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FIG. 6. Transient MR signal changes reveal orientation selectivity in human V1. Subjects fixated the center of the stimulus screen during MR scans, in a 1.5-T scanner. In A, scans were 4 min and 40 sec long. During the first 40 sec, the stimulus was a uniform gray field (dark gray time bin in A). During the remaining 4 min. the grating was presented continuously, with stripe width (0.1–2°) and position varied randomly every 0.4 sec. The flickering gratings were presented at a single orientation for 40 sec at a time. Every 40 sec, the grating orientation changed from one oblique orientation to the other, each 90° different from each other (white and light gray time bins in A). Signals were acquired continuously (1 image per slice per 2 sec) from voxels in area V1, selected on the basis of field sign map boundaries. A shows the averaged time course from 20 scans in one subject, in one ≈2-hr scan session. B shows the averaged response to each change in orientation; thus it represents the average of all epochs of a single orientation except the first grating presentation in each scan. Approximately 7 sec (the expected hemodynamic delay) following each change in orientation, a positive inflection (the “orientation transient”) is produced in the averaged MR signal (A and B). The second set of experiments (C and D) shows that smaller angular changes in orientation produce correspondingly smaller fMRI “transients.” C shows the average increase in signal between the actual time of orientation change (time=0 sec) and the MR signal 6–8 sec later, when the transient MR response occurred. These changes were measured during two sets of scans, corresponding to the two curves shown in C. In one set of scans, the change in orientation between epochs began at 90°, becoming progressively smaller (67.5°, 45°, 22.5°, then 0°) at each subsequent epoch. During the second set of scans (presented in interleaved fashion with the first set of scans), the order of the size of orientation change was reversed (0°, 22.5°, 45°, 67.5°, then 90°). The values obtained after a specific size of orientation change were similar irrespective of presentation order, and they were averaged together to produce the average bandwidth shown in D. Averaged values for each orientation change in C are displayed twice in D (excepting the 90° change), for illustrative purposes.

addition to telling us where V1 is usually located, prior studies from V1 in macaques and humans had already suggested a high degree of retinotopic precision and a polar organization of the V1 retinotopy ((e.g., refs. 9, 10, 13, 34, 35, 46, 47), monocular dominance in the blind spot representation (29, 30, 35, 36), orientation selectivity (e.g., refs. 4143), and even the averaged contrast gain functions (5, 48). In this sense the present study has value as a “calibration” or “confirmation” study.

However, some other aspects of the present study are more novel. The tests for orientation selectivity based on transient fMRI signals are an approach that could easily be generalized to tests for similarly coded stimulus dimensions, such as visual motion, color, etc. The tests for the blind spot representation could likewise be generalized to trace where and when other retinal inhomogenieties (e.g., rod/cone ratio changes with eccentricity, etc.) are “filled in” in cortex. For instance, it is interesting that the monocular blind spot representation does not appear in V2 (Fig. 4), although a binocular stimulus of almost equal dimensions is represented in V2 (Fig. 2). Because we are largely unconscious of these retinal variations, this issue also bears on the question of which cortical visual areas, and what functional aspects of visual processing, have access to conscious perception (e.g., ref. 49). Finally, the maps of contrast sensitivity (Fig. 5) suggest that contrast gain may be better accounted for by considering models of probability summation within progressively larger receptive fields (e.g., ref. 40), rather than in terms of predominant input from either magnocellular or parvocellular “streams” (e.g., refs. 5 and 48).

We thank Mary Foley, Terrance Campbell, William Kennedy, Bruce Rosen, and Thomas Brady for invaluable assistance during the course of this project. We are especially grateful to Dr. Stephan Brandt for helping to acquire some of the data. This work was supported by grants from the Human Frontiers Science Program and the National Eye Institute to R.B.H.T., the Swiss Fonds National de la Recherche Scientifique to N.K.H., and the McDonnell-Pew Foundation to J.D.M.

1. Lueck, C.J., Zeki, S., Friston, K.J., Dieber, M.-P., Cope, P., Cunningham, V.J., Lammertsma, A.A., Kennard C. & Frackowiak, R.S.J. (1989) Nature (London) 340, 386–389.

2. Zeki, S., Watson, J.D.G., Lueck, C.J., Friston, K.J., Kennard, C. & Frackowiak, R.S.J. (1991) J. Neurosci. 11, 641–649.

3. Watson, J.D.G., Myers, R., Frackowiak, R.S.J., Hajnal, J.V., Woods, R.P., Mazziota, J.C., Shipp, S. & Zeki, S. (1993) Cereb. Cortex 3, 79–94.

4. Dupont, P., Orban, G.A., DeBruyn, B., Verbruggen, A. & Mortelmans, L. (1994) J. Neurophysiol. 72, 1420–1424.

5. Tootell, R.B.H., Reppas, J.B., Kwong, K.K., Malach, R., Born, R.T., Brady, T.J., Rosen, B.R. & Belliveau, J.W. (1995) J. Neurosci. 15, 3215–3230.

6. Tootell, R.B.H., Reppas, J.B., Dale, A.M., Look, R.B., Malach, R. , Jiang, H.-J., Brady, T.J. & Rosen, B.R. (1995) Nature (London) 375, 139–141.

7. McCarthy, G., Spicer, M., Adrignolo, A., Luby, M., Gore, J. & Allison, T. (1995) Hum. Brain Mapp. 2, 234–243.

8. Schneider, W., Noll, D.C. & Cohen, J.D. (1993) Nature (London) 365, 150–153.

9. Engel, S.A., Rumelhart, D.E., Wandell, B.A., Lee, A.T., Glover, G.H.E., Chichilnisky, J. & Shadlen, M.N. (1994) Nature (London) 370, 106.

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