- Solving linear systems of equations
- Pseudo-inverse calculation
- Sparsest and Least Norm solutions to a linear system
- Calculation of common statistics
- Confidence Interval and Standard Error calculation
- Resampling methods: Bootstrapping and Jackknifing
- Reverse inference via Bayesian Statistics
- Multivariate Normal Distribution
- Standard Deviational Ellipse
- Neuroelectronics
- Leaky Integrate-and-Fire Neuron Model
- Spike Triggerred Average (STA)
- Lateral Geniculate Nuclei cells and their Neural Activity
- Analysis of Neural Response
- Difference of Gaussians center-surround receptive fields
- Gabor receptive fields
- Image processing and Convolution
- Ordinary Least Squares
- Linear & Higher Order Linearized Models
- Parametric & Nonparametric Nonlinear Models
- Maximum Likelihood Estimator
- Ridge Regression
- Cross Validation
- Hypothesis Testing
- Principal Component Analysis (PCA)
- Independent Component Analysis (ICA)
- Nonnegative Matrix Factorization (NNMF)
- Classical Multi-dimensional Scaling (CMDS)
- k-means Clustering
- Winner Take All Decoder
- Maximum Likelihood Decoder
- Maximum-a-Posteriori Decoder
- Linear Discriminant Analysis (LDA) Based Classifer
- Task: Building a decoder that can map fMRI brain activity to the actual visual stimulus category.
- Note: Data used in the projects is very large so it is not provided here, however the data can be downloaded from:
-> must be named data
-> must be named haxby - Teammates: Hygerta Imeri, Utku Gorkem Erturk