Artificial Stimuli Research Articles

Visual channel facilitates the comprehension of the intonation of Brazilian Portuguese wh-questions and wh-exclamations: evidence from congruent and incongruent stimuli

Abstract This paper presents an audiovisual perceptual analysis of the wh-question and wh-exclamation intonation in Brazilian Portuguese using auditory–visual congruent and incongruent stimuli, to investigate the relative importance of each modality in signaling pragmatic meanings. Ten Brazilian Portuguese speakers (five female) were filmed while producing both speech acts 10 times. Next, artificial stimuli were created: audio and visual cues were either matched (audio and video from the same speech act) or mismatched (audio and video from the different speech acts), resulting in 10 congruent and 10 incongruent stimuli of the wh-questions and the wh-exclamations. The perceptual experiment was taken by 36 Brazilians who identified the stimulus as a question or an exclamation. Results from the logistic regression showed that the factor ‘congruence’ was significant and had a significant interaction with ‘speakers’, which means that the congruent stimuli increased the comprehension of the Brazilian Portuguese wh-questions and wh-exclamations. In contrast, the incongruent stimuli tended to lower listeners’ identification, but to a degree depending on individual speakers’ strategies. Although variation in the accuracy of expressing both speech acts was also found across speakers, this study corroborates that the visual channel impacts the perceptual identification of the pragmatic intonation function of distinguishing sentence mode.

Establishment of Murine Pregnancy Requires the Promyelocytic Leukemia Zinc Finger Transcription Factor.

Using an established human primary cell culture model, we previously demonstrated that the promyelocytic leukemia zinc finger (PLZF) transcription factor is a direct target of the progesterone receptor (PGR) and is essential for progestin-dependent decidualization of human endometrial stromal cells (HESCs). These in vitro findings were supported by immunohistochemical analysis of human endometrial tissue biopsies, which showed that the strongest immunoreactivity for endometrial PLZF is detected during the progesterone (P4)-dominant secretory phase of the menstrual cycle. While these human studies provided critical clinical support for the important role of PLZF in P4-dependent HESC decidualization, functional validation in vivo was not possible due to the absence of suitable animal models. To address this deficiency, we recently generated a conditional knockout mouse model in which PLZF is ablated in PGR-positive cells of the mouse (Plzf d/d). The Plzf d/d female was phenotypically analyzed using immunoblotting, real-time PCR, and immunohistochemistry. Reproductive function was tested using the timed natural pregnancy model as well as the artificial decidual response assay. Even though ovarian activity is not affected, female Plzf d/d mice exhibit an infertility phenotype due to an inability of the embryo to implant into the Plzf d/d endometrium. Initial cellular and molecular phenotyping investigations reveal that the Plzf d/d endometrium is unable to develop a transient receptive state, which is reflected at the molecular level by a blunted response to P4 exposure with a concomitant unopposed response to 17-β estradiol. In addition to a defect in P4-dependent receptivity, the Plzf d/d endometrium fails to undergo decidualization in response to an artificial decidual stimulus, providing the in vivo validation for our earlier HESC culture findings. Collectively, our new Plzf d/d mouse model underscores the physiological importance of the PLZF transcription factor not only in endometrial stromal cell decidualization but also uterine receptivity, two uterine cellular processes that are indispensable for the establishment of pregnancy.

Distributed feature representations of natural stimuli across parallel retinal pathways

How sensory systems extract salient features from natural environments and organize them across neural pathways is unclear. Combining single-cell and population two-photon calcium imaging in mice, we discover that retinal ON bipolar cells (second-order neurons of the visual system) are divided into two blocks of four types. The two blocks distribute temporal and spatial information encoding, respectively. ON bipolar cell axons co-stratify within each block, but separate laminarly between them (upper block: diverse temporal, uniform spatial tuning; lower block: diverse spatial, uniform temporal tuning). ON bipolar cells extract temporal and spatial features similarly from artificial and naturalistic stimuli. In addition, they differ in sensitivity to coherent motion in naturalistic movies. Motion information is distributed across ON bipolar cells in the upper and the lower blocks, multiplexed with temporal and spatial contrast, independent features of natural scenes. Comparing the responses of different boutons within the same arbor, we find that axons of all ON bipolar cell types function as computational units. Thus, our results provide insights into the visual feature extraction from naturalistic stimuli and reveal how structural and functional organization cooperate to generate parallel ON pathways for temporal and spatial information in the mammalian retina.

Artificial nighttime lighting impacts Plasmodium falciparum mature stage V gametocytes infectivity in Anopheles stephensi

BackgroundMalaria is one of the most important vector-borne diseases of humans with an estimated 241 million cases worldwide in 2020. As an urban and periurban mosquito species, Anopheles stephensi is exposed to artificial human stimuli like light that can alter many aspects of mosquito behaviour, physiology and metabolism. Therefore, fluctuations in the light environment may influence the host, parasite and/or mosquito biology and hence modulate risk for disease transmission. In this study, the effect of artifitial light at night on mosquito infectivity by Plasmodium falciparum during the first hours of blood digestion was tested.MethodsA total of three independent standard membrane feeding assays were performed to artificially fed septic and aseptic mosquitoes with P. falciparum infected blood. After blood feeding, females were transferred to incubators with different photoperiod cycles, so digestion occurred under day artificial light or dark. At 7 and 16 days post blood feeding, mosquitoes were dissected for midguts and salivary glands, respectively. Percentage of mosquitoes fed, percentage of prevalence and P. falciparum oocyst intensity between septic and aseptic mosquitoes in the two different photoperiod regimes, were compared using a Kruskal-Wallis test followed by a Dunn´s multiple comparison test .ResultsThe exposition of mosquitoes to light after they took an infected blood meal has a negative effect on the successful progression of P. falciparum in the mosquito midgut. Antibiotic treatment significantly incremented the number of oocysts per midgut. Photophase significantly reduced the median oocyst intensity in both septic and aseptic mosquitoes. The percentage of oocyst reduction, understood as the percentage of reduction in the mean oocyst intensity of the parasite in the mosquito midgut between photophase and scotophase, was 51% in the case of aseptic mosquitoes and 80% for septic mosquitoes, both in the photophase condition.ConclusionAlthough there are still many gaps in the understanding of parasite-mosquito interactions, these results support the idea that light can, not only, influence mosquito biting behaviour but also parasite success in the mosquito midgut. Hence, light can be considered an interesting additional mosquito-control strategy to reduce mosquito-borne diseases.

Scaling models of visual working memory to natural images

Over the last few decades, psychologists have developed precise quantitative models of human recall performance in visual working memory (VWM) tasks. However, these models are tailored to a particular class of artificial stimulus displays and simple feature reports from participants (e.g., the color or orientation of a simple object). Our work has two aims. The first is to build models that explain people’s memory errors in continuous report tasks with natural images. Here, we use image generation algorithms to generate continuously varying response alternatives that differ from the stimulus image in natural and complex ways, in order to capture the richness of people’s stored representations. The second aim is to determine whether models that do a good job of explaining memory errors with natural images also explain errors in the more heavily studied domain of artificial displays with simple items. We find that: (i) features taken from state-of-the-art deep encoders predict trial-level difficulty in natural images better than several reasonable baselines; and (ii) the same visual encoders can reproduce set-size effects and response bias curves in the artificial stimulus domains of orientation and color. Moving forward, our approach offers a scalable way to build a more generalized understanding of VWM representations by combining recent advances in both AI and cognitive modeling.

The Pigeon as a Model of Complex Visual Processing and Category Learning.

Over the past 30 years, behavioral, computational, and neuroscientific investigations have yielded fresh insights into how pigeons adapt to the diverse complexities of their visual world. A prime area of interest has been how pigeons categorize the innumerable individual stimuli they encounter. Most studies involve either photorealistic representations of actual objects thus affording the virtue of being naturalistic, or highly artificial stimuli thus affording the virtue of being experimentally manipulable. Together those studies have revealed the pigeon to be a prodigious classifier of both naturalistic and artificial visual stimuli. In each case, new computational models suggest that elementary associative learning lies at the root of the pigeon's category learning and generalization. In addition, ongoing computational and neuroscientific investigations suggest how naturalistic and artificial stimuli may be processed along the pigeon's visual pathway. Given the pigeon's availability and affordability, there are compelling reasons for this animal model to gain increasing prominence in contemporary neuroscientific research.

β-Cell Regeneration Is Driven byPancreatic Plasticity.

The pancreas has been considered a non-regenerative organ. β cells lost in diabetes are not replaced due to the inability of the pancreas to regenerate. However, ample evidence generated in the last few decades using murine models has demonstrated that the pancreas has a remarkable plasticity wherein differentiated cells can change cell fate toward a β-like cell phenotype. Although this process is observed after using rather artificial stimuli and the conversion efficiency is very limited, these findings have shed some light on novel pathways for β-cell regeneration. In this chapter, we will summarize the different cellular interconversion processes described to date, the experimental details and molecular regulation of such interconversions, and the genomic technologies that have allowed the identification of potential new ways to generate β cells.

Toddlers’ sensitivity to dominance traits from faces

In adults, seeing individual faces is sufficient to trigger dominance evaluations, even when conflict is absent. From early on, infants represent dyadic dominance relations and they can infer conflict outcomes based on a variety of cues. To date, it is unclear if toddlers also make automatic dominance trait evaluations of individual faces. Here we asked if toddlers are sensitive to dominance traits from faces, and whether their sensitivity depends on their face experience. We employed a visual preference paradigm to study 18- and 24-month-old toddlers’ sensitivity to dominance traits from three types of faces: artificial, male, female. When presented with artificial faces (Experiment 1), 18- and 24-month-olds attended longer to the non-dominant faces, but only when they were in upright orientation. For real male faces (Experiment 2), toddlers showed equivalent looking durations to the dominant and non-dominant upright faces. However, when looking at female faces (Experiment 3), toddlers displayed a visual preference for the upright non-dominant faces at 24 months. To our knowledge, this is the first study to show that toddlers already display sensitivity to facial cues of dominance from 18 months of age, at least for artificial face stimuli.

A systematic review of methodologies for studying behavioral imprinting

AbstractBehavioral imprinting is a learning phenomenon by which animals acquire preferences for stimuli through perceptual exposure during critical periods, without substantial external reinforcement. Since being acknowledged in 1516 by Sir Thomas More in artificially incubated domestic chickens, imprinting has been reported in diverse species, across various sensory modalities, and during different life‐history stages. Due to this diversity, imprinting research uses highly varied methodologies, with distinctive differences between the methods employed for different types of imprinting. We systematically review relevant literature, identifying and describing the range of methodologies used to study imprinting across taxa and modalities. After compiling a representative dataset of 192 behavioral imprinting‐focused experiments, we categorize studies by imprinting sensory modality, focal species, ontogenetic stage addressed, and methods applied for both exposure and testing. The majority of studies in the sample focus on filial imprinting in precocial birds but nonfilial types, such as sexual or home range imprinting in altricial and non‐avian species, are also present, albeit at far lower proportions. Filial imprinting is studied across different sensory modalities, mostly through applying artificial stimuli, but nonfilial imprinting studies mainly use live animals as stimuli, without isolating the relevant sensory modalities. Most studies of filial imprinting measure preference by spatial proximity, following response, or the suppression of a fear response, whereas most studies of sexual imprinting employ the attempt frequency of sexual behaviors. Finally, we analyze the relative frequencies of methodological approaches in each imprinting category, to highlight potential biases due to uneven research effort rather than intrinsic biology. The patterns and biases in imprinting methodologies that we uncover hamper attempts to establish whether different forms of imprinting share mechanistic foundations, including whether imprinting constitutes a biologically meaningful learning category.

Accurate knowledge about feature diagnosticities leads to less preference for unidimensional strategy.

In classification learning of artificial stimuli, participants learn the perfectly diagnostic dimension better than the partially diagnostic dimensions. Also, there is a strong preference for a unidimensional categorization based on the perfectly diagnostic dimension. In a different experimental procedure, called array-based classification task, participants do not exhibit a preference for a unidimensional categorization. In Experiment 1, we replicate the above results. In Experiment 2, we show that when participants learn the partially diagnostic features through repeated testing, there is a decrease in unidimensional categorization. We use Bayesian modeling to show that only those participants who learned the diagnosticity of a dimension with a high level of accuracy (≥ 75%) used the dimension for categorization. Our results show that whenever accurate knowledge about feature diagnosticities is available, there is a lesser preference for unidimensional categorization. Our results provide a possible explanation for the preference of unidimensional categorization in classification and observation learning. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Scalable Gaussian process inference of neural responses to natural images

Predicting the responses of sensory neurons is a long-standing neuroscience goal. However, while there has been much progress in modeling neural responses to simple and/or artificial stimuli, predicting responses to natural stimuli remains an ongoing challenge. On the one hand, deep neural networks perform very well on certain datasets but can fail when data are limited. On the other hand, Gaussian processes (GPs) perform well on limited data but are poor at predicting responses to high-dimensional stimuli, such as natural images. Here, we show how structured priors, e.g., for local and smooth receptive fields, can be used to scale up GPs to model neural responses to high-dimensional stimuli. With this addition, GPs largely outperform a deep neural network trained to predict retinal responses to natural images, with the largest differences observed when both models are trained on a small dataset. Further, since they allow us to quantify the uncertainty in their predictions, GPs are well suited to closed-loop experiments, where stimuli are chosen actively so as to collect "informative" neural data. We show how GPs can be used to actively select which stimuli to present, so as to i) efficiently learn a model of retinal responses to natural images, using few data, and ii) rapidly distinguish between competing models (e.g., a linear vs. a nonlinear model). In the future, our approach could be applied to other sensory areas, beyond the retina.

Model aversiveness and the evolution of imperfect Batesian mimics.

There are numerous examples of Batesian mimics that only imperfectly resemble their models. Given that inaccurate mimics are known to be predated more frequently than accurate ones, imperfect mimicry therefore poses something of a conundrum. One putative explanation, the relaxed selection hypothesis, predicts that when the cost of attacking a model is high relative to the benefit of consuming a mimic, selection against imperfect mimics will be relaxed, allowing mimics to be more imperfect for a given level of fitness. However, empirical support for this hypothesis is equivocal. Here, we report an experimental test of the relaxed selection hypothesis, in which human participants were tasked with discriminating between artificial stimuli representing models and mimics. In response to "attacking" a model (i.e., misclassifying it as palatable, or non-aversive) they received either a mild electric shock (high cost) or vibratory feedback (low cost). Consistent with the predictions of this hypothesis, we found that when the cost of attacking a model was high, mimetic phenotype could deviate more from the model (i.e., be more imperfect) for a given level of fitness than when the cost of attacking a model was low. Moreover, when the cost of attacking a model was high, participants showed an increased latency to attack. This finding shows that given sufficient costs, the relaxed selection hypothesis is a plausible explanation for the evolution of imperfect mimicry.

The potential of robot eyes as predictive cues in HRI-an eye-tracking study.

Robots currently provide only a limited amount of information about their future movements to human collaborators. In human interaction, communication through gaze can be helpful by intuitively directing attention to specific targets. Whether and how this mechanism could benefit the interaction with robots and how a design of predictive robot eyes in general should look like is not well understood. In a between-subjects design, four different types of eyes were therefore compared with regard to their attention directing potential: a pair of arrows, human eyes, and two anthropomorphic robot eye designs. For this purpose, 39 subjects performed a novel, screen-based gaze cueing task in the laboratory. Participants' attention was measured using manual responses and eye-tracking. Information on the perception of the tested cues was provided through additional subjective measures. All eye models were overall easy to read and were able to direct participants' attention. The anthropomorphic robot eyes were most efficient at shifting participants' attention which was revealed by faster manual and saccadic reaction times. In addition, a robot equipped with anthropomorphic eyes was perceived as being more competent. Abstract anthropomorphic robot eyes therefore seem to trigger a reflexive reallocation of attention. This points to a social and automatic processing of such artificial stimuli.

It is not real until it feels real: Testing a new method for simulation of eyewitness experience with virtual reality technology and equipment.

Laboratory research in the psychology of witness testimony is often criticized for its lack of ecological validity, including the use of unrealistic artificial stimuli to test memory performance. The purpose of our study is to present a method that can provide an intermediary between laboratory research and field studies or naturalistic experiments that are difficult to control and administer. It uses Video-360° technology and virtual reality (VR) equipment, which cuts subjects off from external stimuli and gives them control over the visual field. This can potentially increase the realism of the eyewitness's experience. To test the method, we conducted an experiment comparing the immersion effect, emotional response, and memory performance between subjects who watched a video presenting a mock crime on a head-mounted display (VR goggles; n = 57) and a screen (n = 50). The results suggest that, compared to those who watched the video on a screen, the VR group had a deeper sense of immersion, that is, of being part of the scene presented. At the same time, they were not distracted or cognitively overloaded by the more complex virtual environment, and remembered just as much detail about the crime as those viewing it on the screen. Additionally, we noted significant differences between subjects in ratings of emotions felt during the video. This may suggest that the two formats evoke different types of discrete emotions. Overall, the results confirm the usefulness of the proposed method in witness research.

The Impact of Artificial Intelligence Technology Stimuli on Sustainable Consumption Behavior: Evidence from Ant Forest Users in China.

With the global economy and population growing rapidly, the problems of excessive resource consumption and environmental pollution have become increasingly serious. Thus, the need to promote sustainable development has become more urgent. Sustainable consumption behavior plays a crucial role in achieving sustainable development goals as it can significantly reduce both greenhouse gas emissions and resource consumption. Artificial intelligence technology has broken the limitations of time and space in environmental protection. For example, the Ant Forest leverages the design of "green energy" to inspire the public to engage in energy-saving and emission-reducing activities. To examine the impact mechanisms of customers' sustainable consumption behavior, this study applies the stimulus-organism-response theory and the theory of planned behavior. The study conducts regression analysis and bootstrapping methods on a sample consisting of 280 Ant Forest users to explore the influence of artificial intelligence technology stimuli on sustainable consumption behavior and the mediating effects of customer-perceived value and customer stickiness. The results demonstrate a "linkage effect" between online green consumption habits and offline sustainable consumption behavior. Moreover, the study finds that passion and usability indirectly promote offline sustainable consumption behavior through customer-perceived value and customer stickiness. Specifically, the influence of customer-perceived emotional value (β = 0.121; β = 0.100) is stronger than that of customer-perceived social value (β = 0.043; β = 0.038). Due to the limitation of the sample size, future research should broaden its scope by incorporating additional variables, specifically customer-specific factors. Furthermore, more advanced research methods, such as big data analysis, should be employed to comprehensively explore the influencing factors of sustainable consumer behavior.

Contrast normalization affects response time-course of visual interneurons.

In natural environments, light intensities and visual contrasts vary widely, yet neurons have a limited response range for encoding them. Neurons accomplish that by flexibly adjusting their dynamic range to the statistics of the environment via contrast normalization. The effect of contrast normalization is usually measured as a reduction of neural signal amplitudes, but whether it influences response dynamics is unknown. Here, we show that contrast normalization in visual interneurons of Drosophila melanogaster not only suppresses the amplitude but also alters the dynamics of responses when a dynamic surround is present. We present a simple model that qualitatively reproduces the simultaneous effect of the visual surround on the response amplitude and temporal dynamics by altering the cells' input resistance and, thus, their membrane time constant. In conclusion, single-cell filtering properties as derived from artificial stimulus protocols like white-noise stimulation cannot be transferred one-to-one to predict responses under natural conditions.

Jackdaws form categorical prototypes based on experience with category exemplars

Categorization represents one cognitive ability fundamental to animal behavior. Grouping of elements based on perceptual or semantic features helps to reduce processing resources and facilitates appropriate behavior. Corvids master complex categorization, yet the detailed categorization learning strategies are less well understood. We trained two jackdaws on a delayed match to category paradigm using a novel, artificial stimulus type, RUBubbles. Both birds learned to differentiate between two session-unique categories following two distinct learning protocols. Categories were either introduced via central category prototypes (low variability approach) or using a subset of diverse category exemplars from which diagnostic features had to be identified (high variability approach). In both versions, the stimulus similarity relative to a central category prototype explained categorization performance best. Jackdaws consistently used a central prototype to judge category membership, regardless of whether this prototype was used to introduce distinct categories or had to be inferred from multiple exemplars. Reliance on a category prototype occurred already after experiencing only a few trials with different category exemplars. High stimulus set variability prolonged initial learning but showed no consistent beneficial effect on later generalization performance. High numbers of stimuli, their perceptual similarity, and coherent category structure resulted in a prototype-based strategy, reflecting the most adaptive, efficient, and parsimonious way to represent RUBubble categories. Thus, our birds represent a valuable comparative animal model that permits further study of category representations throughout learning in different regions of a brain producing highly cognitive behavior.Graphical abstract

To What Extent Does Technological Overstimulation Affect Productivity?

This research paper investigates the consequences of technological overstimulation on productivity. By establishing a structural basis of the conscious and subconscious effects of technology usage on the mind, through the effects of artificial stimuli on Dopamine release and the myelination of neural pathways, a proportionate relationship between varying degrees of overstimulation and a person's productive output can be determined: signified by fluctuations in the quantity or quality of one's work.

Audiovisual correspondence facilitates the visual search for biological motion

Hearing synchronous sounds may facilitate the visual search for the concurrently changed visual targets. Evidence for this audiovisual attentional facilitation effect mainly comes from studies using artificial stimuli with relatively simple temporal dynamics, indicating a stimulus-driven mechanism whereby synchronous audiovisual cues create a salient object to capture attention. Here, we investigated the crossmodal attentional facilitation effect on biological motion (BM), a natural, biologically significant stimulus with complex and unique dynamic profiles. We found that listening to temporally congruent sounds, compared with incongruent sounds, enhanced the visual search for BM targets. More intriguingly, such a facilitation effect requires the presence of distinctive local motion cues (especially the accelerations in feet movement) independent of the global BM configuration, suggesting a crossmodal mechanism triggered by specific biological features to enhance the salience of BM signals. These findings provide novel insights into how audiovisual integration boosts attention to biologically relevant motion stimuli and extend the function of a proposed life detection system driven by local kinematics of BM to multisensory life motion perception.

Efficient coding of natural scenes improves neural system identification.

Neural system identification aims at learning the response function of neurons to arbitrary stimuli using experimentally recorded data, but typically does not leverage normative principles such as efficient coding of natural environments. Visual systems, however, have evolved to efficiently process input from the natural environment. Here, we present a normative network regularization for system identification models by incorporating, as a regularizer, the efficient coding hypothesis, which states that neural response properties of sensory representations are strongly shaped by the need to preserve most of the stimulus information with limited resources. Using this approach, we explored if a system identification model can be improved by sharing its convolutional filters with those of an autoencoder which aims to efficiently encode natural stimuli. To this end, we built a hybrid model to predict the responses of retinal neurons to noise stimuli. This approach did not only yield a higher performance than the "stand-alone" system identification model, it also produced more biologically plausible filters, meaning that they more closely resembled neural representation in early visual systems. We found these results applied to retinal responses to different artificial stimuli and across model architectures. Moreover, our normatively regularized model performed particularly well in predicting responses of direction-of-motion sensitive retinal neurons. The benefit of natural scene statistics became marginal, however, for predicting the responses to natural movies. In summary, our results indicate that efficiently encoding environmental inputs can improve system identification models, at least for noise stimuli, and point to the benefit of probing the visual system with naturalistic stimuli.