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Emphasizing scientific and cultural-historical aspects of human remains, we describe the historical background and present status of the Anatomical Collection at the University of Jena. In addition to safekeeping issues and exhibition practice, we provide typical examples of provenance research in the Collection and refer to relevant literature and recommendations. A reappraisal of the Anatomical Collection culminated in the implementation of a new exhibition concept that diverts attention away from dead bodies as mere anatomical objects and emphasizes ethical considerations, such as consented body donation. The visitor is encouraged to respect the deceased as human subjects who are individuals with their personal biography and entitled to human dignity also after death. A particular focus of our approach is on contexts of colonial injustice and racism, which require a high degree of ethical sensitivity. By providing practical hints on how to conduct provenance research, we want to encourage other anatomists to have a closer look at their historical collections. While some human remains can be restituted, others will probably stay in the collections for various reasons. Concepts for the appropriate handling of these remains have yet to be developed. In conclusion, we argue that, with a renewed understanding and sensitivity, the importance and value of the historical anatomical collections can be recognized once again.

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In this exploratory study, we asked whether objective statistical image properties can predict subjective aesthetic ratings for a set of 48 abstract paintings created by the artist Robert Pepperell. Ruta and colleagues (2021) used the artworks previously to study the effect of curved/angular contour on liking and wanting decisions. We related a predefined set of statistical image properties to the eight different dimensions of aesthetic judgments from their study. Our results show that the statistical image properties can predict a large portion of the variance in the different aesthetic judgments by Ruta and colleagues. For example, adjusted R2 values for liking, attractiveness, visual comfort, and approachability range between 0.52 and 0.60 in multiple linear regression models with four predictors each. For wanting judgments in an (imagined) gallery context, the explained variance is even higher (adjusted R2 of 0.78). To explain these findings, we hypothesize that differences in cognitive processing of Pepperell's abstract paintings are minimized because this set of stimuli has no apparent content and is of uniform artistic style and cultural context. Under this condition, the aesthetic ratings by Ruta and colleagues are largely based on perceptual processing that systematically varies along a relatively small set of objective image properties.

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Research in computational textual aesthetics has shown that there are textual correlates of preference in prose texts. The present study investigates whether textual correlates of preference vary across different time periods (contemporary texts versus texts from the 19th and early 20th centuries). Preference is operationalized in different ways for the two periods, in terms of canonization for the earlier texts, and through sales figures for the contemporary texts. As potential textual correlates of preference, we measure degrees of (un)predictability in the distributions of two types of low-level observables, parts of speech and sentence length. Specifically, we calculate two entropy measures, Shannon Entropy as a global measure of unpredictability, and Approximate Entropy as a local measure of surprise (unpredictability in a specific context). Preferred texts from both periods (contemporary bestsellers and canonical earlier texts) are characterized by higher degrees of unpredictability. However, unlike canonicity in the earlier texts, sales figures in contemporary texts are reflected in global (text-level) distributions only (as measured with Shannon Entropy), while surprise in local distributions (as measured with Approximate Entropy) does not have an additional discriminating effect. Our findings thus suggest that there are both time-invariant correlates of preference, and period-specific correlates.

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Artificial intelligence has emerged as a powerful computational tool to create artworks. One application is Neural Style Transfer, which allows to transfer the style of one image, such as a painting, onto the content of another image, such as a photograph. In the present study, we ask how Neural Style Transfer affects objective image properties and how beholders perceive the novel (style-transferred) stimuli. In order to focus on the subjective perception of artistic style, we minimized the confounding effect of cognitive processing by eliminating all representational content from the input images. To this aim, we transferred the styles of 25 diverse abstract paintings onto 150 colored random-phase patterns with six different Fourier spectral slopes. This procedure resulted in 150 style-transferred stimuli. We then computed eight statistical image properties (complexity, self-similarity, edge-orientation entropy, variances of neural network features, and color statistics) for each image. In a rating study, we asked participants to evaluate the images along three aesthetic dimensions (Pleasing, Harmonious, and Interesting). Results demonstrate that not only objective image properties, but also subjective aesthetic preferences transferred from the original artworks onto the style-transferred images. The image properties of the style-transferred images explain 50 - 69% of the variance in the ratings. In the multidimensional space of statistical image properties, participants considered style-transferred images to be more Pleasing and Interesting if they were closer to a "sweet spot" where traditional Western paintings (JenAesthetics dataset) are represented. We conclude that NST is a useful tool to create novel artistic stimuli that preserve the image properties of the input style images. In the novel stimuli, we found a strong relationship between statistical image properties and subjective ratings, suggesting a prominent role of perceptual processing in the aesthetic evaluation of abstract images.

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OBJECTIVE: Ultrasonography (US) has become the first-line imaging modality even for physicians who are not imaging specialists. The progress has not yet been sufficiently considered in medical education. The aim was to develop a curriculum that integrates US as a compulsory part into medical education directly from the start, to build up professional competencies toward residency. METHODS: Development was based on Kern's six-step approach to identify problems, specify needs, define goals, outline strategies, and propose methods. RESULTS: The proposed curriculum follows a spiral course within which students should pass through four levels of training with increasing complexity. Students will be asked to independently prepare for courses by using learning videos. On the first training level, US should be closely linked to anatomy and physiology courses. Competency-centered courses should be held in small groups. On the second level, in the third year of education, students will apply point-of-care ultrasonography concerning multiple medical disciplines. On the third level, they will select a compulsory course in a specialty of their choice, held at five consecutive dates. From then on, US will be conducted in patients. Finally, during the final year, students are expected to use US under pro-active supervision with a large degree of independence and confidence. Throughout the curriculum, the discipline of radiology combines vertically with foundational sciences and horizontally with other medical specialties. CONCLUSION: The conceptual proposal for a longitudinal US curriculum presented here has been developed by radiologists to equip students with competencies needed for contemporary patient care.

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Computational textual aesthetics aims at studying observable differences between aesthetic categories of text. We use Approximate Entropy to measure the (un)predictability in two aesthetic text categories, i.e., canonical fiction ('classics') and non-canonical fiction (with lower prestige). Approximate Entropy is determined for series derived from sentence-length values and the distribution of part-of-speech-tags in windows of texts. For comparison, we also include a sample of non-fictional texts. Moreover, we use Shannon Entropy to estimate degrees of (un)predictability due to frequency distributions in the entire text. Our results show that the Approximate Entropy values can better differentiate canonical from non-canonical texts compared with Shannon Entropy, which is not true for the classification of fictional vs. expository prose. Canonical and non-canonical texts thus differ in sequential structure, while inter-genre differences are a matter of the overall distribution of local frequencies. We conclude that canonical fictional texts exhibit a higher degree of (sequential) unpredictability compared with non-canonical texts, corresponding to the popular assumption that they are more 'demanding' and 'richer'. In using Approximate Entropy, we propose a new method for text classification in the context of computational textual aesthetics.

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Color has been a defining feature of paintings throughout art history. Despite the great diversity in the use of color between epochs, there are some surprisingly stable and unifying features in chromatic properties across visual artworks. For example, artists' palettes seem to be biased toward the yellow-red range of the spectrum. Here, we assess the impact of a holistic color manipulation (i.e., rotating the color gamut) on aesthetic liking and perceived colorfulness of abstract paintings. We presented 6 versions each of 100 abstract artworks that differed only in the rotational degree of their color gamut within the CIELAB space. Results indicated a very stable preference for the original color compositions-both on a participant level and on an item level. Furthermore, participants perceived original color compositions as more colorful than rotated versions. This effect remained robust even when the exact number of different colors-among other chromatic features-was taken into account in covariate analyses. Thus, it seems that original color compositions are inherently special. Specifically, it seems that the aesthetic appeal of original artworks arises from nontrivial color features, which are characterized by their distribution within the visible spectrum. We assume that the rotation manipulation may change the perception of some colors more strongly than others due to differences in sensitivity of our visual system to these hues. We discuss these findings with respect to category-specific color perception, which may be a potential contender for a neurobiological foundation of the observed effects. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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This study investigates global properties of three categories of English text: canonical fiction, non-canonical fiction, and non-fictional texts. The central hypothesis of the study is that there are systematic differences with respect to structural design features between canonical and non-canonical fiction, and between fictional and non-fictional texts. To investigate these differences, we compiled a corpus containing texts of the three categories of interest, the Jena Corpus of Expository and Fictional Prose (JEFP Corpus). Two aspects of global structure are investigated, variability and self-similar (fractal) patterns, which reflect long-range correlations along texts. We use four types of basic observations, (i) the frequency of POS-tags per sentence, (ii) sentence length, (iii) lexical diversity, and (iv) the distribution of topic probabilities in segments of texts. These basic observations are grouped into two more general categories, (a) the lower-level properties (i) and (ii), which are observed at the level of the sentence (reflecting linguistic decoding), and (b) the higher-level properties (iii) and (iv), which are observed at the textual level (reflecting comprehension/integration). The observations for each property are transformed into series, which are analyzed in terms of variance and subjected to Multi-Fractal Detrended Fluctuation Analysis (MFDFA), giving rise to three statistics: (i) the degree of fractality ( H ), (ii) the degree of multifractality ( D ), i.e., the width of the fractal spectrum, and (iii) the degree of asymmetry ( A ) of the fractal spectrum. The statistics thus obtained are compared individually across text categories and jointly fed into a classification model (Support Vector Machine). Our results show that there are in fact differences between the three text categories of interest. In general, lower-level text properties are better discriminators than higher-level text properties. Canonical fictional texts differ from non-canonical ones primarily in terms of variability in lower-level text properties. Fractality seems to be a universal feature of text, slightly more pronounced in non-fictional than in fictional texts. On the basis of our results obtained on the basis of corpus data we point out some avenues for future research leading toward a more comprehensive analysis of textual aesthetics, e.g., using experimental methodologies.

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Curvilinearity is a perceptual feature that robustly predicts preference ratings for a variety of visual stimuli. The predictive effect of curved/angular shape overlaps, to a large degree, with regularities in second-order edge-orientation entropy, which captures how independent edge orientations are distributed across an image. For some complex line patterns, edge-orientation entropy is actually a better predictor for what human observers like than curved/angular shape. The present work was designed to disentangle the role of the two features in artificial patterns that consisted of either curved or angular line elements. We systematically varied these patterns across two more dimensions, edge-orientation entropy and the number of lines. Eighty-three participants rated the stimuli along three aesthetic dimensions (pleasing, harmonious, and complex). Results showed that curved/angular shape was a stronger predictor for ratings of pleasing and harmonious if the stimuli consisted of a few lines that were clearly discernible. By contrast, edge-orientation entropy was a stronger predictor for the ratings if the stimuli showed many lines, which merged into a texture. No such differences were obtained for complexity ratings. Our findings are in line with results from neurophysiological studies that the processing of shape and texture, respectively, is mediated by different cortical mechanisms.

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In recent years, there has been an increasing number of studies on objective image properties in visual artworks. Little is known, however, about how these image properties emerge while artists create their artworks. In order to study this matter, I produced five colored abstract artworks by myself and recorded state images at all stages of their creation. For each image, I then calculated low-level features from deep neural networks, which served as a model of responses properties in visual cortex. Two-dimensional plots of variances that were derived from these features showed that the drawings differ greatly at early stages of their creation, but then follow a narrow common path to terminate at or close to a position where traditional paintings cluster in the plots. Whether other artists use similar perceptive strategies while they create artworks remains to be studied.

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Affective pictures are widely used in studies of human emotions. The objects or scenes shown in affective pictures play a pivotal role in eliciting particular emotions. However, affective processing can also be mediated by low-level perceptual features, such as local brightness contrast, color or the spatial frequency profile. In the present study, we asked whether image properties that reflect global image structure and image composition affect the rating of affective pictures. We focused on 13 global image properties that were previously associated with the esthetic evaluation of visual stimuli, and determined their predictive power for the ratings of five affective picture datasets (IAPS, GAPED, NAPS, DIRTI, and OASIS). First, we used an SVM-RBF classifier to predict high and low ratings for valence and arousal, respectively, and achieved a classification accuracy of 58-76% in this binary decision task. Second, a multiple linear regression analysis revealed that the individual image properties account for between 6 and 20% of the variance in the subjective ratings for valence and arousal. The predictive power of the image properties varies for the different datasets and type of ratings. Ratings tend to share similar sets of predictors if they correlate positively with each other. In conclusion, we obtained evidence from non-linear and linear analyses that affective pictures evoke emotions not only by what they show, but they also differ by how they show it. Whether the human visual system actually uses these perceptive cues for emotional processing remains to be investigated.

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Curvature along a contour is important for shape perception, and a special role may be played by points of maxima (extrema) along the contour. Angles are discontinuities in curvature, a special case at one extreme of the curvature continuum. We report 4 studies using abstract shapes and comparing polygons (curvature discontinuities at the vertices) and a smoothed version of polygons (no vertices). Polygons are simpler and are defined by a small set of vertices, whereas smoothed shapes have a continuous curvature change along the contour. Angles have also been discussed as an early signal of threat and danger, and on that basis, one may predict faster responses to polygons. However, curved shapes are more typical of the natural environment in which the visual system has evolved. For a detection task, we found faster responses to smooth shapes, not mediated by complexity (Experiment 1). We then tested 3 orthogonal shape tasks: comparison between shapes (detection of repetition; Experiment 2a), comparison after a rotation (Experiment 2b), and detection of bilateral symmetry (Experiment 3). In all tasks, responses for smoothed stimuli were faster; there was also an interaction with type of response: Trials with smooth shapes were faster when a positive response was produced. Overall, there was evidence that smooth shapes with continuous change in curvature along the contour are processed more efficiently, and they tend to be classified as targets. We discuss this in relation to shape analysis and to the preference for smoothed over angular shapes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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The practice of human and veterinary medicine is based on the science of anatomy and dissection courses are still irreplaceable in the teaching of anatomy. Embalming is required to preserve body donors, for which process formaldehyde (FA) is the most frequently used and well characterized biocidal substance. Since January 2016, a new occupational exposure limit (OEL) for FA of 0.37mg/m3 issued by the European Committee on Hazardous Substances is obligatory since FA has been classified as a human 1B carcinogen. The anatomical institutes in the German-speaking region are called upon to consolidate efforts to reduce use of FA in anatomical curricula and body donations. As a result, the Anatomische Gesellschaft (AG) has formed a "Working Group for Reduction of Formaldehyde Exposure in Dissection Courses" tasked with discussion and recommendation of measures to reduce FA. Based on the assessment of the Working Group, the AG has issued an official opinion to the effect that, at this point in time, embalming of body donors without FA completely is not feasible. Therefore, a combination of approaches are to be used to reduce FA exposure, including technical and structural (architectural) adaptations, modification of protocols for fixation and preservation as well as organizational measures. One structural measure considered unavoidable is the integration of air supply and exhaust of individual dissecting tables into the ventilation system of the anatomy building. To embalm human body donors, intra-arterial perfusion fixation with up to 4% FA and a total fluid volume of 150mL/kg body weight will suffice. For animals where body weights and biology of bodies vary widely (i.e. special needs of fixation for ruminants, large animals as horses) perfusion fixation with up to 4% FA and a quantity of fixative solution of 10-15% of the body weight may be required. Preservation of body donors in storage (immersion) can be done with 40% ethanol or in a full bath preservation containing up to 2% FA. Corpse humidification in the dissecting room is possible with 2% phenoxyethanol, in each case without FA. In veterinary anatomy, microbiological burden is often higher and therefore might lead to a need of FA in long-time storage. Compliance with the current OEL in all institutes would appear to be feasible in combination with various organizational measures.

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We recently found that luminance edges are more evenly distributed across orientations in large subsets of traditional artworks, i.e., artworks are characterized by a relatively high entropy of edge orientations, when compared to several categories of other (non-art) images. In the present study, we asked whether edge-orientation entropy is associated with aesthetic preference in a wide variety of other man-made visual patterns and scenes. In the first (exploratory) part of the study, participants rated the aesthetic appeal of simple shapes, artificial ornamental patterns, facades of buildings, scenes of interior architecture, and music album covers. Results indicated that edge-orientation entropy predicts aesthetic ratings for these stimuli. However, the magnitude of the effect depended on the type of images analyzed, on the range of entropy values encountered, and on the type of aesthetic rating (pleasing, interesting, or harmonious). For example, edge-orientation entropy predicted about half of the variance when participants rated facade photographs for pleasing and interesting, but only for 3.5% of the variance for harmonious ratings of music album covers. We also asked whether edge-orientation entropy relates to the well-established human preference for curved over angular shapes. Our analysis revealed that edge-orientation entropy was as good or an even better predictor for the aesthetic ratings than curvilinearity. Moreover, entropy could substitute for shape, at least in part, to predict the aesthetic ratings. In the second (experimental) part of this study, we generated complex line stimuli that systematically varied in their edge-orientation entropy and curved/angular shape. Here, edge-orientation entropy was a more powerful predictor for ratings of pleasing and harmonious than curvilinearity, and as good a predictor for interesting. Again, the two image properties shared a large portion of variance between them. In summary, our results indicate that edge-orientation entropy predicts aesthetic ratings in diverse man-made visual stimuli. Moreover, the preference for high edge-orientation entropy shares a large portion of predicted variance with the preference for curved over angular stimuli.

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Most recent studies in experimental aesthetics have focused on the cognitive processing of visual artworks. In contrast, the perception of formal compositional features of artworks has been studied less extensively. Here, we investigated whether fast and automatic processing of artistic image composition can lead to a stable and consistent aesthetic evaluation when cognitive processing is minimized or absent. To this aim, we compared aesthetic ratings on abstract artworks and their shuffled counterparts in a gist experiment. Results show that exposure times as short as 50 ms suffice for the participants to reach a stable and consistent rating on how ordered and harmonious the abstract stimuli were. Moreover, the rating scores for the 50 ms exposure time exhibited similar dependencies on image type and self-similarity and a similar pattern of correlations between different rating terms, as the rating scores for the long exposure time (3,000 ms). Ratings were less consistent for the term interesting and inconsistent for the term pleasing. Our results are compatible with a model of aesthetic experience, in which the early perceptual processing of the formal aspects of visual artworks can lead to a consistent aesthetic judgment, even if there is no cognitive contribution to this judgment.

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We studied low-level image properties of face photographs and analyzed whether they change with different emotional expressions displayed by an individual. Differences in image properties were measured in three databases that depicted a total of 167 individuals. Face images were used either in their original form, cut to a standard format or superimposed with a mask. Image properties analyzed were: brightness, redness, yellowness, contrast, spectral slope, overall power and relative power in low, medium and high spatial frequencies. Results showed that image properties differed significantly between expressions within each individual image set. Further, specific facial expressions corresponded to patterns of image properties that were consistent across all three databases. In order to experimentally validate our findings, we equalized the luminance histograms and spectral slopes of three images from a given individual who showed two expressions. Participants were significantly slower in matching the expression in an equalized compared to an original image triad. Thus, existing differences in these image properties (i.e., spectral slope, brightness or contrast) facilitate emotion detection in particular sets of face images.

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In complex abstract art, image composition (i.e., the artist's deliberate arrangement of pictorial elements) is an important aesthetic feature. We investigated whether the human brain detects image composition in abstract artworks automatically (i.e., independently of the experimental task). To this aim, we studied whether a group of 20 original artworks elicited a visual mismatch negativity when contrasted with a group of 20 images that were composed of the same pictorial elements as the originals, but in shuffled arrangements, which destroy artistic composition. We used a passive oddball paradigm with parallel electroencephalogram recordings to investigate the detection of image type-specific properties. We observed significant deviant-standard differences for the shuffled and original images, respectively. Furthermore, for both types of images, differences in amplitudes correlated with the behavioral ratings of the images. In conclusion, we show that the human brain can detect composition-related image properties in visual artworks in an automatic fashion.

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Aesthetics has been the subject of long-standing debates by philosophers and psychologists alike. In psychology, it is generally agreed that aesthetic experience results from an interaction between perception, cognition, and emotion. By experimental means, this triad has been studied in the field of experimental aesthetics, which aims to gain a better understanding of how aesthetic experience relates to fundamental principles of human visual perception and brain processes. Recently, researchers in computer vision have also gained interest in the topic, giving rise to the field of computational aesthetics. With computing hardware and methodology developing at a high pace, the modeling of perceptually relevant aspect of aesthetic stimuli has a huge potential. In this review, we present an overview of recent developments in computational aesthetics and how they relate to experimental studies. In the first part, we cover topics such as the prediction of ratings, style and artist identification as well as computational methods in art history, such as the detection of influences among artists or forgeries. We also describe currently used computational algorithms, such as classifiers and deep neural networks. In the second part, we summarize results from the field of experimental aesthetics and cover several isolated image properties that are believed to have a effect on the aesthetic appeal of visual stimuli. Their relation to each other and to findings from computational aesthetics are discussed. Moreover, we compare the strategies in the two fields of research and suggest that both fields would greatly profit from a joined research effort. We hope to encourage researchers from both disciplines to work more closely together in order to understand visual aesthetics from an integrated point of view.

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Several statistical image properties have been associated with large subsets of traditional visual artworks. Here, we investigate some of these properties in three categories of art that differ in artistic claim and prestige: (1) Traditional art of different cultural origin from established museums and art collections (oil paintings and graphic art of Western provenance, Islamic book illustration and Chinese paintings), (2) Bad Art from two museums that collect contemporary artworks of lesser importance (© Museum Of Bad Art [MOBA], Somerville, and Official Bad Art Museum of Art [OBAMA], Seattle), and (3) twentieth century abstract art of Western provenance from two prestigious museums (Tate Gallery and Kunstsammlung Nordrhein-Westfalen). We measured the following four statistical image properties: the fractal dimension (a measure relating to subjective complexity); self-similarity (a measure of how much the sections of an image resemble the image as a whole), 1st-order entropy of edge orientations (a measure of how uniformly different orientations are represented in an image); and 2nd-order entropy of edge orientations (a measure of how independent edge orientations are across an image). As shown previously, traditional artworks of different styles share similar values for these measures. The values for Bad Art and twentieth century abstract art show a considerable overlap with those of traditional art, but we also identified numerous examples of Bad Art and abstract art that deviate from traditional art. By measuring statistical image properties, we quantify such differences in image composition for the first time.

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For centuries, oil paintings have been a major segment of the visual arts. The JenAesthetics data set consists of a large number of high-quality images of oil paintings of Western provenance from different art periods. With this database, we studied the relationship between objective image measures and subjective evaluations of the images, especially evaluations on aesthetics (defined as artistic value) and beauty (defined as individual liking). The objective measures represented low-level statistical image properties that have been associated with aesthetic value in previous research. Subjective rating scores on aesthetics and beauty correlated not only with each other but also with different combinations of the objective measures. Furthermore, we found that paintings from different art periods vary with regard to the objective measures, that is, they exhibit specific patterns of statistical image properties. In addition, clusters of participants preferred different combinations of these properties. In conclusion, the results of the present study provide evidence that statistical image properties vary between art periods and subject matters and, in addition, they correlate with the subjective evaluation of paintings by the participants.