Dynamic and geometric analysis of short time series: a new comparative approach to cell-based biosensors

This Letter describes two approaches for sensing changes in spiking cells w hen only a limited amount of spike data is available. The first method dete cts changes in dynamically constructed local expansion rates, and the other uses spike area distributions. These two methods were tested on time serie s from cultured neurons. Over-sampled data was generated from experiments o n single cells before and after being treated with a small concentration of channel blocker, but relatively few spikes were recorded. In the spontaneo usly spiking cells, the local expansion rates showed a sensitivity that cor related with the channel concentration level, while the driven cells showed no such correlation. Spike area distributions showed measurable difference s between control and treated conditions for both types of spiking, and a m uch higher degree of sensitivity. Because these methods are based on analys is of short time series analysis, they might provide novel means for cell d rug and toxin detection. Published by Elsevier Science B.V.