Encoding of mixtures in a simple olfactory system

Datasets Spike times from two sets of experiments were analyzed in the paper and have been provided here. Spike Times The spike times provided in `data/spt` are matrices in 'toc' (trials-odors-cells) format: Each column contains the spikes times of the response of one cell in one trial to one odor. The columns are arranged by iterating over trials, then odors, then cells.

For example, if there are T trials, R odors, and C cells, Columns 1 to T are the response of cell 1 to odor 1 in consecutive trials, Columns T+1 to 2T are its response to odor 2, Columns (R-1)T + 1 to RT are its response to odor R, Column RT+1 is the response of cell 2 to the first trial of odor 1, and so on. Equivalently, if A is a 4-D matrix such that A(n,i,j,k) is the time of the n'th spike in the response in trial i of odor j of cell k, then Atoc = reshape(A, [], T

• R *C); A = reshape(Atoc, [], T, R, C); The columns of the the toc matrices contain the actual spike times. If a cell produced fewer spikes than the length of the column, the remainder of the column is set to zero. This could in principle be problematic if cells also tend to produce spikes at exactly t = 0, but this is very rare because odor onset is at t = 2.0 seconds and the baseline period is long (> 10 seconds). The function `ConvertSpikeTimesFromSparseToFull` converts the sparse matrices to full by setting the 0 elements to -Inf.