Selective labelling of GBA2 in cells with fluorescent ß-d-arabinofuranosyl cyclitol aziridines.

GBA2, the non-lysosomal ß-glucosylceramidase, is an enzyme involved in glucosylceramide metabolism. Pharmacological inhibition of GBA2 by N-alkyl iminosugars is well tolerated and benefits patients suffering from Sandhoff and Niemann-Pick type C diseases, and GBA2 inhibitors have been proposed as candidate-clinical drugs for the treatment of parkinsonism. With the ultimate goal to unravel the role of GBA2 in (patho)physiology, we sought to develop a GBA2-specific activity-based probe (ABP). A library of probes was tested for activity against GBA2 and the two other cellular retaining ß-glucosidases, lysosomal GBA1 and cytosolic GBA3. We show that ß-d-arabinofuranosyl cyclitol aziridine (ß-d-Araf aziridine) reacts with the GBA2 active site nucleophile to form a covalent and irreversible bond. Fluorescent ß-d-Araf aziridine probes potently and selectively label GBA2 both in vitro and in cellulo, allowing for visualization of the localization of overexpressed GBA2 using fluorescence microscopy. Co-staining with an antibody selective for the lysosomal ß-glucosylceramidase GBA1, shows distinct subcellular localization of the two enzymes. We proffer our ABP technology for further delineating the role and functioning of GBA2 in disease and propose the ß-d-Araf aziridine scaffold as a good starting point for the development of GBA2-specific inhibitors for clinical development.

Measuring transformative virtual reality experiences in children's drawings.

Transformative experiences in an individual's life have a lasting impact on identity, belief system, and values. At the core of these experiences is the complex emotion of awe that promotes learning, making it worthwhile to study from an educational point of view. Drawing studies may provide a useful measure of awe in children-one that is more intuitive and attractive than questionnaires alone. Previous studies conducted with adults indicated that the diminished self, associated with transformative experiences, manifests in an actual decrease in size for figures representing the self in drawings. In the current study, self-representation was investigated in drawings of 10- to 12-year-old primary school children within the context of an immersive virtual reality (VR) experience that elicits the overview effect, known to lead to an intense apperception of awe. We did not replicate the adult findings regarding self-size in this younger age group. However, details and complexity in children's drawings appeared to be impacted by the awe-elicitation procedure in VR. These elements subsequently correlated to learning gains instead of the overview effect, indicating that this measure could be linked to cognitive ability. The findings of the current study contribute to a better understanding of how drawings reflect self-transcendental experiences; however, they also reveal that in younger age groups, they are not necessarily reflected in decreased self-size.

Lingualyzer: A computational linguistic tool for multilingual and multidimensional text analysis.

Most natural language models and tools are restricted to one language, typically English. For researchers in the behavioral sciences investigating languages other than English, and for those researchers who would like to make cross-linguistic comparisons, hardly any computational linguistic tools exist, particularly none for those researchers who lack deep computational linguistic knowledge or programming skills. Yet, for interdisciplinary researchers in a variety of fields, ranging from psycholinguistics, social psychology, cognitive psychology, education, to literary studies, there certainly is a need for such a cross-linguistic tool. In the current paper, we present Lingualyzer ( https://lingualyzer.com ), an easily accessible tool that analyzes text at three different text levels (sentence, paragraph, document), which includes 351 multidimensional linguistic measures that are available in 41 different languages. This paper gives an overview of Lingualyzer, categorizes its hundreds of measures, demonstrates how it distinguishes itself from other text quantification tools, explains how it can be used, and provides validations. Lingualyzer is freely accessible for scientific purposes using an intuitive and easy-to-use interface.

Surface and Contextual Linguistic Cues in Dialog Act Classification: A Cognitive Science View.

What role do linguistic cues on a surface and contextual level have in identifying the intention behind an utterance? Drawing on the wealth of studies and corpora from the computational task of dialog act classification, we studied this question from a cognitive science perspective. We first reviewed the role of linguistic cues in dialog act classification studies that evaluated model performance on three of the most commonly used English dialog act corpora. Findings show that frequency-based, machine learning, and deep learning methods all yield similar performance. Classification accuracies, moreover, generally do not explain which specific cues yield high performance. Using a cognitive science approach, in two analyses, we systematically investigated the role of cues in the surface structure of the utterance and cues of the surrounding context individually and combined. By comparing the explained variance, rather than the prediction accuracy of these cues in a logistic regression model, we found that (1) while surface and contextual linguistic cues can complement each other, surface linguistic cues form the backbone in human dialog act identification, (2) with word frequency statistics being particularly important for the dialog act, and (3) the similar trends across corpora, despite differences in the type of dialog, corpus setup, and dialog act tagset. The importance of surface linguistic cues in dialog act classification sheds light on how both computers and humans take advantage of these cues in speech act recognition.

Fluorescence polarisation activity-based protein profiling for the identification of deoxynojirimycin-type inhibitors selective for lysosomal retaining alpha- and beta-glucosidases.

Lysosomal exoglycosidases are responsible for processing endocytosed glycans from the non-reducing end to produce the corresponding monosaccharides. Genetic mutations in a particular lysosomal glycosidase may result in accumulation of its particular substrate, which may cause diverse lysosomal storage disorders. The identification of effective therapeutic modalities to treat these diseases is a major yet poorly realised objective in biomedicine. One common strategy comprises the identification of effective and selective competitive inhibitors that may serve to stabilize the proper folding of the mutated enzyme, either during maturation and trafficking to, or residence in, endo-lysosomal compartments. The discovery of such inhibitors is greatly aided by effective screening assays, the development of which is the focus of the here-presented work. We developed and applied fluorescent activity-based probes reporting on either human GH30 lysosomal glucosylceramidase (GBA1, a retaining ß-glucosidase) or GH31 lysosomal retaining α-glucosidase (GAA). FluoPol-ABPP screening of our in-house 358-member iminosugar library yielded compound classes selective for either of these enzymes. In particular, we identified a class of N-alkyldeoxynojirimycins that inhibit GAA, but not GBA1, and that may form the starting point for the development of pharmacological chaperone therapeutics for the lysosomal glycogen storage disease that results from genetic deficiency in GAA: Pompe disease.

Zipf's law revisited: Spoken dialog, linguistic units, parameters, and the principle of least effort.

The ubiquitous inverse relationship between word frequency and word rank is commonly known as Zipf's law. The theoretical underpinning of this law states that the inverse relationship yields decreased effort in both the speaker and hearer, the so-called principle of least effort. Most research has focused on showing an inverse relationship only for written monolog, only for frequencies and ranks of one linguistic unit, generally word unigrams, with strong correlations of the power law to the observed frequency distributions, with limited to no attention to psychological mechanisms such as the principle of least effort. The current paper extends the existing findings, by not focusing on written monolog but on a more fundamental form of communication, spoken dialog, by not only investigating word unigrams but also units quantified on syntactic, pragmatic, utterance, and nonverbal communicative levels by showing that the adequacy of Zipf's formula seems ubiquitous, but the exponent of the power law curve is not, and by placing these findings in the context of Zipf's principle of least effort through redefining effort in terms of cognitive resources available for communication. Our findings show that Zipf's law also applies to a more natural form of communication-that of spoken dialog, that it applies to a range of linguistic units beyond word unigrams, that the general good fit of Zipf's law needs to be revisited in light of the parameters of the formula, and that the principle of least effort is a useful theoretical framework for the findings of Zipf's law.

Corneal reflections and skin contrast yield better memory of human and virtual faces.

Virtual faces have been found to be rated less human-like and remembered worse than photographic images of humans. What it is in virtual faces that yields reduced memory has so far remained unclear. The current study investigated face memory in the context of virtual agent faces and human faces, real and manipulated, considering two factors of predicted influence, i.e., corneal reflections and skin contrast. Corneal reflections referred to the bright points in each eye that occur when the ambient light reflects from the surface of the cornea. Skin contrast referred to the degree to which skin surface is rough versus smooth. We conducted two memory experiments, one with high-quality virtual agent faces (Experiment 1) and the other with the photographs of human faces that were manipulated (Experiment 2). Experiment 1 showed better memory for virtual faces with increased corneal reflections and skin contrast (rougher rather than smoother skin). Experiment 2 replicated these findings, showing that removing the corneal reflections and smoothening the skin reduced memory recognition of manipulated faces, with a stronger effect exerted by the eyes than the skin. This study highlights specific features of the eyes and skin that can help explain memory discrepancies between real and virtual faces and in turn elucidates the factors that play a role in the cognitive processing of faces.

Aviation and neurophysiology: A systematic review.

This paper systematically reviews 20 years of publications (N = 54) on aviation and neurophysiology. The main goal is to provide an account of neurophysiological changes associated with flight training with the aim of identifying neurometrics indicative of pilot's flight training level and task relevant mental states, as well as to capture the current state-of-art of (neuro)ergonomic design and practice in flight training. We identified multiple candidate neurometrics of training progress and workload, such as frontal theta power, the EEG Engagement Index and the Cognitive Stability Index. Furthermore, we discovered that several types of classifiers could be used to accurately detect mental states, such as the detection of drowsiness and mental fatigue. The paper advances practical guidelines on terminology usage, simulator fidelity, and multimodality, as well as future research ideas including the potential of Virtual Reality flight simulations for training, and a brain-computer interface for flight training.

Measures of prefrontal functional near-infrared spectroscopy in visuomotor learning.

Functional near-infrared spectroscopy (fNIRS) is a promising technique for non-invasively assessing cortical brain activity during learning. This technique is safe, portable, and, compared to other imaging techniques, relatively robust to head motion, ocular and muscular artifacts and environmental noise. Moreover, the spatial resolution of fNIRS is superior to electroencephalography (EEG), a more commonly applied technique for measuring brain activity non-invasively during learning. Outcomes from fNIRS measures during learning might therefore be both sensitive to learning and to feedback on learning, in a different way than EEG. However, few studies have examined fNIRS outcomes in learning and no study to date additionally examined the effects of feedback. To address this apparent gap in the literature, the current study examined prefrontal cortex activity measured through fNIRS during visuomotor learning and how this measure is affected by task feedback. Activity in the prefrontal cortex decreased over the course of learning while being unaffected by task feedback. The findings demonstrate that fNIRS in the prefrontal cortex is valuable for assessing visuomotor learning and that this measure is robust to task feedback. The current study highlights the potential of fNIRS in assessing learning even under different task feedback conditions.

Creating Ambassadors of Planet Earth: The Overview Effect in K12 Education.

The overview effect is the commonly reported experience of astronauts viewing planet Earth from space and the subsequent reflection on and processing of this experience. The overview effect is associated with feelings of awe, self-transcendence, and a change of perspective and identity that manifest themselves in taking steps toward protecting the fragile ecosystem. In the current study, we investigated whether the overview effect can be obtained in school children when simulated using virtual reality (VR) and whether the effect has a positive impact on learning gains. Using questionnaires and attention data in an existing simulation environment used in the school system, we showed that the VR simulation elicits an overview effect experience. Moreover, the experience yields learning gains in the domain of astrophysics. These findings are in line with past evidence regarding the positive impact of awe on learning and can be used to support further investigations of the relation between the overview effect and behavioral changes, specifically for educational purposes.

Non-invasive Neurophysiology in Learning and Training: Mechanisms and a SWOT Analysis.

Although many scholars deem non-invasive measures of neurophysiology to have promise in assessing learning, these measures are currently not widely applied, neither in educational settings nor in training. How can non-invasive neurophysiology provide insight into learning and how should research on this topic move forward to ensure valid applications? The current article addresses these questions by discussing the mechanisms underlying neurophysiological changes during learning followed by a SWOT (strengths, weaknesses, opportunities, and threats) analysis of non-invasive neurophysiology in learning and training. This type of analysis can provide a structured examination of factors relevant to the current state and future of a field. The findings of the SWOT analysis indicate that the field of neurophysiology in learning and training is developing rapidly. By leveraging the opportunities of neurophysiology in learning and training (while bearing in mind weaknesses, threats, and strengths) the field can move forward in promising directions. Suggestions for opportunities for future work are provided to ensure valid and effective application of non-invasive neurophysiology in a wide range of learning and training settings.

Does Number Perception Cause Automatic Shifts of Spatial Attention? A Study of the Att-SNARC Effect in Numbers and Chinese Months.

The Attentional Spatial Numerical Association of Response Codes (Att-SNARC) effect has shown that number perception induces shifts in spatial attention (Fischer et al., 2003; Dodd et al., 2008). However, many replications were attempted and they often failed. In the present study, we investigated whether the Att-SNARC effect can be found for numbers in different notations: months in Arabic form, Simplified Chinese form, Traditional Chinese form (includes numerical ordinal information) and in Chinese non-numerical form (an ordinal sequence). By varying the cognitive task, we also examined whether the effect is a consequence of automatic perceptual processing. In Experiment 1, an Att-SNARC effect was observed for numbers regardless of notation. In Experiment 2 (order-irrelevant task) and Experiment 3 (order-relevant task), the effect was also found consistently for months in Arabic form, Simplified Chinese form, and Traditional Chinese form. This effect was not observed for months in Chinese non-numerical form in Experiment 3. These results show that number and numerical sequence perception automatically causes a spatial shift of attention. Our study provides positive evidence for the Att-SNARC effect and indicates that the effect can generalize to other numerical ordinal sequences that contain numeric information.

Neurophysiological changes in visuomotor sequence learning provide insight in general learning processes: Measures of brain activity, skin conductance, heart rate and respiration.

Prior research has shown neurophysiological measures of learning yield large effect sizes, suggesting that these measures have high potential in providing insight into learning. Yet, most literature on learning and neurophysiological measures focused on a single outcome measure, neglecting the interplay between different types of measures. Additionally, it is not yet clear which measures change robustly in a way specific to the learning process. The current study assessed implicit visuomotor sequence learning through multiple neurophysiological outcome measures. In two experiments participants were presented with an arm-movement version of the Serial Reaction Time Task with blocks in which targets were selected in a repeating sequence and blocks in which targets were selected randomly. While participants were executing this task, measures of EEG, skin conductance, heart rate (variability) and respiration, in addition to measures of behavioral performance, were collected. Although behavioral performance was sensitive to sequence learning, as demonstrated by faster responses in sequence than in random blocks, neurophysiology was not sensitive to sequence learning. However, in both experiments, skin conductance level and parietal EEG alpha and gamma power were sensitive to task induction and changed during sequence blocks in the direction of a pre-task baseline and were related to behavioral performance. In general, models including only EEG parietal gamma power were just as powerful in explaining behavioral measures during learning as models including a combination of neurophysiological outcome measures. The findings of the current study demonstrate that neurophysiology is not sensitive to implicit sequence learning specifically, but that general learning effects on a visuomotor learning task are reflected in measures of neurophysiology. Additionally, the findings highlight that a combination of neurophysiological outcome measures is not necessarily better in explaining task learning than a single measure.

Non-invasive neurophysiological measures of learning: A meta-analysis.

In a meta-analysis of 113 experiments we examined neurophysiological outcomes of learning, and the relationship between neurophysiological and behavioral outcomes of learning. Findings showed neurophysiology yielding large effect sizes, with the majority of studies examining electroencephalography and eye-related outcome measures. Effect sizes on neurophysiological outcomes were smaller than effect sizes on behavioral outcomes, however. Neurophysiological outcomes were, but behavioral outcomes were not, influenced by several modulating factors. These factors included the sensory system in which learning took place, number of learning days, whether feedback on performance was provided, and age of participants. Controlling for these factors resulted in the effect size differences between behavior and neurophysiology to disappear. The findings of the current meta-analysis demonstrate that neurophysiology is an appropriate measure in assessing learning, particularly when taking into account factors that could have an influence on neurophysiology. We propose a first model to aid further studies that are needed to examine the exact interplay between learning, neurophysiology, behavior, individual differences, and task-related aspects.

Respiratory Biofeedback Does Not Facilitate Lowering Arousal in Meditation Through Virtual Reality.

The current study examined the effectiveness of respiratory biofeedback in lowering subjective and objective arousal after stress. Participants were presented with a meditation session in virtual reality while subjective and objective arousal were measured, the latter measured through ECG and EEG. Three conditions were used: (a) a respiratory biofeedback condition, in which visual feedback was paired to breathing; (b) a control feedback placebo condition, in which visual feedback was not paired to breathing; and (c) a control no-feedback condition, in which no visual feedback was used. Subjective and objective arousal decreased during meditation after stress in all conditions, demonstrating recovery after stress during meditation in virtual reality. However, the reduction in arousal (on all outcome measures combined and heart rate specifically) was largest in the control feedback placebo condition, in which no biofeedback was used, indicating that respiratory biofeedback had no additional value in reducing arousal. The findings of the current study highlight the importance of including a control feedback placebo condition in order to establish the exact additional value of biofeedback and offer insights in applying cost-effective virtual reality meditation training.

Knowing the Meaning of a Word by the Linguistic and Perceptual Company It Keeps.

Debates on meaning and cognition suggest that an embodied cognition account is exclusive of a symbolic cognition account. Decades of research in the cognitive sciences have, however, shown that these accounts are not at all mutually exclusive. Acknowledging cognition is both symbolic and embodied generates more relevant questions that propel, rather than divide, the cognitive sciences: questions such as how computational symbolic findings map onto experimental embodied findings, and under what conditions cognition is relatively more symbolic or embodied in nature. The current paper revisits the Symbol Interdependency Hypothesis, which argues that language encodes perceptual information and that language users rely on these language statistics in cognitive processes. It argues that the claim that words are abstract, amodal, and arbitrary symbols and therefore must always be grounded to become meaningful is an oversimplification of the language system. Instead, language has evolved such that it maps onto the perceptual system, whereby language users rely on language statistics, which allow for bootstrapping meaning also when grounding is limited.

The Bursts and Lulls of Multimodal Interaction: Temporal Distributions of Behavior Reveal Differences Between Verbal and Non-Verbal Communication.

Recent studies of naturalistic face-to-face communication have demonstrated coordination patterns such as the temporal matching of verbal and non-verbal behavior, which provides evidence for the proposal that verbal and non-verbal communicative control derives from one system. In this study, we argue that the observed relationship between verbal and non-verbal behaviors depends on the level of analysis. In a reanalysis of a corpus of naturalistic multimodal communication (Louwerse, Dale, Bard, & Jeuniaux, ), we focus on measuring the temporal patterns of specific communicative behaviors in terms of their burstiness. We examined burstiness estimates across different roles of the speaker and different communicative modalities. We observed more burstiness for verbal versus non-verbal channels, and for more versus less informative language subchannels. Using this new method for analyzing temporal patterns in communicative behaviors, we show that there is a complex relationship between verbal and non-verbal channels. We propose a "temporal heterogeneity" hypothesis to explain how the language system adapts to the demands of dialog.

Estimating Emotions Through Language Statistics and Embodied Cognition.

Recent research has suggested that language processing activates perceptual simulations. We have demonstrated that findings that have been attributed to an embodied cognition account can also be explained by language statistics, because language encodes perceptual information. We investigated whether comprehension of emotion words can be explained by an embodied cognition or a language statistics account. A corpus linguistic study comparing emotions words showed that words denoting the same emotions (happy-delighted) co-occur more frequently than different emotions (happy-angry). These findings were used in two experiments in which participants read same-emotion and different-emotion sentence pairs. Sentence pairs with different emotions yielded longer RTs than sentences with the same emotions both in a cognitive task tailored toward linguistic representations and a task tailored toward embodied representations. These findings contribute to a growing body of literature that demonstrates that language processing does not always rely solely on perceptual simulation.

Estimating valence from the sound of a word: Computational, experimental, and cross-linguistic evidence.

It is assumed linguistic symbols must be grounded in perceptual information to attain meaning, because the sound of a word in a language has an arbitrary relation with its referent. This paper demonstrates that a strong arbitrariness claim should be reconsidered. In a computational study, we showed that one phonological feature (nasals in the beginning of a word) predicted negative valence in three European languages (English, Dutch, and German) and positive valence in Chinese. In three experiments, we tested whether participants used this feature in estimating the valence of a word. In Experiment 1, Chinese and Dutch participants rated the valence of written valence-neutral words, with Chinese participants rating the nasal-first neutral-valence words more positive and the Dutch participants rating nasal-first neutral-valence words more negative. In Experiment 2, Chinese (and Dutch) participants rated the valence of Dutch (and Chinese) written valence-neutral words without being able to understand the meaning of these words. The patterns replicated the valence patterns from Experiment 1. When the written words from Experiment 2 were transformed into spoken words, results in Experiment 3 again showed that participants estimated the valence of words on the basis of the sound of the word. The computational study and psycholinguistic experiments indicated that language users can bootstrap meaning from the sound of a word.