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Is In-out asymmetry diagnostic of visual crowding? Ramakrishna Chakravarthi and Alasdair D F Clarke Objects in clutter are hard to identify. This clutter induced interference is known as visual crowding. Visual crowding has been extensively studied over the past several decades and has provided valuable insights into several cognitive processes, including object recognition (Levi, 2008; Whitney & Levi, 2011), reading (Martelli, Di Filippo, Spinelli, & Zoccolotti, 2009; Pelli et al., 2007), and awareness (Atas, Faivre, Timmermans, Cleeremans, & Kouider, 2014; Kouider, Berthet, & Faivre, 2011). However, deleterious interactions between an object and its flankers can also occur due to other spatial processes, including surround suppression and contrast masking (Levi, Hariharan, & Klein, 2002; Pelli, Palomares, & Majaj, 2004; Petrov, Popple, & McKee, 2007), wherein nearby flankers suppress the target. It has been suggested (Levi et al., 2002; Pelli et al., 2004) that crowding and contrast masking mechanisms can be distinguished by a set of properties: masking impairs detection, whereas crowding only affects identification; masking scales with the size of the objects, whereas crowding does not; masking is independent of eccentricity, whereas crowding is deeply dependent on it. Hence, the diagnostic test to determine if a particular target has suffered from crowding and not from masking was to check if the spatial extent of the target-flanker interaction scaled with eccentricity but not with stimulus size. If it did, then it was crowding. However, this set of diagnostic properties was challenged by Petrov et al. (2007), who argued that surround suppression also has the same set of features. They proposed that the unique property differentiating crowding and surround suppression was that crowding displayed a specific sort of asymmetry known as In-Out Asymmetry (IOA) that surround suppression did not. IOA is the finding that the flanker farther away from the fovea (the ‘outward’ flanker) relative to the target causes more crowding than the flanker that is closer to the fovea (the ‘inward’ flanker). This appears counter-intuitive since the inward flanker should be more ‘perceptible’, because of better acuity for objects closer to the fovea, and hence should lead to more interference. However, increased interference from the outward flanker can be explained by cortical magnification, due to which neurons that fire to the outward flanker are closer to the neurons responding to the target than are the neurons responding to the inward flanker (Pelli, 2008), and hence can cause more interference. IOA has been noticed and reported in a variety of settings right from the early days of crowding research (Bex, Dakin, & Simmers, 2003; Bouma, 1970; Manassi, Sayim, & Herzog, 2012). Consequently, Petrov et al. (2007) proposed that demonstration of IOA should be considered diagnostic of crowding. However, IOA is not observed in all situations. For example, Petrov and Meleshkevich (2011a) found that, in the specific setup they used, IOA was present only in the horizontal meridian and not at other locations. In fact, most previous studies where IOA has been demonstrated also seem to have documented it along the horizontal axis; few have tested other locations. They also showed that IOA was stronger if participants had to monitor two spatial locations than if the target was consistently presented at the same location. They argued that this effect could be ascribed to attentional deployment. That is, IOA is observed only if attention is spread out, but not if it can be focused on a given location, which is the case when the target is predictably presented at the same location. Further evidence for the role of attention was provided when, in a different study, they showed that varying the target location, and thus increasing the need for attention to monitor more locations, increased the strength of IOA. Additionally, when participants had to attend a central location, IOA was eliminated or even reversed in some participants (Petrov & Meleshkevich, 2011b). On the other hand, there are potential issues with the stimulus setup and participants used in these paradigms. Generally, these studies have been conducted with a few, experienced participants. Further, considerable inter-observer variability has been documented. A property should be evident consistently in all observers and not just experienced ones if it is to be considered diagnostic. Incidentally, Petrov and Meleshkevich (2011b, 2011a) used coarsely discriminable stimuli (identifying Gabor orientations separated by 90 deg), which themselves might result in little to no crowding (Pelli et al., 2004). Hence, stimulus choice might also be important in determining the robustness of IOA. Given these findings, the question arises if IOA exists and if it can be considered diagnostic of crowding. This study, therefore, is intended to address a few related issues: 1) Does IOA exist? 2) If yes, can it be observed in a relatively larger sample of naïve observers and how prevalent is it within this sample? 3) The strength of IOA appeared to vary dramatically. Here we hope to derive an estimate of the strength of IOA and its variance across the sample tested. 4) Is IOA restricted to the horizontal meridian, as claimed by Petrov and Meleshkevich (2011a)? If so, it cannot be considered diagnostic of crowding. 5) It was suggested that IOA depended on attentional deployment. This study will test if this is the case by directly manipulating attentional deployment using precues in a typical crowding paradigm. Finally, we will use letters as stimuli, which require fine discrimination and have been widely documented to be susceptible to crowding. Methods: 40 undergraduate students will be recruited at two separate sites (20 each at Universities of Aberdeen and Essex). Stimuli will be generated using MATLAB with Psychtoolbox extensions (Kleiner, Brainard, & Pelli, 2007) and presented on CRT monitors in a darkened room. Stimuli will be 9 black letters in the Sloan font (D, H, K, N, O, R, S, V and Z) presented on a grey background. The letter C is omitted since C and O are much less discriminable than other pairs in the Sloan font (Elliott, Whitaker, & Bonette, 1990). One target and one flanker from this set will be randomly chosen on any given trial. The target will be presented at 8 deg eccentricity at one of four locations (left, right, above, or below the fixation, on the horizontal or vertical meridian). Two white lines, 2 deg on either side of the meridian, will mark the position of each target location throughout the experiment, so as to reduce confusion about which of the two letters is the target. These lines should not cause any crowding themselves, as they will be placed far apart in the tangential direction and will be of the opposite contrast polarity to the target (Kooi, Toet, Tripathy, & Levi, 1994; Toet & Levi, 1992). Participants will be tested in three conditions: Blocked target location, Random target location, and Random target location with precue. In the blocked target location condition, the target will always be presented at the same location pre-chosen from the four possible locations. In the random target location condition, the target can be presented in any of the four locations with equal probability. Finally, the random target location with precue condition will utilise the same procedure as the previous condition, but with a precue (a 0.3 deg red dot) presented at the target location 100 ms before target onset (Nakayama & Mackeben, 1989). The cue will last for 50 ms. The target might be accompanied by a single flanker, placed either inwards or outwards relative to the target. The target (and flanker) will be presented for 100 ms. The participant will then be asked to report the identity of the target letter. No feedback will be provided. Overall, we will assess performance in three conditions, four target locations and two flanker locations, for a total of 24 combinations. Figure 1: Stimulus conditions in experiment 1. Panel (a) illustrates trials in the ‘Blocked target location’ condition. Here, targets are always presented at the same location within a block. In this example, a single ‘outward’ flanker is presented along with the target. However, in other blocks, the flanker might be presented on the ‘inward’ side or not presented. The size of the letters (and hence spacing, which is set as 1.1*size) is controlled by the QUEST algorithm to determine flanked acuity. Panel (b) illustrates trials in the ‘Random target location’ condition, where targets and their flankers can be presented in any of the four locations within the block. Finally, panel (c) illustrates trials in the ‘Random target location with precue’ condition where a target is presented at a randomly chosen but precued location. Panels a and b show outward flankers, and panel c shows inward flankers. Following Song, Levi and Pelli (2014) and Petrov and Meleshkevich (2011b, 2011a), we will compare flanked with unflanked visual acuity to determine the extent of crowding for each combination. We will obtain, separately, flanked and unflanked acuity thresholds using the QUEST algorithm. This algorithm will control the size of an isolated letter to estimate unflanked acuity and it will control the sizes of both the target and its flanker to obtain flanked acuity. In the latter case, the centre-to-centre spacing between the target and the flanker will be fixed at 1.1 times the size, such that the spacing increases with size, in order to prevent overlap and to measure the extent of crowding. Each acuity (flanked and unflanked for each condition-target location-flanker location combination) will be assessed twice with a run of 40 trials each and averaged. The ratio of flanked to unflanked acuity for each combination, called the crowding factor (Petrov & Meleshkevich, 2011b, 2011a), will specify the extent of crowding. A crowding factor of greater than one will indicate the presence of crowding, and the larger the factor the larger the target-flanker interference zone is. We will then take a ratio of outward to inward crowding factors. A ratio of greater than one, here, will indicate IOA. This ratio can be used to determine the answers to the five questions posed above. In sum, we will determine 48 flanked acuity thresholds and 24 unflanked thresholds. These will be randomly intermixed and distributed over two sessions of about 45 min each per participant. The parameters proposed here (target eccentricity, target location marker size and configuration, stimulus duration, cue duration, colour and size, etc.) are based on reasonable estimates derived from previous successful crowding experiments. However, these might not be optimal for testing our questions. We will initially run 4-5 pilot participants with these parameters and ascertain if we can obtain meaningful thresholds. If we do not, then we will modify the parameters accordingly. Nevertheless, we plan to also report what didn’t work. Experiment 2: If we discover an effect of attentional deployment in experiment 1, we will run a second experiment that will more systematically vary deployment of both endogenous and exogenous attention to test if either kind of attention influences IOA. Here, we will use 8 possible target locations arranged equidistantly along an imaginary circle around fixation (radius 8 deg), indicated by pairs of lines (their orientations are changed relative to experiment 1, because using the same orientations as in that experiment would cause confusion due to the extra locations coupled with grouping due to proximity of lines belonging to adjacent targets). We will then cue 1, 2, 4 or all 8 locations, either endogenously (white arrows pointing to the locations with an onset 350 ms before target onset) or exogenously (a red dot at the relevant target locations 100 ms before target onset). Subsequently a target and one flanker (inward or outward) will be presented at one of the cued locations. We will determine crowding factors under these conditions and check if IOA is affected by the number of cued locations and the type of cueing. Figure 2: Protocol for Experiment 2. In this experiment, there will be eight target locations, indicated by pairs of white lines. 1, 2, 4 or 8 locations will be precued either endogenously (panel a) or exogenously (panel b). The target with its flanker (inward, outward or none) will be presented in one of the cued locations. Acknowledgements We thank John Greenwood and Mauro Manassi for valuable comments on a previous version of this proposal. References Atas, A., Faivre, N., Timmermans, B., Cleeremans, A., & Kouider, S. (2014). Nonconscious learning from crowded sequences. Psychological Science, 25(1), 113–119. Bex, P. J., Dakin, S. C., & Simmers, A. J. (2003). The shape and size of crowding for moving targets. Vision Research, 43(27), 2895–2904. https://doi.org/10.1016/S00426989(03)00460-7 Bouma, H. (1970). 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