arXiv subjects

Rob de Ruyter van Steveninck

Publications and source records attributed to Rob de Ruyter van Steveninck.

3 recordsLinked to original sources

arXiv2004

Entropy and information in neural spike trains: Progress on the sampling problem

The major problem in information theoretic analysis of neural responses and other biological data is the reliable estimation of entropy--like quantities from small samples. We apply a recently introduced Bayesian entropy estimator to synthetic data inspired by experiments, and to real experimental spike trains. The estimator performs admirably even very deep in the undersampled regime, where other techniques fail. This opens new possibilities for the information theoretic analysis of experiments, and may be of general interest as an example of learning from limited data.

physics.data-an↗

arXiv2002

Timing and Counting Precision in the Blowfly Visual System

We measure the reliability of signals at three levels within the blowfly visual system, and present a theoretical framework for analyzing the experimental results, starting from the Poisson process. We find that blowfly photoreceptors, up to frequencies of 50-100 Hz and photon capture rates of up to about 3*10^5/s, operate well within an order of magnitude from ideal photon counters. Photoreceptors signals are transmitted to LMCs through an array of chemical synapses. We quantify a lower bound on LMC reliability, which in turn provides a lower bound on synaptic vesicle release rate, assuming Poisson statistics. This bound is much higher than what is found in published direct measurements of vesicle release rates in goldfish bipolar cells, suggesting that release statistics may be significantly sub-Poisson. Finally we study H1, a motion sensitive tangential cell in the fly's lobula plate, which transmits information about a continuous signal by sequences of action potentials. In an experiment with naturalistic motion stimuli performed on a sunny day outside in the field, H1 transmits information at about 50% coding efficiency down to millisecond spike timing precision. Comparing the measured reliability of H1's response to motion steps with the bounds on the accuracy of motion computation set by photoreceptor noise, we find that the fly's brain makes efficient use of the information available in the photoreceptor array.

physics.bio-ph↗

arXiv2000

Real time encoding of motion: Answerable questions and questionable answers from the fly's visual system

In the past decade, a small corner of the fly's visual system has become an important testing ground for ideas about coding and computation in the nervous system. A number of results demonstrate that this system operates with a precision and efficiency near the limits imposed by physics, and more generally these results point to the reliability and efficiency of the strategies that nature has selected for representing and processing visual signals. A recent series of papers by Egelhaaf and coworkers, however, suggests that almost all these conclusions are incorrect. In this contribution we place these controversies in a larger context, emphasizing that the arguments are not just about flies, but rather about how we should quantify the neural response to complex, naturalistic inputs. As an example, Egelhaaf et al. (and many others) compute certain correlation functions and use the apparent correlation times as a measure of temporal precision in the neural response. This analysis neglects the structure of the correlation function at short times, and we show how to analyze this structure to reveal a temporal precision 30 times better than suggested by the correlation time; this precision is confirmed by a much more detailed information theoretic analysis. In reviewing other aspects of the controversy, we find that the analysis methods used by Egelhaaf et al. suffer from some mathematical inconsistencies, and that in some cases we are unable to reproduce their experimental results. Finally, we present results from new experiments that probe the neural response to inputs that approach more closely the natural context for freely flying flies. These new experiments demonstrate that the fly's visual system is even more precise and efficient under natural conditions than had been inferred from our earlier work.

physics.bio-ph↗