Name
Abstract | ||
|---|---|---|
We develop a model-independent method for characterizing the reliability of neural responses to brief stimuli. This approach allows us to measure the discriminability of similar stimuli, based on the real-time response of a single neuron. Neurophysiological data were obtained from a movement(cid:173) sensitive neuron (HI) in the visual system of the blowfly Calliphom ery(cid:173) throcephala. Furthermore, recordings were made from blowfly photore(cid:173) ceptor cells to quantify the signal to noise ratios in the peripheral visual system. As photoreceptors form the input to the visual system, the reli(cid:173) ability of their signals ultimately determines the reliability of any visual discrimination task. For the case of movement detection, this limit can be computed, and compared to the HI neuron's reliability. Under favor(cid:173) able conditions, the performance of the HI neuron closely approaches the theoretical limit, which means that under these conditions the nervous system adds little noise in the process of computing movement from the correlations of signals in the photoreceptor array. |
Year | Venue | Field |
|---|---|---|
1991 | ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 4 | H1 neuron,Neuroscience,Reliability (statistics),Neurophysiology,Computer science,Signal-to-noise ratio,Movement detection,Nervous system,Artificial intelligence,Stimulus (physiology),Neuron,Machine learning |
DocType | Volume | Citations |
Conference | 4 | 0 |
PageRank | References | Authors |
0.34 | 2 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert R. De Ruyter Van Steveninck | 1 | 9 | 2.31 |
| Bialek, William | 2 | 800 | 194.81 |