Associative Learning Research Articles

Effects of anisometropic amblyopia on visual cognitive functions in children.

To investigate visual cognitive functions, including visual attention, executive function, and visual working memory, in children with anisometropic amblyopia versus those with normal vision. Thirty-five children with anisometropic amblyopia and 34 with normal vision participated. Visual acuity, stereoacuity, and contrast sensitivity were measured, followed by the Cambridge Neuropsychological Test Automated Battery's six subtests for cognitive evaluation. Visual attention was assessed using reaction time (RTI) and rapid visual information processing (RVP). Executive function was evaluated through the multitasking test (MTT). Visual working memory was assessed with spatial working memory (SWM), delayed matching to sample (DMS), and paired association learning (PAL), all under binocular conditions. The amblyopia group exhibited longer reaction and movement times in the RTI than the control group (p < 0.01). A trend towards lower RVP A' scores, reflecting reduced ability to detect target sequences, appeared in the amblyopia group (p = 0.056). Amblyopic children demonstrated a lower multitasking cost in the MTT compared with the control group (p = 0.04). As difficulty increased in the SWM (from four to six boxes), amblyopic children revisited more (p = 0.01). In the DMS task, while no differences were observed across all delay times (p = 0.55), amblyopic children performed significantly worse than the control group under the 12-second delay (p = 0.04). In the eight-pattern PAL condition, the amblyopia group made more errors (p = 0.01). Children with anisometropic amblyopia performed poorly on neuropsychological tests, particularly visual attention and working memory, but outperformed the control group in multitasking. These findings highlight the broader cognitive impacts of anisometropic amblyopia beyond vision.

Effects of experience and familiarity on visual attention and behaviours of bottlenose dolphins (Tursiops truncatus) in presence of humans

Visual attention is an intrinsic part of intra- and inter-specific interactions. Its structure (e.g. short glances vs. long gazes) depends on the species, type and expected outcome of the interaction. The outcomes of earlier repeated interactions determine the resulting valence of the relationships. Human-animal relationships rely upon species-specific cognitive abilities and attentional characteristics for associative learning and memory formation. Visual attention is crucial in cognitive processing and relationships construction, but its structure may depend on species-specific characteristics and relationships’ quality. Dolphins are renowned for their cognitive abilities and in human-care settings they have regular interactions with caretakers. Dolphins’ visual attention structure and laterality both differ depending on the visual stimulus to which the animal is attending (species-specific, non-biological). We hypothesized that visual attentional characteristics and associated behaviours, in a group of 9 captive bottlenose dolphins (Tursiops truncatus), would differ according to past experience and familiarity with humans. Human motionless tests showed a role of experience (time spent) in the facility on play and vocal production near humans regardless of familiarity. However, familiarity influenced dolphin presence near humans and visual laterality: they stayed longer and used their right eye more to glance at familiar humans. These findings provide new insights on how dolphins cognitively process stimuli according to familiarity and past experiences, as well as on how human – animal relationships evolve in captive settings.

Optically Modulated Nanofluidic Ionic Transistor for Neuromorphic Functions

Neuromorphic systems that can emulate the behavior of neurons have garnered increasing interest across interdisciplinary fields due to their potential applications in neuromorphic computing, artificial intelligence and brain‐machine interfaces. However, the optical modulation of nanofluidic ion transport for neuromorphic functions has been scarcely reported. Herein, inspired by biological systems that rely on ions as signal carriers for information perception and processing, we present a nanofluidic transistor based on a metal‐organic framework membrane (MOFM) with optically modulated ion transport properties, which can mimic the functions of biological synapses. Through the dynamic modulation of synaptic weight, we successfully replicate intricate learning‐experience behaviors and Pavlovian associate learning processes by employing sequential optical stimuli. Additionally, we demonstrate the application of the International Morse Code with the nanofluidic device using patterned optical pulse signals, showing its encoding and decoding capabilities in information processing process. This study would largely advance the development of nanofluidic neuromorphic devices for biomimetic iontronics integrated with sensing, memory and computing functions.

A cognitive computing approach for product configuration design based on associative rule mining and deep reinforcement learning

Product configuration design is instrumental in combining available configurable components to rapidly generate new products that align with customised requirements, aiding manufacturing enterprises in enhancing production efficiency and reducing development costs. Nevertheless, traditional methods remain inadequate for effectively leveraging historical configuration knowledge and rapidly generating new configuration design schemes devoid of established references. Inspired by the combined effects of the associative learning of the cerebellum and the reward modulation learning of the basal ganglia on goal-oriented behaviours, this paper proposes a cognitive computing method for product configuration design based on associative rule mining and deep reinforcement learning. For one thing, the benchmark learning-based association rule mining method, which simulates the cerebellum's function, automatically extracts configuration design knowledge that connects customer requirements with module instances, thereby promoting the end-to-end reusing of historical configuration design solutions. For another, the improved deep Q-network is proposed to mimic the function of the basal ganglia, which is employed to generate new configuration design schemes in the absence of historical precedents. A case study on the configuration design of the essential service water system of a nuclear power plant is implemented to demonstrate the reliability and reasonability of the proposed approach.

Dynamic Changes in Chloride Homeostasis Coordinate Midbrain Inhibitory Network Activity during Reward Learning.

The ability to associate environmental stimuli with positive outcomes is a fundamental form of learning. While extensive research has focused on the response profiles of midbrain dopamine neurons during associative learning, less is known about learning-mediated changes in the afferents that shape their responses. We demonstrate that during critical phases of learning, anion homeostasis in midbrain GABA neurons - a primary source of input to dopamine neurons - is disrupted due to downregulation of the chloride transporter KCC2. This alteration in GABA neurons preferentially impacted lateral mesoaccumbal dopamine pathways and was not observed after learning was established. At the network level, learning-mediated KCC2 downregulation was associated with enhanced synchronization between individual GABA neurons and increased dopamine responses to reward-related stimuli. Conversely, enhancing KCC2 function during learning reduced GABA synchronization, diminished relevant dopamine signaling, and prevented cue-reward associations. Thus, circuit-specific adaptations in midbrain GABA neurons are crucial for forming new reward-related behaviors.

Multi-Label Feature Selection with Feature-Label Subgraph Association and Graph Representation Learning.

In multi-label data, a sample is associated with multiple labels at the same time, and the computational complexity is manifested in the high-dimensional feature space as well as the interdependence and unbalanced distribution of labels, which leads to challenges regarding feature selection. As a result, a multi-label feature selection method based on feature-label subgraph association with graph representation learning (SAGRL) is proposed to represent the complex correlations of features and labels, especially the relationships between features and labels. Specifically, features and labels are mapped to nodes in the graph structure, and the connections between nodes are established to form feature and label sets, respectively, which increase intra-class correlation and decrease inter-class correlation. Further, feature-label subgraphs are constructed by feature and label sets to provide abundant feature combinations. The relationship between each subgraph is adjusted by graph representation learning, the crucial features in different label sets are selected, and the optimal feature subset is obtained by ranking. Experimental studies on 11 datasets show the superior performance of the proposed method with six evaluation metrics over some state-of-the-art multi-label feature selection methods.

Orbitofrontal control of the olfactory cortex regulates olfactory discrimination learning.

Serving as an integral node for cognitive processing and value-based decision-making, the orbitofrontal cortex (OFC) plays a multifaceted role in associative learning and reward-driven behaviours through its widespread synaptic integration with both subcortical structures and sensory cortices. Despite the OFC's robust innervation of the olfactory cortex, the functional implications and underlying mechanisms of this top-down influence remain largely unexplored. In this study, we demonstrated that the OFC formed both direct excitatory and indirect inhibitory synaptic connections with pyramidal neurons in the anterior piriform cortex (aPC). OFC projection predominantly regulated spontaneous and odour-evoked excitatory activity in the aPC of awake mice. Importantly, suppression of this OFC-aPC projection disrupted olfactory discrimination learning, potentially due to a consequent decrease in the excitability of aPC principal output neurons following inhibition of this projection. Whole-cell recordings revealed that olfactory learning increased the intrinsic excitability of aPC neurons while concurrently decreasing OFC input to these neurons. These findings underscore the pivotal influence of orbitofrontal modulation over the olfactory cortex in the context of olfactory learning and provide insight into the associated neurophysiological mechanisms. KEY POINTS: The orbitofrontal cortex (OFC) densely innervates the anterior piriform cortex (aPC) through direct excitatory synaptic connections. The OFC regulates both spontaneous and odour-evoked excitatory activities in the aPC of awake mice. Inhibition of OFC projections disrupts olfactory discrimination learning, probably due to reduced excitability of aPC main output neurons. Following olfactory learning, the intrinsic excitability of aPC neurons increases while the OFC-aPC input decreases, highlighting the importance of adaptable OFC input for olfactory learning. These results provide new perspectives on how the OFC's top-down control modulates sensory integration and associative learning.

Insights of BDAPbI4-Based Flexible Memristor for Artificial Synapses and In-Memory Computing.

Inspired by brain-like spiking computational frameworks, neuromorphic computing-brain-inspired computing for machine intelligence promises to realize artificial intelligence (AI) while reducing the energy requirements of computing platforms. In this work, we show the potential of advanced learnings of butane-1,4-diammonium based low-dimensional Dion-Jacobson hybrid perovskite (BDAPbI4) memristor devices in the realm of artificial synapses and neuromorphic computing. Memristors validate Hebbian learning rules with various spike-dependent plasticity within a 10 ± 2 ms time frame, reminiscent of the human brains under flat and bending conditions (∼5 mm radium). A high recognition accuracy of ∼94% of handwritten images from the MNIST database via an artificial neural network (ANN) is achieved with only 50 epochs. An efficient demonstration of second-order memristors and the Pavlovian dog experiment exhibit significant promise in expediting learning and memory consolidation. To showcase the in-memory computing potential, a flexible 4 × 4 crossbar array is designed with measured data retention up to ∼103 s along with 26 multilevel resistance states. The crossbar array is successfully programmed for the facile configurability of image "Z". In conclusion, the integration of supervised, unsupervised, and associative learning holds great promise across a spectrum of future technologies, ranging from the realm of spiking neural networks to neuromorphic computing, brain-machine interfaces, and adaptive control systems.

Conductive Islands Assisted Resistive Switching in Biomimetic Artificial Synapse for Associative Learning and Image Recognition

AbstractSolution‐processed memristor devices hold significant potential for advancing synaptic applications, offering scalable, cost‐effective, and efficient solutions for next‐generation neuromorphic systems. These devices replicate the behavior of biological synapses with their gradual and continuous changes in resistance, making them promising for neuromorphic computing and artificial neural networks. However, understanding the temporal characteristics and cumulative effect of successive pulses on the devices is essential for emulating the dynamics of biological synapses. This study proposes a hybrid materials‐based conductive islands‐assisted resistive switching (CIARS) in a solution‐processed active layer consisting of thermally exfoliated graphitic carbon nitride (g‐C3N4 abbreviated as CN) nanosheets embedded with silver nanoparticles (Ag NPs). The fabricated devices demonstrate repeatable and bipolar memory features with a lower operating voltage (≤0.5 V), emulating the frequency and amplitude‐dependent synaptic plasticities. The threshold switching occurs due to the formation of conduction filaments (CFs) of silver ion (Ag+), whereas the analog behavior results from the voltage pulse‐dependent modulation of Schottky barrier height combined with metallic CFs formation. The experimental findings demonstrate the efficacy of the CIARS mechanism within the material platform, highlighting its potential for applications in associative learning, Morse code detection, and image recognition.

Beyond the information (not) given: Associative mechanisms versus representations of uncertainty in extinction in laboratory rats (Rattus norvegicus).

Associative learning models typically reflect statistical relationships between experienced events. Causal models can go beyond this information to specify the ways in which events are related. This meta-representational aspect of causal models allows them to reflect uncertainty about relationships between events: for example, if a light initially leads to sucrose but subsequently the light is experienced without sucrose, this might first support formation of a light-causes-sucrose model and subsequently lead to uncertainty over whether the model remained accurate. Prior studies of Pavlovian conditioning in rats manipulated sucrose-magazine access during extinction to produce uncertainty about reward presence or absence. Rats were sensitive to covering of the site of reward delivery, which was interpreted as evidence for a causal-model account reflecting uncertainty. However, associative accounts-based on the direct impact of the dipper mechanism used to deliver sucrose through secondary reinforcement or contextual renewal of responding-can also explain the results. In two new experiments, manipulation of the dipper mechanism through extinction and test phases resulted in behavior consistent with these associative accounts. However, demonstration of the importance of the sucrose dipper suggests that the reward delivery mechanism should be included in a causal model. Such a revised causal model also provides an account of the impact of manipulating the sucrose dipper. While these experiments do not conclusively decide between associative and causal models as explanations of rodent behavior, they do illustrate the value of incremental experimental study and the importance of methodological detail in addressing questions of comparative cognition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

DArc1 controls sugar reward valuation in Drosophila melanogaster.

The Arc genes - which include Drosophila Arc1 and Arc2 ( dArc ) - evolved from Ty3 retrotransposons and encode proteins that form virus-like capsids. These capsids enable a novel form of intercellular communication by transferring RNAs between cells. However, the specific neuronal circuits and brain processes Arc intercellular signaling regulates remain unknown. Here, we show that loss of both dArc genes in Drosophila melanogaster enhances associative learning in an appetitive conditioning paradigm, where flies associate an odor with sugar rewards. This increased learning performance arises from an increased valuation of sugar rewards: unlike wild-type flies, dArc -/- flies form abnormally strong associations even when the sugar reward is small or has no caloric value. We found that the γ5-dopaminergic neurons of the protocerebral anterior medial (PAM) cluster, which encode the positive valence of sugar rewards, show heightened activity in response to sucrose in dArc -/- flies. We further show that the learning phenotype of dArc -/- flies depends on the formation of capsids, underscoring a direct role for capsid-mediated Arc signaling in sugar valuation. Our findings establish dArc genes as critical regulators of reward valuation in D. melanogaster , acting through a non-cell autonomous mechanism that relies on capsid-mediated communication between cells.

Emotional stimuli boost incidental learning through predictive processing.

Extracting regularities and probabilities from the environment is a fundamental and critical ability in an ever-changing surrounding. Previous findings showed that people are highly efficient in learning these regularities and that emotional stimuli are better learned than neutral ones. Yet, the generality and the underlying mechanism of this benefit are poorly understood. Here, participants viewed a stream of images with negative and neutral valence. Unbeknownst, the items recurred in regularity as triplets. Then, to assess learning, a surprised familiarity test was conducted. The results of Experiment 1, using two sets of stimuli, found better statistical learning for negative triplets than for neutral triplets. Experiment 2 revealed similar benefits even when only a single negative item was in the triplet at the second or third position, suggesting the advantage is not cumulative. We speculated that the predictability of the negative items is driving the effect. Consequently, Experiment 3 confirmed that the memory for neutral items preceding negative items was better than for neutral items preceding neutral items. Together, these findings provide novel insights into the mechanism of how the learning of incidental temporal associations is influenced by negative stimuli and the role of predictability in the negative valence benefit.

Mitigation measures for pinniped-fisheries interactions based on knowledge of animal behavior

Abstract A rise in pinniped-fisheries interactions has been observed due to the global decline in fish populations primarily attributed to overfishing, and/or due to the recent population recovery of several pinniped species. Although many studies have quantified these interactions, a limited number delve into their behavioral aspects. We consulted 374 studies on pinniped-fisheries interactions from 1980 to 2020 and analyzed which of them addressed the interaction from a behavioral perspective. Additionally, we examined the role of learning in pinnipeds and their ability to capture prey from fishing gear. The stimulus-reward relationship in operational interactions was addressed in 51 (14%) studies, involving 10 (19%) of the world’s 54 pinniped species or subspecies. Depredation behavior (43%) and attack behavior (35%) were frequently reported during fishing interactions. Understanding associative and non-associative learning mechanisms has the potential to reduce economic losses from fishing activity, advance efficient mitigation measures to minimize conflicts, and establish pragmatic conservation priorities based on a better understanding of the behavioral aspects of these interactions. More research is needed to explore the effectiveness of deterrents in different species, improve methods of reducing habituation, and evaluate long-term behavioral effects, fostering effective strategies for minimizing conflicts and promoting coexistence between humans and pinnipeds.

Evidence for a general cognitive structure in pigeons (Columba livia)

A well replicated result in humans is that performance, whether good or bad, is consistent across a wide variety of cognitive tasks. Factor analysis extracts one factor that can account for approximately half of the variance in performance. This factor is termed g and almost all cognitive tasks positively load onto this factor. While some neurobiological correlates of g have been identified in humans, causal experiments are only feasible in animals. When mice and some avian species are assessed with cognitive test batteries, performance positively correlates, and the first component extracted has similar properties to g. There are some limitations to the species tested thus far, including comparability in the cognitive domains assessed. The pigeon is an ideal subject to overcome these issues since pigeons, humans, and other primates are frequently given similar tasks and many neural correlates of performance have been identified in the pigeon. We created a test battery that assessed different domains, including associative learning, memory, cognitive flexibility, and reaction time. When all tasks were included, there was evidence for a two-component structure that was influenced by subjects’ age. When the reaction time task was excluded, there was a g-like component. The implications for these results when constructing future test batteries and comparing across species are discussed.

Dopamine release in striatal striosome compartments in response to rewards and aversive outcomes during classical conditioning in mice

The striatum consists of two anatomically and neurochemically distinct compartments, striosomes and the matrix, which receive dopaminergic inputs from the midbrain and exhibit distinct dopamine release dynamics in acute brain slices. Striosomes comprise approximately 15 % of the striatum by volume and are distributed mosaically. Therefore, it is difficult to selectively record dopamine dynamics in striosomes using traditional neurochemical measurements in behaving animals, and it is unclear whether distinct dynamics play a role in associative learning. In this study, we used transgenic mice selectively expressing Cre in striosomal neurons, combined with a fiber photometry technique, to selectively record dopamine release in striosomes during classical conditioning. Water-restricted mice could distinguish the conditioned stimulus (CS) associated with saccharin water from the air-puff-associated CS. The air-puff-associated CS evoked phasic dopamine release only in striosomes. Furthermore, air puff presentation induced dopamine release to striosomal neurons but suppressed release to striatal neurons non-selectively recorded. These findings suggest that dopamine is released in a differential manner in striosomes and the matrix in behaving animals and that dopamine release in striosomes is preferentially induced by the air-puff-associated CS and air puff presentation. These findings support the hypothesis that striosomal neurons play a dominant role in aversive stimuli prediction.

Behavioral and neural correlates of diverse conditioned fear responses in male and female rats

Pavlovian fear conditioning is a widely used tool that models associative learning in rodents. For decades the field has used predominantly male rodents and focused on a sole conditioned fear response: freezing. However, recent work from our lab and others has identified darting as a female-biased conditioned response, characterized by an escape-like movement across a fear conditioning chamber. It is also accompanied by a behavioral phenotype: Darters reliably show decreased freezing compared to Non-darters and males and reach higher velocities in response to the foot shock (“shock response”). However, the relationship between shock response and conditioned darting is not known. This study investigated if this link is due to differences in general processing of aversive stimuli between Darters, Non-darters and males. Across a variety of modalities, including corticosterone measures, the acoustic startle test, and sensitivity to thermal pain, Darters were found not to be more reactive or sensitive to aversive stimuli, and, in some cases, they appear less reactive to Non-darters and males. Analyses of cFos activity in regions involved in pain and fear processing following fear conditioning identified discrete patterns of expression among Darters, Non-darters, and males exposed to low and high intensity foot shocks. The results from these studies further our understanding of the differences between Darters, Non-darters and males and highlight the importance of studying individual differences in fear conditioning as indicators of fear state.

The Memory Abilities of the Elderly Horse.

Studies on short- and long-term memory and their decline with aging in horses are still limited. This research aimed to assess the learning and short- and long-term memory abilities of adult and senior horses. A total of 21 adult horses (5-15 years) and 23 senior horses (16 years and older) were subjected to a behavioral test (Target Touch Test), which was repeated three times each for the initial test (T1) and again after 10 days (T10). Statistical analysis revealed no significant differences between adult and senior horses in the three tests conducted at T1. However, a significant difference was observed at T10 (χ2 = 42.1; p < 0.001). In fact, senior horses took longer to complete the test than adults. A significant difference between males and females, adults and seniors, at T1 and T10 (χ2 = 56.3; p < 0.001) was found, but no difference between male and female adult and senior horses in completing the three single tests at T1 and T10 was evidenced. In conclusion, even senior horses are capable of associative learning, maintaining the memory of this learning even after 10 days. However, they show slower recovery times for recalling memorized information compared to animals under 16 years of age.

Leveraging how animals learn in conservation science: Behavioral responses of reintroduced bison to management interventions

AbstractReintroduction programs have increased amid unprecedented biodiversity loss, yet the success of these programs lag. A prominent reason for program failure is dispersal beyond the planned range of the population. Management techniques, such as hazing, can be used to prevent movement beyond set boundaries, but to be effective long‐term, the animals must learn to avoid the areas where they are hazed. Although concepts of animal learning have been used to improve reintroduction programs, learning is not often explicitly tested or used as an indicator of program success. We used a conservation behavior framework to evaluate how a range of management techniques influenced learning in a reintroduced population of bison in Banff National Park, Canada. We hypothesized exposure to stronger negative stimuli would enhance learning, leading to more pronounced behavioral responses. Specifically, we tested the degree to which management actions (i.e., drift fence encounters, foot, horseback, helicopter, and combined hazing) elicited behavioral responses and how they facilitated learning. Consistent with our predictions, drift fence interactions and foot and horseback hazing elicited fewer behavioral responses of a smaller magnitude than helicopter hazing or combined methods, suggesting these techniques cause less disturbance to the bison. Bison continually returned to locations where they encountered management actions that caused the least disturbance, demonstrating a lack of associative learning. Bison appeared to form negative associations with locations where they were hazed via helicopter or combined methods, however, and rarely returned to these locations. Evaluating management techniques is essential for improving conservation success. We demonstrate that by bridging the fields of conservation biology and animal learning, we can understand how management techniques influence learning and behavior thereby facilitating effective conservation plans that incorporate disruption levels of the animals, financial costs, and overall effectiveness. Effective conservation plans, in turn, improve our likelihood of successfully managing and recovering species.

Long-term memory in &lt;i&gt;Thrips tabaci&lt;/i&gt; (Thysanoptera, Thripidae)

Microinsects are capable of associative learning and memory retention despite significant reduction in the number and size of neurons. Previously, the capabilities of Thrips tabaci (Thysanoptera, Thripidae) for associative learning and the formation of short-term memory have been demonstrated. In this study, an additional training session was added, as well as a time interval between them. Increasing the number of training sessions and spacing these out over time allowed us to demonstrate the persistence of memory traces for up to 24 hours. Thus, for the first time, the presence of consolidated forms of memory in the order Thysanoptera has been revealed.

Complexity and accuracy of verbal morphology in written L2 Italian

Abstract The present study aims to verify previous findings on the role of proficiency in the degree of complexity and accuracy of verbal morphemes in written essays from intermediate and advanced L2 Italian learners. In addition, by taking the perspective of usage-based theories on the distributional properties in the input, it investigates the extent to which contingency affects morphological complexity and accuracy by the emergence of cue-outcome associations. Hypotheses on the effects of contingency and proficiency on complexity and accuracy, and on their mutual relationships, are verified by adopting a confirmatory approach and by using Structural equation modeling. Results support the claims for non-universal mechanisms in the acquisition of verbal morphology: proficiency does not affect the morphological complexity of learner texts in the same way in inflectionally rich and poor languages, and the cue-outcome mechanisms of associative learning work to different extents depending on the inflectional systems of the target languages.