Work

Network Connections That Evolve to Circumvent the Inverse Optics Problem

Year: 2013

Type: article

Abstract: A fundamental problem in vision science is how useful perceptions and behaviors arise in the absence of information about the physical sources of retinal stimuli (the inverse optics problem). Psychophysical studies show that human observers contend with this problem by using the frequency of occurrence of stimulus patterns in cumulative experience to generate percepts. To begin to understand the neural mechanisms underlying this strategy, we examined the connectivity of simple neural networks evolved to respond according to the cumulative rank of stimulus luminance values. Evolved similarities with the connectivity of early level visual neurons suggests that biological visual circuitry uses the same mechanisms as a means of creating useful perceptions and behaviors without information about the real world.

Source: PLoS ONE

DOI: 10.1371/journal.pone.0060490

Authors: Cherlyn Ng, Janani Sundararajan, Michael Hogan, Dale Purves

Institutions: National University of Singapore, Duke-NUS Medical School, Duke University, Duke Medical Center

Language: English

Topic: Visual perception and processing mechanisms

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,382

Funder: Duke-NUS Medical School