Mining the neural code of a guinea pig auditory cortex

J. Si, R. Witte, Jing Hu, D. R. Kipke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

One primary objective of mining the brain is to learn the inner workings of the mind and how external events become internal perceptions. But to mine the brain also means to mine the continuous network of neural signals that transcend across billions of its neurons. Advances in the past several decades in computational neuroscience have provided fundamental clues into understanding brain processes in relation to memory, movement, and sensory perception. We analyze the responses of a population of neurons recorded simultaneously in guinea pig auditory cortex while various sound stimuli are presented in the free field. By mining the responses of auditory neurons in the awake animal to different acoustic stimuli, we hope to address a few key questions. 1) Do the neurons respond in specific ways to particular features of the stimuli? 2) Is there a clear relation between groups of neurons and a specific sound stimulus? 3) How many neurons are needed to decode the stimuli? 4) What are the optimum algorithms to interpret the neural responses? 5) How much pre-processing is necessary to account for missing data, noise, and high levels of variability of neural responses even to similar stimuli? We first introduce techniques that are used to transform the original data set from spike times to identifiable signal waveforms for discrimination analysis. We then demonstrate the level of complexity of the problem by providing results obtained with template matching. Finally, the self-organizing map (SOM) is described as a promising technique that extracts the most relevant information from the complex data set.

Original languageEnglish (US)
Title of host publication2001 International Conferences on Info-Tech and Info-Net
Subtitle of host publicationA Key to Better Life, ICII 2001 - Proceedings
EditorsZhongzhi Shi, Hui Li, Y.X. Zhong
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages84-89
Number of pages6
ISBN (Electronic)0780370104, 9780780370104
DOIs
StatePublished - Jan 1 2001
Externally publishedYes
EventInternational Conferences on Info-Tech and Info-Net, ICII 2001 - Beijing, China
Duration: Oct 29 2001Nov 1 2001

Publication series

Name2001 International Conferences on Info-Tech and Info-Net: A Key to Better Life, ICII 2001 - Proceedings
Volume3

Other

OtherInternational Conferences on Info-Tech and Info-Net, ICII 2001
CountryChina
CityBeijing
Period10/29/0111/1/01

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Signal Processing
  • Computers in Earth Sciences
  • Control and Systems Engineering
  • Instrumentation

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