  An optical flow gradient algorithm was applied to spontaneously forming net-
works of neurons and glia in culture imaged by fluorescence optical microscopy
in order to map functional calcium signaling with single pixel resolution.
Optical flow estimates the direction and speed of motion of objects in an image
between subsequent frames in a recorded digital sequence of images (i.e. a
movie). Computed vector field outputs by the algorithm were able to track the
spatiotemporal dynamics of calcium signaling pat- terns. We begin by briefly
reviewing the mathematics of the optical flow algorithm, and then describe how
to solve for the displacement vectors and how to measure their reliability. We
then compare computed flow vectors with manually estimated vectors for the
progression of a calcium signal recorded from representative astrocyte
cultures. Finally, we applied the algorithm to preparations of primary
astrocytes and hippocampal neurons and to the rMC-1 Muller glial cell line in
order to illustrate the capability of the algorithm for capturing different
types of spatiotemporal calcium activity. We discuss the imaging requirements,
parameter selection and threshold selection for reliable measurements, and
offer perspectives on uses of the vector data.
