Bias-free estimation of information content in temporally sparse neuronal activity
Fig 2
Limited sample sizes and temporally sparse neuronal activity positively bias the naïve calculation of information content.
(A) Top: Neuronal activity (red) of four example cells overlaid on the mouse trajectory (cyan) during rightward running epochs in the linear track. Inset, the full mouse trajectory during 200 seconds in the linear track, with the rightward running epochs marked in cyan. Middle: Tuning curves of the same example cells, and their naïve SI expressed in bit/spike. Bottom: The naïve SI (blue) and distribution of shuffle SI (black) of the same cells. Note that the naïve SI of a cell with significant place tuning and high firing rates (cell 2) is lower than that of a cell without significant place tuning and with low firing rates (cell 4). (B) Naïve SI (mean ± SD) as a function of the sample duration for real (blue) and shuffled (black) data. Inset, entropy of the mouse position (mean ± SD) as a function of sample duration. (C-D) The naïve SI (mean ± SD) as a function of the average firing rate (C) or number of active time bins (D) for real (blue) and shuffled (black) data. Data in B-D were averaged across N = 9 mice. For each mouse, SI was averaged across the last four imaging sessions in each of the two environments when they are familiar (a total of 740–4,003 place cells per mouse).