Aim: In this experiment we wanted to determine whether similar patterns of shape activity would be observed in a better-controlled, event-related design.
Block-based studies of shape selectivity may not reveal only shape selective regions as they are confounded by the task. In block-based studies, the subject is either performing a shape-discrimination task or no task at all. This difference in task may be responsible for the typical pattern of activity found in shape or object localiser studies. We therefore changed our shape localiser scans by using an event related design. In this experiment, we used blocks of C or M shapes as in Experiment 5, but we also varied the noise of the shapes from 0 to 100%. Shape specific activity could then be revealed by comparing low-noise, highly visible shapes to high-noise, invisible shapes in an event-related fashion. As subjects were performing the same task in each condition, this approach is very well matched for attentional demands. Furthermore the structural similarity of the stimuli between the shape and non-shape conditions was much higher than in experiment 5 in which shapes were compared to high coherence controls. This provides a better-matched control that may be able to reveal more specific activations than a block-based study.
2.7.1. Experiment 6 - procedure
The stimuli were similar to those used in Experiment 1 except that no CM shapes were included and non-limited lifetime dots were used to ensure that the motion-defined shapes were matched for difficulty with the colour-defined ones. This experiment also contained blocks of shapes that were split in half horizontally but these will not be discussed here. Other than this difference, the subject’s training procedure was identical to that in Experiment 5. The amount of noise in the shape was varied from 0-100% in steps of 1.53% to provide 66 noise values.
After training, the subjects (8 in total, 6 male, all right-handed, mean age 28.3 years) were moved into a Magnetom Vision scanner where they were provided with headphones and a button-box to allow their responses to be recorded. Inside the scanner, their task was changed to a target detection task. At the beginning of each block they were presented with a randomly chosen shape that was to be the target for that block; they were then presented with a block o f 6 shapes lasting Is each and separated by 0.5s. If they saw the target shape they were instructed to press a button with their right-hand index finger. The number o f targets per block was randomly selected to be between 0 and 2 and they were randomly distributed over the entire noise range, meaning some targets were actually invisible. Blocks o f either C shapes or M shapes, either whole or split in half and lasting 9.5s each were presented in a pseudo randomised order so that every four blocks contained both a C and an M block. Each condition contained a total of 66 shapes with only one stimulus at each noise value. A total of 210 functional volumes were acquired.
2.7.2. Experiment 6 - Data analysis.
The data were pre-processed in exactly the same fashion as in experiment 5 except for one extra stage. After the data were realigned in space they were also realigned in time using a Fourier analysis based approach (Josephs and Henson, 1999). This stage was done because SPM treats each volume as if it was acquired instantaneously at one point in time (the time of the first slice in the volume). This means that in an experiment such as this, with 38 slices and a TR of 2.89s, there can be a 2.81s difference between the actual time a slice was acquired and the time SPM attributes to that slice. This problem is not of great significance in block-based designs such as experiment 5 in which the length of a block is far greater than the TR. But in event-related designs this effect may be a source of significant loss of statistical power. The data were realigned in time by converting the images into frequency space using a fast Fourier transform. The data were then realigned in frequency space using sine interpolation before the inverse Fourier transform was taken.
_ — " Low-noise (L) High-noise (H)
Colour defined (C) CL CH
Motion defined (M) ML MH
Table 2. The factorial design of experiment 6.
Shapes were divided into four groups visualised as a 2x2 design. The two factors were the cue that defined the shape and the amount of noise in the shape. The shapes were split into high and low noise by considering anything with a noise value of less than or equal to 50% to be low-noise an anything above 50% to be high noise.
The experimental paradigm was modelled as a 2x2 design (Table 2); the split-shape conditions were also modelled but will not be discussed here. Each shape presentation was modelled as a stick function (a box-car function o f very brief duration) with a duration of 1/16^^ of a TR, 0.18s in this case, which was then convolved with the canonical haemodynamic response function (HRF). Subject’s responses (i.e. the time at which they pressed a button to indicate they had seen a target shape) were also modelled as stick functions and entered into the analysis as a separate regressor.
2.7.3. Experiment 6 - Results.
The main effect o f interest was shape-selective activity. This could be seen by subtracting the activity in the high-noise conditions from the activity in the low noise conditions using the contrast [ML - MH] for motion defined shapes and [CL - CH] for colour. The results from these contrasts are shown in Figure 21 revealing that specific regions were more active when subjects saw low noise shapes than high noise shapes and the pattern of activation varied slightly according to whether the shape was defined by colour or motion. Areas which gave significantly higher responses for motion shapes but not colour shapes included V5 bilaterally and the superior parietal lobule. These areas have previously been shown to be involved in motion processing (Zeki et al, 1991a, Watson et al, 1993) or attention to motion (Corbetta et al, 1990; Petersen et al, 1994; Buchel et al 1998). Areas responding specifically to colour shapes were
confined to the ventral surface of the brain in regions consistent with the co-ordinates of V4 and V4a in previous studies (see Bartels and Zeki, 2000, for a review) as well as more anterior parts of the fusiform gyrus that have also been previously identified as colour-shape selective areas (Zeki and Marini, 1998).
We also searched for areas which responded significantly to both colour and motion defined shapes and found a bilateral region of cortex consistent with the position of a large region known as the lateral occipital complex (LOC). This region has previously been identified as responding more strongly to objects than fragments of objects (Malach et al, 1995; Kan wisher et al, 1996). The region has also previously been demonstrated to respond well to objects defined by different cues (Grill-Spector et al 1998, although note that colour defined objects were not used in that study).
V4(r)n
V4a(r)
LOC(I)
Figure 21. Shape specific activity from Experiment 6. Cue-specific shape activity is shown overlaid on rendered, single-subject brains masked in MRIcro (Rorden and Brett, 2000) so that the cerebellum is removed. The data are shown in radiological convention so that the left hemisphere in the image is the right hemisphere of the subject. Voxels in red show significantly (P < 0.0001, uncorrected) higher responses to easily visible motion shapes compared to noisy, subliminal motion shapes, the green voxels are the equivalent comparison for colour shapes. Yellow voxels are those which show significant shape responses to both colour and motion defined shapes, revealed by inclusive masking so that only voxels, which reach significance in both the above contrasts, are shown. The bar plots accompanying each area show the difference between BOLD activation for shapes compared to subliminal shapes, the yellow bars indicate shape from colour responses, the black bars indicate shape from motion. From these bar plots it can
be seen that there are some cue-specific shape activations both for motion, in V5 and the superior parietal lobule, and for colour, in V4 and V4a. Areas in the lateral occipital complex differ in that they respond equally well to shapes regardless of the cue from which they were defined. The scales of the box plots are identical with each box covering 0.2% change in BOLD signal.
Left hemisphere Right hemisphere Areas selective for colour:
V4 - 22, -78, -10
V 4a -22, -50, -16 32, -56, -18
Anterior Fusiform -24, -38,-16 36, -40, -24
Areas selective for motion:
V5/L0 -50, -68, -2 54, -68, -4
V5 (posterior) -44, -76, -2 44, -78, -4
SPL -24, -64, 60 18, -60, 66
Areas responding to both:
LG -42, -72, -14 40, -78, -16
LOa -42, -60, -20 50, -60, -18
Table 3. Talairach co-ordinates of the regions shown in Figure 21.