Computations that sustain neural feature selectivity across processing stages

Ryan J Rowekamp and Tatyana O Sharpee

PLOS Computational Biology, 2025, vol. 21, issue 6, 1-23

Abstract: Biological visual systems are celebrated for their ability to reliably and precisely recognize objects. However, the specific neural mechanisms responsible for this capability remain largely elusive. In this study, we investigate neural responses in the visual areas V1, V2, and V4 of the brain to natural stimuli using a framework that includes quadratic computations in order to capture local recurrent interactions, both excitatory and suppressive. We find that these quadratic computations and specific coordination between their elements strongly increase both the predictive power of the model and the neural selectivity to natural stimuli. Particularly important were (i) coordination between excitatory and suppressive features to represent mutually exclusive hypotheses regarding incoming stimuli, such as orthogonal orientations or opposing motion directions in area V4, (ii) balance in the contribution of excitatory and suppressive components and its maintenance at similar levels across stages of processing, and (iii) refinement of feature selectivity between stages, with earlier stages representing broader category of inputs. Overall, this work describes how the brain could use multiple nonlinear mechanisms to increase selectivity of neural responses to natural stimuli.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013075 (text/html)
https://journals.plos.org/ploscompbiol/article/fil ... 13075&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1013075

DOI: 10.1371/journal.pcbi.1013075

Access Statistics for this article

More articles in PLOS Computational Biology from Public Library of Science
Bibliographic data for series maintained by ploscompbiol ().