Pubmed: Wilbrecht L
Adolescent Development of Biological Rhythms: Estradiol Dependence and Effects of Combined Contraceptives
Purpose 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.
Methods 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, and the effects of hormonal […]
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 […]
Prepubertal ovariectomy alters dorsomedial striatum indirect pathway neuron excitability and explore/exploit balance in female mice
Decision-making circuits are modulated across life stages (e.g. juvenile, adolescent, or adult)—as well as on the shorter timescale of reproductive cycles in females—to meet changing environmental and physiological demands. Ovarian hormonal modulation of relevant neural circuits is a potential mechanism by which behavioral flexibility is regulated in females. Here we examined the influence of prepubertal ovariectomy (pOVX) versus sham surgery on performance in an odor-based multiple choice reversal task. We observed that pOVX females made different types of errors during reversal learning compared to sham surgery controls. Using reinforcement learning models fit to trial-by-trial behavior, we found that pOVX females exhibited […]
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) […]
Learning Rates Are Not All the Same: The Interpretation of Computational Model Parameters Depends on the Context
Reinforcement Learning (RL) has revolutionized the cognitive and brain sciences, explaining behavior from simple conditioning to problem solving, across the life span, and anchored in brain function. However, discrepancies in results are increasingly apparent between studies, particularly in the developmental literature. To better understand these, we investigated to which extent parameters generalize between tasks and models, and capture specific and uniquely interpretable (neuro)cognitive processes. 291 participants aged 8-30 years completed three learning tasks in a single session, and were fitted using state-of-the-art RL models. RL decision noise/exploration parameters generalized well between tasks, decreasing between ages 8-17. Learning rates for negative feedback […]
What do Reinforcement Learning Models Measure? Interpreting Model Parameters in Cognition and Neuroscience
Reinforcement learning (RL) is a concept that has been invaluable to research fields including machine learning, neuroscience, and cognitive science. However, what RL entails partly differs between fields, leading to difficulties when interpreting and translating findings.
This paper lays out these differences and zooms in on cognitive (neuro)science, revealing that we often overinterpret RL modeling results, with severe consequences for future research. Specifically, researchers often assume—implicitly—that model parameters generalize between tasks, models, and participant populations, despite overwhelming negative empirical evidence for this assumption. We also often assume that parameters measure specific, unique, and meaningful (neuro)cognitive processes, a concept we call interpretability, for which […]
The Unique Advantage of Adolescents in Probabilistic Reversal: Reinforcement Learning and Bayesian Inference Provide Adequate and Complementary Models
During adolescence, youth venture out, explore the wider world, and are challenged to learn how to navigate novel and uncertain environments. We investigated whether adolescents are uniquely adapted to this transition, compared to younger children and adults. In a stochastic, volatile reversal learning task with a sample of 291 participants aged 8-30, we found that adolescents 13-15 years old outperformed both younger and older participants. We developed two independent cognitive models, one based on Reinforcement learning (RL) and the other Bayesian inference (BI), and used hierarchical Bayesian model fitting to assess developmental changes in underlying cognitive mechanisms. Choice parameters in both […]
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 […]
Choice suppression is achieved through opponent but not independent function of the striatal indirect pathway in mice
The dorsomedial striatum (DMS) plays a key role in action selection, but little is known about how direct and indirect pathway spiny projection neurons (dSPNs and iSPNs) contribute to choice suppression in freely moving animals. Here, we used pathway-specific chemogenetic manipulation during a serial choice foraging task to test opposing predictions for iSPN function generated by two theories: 1) the ‘select/suppress’ heuristic which suggests iSPN activity is required to suppress alternate choices and 2) the network-inspired Opponent Actor Learning model (OpAL) which proposes that the weighted difference of dSPN and iSPN activity determines choice. We found that chemogenetic activation, but not […]