Pfizer COVID-19 vaccine appointments are available to our patients. Sign up for Connect today to schedule your vaccination. Continue your routine care with us by scheduling an in-person appointment or Video Visit.

Manipulating the structure of natural scenes using wavelets to study the functional architecture of perceptual hierarchies in the brain.

TitleManipulating the structure of natural scenes using wavelets to study the functional architecture of perceptual hierarchies in the brain.
Publication TypeJournal Article
Year of Publication2020
AuthorsPuckett AM, Schira MM, Isherwood ZJ, Victor JD, Roberts JA, Breakspear M
JournalNeuroimage
Volume221
Pagination117173
Date Published2020 Jul 17
ISSN1095-9572
Abstract

Functional neuroimaging experiments that employ naturalistic stimuli (natural scenes, films, spoken narratives) provide insights into cognitive function "in the wild". Natural stimuli typically possess crowded, spectrally dense, dynamic, and multimodal properties within a rich multiscale structure. However, when using natural stimuli, various challenges exist for creating parametric manipulations with tight experimental control. Here, we revisit the typical spectral composition and statistical dependences of natural scenes, which distinguish them from abstract stimuli. We then demonstrate how to selectively degrade subtle statistical dependences within specific spatial scales using the wavelet transform. Such manipulations leave basic features of the stimuli, such as luminance and contrast, intact. Using functional neuroimaging of human participants viewing degraded natural images, we demonstrate that cortical responses at different levels of the visual hierarchy are differentially sensitive to subtle statistical dependences in natural images. This demonstration supports the notion that perceptual systems in the brain are optimally tuned to the complex statistical properties of the natural world. The code to undertake these stimulus manipulations, and their natural extension to dynamic natural scenes (films), is freely available.

DOI10.1016/j.neuroimage.2020.117173
Alternate JournalNeuroimage
PubMed ID32682991