Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas

Frontiers in Computational Neuroscience

Volumn 9, Issue November, 2015, Pages 1-20

  Lescroart, Mark D ^a   Stansbury, Dustin E ^a   Gallant, Jack L ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Encoding models; FMRI; Neuroscience; Scene perception; Vision; Voxel wise modeling

Indexed keywords

ENCODING (SYMBOLS); FOURIER TRANSFORMS; VISION;

ALTERNATIVE HYPOTHESIS; ENCODING MODELS; FMRI; INDIVIDUAL MODELS; NEUROSCIENCE; OBJECT CATEGORIES; RETROSPLENIAL COMPLEX (RSC); VISUAL REPRESENTATIONS;

BRAIN;

ALTERNATIVE HYPOTHESIS; BOLD SIGNAL; BRAIN FUNCTION; FUNCTIONAL MAGNETIC RESONANCE IMAGING; LINEAR REGRESSION ANALYSIS; MODEL; PREDICTION;

EID: 84948762599     PISSN: 16625188     EISSN: 16625188     Source Type: Journal    
DOI: 10.3389/fncom.2015.00135     Document Type: Article

References (56)

1. Aguirre, G. K., Zarahn, E., and D'Esposito, M. (1998). An area within human ventral cortex sensitive to “building” stimuli: evidence and implications. Neuron 21,373-383.
2. Albrecht, D. G., and Hamilton, D. B. (1982). Striate cortex of monkey and cat: contrast response function. J. Neurophysiol. 48, 217-237.
3. Amit, E., Mehoudar, E., Trope, Y., and Yovel, G. (2012). Do object-category selective regions in the ventral visual stream represent perceived distance information? Brain Cogn. 80,201-213. doi: 10.1016/j.bandc.2012.06.006
4. Auger, S. D., Mullally, S. L., and Maguire, E. A. (2012). Retrosplenial cortex codes for permanent landmarks. PLoS ONE 7:e43620. doi: 10.1371/journal.pone.0043620
5. Benjamini, Y., and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Ann. Stat. 29, 1165-1188. Available online at: http://www.jstor.org/stable/2674075
6. Carandini, M., Demb, J. B., Mante, V., Tolhurst, D. J., Dan, Y., Olshausen, B. A., et al. (2005). Do we know what the early visual system does? J. Neurosci. 25, 10577-10597. doi: 10.1523/JNEUROSCI.3726-05.2005
7. Cate, A. D., Goodale, M. A., and Kohler, S. (2011). The role of apparent size in building- and object-specific regions of ventral visual cortex. Brain Res. 1388, 109-122. doi: 10.1016/j.brainres.2011.02.022
8. Dale, A. M., Fischl, B., and Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 9, 179-194. doi: 10.1006/nimg.1998.0395
9. David, S. V., and Gallant, J. L. (2005). Predicting neuronal responses during natural vision. Network 16, 239-260. doi: 10.1080/09548980500464030
10. David, S. V., Vinje, W. E., and Gallant, J. L. (2004). Natural stimulus statistics alter the receptive field structure ofv1 neurons. J. Neurosci. 24, 6991-7006. doi: 10.1523/JNEUROSCI.1422-04.2004
11. Dilks, D. D., Julian, J. B., Paunov, A. M., and Kanwisher, N. (2013). The occipital place area is causally and selectively involved in scene perception. J. Neurosci. 33, 1331-1336a. doi: 10.1523/JNEUROSCI.4081-12.2013
12. Epstein, R. A. (2008). Parahippocampal and retrosplenial contributions to human spatial navigation. Trends Cogn. Sci. 12, 388-396. doi: 10.1016/j.tics.2008.07.004
13. Epstein, R., and Kanwisher, N. (1998). A cortical representation of the local visual environment. Nature 392, 598-601. doi: 10.1038/33402
14. Epstein, R. A., Parker, W. E., and Feiler, A. M. (2007). Where am I now? Distinct roles for parahippocampal and retrosplenial cortices in place recognition. J. Neurosci. 27, 6141-6149. doi: 10.1523/JNEUROSCI.0799-07.2007
15. Field, D. J. (1987). Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A 4, 2379-2394. doi: 10.1364/JOSAA.4.002379
16. Fisher, R. (1915). Frequency distribution of the values ofthe correlation coefficient in samples from an indefinitely large population. Biometrika 10, 507-521. doi: 10.2307/2331838
17. Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J.-P., Frith, C. D., and Frackowiak, R. S. J. (1994). Statistical parametric maps in functional imaging: a general linear approach. Hum. Brain Mapp. 2, 189-210. doi: 10.1002/hbm.460020402
18. Gallant, J. L., Nishimoto, S., Naselaris, T., and Wu, M. C.-K. (2012). “System identification, encoding models, and decoding models: a powerful new approach to fMRI research” in Visual Population Codes: Toward a Common Multivariate Framework for Cell Recording and Functional Imaging, eds N. Kriegeskorte and G. Kreiman (Cambridge, MA; London, UK: MIT Press), 163-188.
19. Gao, J. S., Huth, A. G., Lescroart, M. D., and Gallant, J. L. (2015). Pycortex: an interactive surface visualizer for fMRI. Front. Neuroinform. 9:23. doi: 10.3389/fninf.2015.00023
20. Gardner, J. L., Sun, P., Waggoner, R. A., Ueno, K., Tanaka, K., and Cheng, K. (2005). Contrast adaptation and representation in human early visual cortex. Neuron 47, 607-620. doi: 10.1016/j.neuron.2005.07.016
21. Hansen, K. A., Kay, K. N., and Gallant, J. L. (2007). Topographic organization in and near human visual area V4. J. Neurosci. 27, 11896-11911. doi: 10.1523/JNEUROSCI.2991-07.2007
22. Hsu, A., Borst, A., and Theunissen, F. E. (2004). Quantifying variability in neural responses and its application for the validation of model predictions. Network 15, 91-109. doi: 10.1088/0954-898X_15_2_002
23. Huth, A. G., Nishimoto, S., Vu, A. T., and Gallant, J. L. (2012). A continuous semantic space describes the representation of thousands of object and action categories across the human brain. Neuron 76, 1210-1224. doi: 10.1016/j.neuron.2012.10.014
24. Janzen, G., and van Turennout, M. (2004). Selective neural representation of objects relevant for navigation. Nat. Neurosci. 7, 673-677. doi: 10.1038/nn1257
25. Jones, J. P., and Palmer, L. A. (1987). An evaluation of the two-dimensional Gabor filter model of simple receptive fields in cat striate cortex. J. Neurophysiol. 58, 1233-1258.
26. Kanwisher, N., McDermott, J., and Chun, M. M. (1997). The fusiform face area: a module in human extrastriate cortex specialized for face perception. J. Neurosci. 17, 4302-4311.
27. Kanwisher, N., and Yovel, G. (2006). The fusiform face area: a cortical region specialized for the perception of faces. Philos. Trans. R. Soc. Lond. B Biol. Sci. 361, 2109-2128. doi: 10.1098/rstb.2006.1934
28. Kay, K. N., Naselaris, T., Prenger, R. J., and Gallant, J. L. (2008). Identifying natural images from human brain activity. Nature 452, 352-355. doi: 10.1038/nature06713
29. Konkle, T., and Oliva, A. (2012). A real-world size organization of object responses in occipitotemporal cortex. Neuron 74, 1114-1124. doi: 10.1016/j.neuron.2012.04.036
30. Kornblith, S., Cheng, X., Ohayon, S., and Tsao, D. Y. (2013). A network for scene processing in the macaque temporal lobe. Neuron 79, 766-781. doi: 10.1016/j.neuron.2013.06.015
31. Kravitz, D. J., Peng, C. S., and Baker, C. I. (2011). Real-world scene representations in high-level visual cortex: it's the spaces more than the places. J. Neurosci. 31, 7322-7333. doi: 10.1523/JNEUROSCI.4588-10.2011
32. Maguire, E. A. (2001). The retrosplenial contribution to human navigation: a review of lesion and neuroimaging findings. Scand. J. Psychol. 42, 225-238. doi: 10.1111/1467-9450.00233
33. Miller, G. A. (1995). WordNet: a lexical database for English. Commun. ACM 38, 39-41. doi: 10.1145/219717.219748
34. Morgan, L. K., Macevoy, S. P., Aguirre, G. K., and Epstein, R. A. (2011). Distances between real-world locations are represented in the human hippocampus. J. Neurosci. 31, 1238-1245. doi: 10.1523/JNEUROSCI.4667-10.2011
35. Naselaris, T., Kay, K. N., Nishimoto, S., and Gallant, J. L. (2011). Encoding and decoding in fMRI. Neuroimage 56, 400-410. doi: 10.1016/j.neuroimage.2010.07.073
36. Naselaris, T., Prenger, R. J., Kay, K. N., Oliver, M., and Gallant, J. L. (2009). Bayesian reconstruction of natural images from human brain activity. Neuron 63, 902-915. doi: 10.1016/j.neuron.2009.09.006
37. Naselaris, T., Stansbury, D. E., and Gallant, J. L. (2012). Cortical representation of animate and inanimate objects in complex natural scenes. J. Physiol. Paris 106, 239-249. doi: 10.1016/j.jphysparis.2012.02.001
38. Nasr, S., Echavarria, C. E., and Tootell, R. B. H. (2014). Thinking outside the box: rectilinear shapes selectively activate scene-selective cortex. J. Neurosci. 34, 6721-6735. doi: 10.1523/JNEUROSCI.4802-13.2014
39. Nasr, S., Liu, N., Devaney, K. J., Yue, X., Rajimehr, R., Ungerleider, L. G., et al. (2011). Scene-selective cortical regions in human and nonhuman primates. J. Neurosci. 31, 13771-13785. doi: 10.1523/JNEUROSCI.2792-11.2011
40. Nasr, S., and Tootell, R. B. H. (2012). A cardinal orientation bias in scene-selective visual cortex. J. Neurosci. 32, 14921-14926. doi: 10.1523/JNEUROSCI.2036- 12.2012
41. Nishimoto, S., Vu, A. T., Naselaris, T., Benjamini, Y., Yu, B., and Gallant, J. L. (2011). Reconstructingvisual experiences from brain activity evoked by natural movies. Curr. Biol. 21, 1641-1646. doi: 10.1016/j.cub.2011.08.031
42. Oliva, A., and Torralba, A. (2001). Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vis. 42, 145-175. doi: 10.1023/A: 1011139631724
43. Park, S., Brady, T. F., Greene, M. R., and Oliva, A. (2011). Disentangling scene content from spatial boundary: complementary roles for the parahippocampal place area and lateral occipital complex in representing real-world scenes. J. Neurosci. 31, 1333-1340. doi: 10.1523/JNEUROSCI.3885-10.2011
44. Park, S., Konkle, T., and Oliva, A. (2015). Parametric coding of the size and clutter of natural scenes in the human brain. Cereb. Cortex 25, 1792-1805. doi: 10.1093/cercor/bht418
45. Rajimehr, R., Devaney, K. J., Bilenko, N. Y., Young, J. C., and Tootell, R. B. H. (2011). The “parahippocampal place area” responds preferentially to high spatial frequencies in humans and monkeys. PLoS Biol. 9:e1000608. doi: 10.1371/journal.pbio.1000608
46. Simoncelli, E. P., and Olshausen, B. A. (2001). Natural image statistics and neural representation. Annu. Rev. Neurosci. 24, 1193-1216. doi: 10.1146/annurev.neuro.24.1.1193
47. Spiridon, M., Fischl, B., and Kanwisher, N. (2006). Location and spatial profile of category-specific regions in human extrastriate cortex. Hum. Brain Mapp. 27, 77-89. doi: 10.1002/hbm.20169
48. Stansbury, D. E., Naselaris, T., and Gallant, J. L. (2013). Natural scene statistics account for the representation of scene categories in human visual cortex. Neuron 79, 1025-1034. doi: 10.1016/j.neuron.2013.06.034
49. Talebi, V., and Baker, C. L. (2012). Natural versus synthetic stimuli for estimating receptive field models: a comparison of predictive robustness. J. Neurosci. 32, 1560-1576. doi: 10.1523/JNEUROSCI.4661-12.2012
50. Van Essen, D. C., Anderson, C. H., and Felleman, D. J. (1992). Information processing in the primate visual system: an integrated systems perspective. Science 255,419-423.doi:10.1126/science.1734518
51. Walther, D. B., Caddigan, E., Fei-Fei, L., and Beck, D. M. (2009). Natural scene categories revealed in distributed patterns of activity in the human brain. J. Neurosci. 29, 10573-10581. doi: 10.1523/JNEUROSCI.0559-09.2009
52. Walther, D. B., Chai, B., Caddigan, E., Beck, D. M., and Fei-Fei, L. (2011). Simple line drawings suffice for functional MRI decoding of natural scene categories. Proc. Natl. Acad. Sci. U.S.A. 108, 9661-9666. doi: 10.1073/pnas.10156 66108
53. Watson, D. M., Hartley, T., and Andrews, T. J. (2014). Patterns of response to visual scenes are linked to the low-level properties of the image. Neuroimage 99, 402-410. doi: 10.1016/j.neuroimage.2014.05.045
54. Wightman, F. L. (1973a). Pitch and stimulus fine structure. J. Acoust. Soc. Am. 54, 397-406. doi: 10.1121/1.1913591
55. Wightman, F. L. (1973b). The pattern-transformation model of pitch. J. Acoust. Soc. Am. 54, 407-416. doi: 10.1121/1.1913592
56. Wu, M. C.-K., David, S. V., and Gallant, J. L. (2006). Complete functional characterization of sensory neurons by system identification. Annu. Rev. Neurosci. 29, 477-505. doi: 10.1146/annurev.neuro.29.051605.113024