Uncomfortable images produce non-sparse responses in a model of primary visual cortex.

Paul B Hibbard,Louise O'Hare

doi:10.1098/rsos.140535

Abstract

The processing of visual information by the nervous system requires significant metabolic resources. To minimize the energy needed, our visual system appears to be optimized to encode typical natural images as efficiently as possible. One consequence of this is that some atypical images will produce inefficient, non-optimal responses. Here, we show that images that are reported to be uncomfortable to view, and that can trigger migraine attacks and epileptic seizures, produce relatively non-sparse responses in a model of the primary visual cortex. In comparison with the responses to typical inputs, responses to aversive images were larger and less sparse. We propose that this difference in the neural population response may be one cause of visual discomfort in the general population, and can produce more extreme responses in clinical populations such as migraine and epilepsy sufferers.

Highlights

The high metabolic cost of neural computation means that it is only possible for a small fraction of cortical neurons to be active at any one time
We show that images that create discomfort, and that can trigger epileptic seizures [14] and migraine attacks [15], produce relatively non-sparse responses
The responses of our modified, physiology-based model are clearly more concentrated around zero than those for the original, unmodified model. This is reflected in both the mean of the absolute values of the responses (53% of the value of those for the original Field model parameters) and the population excess kurtosis (149 for the modified model, 6.2 for the original model)

Summary

Introduction

The high metabolic cost of neural computation means that it is only possible for a small fraction of cortical neurons to be active at any one time. One way of accomplishing this is to ensure a sparse distribution of responses across the population of cortical neurons. This is a response in which information is conveyed by strong activity in a small proportion of neurons, while the majority remain relatively inactive. It is possible to create metabolically efficient, sparse responses to natural images [2] by exploiting their statistical redundancy [3].

Methods

Results

Discussion

Conclusion