A Neural Computation for Visual Acuity in the Presence of Eye Movements
Abstract
Humans can distinguish visual stimuli that differ by features the size of only a few photoreceptors. This is possible despite the incessant image motion due to fixational eye movements, which can be many times larger than the features to be distinguished. To perform well, the brain must identify the retinal firing patterns induced by the stimulus while discounting similar patterns caused by spontaneous retinal activity. This is a challenge since the trajectory of the eye movements, and consequently, the stimulus position, are unknown. We derive a decision rule for using retinal spike trains to discriminate between two stimuli, given that their retinal image moves with an unknown random walk trajectory. This algorithm dynamically estimates the probability of the stimulus at different retinal locations, and uses this to modulate the influence of retinal spikes acquired later. Applied to a simple orientation-discrimination task, the algorithm performance is consistent with human acuity, whereas naive strategies that neglect eye movements perform much worse. We then show how a simple, biologically plausible neural network could implement this algorithm using a local, activity-dependent gain and lateral interactions approximately matched to the statistics of eye movements. Finally, we discuss evidence that such a network could be operating in the primary visual cortex.
Additional Information
© 2007 Pitkow et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received March 27, 2007; Accepted November 9, 2007; Published December 27, 2007. The authors thank Ralf Engbert and Reinhold Kliegl for their eye movement data, and Daniel Fisher, Maneesh Sahani, and an anonymous referee for helpful conversations and suggestions. Author Contributions: XP, HS, and MM conceived and designed the experiments, analyzed the data, and wrote the paper. XP performed the experiments. XP and MM were supported by a National Institutes of Health grant. The work of HS was partially supported by a grant of the US-Israel Binational Science Foundation. The authors have declared that no competing interests exist.Attached Files
Published - journal.pbio.0050331.PDF
Supplemental Material - journal.pbio.0050331.sd001.PDF
Files
Name | Size | Download all |
---|---|---|
md5:67357dd1dfc1af20e77ee71c72ba65b4
|
1.2 MB | Preview Download |
md5:6547601425de69ea90d920fc14d46b81
|
638.2 kB | Preview Download |
Additional details
- PMCID
- PMC2222970
- Eprint ID
- 75725
- Resolver ID
- CaltechAUTHORS:20170405-083802627
- NIH
- Binational Science Foundation (USA-Israel)
- Created
-
2017-04-05Created from EPrint's datestamp field
- Updated
-
2021-11-15Created from EPrint's last_modified field