Analysis of calcium imaging signals from the honeybee brain by nonlinear models

Recent Ca2+-imaging studies on the antennal lobe of the honeybee (Apis mell ifera) have shown that olfactory stimuli evoke complex spatiotemporal chang es of the intracellular Ca2+ concentration, in which stimulus-dependent sub sets of glomeruli are highlighted. In this work we use nonlinear models for the quantitative identification of the spatial and temporal properties of the Ca2+-dependent fluorescence signal. This technique describes time serie s of the Ca2+ signal as a superposition of biophysically motivated model fu nctions for photobleaching and Ca2+ dynamics and provides optimal estimates of their amplitudes (signal strengths) and time constants together with er ror measures. Using this method, we can reliably identify two different sti mulus-dependent signal components. Their delays and rise times, delta (c1) = (0.4 +/- 0.3) s, tau (c1) = (3.8 +/- 1.2) s for the fast component and de lta (c2) = (2.4 +/- 0.6) s, tau (c2) = (10.3 +/- 3.2) s for the slow compon ent, are constant over space and across different odors and animals. In chr onological experiments, the amplitude of the fast (slow) component often de creases (increases) with time. The pattern of the Ca2+ dynamics in space an d time can be reliably described as a superposition of only two spatiotempo rally separable patterns based on the fast and slow components. However, th e distributions of both components over space turn out to differ from each other, and more work has to be done in order to specify their relationship with neuronal activity. (C) 2001 Academic Press.