Basics of Programming (Thurs. / Fri.; Springer)

• Reading a line of code
• Variables – x=2
• Entering
• Retrieving
• Mathematical Operations + - * / ^
• Order of Operations
• Arrays
• Visualizing
• Retrieving Values
• Altering Values
• Basic Functions – Analyzing a dataset
• Length, size
• Mean, median, standard deviation
• Sort
• Functions of 2D arrays
• Entering Arrays
• Bracket operator
• Colon operator
• Comma semicolon
• Conditional Retrieval
• >
• find
• Ploting
• 2D: colors, lines, labels
• 3D
• Scripts
• Conditional States and Control Flow
• For loops
• If, Elseif, Else
• !, ==, >, <, >=
• Or and And (| || & &&)
• While
• Counters
• Cell Arrays
• Entering
• Retrieving
• fieldnames
• Function
• Simple functions
• Scope
• Data Structures
• Strings – dealing with text and mixed data
• Parsing data

Statistics with MATLAB (Monday, AM; Born)

• Rattus binomialis: When is he guessing?
• all you need is 'rand'
• simulations and probability
• 'for' loops
• tricky indexing into arrays
• 'tic' and 'toc' to time code execution
• binomial distribution
• pdf's and cdf's

• Bootstrap Bill: Statistics for the common man
• operations along columns of 2D matrix
• use of 'repmat'
• simple descriptive statistics: mean, median, standard error
• plotting functions: 'plot', 'errorbar', 'polar'
• handle graphics
• bootstrapping: null hypothesis; permutation test; confidence intervals

• Sorting spikes: The joys of dimensionality reduction
• thresholding to find peaks in data
• using 'diff' to find events in continuous data
• PCA/SVD to reduce dimensionality of data
• 3D plotting
• ISI histograms

Image Processing I: Computer Processing (Monday, PM; Springer)

• Visualizing an image in MATLAB
• displaying images –imshow, imagesc, surf
• data types – double, mat2gray
• Manipulating Pixels
• Background Subtraction
• Rescaling
• Transform – e.g. log

• Manipulating Field of pixels – Filters
• Intensity Preserving
• Smoothing Filters
• Non-Intensity Preserving
• Contrast
• Vertical Lines
• Horizontal Lines
• Edges
• Contrast – Laplacian
• Laplacian of Gaussian (LoG)

Image Processing II: Images and Your Brain (Tuesday, AM; Born)

• Horace Barlow: Image Statistics and "Suspicious Coincidences"
• histograms and probability density functions
• nearby pixels are similar: correlation with 'corrcoef'
• center-surround: LoG and 'imfilter'
• orientation selectivity: finding "suspicious coincidences with 'colfilt'

• David Marr: Where's Abe?
• image manipulation: blkproc
• edge detection: LoG and thresholding
• image filtering in the frequency domain: 'fft2', 'ifft2'
• band-rejection filters
• zero-crossings and the "raw primal sketch"
• better recognition through subtraction

Image Processing III: Segmentation

• Finding cells or features
• Thresholding
• Bwlabel
• Cleaning up the features – imopen, imclose, imerode imdialate
• Quantitating Cell
• Regionprops
• Extracting values from pixels

Modeling with SIMBIOLOGY

(Tuesday, PM; Springer)