dorsal/arxiv
View SchemaTiming and Counting Precision in the Blowfly Visual System
| Authors | Rob de Ruyter van Steveninck, William Bialek |
|---|---|
| Categories | |
| ArXiv ID | physics/0202014 |
| URL | https://arxiv.org/abs/physics/0202014 |
| Journal | In: Methods in Neural Networks IV (J. van Hemmen, J.D. Cowan, E. Domany, eds.). Springer Verlag, Heidelberg, New York, 2001, pp 313-371 |
Abstract
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.
{
"annotation_id": "469c8b57-1bc5-4742-bb06-af01d4c081ea",
"date_created": "2026-03-02T18:00:39.774000Z",
"date_modified": "2026-03-02T18:00:39.774000Z",
"file_hash": "24e3e83cc06edfbc902f8e16873cbad29a9f6e89ab1920fd415413b5b904b48d",
"private": false,
"record": {
"abstract": "We measure the reliability of signals at three levels within the blowfly\nvisual system, and present a theoretical framework for analyzing the\nexperimental results, starting from the Poisson process. We find that blowfly\nphotoreceptors, up to frequencies of 50-100 Hz and photon capture rates of up\nto about 3*10^5/s, operate well within an order of magnitude from ideal photon\ncounters. Photoreceptors signals are transmitted to LMCs through an array of\nchemical synapses. We quantify a lower bound on LMC reliability, which in turn\nprovides a lower bound on synaptic vesicle release rate, assuming Poisson\nstatistics. This bound is much higher than what is found in published direct\nmeasurements of vesicle release rates in goldfish bipolar cells, suggesting\nthat release statistics may be significantly sub-Poisson. Finally we study H1,\na motion sensitive tangential cell in the fly\u0027s lobula plate, which transmits\ninformation about a continuous signal by sequences of action potentials. In an\nexperiment with naturalistic motion stimuli performed on a sunny day outside in\nthe field, H1 transmits information at about 50% coding efficiency down to\nmillisecond spike timing precision. Comparing the measured reliability of H1\u0027s\nresponse to motion steps with the bounds on the accuracy of motion computation\nset by photoreceptor noise, we find that the fly\u0027s brain makes efficient use of\nthe information available in the photoreceptor array.",
"arxiv_id": "physics/0202014",
"authors": [
"Rob de Ruyter van Steveninck",
"William Bialek"
],
"categories": [
"physics.bio-ph",
"q-bio.NC"
],
"journal_ref": "In: Methods in Neural Networks IV (J. van Hemmen, J.D. Cowan, E.\n Domany, eds.). Springer Verlag, Heidelberg, New York, 2001, pp 313-371",
"title": "Timing and Counting Precision in the Blowfly Visual System",
"url": "https://arxiv.org/abs/physics/0202014"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "56f2b4af-e488-4c1c-ad14-01e9a7dd3582",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}