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Results for “Animal Behavior and Cognition”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

Impaired hippocampal representation of place in the Fmr1-knockout mouse model of Fragile X syndrome

Fragile X syndrome (FXS) is an X-chromosome linked intellectual disability and the most common genetic cause of autism spectrum disorder (ASD). Building upon demonstrated deficits in neuronal plasticity and spatial memory in FXS, we investigated how spatial information processing is affected in vivo in an FXS mouse model (Fmr1-KO). Healthy hippocampal neurons (so-called place cells) exhibit place-related activity during spatial exploration, and the stability of these spatial representations can be taken as an index of memory function. We find impaired stability and reduced specificity of Fmr1-KO spatial representations. This is a potential biomarker for the cognitive dysfunction observed in FXS, informative on the ability to integrate sensory information into an abstract representation and successfully retain this conceptual memory. Our results provide key insight into the biological mechanisms underlying cognitive disabilities in FXS and ASD, paving the way for a targeted approach to remedy these.

animal behavior and cognition↗

bioRxiv2018

Coffee polyphenols prevent cognitive dysfunction and suppress amyloid β plaques in APP/PS2 transgenic mouse

Epidemiological studies have found that habitual coffee consumption may reduce the risk of Alzheimers disease. Coffee contains numerous phenolic compounds (coffee polyphenols) such as chlorogenic acids. However, evidence demonstrating the contribution of chlorogenic acids in preventing cognitive dysfunction induced by Alzheimers disease is limited. In this study, we investigated the effect of chlorogenic acids on prevention of cognitive dysfunction in APP/PS2 transgenic mouse model of Alzheimers disease. Five-week-old APP/PS2 mice were administered a diet supplemented with coffee polyphenols daily for 5 months. The memory and cognitive function of mice was determined using the novel object recognition test, the Morris water maze test, and the step-through passive avoidance test. We found that chronic treatment with coffee polyphenols prevented cognitive dysfunction and significantly reduced hippocampal A{beta} deposition. We then determined the effect of 5-caffeoylquinic acid, one of the primary components of coffee polyphenols, on A{beta} formation. 5-Caffeoylquinic acid did not inhibit A{beta} fibrillation, but degraded A{beta} fibrils in a dose-dependent manner. In conclusion, these results demonstrate that coffee polyphenols prevented cognitive deficits and alleviated A{beta} plaque deposition via disaggregation of A{beta} in APP/PS2 mouse.

animal behavior and cognition↗

bioRxiv2018

Cognition and behaviour in learning difficulties and ADHD: A dimensional approach

BackgroundAcademic underachievement often accompanies the symptoms of inattention and hyperactivity/ impulsivity associated with ADHD. The aim of the present study is to establish whether learning difficulties have the same cognitive origins in this comorbid condition as in children who do not have ADHD.\n\nMethodsParticipants were 163 school-aged children with learning difficulties. Over a third also had a diagnosis of ADHD. Cognition, behaviour and learning attainments were assessed.\n\nResultsThe sample was distinguished by three cognitive and three behavioural dimensions. Learning was equivalently related to cognitive dimensions for children with and without ADHD. A diagnosis of ADHD was associated only with elevated levels of ADHD symptoms and problems with emotional control.\n\nConclusionsDistinct dimensions underpin academic learning and the control of impulsive and emotional behaviour impaired in ADHD. Phonological deficits are associated with learning problems in literacy and maths, and impairments in nonverbal and executive abilities with mathematical learning difficulties. The comorbid condition of ADHD combined with learning difficulties reflects independent deficits in the cognitive dimensions critical for learning and in the control of impulsive and emotional behaviour.

animal behavior and cognition↗

bioRxiv2018

Deterministic response strategies in trial-and-error learning

Trial-and-error learning is a universal strategy for establishing which actions are beneficial or harmful in new environments. However, learning stimulus-response associations solely via trial-and-error is often suboptimal, as in many settings dependencies among stimuli and responses can be exploited to increase learning efficiency. Previous studies have shown that in settings featuring such dependencies, humans typically engage high-level cognitive processes and employ advanced learning strategies to improve their learning efficiency. Here we analyze in detail the initial learning phase of a sample of human subjects (N = 85) performing a trial-and-error learning task with deterministic feedback and hidden stimulus-response dependencies. Using computational modeling, we find that the standard Q-learning model cannot sufficiently explain human learning strategies in this setting. Instead, newly introduced deterministic response models, which are theoretically optimal and transform stimulus sequences unambiguously into response sequences, provide the best explanation for 50.6% of the subjects. Most of the remaining subjects either show a tendency towards generic optimal learning (21.2%) or at least partially exploit stimulus-response dependencies (22.3%), while a few subjects (5.9%) show no clear preference for any of the employed models. After the initial learning phase, asymptotic learning performance during the subsequent practice phase is best explained by the standard Q-learning model. Our results show that human learning strategies in trial-and-error learning go beyond merely associating stimuli and responses via incremental reinforcement. Specifically during initial learning, high-level cognitive processes support sophisticated learning strategies that increase learning efficiency while keeping memory demands and computational efforts bounded. The good asymptotic fit of the Q-learning model indicates that these cognitive processes are successively replaced by the formation of stimulus-response associations over the course of learning.

animal behavior and cognition↗

bioRxiv2018

Network Structure and Social Complexity in Primates

Primates use social grooming to create and maintain coalitions. Because of this, individuals focus their time on a small number of individuals, and this means that in many cases group networks are not fully connected. I use data on primate grooming networks to show that three different social grades can be differentiated in terms of network structuring. These grades seem to arise from a glass ceiling imposed on group size by limits on the time available for social grooming. It seems that certain genera have managed to circumvent this constraint by a phase shift in the behavioural and cognitive mechanisms that underpin social relationships in a way that allows a form of multilevel sociality based on weak and strong ties not unlike those found in human social networks.

animal behavior and cognition↗

bioRxiv2018

Schizophrenia-related cognitive dysfunction in the Cyclin-D2 knockout mouse model of ventral hippocampal hyperactivity

Elevated activity at the output stage of the anterior hippocampus has been described as a physiological endophenotype of schizophrenia, and its development maps onto the transition from its prodromal to its psychotic state. Interventions that halt the spreading glutamatergic over-activity in this region and thereby the development of overt schizophrenia could be promising therapies. However, animal models with high construct validity to support such pre-clinical development are scarce. The Cyclin-D2 knockout (CD2-KO) mouse model shows a hippocampal Parvalbumin-interneuron dysfunction and its pattern of hippocampal over-activity shares similarities with that seen in prodromal patients. In a comprehensive phenotyping of CD2-KO mice, we found that they displayed novelty-induced hyperlocomotion (a correlate in the positive symptom domain), that was largely resistant against D1- and D2-dopamine receptor antagonism, but responsive to the mGluR2/3-agonist LY379268. In the negative symptom domain, CD2-KO mice showed transiently reduced sucrose-preference (anhedonia), but enhanced interaction with novel mice and objects, as well as normal nest building and incentive motivation. Also, unconditioned anxiety, perseveration, and motor impulsivity were unaltered. However, in the cognitive domain, CD2-knockouts showed reduced executive function in assays of rule-shift and rule-reversal learning, but also an impairment in working memory, that was resistant against LY379268. In contrast, sustained attention and forms of spatial and object-related memory that are mediated by short-term habituation of stimulus-specific attention were intact. Our results suggest, that CD2-KO mice are a valuable model in translational research targeted at the pharmacoresistant cognitive symptom domain in causal relation to hippocampal over-activity in the prodrome-to-psychosis transition.

animal behavior and cognition↗

bioRxiv2017

Amortized Hypothesis Generation

Bayesian models of cognition posit that people compute probability distributions over hypotheses, possibly by constructing a sample-based approximation. Since people encounter many closely related distributions, a computationally efficient strategy is to selectively reuse computations - either the samples themselves or some summary statistic. We refer to these reuse strategies as amortized inference. In two experiments, we present evidence consistent with amortization. When sequentially answering two related queries about natural scenes, we show that answers to the second query vary systematically depending on the structure of the first query. Using a cognitive load manipulation, we find evidence that people cache summary statistics rather than raw sample sets. These results enrich our notions of how the brain approximates probabilistic inference.

animal behavior and cognition↗

bioRxiv2017

Molecular Correlate Of Mouse Executive Function. Top-Down And Bottom-Up Information Flows Complementation By Ntng Gene Paralogs

Executive function (EF) is a regulatory construct of learning and general cognitive abilities. Genetic variations underlying the architecture of cognitive phenotypes are likely to affect EF and associated behaviors. Mice lacking one of Ntng gene paralogs, encoding the vertebrate brain-specific presynaptic Netrin-G proteins, exhibit prominent deficits in the EF control. Brain areas responsible for gating the bottom-up and top-down information flows differentially express Ntng1 and Ntng2, distinguishing neuronal circuits involved in perception and cognition. As a result, high and low cognitive demand tasks (HCD and LCD, respectively) modulate Ntng1 and Ntng2 associations either with attention and impulsivity (AI) or working memory (WM), in a complementary manner. During the LCD Ntng2supported neuronal gating of AI and WM dominates over the Ntng1-associated circuits. This is reversed during the HCD, when the EF requires a larger contribution of cognitive control, supported by Ntng1, over the Ntng2 pathways. Since human NTNG orthologs have been reported to affect human IQ (1), and an array of neurological disorders (2), we believe that mouse Ntng gene paralogs serve an analogous role but influencing brain executive functioning.

animal behavior and cognition↗

bioRxiv2016

Approach-induced biases in human information sampling

Information sampling is often biased towards seeking evidence that confirms ones prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here we demonstrate involvement of Pavlovian approach biases in determining which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled ( positive evidence approach), the selection of which information to sample ( sampling the favorite), and the interaction between information sampling and subsequent choices ( rejecting unsampled options). The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in information seeking are a stable trait across multiple gameplays, and can be related to demographic measures including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.

Animal Behavior and Cognition↗

bioRxiv2018

Evolutionary dynamics of recent selection for enhanced social cognition

Cognitive abilities can vary dramatically among species though little is known about the dynamics of cognitive evolution. Here we demonstrate that recent evolution of visual individual recognition in the paper wasp Polistes fuscatus is the target of arguably the strongest positive selective pressure in the species recent history. The most extreme selective sweeps in P. fuscatus are associated with genes known to be involved in long-term memory formation, mushroom body development and visual processing - all traits that have recently evolved in association with individual recognition. Cognitive evolution appears to have been driven initially by selection on standing variation in perceptual traits followed by both hard and soft sweeps on learning and memory. Evolutionary modeling reveals that intense selection as observed in P. fuscatus is likely the norm during the early stages of cognitive evolution. These data provide insight into the dynamics of cognition evolution demonstrating that social selection for increased intelligence can lead to rapid multi-genic adaptation of enhanced recognition abilities.

animal behavior and cognition↗

bioRxiv2018

Behavioral flexibility in an OCD mouse model: Impaired Pavlovian reversal learning in SAPAP3 mutants

Obsessive-compulsive disorder (OCD) is characterized by obsessive thinking, compulsive behavior, and anxiety, and is often accompanied by cognitive deficits. The neuropathology of OCD involves dysregulation of cortical-striatal circuits. Similar to OCD patients, SAPAP3 knockout mice 3 (SAPAP3-/-) exhibit compulsive behavior (grooming), anxiety, and dysregulated cortical-striatal function. However, it is unknown whether SAPAP3-/- display cognitive deficits and how these different behavioral traits relate to one another. SAPAP3-/- and wild-type littermates (WT) were trained in a Pavlovian conditioning task pairing the delivery of visual cues with that of sucrose solution. After mice learned to discriminate between a reward-predicting conditioned stimulus (CS+) and a non-reward stimulus (CS-), contingencies were reversed (CS+ became CS- and vice versa). Additionally, we assessed grooming, anxiety, and general activity. SAPAP3-/- acquired Pavlovian approach behavior similarly to WT, albeit less vigorously and with a different strategy. However, unlike WT, SAPAP3-/- were unable to adapt their behavior after contingency reversal, exemplified by a lack of re-establishing CS+ approach behavior (sign tracking). Surprisingly, such behavioral inflexibility, decreased vigor, compulsive grooming, and anxiety were unrelated. This study demonstrates that SAPAP3-/- are capable of Pavlovian learning, but lack flexibility to adapt associated conditioned approach behavior. Thus, SAPAP3-/- do not only display compulsive-like behavior and anxiety, but also cognitive deficits, confirming and extending the validity of SAPAP3-/- as a suitable model for OCD. The observation that compulsive-like behavior, anxiety, and behavioral inflexibility were unrelated suggests a non-causal relationship between these traits and may be of clinical relevance for OCD patients.

animal behavior and cognition↗

bioRxiv2017

Forgot what you like? Evidence for hippocampal dependence of value-based decisions

Consistent decisions are intuitively desirable and theoretically important for utility maximization. Neuroeconomics has established the neurobiological substrate of value representation, but brain regions that provide input to the value-processing network is less explored. The constructed-preference tradition within behavioral decision research gives a critical role to cognitive processes that rely on associations, suggesting a role for the hippocampus in making decisions and to do so consistently. We compared the performance of 31 patients with mediotemporal lobe (MTL) epilepsy and hippocampal lesions, 30 patients with extratemporal lobe epilepsy, and 30 healthy controls on two tasks: binary choices between candy bars based on their preferences and a number-comparison control task where the larger number is chosen. MTL patients make more inconsistent choices than the other two groups for the value-based choice but not the number-comparison task. These inconsistencies increase with the volume of compromised hippocampal tissue. These results suggest a critical involvement of the MTL in preference construction and value-based choices.\n\nSignificanceOur days are full of choices that reflect our preferences. Economics lays out models of how to optimally make these decisions. Neuroeconomics has identified a cortical value-processing network whose activity correlates with constructs related to valuation and choice in economic models. However open questions remain: How are these value signals formed, and what regions might be necessary for retrieving and computing these value signals? Inspired by cognitive models calling on associative processes in value-based decisions, this paper uses unique neuropsychological data to establish the critical role of the medial temporal lobe in making consistent choices and further informs our understanding of the value-processing network.

animal behavior and cognition↗

bioRxiv2018

Human perception-motor decision-making is not optimal

The rationality of human behavior has been a major problem in philosophy for centuries. The pioneering work of Kahneman and Tversky provides strong evidence that people are not rational. Recent work in psychophysics argues that incentivized sensorimotor decisions (such as deciding where to reach to get a reward) maximizes expected gain, suggesting that it may be impervious to cognitive biases and heuristics. We rigorously tested this hypothesis using multiple experiments and multiple computational models. We obtained strong evidence that people deviated from the objectively rational strategy when potential losses were large. They instead appeared to follow a strategy in which they simplify the decision problem and satisfice rather than optimize. This work is consistent with the framework known as bounded rationality, according to which people behave rationally given their computational limitations.

animal behavior and cognition↗

bioRxiv2018

Foraging as an evidence accumulation process

A canonical foraging task is the patch-leaving problem, in which a forager must decide to leave a current resource in search for another. Theoretical work has derived optimal strategies for when to leave a patch, and experiments have tested for conditions where animals do or do not follow an optimal strategy. Nevertheless, models of patch-leaving decisions do not consider the imperfect and noisy sampling process through which an animal gathers information, and how this process is constrained by neurobiological mechanisms. In this theoretical study, we formulate an evidence accumulation model of patch-leaving decisions where the animal averages over noisy measurements to estimate the state of the current patch and the overall environment. Evidence accumulation models belong to the class of drift diffusion processes and have been used to model decision making in different contexts especially in cognitive and systems neuroscience. We solve the model for conditions where foraging decisions are optimal and equivalent to the marginal value theorem, and perform simulations to analyze deviations from optimal when these conditions are not met. By adjusting the drift rate and decision threshold, the model can represent different \"strategies\", for example an increment-decrement or counting strategy. These strategies yield identical decisions in the limiting case but differ in how patch residence times adapt when the foraging environment is uncertain. To account for sub-optimal decisions, we introduce an energy-dependent utility function that predicts longer than optimal patch residence times when food is plentiful. Our model provides a quantitative connection between ecological models of foraging behavior and evidence accumulation models of decision making. Moreover, it provides a theoretical framework for potential experiments which seek to identify neural circuits underlying patch leaving decisions.

animal behavior and cognition↗

bioRxiv2017

Decision by sampling implements efficient coding of psychoeconomic functions

The theory of decision by sampling (DbS) proposes that an attributes subjective value is its rank within a sample of attribute values retrieved from memory. This can account for instances of context dependence beyond the reach of classic theories which assume stable preferences. In this paper, we provide a normative justification for DbS that is based on the principle of efficient coding. The efficient representation of information in a noiseless communication channel is characterized by a uniform response distribution, which the rank transformation implements. However, cognitive limitations imply that decision samples are finite, introducing noise. Efficient coding in a noisy channel requires smoothing of the signal, a principle that leads to a new generalization of DbS. This generalization is closely connected to range-frequency theory, and helps descriptively account for a wider set of behavioral observations, such as how context sensitivity varies with the number of available response categories.

animal behavior and cognition↗

bioRxiv2018

Do city cachers store less? The effect of urbanization and exploration on spatial memory in individual scatter hoarders

Urbanization has been shown to affect a variety of traits in animals, including their physiology, morphology, and behaviour, but it is less clear how cognitive traits are modified. Urban habitats contain artificially elevated food sources, such as bird feeders, that are known to affect the foraging behaviours of urban animals. As of yet however, it is not known whether urbanization and the abundance of supplemental food during the winter reduce caching behaviours and spatial memory in scatter hoarders. We aimed to examine individual variation in caching and spatial memory between and within urban and rural habitats to determine i) whether urban individuals cache less frequently and perform less accurately on a spatial task, and ii) explore, for the first time in scatter hoarders, whether slower explorers perform more accurately on a spatial task, indicating a speed-accuracy trade-off within individuals. We assessed spatial memory of wild-caught black-capped chickadees (Poecile atricapillus; N = 96) from 14 sites along an urban gradient. While the individuals that cached more food in captivity were all from rural environments, we find no clear evidence that caching intensity and spatial memory accuracy differ along an urban gradient, and find no significant relationship between spatial cognition and exploration of a novel environment within individuals. However, individuals that performed more accurately also tended to cache more frequently, suggesting for the first time that the specialization of spatial memory in scatter hoarders may also occur at the level of the individual in addition to the population and species levels.

animal behavior and cognition↗

bioRxiv2016

Learning of speech categories in humans and Zebra finches

The survival of organisms depends highly on their ability to adjust their behavior according to proper categorizations of various events. More than one strategy can be used in categorization. One is the Rule-Based (RB) strategy and the other is Information-Integration (II) strategy. In this research we analyzed the differences between avian and human cognition. Twelve Greek listeners and four Zebra finches were tested in speech category learning tasks. In particular, both humans and Zebra finches had to categorize between Dutch vowels that differ on duration, frequency or both depending on the condition. Feedback was given for correct and incorrect responses. The results showed that humans and Zebra finches are probably using the same methods of learning depending on the categorization tasks that they are exposed to. If Zebra Finches are actually able to acquire (RB) and (II) category structures using the same strategies as humans, the utility of multiple systems of categorization might not be restricted to primates as current literature suggest.

Animal Behavior and Cognition↗

bioRxiv2018

An entropic barriers diffusion theory of decision-making in multiple alternative tasks

We present a theory of decision-making in the presence of multiple choices that departs from traditional approaches by explicitly incorporating entropic barriers in a stochastic search process. We analyze response time data from an on-line repository of 15 million blitz chess games, and show that our model fits not just the mean and variance, but the entire response time distribution (over several response-time orders of magnitude) at every stage of the game. We apply the model to show that (a) higher cognitive expertise corresponds to the exploration of more complex solution spaces, and (b) reaction times of users at an on-line buying website can be similarly explained. Our model can be seen as a synergy between diffusion models used to model simple two-choice decision-making and planning agents in complex problem solving.

animal behavior and cognition↗