Arduino code

EDShiftLight_BL: Runs any variant of the set-shifting task, including functionality for simple discrimination, compound discrimination, intra-dimensional shift (whisker and/or odor cues), reversal learning, extradimentional shifting, and serial shifting.

lickDispense: A script for habituation. Dispenses liquid rewards in response to spout licks with brief, randomized refractory periods.

recordBehaviorBin: Streams data from an Arduino board by packaging binary data (bits) into 8-character bytes for serial port collection.

Matlab code

brainAxes: An annotatable brain atlas navigator, for use with the Allen Institute's Common Coordinate Framework.

taskClassify_MultiSets: Performs iterative, cross-validated classification in labeled data using support vector machines. Handles multiple data sets of varying sizes, equalizes observation numbers across classes, returns mean classifier accuracy, beta-weights and confidence intervals.

imageProcessing4D: Assembles 4D videos from sequences of volumetric tiff stacks, with options for motion correction, down-sampling, minimum subtraction, and contrast/brightness modulation.

FourGoalTmaze_Running: Matlab code for controlling a 4-goal T-maze.

fibonacciKStep: Uses the Fibonacci sequence to estimate the probability of observing k binary outcomes in a row from n obervations. Useful for evaluating the results of binary-choice behavioral testing.

bassToneGenerator2: Generates wav files of specified frequency and temporal modulation as stimuli for behavioral testing (auditory, whisker somatosensory).

animateDots: Generates stochastic fields of horizontally and vertically moving dots for visual psychometric tasks.

Tree2: Draws random trees.

randomWalk: Traces out a k-step random walk.

seeThruScatter: Creates a scatter plot with semi-transparent dots in case of overlap. Also fits a regression line.

tim_coreg_resave: Manually co-register cell masks/ROIs across sessions.

sortByCovar2: Takes time series (e.g. calcium imaging traces) and sorts by paired similarity as measured by covariance. Displays as thresholded, rasterized event markers.