NB204 Special Topics Primers

Below you will find a list of resources for some of the basic statistical and analytical methods that you will encounter during the course. They are designed to give you an adequate introduction to these topics. Those particularly recommended are highlighted with an asterisk.

Matlab

1. *Boot Camp in Quantitative Methods: MATLAB programming, including exercises, tutorials and how to download and install MATLAB

2. *For "live" help, attend Dr. Melanie Stefan's Quant Bio Club, which meets every Monday from 3-5 p.m. in Goldenson 229

2. A MATLAB Primer

Information Theory

1. *Reinagel P (2000) "Information theory in the brain." Curr. Biol. 10:R542-4. (pdf)

2. Panzeri S et al. (2007) "Correcting for the sampling bias problem in spike train information measures." J. Neurophysiol. 98:1064-1072. (pdf)

3. *Butts DA and Goldman MS (2006) "Tuning curves, neuronal variability, and sensory coding." PLoS Biol. 4:639-46. (pdf)

Signal detection theory

1. Wikipedia: Detection Theory

2. *Chapter 1 of McNicol's "A Primer of Signal Detection Theory" (pdf)

3. David Heeger: Signal Detection Theory (intro)

4. *David Heeger: Signal Detection Theory (advanced)

Reverse correlation maps of receptive fields

1. *Izumi Ohzawa web page: Space-Time Receptive Fields of Visual Neurons

2. DeAngelis GC et al. (1995) "Receptive-field dynamics in the central visual pathways." Trends Neurosci. 18:451-458. (pdf)

Poisson Statistics (and basic probability)

1. Wikipedia: Poisson Distribution

2. *Ash, C. The Probability Tutoring Book, (NY: IEEE Press 1993). Chapters 1 and 2. (pdf)

3. *David Heeger: Poisson Model of Spike Generation

4. *David Heeger: Poisson Tutorial in MATLAB

Non-parametric statistics (including bootstrap)

1. Wikipedia: Resampling Statistics

2. *Efron B and Tibshirani RJ. An Introduction to the Bootstrap, (London: Chapman & Hall 1993).

Chapters 1 and 2 (pdf) and sample Matlab scripts (bs_ex1.m and bs_ex2.m)

Updated 29 January 2014 by RTB