Spatial Frequency Preferences in Visual Cortex

2017-07-24

Everyone's intuition

people's intuition looks basically like this:

preferred spatial frequency starts high in the fovea, then decreases as you move towards the periphery
the preferred spatial frequency at a given eccentricity decreases as you move to higher visual areas (because receptive field size increases)
at a given eccentricity, you have many neurons, all of whose responses are centered at similar frequencies (and have roughly log-Gaussian response curves)
probably not linear, probably exponential decay, but this is basically it

data typically qualitatively follows this pattern, but there's little done to systematically map this out, and it does vary across studies

I found a handful of studies, which I'm going to go through in chronological order and then summarize at the end.

BUT:

actual numbers disagree
no standard way to display this data
if curves fit, no parameters given
therefore, hard to read off numbers
different stimuli used
for the project I'm working on, we wanted to start with degrees 2 to 4 in V1, so that's what I'm going to point out
inconsistent data from areas other than V1
no comparison across subjects

For almost all of these, they showed stimuli to participants in some sort of block design, then fit the results using a GLM and estimated response / peak SF that way

unless marked otherwise, all results are in V1

Sasaki et al, 2001

Henriksson et al, 2008

Kay et al, 2008 and Kay, 2011

Hess et al, 2009

D'Souza et al, 2016

Farivar et al, 2017

Catherine's pilot data

Summary of V1 results

Next steps

Systematically evaluate spatial frequency sensitivity as function of eccentricity in V1, V2, and V3
Create annuli and rotating wedges with spatial frequencies spanning .1 to 10 cpd (and potentially test different patterns: sine waves in different directions, random lines, etc.)
Subjects fixate at center of stimuli, perform distractor task
For each voxel, fit parameterized tuning curves (based on eccentricity, visual area)
Please give feedback!

Bibliography

D'Souza, D. V., Auer, T., Frahm, J., Strasburger, H., & Lee, B. B. (2016). Dependence of chromatic responses in v1 on visual field eccentricity and spatial frequency: an fmri study. JOSA A, 33(3), 53-64.
Farivar, R., Clavagnier, S., Hansen, B. C., Thompson, B., & Hess, R. F. (2017). Non-uniform phase sensitivity in spatial frequency maps of the human visual cortex. The Journal of Physiology, 595(4), 1351-1363. http://dx.doi.org/10.1113/jp273206
Henriksson, L., Nurminen, L., Hyvarinen, Aapo, & Vanni, S. (2008). Spatial frequency tuning in human retinotopic visual areas. Journal of Vision, 8(10), 5. http://dx.doi.org/10.1167/8.10.5
Hess, R. F., Li, X., Mansouri, B., Thompson, B., & Hansen, B. C. (2009). Selectivity as well as sensitivity loss characterizes the cortical spatial frequency deficit in amblyopia. Human Brain Mapping, 30(12), 4054-4069. http://dx.doi.org/10.1002/hbm.20829
Kay, K. N., Naselaris, T., Prenger, R. J., & Gallant, J. L. (2008). Identifying Natural Images From Human Brain Activity. Nature, 452(7185), 352-355. http://dx.doi.org/10.1038/nature06713
Kay, K. N. (2011). Understanding Visual Representation By Developing Receptive-Field Models. Visual Population Codes: Towards a Common Multivariate Framework for Cell Recording and Functional Imaging, (), 133-162.
Sasaki, Y., Hadjikhani, N., Fischl, B., Liu, A. K., Marret, S., Dale, A. M., & Tootell, R. B. (2001). Local and global attention are mapped retinotopically in human occipital cortex. Proceedings of the National Academy of Sciences, 98(4), 2077-2082.