A general ability for judging simple and complex ensembles.

People can report summary statistics for various features about a group of objects. One theory is that different abilities support ensemble judgments about low-level features like color versus high-level features like identity. Existing research mostly evaluates such claims based on evidence of correlations within and between feature domains. However, correlations between two identical tasks that only differ in the type of feature that is used can be inflated by method variance. Another concern is that conclusions about high-level features are mostly based on faces. We used latent variable methods on data from 237 participants to investigate the abilities supporting low-level and high-level feature ensemble judgments. Ensemble judgment was measured with six distinct tests, each requiring judgments for a distinct low-level or high-level feature, using different task requirements. We also controlled for other general visual abilities when examining how low-level and high-level ensemble abilities relate to each other. Confirmatory factor analyses showed a perfect correlation between the two factors, suggesting a single ability. There was a unique relationship between these two factors beyond the influence of object recognition and perceptual speed. Additional results from 117 of the same participants also ruled out the role of working memory. This study provides strong evidence of a general ensemble judgment ability across a wide range of features at the latent level and characterizes its relationship to other visual abilities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Measuring object recognition ability: Reliability, validity, and the aggregate z-score approach.

Measurement of domain-general object recognition ability (o) requires minimization of domain-specific variance. One approach is to model o as a latent variable explaining performance on a battery of tests which differ in task demands and stimuli; however, time and sample requirements may be prohibitive. Alternatively, an aggregate measure of o can be obtained by averaging z-scores across tests. Using data from Sunday et al., Journal of Experimental Psychology: General, 151, 676-694, (2022), we demonstrated that aggregate scores from just two such object recognition tests provide a good approximation (r = .79) of factor scores calculated from a model using a much larger set of tests. Some test combinations produced correlations of up to r = .87 with factor scores. We then revised these tests to reduce testing time, and developed an odd one out task, using a unique object category on nearly every trial, to increase task and stimuli diversity. To validate our measures, 163 participants completed the object recognition tests on two occasions, one month apart. Providing the first evidence that o is stable over time, our short aggregate o measure demonstrated good test-retest reliability (r = .77). The stability of o could not be completely accounted for by intelligence, perceptual speed, and early visual ability. Structural equation modeling suggested that our tests load significantly onto the same latent variable, and revealed that as a latent variable, o is highly stable (r = .93). Aggregation is an efficient method for estimating o, allowing investigation of individual differences in object recognition ability to be more accessible in future studies.

Challenges in replication: Does amygdala gray matter volume relate to social network size?

In this work, we tried to replicate and extend prior research on the relationship between social network size and the volume of the amygdala. We focused on the earliest evidence for this relationship (Bickart et al., Nature Neuroscience 14(2), 163-164, 2011) and another methodologically unique study that often is cited as a replication (Kanai et al., Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012). Despite their tight link in the literature, we argue that Kanai et al. (Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012) is not a replication of Bickart et al. Nature Neuroscience 14(2), 163-164 (2011), because it uses different morphometric measurements. We collected data from 128 participants on a 7-Tesla MRI and examined variations in gray matter volume (GMV) in the amygdala and its nuclei. We found inconclusive support for a correlation between measures of real-world social network and amygdala GMV, with small effect sizes and only anecdotal evidence for a positive relationship. We found support for the absence of a correlation between measures of online social network and amygdala GMV. We discuss different challenges faced in replication attempts for small effects, as initially reported in these two studies, and suggest that the results would be most helpful in the context of estimation and future meta-analytical efforts. Our findings underscore the value of a narrow approach in replication of brain-behavior relationships, one that is focused enough to investigate the specifics of what is measured. This approach can provide a complementary perspective to the more popular "thematic" alternative, in which conclusions are often broader but where conclusions may become disconnected from the evidence.

Distinct but related abilities for visual and haptic object recognition.

People vary in their ability to recognize objects visually. Individual differences for matching and recognizing objects visually is supported by a domain-general ability capturing common variance across different tasks (e.g., Richler et al., Psychological Review, 126, 226-251, 2019). Behavioral (e.g., Cooke et al., Neuropsychologia, 45, 484-495, 2007) and neural evidence (e.g., Amedi, Cerebral Cortex, 12, 1202-1212, 2002) suggest overlapping mechanisms in the processing of visual and haptic information in the service of object recognition, but it is unclear whether such group-average results generalize to individual differences. Psychometrically validated measures are required, which have been lacking in the haptic modality. We investigate whether object recognition ability is specific to vision or extends to haptics using psychometric measures we have developed. We use multiple visual and haptic tests with different objects and different formats to measure domain-general visual and haptic abilities and to test for relations across them. We measured object recognition abilities using two visual tests and four haptic tests (two each for two kinds of haptic exploration) in 97 participants. Partial correlation and confirmatory factor analyses converge to support the existence of a domain-general haptic object recognition ability that is moderately correlated with domain-general visual object recognition ability. Visual and haptic abilities share about 25% of their variance, supporting the existence of a multisensory domain-general ability while leaving a substantial amount of residual variance for modality-specific abilities. These results extend our understanding of the structure of object recognition abilities; while there are mechanisms that may generalize across categories, tasks, and modalities, there are still other mechanisms that are distinct between modalities.

Inaugural editorial for Journal of Experimental Psychology: Human Perception and Performance.

As the author begins her second term as editor of the Journal of Experimental Psychology: Human Perception and Performance (and third term as editor of an APA journal), she wants to reflect on the editorial team's successes, on how the work they publish is changing, and looks forward to new ways for the Journal stakeholders to meet their common goals. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

How general is ensemble perception?

People can summarize features of groups of objects (e.g., the mean size of apples). Claims of dissociations or common mechanisms supporting such ensemble perception (EP) judgments have generally been made on the basis of correlations between pairs of tasks. These correlations can be inflated because they use the same stimuli, summary statistics and/or task format. Performance on EP tasks also correlates with that on object recognition (OR) tasks. Here, we seek evidence for a general EP ability that is also distinct from OR ability. Two-hundred participants completed three tasks that did not overlap in stimuli, summary statistic or task format. Participants performed a diversity comparison for arrays of nonsense blobs, a mean identity judgment with ensembles of Transformer toys, and the novel object memory task with novel objects (NOMT-Greeble). We hypothesized that EP contributes to the first two of these tasks, while OR contributes only to the last two. Performance on the two tasks suggested to tap an EP ability were correlated after controlling for the third task. Confirmatory factor analysis was used to test our predictions without the confound of measurement error. Correlations between factors assumed to share influence from EP or from OR were higher than that between the factors that we expect did not share these influences. The results provide the first clear evidence for a domain-general EP ability distinct from OR. We argue that understanding such a general ability will require a change in designs and analytical approaches in the study if individual differences in EP.

Evidence for an amodal domain-general object recognition ability.

A general object recognition ability predicts performance across a variety of high-level visual tests, categories, and performance in haptic recognition. Does this ability extend to auditory recognition? Vision and haptics tap into similar representations of shape and texture. In contrast, features of auditory perception like pitch, timbre, or loudness do not readily translate into shape percepts related to edges, surfaces, or spatial arrangement of parts. We find that an auditory object recognition ability correlates highly with a visual object recognition ability after controlling for general intelligence, perceptual speed, low-level visual ability, and memory ability. Auditory object recognition was a stronger predictor of visual object recognition than all control measures across two experiments, even though those control variables were also tested visually. These results point towards a single high-level ability used in both vision and audition. Much work highlights how the integration of visual and auditory information is important in specific domains (e.g., speech, music), with evidence for some overlap of visual and auditory neural representations. Our results are the first to reveal a domain-general ability, o, that predicts object recognition performance in both visual and auditory tests. Because o is domain-general, it reveals mechanisms that apply across a wide range of situations, independent of experience and knowledge. As o is distinct from general intelligence, it is well positioned to potentially add predictive validity when explaining individual differences in a variety of tasks, above and beyond measures of common cognitive abilities like general intelligence and working memory.

Deep whole brain segmentation of 7T structural MRI.

7T magnetic resonance imaging (MRI) has the potential to drive our understanding of human brain function through new contrast and enhanced resolution. Whole brain segmentation is a key neuroimaging technique that allows for region-by-region analysis of the brain. Segmentation is also an important preliminary step that provides spatial and volumetric information for running other neuroimaging pipelines. Spatially localized atlas network tiles (SLANT) is a popular 3D convolutional neural network (CNN) tool that breaks the whole brain segmentation task into localized sub-tasks. Each sub-task involves a specific spatial location handled by an independent 3D convolutional network to provide high resolution whole brain segmentation results. SLANT has been widely used to generate whole brain segmentations from structural scans acquired on 3T MRI. However, the use of SLANT for whole brain segmentation from structural 7T MRI scans has not been successful due to the inhomogeneous image contrast usually seen across the brain in 7T MRI. For instance, we demonstrate the mean percent difference of SLANT label volumes between a 3T scan-rescan is approximately 1.73%, whereas its 3T-7T scan-rescan counterpart has higher differences around 15.13%. Our approach to address this problem is to register the whole brain segmentation performed on 3T MRI to 7T MRI and use this information to finetune SLANT for structural 7T MRI. With the finetuned SLANT pipeline, we observe a lower mean relative difference in the label volumes of ~8.43% acquired from structural 7T MRI data. Dice similarity coefficient between SLANT segmentation on the 3T MRI scan and the after finetuning SLANT segmentation on the 7T MRI increased from 0.79 to 0.83 with p<0.01. These results suggest finetuning of SLANT is a viable solution for improving whole brain segmentation on high resolution 7T structural imaging.

Does food recognition depend on color?

Color is considered important in food perception, but its role in food-specific visual mechanisms is unclear. We explore this question in North American adults. We build on work revealing contributions from domain-general and domain-specific abilities in food recognition and a negative correlation between the domain-specific component and food neophobia (FN, aversion to novel food). In Study 1, participants performed two food-recognition tests, one in color and one in grayscale. Removing color reduced performance, but food recognition was predicted by domain-general and -specific abilities, and FN negatively correlated with food recognition. In Study 2, we removed color from both food tests. Food recognition was still predicted by domain-general and food-specific abilities, but with a relation between food-specific ability and FN. In Study 3, color-blind men reported lower FN than men with normal color perception. These results suggest two separate food-specific recognition mechanisms, only one of which is dependent on color.

Object recognition ability predicts category learning with medical images.

We investigated the relationship between category learning and domain-general object recognition ability (o). We assessed this relationship in a radiological context, using a category learning test in which participants judged whether white blood cells were cancerous. In study 1, Bayesian evidence negated a relationship between o and category learning. This lack of correlation occurred despite high reliability in all measurements. However, participants only received feedback on the first 10 of 60 trials. In study 2, we assigned participants to one of two conditions: feedback on only the first 10 trials, or on all 60 trials of the category learning test. We found strong Bayesian evidence for a correlation between o and categorisation accuracy in the full-feedback condition, but not when feedback was limited to early trials. Moderate Bayesian evidence supported a difference between these correlations. Without feedback, participants may stick to simple rules they formulate at the start of category learning, when trials are easier. Feedback may encourage participants to abandon less effective rules and switch to exemplar learning. This work provides the first evidence relating o to a specific learning mechanism, suggesting this ability is more dependent upon exemplar learning mechanisms than rule abstraction. Object-recognition ability could complement other sources of individual differences when predicting accuracy of medical image interpretation.

The neural correlates of domain-general visual ability.

People vary in their general ability to compare, identify, and remember objects. Research using latent variable modeling identifies a domain-general visual recognition ability (called o) that reflects correlations among different visual tasks and categories. We measure associations between a psychometrically-sensitive measure of o and a neurometrically-sensitive measure of visual sensitivity to shape. We report evidence for distributed neural correlates of o using functional and anatomical regions-of-interest (ROIs) as well as whole brain analyses. Neural selectivity to shape is associated with o in several regions of the ventral pathway, as well as additional foci in parietal and premotor cortex. Multivariate analyses suggest the distributed effects in ventral cortex reflect a common mechanism. The network of brain areas where neural selectivity predicts o is similar to that evoked by the most informative features for object recognition in prior work, showing convergence of 2 different approaches on identifying areas that support the best object recognition performance. Because o predicts performance across many visual tasks for both novel and familiar objects, we propose that o could predict the magnitude of neural changes in task-relevant areas following experience with specific task and object category.

Visual object recognition ability is not related to experience with visual arts.

Visual arts require the ability to process, categorize, recognize, and understand a variety of visual inputs. These challenges may engage and even influence mechanisms that are also relevant for visual object recognition beyond visual arts. A domain-general object recognition ability that applies broadly across a range of visual tasks was recently discovered. Here, we ask whether experience with visual arts is correlated with this domain-general ability. We developed a new survey to measure general visual arts experience and use it to measure arts experience in 142 individuals in whom we also estimated domain-general object recognition ability. Despite our measures demonstrating high reliability in a large sample size, we found substantial evidence (BF01 = 9.52) for no correlation between visual arts experience and general object recognition ability. This suggests that experience in visual arts has little influence on object recognition skills or vice versa, at least in our sample ranging from low to moderately high levels of arts experience. Our methods can be extended to other populations and our results should be replicated, as they suggest some limitations for the generalization of programs targeting visual literacy beyond the visual arts.

Domain-general ability underlies complex object ensemble processing.

When seeing groups of objects, various features can be extracted to form an ensemble representation, including low-level features such as orientation and higher-level features like facial expression. Past research proposed distinct abilities for ensemble coding of high-level versus low-level visual features, but the only complex objects used were faces. Here, we examine evidence for a shared ability supporting ensemble representations for complex objects from different object categories. In 2 experiments, participants completed an ensemble mean judgment task for an array of 4 objects, including planes and birds (Experiment 1) or cars and birds (Experiment 2). We also measured and controlled for domain-specific recognition ability. Across the 2 experiments, performance on ensemble judgments with different objects were correlated, even after controlled for domain-specific recognition abilities. These findings provide the strongest evidence to date of a domain-general ability involved in complex object ensemble coding. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Novel and familiar object recognition rely on the same ability.

There is recent evidence for a domain-general object recognition ability, called O, which is distinct from general intelligence and other cognitive and personality constructs. We extend the study of O by characterizing how it generalizes to the ability to recognize familiar objects and to the ability to make judgments of the average identity of ensembles of objects. We applied latent variable modeling to data collected from a sample of adults (N = 284) in three different tasks and for six different object domains (three novel and three familiar). The results replicated prior work in finding that on average 88% of the variance of lower-order factors could be accounted by O for novel objects. The latent constructs recruited by the higher-order factor for novel objects and for familiar objects were almost perfectly correlated and therefore functionally identical. A latent factor for ensemble perception shared about 42% of the variance with O, suggesting at least strong overlap between abilities supporting judgments about individual objects and ensemble of objects. This work extends the theoretical reach of O by showing generalization across two dimensions (familiar vs. novel objects; individual vs. ensemble object perception). With respect to the structure of individual differences in high-level vision, researchers would benefit from accounting for the contribution of O when seeking to understand various domain-specific abilities. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Haptic object recognition based on shape relates to visual object recognition ability.

Visual object recognition depends in large part on a domain-general ability (Richler et al. Psychol Rev 126(2): 226-251, 2019). Given evidence pointing towards shared mechanisms for object perception across vision and touch, we ask whether individual differences in haptic and visual object recognition are related. We use existing validated visual tests to estimate visual object recognition ability and relate it to performance on two novel tests of haptic object recognition ability (n = 66). One test includes complex objects that participants chose to explore with a hand grasp. The other test uses a simpler stimulus set that participants chose to explore with just their fingertips. Only performance on the haptic test with complex stimuli correlated with visual object recognition ability, suggesting a shared source of variance across task structures, stimuli, and modalities. A follow-up study using a visual version of the haptic test with simple stimuli shows a correlation with the original visual tests, suggesting that the limited complexity of the stimuli did not limit correlation with visual object recognition ability. Instead, we propose that the manner of exploration may be a critical factor in whether a haptic test relates to visual object recognition ability. Our results suggest a perceptual ability that spans at least across vision and touch, however, it may not be recruited during just fingertip exploration.

Contribution of a common ability in average and variability judgments.

People can make judgments about statistical properties of visual features within groups of objects, such as the average size, size variability, or numerosity of circles. Emerging from recent work is the view that these kinds of visual estimations, collectively dubbed ensemble perception, rely on independent abilities that are specific to the statistical property being estimated (mean, variance, range, numerosity). Here we revisit evidence for the claim that different statistical judgments (i.e., average and variability) for the same object feature are based on independent abilities. We tested a large sample of people, using a pre-registered open-ended sequential design to avoid ending up with weak evidence. We estimated the shared variance in ability across different ensemble judgments, with common constraints for the different tasks. We found that the abilities to judge the average size and the size variability for an array of circles are positively correlated, even after controlling for the ability to discriminate the size of single circles. Our results refute the idea that judgments of average and variability for the same object feature rely on completely independent abilities.

The Relation between Ensemble Coding of Length and Orientation Does Not Depend on Spatial Attention.

Most people are good at estimating summary statistics for different features of groups of objects. For instance, people can selectively attend to different features of a group of lines and report ensemble properties such as the mean length or mean orientation and there are reliable individual differences in such ensemble judgment abilities. Our recent study found decisive evidence in support of a correlation between the errors on mean length and mean orientation judgments (r = 0.62). The present study investigates one possible mechanism for this correlation. The ability to allocate spatial attention to single items varies across individuals, and in the recent study, this variability could have contributed to both judgments because the location of lines was unpredictable. Here, we replicate this prior work with arrays of lines with fully predictable spatial locations, to lower the contribution of the ability to distribute attention effectively over all items in a display. We observed a strong positive correlation between errors on the length and orientation averaging tasks (r = 0.65). This provides evidence against individual differences in spatial attention as a common mechanism supporting mean length and orientation judgments. The present result aligns with the growing evidence for at least one ensemble-specific ability that applies across different kinds of features and stimuli.

Domain-specific and domain-general contributions to reading musical notation.

Musical practice may benefit not only domain-specific abilities, such as pitch discrimination and music performance, but also domain-general abilities, like executive functioning and memory. Behavioral and neural changes in visual processing have been associated with music-reading experience. However, it is still unclear whether there is a domain-specific visual ability to process musical notation. This study investigates the specificity of the visual skills relevant to simple decisions about musical notation. Ninety-six participants varying in music-reading experience answered a short survey to quantify experience with musical notation and completed a test battery that assessed musical notation reading fluency and accuracy at the level of individual note or note sequence. To characterize how this ability may relate to domain-general abilities, we also estimated general intelligence (as measured with the Raven's Progressive Matrices) and general object-recognition ability (as measure by a recently proposed construct o). We obtained reliable measurements on our various tasks and found evidence for a domain-specific ability of the perception of musical notation. This music-reading ability and domain-general abilities were found to contribute to performance on specific tasks differently, depending on the level of experience reading music.

Ensemble coding of average length and average orientation are correlated.

Viewers can summarize redundant features in groups of objects into an ensemble percept. There appears to be separate mechanisms underlying ensemble perception of low- and high-level visual features, but it is unclear whether ensemble perception of different low-level features is supported by common mechanisms. Yörük and Boduroglu, in Attention, Perception, & Psychophysics 82 (2020) 852-864, investigated whether length and orientation summarization tap common mechanisms by examining the correlation between errors on length- and orientation-averaging tasks and concluded that because they did not find any correlations, the two features are summarized by different, feature-specific mechanisms. However, their study was conducted with a small sample size and included sources of individual performance variance that may have diminished correlations. We report two studies that tested the correlation between performance in the length- and orientation-averaging tasks, with larger samples and modifications that sought to reduce the sources of variance. Study 1 used ensembles that varied in both feature dimensions and Study 2 used ensembles that only varied in the task-relevant dimension. Both studies showed that errors in length- and orientation-averaging are correlated, suggesting that ensemble perception of these low-level features is supported, at least to some extent, by a common ability.

Car expertise does not compete with face expertise during ensemble coding.

When objects from two categories of expertise (e.g., faces and cars in dual car/face experts) are processed simultaneously, competition occurs across a variety of tasks. Here, we investigate whether competition between face and car processing also occurs during ensemble coding. The relationship between single object recognition and ensemble coding is debated, but if ensemble coding relies on the same ability as object recognition, we expect cars to interfere with ensemble coding of faces as a function of car expertise. We measured the ability to judge the variability in identity of arrays of faces, in the presence of task-irrelevant distractors (cars or novel objects). On each trial, participants viewed two sequential arrays containing four faces and four distractors, judging which array was the more diverse in terms of face identity. We measured participants' car expertise, object recognition ability, and face recognition ability. Using Bayesian statistics, we found evidence against competition as a function of car expertise during ensemble coding of faces. Face recognition ability predicted ensemble judgments for faces, regardless of the category of task-irrelevant distractors. The result suggests that ensemble coding is not susceptible to competition between different domains of similar expertise, unlike single-object recognition.