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Processing the Local Field Potential Signals in Comparison to Neighboring Simple and Complex Neurons of Primary Visual Cortex

Eftekhar, Morteza | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 51720 (04)
  4. University: Sharif University of Technology
  5. Department: Physics
  6. Advisor(s): Lashgari, Reza
  7. Abstract:
  8. In neural systems of living organism, moreover than differences in anatomic structure of cells, there is also differences in physiological functions of analogous cells.Specification and categorization of neurons based on physiological functions is one of objectives of neuroscience. Study of cognitive behaviors and systematic study of neural system, modeling and practical applications in neural prosthesis design are some of applications of categorizing neural cells. Neural signals can be studied by Spike rate of a single neuron activity or Local Field Potential (LFP) of a finite number of neurons. In previous studies neurons of first visual cortex are divided into two groups of simple and complex cells according to single neuron activities. Simple cells have discontinuous response to stimulus due to their specific regions of excitatory and inhibitory receptive field in spite of complex cells that have continuous response to stimulus due to indistinct of mentioned receptive fields. In this proposal, first we categorize the first visual cortex’s neurons into two groups of simple and complex based on spikes rates and then analyze the LFPs of them that are recorded simultaneously with spikes. Detaching action potentials from LFPs requires many stage of processes. The suggested methods is Spikes’ Waiting Times, Horizontal Visibility Graph (HVG) and Marked Events of time series. The analysis based on these method suggest that these neurons have similar structure and can not be identified through these means but they can be identified by applying these method on Spikes’ time series
  9. Keywords:
  10. Neuron ; Visual Cortex ; Local Field Potential ; Simple Cells ; Waiting Time ; Complex Cells ; Stochastic Process ; Time Series ; Poisson Distribution ; Correlation Functions ; Horizontal Visibility Graph ; Marked Events

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