Experimental biology can inform our understanding of food insecurity.

Food insecurity is a major public health issue. Millions of households worldwide have intermittent and unpredictable access to food and this experience is associated with greater risk for a host of negative health outcomes. While food insecurity is a contemporary concern, we can understand its effects better if we acknowledge that there are ancient biological programs that evolved to respond to the experience of food scarcity and uncertainty, and they may be particularly sensitive to food insecurity during development. Support for this conjecture comes from common findings in several recent animal studies that have modeled insecurity by manipulating predictability of food access in various ways. Using different experimental paradigms in different species, these studies have shown that experience of insecure access to food can lead to changes in weight, motivation and cognition. Some of these studies account for changes in weight through changes in metabolism, while others observe increases in feeding and motivation to work for food. It has been proposed that weight gain is an adaptive response to the experience of food insecurity as 'insurance' in an uncertain future, while changes in motivation and cognition may reflect strategic adjustments in foraging behavior. Animal studies also offer the opportunity to make in-depth controlled studies of mechanisms and behavior. So far, there is evidence that the experience of food insecurity can impact metabolic efficiency, reproductive capacity and dopamine neuron synapses. Further work on behavior, the central and peripheral nervous system, the gut and liver, along with variation in age of exposure, will be needed to better understand the full body impacts of food insecurity at different stages of development.

Goal-directed learning in adolescence: neurocognitive development and contextual influences.

Adolescence is a time during which we transition to independence, explore new activities and begin pursuit of major life goals. Goal-directed learning, in which we learn to perform actions that enable us to obtain desired outcomes, is central to many of these processes. Currently, our understanding of goal-directed learning in adolescence is itself in a state of transition, with the scientific community grappling with inconsistent results. When we examine metrics of goal-directed learning through the second decade of life, we find that many studies agree there are steady gains in performance in the teenage years, but others report that adolescent goal-directed learning is already adult-like, and some find adolescents can outperform adults. To explain the current variability in results, sophisticated experimental designs are being applied to test learning in different contexts. There is also increasing recognition that individuals of different ages and in different states will draw on different neurocognitive systems to support goal-directed learning. Through adoption of more nuanced approaches, we can be better prepared to recognize and harness adolescent strengths and to decipher the purpose (or goals) of adolescence itself.

Nucleus accumbens dopamine release reflects Bayesian inference during instrumental learning.

Dopamine release in the nucleus accumbens has been hypothesized to signal reward prediction error, the difference between observed and predicted reward, suggesting a biological implementation for reinforcement learning. Rigorous tests of this hypothesis require assumptions about how the brain maps sensory signals to reward predictions, yet this mapping is still poorly understood. In particular, the mapping is non-trivial when sensory signals provide ambiguous information about the hidden state of the environment. Previous work using classical conditioning tasks has suggested that reward predictions are generated conditional on probabilistic beliefs about the hidden state, such that dopamine implicitly reflects these beliefs. Here we test this hypothesis in the context of an instrumental task (a two-armed bandit), where the hidden state switches repeatedly. We measured choice behavior and recorded dLight signals reflecting dopamine release in the nucleus accumbens core. Model comparison based on the behavioral data favored models that used Bayesian updating of probabilistic beliefs. These same models also quantitatively matched the dopamine measurements better than non-Bayesian alternatives. We conclude that probabilistic belief computation plays a fundamental role in instrumental performance and associated mesolimbic dopamine signaling.

The interpretation of computational model parameters depends on the context.

Reinforcement Learning (RL) models have revolutionized the cognitive and brain sciences, promising to explain behavior from simple conditioning to complex problem solving, to shed light on developmental and individual differences, and to anchor cognitive processes in specific brain mechanisms. However, the RL literature increasingly reveals contradictory results, which might cast doubt on these claims. We hypothesized that many contradictions arise from two commonly-held assumptions about computational model parameters that are actually often invalid: That parameters generalize between contexts (e.g. tasks, models) and that they capture interpretable (i.e. unique, distinctive) neurocognitive processes. To test this, we asked 291 participants aged 8-30 years to complete three learning tasks in one experimental session, and fitted RL models to each. We found that some parameters (exploration / decision noise) showed significant generalization: they followed similar developmental trajectories, and were reciprocally predictive between tasks. Still, generalization was significantly below the methodological ceiling. Furthermore, other parameters (learning rates, forgetting) did not show evidence of generalization, and sometimes even opposite developmental trajectories. Interpretability was low for all parameters. We conclude that the systematic study of context factors (e.g. reward stochasticity; task volatility) will be necessary to enhance the generalizability and interpretability of computational cognitive models.

The maturation of exploratory behavior in adolescent Mus spicilegus on two photoperiods.

Dispersal from the natal site or familial group is a core milestone of adolescent development in many species. A wild species of mouse, Mus spicilegus, presents an exciting model in which to study adolescent development and dispersal because it shows different life history trajectory depending on season of birth. M. spicilegus born in spring and summer on long days (LD) disperse in the first 3 months of life, while M. spicilegus born on shorter autumnal days (SD) delay dispersal through the wintertime. We were interested in using these mice in a laboratory context to compare age-matched mice with differential motivation to disperse. To first test if we could find a proxy for dispersal related behavior in the laboratory environment, we measured open field and novel object investigation across development in M. spicilegus raised on a LD 12 h:12 h light:dark cycle. We found that between the first and second month of life, distance traveled and time in center of the open field increased significantly with age in M. spicilegus. Robust novel object investigation was observed in all age groups and decreased between the 2nd and 3rd month of life in LD males. Compared to male C57BL/6 mice, male M. spicilegus traveled significantly longer distances in the open field but spent less time in the center of the field. However, when a novel object was placed in the center of the open field, Male M. spicilegus, were significantly more willing to contact and mount it. To test if autumnal photoperiod affects exploratory behavior in M. spicilegus in a laboratory environment, we reared a cohort of M. spicilegus on a SD 10 h:14 h photoperiod and tested their exploratory behavior at P60-70. At this timepoint, we found SD rearing had no effect on open field metrics, but led to reduced novel object investigation. We also observed that in P60-70 males, SD reared M. spicilegus weighed less than LD reared M. spicilegus. These observations establish that SD photoperiod can delay weight gain and blunt some, but not all forms of exploratory behavior in adolescent M. spicilegus.

Transient food insecurity during the juvenile-adolescent period affects adult weight, cognitive flexibility, and dopamine neurobiology.

A major challenge for neuroscience, public health, and evolutionary biology is to understand the effects of scarcity and uncertainty on the developing brain. Currently, a significant fraction of children and adolescents worldwide experience insecure access to food. The goal of our work was to test in mice whether the transient experience of insecure versus secure access to food during the juvenile-adolescent period produced lasting differences in learning, decision-making, and the dopamine system in adulthood. We manipulated feeding schedules in mice from postnatal day (P)21 to P40 as food insecure or ad libitum and found that when tested in adulthood (after P60), males with different developmental feeding history showed significant differences in multiple metrics of cognitive flexibility in learning and decision-making. Adult females with different developmental feeding history showed no differences in cognitive flexibility but did show significant differences in adult weight. We next applied reinforcement learning models to these behavioral data. The best fit models suggested that in males, developmental feeding history altered how mice updated their behavior after negative outcomes. This effect was sensitive to task context and reward contingencies. Consistent with these results, in males, we found that the two feeding history groups showed significant differences in the AMPAR/NMDAR ratio of excitatory synapses on nucleus-accumbens-projecting midbrain dopamine neurons and evoked dopamine release in dorsal striatal targets. Together, these data show in a rodent model that transient differences in feeding history in the juvenile-adolescent period can have significant impacts on adult weight, learning, decision-making, and dopamine neurobiology.

Activation, but not inhibition, of the indirect pathway disrupts choice rejection in a freely moving, multiple-choice foraging task.

The dorsomedial striatum (DMS) plays a key role in action selection, but less is known about how direct and indirect pathway spiny projection neurons (dSPNs and iSPNs, respectively) contribute to choice rejection in freely moving animals. Here, we use pathway-specific chemogenetic manipulation during a serial choice foraging task to test the role of dSPNs and iSPNs in learned choice rejection. We find that chemogenetic activation, but not inhibition, of iSPNs disrupts rejection of nonrewarded choices, contrary to predictions of a simple "select/suppress" heuristic. Our findings suggest that iSPNs' role in stopping and freezing does not extend in a simple fashion to choice rejection in an ethological, freely moving context. These data may provide insights critical for the successful design of interventions for addiction or other conditions in which it is desirable to strengthen choice rejection.

Reinforcement learning and Bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal.

During adolescence, youth venture out, explore the wider world, and are challenged to learn how to navigate novel and uncertain environments. We investigated how performance changes across adolescent development in a stochastic, volatile reversal-learning task that uniquely taxes the balance of persistence and flexibility. In a sample of 291 participants aged 8-30, we found that in the mid-teen years, adolescents outperformed both younger and older participants. We developed two independent cognitive models, based on Reinforcement learning (RL) and Bayesian inference (BI). The RL parameter for learning from negative outcomes and the BI parameters specifying participants' mental models were closest to optimal in mid-teen adolescents, suggesting a central role in adolescent cognitive processing. By contrast, persistence and noise parameters improved monotonically with age. We distilled the insights of RL and BI using principal component analysis and found that three shared components interacted to form the adolescent performance peak: adult-like behavioral quality, child-like time scales, and developmentally-unique processing of positive feedback. This research highlights adolescence as a neurodevelopmental window that can create performance advantages in volatile and uncertain environments. It also shows how detailed insights can be gleaned by using cognitive models in new ways.

Sex Differences in Pubertal Circadian and Ultradian Rhythmic Development Under Semi-naturalistic Conditions.

Biological rhythms in core body temperature (CBT) provide informative markers of adolescent development under controlled laboratory conditions. However, it is unknown whether these markers are preserved under more variable, semi-naturalistic conditions, and whether CBT may therefore prove useful in a real-world setting. To evaluate this possibility, we examined fecal steroid concentrations and CBT rhythms from pre-adolescence (p26) through early adulthood (p76) in intact male and female Wistar rats under natural light and climate at the Stephen Glickman Field Station for the Study of Behavior, Ecology and Reproduction. Despite greater environmental variability, CBT markers of pubertal onset and its rhythmic progression were comparable with those previously reported in laboratory conditions in female rats and extend actigraphy-based findings in males. Specifically, sex differences emerged in CBT circadian rhythm (CR) power and amplitude prior to pubertal onset and persisted into early adulthood, with females exhibiting elevated CBT and decreased CR power compared with males. Within-day (ultradian rhythm [UR]) patterns also exhibited a pronounced sex difference associated with estrous cyclicity. Pubertal onset, defined by vaginal opening, preputial separation, and sex steroid concentrations, occurred later than previously reported under lab conditions for both sexes. Vaginal opening and increased fecal estradiol concentrations were closely tied to the commencement of 4-day oscillations in CBT and UR power. By contrast, preputial separation and the first rise in testosterone concentration were not associated with adolescent changes to CBT rhythms in male rats. Together, males and females exhibited unique temporal patterning of CBT and sex steroids across pubertal development, with tractable associations between hormonal concentrations, external development, and temporal structure in females. The preservation of these features outside the laboratory supports CBT as a strong candidate for translational pubertal monitoring under semi-naturalistic conditions in females.

Making sense of strengths and weaknesses observed in adolescent laboratory rodents.

During adolescence, rodents disperse from their natal site, find a new home, and navigate social relationships and threats. Although rats and mice in the laboratory cannot fully express these natural behaviors, they show striking changes in their affective and cognitive behavior across the adolescent period. In some laboratory-based behavior metrics, adolescent rodents fail to show the same behaviors expressed by adults, but in other metrics, adolescent behavioral performance is more robust or more flexible than at other ages. These data are often interpreted in light of proximate level analysis of development of neural circuits. It is also informative to attempt ultimate-level explanations and consider how sex and species-specific adolescent behavioral changes support dispersal, foraging, and social interactions in the wild.

Modeling changes in probabilistic reinforcement learning during adolescence.

In the real world, many relationships between events are uncertain and probabilistic. Uncertainty is also likely to be a more common feature of daily experience for youth because they have less experience to draw from than adults. Some studies suggest probabilistic learning may be inefficient in youths compared to adults, while others suggest it may be more efficient in youths in mid adolescence. Here we used a probabilistic reinforcement learning task to test how youth age 8-17 (N = 187) and adults age 18-30 (N = 110) learn about stable probabilistic contingencies. Performance increased with age through early-twenties, then stabilized. Using hierarchical Bayesian methods to fit computational reinforcement learning models, we show that all participants' performance was better explained by models in which negative outcomes had minimal to no impact on learning. The performance increase over age was driven by 1) an increase in learning rate (i.e. decrease in integration time scale); 2) a decrease in noisy/exploratory choices. In mid-adolescence age 13-15, salivary testosterone and learning rate were positively related. We discuss our findings in the context of other studies and hypotheses about adolescent brain development.

Coming of age in the frontal cortex: The role of puberty in cortical maturation.

Across species, adolescence is a period of growing independence that is associated with the maturation of cognitive, social, and affective processing. Reorganization of neural circuits within the frontal cortex is believed to contribute to the emergence of adolescent changes in cognition and behavior. While puberty coincides with adolescence, relatively little is known about which aspects of frontal cortex maturation are driven by pubertal development and gonadal hormones. In this review, we highlight existing work that suggests puberty plays a role in the maturation of specific cell types in the medial prefrontal cortex (mPFC) of rodents, and highlight possible routes by which gonadal hormones influence frontal cortical circuit development.

Adolescent Development of Biological Rhythms in Female Rats: Estradiol Dependence and Effects of Combined Contraceptives.

Adolescence is a period of continuous development, including the maturation of endogenous rhythms across systems and timescales. Although, these dynamic changes are well-recognized, their continuous structure and hormonal dependence have not been systematically characterized. Given the well-established link between core body temperature (CBT) and reproductive hormones in adults, we hypothesized that high-resolution CBT can be applied to passively monitor pubertal development and disruption with high fidelity. To examine this possibility, we used signal processing to investigate the trajectory of CBT rhythms at the within-day (ultradian), daily (circadian), and ovulatory timescales, their dependence on estradiol (E2), and the effects of hormonal contraceptives. Puberty onset was marked by a rise in fecal estradiol (fE2), followed by an elevation in CBT and circadian power. This time period marked the commencement of 4-day rhythmicity in fE2, CBT, and ultradian power marking the onset of the estrous cycle. The rise in circadian amplitude was accelerated by E2 treatment, indicating a role for this hormone in rhythmic development. Contraceptive administration in later adolescence reduced CBT and circadian power and resulted in disruption to 4-day cycles that persisted after discontinuation. Our data reveal with precise temporal resolution how biological rhythms change across adolescence and demonstrate a role for E2 in the emergence and preservation of multiscale rhythmicity. These findings also demonstrate how hormones delivered exogenously in a non-rhythmic pattern can disrupt rhythmic development. These data lay the groundwork for a future in which temperature metrics provide an inexpensive, convenient method for monitoring pubertal maturation and support the development of hormone therapies that better mimic and support human chronobiology.

What do Reinforcement Learning Models Measure? Interpreting Model Parameters in Cognition and Neuroscience.

Reinforcement learning (RL) is a concept that has been invaluable to fields including machine learning, neuroscience, and cognitive science. However, what RL entails differs between fields, leading to difficulties when interpreting and translating findings. After laying out these differences, this paper focuses on cognitive (neuro)science to discuss how we as a field might over-interpret RL modeling results. We too often assume-implicitly-that modeling results generalize between tasks, models, and participant populations, despite negative empirical evidence for this assumption. We also often assume that parameters measure specific, unique (neuro)cognitive processes, a concept we call interpretability, when evidence suggests that they capture different functions across studies and tasks. We conclude that future computational research needs to pay increased attention to implicit assumptions when using RL models, and suggest that a more systematic understanding of contextual factors will help address issues and improve the ability of RL to explain brain and behavior.

Sex and Pubertal Status Influence Dendritic Spine Density on Frontal Corticostriatal Projection Neurons in Mice.

In humans, nonhuman primates, and rodents, the frontal cortices exhibit grey matter thinning and dendritic spine pruning that extends into adolescence. This maturation is believed to support higher cognition but may also confer psychiatric vulnerability during adolescence. Currently, little is known about how specific cell types in the frontal cortex mature or whether puberty plays a role in the maturation of some cell types but not others. Here, we used mice to characterize the spatial topography and adolescent development of cross-corticostriatal (cSTR) neurons that project through the corpus collosum to the dorsomedial striatum. We found that apical spine density on cSTR neurons in the medial prefrontal cortex decreased significantly between late juvenile (P29) and young adult time points (P60), with females exhibiting higher spine density than males at both ages. Adult males castrated prior to puberty onset had higher spine density compared to sham controls. Adult females ovariectomized before puberty onset showed greater variance in spine density measures on cSTR cells compared to controls, but their mean spine density did not significantly differ from sham controls. Our findings reveal that these cSTR neurons, a subtype of the broader class of intratelencephalic-type neurons, exhibit significant sex differences and suggest that spine pruning on cSTR neurons is regulated by puberty in male mice.

Distentangling the systems contributing to changes in learning during adolescence.

Multiple neurocognitive systems contribute simultaneously to learning. For example, dopamine and basal ganglia (BG) systems are thought to support reinforcement learning (RL) by incrementally updating the value of choices, while the prefrontal cortex (PFC) contributes different computations, such as actively maintaining precise information in working memory (WM). It is commonly thought that WM and PFC show more protracted development than RL and BG systems, yet their contributions are rarely assessed in tandem. Here, we used a simple learning task to test how RL and WM contribute to changes in learning across adolescence. We tested 187 subjects ages 8 to 17 and 53 adults (25-30). Participants learned stimulus-action associations from feedback; the learning load was varied to be within or exceed WM capacity. Participants age 8-12 learned slower than participants age 13-17, and were more sensitive to load. We used computational modeling to estimate subjects' use of WM and RL processes. Surprisingly, we found more protracted changes in RL than WM during development. RL learning rate increased with age until age 18 and WM parameters showed more subtle, gender- and puberty-dependent changes early in adolescence. These results can inform education and intervention strategies based on the developmental science of learning.

A role for adaptive developmental plasticity in learning and decision making.

From both a medical and educational perspective, there is enormous value to understanding the environmental factors that sculpt learning and decision making. These questions are often approached from proximate levels of analysis, but may be further informed by the adaptive developmental plasticity framework used in evolutionary biology. The basic adaptive developmental plasticity framework posits that biological sensitive periods evolved to use information from the environment to sculpt emerging phenotypes. Here we lay out how we can apply this framework to learning and decision making in the mammalian brain and propose a working model in which dopamine neurons and their activity may serve to inform downstream circuits about environmental statistics. More widespread use of this evolutionary framework and its associated models can help inform and guide basic research and intervention science.

Variation in early life maternal care predicts later long range frontal cortex synapse development in mice.

Empirical and theoretical work suggests that early postnatal experience may inform later developing synaptic connectivity to adapt the brain to its environment. We hypothesized that early maternal experience may program the development of synaptic density on long range frontal cortex projections. To test this idea, we used maternal separation (MS) to generate environmental variability and examined how MS affected 1) maternal care and 2) synapse density on virally-labeled long range axons of offspring reared in MS or control conditions. We found that MS and variation in maternal care predicted bouton density on dorsal frontal cortex axons that terminated in the basolateral amygdala (BLA) and dorsomedial striatum (DMS) with more, fragmented care associated with higher density. The effects of maternal care on these distinct axonal projections of the frontal cortex were manifest at different ages. Maternal care measures were correlated with frontal cortex → BLA bouton density at mid-adolescence postnatal (P) day 35 and frontal cortex → DMS bouton density in adulthood (P85). Meanwhile, we found no evidence that MS or maternal care affected bouton density on ascending orbitofrontal cortex (OFC) or BLA axons that terminated in the dorsal frontal cortices. Our data show that variation in early experience can alter development in a circuit-specific and age-dependent manner that may be relevant to understanding the effects of early life adversity.

Prepubertal gonadectomy reveals sex differences in approach-avoidance behavior in adult mice.

Adolescence is a developmental period that is associated with physical, cognitive, and affective maturation and a time when sex biases in multiple psychiatric diseases emerge. While puberty onset marks the initiation of adolescence, it is unclear whether the pubertal rise in gonadal hormones generates sex differences in approach-avoidance behaviors that may impact psychiatric vulnerability. To examine the influence of pubertal development on adult behavior, we removed the gonads or performed sham surgery in male and female mice just prior to puberty onset and assessed performance in an odor-guided foraging task and anxiety-related behaviors in adulthood. We observed no significant sex differences in foraging or anxiety-related behaviors between intact adult male and female mice but found significant differences between adult male and female mice that had been gonadectomized (GDX) prior to puberty onset. GDX males failed to acquire the odor-guided foraging task, showed reduced locomotion, and exhibited increased anxiety-like behavior, while GDX females showed the opposite pattern of behavior. These data suggest that puberty may minimize rather than drive differences in approach-avoidance phenotypes in male and female mice.