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Lansdell, B.

Publications and source records attributed to Lansdell, B..

2 recordsLinked to original sources

Tracking Activity In A Deformable Nervous System With Motion Correction And Point-Set Registration

The combination of fluorescent probes with time-lapse microscopy allows for the visualization of the entire neuronal activity of small animals, such as worms or cnidarians, over a long period of time. However, large deformations of the animal combined with the natural intermittency of neuronal activity make robust automated tracking of firing fluorescent neurons challenging. Here we present an hybrid approach where (i) a subset of very bright neurons is used as moving reference points (fiducials) to estimate the elastic deformation of the animal; (ii) deformation is frame-by-frame corrected, and firing neurons are aligned at each time with the initial mask; and (iii) point-set registration is used to robustly track the intermittent activity of all the immobilized neurons. We compare different registration strategies with manual tracking performed over {approx}620 neurons over 100 time frames in the cnidarian Hydra vulgaris.\n\nIndex TermsFluorescence imaging, wavelet detection, tracking, point-set registration, elastic deformation, Thin Plate Spline (TPS) transform, Coherent Point Drift (CPD), Hydra.

neuroscience

Spiking allows neurons to estimate their causal effect

When a neuron is driven beyond its threshold it spikes, and the fact that it does not communicate its continuous membrane potential is usually seen as a computational liability. Here we show that this spiking mechanism allows neurons to produce an unbiased estimate of their causal influence, and a way of approximating gradient descent learning. Importantly, neither activity of upstream neurons, which act as confounders, nor downstream non-linearities bias the results. By introducing a local discontinuity with respect to their input drive, we show how spiking enables neurons to solve causal estimation and learning problems.

neuroscience