Title: Object-selective Cortex Exhibits Performance-independent Repetition Suppression Performance-independent Rs in Object Cortex -2

Object-selective cortical regions exhibit a decreased response when an object stimulus is repeated (repetition suppression, RS). RS is often associated with priming: reduced response times and increased accuracy for repeated stimuli. It is unknown whether RS reflects stimulus-specific repetition, the associated changes in response time, or the combination of the two. To address this question, we performed a rapid event-related fMRI study in which we measured BOLD signal in object-selective cortex, as well as object recognition performance, while we manipulated stimulus repetition. Our design allowed us to examine separately the roles of response time and repetition in explaining RS. We found that repetition played a robust role in explaining RS: repeated trials produced weaker BOLD responses than nonrepeated trials, even when comparing trials with matched response times. In contrast, response time played a weak role in explaining RS when repetition was controlled for: it explained BOLD responses only for one ROI and one experimental condition. Thus, repetition suppression appears to be mostly driven by repetition, rather than performance changes. We further examined whether RS reflects processes occurring at the same time as recognition, or after recognition, by manipulating stimulus presentation duration. In one experiment, durations were longer than required for recognition (2 sec), while in a second experiment durations were close to the minimum time required for recognition (67-101 ms). We found significant RS for brief presentations (albeit with a reduced magnitude), which again persisted when controlling for performance. This suggests a substantial amount of RS occurs during recognition. Performance-independent RS in object cortex 3 INTRODUCTION A large extent of human occipital and temporal cortex responds more strongly to intact object images over other visual stimulation (Grill-Spector, 2003; Malach et al., 1995). This object-selective cortex contains a number of functionally-defined regions of interest (ROIs), including the lateral occipital complex (Kourtzi and Kanwisher, 2001; Grill-Spector, 2003) and fusiform regions (Kanwisher et al., 1997; Grill-Spector et al., 2000). These ROIs are implicated in object recognition (Grill-Spector et al., 2000) and have been shown to correlate with the perception of different classes of objects (GrillSpector et al., 2004; Tong et al., 1998). The fMRI BOLD response in object-selective cortex is consistently lower for repeated versus novel images (Henson, 2003; Grill-Spector, et al., 1999; Epstein, et al., 2003; Koutstaal et al., 2001; Winston et al., 2004). This phenomenon has been referred to as repetition suppression (Henson, 2003), functional magnetic resonance adaptation (Grill-Spector et al. 1999, Grill-Spector and Malach, 2001), and repetition-priming (Schacter and Buckner, 1998). Here, we will use the term Repetition suppression (RS) to refer to reduced activation in object-selective cortex with repeated object presentation. Interest in RS has been motivated by several (possibly overlapping) interpretations of this phenomenon. It is thought to reflect priming, performance improvement (faster response times and greater accuracy) that is often observed in conjunction with stimulus repetition (Schacter and Buckner, 1998; Wiggs and Martin, 1998, Dobbins 2004, Lustig 2004). Conversely, it may relate to classical adaptation effects found in earlier visual areas (Boynton and Finney, 2003; Tolias et al., 2001; Bradley et al., 1988), which tend to correlate with impaired task performance (Boynton and Finney, 2003; Bradley et al., 1988), although they sometimes facilitate certain fine discriminations (Clifford and Performance-independent RS in object cortex 4 Wenderoth, 1999). Repetition suppression may also reflect memory processes, which may be independent from performance changes (Jiang et al. 2000; Ranganath and Rainer, 2003), and may relate to similar effects found using electrophysiology in macaque inferotemporal cortex (Miller and Desimone, 1994). Further, RS is used as an experimental tool to characterize the selectivity of neuronal populations (Grill-Spector and Malach 2001; Kourtzi and Kanwisher, 2001; Vuilleumier et al., 2002; Avidan et al. 2002; Winston et al., 2004). Finally, it may reflect changes in the nature of object representations as a consequence of repetition (Wiggs and Martin, 1998). These studies indicate that RS is a useful measure, and may provide information on many aspects of object representation and behavior. Different interpretations of RS focus on distinct factors that may contribute to this phenomenon. For instance, the use of RS to investigate priming associates RS with performance changes, while the examination of mnemonic processes relates RS to repetition independently of performance changes. Although repetition and performance changes are known to be correlated, they may not coincide under all conditions. Further, RS may reflect only one of these factors, but not the other. For instance, RS may be driven by changes in response time (e.g., shorter response times may produce lower BOLD), but not repetition. Variations in response time to different nonrepeated stimuli might produce the same sort of changes in the BOLD signal as variations caused by repetition. If this is the case, interpretations relying on the relationship between RS and repetition would be difficult to justify. To examine whether stimulus-specific repetition, performance or both contribute to RS, we conducted a set of rapid event-related fMRI experiments. We imaged objectselective cortex in an MRI scanner while subjects classified these images as feline Performance-independent RS in object cortex 5 (housecats, lions and tigers) or not feline (horses, donkeys and dogs) and compared neuroimaging and behavioral data (Figure 1). Half of the repeated objects were felines and half were other four legged animals. The presentation of repeated images included parametric variations of several repetition parameters: presentation number of images (18 presentations, or 7 repetitions), number of intervening images between repeats (0-16+) and time between repeats (0-32+ sec). This design allows for a better characterization of RS and provides multiple ways to examine the relationship between RS and performance (see Buracas et al., 2005). Further, by measuring both repetition and performance information for each trial, we could separate out the effects of each factor, to examine whether one or both contribute to RS. A related consideration is whether RS represents changes in neural activity occurring during the process of recognition, or whether it reflects changes after recognition occurs. Under most conditions, recognition reflects only a small part of the time period from which the BOLD signal is derived. Human observers can recognize briefly presented (~100ms) and masked stimuli (Grill-Spector and Kanwisher 2005; Zago et al., 2005), yet the BOLD response integrates temporally over several seconds. As a consequence, the observed changes in the BOLD signal associated with RS may result from processes that occur well after the subject has recognized the object. To address this question, we manipulated stimulus presentation duration across two experiments. In the first experiment, the duration was substantially longer than required for recognition (2 sec), while in the second experiment we presented stimuli for a short duration (67, 85, or 101ms) and masked them. We masked the briefly-presented images with scrambled images, which reduce neural activity in object selective cortex (Kovacs et al., 1995; Grill-Spector et al., 2000). The duration of presentation in our Performance-independent RS in object cortex 6 second experiment was determined separately for each subject to achieve at least 85% accuracy in the classification task (see Figure 1 and Methods). Varying the presentation time allowed us to examine whether the factors that explain RS are the same for early periods in a trial, when recognition is taking place, versus later periods that occur after the subject has recognized the object. METHODS We conducted two experiments that had the same basic design, but varied in stimulus presentation durations (Figure 1). Experiment 1: We presented gray level pictures of animals in a rapid event-related design intermixed with blank fixation trials. Each scan consisted of 127 two-second trials that included: 43 fixation trials, 36 nonrepeated images that were shown once, and six repeated images, which were shown a total of eight times each. The nonrepeated condition included both nonrepeated distractors and the first presentation of repeated images. Stimuli consisted of gray level images of animals: housecats, lions, tigers, dogs, horses, and donkeys. Subjects were instructed to classify whether the animal was feline (cat, lion or tiger) or not (horse, donkey or dog) while fixating. The classification task was independent of repetition: half of the images (both repeated and non repeated) were felines and the rest were other 4-legged animals. During fixation trials, subjects were instructed to press a button for brief (~50-ms) fixation flickers, to ensure consistent attention throughout the scan. The order of repeated, nonrepeated, and fixation conditions was counterbalanced for each scan and images did not repeat across scans. The order of image presentation within the repeated condition was determined by an algorithm that optimized counterbalancing for number of intervening trials between repeats. Subjects Performance-independent RS in object cortex 7 performed at ceiling for this task (mean accuracy ≥ 94% for all subjects). Experiment 2: used the same basic design as Experiment 1, with the exception that images were presented briefly (67, 85, or 101ms) and then were followed by a masking stimulus. The masking stimulus was a scrambled image (randomly-assigned object image broken into 100 tiles which were randomly shuffled). Prior to scanning, subjects participated in a psychophysical experiment in which we determined the minimum exposure duration for 85% correct performance (Grill-Spector and Kanwisher, 2005). This duration was used during the fMRI scans. A psychophysical performance curve from one subject is shown in Figure 1. The exposure duration used during scanning is shown in red. The same animal images were used as Experiment 1, except that a different subset of images were repeated (48 images randomly selected from a set of 384 total images). Five subjects who participated in Experiment 1 also participated in Experiment 2. The average time that had elapsed between experiments was 16 months. Subjects. Eight subjects (3 female, ages 21-35) participated in Experiment 1. Seven subjects (3 female, ages 21-44) participated in Experiment 2. Five subjects participated in both experiments. All subjects were right-handed and had normal or corrected-to-normal vision. Each subject participated in one scanning session per experiment, which included eight scans of the experiment and a reference scan to define object-selective cortex. For one subject on the first experiment, data were only collected for 5 scans due to subject movement. The experiments were undertaken with the written consent of each subject, and procedures were approved in advance by the Stanford Internal Review Board on Human Subjects Research. Subject initials were changed to protect their privacy. fMRI data collection. MR imaging was performed on a research-only GE 3T Signa scanner, using a custom transmit-received occipital quadrature RF surface coil (Nova Performance-independent RS in object cortex 8 Medical, Inc., Wilmington, MA, USA). The dimensions of the coil are: interior dimension left/right = 9 inches, exterior dimension left/right = 10 1/8 inches; height= 5 1/4 inches; length = 7.5 inches. Subjects lay supine with the coil positioned beneath the head, and a front-angled mirror mounted overhead for viewing the stimulus. Data were collected from sixteen oblique slices, positioned perpendicularly to the calcarine sulcus, with a slice thickness of 4 mm. First, a set of anatomical inplane images was collected using a T1-weighted SPGR pulse sequence (TR = 1000 ms, min TE, FA = 45°, 2 NEX, FOV = 200 mm), with an inplane resolution of 0.78 x 0.78 mm. Then, functional scans were collected in the same slices, using a one-shot, T2*-sensitive, spiraltrajectory (Glover, 1999) gradient-recalled-echo pulse sequence (TE = 30 ms, TR = 1000 ms, FA = 60°, FOV = 200 mm, 16 slices which were 4-mm thick and with effective inplane pixel size = 3.125 x 3.125 mm). Functional volumes were collected with a time resolution of 1 second. Since there is a tradeoff between temporal and spatial resolution, we chose to use a relatively high temporal resolution (TR = 1 second) to get accurate deconvolution of rapid event-related data, but only covered posterior regions of the brain at this resolution. Our slice prescription covered occipito-temporal cortex and posterior parietal cortex. Behavioral responses were collected during scanning using a magnet-compatible button box connected to the stimulus computer. In addition, a whole-brain anatomical scan was run on each subject during a separate session. The anatomical images from this scan were segmented into gray and white matter, to restrict activation patterns to gray matter and for creating surface-based visualizations (Figure 2). Stimuli. We used 192 gray level images of felines and 192 images of other 4-legged animals that subtended a visual angle of 11.9 degrees. All stimuli were programmed in Performance-independent RS in object cortex 9 MATLAB (The Mathworks, Inc., Natick, MA, version 5.1) using the Psychophysics Toolbox (Brainard, 1997). Stimuli were projected on to a screen mounted on the cradle for the coil. Subjects lay on their backs in the bore of the MR scanner and viewed the screen through an angled first-surface mirror positioned 3” in front of their eyes. Block-design localizer scans. We used an independent localizer scan to define objectselective cortex (see ROI selection below). Subjects were presented with gray-level images of animals, novel objects (abstract sculptures), empty scenes, and scrambled objects (Grill-Spector et al., 2004). Stimuli were presented at rate of 1Hz in blocks for 16 seconds. Subjects were asked to covertly name the stimuli while fixating. Retinotopic mapping scans. We defined visual area V1 using separate retinotopic mapping scans. Retinotopic ROIs were imported into the event-related sessions by aligning both sessions to a high-resolution volume anatomy for each subject. The stimuli for these scans consisted of a 30° wedge containing object images which extended 10° in visual angle from the fovea, and which rotated for 6 cycles of 32 sec/cycle, for at least two scans for each subject (one clockwise and one counterclockwise rotation; details in Grill-Spector and Malach, 2004). Visual areas were defined by counting phase reversals at representations of the vertical / horizontal meridians, as described previously (Sereno et al., 1995). The ROIs defining these visual regions were then restricted to those voxels that showed a response to our object stimuli (object stimuli > blank baseline, t-test p < 0.01). For one subject in Experiment 1, the imaging prescription did not extend posterior enough to include all of V1, so this subject was excluded from the V1 analyses. Data analysis. Data were analyzed using the mrVista analysis package (http://white.stanford.edu/software/) for MATLAB (version 6.5), and SurfRelax segmentation/visualization software (Larsson, 2001). Event-related analyses, including Performance-independent RS in object cortex 10 application of general linear models and hypothesis tests to generate contrast maps, were performed as outlined in Dale and Buckner (1997) and Burock and Dale (2000). ROI selection. We defined all ROIs on a subject-by-subject basis. LO and Fusiform ROIs were selected based on a conjunction of functional and anatomical cues. ROIs had to be in the appropriate anatomical location (near the lateral occipital sulcus for LO, within the fusiform gyrus for pFus), respond significantly more to intact images of animals versus scrambled images (Malach et al., 1995), and remain centered in the same place at different statistical thresholds. The minimum threshold for a voxel being considered responsive to animal images more than scrambled animals was p < 10 (t-test on the contrast animals>scrambled). Bilateral LO and pFus ROIs were defined in all subjects for both experiments. However, because of low signal strength during the masked experiment (Experiment 2) combined with the drop off from our surface coil we were not able to get reliable data from the pFus ROIs from 2 of our 7 subjects in the second experiment. The fusiform data from that experiment therefore derives from the other 5 subjects. Sorting Data by Repetition Parameters. All data were sorted according to several criteria. Sortings included: (a) Repeated vs. nonrepeated: All repeated trials across all conditions were collapsed into one bin. This analysis measures the basic RS effect (Figure 3). (b) Sorting by presentation number: The first presentation was the nonrepeated condition, the second presentation was the first time the stimulus was repeated, etc., up to the eighth occurrence of the image. (c) Sorting by intervening stimuli: We grouped repeated trials into 4 bins based on number of animal images between repeats: the bins had 0, 1-3, 4-7, and ≥ 8 intervening images. (d) Time between repeats (inter-stimulus interval): We grouped repeated trials into 4 bins based on the time that elapsed between Performance-independent RS in object cortex 11 repeats: 0, 2-6, 8-14, and ≥ 16 seconds. Analyses b-d examine the effect of repetition parameters on RS (Figures 4, 5). (e) Sorting by response time and repetition: nonrepeated and repeated trials were separately grouped into four bins according to the response time of each trial, from fastest to slowest trials (Figure 7). By first separating trials to repeated and nonrepeated conditions and then binning the data by response time (RT), each bin contained the same number of correct trials. Further, this sorting also allowed us to calculate separate regressions between RT and the fMRI signal on the nonrepeated and repeated data (Figure 6). We also performed a similar sorting to (e) above by first binning all response times into four bins, then subdividing each bin into nonrepeated and repeated trials. Because the distribution of response times was different for repeated and nonrepeated trials, this sorting included different numbers of repeated and non-repeated trials in each bin. Results of the second analysis were similar to the analysis in Figure 7. Time Series Processing. Functional time series were detrended using a temporal highpass filter to remove scanner signal drift, and converted to percent signal by dividing each voxel's time series by its mean intensity. We then deconvolved each voxel’s time series according to each sorting (Burock and Dale, 2000; Dale and Buckner, 1997). This method does not assume a shape for the hemodynamic response to each condition; rather, it uses a general linear model to estimate the mean and variance of response at each time point for each condition. The hemodynamic response at each voxel to the same stimulus presented several times over an experiment is assumed to be governed by the following linear time invariant system: Performance-independent RS in object cortex 12 ) ( ) ( * ) ( ) ( 1 t n t x t h t y n