1_27_09_NoiseAnalysis

1_27_09_NoiseAnalysis - Outline of the Lecture Outline of...

Info iconThis preview shows pages 1–8. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Outline of the Lecture Outline of the Lecture Noise Analysis Noise Analysis Neural Noise Mean & Variance Power Neural Noise Mean & Variance Power Spectrum Spectrum Statistical Properties of Statistical Properties of Neural Noise Reveal Neural Noise Reveal Underlying Unitary Events Underlying Unitary Events The K + channel has one open and four closed states with probabilistic transitions given by α n and β n from the Hodgkin-Huxley model. Long voltage pulses under K +-channel blockade cause fluctuating Na + currents. Single-event Responses Time (ms) Time (ms) Single-event Responses σ x 2 = 1 n x i- x ( ) 2 i = 1 n å The variance of a random variable x is Where the overbar indicates “mean” and n is the sample size. Opening the square gives σ x 2 = x i 2 i = 1 n å n- 2 x x i i = 1 n å n + x 2 = 1 n x i 2 i = 1 n å ae è ç ö ø ÷- x 2 σ...
View Full Document

This note was uploaded on 06/08/2009 for the course BME 575L taught by Professor Grzywacz during the Spring '09 term at USC.

Page1 / 17

1_27_09_NoiseAnalysis - Outline of the Lecture Outline of...

This preview shows document pages 1 - 8. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online