Abstract
Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation -- primarily in the visual cortex. Reported evidence indicates that such signals are spatially broadband in nature, and are not primarily comprised of fine-grained activation patterns. However, it is unclear whether this is a general property of the BOLD signal, or whether it is specific to the details of employed analyses and stimuli. Here we performed an analysis of publicly available, high-resolution 7T fMRI on the response BOLD response to musical genres in primary auditory cortex that matches a previously conducted study on decoding visual orientation from V1. The results show that the pattern of decoding accuracies with respect to different types and levels of spatial filtering is comparable to that obtained from V1, despite considerable differences in the respective cortical circuitry.
Highlights
We recently reported[1] that spatial band-pass filtering of 7 Tesla BOLD fMRI data boosts accuracy of decoding visual orientations from human V1
Maximum decoding performance was observed for a band equivalent to a difference-of-Gaussians (DoG) filter of 5–8 mm full width at half maximum (FWHM), indicating that low spatial frequency fMRI components contribute to noise with respect to orientation discrimination
Stimulus and fMRI data Data were taken from a published dataset[2] which were repeatedly analyzed previously[4,5], and publicly available from the studyforrest.org project of 20 participants passively listening to five natural, stereo, high-quality music stimuli (6 s duration; 44.1 kHz sampling rate) for each of five different musical genres: 1) Ambient, 2) Roots Country 3) Heavy Metal, 4) 50s Rock’ n’Roll, and 5) Symphonic, while fMRI data were recorded in a 7 Tesla Siemens scanner (1.4 mm isotropic voxel size, TR=2 s, matrix size 160×160, 36 slices, 10% interslice gap). fMRI data were scanner-side corrected for spatial distortions[6]
Summary
We recently reported[1] that spatial band-pass filtering of 7 Tesla BOLD fMRI data boosts accuracy of decoding visual orientations from human V1. Maximum decoding performance was observed for a band equivalent to a difference-of-Gaussians (DoG) filter of 5–8 mm full width at half maximum (FWHM), indicating that low spatial frequency fMRI components contribute to noise with respect to orientation discrimination. This finding raises the question whether this reflects a specific property of early visual cortex and the particular stimuli used in 1, or whether it represents a more general aspect of BOLD fMRI data with implications for data preprocessing of decoding analyses. I believe it was axial, but Figure 1 could mislead people into thinking it was coronal.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
