Orientation selectivity in pinwheel centers in cat striate cortex

Science

Volumn 276, Issue 5318, 1997, Pages 1551-1555

  Maldonado, Pedro E ^a,b   Gödecke, Imke ^a   Gray, Charles M ^c   Bonhoeffer, Tobias ^a  

^a MAX PLANCK INSTITUTE OF PSYCHIATRY   (Germany)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CAT; CELL POPULATION; NERVE POTENTIAL; ORIENTATION; PRIORITY JOURNAL; SINGLE UNIT ACTIVITY; STRIATE CORTEX; VISUAL CORTEX;

ACTION POTENTIALS; ANIMALS; BRAIN MAPPING; CATS; DIAGNOSTIC IMAGING; MODELS, STATISTICAL; NEURONS; VISUAL CORTEX;

EID: 0142019162     PISSN: 00368075     EISSN: None     Source Type: Journal    
DOI: 10.1126/science.276.5318.1551     Document Type: Article

References (28)

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7. 2, and rectal temperature were continuously monitored. The skull was opened above areas 17 and 18, and a titanium chamber was implanted, filled with silicon oil, and closed with a glass cover slip (16). After the surgery, the animals were paralyzed with succinylcholine hydrochloride (20 mg per kilogram of body weight per hour) administered in Ringer solution containing 5% dextrose (4 ml/kg per hour). Details of the optical imaging procedures can be found (4, 16). Briefly, the cortical surface was illuminated with light of 707-nm wavelength, and the animal was presented with moving square wave gratings (0.3 to 1 cycle per degree) of four different orientations, back-projected onto a translucent frosted-glass screen covering 60° of visual angle, located 1 m in front of the animal. The eyes were focused on the tangent screen with an appropriate pair of contact lenses. Images were acquired from the exposed part of the cortex with a slow-scan charge-coupled device camera (ORA 2001, Optical Imaging, Germantown, NY).
8. Activity maps were calculated by dividing the images obtained for one orientation by the sum of the images obtained for all orientations or "cocktail blank" (4, 16). Angle maps were computed by summing the responses to all stimulus orientations for each pixel vectorially, taking the magnitude of the responses as vector lengths and the stimulus orientation as vector angles, and plotting the vector angle with a discrete pseudocolor code. In polar maps the magnitude of the resulting vector is additionally displayed as the brightness of the color at the respective pixel, constituting a measure of the sharpness in orientation tuning of the respective cortical location (4, 16).
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11. Tetrode fabrication and recording methods are described in (8). For each of the different data sets, spike separation was achieved by an interactive computer program. Action potentials arising from geniculate fibers and axons of passage were excluded from our sample on the basis of their distinct wave form. From the individual spike trains, orientation-tuning curves were constructed on the basis of mean firing rate over all trials during the presentation of the stimulus and the cell's spontaneous activity. The stimuli were the same as for the imaging session except that stimulation was monocular with eight different orientations and two directions of motion. For each point in a tuning curve, the mean and standard deviation was calculated. To determine if a particular cell was responsive to the stimulus, we performed a Student's t test between the peak value of the tuning curve and its corresponding value of spontaneous activity.
12. 2 represents the statistical measure of the difference between the experimental data and the Gaussian. From the Gaussian fit of each cell, we estimated the orientation preference (peak) and the orientation bandwidth (σ of Gaussian). In the case of nondirectional cells, the Gaussians were always fit to the higher of the two peaks. Orientation preference was used modulo 180° for determining orientation scatter and orientation range [see (13)].
13. These penetrations were aimed at regions where the orientation signal was strong (that is, where colors in the polar map were bright). Whenever possible we tried to exclude "saddle points" (where the progression of orientation values reverses). Although orientation preference in saddle points generally changes more slowly, these locations were avoided, because they are singular points in the orientation preference map and are thus not representative for iso-orientation domains.
14. 2 test (10)], or where the Gaussian fit was not significantly better than the linear fit to the mean firing rate, the cells were considered untuned for orientation.
15. We used circular statistics [for example, E. Batschelet, Circular Statistics in Biology (Academic Press, New York, 1991)] to assess the variance in orientation preference for the different recording sites. Using vectorial addition, we computed the mean and standard deviation of the orientation preferences of all cells at each site. The standard deviation constitutes a measure of the orientation scatter, which has the virtue of being independent from the number of cells recorded at each site. Its magnitude reflects the variability of orientation preference among all tuned cells at each site. The orientation range, defined as the smallest arc containing all orientation preferences, was also used for quantification.
16. Assuming a hypercolumn spacing of 1 mm, it follows that two cells separated maximally in our tetrode recordings [∼130 μm (8)] should exhibit an orientation preference difference no larger than 23°, with the majority yielding correspondingly smaller values. Yet in iso-orientation domains, there was a substantial number of cell pairs (28%) whose orientation preference differed by more than 23°.
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28. We thank F. Brinkmann for technical help and M. Hübener and K. Britten for helpful comments on earlier versions of the manuscript. This work was supported by the Max-Planck Gesellschaft, by a grant from the National Eye Institute to C.M.G., and fellowships from the McDonnell-Pew Foundation to P.E.M. and the Klingenstein Fund to C.M.G.