Cue Learning Research Articles

Neuronal activity in the ventral tegmental area during goal-directed navigation recorded by low-curvature microelectrode arrays

Navigating toward destinations with rewards is a common behavior among animals. The ventral tegmental area (VTA) has been shown to be responsible for reward coding and reward cue learning, and its response to other variables, such as kinematics, has also been increasingly studied. These findings suggest a potential relationship between animal navigation behavior and VTA activity. However, the deep location and small volume of the VTA pose significant challenges to the precision of electrode implantation, increasing the uncertainty of measurement results during animal navigation and thus limiting research on the role of the VTA in goal-directed navigation. To address this gap, we innovatively designed and fabricated low-curvature microelectrode arrays (MEAs) via a novel backside dry etching technique to release residual stress. Histological verification confirmed that low-curvature MEAs indeed improved electrode implantation precision. These low-curvature MEAs were subsequently implanted into the VTA of the rats to observe their electrophysiological activity in a freely chosen modified T-maze. The results of the behavioral experiments revealed that the rats could quickly learn the reward probability corresponding to the left and right paths and that VTA neurons were deeply involved in goal-directed navigation. Compared with those in no-reward trials, VTA neurons in reward trials presented a significantly greater firing rate and larger local field potential (LFP) amplitude during the reward-consuming period. Notably, we discovered place fields mapped by VTA neurons, which disappeared or were reconstructed with changes in the path–outcome relationship. These results provide new insights into the VTA and its role in goal-directed navigation. Our designed and fabricated low-curvature microelectrode arrays can serve as a new device for precise deep brain implantation in the future.

Question generation type and organizational cues in video learning: A study on their effects on online learning behaviors

This study examined the influence of question generation types and organizational cues on video learning. Participants were 100 undergraduate students randomly assigned to view videos that differed in terms of question generation type (instructor-generated vs. self-generated) and organizational cues (with vs. without). The results revealed that self-generated questions led to superior learning performance and higher cognitive load compared to instructor-generated questions in the absence of organizational cues, but when combined with organizational cues, there was no significant difference between the instructor and self-generated questions. Additionally, students who engaged with self-generated questions demonstrated a higher frequency of interaction and seeking behaviors and meta-cognition. Mediation analysis further indicated that self-generated questions, compared to instructor-generated questions, improved learning performance by increasing both the seeking frequency and cognitive load. These findings underscore the importance of question generation and organizational cues in video learning. They also have practical implications for design and use of video learning: if students are required to generate questions by themselves, it is better not to provide organizational cues; this will foster their engagement (more research behaviors and higher cognitive load) and thus their learning. In contrast, if they must answer questions generated by the instructor, the presence or absence of organizational cues does not matter.

Perceiving depth beyond sight: Evaluating intrinsic and learned cues via a proof of concept sensory substitution method in the visually impaired and sighted.

This study explores spatial perception of depth by employing a novel proof of concept sensory substitution algorithm. The algorithm taps into existing cognitive scaffolds such as language and cross modal correspondences by naming objects in the scene while representing their elevation and depth by manipulation of the auditory properties for each axis. While the representation of verticality utilized a previously tested correspondence with pitch, the representation of depth employed an ecologically inspired manipulation, based on the loss of gain and filtration of higher frequency sounds over distance. The study, involving 40 participants, seven of which were blind (5) or visually impaired (2), investigates the intrinsicness of an ecologically inspired mapping of auditory cues for depth by comparing it to an interchanged condition where the mappings of the two axes are swapped. All participants successfully learned to use the algorithm following a very brief period of training, with the blind and visually impaired participants showing similar levels of success for learning to use the algorithm as did their sighted counterparts. A significant difference was found at baseline between the two conditions, indicating the intuitiveness of the original ecologically inspired mapping. Despite this, participants were able to achieve similar success rates following the training in both conditions. The findings indicate that both intrinsic and learned cues come into play with respect to depth perception. Moreover, they suggest that by employing perceptual learning, novel sensory mappings can be trained in adulthood. Regarding the blind and visually impaired, the results also support the convergence view, which claims that with training, their spatial abilities can converge with those of the sighted. Finally, we discuss how the algorithm can open new avenues for accessibility technologies, virtual reality, and other practical applications.

Emotional Overshadowing: Pleasant and Unpleasant Cues Overshadow Neutral Cues in Human Associative Learning.

The online version contains supplementary material available at 10.1007/s42761-024-00270-0.

The "what" and "when" of language input to children: Linguistic and temporal predictors of vocabulary in 3-year-olds.

The quantity, quality, and complexity of language input are important for children's language development. This study examined how the detailed timing of this input relates to children's vocabulary at 3 years of age in 64 mother-child dyads (male = 28; female = 36; White = 69%, Black = 31%). Acoustical analysis of turn taking in mother-child dialogue found that more consistently timed maternal responses (lower response latency variability) were associated (r = .42, p < .001) with higher vocabulary (Peabody Picture Vocabulary Test, third edition) scores. In mothers with consistently timed responses, the complexity (mean length of utterance) of their child-directed speech significantly predicted (r = .53, p = .002) their children's vocabulary. This suggests that predictably timed contingent maternal responses provide an important learning cue that supports language development beyond the content of language input itself. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The visual statistical learning overcomes scene dissimilarity through an independent clustering process.

Contextual cueing is a phenomenon of visual statistical learning observed in visual search tasks. Previous research has found that the degree of deviation of items from its centroid, known as variability, determines the extent of generalization for that repeated scene. Introducing variability increases dissimilarity between multiple occurrences of the same repeated layout significantly. However, current theories do not explain the mechanisms that help to overcome this dissimilarity during contextual cue learning. We propose that the cognitive system initially abstracts specific scenes into scene layouts through an automatic clustering unrelated to specific repeated scenes, and subsequently uses these abstracted scene layouts for contextual cue learning. Experiment 1 indicates that introducing greater variability in search scenes leads to a hindering in the contextual cue learning. Experiment 2 further establishes that conducting extensive visual searches involving spatial variability in entirely novel scenes facilitates subsequent contextual cue learning involving corresponding scene variability, confirming that learning clustering knowledge precedes the contextual cue learning and is independent of specific repeated scenes. Overall, this study demonstrates the existence of multiple levels of learning in visual statistical learning, where item-level learning can serve as material for layout-level learning, and the generalization reflects the constraining role of item-level knowledge on layout-level knowledge.

Spatially organized striatum-wide acetylcholine dynamics for the learning and extinction of Pavlovian cues and actions.

Striatal acetylcholine (ACh) has been linked to behavioral flexibility. A key component of flexibility is down-regulating responding as valued cues and actions become decoupled from positive outcomes. We used array fiber photometry in mice to investigate how ACh release across the striatum evolves during learning and extinction of Pavlovian associations. Changes in multi-phasic release to cues and consummatory actions were bi-directional and region-specific. Following extinction, increases in cue-evoked ACh release emerged in the anterior dorsal striatum (aDS) which preceded a down-regulation of anticipatory behavior. Silencing ACh release from cholinergic interneurons in the aDS blocked behavioral extinction. Dopamine release dipped below baseline for down-shifted cues, but glutamate input onto cholinergic interneurons did not change, suggesting an intrastriatal mechanism for the emergence of ACh increases. Our large-scale mapping of striatal ACh dynamics during learning pinpoints region-specific elevations in ACh release positioned to down-regulate behavior during extinction, a central feature of flexible behavior.

Cultural transmission and religious belief: An extended replication of Gervais and Najle (2015) using data from the International Social Survey Programme.

Beliefs in supernatural agents or religious beliefs are pervasive, yet there are individual differences in such beliefs. Although various factors have been proposed as relevant, recent research has increasingly emphasized the importance of cultural learning, showing that enthusiastic religious behavior (credibility enhancing displays; CREDs) from parents predicts increased religious beliefs among their children. In addition to this kin-biased learning, Gervais and Najle (2015) analyzed data from the World Values Survey to demonstrate that the number of adults who show religious CREDs is also an important predictor of people's beliefs, indicating that individuals develop their religious beliefs through conformist learning. This pre-registration study aimed to replicate and extend these findings by analyzing data from the International Social Survey Programme (ISSP), which is another large social survey. We examined the generalizability of the results by analyzing multigenerational samples. Multilevel regression and signal detection analyses revealed that the presence of both kin-biased and conformist learning cues was significantly associated with respondents' religious beliefs. Moreover, they suggested tension between the two cultural learning cues, thereby suggesting that the effect of kin-biased learning on religious beliefs becomes stronger (weaker) when the cue for conformist learning is unclear (clear). These results support the idea that these two types of cultural learning are crucial to the development of religious beliefs.

Self-Supervised Monocular Depth Estimation via Binocular Geometric Correlation Learning

Monocular depth estimation aims to infer a depth map from a single image. Although supervised learning-based methods have achieved remarkable performance, they generally rely on a large amount of labor-intensively annotated data. Self-supervised methods, on the other hand, do not require any annotation of ground-truth depth and have recently attracted increasing attention. In this work, we propose a self-supervised monocular depth estimation network via binocular geometric correlation learning. Specifically, considering the inter-view geometric correlation, a binocular cue prediction module is presented to generate the auxiliary vision cue for the self-supervised learning of monocular depth estimation. Then, to deal with the occlusion in depth estimation, an occlusion interference attenuated constraint is developed to guide the supervision of the network by inferring the occlusion region and producing paired occlusion masks. Experimental results on two popular benchmark datasets have demonstrated that the proposed network obtains competitive results compared to state-of-the-art self-supervised methods and achieves comparable results to some popular supervised methods.

Age-related contextual cueing features are more evident in reaction variability than in reaction time.

Visual-spatial contextual cueing learning underpins the daily lives of older adults, enabling them to navigate their surroundings, perform daily activities, and maintain cognitive function. While the contextual cueing effect has received increasing attention from researchers, the relationship between this cognitive ability and healthy ageing remains controversial. To investigate whether visual-spatial contextual cueing learning declines with age, we examined the contextual learning patterns of older (60-71 years old) and younger adults (18-26 years old) using a contextual-guided visual search paradigm and response variability measurements. We observed significant contextual learning effects in both age groups, impacting response speed and variability, with these effects persisting for at least 24 days. However, older adults required more repetitions and memorised fewer repeated stimuli during initial learning. Interestingly, their long-term memory maintenance appeared stronger, as their contextual facilitation persisted in both response speed and variability, while younger adults only persisted in response speed but not variability. Overall, our results suggest an age-related complex and diverse contextual cueing pattern, with older adults showing weaker learning but stronger long-term memory maintenance compared with younger adults.

Measuring the importance of olfaction in Chinese children: A psychometric study of the Chinese version of the Children's Personal Significance of Olfaction Questionnaire

AbstractThe Children's Personal Significance of Olfaction Questionnaire (ChiPSO) is a measurement tool for assessing the importance of olfactory information in children. Due to limited research on the importance of olfaction in Chinese children, this study aims to translate the ChiPSO into Chinese and validate this version, thereby examining its applicability within the Chinese context. The study involved 1015 participants aged 6–15 years, with confirmatory factor analysis (CFA) used to evaluate the questionnaire's factor structure, alongside tests for internal consistency, test–retest reliability, and concurrent validity. The results confirmed a robust three‐factor structure (food, environment, and social) with adequate internal consistency and test–retest reliability. Furthermore, concurrent validity was confirmed through significant correlations with the Chemosensory Pleasure Scale for Children and the Body Odor Sniffing Questionnaire. In conclusion, this study effectively validated the ChiPSO‐C, proving it to be a reliable instrument for investigating olfactory significance in Chinese children.Practical ApplicationThe Chinese version of the Children's Personal Significance of Olfaction offers a validated tool to assess the personal significance of olfaction in Chinese children. Researchers and educators can use this tool to better understand and support children who may rely more significantly on olfactory cues for learning and interaction. Furthermore, this tool facilitates cross‐cultural research by providing a means to compare olfactory significance across different cultural contexts.

Overburdening associations: The dependency of psychopathy-related acquisitional learning deficits on processing load

Psychopathic personality traits have been identified as an important predictor of associative learning capacity. Prior work has associated psychopathy with deficits when adapting learned associations in response to novel information. However, findings are inconsistent and are hypothesised to vary as a function of the processing load created by different experimental paradigms. We tested this hypothesis by examining the association between psychopathic traits and Stimulus-Response-Outcome contingency learning whilst manipulating contextual processing load. In experiments one and two, participants completed three versions of a configural object discrimination task that required participants to use increasingly multidimensional learning cues. Across both experiments, it was found that elevated levels of psychopathic traits were associated with a lesser capacity to form S-R-O associations in the bidimensional but not tridimensional versions of the learning task. This suggests psychopathy-related learning deficits may vary as a function of the processing load inherent to the bidimensional learning environment, rather than the type of learning taking place. This provides some of the first experimental evidence that psychopathic learning deficits are detectable during the acquisition phase of learning.

The representation of contextual cue is stimulus-specific yet its expression is flexible.

Contextual cueing refers to the phenomenon in which individuals utilize frequently encountered environmental contexts, comprised of distractors, as cues to expedite a target search. Due to the conflict between the widespread occurrence of contextual cue transfer and the observed impact of changing the identity of distractors on contextual cue learning, the content of contextual cue representations remains contentious. Considering the independent nature of contextual cue learning and expression, our proposition is twofold: (1) Contextual cue representations are stimulus-specific, and (2) their expression is highly flexible. To validate the model, two experiments were conducted. Experiment 1 aimed to confirm the hypothesis that contextual cue representations are stimulus-specific. We manipulated the identity consistency of distractors within repeated scenes during contextual cue learning. Difficulty in contextual cue learning under the identity-changing condition would suggest the necessity of identity within contextual cue representation, indicating the stimulus-specific nature of these representations. Experiment 2 was designed to affirm the conclusion of Experiment 1 and explore the flexibility in the expression of contextual cue representations. This experiment comprised two phases: learning and testing. During the learning phase, participants were exposed to two sets of repeated scenes in different colors under two learning conditions: load and no-load. Working memory load was introduced to interfere with the expression to prevent it from becoming automatic. In the subsequent testing phase, the colors of the two scene sets were interchanged to impede retrieval based on identity. If both load and no-load conditions demonstrate similar levels of contextual cue effects during the testing phase, it implies the flexibility in the expression of contextual cue representations and confirms the conclusion of Experiment 1. In Experiment 1, a notable contextual cue learning effect was observed under the identity-consistent condition (p = 0.001). However, this effect was not evident under the identity-changing condition (p = 0.286). This finding strongly supports the stimulus-specific nature of contextual cue representation. In Experiment 2, the contextual cueing effect appeared but did not show a significant difference between the two conditions (t(23) = 0.02, p = 0.987, BF10 = 0.215), indicating the cognitive system's ability to flexibly redefine retrieval cues. This adaptability aligns with our hypothesis and confirms the high flexibility in the expression process of contextual cue representations and confirms the conclusion of Experiment 1.

Spatiotemporal feature learning for no-reference gaming content video quality assessment

Recently, over-the-top live gaming content video (GCV) services have significantly contributed to the overall internet traffic. Consequently, there is a growing demand of GCV quality assessment (GCVQA) to maintain service quality. Although recent literature has proposed a few GCVQA methods, these mainly focus on extracting spatial features and temporal fusion separately, limiting their performance due to the neglect of spatiotemporal feature learning, which is crucial for GCV as it typically shares spatial and temporal features across frames. To address this, we propose a novel GCVQA model, focusing on GCV spatiotemporal feature learning. First, we employ a multi-task self-supervised learning spatiotemporal pyramid convolutional neural network (STP-CNN) model to extract short-term spatiotemporal quality feature representations (STQFR) of GCVs. Our STP-CNN model specifically extracts multiscale spatiotemporal features from various temporal scales of multi-frames in pyramid mode, enabling dynamic learning of diverse spatiotemporal cues. Subsequently, we propose the differential Transformer model to process all short-term STQFR within a GCV, extracting global spatiotemporal features of GCV to assess the overall quality of GCV. To evaluate the effectiveness of our proposed method, we conducted experiments using four GCVQA datasets. The results demonstrate that our method outperforms existing approaches in predicting the perceived quality of GCV.

Examination of medical students' opinions on multimedia learning materials according to social cues: focusing on sound principles.

Although interest in various forms of learning media is increasing due to the coronavirus disease 2019 (COVID-19) pandemic there is relatively little research on influencing student motivation by intervening in cognitive processing. The purpose of this study was to present the optimal form of learning materials provided to medical students. This study provided learning materials in class at a level according to social cues (script, video [artificial intelligence (AI) voice], video [professor voice]) based on the principle of voices among the principles of personalization, voices, image, and embodiment of social cues in multimedia learning, and surveyed students' opinions. There was no statistically significant difference according to social clues in satisfaction and learning help, but both appeared in the order of silent videos containing the professor's voice, followed by videos containing the AI voice. This study is significant in that there is no research on the impact of student motivation on the provision of learning materials for medical school education in Korea, and we hope that it will help provide learning materials for self-directed learning of medical students in the post-COVID-19.

Fusion-GRU: A Deep Learning Model for Future Bounding Box Prediction of Traffic Agents in Risky Driving Videos

To ensure the safe and efficient navigation of autonomous vehicles and advanced driving assistance systems in complex traffic scenarios, predicting the future bounding boxes of surrounding traffic agents is crucial. However, simultaneously predicting the future location and scale of target traffic agents from the egocentric view poses challenges because the vehicles’ egomotion causes considerable field-of-view changes. Moreover, in anomalous or risky situations, tracking loss or abrupt motion changes limit the available observation time, requiring learning of cues within a short time window. Existing methods typically use a simple concatenation operation to combine different cues, overlooking their dynamics over time. To address this, this paper introduces the Fusion-Gated Recurrent Unit (Fusion-GRU) network, a novel encoder-decoder architecture for future bounding box localization. Unlike traditional gated recurrent units (GRUs), Fusion-GRU accounts for mutual and complex interactions among input features. Moreover, an intermediary estimator coupled with a self-attention aggregation layer is also introduced to learn sequential dependencies for long-range prediction. Finally, a GRU decoder is employed to predict the future bounding boxes. The proposed method is evaluated on two publicly available datasets, Risky Object Localization and Honda Egocentric Vehicle Intersection. The experimental results showcase the promising performance of the Fusion-GRU, demonstrating its effectiveness in predicting future bounding boxes of traffic agents.

No evidence that recruitment pheromone modulates olfactory, visual, or spatial learning in the ant Lasius niger

Pheromones are perhaps the most common form of intraspecific communication in the animal kingdom and used in various contexts. Their modulatory potential on cognitive processes has been demonstrated in both vertebrates and invertebrates. Particularly interesting in this regard are social insects, due to their extensive use of pheromones to organise collective behaviour. Recruitment pheromones might be expected to encourage learning, but could also hinder learning due to a blocking effect, whereby the pheromone already partially predicts the reward, hindering further cues being associated with the reward. Here, we use free-running learning assays using realistic pheromone strength to test for a modulation effect on learning in the black garden ant Lasius niger. We found no evidence that learning in three modalities (olfactory, visual, and spatial) is affected by the presence of a realistic pheromone trail. Interestingly, this is in contrast to findings in honeybees. The fact that associative learning does not seem to be influenced by recruitment pheromone in L. niger and reportedly the Argentine ant, while it is in honeybees, the possibly best-studied social insect species, is noteworthy. We speculate that a species-specific importance of social information use could drive modulatory effects of pheromones on a wide range of cognitive processes.Significance statementPheromones have been shown to modulate associative learning in a variety of animals. Among social insects, attractive pheromone has been found to enhance associative olfactory learning in honeybees but not in ants. In ants, recruitment pheromone predicts a food source; therefore, it might hinder learning of a new cue for a food reward. We use a free-running learning assay to test for an effect of trail pheromone on associative learning in three different modalities—olfactory, spatial, visual—in Lasius niger, but find no evidence of any effect. Our learning assay demonstrated fast olfactory learning, moderate spatial learning, and no visual learning after only one training visit. Based on our findings, and findings in two other ant species, we speculate that the ecological foraging conditions of mass-recruiting ants, i.e. following a trail, have not favoured a modulation potential of recruitment pheromone opposed to attractive pheromone in honeybees.

Modulation of learning safety signals by acute stress: paraventricular thalamus and prefrontal inhibition

Distinguishing between cues predicting safety and danger is crucial for survival. Impaired learning of safety cues is a central characteristic of anxiety-related disorders. Despite recent advances in dissecting the neural circuitry underlying the formation and extinction of conditioned fear, the neuronal basis mediating safety learning remains elusive. Here, we showed that safety learning reduces the responses of paraventricular thalamus (PVT) neurons to safety cues, while activation of these neurons controls both the formation and expression of safety memory. Additionally, the PVT preferentially activates prefrontal cortex somatostatin interneurons (SOM-INs), which subsequently inhibit parvalbumin interneurons (PV-INs) to modulate safety memory. Importantly, we demonstrate that acute stress impairs the expression of safety learning, and this impairment can be mitigated when the PVT is inhibited, indicating PVT mediates the stress effect. Altogether, our findings provide insights into the mechanism by which acute stress modulates safety learning.

Human-Centric Transformer for Domain Adaptive Action Recognition.

We study the domain adaptation task for action recognition, namely domain adaptive action recognition, which aims to effectively transfer action recognition power from a label-sufficient source domain to a label-free target domain. Since actions are performed by humans, it is crucial to exploit human cues in videos when recognizing actions across domains. However, existing methods are prone to losing human cues but prefer to exploit the correlation between non-human contexts and associated actions for recognition, and the contexts of interest agnostic to actions would reduce recognition performance in the target domain. To overcome this problem, we focus on uncovering human-centric action cues for domain adaptive action recognition, and our conception is to investigate two aspects of human-centric action cues, namely human cues and human-context interaction cues. Accordingly, our proposed Human-Centric Transformer (HCTransformer) develops a decoupled human-centric learning paradigm to explicitly concentrate on human-centric action cues in domain-variant video feature learning. Our HCTransformer first conducts human-aware temporal modeling by a human encoder, aiming to avoid a loss of human cues during domain-invariant video feature learning. Then, by a Transformer-like architecture, HCTransformer exploits domain-invariant and action-correlated contexts by a context encoder, and further models domain-invariant interaction between humans and action-correlated contexts. We conduct extensive experiments on three benchmarks, namely UCF-HMDB, Kinetics-NecDrone and EPIC-Kitchens-UDA, and the state-of-the-art performance demonstrates the effectiveness of our proposed HCTransformer.

The effect of cue length and position on noticing and learning of determiner agreement pairings: Evidence from a cue-balanced artificial vocabulary learning task.

The importance of cues in language learning has long been established and it is clear that cues are an essential part of both first language (L1) and second/additional language (L2/A) acquisition. The effects of cue reliability and frequency, along with the competition between cues have been shown to significantly impact learners' pace of acquisition of these language-specific patterns. However, natural languages do not allow for a clear picture of how the forms of cues themselves affect their perception, uptake, and generalizability. In this study, we developed an artificial vocabulary consisting of determiners and nouns. Within these nouns, completely reliable cues were developed and equally distributed as long and short cues over three possible positions: beginning, middle, or end. Through a word-pair learning study, we show that length and position of cues variably affects agreement accuracy, and that noticing of cues during training is less important for known words, and more important for novel ones when deciding on inter-word gender-like agreement.