Beaudot W.H.A., Hess R.F., Mullen K.T. (2000), Dynamics of Contour Integration, ARVO (Association for Research in Vision and Ophthalmology) Annual Meeting, Fort Lauderdale, Florida, April 30-May 5, Investigative Ophthalmology & Vision Science 41(4), S441/2336, March 2000.
Full paper published as:
Hess R.F., Beaudot W.H.A. & Mullen K.T. (2001) Dynamics of contour integration Vision Research, 41(8):1023-1037, April 2001 .
DYNAMICS OF CONTOUR INTEGRATION
((W.H.A. Beaudot, R.F. Hess, K.T. Mullen))
McGill Vision Research, Department of Ophthalmology, McGill University, Montreal, Canada.
Purpose. To determine the dynamics of contour integration we varied the temporal properties of the individual elements in a stimulus composed of arrays of randomly oriented Gabors.
Methods. The task requires the linking of orientation across space to detect a path, measured using a temporal 2AFC method of constant stimuli. Gabor patches (1.5 cpd, s = 0.17 deg) were randomly positioned within a 14 x 14 degree square grid. In experiment 1, we looked at path detection as a function of its duration. The path stimulus was masked before and after with a no-path stimulus identical to the test stimulus but with random orientation of its individual elements. In experiment 2, we measured the effect of this temporal modulation of orientation of the individual elements as a function of temporal frequency. The path and no-path stimuli were presented cyclically for 1 s modulated by a temporal Gaussian window. In experiment 3, we looked at the effect of temporally modulating the contrast of all the individual elements under spatial in-phase and out-phase conditions. In all experiments curvature and contrast were varied.
Results. Our results reveal the temporal resolution of contour integration: it is best for straight paths (6-12 Hz), and declines for more curved paths falling to 1-2 Hz, and is not dependent on the absolute contrast of the linking elements so long as they are visible. Furthermore while these dynamics are quite poor when the contour linking per se is modulated in time, they are better (10-30 Hz) when the contrast of the individual elements is modulated in time.
Conclusions. Contour integration is: 1) slower for curved than for straight paths, compatible with previous results on reaction times (Beaudot & Mullen, ARVO, S809, 1999); and 2) significantly slower than contrast integration. Since it is unlikely that contours of different curvatures are each detected by dedicated detectors, we suggest that path detection could arise from a dynamic process intrinsically tuned to straight paths and temporally evolving to match the spatial properties of the path. Such a process is likely to depend on intra- and extra-cortical feedback known to be important in contextual modulation.
Research supported MRC grants MT-10819 and MT-10818