Discrimination sensitivity of visual shapes sharpens in autistic adults but only after explicit category learning.

BACKGROUND: Categorization and its influence on perceptual discrimination are essential processes to organize information efficiently. Individuals with Autism Spectrum Condition (ASC) are suggested to display enhanced discrimination on the one hand, but also to experience difficulties with generalization and ignoring irrelevant differences on the other, which underlie categorization. Studies on categorization and discrimination in ASC have mainly focused on one process at a time, however, and typically only used either behavioral or neural measures in isolation. Here, we aim to investigate the interrelationships between these perceptual processes using novel stimuli sampled from a well-controlled artificial stimulus space. In addition, we complement standard behavioral psychophysical tasks with frequency-tagging EEG (FT-EEG) to obtain a direct, non-task related neural index of discrimination and categorization. METHODS: The study was completed by 38 adults with ASC and 38 matched neurotypical (NT) individuals. First, we assessed baseline discrimination sensitivity by administering FT-EEG measures and a complementary behavioral task. Second, participants were trained to categorize the stimuli into two groups. Finally, participants again completed the neural and behavioral discrimination sensitivity measures. RESULTS: Before training, NT participants immediately revealed a categorical tuning of discrimination, unlike ASC participants who showed largely similar discrimination sensitivity across the stimuli. During training, both autistic and non-autistic participants were able to categorize the stimuli into two groups. However, in the initial training phase, ASC participants were less accurate and showed more variability, as compared to their non-autistic peers. After training, ASC participants showed significantly enhanced neural and behavioral discrimination sensitivity across the category boundary. Behavioral indices of a reduced categorical processing and perception were related to the presence of more severe autistic traits. Bayesian analyses confirmed overall results. LIMITATIONS: Data-collection occurred during the COVID-19 pandemic. CONCLUSIONS: Our behavioral and neural findings indicate that adults with and without ASC are able to categorize highly similar stimuli. However, while categorical tuning of discrimination sensitivity was spontaneously present in the NT group, it only emerged in the autistic group after explicit categorization training. Additionally, during training, adults with autism were slower at category learning. Finally, this multi-level approach sheds light on the mechanisms underlying sensory and information processing issues in ASC.

Unveiling the factors of aesthetic preferences with explainable AI.

The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences. Our models process these attributes as inputs to predict the aesthetic scores of images. Moreover, to delve deeper and obtain interpretable explanations regarding the factors driving aesthetic preferences, we utilize the popular Explainable AI (XAI) technique known as SHapley Additive exPlanations (SHAP). Our methodology compares the performance of various ML models, including Random Forest, XGBoost, Support Vector Regression, and Multilayer Perceptron, in accurately predicting aesthetic scores, and consistently observing results in conjunction with SHAP. We conduct experiments on three image aesthetic benchmarks, namely Aesthetics with Attributes Database (AADB), Explainable Visual Aesthetics (EVA), and Personalized image Aesthetics database with Rich Attributes (PARA), providing insights into the roles of attributes and their interactions. Finally, our study presents ML models for aesthetics research, alongside the introduction of XAI. Our aim is to shed light on the complex nature of aesthetic preferences in images through ML and to provide a deeper understanding of the attributes that influence aesthetic judgements.

An efficient Bayesian observer model of attractive and repulsive temporal context effects when perceiving multistable dot lattices.

In multistable dot lattices, the orientation we perceive is attracted toward the orientation we perceived in the immediately preceding stimulus and repelled from the orientation for which most evidence was present previously (Van Geert, Moors, Haaf, & Wagemans, 2022). Theoretically-inspired models have been proposed to explain the co-occurrence of attractive and repulsive context effects in multistable dot lattice tasks, but these models artificially induced an influence of the previous trial on the current one without detailing the process underlying such an influence (Gepshtein & Kubovy, 2005; Schwiedrzik et al., 2014). We conducted a simulation study to test whether the observed attractive and repulsive context effects could be explained with an efficient Bayesian observer model (Wei & Stocker, 2015). This model assumes variable encoding precision of orientations in line with their frequency of occurrence (i.e., efficient encoding) and takes the dissimilarity between stimulus space and sensory space into account. An efficient Bayesian observer model including both a stimulus and a perceptual level was needed to explain the co-occurrence of both attractive and repulsive temporal context effects. Furthermore, this model could reproduce the empirically observed strong positive correlation between individuals' attractive and repulsive effects (Van Geert et al., 2022), by assuming a positive correlation between temporal integration constants at the stimulus and the perceptual level. To conclude, the study brings evidence that efficient encoding and likelihood repulsion on the stimulus level can explain the repulsive context effect, whereas perceptual prior attraction can explain the attractive temporal context effect when perceiving multistable dot lattices.

Exploring the Semantic-Inconsistency Effect in Scenes Using a Continuous Measure of Linguistic-Semantic Similarity.

Viewers use contextual information to visually explore complex scenes. Object recognition is facilitated by exploiting object-scene relations (which objects are expected in a given scene) and object-object relations (which objects are expected because of the occurrence of other objects). Semantically inconsistent objects deviate from these expectations, so they tend to capture viewers' attention (the semantic-inconsistency effect). Some objects fit the identity of a scene more or less than others, yet semantic inconsistencies have hitherto been operationalized as binary (consistent vs. inconsistent). In an eye-tracking experiment (N = 21 adults), we study the semantic-inconsistency effect in a continuous manner by using the linguistic-semantic similarity of an object to the scene category and to other objects in the scene. We found that both highly consistent and highly inconsistent objects are viewed more than other objects (U-shaped relationship), revealing that the (in)consistency effect is more than a simple binary classification.

Finding the meaning in meaning maps: Quantifying the roles of semantic and non-semantic scene information in guiding visual attention.

In real-world vision, people prioritise the most informative scene regions via eye-movements. According to the cognitive guidance theory of visual attention, viewers allocate visual attention to those parts of the scene that are expected to be the most informative. The expected information of a scene region is coded in the semantic distribution of that scene. Meaning maps have been proposed to capture the spatial distribution of local scene semantics in order to test cognitive guidance theories of attention. Notwithstanding the success of meaning maps, the reason for their success has been contested. This has led to at least two possible explanations for the success of meaning maps in predicting visual attention. On the one hand, meaning maps might measure scene semantics. On the other hand, meaning maps might measure scene features, overlapping with, but distinct from, scene semantics. This study aims to disentangle these two sources of information by considering both conceptual information and non-semantic scene entropy simultaneously. We found that both semantic and non-semantic information is captured by meaning maps, but scene entropy accounted for more unique variance in the success of meaning maps than conceptual information. Additionally, some explained variance was unaccounted for by either source of information. Thus, although meaning maps may index some aspect of semantic information, their success seems to be better explained by non-semantic information. We conclude that meaning maps may not yet be a good tool to test cognitive guidance theories of attention in general, since they capture non-semantic aspects of local semantic density and only a small portion of conceptual information. Rather, we suggest that researchers should better define the exact aspect of cognitive guidance theories they wish to test and then use the tool that best captures that desired semantic information. As it stands, the semantic information contained in meaning maps seems too ambiguous to draw strong conclusions about how and when semantic information guides visual attention.

GABA and Glx predict EEG responses of visual sensitivity in autism.

The mechanisms underlying atypical sensory processing in autism remain to be elucidated, but research points toward a role of the glutamatergic/GABAergic balance. To investigate the potential relationships between visual sensitivity and its molecular correlates in autism, we combined data from electroencephalography (EEG) and magnetic resonance spectroscopy (MRS) studies. Twenty autistic adults and sixteen neurotypical adults (NT) participated in both an EEG study assessing visual sensitivity (Sapey-Triomphe et al., Autism Research, 2023) and in an MRS study measuring Glx and GABA+ concentrations in the occipital cortex (Sapey-Triomphe et al., Molecular Autism, 2021). These studies revealed no group differences in neural detection thresholds or in Glx/GABA levels in the occipital cortex. Neural detection thresholds for contrast and spatial frequency (SF) were determined using fast periodic visual stimulations and neural frequency tagging. In the present study, Glx/GABA+ concentrations in the occipital cortex and neural detection thresholds did not differ between groups. Interestingly, lower Glx/GABA+ ratios were associated with lower contrast detection thresholds and higher SF detection thresholds. These correlations were also significant within the neurotypical and autistic groups. This report suggests that the Glx/GABA balance regulates visual detection thresholds across individuals. In both autistic and NTs, lower Glx/GABA ratios in the occipital cortex allow for better detection of visual inputs at the neural level. This study sheds light on the neurochemical underpinnings of visual sensitivity in autism and warrants further investigation.

Assessing Spontaneous Categorical Processing of Visual Shapes via Frequency-Tagging EEG.

Categorization is an essential cognitive and perceptual process, which happens spontaneously. However, earlier research often neglected the spontaneous nature of this process by mainly adopting explicit tasks in behavioral or neuroimaging paradigms. Here, we use frequency-tagging (FT) during electroencephalography (EEG) in 22 healthy human participants (both male and female) as a direct approach to pinpoint spontaneous visual categorical processing. Starting from schematic natural visual stimuli, we created morph sequences comprising 11 equal steps. Mirroring a behavioral categorical perception discrimination paradigm, we administered a FT-EEG oddball paradigm, assessing neural sensitivity for equally sized differences within and between stimulus categories. Likewise, mirroring a behavioral category classification paradigm, we administered a sweep FT-EEG oddball paradigm, sweeping from one end of the morph sequence to the other, thereby allowing us to objectively pinpoint the neural category boundary. We found that FT-EEG can implicitly measure categorical processing and discrimination. More specifically, we could derive an objective neural index of the required level to differentiate between the two categories, and this neural index showed the typical marker of categorical perception (i.e., stronger discrimination across as compared with within categories). The neural findings of the implicit paradigms were also validated using an explicit behavioral task. These results provide evidence that FT-EEG can be used as an objective tool to measure discrimination and categorization and that the human brain inherently and spontaneously (without any conscious or decisional processes) uses higher-level meaningful categorization information to interpret ambiguous (morph) shapes.

High-level aftereffects reveal the role of statistical features in visual shape encoding.

Visual shape perception is central to many everyday tasks, from object recognition to grasping and handling tools.1,2,3,4,5,6,7,8,9,10 Yet how shape is encoded in the visual system remains poorly understood. Here, we probed shape representations using visual aftereffects-perceptual distortions that occur following extended exposure to a stimulus.11,12,13,14,15,16,17 Such effects are thought to be caused by adaptation in neural populations that encode both simple, low-level stimulus characteristics17,18,19,20 and more abstract, high-level object features.21,22,23 To tease these two contributions apart, we used machine-learning methods to synthesize novel shapes in a multidimensional shape space, derived from a large database of natural shapes.24 Stimuli were carefully selected such that low-level and high-level adaptation models made distinct predictions about the shapes that observers would perceive following adaptation. We found that adaptation along vector trajectories in the high-level shape space predicted shape aftereffects better than simple low-level processes. Our findings reveal the central role of high-level statistical features in the visual representation of shape. The findings also hint that human vision is attuned to the distribution of shapes experienced in the natural environment.

Prägnanz in visual perception.

How do we perceptually and cognitively organize incoming stimulation? A century ago, Gestalt psychologists posited the law of Prägnanz: psychological organization will always be as 'good' as possible given the prevailing conditions. To make the Prägnanz law a useful statement, it needs to be specified further (a) what a 'good' psychological organization entails, (b) how the Prägnanz tendency can be realized, and (c) which conditions need to be taken into account. Although the Gestalt school did provide answers to these questions, modern-day mentions of Prägnanz or good Gestalt often lack these clarifications. The concept of Prägnanz has been (mis)understood in many different ways, and by looking back on the rich history of the concept, we will attempt to present a more fine-grained view and promote a renewed understanding of the central role of Prägnanz in visual perception and beyond. We review Gestalt psychology's answers to the questions listed above, and also discuss the four main uses of the Prägnanz concept in more detail: (a) a Prägnanz tendency in each organizational process, (b) Prägnanz as a property of a Gestalt, (c) Prägnanz steps as internal reference points, and (d) Prägnanz in relation to aesthetic appreciation. As a key takeaway, Prägnanz is a multifaceted Gestalt psychological concept indicating the "goodness" of an experienced organization. Both the removal of unnecessary details and the emphasis on characteristic features of the overall organization compared to a reference organization can contribute to the emergence of a 'better' Gestalt. The stimulus constellation is not the only factor in determining the goodness of an organization, also the stimulus' interaction with an individual in a specific spatial and temporal context plays a role. Taking the ideas on Prägnanz as a generative framework and keeping the original Gestalt psychological context in mind, future research on perceptual organization can improve our understanding of the principles underlying psychological organization by further specifying how different organizational principles interact in concrete situations. Public significance statement: This paper reviews what a 'good' psychological organization entails, and how the incoming stimulation is clarified in human perception to achieve the best possible psychological organization. The review debunks common misconceptions on the meaning of "goodness" and synthesizes the most important perspectives and developments on "goodness" from its conception until now.

Beautification of images by generative adversarial networks.

Finding the properties underlying beauty has always been a prominent yet difficult problem. However, new technological developments have often aided scientific progress by expanding the scientists' toolkit. Currently in the spotlight of cognitive neuroscience and vision science are deep neural networks. In this study, we have used a generative adversarial network (GAN) to generate images of increasing aesthetic value. We validated that this network indeed was able to increase the aesthetic value of an image by letting participants decide which of two presented images they considered more beautiful. As our validation was successful, we were justified to use the generated images to extract low- and mid-level features contributing to their aesthetic value. We compared the brightness, contrast, sharpness, saturation, symmetry, colorfulness, and visual complexity levels of "low-aesthetic" images to those of "high-aesthetic" images. We found that all of these features increased for the beautiful images, implying that they may play an important role underlying the aesthetic value of an image. With this study, we have provided further evidence for the potential value GANs may have for research concerning beauty.

Additivity of grouping by proximity and luminance similarity is dependent on relative grouping strength: An analysis of individual differences in grouping sensitivity.

It has previously been shown that grouping by proximity is well described by a linear function relating the perceived orientation of a dot lattice to the ratio of the distances between the dots in the different orientations. Similarly, luminance influences how observers perceptually group stimuli. Using the dot lattice paradigm, it has been shown that proximity and luminance similarity interact additively, which means that their effects can be summed to predict an observers' percept. In this study, we revisit the additive interplay between proximity and luminance similarity and we ask whether this pattern might be the result of inappropriately averaging different types of observers or the imbalance between the strength of proximity grouping and luminance similarity grouping. To address these questions, we first ran a replication of the original study reporting the additive interplay between proximity and luminance similarity. Our results showed a convincing replication at the aggregate and individual level. However, at the individual level, all observers showed grouping by proximity whereas some observers did not show grouping by luminance similarity. In response, we ran a second experiment with enlarged luminance differences to reinforce the strength of grouping by luminance similarity and balance the strength of the two grouping cues. Interestingly, in this second experiment, additivity was not observed but instead a significant interaction was obtained. This disparity suggests that the additivity or interaction between two grouping cues in a visual stimulus is not a general rule of perceptual grouping but a consequence of relative grouping strength.

What good is goodness? The effects of reference points on discrimination and categorization of shapes.

Earlier research reported a category boundary effect on perception: differences between stimuli belonging to the same category are perceived as smaller than differences between stimuli belonging to different categories even when the physical dissimilarity between the stimuli in the pairs is the same. In this article, we propose that the existence of reference points (i.e., exemplars that serve as a point of comparison) can explain the occurrence of the category boundary effect as well as the directional asymmetries in within-category pairs. We investigated how reference points influence categorization and discrimination performance, using three different tasks: categorization, successive discrimination, and similarity judgment. We used both recognizable and non-recognizable morph figures as stimuli, assuming that recognizable series have clearer reference points. We replicated the overall category boundary effect for both discrimination and similarity and show the effect's dependence on the strength of the reference points involved. The general category boundary effect is not a proper category boundary effect, however: rather than the type of stimulus pair presented (i.e., within- or between-category) one needs to take into account the distance from the reference points for each of the individual stimuli in the pair to actually predict discrimination performance and similarity judgments. These results provide evidence that reference points on a dimension and their strength have tangible consequences for how we perceive, categorize, and react to stimuli on that dimension. Moreover, our findings remind us of the danger of averaging without looking at underlying data patterns, and of the gains that can be made by seriously exploring consistent variability in extensive data sets. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Towards the most prägnant Gestalt: Leveling and sharpening as contextually dependent adaptive strategies.

Gestalt psychologists posited that we always organize our visual input in the best way possible under the given conditions. Both weakening or removing unnecessary details (i.e., leveling) and exaggerating distinctive features (i.e., sharpening) can contribute to achieving a better organization. When is a feature leveled or sharpened, however? We investigated whether the importance of a feature for discrimination among alternatives influences which organizational tendency occurs. Participants were simultaneously presented with four figures composed of simple geometrical shapes, and asked to reconstruct one of these figures in such a way that another participant would be able to recognize it among the alternatives. The four figures differed either qualitatively or only quantitatively (i.e., far or close context). Regarding quantitative differences, two feature dimensions were varied, with one manifesting a wider range of variability across the alternatives than the other. In case of a smaller variability range, the target figure was either at the extreme of the range or had an in-between value. As expected, the results indicated that sharpening occurred more often for the feature with an extreme value, for the feature exhibiting more variability, and for the features of figures presented in the close context, than for the feature with a non-extreme value, exhibiting less variability, or in the far context. In line with Metzger's (1941) definition of prägnant Gestalts, the essence of a Gestalt is context-dependent, and this will influence whether leveling or sharpening of a feature will lead to the best organization in the specific context.

Neural correlates of hierarchical predictive processes in autistic adults.

Bayesian theories of autism spectrum disorders (ASD) suggest that atypical predictive mechanisms could underlie the autistic symptomatology, but little is known about their neural correlates. Twenty-six neurotypical (NT) and 26 autistic adults participated in an fMRI study where they performed an associative learning task in a volatile environment. By inverting a model of perceptual inference, we characterized the neural correlates of hierarchically structured predictions and prediction errors in ASD. Behaviorally, the predictive abilities of autistic adults were intact. Neurally, predictions were encoded hierarchically in both NT and ASD participants and biased their percepts. High-level predictions were following activity levels in a set of regions more closely in ASD than NT. Prediction errors yielded activation in shared regions in NT and ASD, but group differences were found in the anterior cingulate cortex and putamen. This study sheds light on the neural specificities of ASD that might underlie atypical predictive processing.

A multilevel investigation of sensory sensitivity and responsivity in autistic adults.

Atypical sensory processing is a core symptom of autism spectrum disorders (ASD). We aimed at better characterizing visual sensitivity and responsivity in ASD at the self-reported, behavioral and neural levels, and at describing the relationships between these levels. We refer to sensory sensitivity as the ability to detect sensory stimuli and to sensory responsivity as an affective response to sensory stimuli. Participants were 25 neurotypical and 24 autistic adults. At the self-reported level, autistic participants had higher scores of sensory sensitivity and responsivity than neurotypicals. The behavioral and neural tasks involved contrast-reversing gratings which became progressively (in)visible as their contrast or spatial frequency evolved. At the behavioral level, autistic participants had higher detection and responsivity thresholds when gratings varied in spatial frequency, but their thresholds did not differ from neurotypicals when gratings varied in contrast. At the neural level, we used fast periodic visual stimulations and electroencephalography to implicitly assess detection thresholds for contrast and spatial frequency, and did not reveal any group difference. Higher self-reported responsivity was associated with higher behavioral responsivity, more intolerance of uncertainty and anxiety, in particular in ASD. At the self-reported level, higher sensitivity was associated with more responsivity in both groups, contrary to the behavioral level where these relationships were not found. These heterogeneous results suggest that sensitivity and responsivity per se are not simply increased in ASD, but may be modulated by other factors such as environmental predictability. Multi-level approaches can shed light on the mechanisms underlying sensory issues in ASD.

Anger is red, sadness is blue: Emotion depictions in abstract visual art by artists and non-artists.

Through the manipulation of color and form, visual abstract art is often used to convey feelings and emotions. Here, we explored how colors and lines are used to express basic emotions and whether non-artists express emotions through art in similar ways as trained artists. Both artists and non-artists created abstract color drawings and line drawings depicting six emotions (i.e., anger, disgust, fear, joy, sadness, and wonder). To test whether people represented basic emotions in similar ways, we computationally predicted the emotion of a given drawing by comparing it to a set of references created by averaging across all other participants' drawings within each emotion category. We found that prediction accuracy was higher for color drawings than line drawings and higher for color drawings by non-artists than by artists. In a behavioral experiment, we found that people (N = 242) could also accurately infer emotions, showing the same pattern of results as our computational predictions. Further computational analyses of the drawings revealed systematic use of certain colors and line features to depict each basic emotion (e.g., anger is generally redder and more densely drawn than other emotions, sadness is more blue and contains more vertical lines). Taken together, these results imply that abstract color and line drawings are able to convey certain emotions based on their visual features, which are also used by human observers to understand the intended emotional connotation of abstract artworks.

Crossmodal correspondences and interactions between texture and taste perception.

In recent years, awareness of the influence of different modalities on taste perception has grown. Although previous research in crossmodal taste perception has touched upon the bipolar distinction between softness/smoothness and roughness/angularity, ambiguity largely remains surrounding other crossmodal correspondences between taste and other specific textures we regularly use to describe our food, such as crispy or crunchy. Sweetness has previously been found to be associated with soft textures but our current understanding does not exceed the basic distinction made between roughness and smoothness. Specifically, the role of texture in taste perception remains relatively understudied. The current study consisted of two parts. First, because of the lack of clarity concerning specific associations between basic tastes and textures, an online questionnaire served to assess whether consistent associations between texture words and taste words exist and how these arise intuitively. The second part consisted of a taste experiment with factorial combinations of four tastes and four textures. The results of the questionnaire study showed that consistent associations are made between soft and sweet and between crispy and salty at the conceptual level. The results of the taste experiment largely showed evidence in support of these findings at the perceptual level. In addition, the experiment allowed for a closer look into the complexity found regarding the association between sour and crunchy, and bitter and sandy.

What ugly and beautiful photographs reveal about COVID-19 lockdown experiences, everyday aesthetics and photography aesthetics.

Against the backdrop of the COVID-19 pandemic, which restricted our daily (visual) experiences, we asked people to take an ugly and beautiful photograph from within their homes. In total, 284 photographs (142 ugly and 142 beautiful) and accompanying statements were submitted and brought to light an intimate portrait of how participants were experiencing their (lockdown) home environment. Results revealed an aesthetic preference for (living) nature. Beauty and ugliness were also connected to good versus bad views, mess versus cosiness, unflattering versus flattering portraits and positive versus negative (COVID-19) emotions. In terms of photography strategies, editing and colour were important for beautiful photographs, whereas a lack of effort and sharpness showed up relatively more in ugly photographs. A follow-up study revealed that other viewers' (n = 86) aesthetic judgements of the photographs were largely in line with the original submissions, and confirmed several of the themes. Overall, our study provides a unique photographic window on our everyday aesthetic experiences at home during the COVID-19 lockdown.

The Order & Complexity Toolbox for Aesthetics (OCTA): A systematic approach to study the relations between order, complexity, and aesthetic appreciation.

Do individuals prefer stimuli that are ordered or disordered, simple or complex, or that strike the right balance of order and complexity? Earlier research mainly focused on the separate influence of order and complexity on aesthetic appreciation. When order and complexity were studied in combination, stimulus manipulations were often not parametrically controlled, only rather specific types of order (i.e., balance or symmetry) were usually studied, and/or the multidimensionality of order and complexity was largely ignored. Progress has also been limited by the lack of an easy way to create reproducible and expandible stimulus sets, including both order and complexity manipulations. The Order & Complexity Toolbox for Aesthetics (OCTA), a Python toolbox that is also available as a point-and-click Shiny application, aims to fill this gap. OCTA provides researchers with a free and easy way to create multi-element displays varying qualitatively (i.e., different types) and quantitatively (i.e., different levels) in order and complexity, based on regularity and variety along multiple element features (e.g., shape, size, color, orientation). The standard vector-based output is ideal for experiments on the web and the creation of dynamic interfaces and stimuli. OCTA will not only facilitate reproducible stimulus construction and experimental design in research on order, complexity, and aesthetics. In addition, OCTA can be a very useful tool in any type of research using visual stimuli, or even to create digital art. To illustrate OCTA's potential, we propose several possible applications and diverse questions that can be addressed using OCTA.

Perceptual grouping in complex rhythmic patterns.

Perception of simple temporal patterns has been shown to rely on accentuations in terms of intensity, pitch, or timbre, but also on grouping according to runs of the same events (intervals between successive sounds or light flashes) or significant gaps between them (Garner in The processing of information and structure. Lawrence Erlbaum, 1974; Preusser et al. in Am J Psychol 83(2):151-170 in 1970; Royer and Garner in Percept Psychophys 1(1):41-47, 1966; Royer and Garner in Percept Psychophys 7(2):115-120, 1970; Yu et al. in Atten Percept Psychophys 77(8):2728-2739, 2015). Here we investigate whether the run and gap principles can also account for participants' perceived start of complex rhythmic patterns. We also investigated the role of participants' musical training. Sixteen novices and 16 amateur musicians listened to rhythmic patterns and indicated perceived starting points by a single tap with a drumstick on electronic pads. Auditory patterns contained prominent gaps, runs, or a combination of the two for target intervals. We systematically varied task complexity in terms of the target durations of intervals constituting the patterns and overall tempos. Overall, run and gap principles proved to be useful grouping principles accounting for a large proportion (59.2%) of the selected starting positions underlining the universal relevance of these principles. Grouping principles were not as successful in predicting the perceived start of a rhythmic pattern compared to previous studies. Results indicate that additional grouping principles must be at play. Predictive power of the grouping principles varied depending on the structure of rhythmic patterns. For rhythmic patterns including longer intervals (i.e., longer gaps) the gap principle alone or in combination with the run principle showed the strongest predictive power. Novices and amateur musicians were similar in their usage of grouping principles suggesting that the underlying principles might be equally at the dispositions of performers and listeners.