Improving laboratory animal genetic reporting: LAG-R guidelines.

The biomedical research community addresses reproducibility challenges in animal studies through standardized nomenclature, improved experimental design, transparent reporting, data sharing, and centralized repositories. The ARRIVE guidelines outline documentation standards for laboratory animals in experiments, but genetic information is often incomplete. To remedy this, we propose the Laboratory Animal Genetic Reporting (LAG-R) framework. LAG-R aims to document animals' genetic makeup in scientific publications, providing essential details for replication and appropriate model use. While verifying complete genetic compositions may be impractical, better reporting and validation efforts enhance reliability of research. LAG-R standardization will bolster reproducibility, peer review, and overall scientific rigor.

Reframing dopamine: A controlled controller at the limbic-motor interface.

Pavlovian influences notoriously interfere with operant behaviour. Evidence suggests this interference sometimes coincides with the release of the neuromodulator dopamine in the nucleus accumbens. Suppressing such interference is one of the targets of cognitive control. Here, using the examples of active avoidance and omission behaviour, we examine the possibility that direct manipulation of the dopamine signal is an instrument of control itself. In particular, when instrumental and Pavlovian influences come into conflict, dopamine levels might be affected by the controlled deployment of a reframing mechanism that recasts the prospect of possible punishment as an opportunity to approach safety, and the prospect of future reward in terms of a possible loss of that reward. We operationalize this reframing mechanism and fit the resulting model to rodent behaviour from two paradigmatic experiments in which accumbens dopamine release was also measured. We show that in addition to matching animals' behaviour, the model predicts dopamine transients that capture some key features of observed dopamine release at the time of discriminative cues, supporting the idea that modulation of this neuromodulator is amongst the repertoire of cognitive control strategies.

Sexual Dimorphism of the Mouse Plasma Metabolome Is Associated with Phenotypes of 30 Gene Knockout Lines.

Although metabolic alterations are observed in many monogenic and complex genetic disorders, the impact of most mammalian genes on cellular metabolism remains unknown. Understanding the effect of mouse gene dysfunction on metabolism can inform the functions of their human orthologues. We investigated the effect of loss-of-function mutations in 30 unique gene knockout (KO) lines on plasma metabolites, including genes coding for structural proteins (11 of 30), metabolic pathway enzymes (12 of 30) and protein kinases (7 of 30). Steroids, bile acids, oxylipins, primary metabolites, biogenic amines and complex lipids were analyzed with dedicated mass spectrometry platforms, yielding 827 identified metabolites in male and female KO mice and wildtype (WT) controls. Twenty-two percent of 23,698 KO versus WT comparison tests showed significant genotype effects on plasma metabolites. Fifty-six percent of identified metabolites were significantly different between the sexes in WT mice. Many of these metabolites were also found to have sexually dimorphic changes in KO lines. We used plasma metabolites to complement phenotype information exemplified for Dhfr, Idh1, Mfap4, Nek2, Npc2, Phyh and Sra1. The association of plasma metabolites with IMPC phenotypes showed dramatic sexual dimorphism in wildtype mice. We demonstrate how to link metabolomics to genotypes and (disease) phenotypes. Sex must be considered as critical factor in the biological interpretation of gene functions.

The role of the lateral orbitofrontal cortex in creating cognitive maps.

We use mental models of the world-cognitive maps-to guide behavior. The lateral orbitofrontal cortex (lOFC) is typically thought to support behavior by deploying these maps to simulate outcomes, but recent evidence suggests that it may instead support behavior by underlying map creation. We tested between these two alternatives using outcome-specific devaluation and a high-potency chemogenetic approach. Selectively inactivating lOFC principal neurons when male rats learned distinct cue-outcome associations, but before outcome devaluation, disrupted subsequent inference, confirming a role for the lOFC in creating new maps. However, lOFC inactivation surprisingly led to generalized devaluation, a result that is inconsistent with a complete mapping failure. Using a reinforcement learning framework, we show that this effect is best explained by a circumscribed deficit in credit assignment precision during map construction, suggesting that the lOFC has a selective role in defining the specificity of associations that comprise cognitive maps.

Vigilance, arousal, and acetylcholine: Optimal control of attention in a simple detection task.

Paying attention to particular aspects of the world or being more vigilant in general can be interpreted as forms of 'internal' action. Such arousal-related choices come with the benefit of increasing the quality and situational appropriateness of information acquisition and processing, but incur potentially expensive energetic and opportunity costs. One implementational route for these choices is widespread ascending neuromodulation, including by acetylcholine (ACh). The key computational question that elective attention poses for sensory processing is when it is worthwhile paying these costs, and this includes consideration of whether sufficient information has yet been collected to justify the higher signal-to-noise ratio afforded by greater attention and, particularly if a change in attentional state is more expensive than its maintenance, when states of heightened attention ought to persist. We offer a partially observable Markov decision-process treatment of optional attention in a detection task, and use it to provide a qualitative model of the results of studies using modern techniques to measure and manipulate ACh in rodents performing a similar task.

Experimental Release of Orphaned Wild Felids into a Tropical Rainforest in Southwestern Costa Rica.

A 3- to 4-mo-old male ocelot (Leopardus pardalis) and a 6- to 8-mo-old female margay (Leopardus weidii) were brought in from the wild, held in captivity, and rehabilitated for 906 and 709 days, respectively, at the Rescate Wildlife Rescue Center in Costa Rica. During captivity, both cats were kept as isolated as possible from humans and fed appropriate live wild prey. After maturing and demonstrating the ability to capture and feed on live prey, the cats were radio-collared, released at a national wildlife refuge previously assessed for predator and prey occurrence, and monitored. After 54 days, the ocelot was trapped while preying on chickens in a nearby community, and after 20 days, the margay was found dead, likely due to ocelot predation. Avoiding habituation to humans, assuring hunting abilities, and assessing release sites likely is not sufficient to assure successful release of these species, and more experimental releases with innovative and detailed protocols and monitoring are needed.

Deep Learning Classification of Canine Behavior Using a Single Collar-Mounted Accelerometer: Real-World Validation.

Collar-mounted canine activity monitors can use accelerometer data to estimate dog activity levels, step counts, and distance traveled. With recent advances in machine learning and embedded computing, much more nuanced and accurate behavior classification has become possible, giving these affordable consumer devices the potential to improve the efficiency and effectiveness of pet healthcare. Here, we describe a novel deep learning algorithm that classifies dog behavior at sub-second resolution using commercial pet activity monitors. We built machine learning training databases from more than 5000 videos of more than 2500 dogs and ran the algorithms in production on more than 11 million days of device data. We then surveyed project participants representing 10,550 dogs, which provided 163,110 event responses to validate real-world detection of eating and drinking behavior. The resultant algorithm displayed a sensitivity and specificity for detecting drinking behavior (0.949 and 0.999, respectively) and eating behavior (0.988, 0.983). We also demonstrated detection of licking (0.772, 0.990), petting (0.305, 0.991), rubbing (0.729, 0.996), scratching (0.870, 0.997), and sniffing (0.610, 0.968). We show that the devices' position on the collar had no measurable impact on performance. In production, users reported a true positive rate of 95.3% for eating (among 1514 users), and of 94.9% for drinking (among 1491 users). The study demonstrates the accurate detection of important health-related canine behaviors using a collar-mounted accelerometer. We trained and validated our algorithms on a large and realistic training dataset, and we assessed and confirmed accuracy in production via user validation.

Biallelic UBE4A loss-of-function variants cause intellectual disability and global developmental delay.

PURPOSE: To identify novel genes associated with intellectual disability (ID) in four unrelated families. METHODS: Here, through exome sequencing and international collaboration, we report eight individuals from four unrelated families of diverse geographic origin with biallelic loss-of-function variants in UBE4A. RESULTS: Eight evaluated individuals presented with syndromic intellectual disability and global developmental delay. Other clinical features included hypotonia, short stature, seizures, and behavior disorder. Characteristic features were appreciated in some individuals but not all; in some cases, features became more apparent with age. We demonstrated that UBE4A loss-of-function variants reduced RNA expression and protein levels in clinical samples. Mice generated to mimic patient-specific Ube4a loss-of-function variant exhibited muscular and neurological/behavioral abnormalities, some of which are suggestive of the clinical abnormalities seen in the affected individuals. CONCLUSION: These data indicate that biallelic loss-of-function variants in UBE4A cause a novel intellectual disability syndrome, suggesting that UBE4A enzyme activity is required for normal development and neurological function.

Generation of desminopathy in rats using CRISPR-Cas9.

BACKGROUND: Desminopathy is a clinically heterogeneous muscle disease caused by over 60 different mutations in desmin. The most common mutation with a clinical phenotype in humans is an exchange of arginine to proline at position 350 of desmin leading to p.R350P. We created the first CRISPR-Cas9 engineered rat model for a muscle disease by mirroring the R350P mutation in humans. METHODS: Using CRISPR-Cas9 technology, Des c.1045-1046 (AGG > CCG) was introduced into exon 6 of the rat genome causing p.R349P. The genotype of each animal was confirmed via quantitative PCR. Six male rats with a mutation in desmin (n = 6) between the age of 120-150 days and an equal number of wild type littermates (n = 6) were used for experiments. Maximal plantar flexion force was measured in vivo and combined with the collection of muscle weights, immunoblotting, and histological analysis. In addition to the baseline phenotyping, we performed a synergist ablation study in the same animals. RESULTS: We found a difference in the number of central nuclei between desmin mutants (1 ± 0.4%) and wild type littermates (0.2 ± 0.1%; P < 0.05). While muscle weights did not differ, we found the levels of many structural proteins to be altered in mutant animals. Dystrophin and syntrophin were increased 54% and 45% in desmin mutants, respectively (P < 0.05). Dysferlin and Annexin A2, proteins associated with membrane repair, were increased two-fold and 32%, respectively, in mutants (P < 0.05). Synergist ablation caused similar increases in muscle weight between mutant and wild type animals, but changes in fibre diameter revealed that fibre hypertrophy in desmin mutants was hampered compared with wild type animals (P < 0.05). CONCLUSIONS: We created a novel animal model for desminopathy that will be a useful tool in furthering our understanding of the disease. While mutant animals at an age corresponding to a preclinical age in humans show no macroscopic differences, microscopic and molecular changes are already present. Future studies should aim to further decipher those biological changes that precede the clinical progression of disease and test therapeutic approaches to delay disease progression.

Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation.

Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the number of samples, or "particles," available to perform inference. To test this idea, we focus on two recent experiments that report positive associations between WMC and two distinct aspects of categorization performance: the ability to learn novel categories, and the ability to switch between different categorization strategies ("knowledge restructuring"). In favor of the idea of modeling WMC as a number of particles, we show that a single model can reproduce both experimental results by varying the number of particles-increasing the number of particles leads to both faster category learning and improved strategy-switching. Furthermore, when we fit the model to individual participants, we found a positive association between WMC and best-fit number of particles for strategy switching. However, no association between WMC and best-fit number of particles was found for category learning. These results are discussed in the context of the general challenge of disentangling the contributions of different potential sources of behavioral variability.

Generating mouse models for biomedical research: technological advances.

Over the past decade, new methods and procedures have been developed to generate genetically engineered mouse models of human disease. This At a Glance article highlights several recent technical advances in mouse genome manipulation that have transformed our ability to manipulate and study gene expression in the mouse. We discuss how conventional gene targeting by homologous recombination in embryonic stem cells has given way to more refined methods that enable allele-specific manipulation in zygotes. We also highlight advances in the use of programmable endonucleases that have greatly increased the feasibility and ease of editing the mouse genome. Together, these and other technologies provide researchers with the molecular tools to functionally annotate the mouse genome with greater fidelity and specificity, as well as to generate new mouse models using faster, simpler and less costly techniques.

Pavlovian-instrumental interactions in active avoidance: The bark of neutral trials.

In active avoidance tasks, subjects have to learn to execute particular actions in order to avoid an aversive stimulus, such as a shock. Such paradigms pose a number of psychological and neural enigmas, and so have attracted substantial computational interest. However, the ratio of conjecture to confirmation remains high. Here, we perform a theoretical inquiry into a recent experiment by Gentry, Lee, and Roesch ('Phasic dopamine release in the rat nucleus accumbens predicts approach and avoidance performance', Nat. Commun., 7:13154) who measured phasic dopamine concentrations in the nucleus accumbens core of rats whilst they avoided shocks, acquired food, or acted to gain no programmed outcome. These last, neutral, trials turned out to be a perfect probe for the workings of avoidance, partly because of the substantial differences between subjects and sessions revealed in the experiment. We suggest a way to interpret this probe, gaining support for opponency-, safety-, and Pavlovian-influenced treatments of avoidance.

Interrupting behaviour: Minimizing decision costs via temporal commitment and low-level interrupts.

Ideal decision-makers should constantly assess all sources of information about opportunities and threats, and be able to redetermine their choices promptly in the face of change. However, perpetual monitoring and reassessment impose inordinate sensing and computational costs, making them impractical for animals and machines alike. The obvious alternative of committing for extended periods of time to limited sensory strategies associated with particular courses of action can be dangerous and wasteful. Here, we explore the intermediate possibility of making provisional temporal commitments whilst admitting interruption based on limited broader observation. We simulate foraging under threat of predation to elucidate the benefits of such a scheme. We relate our results to diseases of distractibility and roving attention, and consider mechanistic substrates such as noradrenergic neuromodulation.

Safety out of control: dopamine and defence.

We enjoy a sophisticated understanding of how animals learn to predict appetitive outcomes and direct their behaviour accordingly. This encompasses well-defined learning algorithms and details of how these might be implemented in the brain. Dopamine has played an important part in this unfolding story, appearing to embody a learning signal for predicting rewards and stamping in useful actions, while also being a modulator of behavioural vigour. By contrast, although choosing correct actions and executing them vigorously in the face of adversity is at least as important, our understanding of learning and behaviour in aversive settings is less well developed. We examine aversive processing through the medium of the role of dopamine and targets such as D2 receptors in the striatum. We consider critical factors such as the degree of control that an animal believes it exerts over key aspects of its environment, the distinction between 'better' and 'good' actual or predicted future states, and the potential requirement for a particular form of opponent to dopamine to ensure proper calibration of state values.

Tamping Ramping: Algorithmic, Implementational, and Computational Explanations of Phasic Dopamine Signals in the Accumbens.

Substantial evidence suggests that the phasic activity of dopamine neurons represents reinforcement learning's temporal difference prediction error. However, recent reports of ramp-like increases in dopamine concentration in the striatum when animals are about to act, or are about to reach rewards, appear to pose a challenge to established thinking. This is because the implied activity is persistently predictable by preceding stimuli, and so cannot arise as this sort of prediction error. Here, we explore three possible accounts of such ramping signals: (a) the resolution of uncertainty about the timing of action; (b) the direct influence of dopamine over mechanisms associated with making choices; and (c) a new model of discounted vigour. Collectively, these suggest that dopamine ramps may be explained, with only minor disturbance, by standard theoretical ideas, though urgent questions remain regarding their proximal cause. We suggest experimental approaches to disentangling which of the proposed mechanisms are responsible for dopamine ramps.

Conditional targeting of Ispd using paired Cas9 nickase and a single DNA template in mice.

CRISPR/Cas9 technology is a highly promising genome editing tool in the mouse, potentially overcoming the costs and time required for more traditional gene targeting methods in embryonic stem (ES) cells. Recently, compared to the wildtype nuclease, paired Cas9 nickase (Cas9n) combined with single guide RNA (sgRNA) molecules has been found to enhance the specificity of genome editing while reducing off-target effects. Paired Cas9n has been shown to be as efficient as Cas9 for generating insertion and deletion (indel) mutations by non-homologous end joining and targeted deletion in the genome. However, an efficient and reliable approach to the insertion of loxP sites flanking critical exon(s) to create a conditional allele of a target gene remains an elusive goal. In this study, we microinjected Cas9n RNA with sgRNAs together with a single DNA template encoding two loxP sites flanking (floxing) exon 2 of the isoprenoid synthase containing domain (Ispd) into the pronucleus and cytoplasm of C57BL/6NCr one-cell stage zygotes. After surgical transfer, one F0 mouse expressing a conditional allele was produced (at a frequency of ∼8% of live pups born). The floxed allele was transmitted through the germline to F1 progeny, and could be successfully recombined using Cre recombinase. This study indicates that conditional targeting can be accomplished effectively using paired Cas9n and a single DNA template.

Context-dependent decision-making: a simple Bayesian model.

Many phenomena in animal learning can be explained by a context-learning process whereby an animal learns about different patterns of relationship between environmental variables. Differentiating between such environmental regimes or 'contexts' allows an animal to rapidly adapt its behaviour when context changes occur. The current work views animals as making sequential inferences about current context identity in a world assumed to be relatively stable but also capable of rapid switches to previously observed or entirely new contexts. We describe a novel decision-making model in which contexts are assumed to follow a Chinese restaurant process with inertia and full Bayesian inference is approximated by a sequential-sampling scheme in which only a single hypothesis about current context is maintained. Actions are selected via Thompson sampling, allowing uncertainty in parameters to drive exploration in a straightforward manner. The model is tested on simple two-alternative choice problems with switching reinforcement schedules and the results compared with rat behavioural data from a number of T-maze studies. The model successfully replicates a number of important behavioural effects: spontaneous recovery, the effect of partial reinforcement on extinction and reversal, the overtraining reversal effect, and serial reversal-learning effects.

Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats.

Learning to form appropriate, task-relevant working memory representations is a complex process central to cognition. Gating models frame working memory as a collection of past observations and use reinforcement learning (RL) to solve the problem of when to update these observations. Investigation of how gating models relate to brain and behavior remains, however, at an early stage. The current study sought to explore the ability of simple RL gating models to replicate rule learning behavior in rats. Rats were trained in a maze-based spatial learning task that required animals to make trial-by-trial choices contingent upon their previous experience. Using an abstract version of this task, we tested the ability of two gating algorithms, one based on the Actor-Critic and the other on the State-Action-Reward-State-Action (SARSA) algorithm, to generate behavior consistent with the rats'. Both models produced rule-acquisition behavior consistent with the experimental data, though only the SARSA gating model mirrored faster learning following rule reversal. We also found that both gating models learned multiple strategies in solving the initial task, a property which highlights the multi-agent nature of such models and which is of importance in considering the neural basis of individual differences in behavior.

The role of ethnic identity in symptoms of anxiety and depression in African Americans.

Ethnic identity has been identified as a factor contributing to resilience and coping in African Americans. Ethnic identity includes positive feelings of ethnic affirmation and belonging, appreciation for one's ethnic identity, and increased ethnic behaviors. This study examines the role of ethnic identity in symptoms of anxiety and depression. Participants were an adult student and community sample (N=572), administered the Beck Anxiety Inventory (BAI), Center for Epidemiologic Studies of Depression Scale (CES-D), State Trait Anxiety Inventory-state portion (STAI-S), and Multigroup Ethnic Identity Measure (MEIM). Compared to European Americans, African Americans reported significantly greater depression and more negative state anxiety, as well as higher levels of ethnic identity. For African Americans, higher ethnic identity was correlated to reduced anxiety and depression, whereas this was not true for European Americans. Findings support the proposition that a strong, positive ethnic identity may serve a protective role among African Americans by moderating the relationship between discriminatory experiences and psychological well-being. An Afrocentric perspective may also contribute to reduced anxiety due to a greater emphasis on a present versus future-oriented worldview. Clinical implications and directions for future research are discussed.