NEUROINFORMATICS
the brain
| August | Syllabus |
| Saturday 16 |
Reception: (Saturday evening)
Introduction: Mitra (Saturday evening) (materials) |
| Sunday 17 |
Nature and measurement of transmembrane potential: Kleinfeld (Sunday morning)
Topics: Sources of intra and extracellular potentials; measurement techniques and noise issues. (materials) Nature and measurement of synaptic transmission: Kleinfeld (Sunday morning) Topics: Ligand-gated ion channels; post-synaptic potentials; synaptic integration (materials) Nature and measurement of network activity: Kleinfeld (Sunday morning) Topics: Optical imaging techniques; intrinsic contrast/dyes/genetic markers. (materials) Probability Theory: Iyengar (Sunday afternoon) Topics: Probability axioms, basic distributions, law of large numbers, CLT. (materials) Statistics I: Estimation: Iyengar (Sunday afternoon) Basic rules of probability; common univariate and multivariate models; approximations (via limit theorems); Bayes' theorem; some stochastic process basics (Markov chain, martingale). (materials) Tutorial: Matlab Prob/Stat I: Estimation: Iyengar (Sunday evening) Topics: (materials) |
| Monday 18 |
MCN Joint Lecture I: Signal processing and spectral analysis: Pesaran (Monday morning)
Topics: Filters, Fourier transforms, estimation of power spectra (materials) MCN Joint Lecture II: Point process models and Splines: Eden (Monday morning) Topics: (materials) MCN Joint Lecture III: Applications to the Vibrissa system: Kleinfeld (Monday afternoon) Topics: (materials) MCN Joint Lecture IV: Neuroanatomy; analysis of ABA data set: Mitra (Monday afternoon) Topics: (materials) Tutorial: Signal Processing, Spectral Analysis. (Chronux): Bokil, Pesaran (Monday evening) Topics: (materials) |
| Tuesday 19 |
Statistics II: Inference: Iyengar (Tuesday morning)
Topics: Hypotheses tests; Type I and II errors; power; nonparametric tests; bootstrap, jackknife; Bayesian inference. (materials) Statistics III: Linear Models: Iyengar (Tuesday morning) Topics: Linear, logistic, and Poisson regression; the method of least squares and its modifications for GLM; model selection; regularization; data reduction techniques (PCA, ICA, factor analysis). (materials) Statistics IV: Local Regression and Likelihood: Bokil (Tuesday afternoon) Topics: Local regression, local likelihood, local likelihood-based density estimation (materials) Statistics V: Adaptive Splines: Kass (Tuesday afternoon) Topics: The problem of nonparametric regression; spline fitting; Bayesian adaptive regression splines. (materials) Tutorial: Locfit: Bokil (Tuesday evening) Topics: Locfit - Use of the locfit component of Chronux for doing local regression and likelihood-based analyses (materials) Tutorial: Linear Models, PCA: Iyengar (Tuesday evening) Topics: (materials) |
| Wednesday 20 |
Inference and classification with spectral feature vectors: Pesaran (Wednesday morning)
Topics: (materials) Nonstationary Spectral Analysis: Bokil (Wednesday morning) Topics: Spectrograms and coherograms, spectral derivatives, non-stationarity test, higher order correlations (materials) Point Processes II: Eden (Wednesday afternoon) Topics: (materials) Point Processes III: Sarma (Wednesday afternoon) Topics: (materials) Tutorial: Point Process Estimation: Sarma, Eden (Wednesday evening) Topics: (materials) Tutorial: Nonstationary Spectral Analysis; Inference/Classification: Pesaran, Bokil (Wednesday evening) Topics: (materials) |
| Thursday 21 |
Multichannel Time Series I: Electrophysiological data: Pesaran (Thursday morning)
Topics: SVD in time and frequency domains (materials) Multichannel Time Series II: Optical Imaging Data: Sornborger (Thursday morning) Topics: (materials) fMRI time series analysis I: Analysis techniques: Bohland (Thursday afternoon) Topics: Noise sources, data conditioning, harmonic analysis, statistical parametric mapping, multiple comparisons (materials) fMRI time series analysis II: Software platforms: Bohland (Thursday afternoon) Topics: Comparison and examples using available software tools for fMRI analysis (materials) Tutorial: Multichannel electrophysiological data: Pesaran (Thursday evening) Topics: (materials) Tutorial: Optical imaging data: Sornborger (Thursday evening) Topics: (materials) |
| Friday 22 |
Prosthetics I: Continuous process readout algorithms: Pesaran (Friday morning)
Topics: Prosthetics and decoding: Linear decoders (materials) Prosthetics II: Point process readout algorithms: Sarma, Eden (Friday morning) Topics: Prosthetics and decoding: Nonlinear filtering methods (materials) Quantifying Behavior: Mice, Fruitflies: Golani (Friday afternoon) Topics: Computational analysis of locomotor and exploratory behavior of small animals. Data acquisition, data preparation for analysis (smoothing, segmentation), a dynamic developmental dissection of behavior. Measurement of exploratory behavior in mice and locomotor behavior in fruit flies. (materials) Entropy and Mutual Information Estimation: Lecture and Tutorial: Victor (Friday evening) Topics: Various methods of estimating entropy and mutual information for spike trains. (materials) |
| Saturday 23 |
Spike Sorting I: Harris, Hill (Saturday morning)
Topics: (materials) Spike Sorting II: Harris, Hill (Saturday morning) Topics: (materials) Spike Sorting Lab: Harris, Hill (Saturday afternoon) Topics: (materials) |
| Monday 25 |
Neuroanatomy I: Experimental methods; brain architecture.: Barbas (Monday morning)
Topics: A survey of classical neuroanatomy in model organisms; Techniques; basic architectural features; computational challenges. (materials) Neuroanatomy II: Human brain atlases: Bohland (Monday morning) Topics: Classical and MRI atlases of the human brain, neuroanatomical nomenclatures, inter-subject registration, brain parcellation, and concordance between atlases. (materials) TBA: Richmond (Monday evening) Topics: (materials) Surface-based approaches to analyzing cortical structure and function: Van Essen (Monday afternoon) Topics: (materials) Neuroinformatics resources on the web: Van Essen (Monday afternoon) Topics: (materials) Demo and Tutorial: Bohland (Monday evening) Topics: (materials) Surface-based morphometry using Caret software: Van Essen (Monday evening) Topics: (materials) |
| Tuesday 26 |
Databases: Lin (Tuesday afternoon)
Topics: Relational database fundamentals: the ER model, relational databases, how to design schemas, etc. Introduction to mySQL (to be followed by a laboratory session in the evening, using mySQL-Matlab with a concrete neural signals based dataset). (materials) Allen Gene Expression Atlas: Hawrylycz (Tuesday afternoon) Topics: An introduction to semantic web and knowledge engineering concepts. (materials) Databases Tutorial: Lin, Bohland (Tuesday evening) Topics: (materials) |
| Wednesday 27 |
Machine Learning I: Niyogi (Wednesday morning)
Topics: Introduction to kernel methods, reproducing kernel Hilbert spaces (materials) Machine Learning II: Niyogi (Wednesday morning) Topics: Regularized least squares, support vector machines, kernel PCA (materials) EEG: Schiff (Wednesday afternoon) Topics: (materials) |
| Thursday 28 |
Computational Neuroanatomy: I: Whitaker (Thursday afternoon)
Topics: Image segmentation, nonlinear diffusion equations (materials) Computational Neuroanatomy: II: Zikopoulos (Thursday afternoon) Topics: Image reconstruction (materials) Tutorial: Computational Neuroanatomy: Zikopoulos (Thursday afternoon) Topics: (materials) Banquet, Party: (Thursday evening) |