As in our previous study (Gorbet et al.,
2012), the current study demonstrates that spatial patterns of BOLD activity in visual areas V2 and V3 can distinguish between RF4 and RF5 motion trajectories. In addition to these regions, MT was also found to be predictive of these trajectories in the current study. A trend toward statistical significance in MT was noted in the first study. However, in addition to decoding blocks of diamond-like RF4 and star-like RF5 motion trajectories, spatial patterns of voxel activity in V2, V3, and MT also distinguished between blocks of RF9 and RF10 trajectories. Although behavioral measures of discrimination were not collected during the MRI portion of the experiment, given the results of the behavioral control study conducted outside the magnet (see
Figure 3), it is highly unlikely that participants were able to distinguish between the RF9 and RF10 motion trajectories. Therefore, we are confident that our finding that spatial patterns of BOLD activity in V2, V3, and MT can distinguish between RF9 and RF10 motion trajectories does not reflect a conscious percept of differences between the shapes of these trajectories. Rather, this finding suggests that decoding of trajectory shape in these early visual regions likely depends on the detection of local properties of the motion trajectories. Disentangling which specific local properties this process relies on is not possible from the data provided by the study presented here; however, some candidates are more likely than others. The mean radius and ranges of path lengths of the radial frequencies tested differed very little between the trajectories that were compared meaning that classification likely did not rely upon differences in the retinotopic extent of the stimuli (
Table 1). On the other hand, ranges of curvatures necessarily differed between radial frequencies (
Table 2), making curvature a potential local property being detected in regions that distinguish between trajectories. Also, keeping the angular speed constant for all of the RF motion trajectories unavoidably meant that the instantaneous tangential speed varied within each trajectory depending on the distance between the dot and the central fixation point. Previous work from our lab demonstrated that detection thresholds for RF motion trajectories do not significantly differ depending on whether angular speed or tangential speed are held constant (Or et al.,
2011). However, it is possible that brain regions in which decoding occurred detected these changes in speed even if this detection does not directly contribute to behavioral discrimination of RF motion trajectories. Also, it is possible that the moving dot may have produced “motion streaks” (Geisler,
1999) as a result of temporal integration within the visual system. If present, these streaks could have provided local orientation and curvature cues that may have driven decoding. Finally, although participants were trained to fixate on the central fixation cross during presentation of the RF motion trajectories, eye movements were not monitored during the fMRI data collection. Therefore, we cannot rule out a potential contribution of eye movement-related processing to the successful decoding of trajectory shape in these regions. All of these possibilities present interesting opportunities for further examination of how V2, V3, and MT contribute to percepts of form from motion.