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

Overview

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.

publication date

  • July 17, 2020

Research

keywords

  • Brain Mapping
  • Visual Cortex
  • Visual Perception

Identity

PubMed Central ID

  • PMC8239382

Scopus Document Identifier

  • 85088895748

Digital Object Identifier (DOI)

  • 10.1016/j.neuroimage.2020.117173

PubMed ID

  • 32682991

Additional Document Info

volume

  • 221