Final Project

The goal of the final project is to demonstrate mastery over one of the topics of the course by replicating a key result from a published paper from the last decade or two. Before beginning serious work on your project, you should send a “project abstract” email with an outline of what paper and what figure(s) you plan to replicate. (In some cases it may be suggested to reduce the scope or simplify the plan!) Please do this by the end of the Thanksgiving break to ensure you have enough time to work.

Below are some suggested / sample papers that you might consider. This is not intended to be an exhaustive list, and students have in the past even proposed using one of the techniques from the class on a topic of their own interest (e.g., clustering of fantasy football players).

Neural Circuit Modeling

• Barreiro et al 2012 “A-current and type I/type II transition determine collective spiking from common input.”
• Pospischil et al 2008 “Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons” BONUS PAPER!
• Kang and Lowery 2014 “Effects of antidromic and orthodromic activation of STN afferent axons during DBS in Parkinson’s disease: a simulation study.”

Point Processes

• Brown et al 2002 “The time-rescaling theorem and its application to neural spike train data analysis.”

Classification

• Kemere et al 2004 “Model-based decoding of reaching movements for prosthetic systems.”
• Yu et al 2004 “Improving neural prosthetic system performance by combining plan and peri-movement activity.”
• Santhanam et al 2009 “Factor-analysis methods for higher-performance neural prostheses.”

Clustering

• Wild et al 2012 “Performance comparison of extracellular spike sorting algorithms for single-channel recordings.”

Dimensionality Reduction

• Yu et al 2009 “Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity.”

Continuous decoding

• Kemere and Meng 2005 “Optimal estimation of feed-foward-controlled linear systems”
• Wu et al 2004 “Modeling and decoding motor cortical activity using a switching Kalman filter.”
• Brown et al 1998 “A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells.”