Perception has long been envisioned to use an internal model of the world to explain the causes of sensory signals. However, such accounts have historically not been testable, typically requiring intractable search through the space of possible explanations. Using auditory scenes as a case study, we leveraged contemporary computational tools to infer explanations of sounds in a candidate internal generative model of the auditory world (ecologically inspired audio synthesizers). Model inferences accounted for many classic illusions. Unlike traditional accounts of auditory illusions, the model is applicable to any sound, and exhibited human-like perceptual organization for real-world sound mixtures. The combination of stimulus-computability and interpretable model structure enabled \'rich falsification\', revealing additional assumptions about sound generation needed to account for perception. The results show how generative models can account for the perception of both classic illusions and everyday sensory signals, and illustrate the opportunities and challenges involved in incorporating them into theories of perception.

Population-based studies of human mitochondrial genetic diversity often require the classification of mitochondrial DNA (mtDNA) haplotypes into more than 5400 described haplogroups, and further grouping those into hierarchically higher haplogroups. Such secondary haplogroup groupings (e.g., \"macro-haplogroups\") vary across studies, as they depend on the sample quality, technical factors of haplogroup calling, the aims of the study, and the researchers\' understanding of the mtDNA haplogroup nomenclature. Retention of historical nomenclature coupled with a growing number of newly described mtDNA lineages results in increasingly complex and inconsistent nomenclature that does not reflect phylogeny well. This \"clutter\" leaves room for grouping errors and inconsistencies across scientific publications, especially when the haplogroup names are used as a proxy for secondary groupings, and represents a source for scientific misinterpretation. Here we explore the effects of phylogenetically insensitive secondary mtDNA haplogroup groupings, and the lack of standardized secondary haplogroup groupings on downstream analyses and interpretation of genetic data. We demonstrate that frequency-based analyses produce inconsistent results when different secondary mtDNA groupings are applied, and thus allow for vastly different interpretations of the same genetic data. The lack of guidelines and recommendations on how to choose appropriate secondary haplogroup groupings presents an issue for the interpretation of results, as well as their comparison and reproducibility across studies. To reduce biases originating from arbitrarily defined secondary nomenclature-based groupings, we suggest that future updates of mtDNA phylogenies aimed for the use in mtDNA haplogroup nomenclature should also provide well-defined and standardized sets of phylogenetically meaningful algorithm-based secondary haplogroup groupings such as \"macro-haplogroups\", \"meso-haplogroups\", and \"micro-haplogroups\". Ideally, each of the secondary haplogroup grouping levels should be informative about different human population history events. Those phylogenetically informative levels of haplogroup groupings can be easily defined using TreeCluster, and then implemented into haplogroup callers such as HaploGrep3. This would foster reproducibility across studies, provide a grouping standard for population-based studies, and reduce errors associated with haplogroup nomenclatures in future studies.

This manuscript discusses the challenges of applying New Approach Methodologies (NAMs) for safe by design and regulatory risk assessment of advanced nanomaterials (AdNMs). The authors propose a framework for Next Generation Risk Assessment of AdNMs involving NAMs that is aligned to the conventional risk assessment paradigm. This framework is exposure-driven, endpoint-specific, makes best use of pre-existing information, and can be implemented in tiers of increasing specificity and complexity of the adopted NAMs. The tiered structure of the approach, which effectively combines the use of existing data with targeted testing will allow safety to be assessed cost-effectively and as far as possible with even more limited use of vertebrates. The regulatory readiness of state-of-the-art emerging NAMs is assessed in terms of Transparency, Reliability, Accessibility, Applicability, Relevance and Completeness, and their appropriateness for AdNMs is discussed in relation to each step of the risk assessment paradigm along with providing perspectives for future developments in the respective scientific and regulatory areas.

Massive studies have explored biological motion (BM) crowds processing for their remarkable social significance, primarily focused on uniformly distributed ones. However, real-world BM crowds often exhibit hierarchical structures rather than uniform arrangements. How such structured BM crowds are processed remains a subject of inquiry. This study investigates the representation of structured BM crowds in working memory (WM), recognizing the pivotal role WM plays in our social interactions involving BM. We propose the group-based ensemble hypothesis and test it through a member identification task. Participants were required to discern whether a presented BM belonged to a prior memory display of eight BM, each with distinct walking directions. Drawing on prominent Gestalt principles as organizational cues, we constructed structured groups within BM crowds by applying proximity and similarity cues in Experiments 1 and 2, respectively. In Experiment 3, we deliberately weakened the visibility of stimuli structures by increasing the similarity between subsets, probing the robustness of results. Consistently, our findings indicate that BM aligned with the mean direction of the subsets was more likely to be recognized as part of the memory stimuli. This suggests that WM inherently organizes structured BM crowds into separate ensembles based on organizational cues. In essence, our results illuminate the simultaneous operation of grouping and ensemble encoding mechanisms for BM crowds within WM.

This manuscript presents a procedure for similarity assessment as a basis for grouping of multi component nanomaterials (MCNMs). This methodology is an adaptation of the approach by Zabeo et al. (2022), which includes an impactful change: the calculated similarities are normalised in the [0,1] domain by means of asymmetric Logistic scaling to simplify comparisons among properties\' distances. This novel approach allows for grouping of nanomaterials that is not affected by the dataset, so that group membership will not change when new candidates are included in the set of assessed materials. It can be applied to assess groups of MCNMs as well as mixed groups of multi and single component nanomaterials as well as chemicals. To facilitate the application of the proposed methodology, a software script was developed by using the Python programming language, which is currently undergoing migration to a user-friendly web-based tool. The presented approach was tested against a real industrial case study provided by the Andalusian Innovation Centre for Sustainable Solution (CIAC): SiO2-ZnO hybrid nanocomposite used in building coatings, which is designed to facilitate photocatalytic removal of NOx gases from the atmosphere. The results of applying the methodology in the case study demonstrated that ZnO is dissimilar from the other candidates mainly due to its different dissolution profiles.

Read-across (RAx) and grouping of chemicals into categories are well-known concepts in toxicology. Recently, ECHA proposed a grouping approach for branched-chain carboxylic acids (BCAs) including more than 60 branched-chain saturated carboxylic acids for hazard identification. Grouping was based only on structural considerations. Due to developmental effects of two members, ECHA postulated that \"all short carbon chain acids … are likely reproductive and developmental toxicants\". This work analyzes available data for BCAs. The number of compounds in the group can be significantly reduced by eliminating metal and organic salts of BCAs, compounds of unknown or variable composition, and complex reaction products or biological materials (UVCB compounds). For the resulting reduced number of compounds, grouping is supported by similar physicochemical data and expected similar biotransformation. However, analysis of adverse effects for compounds in the group and mechanistic information show that BCAs, as a class, do not cause developmental effects in rats. Rather, developmental toxicity is limited to selected BCAs with specific structures that share a common mode of action (histone deacetylase inhibition). Thus, the proposed grouping is unreasonably wide and the more detailed analyses show that structural similarity alone is not sufficient for grouping branched-chain carboxylic acids for developmental toxicity.

It is well known that objects become grouped in perceptual organization when they share some visual feature, like a common direction of motion. Less well known is that grouping can change how people perceive a set of objects. For example, when a pair of shapes consistently share a common region of space, their aspect ratios tend to be perceived as more similar (are attracted toward each other). Conversely, when shapes are assigned to different regions in space their aspect ratios repel from each other. Here we examine whether the visual system produce both attractive and repulsive distortions when the state of grouping between a pair of shapes changes on a moment-to-moment basis. Observers viewed a pair of ellipses that differed in terms of how flat or tall they were and reported the aspect ratio of one ellipse from the pair. Each ellipse was defined by a cloud of coherently-moving dots, and the dots within the two ellipses had either the same or different directions of motion, varying from trial-to-trial. We found that the cued ellipse\'s aspect ratio was reported to be repelled from the aspect ratio of the uncued ellipse when the shapes had different directions of motion compared to when they had the same direction of motion. These results suggest that the visual system can adaptively alter visual experience based on grouping, in particular, repelling the appearance of objects when they do not appear to go together, and it can do so quickly and flexibly.

When memorizing an integrated object such as a Kanizsa figure, the completion of parts into a coherent whole is attained by grouping processes which render a whole-object representation in visual working memory (VWM). The present study measured event-related potentials (ERPs) and oscillatory amplitudes to track these processes of encoding and representing multiple features of an object in VWM. To this end, a change detection task was performed, which required observers to memorize both the orientations and colors of six \"pacman\" items while inducing configurations of the pacmen that systematically varied in terms of their grouping strength. The results revealed an effect of object configuration in VWM despite physically constant visual input: change detection for both orientation and color features was more accurate with increased grouping strength. At the electrophysiological level, the lateralized ERPs and alpha activity mirrored this behavioral pattern. Perception of the orientation features gave rise to the encoding of a grouped object as reflected by the amplitudes of the Ppc. The grouped object structure, in turn, modulated attention to both orientation and color features as indicated by the enhanced N1pc and N2pc. Finally, during item retention, the representation of individual objects and the concurrent allocation of attention to these memorized objects were modulated by grouping, as reflected by variations in the CDA amplitude and a concurrent lateralized alpha suppression, respectively. These results indicate that memorizing multiple features of grouped, to-be-integrated objects involves multiple, sequential stages of processing, providing support for a hierarchical model of object representations in VWM.

Per- and poly-fluoroalkyl substances (PFAS) are extensively used in commerce leading to their prevalence in the environment. Due to their chemical stability, PFAS are considered to be persistent and bioaccumulative; they are frequently detected in both the environment and humans. Because of this, PFAS as a class (composed of hundreds to thousands of chemicals) are contaminants of very high concern. Little information is available for the vast majority of PFAS, and regulatory agencies lack safety data to determine whether exposure limits or restrictions are needed. Cell-based assays are a pragmatic approach to inform decision-makers on potential health hazards; therefore, we hypothesized that a targeted battery of human in vitro assays can be used to determine whether there are structure-bioactivity relationships for PFAS, and to characterize potential risks by comparing bioactivity (points of departure) to exposure estimates. We tested 56 PFAS from 8 structure-based subclasses in concentration response (0.1-100 μM) using six human cell types selected from target organs with suggested adverse effects of PFAS - human induced pluripotent stem cell (iPSC)-derived hepatocytes, neurons, and cardiomyocytes, primary human hepatocytes, endothelial and HepG2 cells. While many compounds were without effect; certain PFAS demonstrated cell-specific activity highlighting the necessity of using a compendium of in vitro models to identify potential hazards. No class-specific groupings were evident except for some chain length- and structure-related trends. In addition, margins of exposure (MOE) were derived using empirical and predicted exposure data. Conservative MOE calculations showed that most tested PFAS had a MOE in the 1-100 range; ∼20% of PFAS had MOE<1, providing tiered priorities for further studies. Overall, we show that a compendium of human cell-based models can be used to derive bioactivity estimates for a range of PFAS, enabling comparisons with human biomonitoring data. Furthermore, we emphasize that establishing structure-bioactivity relationships may be challenging for the tested PFAS.

Crowding occurs when an easily identified isolated stimulus is surrounded by stimuli with similar properties, making it very difficult to identify. Crowding is suggested as a mechanism that creates a bottleneck in object recognition and awareness. Recently, we showed that brief presentation times at the fovea resulted in a significant crowding effect on target identification, impaired the target\'s color awareness, and resulted in a slower reaction time. However, when tagging the target with a red letter, the crowding effect is abolished. Crowding is widely considered a grouping; hence, it is pre-attentive. An event-related potential (ERP) study that investigated the spatial-temporal properties of crowding suggested the involvement of higher-level visual processing. Here, we investigated whether ERP\'s components may be affected by crowding and tagging, and whether the temporal advantage of ERP can be utilized to gain further information about the crowding mechanism. The participants reported target identification using our standard foveal crowing paradigm. It is assumed that crowding occurs due to a suppressive effect; thus, it can be probed by changes in perceptual (N1, ~160 ms) and attentive (P3 ~300-400 ms) components. We found a suppression effect (less negative ERP magnitude) in N1 under foveal crowding, which was recovered under tagging conditions. ERP\'s amplitude components (N1 and P3) and the behavioral proportion correct are highly correlated. These findings suggest that crowding is an early grouping mechanism that may be combined with later processing involving the segmentation mechanism.