Are single-peaked tuning curves tuned for speed rather than accuracy?
According to the efficient coding hypothesis, sensory neurons are adapted to provide maximal information about the environment, given some biophysical constraints. In early visual areas, stimulus-induced modulations of neural activity (or tunings) are predominantly single-peaked. However, periodic tuning, as exhibited by grid cells, has been linked to a significant increase in decoding performance. Does this imply that the tuning curves in early visual areas are sub-optimal? We argue that the time scale at which neurons encode information is imperative to understanding the advantages of single-peaked and periodic tuning curves. Here, we show that the possibility of catastrophic (large) errors creates a trade-off between decoding time and decoding ability. We investigate how decoding time and stimulus dimensionality affect the optimal shape of tuning curves for removing catastrophic errors. In particular, we focus on the spatial periods of the tuning curves for a class of circular tuning curves. We show an overall trend for minimal decoding time to increase with increasing Fisher information, implying a trade-off between accuracy and speed. This trade-off is reinforced whenever the stimulus dimensionality is high, or there is ongoing activity. Thus, given constraints on processing speed, we present normative arguments for the existence of the single-peaked tuning organization observed in early visual areas.
Code has been made publicly available on Github (https://github.com/movitzle/Short_Decoding_Time)
Article and author information
- Movitz Lenninger
- Mikael Skoglund
- Pawel Andrzej Herman
- Arvind Kumar
- Arvind Kumar
Institute of Advanced Studies Fellowship, University of Strasbourg, France
- Arvind Kumar
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Peter Latham, University College London, United Kingdom
- Received: October 28, 2022
- Accepted: May 11, 2023
- Accepted Manuscript published: May 16, 2023 (version 1)
© 2023, Lenninger et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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