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Parallel, multi-stage processing of colors, faces and shapes in macaque inferior temporal cortex

Nature Neuroscience volume 16, pages 1870–1878 (2013)Cite this article

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Abstract

Visual-object processing culminates in inferior temporal cortex (IT). To assess the organization of IT, we measured functional magnetic resonance imaging responses in alert monkeys to achromatic images (faces, fruit, bodies and places) and colored gratings. IT contained multiple color-biased regions, which were typically ventral to face patches and yoked to them, spaced regularly at four locations predicted by known anatomy. Color and face selectivity increased for more anterior regions, indicative of a broad hierarchical arrangement. Responses to non-face shapes were found across IT, but were stronger outside color-biased regions and face patches, consistent with multiple parallel streams. IT also contained multiple coarse eccentricity maps: face patches overlapped central representations, color-biased regions spanned mid-peripheral representations and place-biased regions overlapped peripheral representations. These results show that IT comprises parallel, multi-stage processing networks subject to one organizing principle.

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Figure 1: Identification of the boundaries of IT and retinotopic visual areas using fMRI and retinotopic mapping.
Figure 2: Functional architecture of color-biased regions in alert macaque IT.
Figure 3: Color-biased fMRI activation (blue and cyan) found at corresponding locations to face patches (orange and red).
Figure 4: Raw functional echo planar coronal images showing MION activation in 1-mm-thick slices through the whole brain; color-biased activation (blue, left) and face-biased activation (orange, right) of M1.
Figure 5: Quantification of the spatial relationship of color-biased regions and face patches in alert macaque IT.
Figure 6: Responses to images of faces, body parts, fruit and vegetables, and places across IT.
Figure 7: IT contains multiple representations of the visual field, which correlate with responses to faces, non-face objects and places.
Figure 8

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Acknowledgements

fMRI data were analyzed using the jip toolbox generously provided by J. Mandeville (Massachusetts General Hospital, http://www.nitrc.org/projects/jip/), and analysis scripts compiled by S. Moeller (RWTH Aachen University). We thank J. Maunsell, D. Hubel and M. Livingstone for research space, helpful discussions and assistance with animal protocols. A. Rehding, N. Kanwisher, J. DiCarlo and P. Mayo provided valuable comments on the manuscript. B.R.C. gratefully acknowledges seminal conversations that took place with D. Tsao, with whom the idea to map multiple stimulus dimensions in IT was conceived and initially begun. We thank Y. Liu for implementing the simulation shown in Figure 5 and help with MRI analysis. We thank J. McCready and E. Erzinger, who designed and built the fMRI primate chair, and C. Stoughton and G. Gagin, who trained the animals. We thank L. Wald and A. Mareyam for providing the four-channel magnetic resonance coil. We thank W. Vanduffel, J. Mandeville, J. Polimeni, T. Witzel, M. O'Hara, G. Khandewal, M. Histed and P. Mayo for help running the experiments and conducting the analyses. This paper is dedicated to the memory of our mentor and beloved friend, David Hubel, who died September 22, 2013 (age 87). This work was supported by grants from the National Science Foundation (0918064), the US National Institutes of Health (EY023322), the Whitehall Foundation, the Radcliffe Institute for Advanced Study (Harvard University) and Wellesley College. This research was carried out at the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital, using resources provided by the Center for Functional Neuroimaging Technologies (P41EB015896) and a P41 Biotechnology Resource grant supported by the National Institute of Biomedical Imaging and Bioengineering. This work also involved the use of instrumentation supported by the US National Institutes of Health Shared Instrumentation Grant Program and/or High-End Instrumentation Grant Program (S10RR021110).

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Authors and Affiliations

  1. Neuroscience Program, Wellesley College, Wellesley, Massachusetts, USA

    Rosa Lafer-Sousa & Bevil R Conway

  2. Department of Neurobiology, Harvard Medical School, Cambridge, Massachusetts, USA

    Bevil R Conway

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R.L.-S. carried out the experiments and analyzed the data. B.R.C. designed the research, carried out the experiments, analyzed the data and wrote the manuscript.

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Correspondence to Bevil R Conway.

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Integrated supplementary information

Supplementary Figure 1 a. Comparison of the responses during meridian mapping using BOLD and a contrast agent (MION).

%Signal change (response to vertical meridian stimulation minus response to horizontal meridian stimulation; see Figure 1) was assessed in two regions of interest, the V1-V2 vertical meridian representation and the PIT/CIT vertical meridian representation. MION substantially enhanced the signal. Data were obtained in the same animal and the BOLD and MION experiments comprises the same number of stimulus runs (N=8). b, Plot showing the C.I.E. xy coordinates of the color stimuli used (left) and the C.I.E. uv coordinates (right).The cardinal axes of DKL color space are shown: L-M and S. C.I.E. Luv space is approximately perceptually uniform. The center point indicates the adaptation point.

Supplementary Figure 2 a, Activation maps showing responses to color versus responses to black-and-white using colors 7 & 8 (a) and colors 1-6 and 9-12 (b) in M1 (left) and M2 (right).

The bottom row in (a) and b shows the 20° ventral rotated view corresponding to Figure 3a. Colors 7 and 8 are the two colors least likely to be contaminated by luminance artifacts (see text). (c) Color-biased regions identified by comparing responses to all colors besides colors 7 & 8 versus responses to achromatic gratings, using no spatial smoothing, in M1. Bottom set of panels shows expanded view of early retinotopic cortex, showing comparable pattern of activation to that described by Conway et al. (2007). Note the luminance bias within V3, and the suggestion of a stripe pattern within V2, presumably reflecting the concentration of color cells within the cytochrome-oxidase thin stripes. Unlike the earlier report, color stimuli were calibrated using the DKL color space, and the saturation of the achromatic gratings was adjusted so that V1 gave the same magnitude of response to the achromatic gratings as it gave to colors 7&8. This calibration procedure was effective, as shown by the lack of a color bias in V1.

Supplementary Figure 3 (a) Time course of the responses to colors within color-biased regions (top) and face-biased regions (bottom) of posterior, central, anterior and anterior-medial IT within the two monkeys (M1, M2).

(b) Time course of the responses to images of objects within color-biased regions (top) and face-biased regions (bottom) of posterior, central, anterior and anterior-medial IT within the two monkeys (M1,M2).

Supplementary Figure 4 Face-biased activation within the hippocampus, anterior insula, entorhinal cortex and amygdala in M1.

Right panels show time courses of the responses to frontal unfamiliar faces (f), bodies (b), familiar faces (ff, cage mate), vegetables & fruits (vf), familiar faces (fs, self), and places (p). Slices show Talairach coordinates.

Supplementary Figure 5 Raw functional echo planar (EPI) coronal images showing MION activation every 1 mm; color-biased activation (blue-cyan, left panels) and face-biased activation (orange-red, right panels) of M2.

Table below shows the approximate Talairach coordinates of face patch and color-biased region centers for M1 and M2.

Supplementary Figure 6 Activation patterns for one monkey (M1), both hemispheres, generated by various contrasts, as indicated.

Black contours show face patches; white contours show color-biased regions. Inset in box shows the activation pattern to all non-face objects compared to scrambled objects.

Supplementary Figure 7 Eccentricity mapping.

a, Spatial distribution of the responses to the eccentricity stimulus within both hemispheres (left hemisphere, top; right hemisphere, bottom) of M2. The left panel of each row shows in blue-cyan the responses that were greater to the foveal disc (1.5°) than to the other eccentricity stimuli combined. In the response maps, the spot of orange-red within the annulus of cyan corresponds to the fixation spot. The subsequent panels show responses to progressively expanding annuli (the radii of the annuli is given). The stimulus comprised a checkerboard of colors defined by the L-M axis and one defined by the S-axis. Note that progressively expanding annuli elicit correspondingly wider annuli of activation within the cortex, as shown by others (e.g. Fize et al, 2003). In addition, along IT is evident clear activation to the central disc and smallest annulus. b, the left panel shows the activation pattern comparing the first two eccentricity conditions with the last two (and is what is reported in Figure 6). For comparison, the right panel shows the results of the meridian mapping experiment. Along IT is shown higher activation to stimulation along the vertical meridian at locations in between the central visual field representations. We do not interpret these as vertical meridian representations, but rather as indication of a peripheral bias: the vertical meridian stimulus comprised 60° wedges, while the horizontal meridian stimulus was 30°. Thus on average, the vertical stimulus represented more activation of the peripheral visual field.

Supplementary Figure 8 Bar plots quantifying the responses to central and peripheral stimulation within color-biased regions (a) and face patches (b) along the posterior-anterior axis.

Compare with Figure 6c, showing the responses within a single combined color-biased region of interest and single combined face-biased region of interest. Error bars indicate s.e. (N=4 hemispheres). c, Histograms of distances from each IT face-selective voxel to its nearest color-selective voxel (red line, mean = 4.0 mm, s.d. 0.2 mm), and from each IT face-selective voxel to its nearest place-selective voxel (blue line, mean = 5.3 mm). The histograms were normalized by the total number of comparisons made. On average, the distance between face-biased and color-biased voxels is shorter than the distance between face-biased voxels and place-biased voxels (Mann–Whitney–Wilcoxon test, p= 1.5x10-24).

Supplementary Figure 9 Extent of visually active voxels in M1.

(a) Activation is found along the full extent of the temporal lobe. (b) time course of response to color 8 and the achromatic gratings within the IT color regions, the IT regions more significantly responsive to achromatic gratings (IT BW), the entire IT volume, and the portions of IT outside of color-biased and luminance-biased regions. Color-biased regions are shown with white contours and face patches are shown with black contours. The patchiness of these functionally biased regions cannot be attributed to lack of signal within the intervening tissue. (c) Color-biased (top row) and face-biased (bottom row) regions shown at three significance level thresholds in M1, right hemisphere.

Supplementary Figure 10 Raw functional echo planar (EPI) coronal images showing MION activation every 1 mm; color-biased activation (blue, left panels) and face-biased activation (blue, right panels) of data obtained in previous reports 13,31.

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Lafer-Sousa, R., Conway, B. Parallel, multi-stage processing of colors, faces and shapes in macaque inferior temporal cortex. Nat Neurosci 16, 1870–1878 (2013). https://doi.org/10.1038/nn.3555

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