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Natural scenes share a consistent distribution of energy across spatial frequencies (SF) known as the 1/fα amplitude spectrum (α≈0.8-1.5, mean 1.2). This distribution is scale-invariant, which is a fractal characteristic of natural scenes with statistically similar structure at different spatial scales. While the sensitivity of the visual system to the 1/f properties of natural scenes has been studied extensively using psychophysics, relatively little is known about the tuning of cortical responses to these properties. Here, we use fMRI and retinotopic mapping techniques to measure and analyze BOLD responses in early visual cortex (V1, V2, and V3) to synthetic noise images that vary in their 1/fα amplitude spectra (α=0.25 to 2.25, step size: 0.50) and contrast levels (10% and 30%) (Experiment 1). To compare the dependence of the BOLD response between the photometric (intensity based) and geometric (fractal) properties of our stimuli, in Experiment 2 we compared grayscale noise images to their binary (thresholded) counterparts, which contain only black and white regions. In both experiments, early visual cortex responded maximally to stimuli generated to have an input 1/f slope corresponding to natural 1/fα amplitude spectra, and lower BOLD responses were found for steeper or shallower 1/f slopes (peak modulation: 0.59% for 1.25 vs. 0.31% for 2.25). To control for changing receptive field sizes, responses were also analyzed across multiple eccentricity bands in cortical surface space. For most eccentricity bands, BOLD responses were maximal for natural 1/fα amplitude spectra, but importantly there was no difference in the BOLD response to grayscale stimuli and their corresponding thresholded counterparts. Since the thresholding of an image changes its measured 1/f slope (α) but not its fractal characteristics, this suggests that neuronal responses in early visual cortex are not strictly driven by spectral slope values (photometric properties) but rather their embedded geometric, fractal-like scaling properties.
Pubmed ID: 27742601
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Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.
View all literature mentionsSoftware package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.
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