Toward a multiscale modeling framework for understanding serotonergic function

Dorsal raphe neurons integrate the values of reward amount, delay, and uncertainty in multi-attribute decision-making

The dorsal raphe nucleus (DRN) is implicated in psychiatric disorders that feature impaired sensitivity to reward amount, impulsivity when facing reward delays, and risk-seeking when confronting reward uncertainty. However, it has been unclear whether and how DRN neurons signal reward amount, reward delay, and reward uncertainty during multi-attribute value-based decision-making, where subjects consider these attributes to make a choice. We recorded DRN neurons as monkeys chose between offers whose attributes, namely expected reward amount, reward delay, and reward uncertainty, varied independently. Many DRN neurons signaled offer attributes, and this population tended to integrate the attributes in a manner that reflected monkeys' preferences for amount, delay, and uncertainty. After decision-making, in response to post-decision feedback, these same neurons signaled signed reward prediction errors, suggesting a broader role in tracking value across task epochs and behavioral contexts. Our data illustrate how the DRN participates in value computations, guiding theories about the role of the DRN in decision-making and psychiatric disease.

Ethological computational psychiatry: Challenges and opportunities

Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions and well-constrained behaviors over short timescales (e.g., trials, hours), many mental health conditions involve complex interactions of mood and cognition that are non-stationary across behavioral contexts and evolve over extended timescales. Here, we discuss opportunities, challenges, and possible future directions in computational psychiatry to quantify non-stationary continuously monitored behaviors. We suggest that this exploratory effort may contribute to a more precision-based approach to treating mental disorders and facilitate a more robust reverse translation across animal species. We conclude with ethical considerations for any field that aims to bridge artificial intelligence and patient monitoring.

Dorsal raphe neurons signal integrated value during multi-attribute decision-making

The dorsal raphe nucleus (DRN) is implicated in psychiatric disorders that feature impaired sensitivity to reward amount, impulsivity when facing reward delays, and risk-seeking when grappling with reward uncertainty. However, whether and how DRN neurons signal reward amount, reward delay, and reward uncertainty during multi-attribute value-based decision-making, where subjects consider all these attributes to make a choice, is unclear. We recorded DRN neurons as monkeys chose between offers whose attributes, namely expected reward amount, reward delay, and reward uncertainty, varied independently. Many DRN neurons signaled offer attributes. Remarkably, these neurons commonly integrated offer attributes in a manner that reflected monkeys' overall preferences for amount, delay, and uncertainty. After decision-making, in response to post-decision feedback, these same neurons signaled signed reward prediction errors, suggesting a broader role in tracking value across task epochs and behavioral contexts. Our data illustrate how DRN participates in integrated value computations, guiding theories of DRN in decision-making and psychiatric disease.

Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration

Degenerate neural circuits perform the same function despite being structurally different. However, it is unclear whether neural circuits with interacting neuromodulator sources can themselves degenerate while maintaining the same neuromodulatory function. Here, we address this by computationally modeling the neural circuits of neuromodulators serotonin and dopamine, local glutamatergic and GABAergic interneurons, and their possible interactions, under reward/punishment-based conditioning tasks. The neural modeling is constrained by relevant experimental studies of the VTA or DRN system using, e.g., electrophysiology, optogenetics, and voltammetry. We first show that a single parsimonious, sparsely connected neural circuit model can recapitulate several separate experimental findings that indicated diverse, heterogeneous, distributed, and mixed DRNVTA neuronal signaling in reward and punishment tasks. The inability of this model to recapitulate all observed neuronal signaling suggests potentially multiple circuits acting in parallel. Then using computational simulations and dynamical systems analysis, we demonstrate that several different stable circuit architectures can produce the same observed network activity profile, hence demonstrating degeneracy. Due to the extensive D2-mediated connections in the investigated circuits, we simulate the D2 receptor agonist by increasing the connection strengths emanating from the VTA DA neurons. We found that the simulated D2 agonist can distinguish among sub-groups of the degenerate neural circuits based on substantial deviations in specific neural populations' activities in reward and punishment conditions. This forms a testable model prediction using pharmacological means. Overall, this theoretical work suggests the plausibility of degeneracy within neuromodulator circuitry and has important implications for the stable and robust maintenance of neuromodulatory functions.

Rhythms, Reward, and Blues: Consequences of Circadian Photoperiod on Affective and Reward Circuit Function

Circadian disruptions, along with altered affective and reward states, are commonly associated with psychiatric disorders. In addition to genetics, the enduring influence of environmental factors in programming neural networks is of increased interest in assessing the underpinnings of mental health. The duration of daylight or photoperiod is known to impact both the serotonin and dopamine systems, which are implicated in mood and reward-based disorders. This review first examines the effects of circadian disruption and photoperiod in the serotonin system in both human and preclinical studies. We next highlight how brain regions crucial for the serotoninergic system (i.e., dorsal raphe nucleus; DRN), and dopaminergic (i.e., nucleus accumbens; NAc and ventral tegmental area; VTA) system are intertwined in overlapping circuitry, and play influential roles in the pathology of mood and reward-based disorders. We then focus on human and animal studies that demonstrate the impact of circadian factors on the dopaminergic system. Lastly, we discuss how environmental factors such as circadian photoperiod can impact the neural circuits that are responsible for regulating affective and reward states, offering novel insights into the biological mechanisms underlying the pathophysiology, systems, and therapeutic treatments necessary for mood and reward-based disorders.

Opportunities for multiscale computational modelling of serotonergic drug effects in Alzheimer's disease

Alzheimer's disease (AD) is an age-specific neurodegenerative disease that compromises cognitive functioning and impacts the quality of life of an individual. Pathologically, AD is characterised by abnormal accumulation of beta-amyloid (Aβ) and hyperphosphorylated tau protein. Despite research advances over the last few decades, there is currently still no cure for AD. Although, medications are available to control some behavioural symptoms and slow the disease's progression, most prescribed medications are based on cholinesterase inhibitors. Over the last decade, there has been increased attention towards novel drugs, targeting alternative neurotransmitter pathways, particularly those targeting serotonergic (5-HT) system. In this review, we focused on 5-HT receptor (5-HTR) mediated signalling and drugs that target these receptors. These pathways regulate key proteins and kinases such as GSK-3 that are associated with abnormal levels of Aβ and tau in AD. We then review computational studies related to 5-HT signalling pathways with the potential for providing deeper understanding of AD pathologies. In particular, we suggest that multiscale and multilevel modelling approaches could potentially provide new insights into AD mechanisms, and towards discovering novel 5-HTR based therapeutic targets.

Multiscale Computation and Dynamic Attention in Biological and Artificial Intelligence

Biological and artificial intelligence (AI) are often defined by their capacity to achieve a hierarchy of short-term and long-term goals that require incorporating information over time and space at both local and global scales. More advanced forms of this capacity involve the adaptive modulation of integration across scales, which resolve computational inefficiency and explore-exploit dilemmas at the same time. Research in neuroscience and AI have both made progress towards understanding architectures that achieve this. Insight into biological computations come from phenomena such as decision inertia, habit formation, information search, risky choices and foraging. Across these domains, the brain is equipped with mechanisms (such as the dorsal anterior cingulate and dorsolateral prefrontal cortex) that can represent and modulate across scales, both with top-down control processes and by local to global consolidation as information progresses from sensory to prefrontal areas. Paralleling these biological architectures, progress in AI is marked by innovations in dynamic multiscale modulation, moving from recurrent and convolutional neural networks-with fixed scalings-to attention, transformers, dynamic convolutions, and consciousness priors-which modulate scale to input and increase scale breadth. The use and development of these multiscale innovations in robotic agents, game AI, and natural language processing (NLP) are pushing the boundaries of AI achievements. By juxtaposing biological and artificial intelligence, the present work underscores the critical importance of multiscale processing to general intelligence, as well as highlighting innovations and differences between the future of biological and artificial intelligence.

Embracing diversity in the 5-HT neuronal system

Neurons that synthesize and release 5-hydroxytryptamine (5-HT; serotonin) express a core set of genes that establish and maintain this neurotransmitter phenotype and distinguish these neurons from other brain cells. Beyond a shared 5-HTergic phenotype, these neurons display divergent cellular properties in relation to anatomy, morphology, hodology, electrophysiology and gene expression, including differential expression of molecules supporting co-transmission of additional neurotransmitters. This diversity suggests that functionally heterogeneous subtypes of 5-HT neurons exist, but linking subsets of these neurons to particular functions has been technically challenging. We discuss recent data from molecular genetic, genomic and functional methods that, when coupled with classical findings, yield a reframing of the 5-HT neuronal system as a conglomeration of diverse subsystems with potential to inspire novel, more targeted therapies for clinically distinct 5-HT-related disorders.

THE EXPOSOME IN HUMAN EVOLUTION: FROM DUST TO DIESEL

Global exposures to air pollution and cigarette smoke are novel in human evolutionary history and are associated with about 16 million premature deaths per year. We investigate the history of the human exposome for relationships between novel environmental toxins and genetic changes during human evolution in six phases. Phase I: With increased walking on savannas, early human ancestors inhaled crustal dust, fecal aerosols, and spores; carrion scavenging introduced new infectious pathogens. Phase II: Domestic fire exposed early Homo to novel toxins from smoke and cooking. Phases III and IV: Neolithic to preindustrial Homo sapiens incurred infectious pathogens from domestic animals and dense communities with limited sanitation. Phase V: Industrialization introduced novel toxins from fossil fuels, industrial chemicals, and tobacco at the same time infectious pathogens were diminishing. Thereby, pathogen-driven causes of mortality were replaced by chronic diseases driven by sterile inflammogens, exogenous and endogenous. Phase VI: Considers future health during global warming with increased air pollution and infections. We hypothesize that adaptation to some ancient toxins persists in genetic variations associated with inflammation and longevity.

Genetic approaches to the investigation of serotonergic neuron functions in animals

The serotonergic system is one of the most important neurotransmitter systems that take part in the regulation of vital CNS functions. The understanding of its mechanisms will help scientists create new therapeutic approaches to the treatment of mental and neurodegenerative diseases and find out how this neurotransmitter system interacts with other parts of the brain and regulates their activity. Since the serotonergic system anatomy and functionality are heterogeneous and complex, the best tools for studying them are based on manipulation of individual types of neurons without affecting neurons of other neurotransmitter systems. The selective cell control is possible due to the genetic determinism of their functions. Proteins that determine the uniqueness of the cell type are expressed under the regulation of cell-specific promoters. By using promoters that are specific for genes of the serotonin system, one can control the expression of a gene of interest in serotonergic neurons. Here we review approaches based on such promoters. The genetic models to be discussed in the article have already shed the light on the role of the serotonergic system in modulating behavior and processing sensory information. In particular, genetic knockouts of serotonin genes sert, pet1, and tph2 promoted the determination of their contribution to the development and functioning of the brain. In addition, the review describes inducible models that allow gene expression to be controlled at various developmental stages. Finally, the application of these genetic approaches in optogenetics and chemogenetics provided a new resource for studying the functions, discharge activity, and signal transduction of serotonergic neurons. Nevertheless, the advantages and limitations of the discussed genetic approaches should be taken into consideration in the course of creating models of pathological conditions and developing pharmacological treatments for their correction.