Primate inferotemporal cortex is subdivided into domains for biologically important categories, such as faces, bodies and scenes, as well as domains for culturally entrained categories, such as text or buildings. These domains are in stereotyped locations in most humans and monkeys. To ask what determines the locations of such domains, we intensively trained seven juvenile monkeys to recognize three distinct sets of shapes. After training, the monkeys developed regions that were selectively responsive to each trained set. The location of each specialization was similar across monkeys, despite differences in training order. This indicates that the location of training effects does not depend on function or expertise, but rather on some kind of proto-organization. We explore the possibility that this proto-organization is retinotopic or shape-based.
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T. Savage trained the monkeys and helped with scanning. This work was supported by US National Institutes of Health (NIH) grants EY 16187 and EY 24187, and the Nancy Lurie Marks Foundation. This research was carried out in part 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, a P41 Biotechnology Resource Grant supported by the US National Institute of Biomedical Imaging and Bioengineering, NIH, and NIH Shared Instrumentation Grant S10RR021110.
The authors declare no competing financial interests.
Integrated supplementary information
Training, testing, & scanning for each symbol set is indicated by the color of the bar. Functional MRI scanning sessions for post-training localization are indicated by hatching; between scanning days the monkeys continued their in-cage training. All multiple-symbol-set trained monkeys were scanned on at least two separate days (1 week apart) at the following time points: 1) before any training; 2) after the first symbol set was learned (and before the second symbol set training began); 3) after the second symbol set was learned (and before the third symbol set training began); 4) after the third symbol set was learned (except for Y2&G1 who did not get trained on a third symbol set before final scanning); 5) after training on all symbol sets. After training on all symbol sets was completed we did behavioral testing on each symbol set (data in Fig. 1); this testing is indicated by black outlined regions of the appropriate color. Note that Y2 was trained on Tetris after all scanning was finished because he grew too large to scan in a helmet. The post-training patches shown in Figs. 2 & 3 were calculated using data obtained immediately after training on each symbol set; these patches are the ROIs that were used to calculate the pre- and post-training bar graphs in Fig. 2d. Post-training data for the bar-graphs in Fig. 2d were obtained in the orange hatched scanning epochs. The pre-training data for the bar graphs in Fig. 2d were collected immediately before training on each symbol set. The centers of mass of each of the training-induced regions shown in Fig. 3c were calculated from data obtained both immediately after training on each symbol set (squares in Fig. 3c) and from data obtained immediately after training on a subsequent symbol set (circles in Fig. 3c). Scanning for the eccentricity, curvature, spatial frequency, and category maps in Figs 4 & S5 was performed in the yellow hatched epochs.
Images were 20° × 20° presented for 0.5 seconds each in 16 second blocks separated by 20 seconds of blank gray screen. A fixation spot was always superimposed at the center of each image.
Supplementary Figure 3 Significant activations for each trained symbol set and for faces overlaid on each monkey’s raw functional slices (thus minimizing registration errors).
Significance criterion: p<0.002; cluster size>=31 voxels. Red indicates significant activations for monkey faces > Helvetica AND monkey faces > Tetris; scans obtained before Cartoon face training. Cyan indicates Cartoon faces > monkey faces; scans obtained immediately after Cartoon face training. Blue indicates Helvetica>control; scans obtained immediately after Helvetica training. Green indicates Tetris>control; scans obtained immediately after Tetris training. In images with iron-oxide contrast agent major sulci are directly visible in the functional slices so registration of data obtained at different times is clear; left hemisphere is on the left. Each row shows the activations for one monkey; each column shows alternate 1mm slices from A+4 to A-4. Color indicates image category; two-color hatching indicates voxels with significant activations to two categories. T-score maps for each contrast for each monkey are shown in Fig. S4,S5,S6,S7,S8,S9,S10,S11.
Supplementary Figure 4 t-score maps for significant activations on functional slices for monkey B1 on alternate 1-mm coronal slices from AP +4 to AP –4 for each contrast; left hemisphere is on the left.
Supplementary Figure 10 t-score maps for significant activations on functional slices for monkey G1.
Supplementary Figure 11 Spatial frequency maps for the same monkeys as in Figure 4 for the contrast of 0.4 cpd patterns minus 2.5 cpd patterns, as well as graphs of the correlation coefficients between spatial frequency maps and all other maps.
Dotted line indicates zero correlation; correlation can vary between -1 and 1. Asterisks at the top indicate correlations that were significantly greater than zero at p<0.05; asterisks at the bottom indicate correlations significantly less than zero at p<0.05.
Supplementary Figure 12 Distribution of average t-scores for eccentricity and curvature contrasts for monkey face, cartoon face, Helvetica and Tetris ROIs.
Three monkeys were scanned with a periphery-minus-central contrast and a straight-minus-curvy contrast, as in Fig. 4. T-scores were averaged over each ROI in each monkey for both contrasts. (The same ROIs as were used as in Fig. 2d.) Black lines at the center of each plot show the 95% confidence limits for distribution of t-scores for the same ROIs calculated from stimulus-shuffled maps.
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Srihasam, K., Vincent, J. & Livingstone, M. Novel domain formation reveals proto-architecture in inferotemporal cortex. Nat Neurosci 17, 1776–1783 (2014). https://doi.org/10.1038/nn.3855
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