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.

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 (β = -0.42, false discovery rate [FDR]-corrected p [pFDR] = .022). Importantly, mood did not independently correlate with cortisol concentration, but rather explained additional variance (β = 0.46, pFDR = .022) and strengthened the relationship between higher cortisol and lower levels of exploratory learning (β = -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 (β = -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.

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.

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.

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.

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 2-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.

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.

Struggling behavior during restraint is regulated by stress experience

Restraint elicits a number of physiological stress responses that can be increased or decreased in magnitude based on prior stress history. For instance, repeated exposure to restraint leads to habituation of hypothalamic-pituitary-adrenal (HPA) activation to restraint. In contrast, acute restraint after a different repeated stressor leads to facilitation of HPA activity to the novel stress. Acute restraint also elicits a variety of behaviors, including struggling, but the effect of prior stress in regulating behavioral responses to restraint is not clear. The goal of the present studies was to assess struggling during restraint with or without a prior history of repeated stress. Using automated behavioral analysis software (EthoVision), we quantified struggling during restraint. We found that acutely restrained rats exhibited vigorous struggling behavior that declined during a single restraint period. Repeated restraint lead to habituated struggling behavior, whereas acute restraint after repeated swim elicited facilitated struggling behavior. These effects on struggling were found alongside expected differences in HPA activity. Removing stress-induced increases in corticosterone via adrenalectomy did not significantly affect struggling responses to restraint. Overall, restraint-induced struggling appears to be regulated in a manner similar to HPA responses to restraint, but is not dictated by adrenal hormones.

The physical context of previous stress exposure modifies hypothalamic-pituitary-adrenal responses to a subsequent homotypic stress

The hypothalamic-pituitary-adrenal (HPA) axis becomes less responsive to some types of repeated stress over time, a process termed habituation. Many facets of the stressful stimulus can modify such HPA responses to stressors, such as predictability and controllability. However, the physical context in which the stressor occurred may also provide a discriminative stimulus that can affect the HPA response to that stressor. In the present study, we examined whether a change in the context in which stress exposure occurs can alter HPA responses to a subsequent [corrected] homotypic stressor. Three separate contexts were produced by manipulating odor cues. Rats housed in the 3 context rooms exhibited similar HPA responses to acute 30-min restraint or repeated (8th) 30-min restraint in their home environments. However, rats that were restrained for 30 min per day for 7 days in a room in one context and then restrained on day 8 in a novel context exhibited attenuated habituation compared to rats restrained on day 8 in the familiar context. These results provide evidence that repeated stress-induced HPA activity depends, in part, on the context in which the stress is experienced.