Modeling of Neural Signals Slides

Modeling of Neural Signals Slides - Modeling of Neural...

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Unformatted text preview: Modeling of Neural Electrophysiological Signals BME 552 Neural Prosthetics March 13, 2009 System System is a set of interacting or interdependent entities, real or abstract, forming an integrated whole. Input Output Model An abstraction or conceptual object used in the creation of a predictive formula Parametric model Non-parametric model Parametric and Nonparametric Models Mechanistic and internal Parameters of the model relate to specific biological processes Specifically defined functions and associated parameters Requires prior knowledge or assumptions about system properties Searching for optimal parameters Experimental verification highly dependent on testing protocols Descriptive and external Parameters of the model relate to input-output mapping Does not rely on knowledge or assumptions about system properties Searching for optimal functions Experimental efficiency resulting from the broadband test stimulus Easy system identification and implementation Biological System Parametric Model Nonparametric Model System: brain, brain region (hippocampus), neuronal circuit, neuron, synapse, ionic channels Signal: spike, EPSP, EPSC, Model: Parametric model, non-parametric model Synapse and EPSC Subcellular 3. Future 2. EONS 1. Introduction Chemical Synapses 20-40 nm Asymmetric Unidirectional Delay: 2 ms Eons & Modeling v.1.0-8- 10 16 synapses during childhood 10 to 50% remain during adulthood Wide variety of responses varying in duration And intensity 4. Parallel Computing Addition of exogenous compounds: Addition of exogenous compounds: Each mechanisms can potentially be a target Each mechanisms can potentially be a target 2. Overall Description 1. Goal Eons & Modeling v.1.0-9- 1. Introduction 3. Future 2. EONS 3. Elements modeled EPSC and Short-term Synaptic Plasticity Whole-cell Recording of CA1 Pyramidal Cell-70 mV...
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Modeling of Neural Signals Slides - Modeling of Neural...

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