Sex mechanisms as nonbinary influences on cognitive diversity.

Essentially all neuropsychiatric diagnoses show some degree of sex and/or gender differences in their etiology, diagnosis, or prognosis. As a result, the roles of sex-related variables in behavior and cognition are of strong interest to many, with several lines of research showing effects on executive functions and value-based decision making in particular. These findings are often framed within a sex binary, with behavior of females described as less optimal than male "defaults"-- a framing that pits males and females against each other and deemphasizes the enormous overlap in fundamental neural mechanisms across sexes. Here, we propose an alternative framework in which sex-related factors encompass just one subset of many sources of valuable diversity in cognition. First, we review literature establishing multidimensional, nonbinary impacts of factors related to sex chromosomes and endocrine mechanisms on cognition, focusing on value- based decision-making tasks. Next, we present two suggestions for nonbinary interpretations and analyses of sex-related data that can be implemented by behavioral neuroscientists without devoting laboratory resources to delving into mechanisms underlying sex differences. We recommend (1) shifting interpretations of behavior away from performance metrics and towards strategy assessments to avoid the fallacy that the performance of one sex is worse than another; and (2) asking how much variance sex explains in measures and whether any differences are mosaic rather than binary, to avoid assuming that sex differences in separate measures are inextricably correlated. Nonbinary frameworks in research on cognition will allow neuroscience to represent the full spectrum of brains and behaviors.

Exposure to in utero inflammation increases locomotor activity, alters cognitive performance and drives vulnerability to cognitive performance deficits after acute immune activation.

Fetal exposure to intrauterine inflammation (IUI) affects brain development. Using intrauterine lipopolysaccharide (LPS) administration to induce a localized, rather than a systemic, inflammation, we have previously shown that IUI increases cytokine expression and microglia number, and reduces white matter in the brains of exposed offspring. Clinical data suggest that IUI may increase the risk for cognitive and neurodevelopmental disorders, however, IUI is often found in the context of preterm birth, making it difficult to disentangle the adverse effects of inflammation from those related to prematurity. Therefore, using a mouse model of IUI that does not involve preterm birth, operant tasks were used to evaluate motivation, attention, impulsivity, and locomotion. IUI-exposed offspring were found to have increased locomotion and increased motivation (females only), and testing in the 5-choice serial reaction time task (5-CSRTT) showed that IUI-exposed offspring performed more trials and could respond accurately at a shorter stimulus length. We have previously shown that IUI animals have a potentiated cytokine response to a "second hit" (acute LPS injection) in adulthood, so animals' performance in the 5CSRTT was evaluated following an acute injection of LPS. As opposed to the improved performance observed under baseline conditions, IUI exposed animals demonstrated a greater decrease in performance after an acute LPS administration. To identify putative molecular mechanisms underlying this potentiated decline in cognitive performance, PFC samples were collected immediately after post-LPS cognitive testing and targeted gene expression analysis was correlated with specific measures of cognitive performance. Three receptors important for neuron-microglia crosstalk were found to correlate with task performance in the males following acute LPS administration. These data demonstrate that early life exposure to localized inflammation of the uterus, in the absence of prematurity, increases locomotor activity and improves some aspects of cognitive performance, but drives a vulnerability for adult cognitive performance deficits in response to acute infection.

Methyl donor supplementation alters cognitive performance and motivation in female offspring from high-fat diet-fed dams.

During gestation, fetal nutrition is entirely dependent on maternal diet. Maternal consumption of excess fat during pregnancy has been linked to an increased risk of neurologic disorders in offspring, including attention deficit/hyperactivity disorder, autism, and schizophrenia. In a mouse model, high-fat diet (HFD)-fed offspring have cognitive and executive function deficits as well as whole-genome DNA and promoter-specific hypomethylation in multiple brain regions. Dietary methyl donor supplementation during pregnancy or adulthood has been used to alter DNA methylation and behavior. Given that extensive brain development occurs during early postnatal life-particularly within the prefrontal cortex (PFC), a brain region critical for executive function-we examined whether early life methyl donor supplementation (e.g., during adolescence) could ameliorate executive function deficits observed in offspring that were exposed to maternal HFD. By using operant testing, progressive ratio, and the PFC-dependent 5-choice serial reaction timed task (5-CSRTT), we determined that F1 female offspring (B6D2F1/J) from HFD-fed dams have decreased motivation (decreased progressive ratio breakpoint) and require a longer stimulus length to complete the 5-CSRTT task successfully, whereas early life methyl donor supplementation increased motivation and shortened the minimum stimulus length required for a correct response in the 5-CSRTT. Of interest, we found that expression of 2 chemokines, CCL2 and CXCL10, correlated with the median stimulus length in the 5-CSRTT. Furthermore, we found that acute adult supplementation of methyl donors increased motivation in HFD-fed offspring and those who previously received supplementation with methyl donors. These data point to early life as a sensitive time during which dietary methyl donor supplementation can alter PFC-dependent cognitive behaviors.-McKee, S. E., Grissom, N. M., Herdt, C. T., Reyes, T. M. Methyl donor supplementation alters cognitive performance and motivation in female offspring from high-fat diet-fed dams.

Suboptimal nutrition in early life affects the inflammatory gene expression profile and behavioral responses to stressors.

Nutritional conditions in early life can have a lasting impact on health and disease risk, though the underlying mechanisms are incompletely understood. In the healthy individual, physiological and behavioral responses to stress are coordinated in such a way as to mobilize resources necessary to respond to the stressor and to terminate the stress response at the appropriate time. Induction of proinflammatory gene expression within the brain is one such example that is initiated in response to both physiological and psychological stressors, and is the focus of the current study. We tested the hypothesis that early life nutrition would impact the proinflammatory transcriptional response to a stressor. Pregnant and lactating dams were fed one of three diets; a low-protein diet, a high fat diet, or the control diet through pregnancy and lactation. Adult male offspring were then challenged with either a physiological stressor (acute lipopolysaccharide injection, IP) or a psychological stressor (15 min restraint). Expression of 20 proinflammatory and stress-related genes was evaluated in hypothalamus, prefrontal cortex, amygdala and ventral tegmental area. In a second cohort, behavioral responses (food intake, locomotor activity, metabolic rate) were evaluated. Offspring from low protein fed dams showed a generally reduced transcriptional response, particularly to LPS, and resistance to behavioral changes associated with restraint, while HF offspring showed an exacerbated transcriptional response within the PFC, a reduced transcriptional response in hypothalamus and amygdala, and an exacerbation of the LPS-induced reduction of locomotor activity. The present data identify differential proinflammatory transcriptional responses throughout the brain driven by perinatal diet as an important variable that may affect risk or resilience to stressors.

Intrauterine inflammation induces sex-specific effects on neuroinflammation, white matter, and behavior.

Exposure to inflammation during pregnancy has been linked to adverse neurodevelopmental consequences for the offspring. One common route through which a developing fetus is exposed to inflammation is with intrauterine inflammation. To that end, we utilized an animal model of intrauterine inflammation (IUI; intrauterine lipopolysaccharide (LPS) administration, 50µg, E15) to assess placental and fetal brain inflammatory responses, white matter integrity, anxiety-related behaviors (elevated zero maze, light dark box, open field), microglial counts, and the CNS cytokine response to an acute injection of LPS in both males and females. These studies revealed that for multiple endpoints (fetal brain cytokine levels, cytokine response to adult LPS challenge) male IUI offspring were uniquely affected by intrauterine inflammation, while for other endpoints (behavior, microglial number) both sexes were similarly affected. These data advance our understanding of sex-specific effects of early life exposure to inflammation in a translationally- relevant model.

Voluntary exercise blocks Western diet-induced gene expression of the chemokines CXCL10 and CCL2 in the prefrontal cortex.

Obesity increases inflammation, both peripherally and centrally, and exercise can ameliorate some of the negative health outcomes associated with obesity. Within the brain, the effect of obesity on inflammation has been well characterized in the hypothalamus and hippocampus, but has been relatively understudied in other brain regions. The current study was designed to address two primary questions; (1) whether western diet (high fat/high sucrose) consumption would increase markers of inflammation in the prefrontal cortex and (2) whether concurrent voluntary wheel running would ameliorate any inflammation. Adult male mice were exposed to a western diet or a control diet for 8weeks. Concurrently, half the animals were given running wheels in their home cages, while half did not have access to wheels. At the conclusion of the study, prefrontal cortex was removed and expression of 18 proinflammatory genes was assayed. Expression of a number of proinflammatory molecules was upregulated by consumption of the western diet. For two chemokines, chemokine (C-C motif) ligand 2 (CCL2) and C-X-C motif chemokine 10 (CXCL10), voluntary exercise blocked the increase in the expression of these genes. Cluster analysis confirmed that the majority of the tested genes were upregulated by western diet, and identified another small cluster of genes that were downregulated by either diet or exercise. These data identify a proinflammatory phenotype within the prefrontal cortex of mice fed a western diet, and indicate that chemokine induction can be blocked by voluntary exercise.

Epigenetic programming of reward function in offspring: a role for maternal diet.

Early life development, through gestation and lactation, represents a timeframe of extreme vulnerability for the developing fetus in general, and for the central nervous system in particular. An adverse perinatal environment can have a lasting negative impact on brain development, increasing the risk for developmental disorders and broader psychopathologies. A major determinant of the fetal developmental environment is maternal diet. The present review summarizes the current literature regarding the effect of poor maternal perinatal nutrition on offspring brain development, with an emphasis on reward-related neural systems and behaviors. Epigenetic mechanisms represent a likely link between maternal diet and persistent changes in offspring brain development, and these mechanisms are presented and discussed within the context of perinatal maternal nutrition.

Sex Differences in Morphine Sensitivity of Neuroligin-3 Knockout Mice.

Sex has a strong influence on the prevalence and course of brain conditions, including autism spectrum disorders. The mechanistic basis for these sex differences remains poorly understood, due in part to historical bias in biomedical research favoring analysis of male subjects, and the exclusion of female subjects. For example, studies of male mice carrying autism-associated mutations in neuroligin-3 are over-represented in the literature, including our own prior work showing diminished responses to chronic morphine exposure in male neuroligin-3 knockout mice. We therefore studied how constitutive and conditional genetic knockout of neuroligin-3 affects morphine sensitivity of female mice. In contrast to male mice, female neuroligin-3 knockout mice showed normal psychomotor sensitization after chronic morphine exposure. However, in the absence of neuroligin-3 expression, both female and male mice show a similar change in the topography of locomotor stimulation produced by morphine. Conditional genetic deletion of neuroligin-3 from dopamine neurons increased the locomotor response of female mice to high doses of morphine, contrasting with the decrease in psychomotor sensitization caused by the same manipulation in male mice. Together, our data reveal that knockout of neuroligin-3 has both common and distinct effects on morphine sensitivity in female and male mice. These results also support the notion that female sex can confer resilience against the impact of autism-associated gene variants.

Individual differences in uncertainty evaluation explain opposing exploratory behaviors in anxiety and apathy.

Navigating uncertain environments is a fundamental challenge for adaptive behavior, and affective states such as anxiety and apathy can profoundly influence an individual's response to uncertainty. Uncertainty encompasses both volatility and stochasticity, where volatility refers to how rapidly the environment changes and stochasticity describes outcomes resulting from random chance. This study investigates how anxiety and apathy modulate perceptions of environmental volatility and stochasticity and how these perceptions impact exploratory behavior. In a large online sample (N = 1001), participants completed a restless three-armed bandit task, and their choices were analyzed using latent state models to quantify the computational processes. We found that anxious individuals attributed uncertainty more to environmental volatility than stochasticity, leading to increased exploration, particularly after reward omission. Conversely, apathetic individuals perceived uncertainty as more stochastic than volatile, resulting in decreased exploration. The ratio of perceived volatility to stochasticity mediated the relationship between anxiety and exploratory behavior following adverse outcomes. These findings reveal distinct computational mechanisms underlying anxiety and apathy in uncertain environments. Our results provide a novel framework for understanding the cognitive and affective processes driving adaptive and potentially maladaptive behaviors under uncertainty, with implications for the characterization and treatment of neuropsychiatric disorders.

Dopamine and norepinephrine differentially mediate the exploration-exploitation tradeoff.

The catecholamines dopamine (DA) and norepinephrine (NE) have been repeatedly implicated in neuropsychiatric vulnerability, in part via their roles in mediating the decision making processes. Although the two neuromodulators share a synthesis pathway and are co-activated under states of arousal, they engage in distinct circuits and roles in modulating neural activity across the brain. However, in the computational neuroscience literature, they have been assigned similar roles in modulating the latent cognitive processes of decision making, in particular the exploration-exploitation tradeoff. Revealing how each neuromodulator contributes to this explore-exploit process will be important in guiding mechanistic hypotheses emerging from computational psychiatric approaches. To understand the differences and overlaps of the roles of these two catecholamine systems in regulating exploration and exploitation, a direct comparison using the same dynamic decision making task is needed. Here, we ran mice in a restless two-armed bandit task, which encourages both exploration and exploitation. We systemically administered a nonselective DA receptor antagonist (flupenthixol), a nonselective DA receptor agonist (apomorphine), a NE beta-receptor antagonist (propranolol), and a NE beta-receptor agonist (isoproterenol), and examined changes in exploration within subjects across sessions. We found a bidirectional modulatory effect of dopamine receptor activity on the level of exploration. Increasing dopamine activity decreased exploration and decreasing dopamine activity increased exploration. Beta-noradrenergic receptor activity also modulated exploration, but the modulatory effect was mediated by sex. Reinforcement learning model parameters suggested that dopamine modulation affected exploration via decision noise and norepinephrine modulation affected exploration via outcome sensitivity. Together, these findings suggested that the mechanisms that govern the transition between exploration and exploitation are sensitive to changes in both catecholamine functions and revealed differential roles for NE and DA in mediating exploration.

A low dimensional manifold of human exploratory behavior reveals opposing roles for apathy and anxiety.

Exploration-exploitation decision-making is a feature of daily life that is altered in a number of neuropsychiatric conditions. Humans display a range of exploration and exploitation behaviors, which can be affected by apathy and anxiety. It remains unknown how factors underlying decision-making generate the spectrum of observed exploration-exploitation behavior and how they relate to states of anxiety and apathy. Here, we report a latent structure underlying sequential exploration and exploitation decisions that explains variation in anxiety and apathy. 1001 participants in a gender-balanced sample completed a three-armed restless bandit task along with psychiatric symptom surveys. Using dimensionality reduction methods, we found that decision sequences reduced to a low-dimensional manifold. The axes of this manifold explained individual differences in the balance between states of exploration and exploitation and the stability of those states, as determined by a statistical mechanics model of decision-making. Position along the balance axis was correlated with opposing symptoms of behavioral apathy and anxiety, while position along the stability axis correlated with the level of emotional apathy. This result resolves a paradox over how these symptoms can be correlated in samples but have opposite effects on behavior. Furthermore, this work provides a basis for using behavioral manifolds to reveal relationships between behavioral dynamics and affective states, with important implications for behavioral measurement approaches to neuropsychiatric conditions.

Integrating Causal Discovery and Clinically-Relevant Insights to Explore Directional Relationships between Autistic Features, Sex at Birth, and Cognitive Abilities.

Prevalence in autism spectrum disorder (ASD) diagnosis has long been strongly male-biased. Yet, consensus has not been reached on mechanisms and clinical features that underlie sex-based discrepancies. Whereas females may be under-diagnosed because of inconsistencies in diagnostic/ascertainment procedures (sex-biased criteria, social camouflaging), diagnosed males may have exhibited more overt behaviors (e.g., hyperactivity, aggression) that prompted clinical evaluation. Applying a novel network-theory-based approach, we extracted data-driven, clinically-relevant insights from a large, well-characterized sample (Simons Simplex Collection) of 2175 autistic males (Ages = 8.9±3.5 years) and 334 autistic females (Ages = 9.2±3.7 years). Exploratory factor analysis (EFA) and expert clinical review reduced data dimensionality to 15 factors of interest. To offset inherent confounds of an imbalanced sample, we identified a subset of males (N=331) matched to females on key variables (Age, IQ) and applied data-driven CDA using Greedy Fast Causal Inference (GFCI) for three groups (All Females, All Males, and Matched Males). Structural equation modeling (SEM) extracted measures of model fit and effect sizes for causal relationships between sex, age, and, IQ on EFA-selected factors capturing phenotypic representations of autism across sensory, social, and restricted and repetitive behavior domains. Our methodology unveiled sex-specific directional relationships to inform developmental outcomes and targeted interventions.

Learning signatures of decision making from many individuals playing the same game.

Human behavior is incredibly complex and the factors that drive decision making--from instinct, to strategy, to biases between individuals--often vary over multiple timescales. In this paper, we design a predictive framework that learns representations to encode an individual's 'behavioral style', i.e. long-term behavioral trends, while simultaneously predicting future actions and choices. The model explicitly separates representations into three latent spaces: the recent past space, the short-term space, and the long-term space where we hope to capture individual differences. To simultaneously extract both global and local variables from complex human behavior, our method combines a multi-scale temporal convolutional network with latent prediction tasks, where we encourage embeddings across the entire sequence, as well as subsets of the sequence, to be mapped to similar points in the latent space. We develop and apply our method to a large-scale behavioral dataset from 1,000 humans playing a 3-armed bandit task, and analyze what our model's resulting embeddings reveal about the human decision making process. In addition to predicting future choices, we show that our model can learn rich representations of human behavior over multiple timescales and provide signatures of differences in individuals.

Prolonged Physiological Stress Is Associated With a Lower Rate of Exploratory Learning That Is Compounded by Depression.

BACKGROUND: Stress is a major risk factor for depression, and both are associated with important changes in decision-making patterns. However, decades of research have only weakly connected physiological measurements of stress to the subjective experience of depression. Here, we examined the relationship between prolonged physiological stress, mood, and explore-exploit decision making in a population navigating a dynamic environment under stress: health care workers during the COVID-19 pandemic. METHODS: We measured hair cortisol levels in health care workers who completed symptom surveys and performed an explore-exploit restless-bandit decision-making task; 32 participants were included in the final analysis. Hidden Markov and reinforcement learning models assessed task behavior. RESULTS: Participants with higher hair cortisol exhibited less exploration (r = -0.36, p = .046). Higher cortisol levels predicted less learning during exploration (ß = -0.42, false discovery rate [FDR]-corrected p [pFDR] = .022). Importantly, mood did not independently correlate with cortisol concentration, but rather explained additional variance (ß = 0.46, pFDR = .022) and strengthened the relationship between higher cortisol and lower levels of exploratory learning (ß = -0.47, pFDR = .022) in a joint model. These results were corroborated by a reinforcement learning model, which revealed less learning with higher hair cortisol and low mood (ß = -0.67, pFDR = .002). CONCLUSIONS: These results imply that prolonged physiological stress may limit learning from new information and lead to cognitive rigidity, potentially contributing to burnout. Decision-making measures link subjective mood states to measured physiological stress, suggesting that they should be incorporated into future biomarker studies of mood and stress conditions.

Learning signatures of decision making from many individuals playing the same game.

Human behavior is incredibly complex and the factors that drive decision making-from instinct, to strategy, to biases between individuals-often vary over multiple timescales. In this paper, we design a predictive framework that learns representations to encode an individual's 'behavioral style', i.e. long-term behavioral trends, while simultaneously predicting future actions and choices. The model explicitly separates representations into three latent spaces: the recent past space, the short-term space, and the long-term space where we hope to capture individual differences. To simultaneously extract both global and local variables from complex human behavior, our method combines a multi-scale temporal convolutional network with latent prediction tasks, where we encourage embeddings across the entire sequence, as well as subsets of the sequence, to be mapped to similar points in the latent space. We develop and apply our method to a large-scale behavioral dataset from 1,000 humans playing a 3-armed bandit task, and analyze what our model's resulting embeddings reveal about the human decision making process. In addition to predicting future choices, we show that our model can learn rich representations of human behavior over multiple timescales and provide signatures of differences in individuals.

Sequential delay and probability discounting tasks in mice reveal anchoring effects partially attributable to decision noise.

Delay discounting and probability discounting decision making tasks in rodent models have high translational potential. However, it is unclear whether the discounted value of the large reward option is the main contributor to variability in animals' choices in either task, which may limit translation to humans. Male and female mice underwent sessions of delay and probability discounting in sequence to assess how choice behavior adapts over experience with each task. To control for "anchoring" (persistent choices based on the initial delay or probability), mice experienced "Worsening" schedules where the large reward was offered under initially favorable conditions that became less favorable during testing, followed by "Improving" schedules where the large reward was offered under initially unfavorable conditions that improved over a session. During delay discounting, both male and female mice showed elimination of anchoring effects over training. In probability discounting, both sexes of mice continued to show some anchoring even after months of training. One possibility is that "noisy", exploratory choices could contribute to these persistent anchoring effects, rather than constant fluctuations in value discounting. We fit choice behavior in individual animals using models that included both a value-based discounting parameter and a decision noise parameter that captured variability in choices deviating from value maximization. Changes in anchoring behavior over time were tracked by changes in both the value and decision noise parameters in delay discounting, but by the decision noise parameter in probability discounting. Exploratory decision making was also reflected in choice response times that tracked the degree of conflict caused by both uncertainty and temporal cost, but was not linked with differences in locomotor activity reflecting chamber exploration. Thus, variable discounting behavior in mice can result from changes in exploration of the decision options rather than changes in reward valuation.

Computational validity: using computation to translate behaviours across species.

We propose a new conceptual framework (computational validity) for translation across species and populations based on the computational similarity between the information processing underlying parallel tasks. Translating between species depends not on the superficial similarity of the tasks presented, but rather on the computational similarity of the strategies and mechanisms that underlie those behaviours. Computational validity goes beyond construct validity by directly addressing questions of information processing. Computational validity interacts with circuit validity as computation depends on circuits, but similar computations could be accomplished by different circuits. Because different individuals may use different computations to accomplish a given task, computational validity suggests that behaviour should be understood through the subject's point of view; thus, behaviour should be characterized on an individual level rather than a task level. Tasks can constrain the computational algorithms available to a subject and the observed subtleties of that behaviour can provide information about the computations used by each individual. Computational validity has especially high relevance for the study of psychiatric disorders, given the new views of psychiatry as identifying and mediating information processing dysfunctions that may show high inter-individual variability, as well as for animal models investigating aspects of human psychiatric disorders. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

Sex differences in learning from exploration.

Sex-based modulation of cognitive processes could set the stage for individual differences in vulnerability to neuropsychiatric disorders. While value-based decision making processes in particular have been proposed to be influenced by sex differences, the overall correct performance in decision making tasks often show variable or minimal differences across sexes. Computational tools allow us to uncover latent variables that define different decision making approaches, even in animals with similar correct performance. Here, we quantify sex differences in mice in the latent variables underlying behavior in a classic value-based decision making task: a restless two-armed bandit. While male and female mice had similar accuracy, they achieved this performance via different patterns of exploration. Male mice tended to make more exploratory choices overall, largely because they appeared to get 'stuck' in exploration once they had started. Female mice tended to explore less but learned more quickly during exploration. Together, these results suggest that sex exerts stronger influences on decision making during periods of learning and exploration than during stable choices. Exploration during decision making is altered in people diagnosed with addictions, depression, and neurodevelopmental disabilities, pinpointing the neural mechanisms of exploration as a highly translational avenue for conferring sex-modulated vulnerability to neuropsychiatric diagnoses.

When faced with a decision to make, humans and other animals reflect on past experiences of similar situations to choose the best option. However, in an uncertain situation, this decision process requires balancing two competing priorities: exploiting options that are expected to be rewarding (exploitation), and exploring alternatives that could be more valuable (exploration). Decision making and exploration are disrupted in many mental disorders, some of which can differ in either presentation or risk of development across women and men. This raises the question of whether sex differences in exploration and exploitation could contribute to the vulnerability to these conditions. To shed light on this question, Chen et al. studied exploration in male and female mice as they played a video game. The mice had the option to touch one of two locations on a screen for a chance to win a small reward. The likelihood of success was different between the two options, and so the mice were incentivized to determine which was the more rewarding button. While the mice were similarly successful in finding rewards regardless of sex, on average male mice were more likely to keep exploring between the options while female mice more quickly gained confidence in an option. These differences were stronger during uncertain periods of learning and exploration than when making choices in a well-known situation, indicating that periods of uncertainty are when the influence of sex on cognition are most visible. However, not every female or male mouse was the same ­ there was as much variability within a sex as was seen between sexes. These results indicate that sex mechanisms, along with many other influences cause individual differences in the cognitive processes important for decision making. The approach used by Chen et al. could help to study individual differences in cognition in other species, and shed light on how individual differences in decision-making processes could contribute to risk and resilience to mental disorders.

Divergent Strategies for Learning in Males and Females.

A frequent assumption in value-based decision-making tasks is that agents make decisions based on the feature dimension that reward probabilities vary on. However, in complex, multidimensional environments, stimuli can vary on multiple dimensions at once, meaning that the feature deserving the most credit for outcomes is not always obvious. As a result, individuals may vary in the strategies used to sample stimuli across dimensions, and these strategies may have an unrecognized influence on decision-making. Sex is a proxy for multiple genetic and endocrine influences on behavior, including how environments are sampled. In this study, we examined the strategies adopted by female and male mice as they learned the value of stimuli that varied in both image and location in a visually cued two-armed bandit, allowing two possible dimensions to learn about. Female mice acquired the correct image-value associations more quickly than male mice, preferring a fundamentally different strategy. Female mice were more likely to constrain their decision-space early in learning by preferentially sampling one location over which images varied. Conversely, male mice were more likely to be inconsistent, changing their choice frequently and responding to the immediate experience of stochastic rewards. Individual strategies were related to sex-biased changes in neuronal activation in early learning. Together, we find that in mice, sex is associated with divergent strategies for sampling and learning about the world, revealing substantial unrecognized variability in the approaches implemented during value-based decision making.

Habituation to repeated stress: get used to it.

Habituation, as described in the landmark paper by Thompson et al. [Thompson, R. F., & Spencer, W. A. (1966). Habituation: A model phenomenon for the study of neuronal substrates of behavior. Psychological Review, 73(1), 16-43], is a form of simple, nonassociative learning in which the magnitude of the response to a specific stimulus decreases with repeated exposure to that stimulus. A variety of neuronal and behavioral responses have been shown to be subject to habituation based on the criteria presented in that paper. It has been known for several decades that the magnitude of hypothalamic-pituitary-adrenal (HPA) activation occurring in response to a stressor declines with repeated exposure to that same stressor. For some time this decline has been referred to as "habituation" in the stress neurobiology literature. However, how this usage compares to the definition proposed by Thompson and Spencer has not been systematically addressed. For this special issue, we review the stress neurobiology literature and examine the support available for considering declines in HPA response to repeated stress to be response habituation in the sense defined by Thompson and Spencer. We conclude that habituation of HPA activity meets many, but not all, important criteria for response habituation, supporting the use of this term within the context of repeated stress. However, we also propose that response habituation can, at best, only partially explain the phenomenon of HPA habituation, which also involves well-known negative feedback mechanisms, activation of broad stress-related neural circuitry and potentially more complex associative learning mechanisms.