Automatic identification of fluorescently labeled brain cells for rapid functional imaging.
JOURNAL OF NEUROPHYSIOLOGY(2010)
Abstract
Valmianski I, Shih AY, Driscoll JD, Matthews DW, Freund Y, Kleinfeld D. Automatic identification of fluorescently labeled brain cells for rapid functional imaging. J Neurophysiol 104: 1803-1811, 2010. First published July 14, 2010; doi: 10.1152/jn.00484.2010. The on-line identification of labeled cells and vessels is a rate-limiting step in scanning microscopy. We use supervised learning to formulate an algorithm that rapidly and automatically tags fluorescently labeled somata in full-field images of cortex and constructs an optimized scan path through these cells. A single classifier works across multiple subjects, regions of the cortex of similar depth, and different magnification and contrast levels without the need to retrain the algorithm. Retraining only has to be performed when the morphological properties of the cells change significantly. In conjunction with two-photon laser scanning microscopy and bulk-labeling of cells in layers 2/3 of rat parietal cortex with a calcium indicator, we can automatically identify similar to 50 cells within 1 min and sample them at similar to 100 Hz with a signal-to-noise ratio of similar to 10.
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Key words
somatosensory cortex
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