:  2010-03-15
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.