Animal Learning Research Articles

The forgotten adaptive social benefits of social learning in animals.

Theoretical and empirical scholars of cultural evolution have traditionally studied social learning strategies, such as conformity, as adaptive strategies to obtain accurate information about the environment, whereas within social psychology there has been a greater focus upon the social consequences of such strategies. Although these two approaches are often used in concert when studying human social learning, we believe the potential social benefits of conformity, and of social learning more broadly, have been overlooked in studies of non-humans. We review evidence from studies of homophily, imitation, and rapid facial mimicry that suggests that behaving like others affords social benefits to non-human animals and that behaviour matching may be deployed strategically to increase affiliation. Furthermore, we review studies of conformity in dispersers, and suggest that forgoing personal information or preferences in favour of those of the new group during immigration may be a strategy to facilitate social integration. We therefore propose that the informational and social functions of conformity apply to humans and animals alike. We use this perspective to generate several interesting research questions to inspire work in this field. For example, under what conditions do animals use informational or social conformity and what role does uncertainty play in social learning in immigrant individuals?

Performance errors during rodent learning reflect a dynamic choice strategy

Humans, even as infants, use cognitive strategies, such as exploration and hypothesis testing, to learn about causal interactions in the environment. In animal learning studies, however, it is challenging to disentangle higher-order behavioral strategies from errors arising from imperfect task knowledge or inherent biases. Here, we trained head-fixed mice on a wheel-based auditory two-choice task and exploited the intra- and inter-animal variability to understand the drivers of errors during learning. During learning, performance errors are dominated by a choice bias, which, despite appearing maladaptive, reflects a dynamic strategy. Early in learning, mice develop an internal model of the task contingencies such that violating their expectation of reward on correct trials (by using short blocks of non-rewarded "probe" trials) leads to an abrupt shift in strategy. During the probe block, mice behave more accurately with less bias, thereby using their learned stimulus-action knowledge to test whether the outcome contingencies have changed. Despite having this knowledge, mice continued to exhibit a strong choice bias during reinforced trials. This choice bias operates on a timescale of tens to hundreds of trials with a dynamic structure, shifting between left, right, and unbiased epochs. Biased epochs also coincided with faster motor kinematics. Although bias decreased across learning, expert mice continued to exhibit short bouts of biased choices interspersed with longer bouts of unbiased choices and higher performance. These findings collectively suggest that during learning, rodents actively probe their environment in a structured manner to refine their decision-making and maintain long-term flexibility.

Emergent neural dynamics and geometry for generalization in a transitive inference task.

Relational cognition-the ability to infer relationships that generalize to novel combinations of objects-is fundamental to human and animal intelligence. Despite this importance, it remains unclear how relational cognition is implemented in the brain due in part to a lack of hypotheses and predictions at the levels of collective neural activity and behavior. Here we discovered, analyzed, and experimentally tested neural networks (NNs) that perform transitive inference (TI), a classic relational task (if A > B and B > C, then A > C). We found NNs that (i) generalized perfectly, despite lacking overt transitive structure prior to training, (ii) generalized when the task required working memory (WM), a capacity thought to be essential to inference in the brain, (iii) emergently expressed behaviors long observed in living subjects, in addition to a novel order-dependent behavior, and (iv) expressed different task solutions yielding alternative behavioral and neural predictions. Further, in a large-scale experiment, we found that human subjects performing WM-based TI showed behavior inconsistent with a class of NNs that characteristically expressed an intuitive task solution. These findings provide neural insights into a classical relational ability, with wider implications for how the brain realizes relational cognition.

Intelligence in animals, humans and machines: a heliocentric view of intelligence?

Intelligence in animals, humans and machines: a heliocentric view of intelligence?

Understanding the limits to animal cognition

The thriving field of comparative cognition examines the behaviour of diverse animals in cognitive terms. Comparative cognition research has primarily focused on the abilities of animals - what tasks they can do - rather than on the limits of their cognition - tasks that exceed an animal's cognitive abilities. We propose that understanding and identifying cognitive limits is as important as demonstrating the capacities of animal minds. Here, we identify challenges that have deterred the study of cognitive limits related to epistemic, practical and publication problems. The epistemic problem is concerned with how we can confidently infer a cognitive limit from null or negative results. The practical problem is how can we be certain our research has identified a cognitive limit rather than failures in tasks due to methodological or experimental design issues. The publication problem outlines the publication bias toward positive and exciting results over negative or null results in animal cognition. We propose solutions to these three challenges and examples of how to conduct research to confidently identify and confirm cognitive limits in animals. We believe a refocus on the cognitive limits of animals is the next step in the field of comparative cognition. Knowing the limits to the intelligence of different animals will aid us in appreciating the diversity of animal intelligence, and will resolve outstanding questions of how cognition evolves.

Distinct Hippocampal Oscillation Dynamics in Trace Eyeblink Conditioning Task for Retrieval and Consolidation of Associations.

Trace eyeblink conditioning (TEBC) has been widely used to study associative learning in both animals and humans. In this paradigm, conditioned responses (CRs) to conditioned stimuli (CS) serve as a measure for retrieving learned associations between the CS and the unconditioned stimuli (US) within a trial. Memory consolidation, that is, learning over time, can be quantified as an increase in the proportion of CRs across training sessions. However, how hippocampal oscillations differentiate between successful memory retrieval within a session and consolidation across TEBC training sessions remains unknown. To address this question, we recorded local field potentials (LFPs) from the rat dorsal hippocampus during TEBC and investigated hippocampal oscillation dynamics associated with these two functions. We show that transient broadband responses to the CS were correlated with memory consolidation, as indexed by an increase in CRs across TEBC sessions. In contrast, induced alpha (8-10 Hz) and beta (16-20 Hz) band responses were correlated with the successful retrieval of the CS-US association within a session, as indexed by the difference in trials with and without CR.

Avian architects: Technology, domestication, and animal minds in urban America.

In the mid-nineteenth century, the house sparrow (Passer domesticus) was introduced to the United States, quickly spreading across the country. For a brief period in the late nineteenth and early twentieth centuries, the observation of sparrow behavior was something of an urban pastime. Traits such as intelligence, reason, persistence, and craftsmanship were conferred onto sparrows by American urbanites. This paper argues that sparrow intelligence was often conflated with domestication: the ability of the birds to adapt to living alongside humans. Praise for the ingenuity of sparrows generally revolved around their nest building, particularly when such structures overcame the challenges posed by urban infrastructure and technology. Sparrows were far less praiseworthy when they caused electricity outages or contaminated water supplies. The sparrow in the United States demonstrates how the relationship between these anecdotes and their implications for animal minds was mediated by the technology and infrastructure of cities. Admirers of sparrows were not measuring the birds' mental capacity, but rather their ability to adapt to human habitations. Sparrows were only granted intelligence once they had demonstrated their ability to become domesticated.

“Belief” and Belief

AbstractOur interest in understanding belief stems partly from our being creatures who think. However, the term ‘belief’ is used to refer to many states: from the fully conscious rational state that partly constitutes knowledge to the fanciful states of alarm clocks. Which of the many ‘belief’ states must a theory of belief be answerable to? This is the scope question. I begin my answer with a reply to a recent argument that belief is invariably weak, i.e., that the evidential standards that are required for belief are low. Although one state we refer to using the term ‘belief’ fits this profile, other ‘belief’ states do not. Crucially, when ‘belief’ is heard in a weak sense, it attributes a state that only a rational creature can be in. I will use this observation as a starting point for an argument that the study of (our) belief should not be constrained by the requirement that the illuminated state be held in common with any non‐rational being. This lends support to the Transformative Theory of Rationality, according to which rationality does not merely add powers or complexity to the animal mind, but transforms it into a different kind of mind altogether.

Exercise Alleviates Fluoride-Induced Learning and Memory Impairment in Mice: Role of miR-206-3p and PREG.

Fluorosis decreases the learning and memory ability in humans and animals, while exercise can reduce the risk of cognitive decline. However, the effect of exercise on learning and memory in fluoride-exposed mice is unclear. For this purpose, in this study, mice were randomly allotted into four groups (16 mice per group, half male and half female): control group (group C), fluoride group (group F, 100mg/L sodium fluoride (NaF)), exercise group (group E, treadmill exercise), and E plus F group (group EF, treadmill exercise, and 100mg/L NaF). During 6months of exposure, exercise alleviated the NaF-induced decline in memory and learning. In addition, NaF induced injuries in mitochondria and myelin sheath ultrastructure and reduced the neurons number, while exercise restored them. Metabolomics results showed that phosphatidylethanolamine, pregnenolone (PREG), and lysophosphatidic acid (LysoPA) were altered among groups C, F, and EF. Combined with previous studies, it can be suggested that PREG might be a biomarker in response to exercise-relieving fluorine neurotoxicity. The miRNA sequencing results indicated that in the differently expressed miRNAs (DEmiRNAs), miR-206-3p, miR-96-5p, and miR-144-3p were shared in groups C, F, and EF. After the QRT-PCR validation and in vitro experiments, it was proved that miR-206-3p could reduce cell death and regulate AP-1 transcription factor subunit (JunD) and histone deacetylase 4 (HDAC4) to alleviate fluoride neurotoxicity. To sum up, the current study reveals that exercise could alleviate NaF-induced neurotoxicity by targeting miR-206-3p or PREG, which will contribute to revealing the pathogenesis and therapeutic method of fluoride neurotoxicity.

Review of neurotoxicity of T-2 toxin.

T-2 toxin is a representative trichothecene that is widely detected in corn, wheat and other grain feeds. T-2 toxin has stable physical and chemical properties, making it difficult to remove from food and feed. Hence, T-2 toxin has become an unavoidable pollutant in food for humans and animals. T-2 toxin can enter brain tissue by crossing the blood-brain barrier and leads to congestion, swelling and even apoptosis of neurons. T-2 toxin poisoning can directly lead to clinical symptoms (anti-feeding reaction and decline of learning and memory function in humans and animals). Maternal T-2 toxin exposure also exerted toxic effects on the central nervous system of offspring. Oxidative stress is the core neurotoxicity mechanism underlying T-2 toxin poison. Oxidative stress-mediated apoptosis, mitochondrial oxidative damage and inflammation are all involved in the neurotoxicity induced by T-2 toxin. Thus, alleviating oxidative stress has become a potential target for relieving the neurotoxicity induced by T-2 toxin. Future efforts should be devoted to revealing the neurotoxic molecular mechanism of T-2 toxin and exploring effective therapeutic drugs to alleviate T-2 toxin-induced neurotoxicity.

How do grazing beef and dairy cattle respond to virtual fences? A review.

Virtual fencing (VF) is a modern fencing technology that requires the animal to wear a device (e.g., a collar) that emits acoustic signals to replace the visual cue of traditional physical fences (PF) and, if necessary, mild electric signals. The use of devices that provide electric signals leads to concerns regarding the welfare of virtually fenced animals. The objective of this review is to give an overview of the current state of VF research into the welfare and learning behavior of cattle. Therefore, a systematic literature search was conducted using two online databases and reference lists of relevant articles. Studies included were peer-reviewed and written in English, used beef or dairy cattle, and tested neck-mounted VF devices. Further inclusion criteria were a combination of audio and electrical signals and a setup as a pasture trial, which implied that animals grazed in groups on grassland for 4h minimum while at least one fence side was virtually fenced. The eligible studies (n = 13) were assigned to one or two of the following categories: animal welfare (n studies = 8) or learning behavior (n studies = 9). As data availability for conducting a meta-analysis was not sufficient, a comparison of the means of welfare indicators (daily weight gain, daily lying time, steps per hour, daily number of lying bouts, and fecal cortisol metabolites [FCM]) for virtually and physically fenced animals was done instead. In an additional qualitative approach, the results from the welfare-related studies were assembled and discussed. For the learning behavior, the number of acoustic and electric signals and their ratio were used in a linear regression model with duration in days as a numeric predictor to assess the learning trends over time. There were no significant differences between VF and PF for most welfare indicators (except FCM with lower values for VF; P = 0.0165). The duration in days did not have a significant effect on the number of acoustic and electric signals. However, a significant effect of trial duration on the ratio of electric-to-acoustic signals (P = 0.0014) could be detected, resulting in a decreasing trend of the ratio over time, which suggests successful learning. Overall, we conclude that the VF research done so far is promising but is not yet sufficient to ensure that the technology could not have impacts on the welfare of certain cattle types. More research is necessary to investigate especially possible long-term effects of VF.

Mind, Biology, and Value Alignment: Precis of The Prospect of a Humanitarian Artificial Intelligence

This is a short sketch of some central ideas developed in my recent monograph The Prospect of a Humanitarian Artificial Intelligence, published by Bloomsbury, London 2023. The monograph is available open access at library.oapen.org/handle/20.500. 12657/61934. It illuminates the development of AI by examining our drive to live a dignified life. It uses the notions of agency and attention to consider our pursuit of what is important. It shows how the best way to guarantee value alignment between humans and potentially intelligent machines is through attention routines that satisfy similar needs. Setting out a theoretical framework for AI, the book acknowledges its legal, moral, and political implications and takes into account how epistemic agency differs from moral agency. Insightful comparisons between human and animal intelligence clarify why adopting a need-based attention approach justifies a humanitarian framework. This is an urgent, timely argument for developing AI technologies based on international human rights agreements.

Integrative learning in the lens of meta-learned models of cognition: Impacts on animal and human learning outcomes

Abstract This commentary examines the synergy between meta-learned models of cognition and integrative learning in enhancing animal and human learning outcomes. It highlights three integrative learning modes – holistic integration of parts, top-down reasoning, and generalization with in-depth analysis – and their alignment with meta-learned models of cognition. This convergence promises significant advances in educational practices, artificial intelligence, and cognitive neuroscience, offering a novel perspective on learning and cognition.

Cognitive and Neural Representations of Fractals in Vision, Music, and Action.

The concept of fractal was popularized by Mandelbrot as a tool to tame the geometrical structure of objects with infinite hierarchical depth. The key aspect of fractals is the use of simple parsimonious rules and initial conditions, which when applied recursively can generate unbounded complexity. Fractals are structures ubiquitous in nature, being present in coast lines, bacteria colonies, trees, and physiological time series. However, within the field of cognitive science, the core question is not which phenomena can generate fractal structures, but whether human or animal minds can represent recursive processes, and if so in which domains. In this chapter, we will explore the cognitive and neural mechanisms underlying the representation of recursive hierarchical embedding. Language is the domain in which this capacity is best studied. Humans can generate an infinite array of hierarchically structured sentences, and this capacity distinguishes us from other species. However, recent research suggests that humans can represent similar structures in the domains of music, vision, and action and has provided additional cues as to how these capacities are cognitively implemented. Using a comparative approach, we will map the commonalities and differences across domains and offer a roadmap to understand the neurobiological implementation of fractal cognition.

Animal Behaviour and Barbarian Customs: Points of Contact Between Ethnography and Ethology in Greek and Latin Sources

In the context of the ancient philosophical discussion of animal intelligence, authors tried to show the commonality of the human and the animal mind by collecting and presenting anecdotes in which animal behaviour appears anthropomorphized. Normally this anthropomorphization follows Greek and Roman standards, but in some cases animals appear behaving in ways reminiscent of “barbarian” customs, as transmitted by ancient historiographical sources. A selection of such cases is the subject of this article. The image of the behaviour of wild animals such as elephants or eagles, and domesticated animals, like dogs and hens, in the works of Pliny, Aelian, and Plutarch can sometimes reflect what recent studies have called “the barbarian repertoire”, whereby animals appear to be endowed with a sort of “alien wisdom”.

Artificial Intelligence: The Future

Artificial intelligence is the intelligence of machines or software, as opposed to the intelligence of humans or animals. It is also the field of study in computer science that develops and studies intelligent machines. "AI" may also refer to the machines themselves. AI is not a new for the scientist, it was introduce in 1943 with artificial neurons model and get popular in 1950 due to “Turting test” the test was done to get answer that machine can think?, purposed by Alan Turing. Basically AI is categorized into three types, Artificial Narrow Intelligence, Artificial General Intelligence and Artificial Super Intelligence. Deep learning and machine learning is major subfield of Artificial intelligence. DL as a subset of ML, which is also another subset of AI. Therefore, AI is the all-encompassing concept that initially erupted. Application of AI fields are Healthcare, Business, Education, Agriculture, Finance, Law, Entertainment and media, Software coding and IT processes, Security, Manufacturing, Banking and Transportation. In reference to Job creation or distraction, Artificial Intelligence is not job killer but a job category killer”. In the latest report (May 2023) on The Future of Jobs, the World Economic Forum (WEF) predicts the creation of 69 million jobs by 2027 thanks to AI, but also the destruction of 89 million jobs. In context to intelligence level, Jan. 2022, Age of IQ level of AI was as 7 year Children and in Dec. 2022, Age of IQ level of AI was as 9 year Children. India is emerging market in global and it has around 12 % of work could be automated by AI. In India more than 2000 startup are related to AI and 90000 plus AI Professional work in India.The economic impact of AI, for select G20 countries and estimates AI to boost India’s annual growth rate by 1.3 percentage points by 2035. AI has potential to add 1 trillion to India’s economy in 2035. We are going to enter into new technological world, it’s may be our fortune or misfortune. Key Words: - Artificial Intelligence, Machine learning, Job, India

A neural autopilot theory of habit: Evidence from consumer purchases and social media use.

This article applies a two-process "neural autopilot" model to field data. The autopilot model hypothesizes that habitual choice occurs when the reward from a behavior has low numerical "doubt" (i.e., reward prediction errors are small). The model toggles between repeating a previous choice (habit) when doubt is low and making a goal-directed choice when doubt is high. The model has ingredients established in animal learning and cognitive neuroscience and is simple enough to make nonobvious predictions. In two empirical applications, we fit the model to field data on purchases of canned tuna and posting on the Chinese social media site Weibo. This style of modeling is called "structural" because there is a theoretical model of how different variables influence choices by agents (the "structure"), which tightly restricts how hidden variables lead to observed choices. There is empirical support for the model, more strongly for tuna purchases than for Weibo posting, relative to a baseline "reduced-form" model in which current choices are correlated with past choices without a mechanistic (structural) explanation. An interesting set of predictions can also be derived about how consumers react to different kinds of changes in prices and qualities of goods (this is called "counterfactual analysis").

Don’t mind milk? The role of animal suffering, speciesism, and guilt in the denial of mind and moral status of dairy cows

Reminding meat-eaters that animals are being harmed for meat production, elicits psychological tension about meat consumption. Individuals deal with this tension by either reducing or stopping meat consumption or by denying the mind of food animals, thereby lowering the moral status of animals. It is currently unclear whether similar reactions occur when considering dairy consumption. In a preregistered experiment (N = 345 animal product consumers), we manipulated perceived harm levels inflicted upon dairy cows (higher versus lower) to investigate people’s use of dairy-related cognitive dissonance reduction strategies. Participants in the high (vs low) harm condition felt more guilty which in turn, was associated with a) lower mind attribution and moral concern for the cow and b) greater intentions to reduce or stop dairy consumption. These effects were especially pronounced for participants higher in speciesism, while among those lower in speciesism, the effects were weaker (on guilt and intentions to change dairy consumption) or non-significant (on mind attribution, moral concern). The findings demonstrate that increased awareness of animal harm in dairy farms, elicits guilt and dissonance reduction reactions similar to meat-related dissonance reactions. Evidence of dairy-related cognitive dissonance highlights the need for a greater research focus on the consumption of animal products other than meat.

Abduction in Animal Minds

Abstract Following ideas of Ch. S. Peirce on continuity of mind (synechism) and universality of semiotic processes (pansemiotism) as well as development of the understanding of manipulative abduction in works of L. Magnani the thesis of possibility of abductive reasoning in non-human animal minds is defended. The animal capacity to form explanatory hypotheses is demonstrated by instances of grasping regularities in environment, behavior of conspecifics and even self-knowledge. In the framework of debate on instinctual or rather inferential nature of abductive capacity questions of innate and acquired mechanisms of learning, the role of language in development of explanations and priority of inner (emotional) or outer (referential) perspectives in genesis of first explanatory hypotheses are considered.

Awards for Distinguished Scientific Early Career Contributions to Psychology.

The Early Career Awards, given for the first time in 1974, recognize the large number of excellent early career psychologists. Recipients of this award may not have held a doctoral degree for more than nine years. For purposes of this award, psychology has been divided into 10 areas: animal learning and behavior, comparative; developmental; health; cognition/human learning; psychopathology; behavioral and cognitive neuroscience; perception/motor performance; social; applied research; and individual differences. Five areas are considered each year, with areas rotated in two-year cycles. The areas considered in 2023 were applied research; behavioral and cognitive neuroscience; individual differences; perception and motor performance; and social psychology. The 2023 recipients of the APA Distinguished Scientific Contribution Awards were recognized by the 2022 Board of Scientific Affairs and selected by the 2022 Committee on Scientific Awards. (PsycInfo Database Record (c) 2024 APA, all rights reserved).