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Abstract:
Two photon calcium imaging in vivo allows for the simultaneous imaging of activity in
populations of cortical neurons. This approach has been shown to achieve both single
action potential (AP) and single cell resolution, an important requirement when measuring
neural activity. However, there still remains room for improvement in both data
acquisition and data analysis. Imaging calcium transients across time allows the inference
of electrical spiking activity, but since the calcium signals are an order of magnitude slower
than the spiking activity which produces them, temporal accuracy can be lost. Here we
describe a possible approach to increase the temporal resolution of such data. We present
an approach that explicitly models signal and noise in the data, and complements the
output of a previous spike detection algorithm. Instead of averaging the signal over 96 ms
(a full frame), we employ higher resolution that averages over 1.5 ms periods, corresponding
to the individual laser scan lines that compose a single image frame. The dierence
between theoretical and observed
uorescence measurements is modeled as a multivariate
Gaussian distribution with zero mean, yielding a likelihood value for each possible spike
time over a two frame window. Taking into account the prior distribution of timing errors
in the output of our AP detection algorithm, we estimate the detected spike's most likely
position. This approach improves temporal resolution signicantly compared to previous
methods. We discuss the future development of this approach, its limitations, and the
crucial role of an accurate estimation of baseline
uorescence.
