![]() Therefore, choice of place cell detection method dramatically affects the number and properties of identified cells. In real datasets, vastly different numbers of place cells were identified using the four methods, with little overlap between the populations identified as place cells. The methods performed differently from each other on both model and real data. These methods use different parameters to identify place cells, including the peak activity in the place field, compared to other locations (the Peak method) the stability of cells’ activity over repeated traversals of an environment (Stability method) a combination of these parameters with the size of the place field (Combination method) and the spatial information held by the cells (Information method). Here we tested four methods that have previously been applied to two-photon hippocampal imaging or electrophysiological data, using both model datasets and real imaging data. ![]() Several methods have been proposed as a means to identify place cells based on their calcium activity but there is no common standard and it is unclear how reliable different approaches are. Historically most studies of these neurons have used electrophysiological recordings from implanted electrodes but optical methods, measuring intracellular calcium, are becoming increasingly common. Place cells, spatially responsive hippocampal cells, provide the neural substrate supporting navigation and spatial memory. (L) Effect of gaussian smoothing of tuning maps on decoding error in the open field. The red arrow indicates the temporal filtering window size yielding the lower decoding error. (K) Effect of temporal filtering on decoding error in the open field. (J) Scatter plot comparing the standard-deviation of the shuffled distribution, and the mouse open field occupancy. (I) Standard-deviation of the shuffled distribution. (H) Thresholded place field using only significant P(active| state) values. (G) P-value computed from the actual tuning map and corresponding shuffled surrogates. (F) Posterior probability P(state| active) for the same cell. (E) Example tuning maps computed from shuffled calcium traces. (D) Tuning map (probability of being active given location) of one neuron. (C) Relative occupancy in the open field. (B) Top view of mouse trajectory (beige trace) with overlaid location corresponding to neuronal activity (green, early activity magenta, late activity). (A) x,y coordinates of mouse location in an open field (bottom) and corresponding raw calcium trace of one example cell and binarized activity (top).
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