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Methodology for extracting activity from functional calcium imaging data
BMC Neuroscience volume 13, Article number: P173 (2012)
Functional calcium imaging is a widespread technique used to measure the activity of multiple cells at a time. Because the activity traces from this data collection technique are noisy, we have developed a new method for extraction of activity episodes from the fluorescence traces. While Gaussian filters are commonly used for smoothing data, this technique alters the frequency of the activity episodes, so instead Butterworth filters are employed. We plotted the spectrograms of individual traces and visually determined the cutoff frequency that would remove the high-frequency noise. After smoothing (Figure 1A), we identify local minima by taking a modified first derivative and then calculating the second derivative from this trace (Figure 1B). Local minima are then selected as activity episodes based on their corresponding first derivative values (Figure 1C). These activity locations are then used in the calculations for frequency of activity episodes. This method has several advantages for use with calcium data: (1) it is independent of the amplitude of the bursts; (2) the function is robust to drift in the trace; (3) the parameters are easily changed to adapt to ground truth data under differing experimental conditions.
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Del Giorno, A., Toporikova, N., Mellen, N. et al. Methodology for extracting activity from functional calcium imaging data. BMC Neurosci 13 (Suppl 1), P173 (2012). https://doi.org/10.1186/1471-2202-13-S1-P173
- Animal Model
- Local Minimum
- Imaging Data
- Cutoff Frequency