Neural landscape diffusion resolves conflicts between needs across time

Does the lateral hypothalamus govern the transition between appetitive and consummatory feeding?

Feeding is a cyclic behaviour that includes appetitive, consummatory and termination phases. Identifying the neural circuits controlling these phases and triggering specific transitions between phases would be a key advance in understanding feeding behaviour. The lateral hypothalamus (LH) has long been recognized for its central role in feeding. We review evidence suggesting that the LH acts as a regulator of the appetitive-consummatory transition using a switchboard-like circuit architecture. Within the LH, several neuronal subpopulations can be defined based on molecular markers, and - although these subpopulations are functionally diverse - they contribute to appetitive and consummatory behaviours to varying extents. We summarise the current evidence on whether these subpopulations have functional identities and speculate on the role of the LH as a controller of behavioural transitions.

Hormonal regulation of behavioral and emotional persistence: Novel insights from a systems-level approach to neuroendocrinology

Gonadal sex steroid hormones regulate internal states, social drive, perception of external cues, and learning and memory. Fluctuating hormones influence mood and emotional states, enabling flexibility in instinctive behaviors and cognitive decisions. Conversely, elevated hormone levels help sustain emotional states and behavioral choices, ensuring the precise execution of costly social behaviors within optimal time windows to maximize reproductive success. While decades of work have shed light on the cellular and molecular mechanisms by which sex hormones alter neural excitability and circuit architecture, recent work has begun to tie many of these changes to principles of computation using the tools of systems neuroscience. Here, we will outline the mechanisms by which sex steroid hormones alter neural functioning at the molecular and cellular level and highlight recent work that points towards changes in specific computational functions, including the generation and maintenance of neural and behavioral persistence.

Neural mechanisms balancing accuracy and flexibility in working memory and decision tasks

The living system follows the principles of physics, yet distinctive features, such as adaptability, differentiate it from conventional systems. The cognitive functions of decision-making (DM) and working memory (WM) are crucial for animal adaptation, but the underlying mechanisms are still unclear. To explore the mechanism underlying DM and WM functions, here we applied a general non-equilibrium landscape and flux approach to a biophysically based model that can perform decision-making and working memory functions. Our findings reveal that DM accuracy improved with stronger resting states in the circuit architecture with selective inhibition. However, the robustness of working memory against distractors was weakened. To address this, an additional non-selective input during the delay period of decision-making tasks was proposed as a mechanism to gate distractors with minimal increase in thermodynamic cost. This temporal gating mechanism, combined with the selective-inhibition circuit architecture, supports a dynamical modulation that emphasizes the robustness or flexibility to incoming stimuli in working memory tasks according to the cognitive task demands. Our approach offers a quantitative framework to uncover mechanisms underlying cognitive functions grounded in non-equilibrium physics.

A normative framework dissociates need and motivation in hypothalamic neurons

Physiological needs evoke motivational drives that produce natural behaviors for survival. In previous studies, the temporally intertwined dynamics of need and motivation have made it challenging to differentiate these two components. On the basis of classic homeostatic theories, we established a normative framework to derive computational models for need-encoding and motivation-encoding neurons. By combining the model-based predictions and naturalistic experimental paradigms, we demonstrated that agouti-related peptide (AgRP) and lateral hypothalamic leptin receptor (LHLepR) neuronal activities encode need and motivation, respectively. Our model further explains the difference in the dynamics of appetitive behaviors induced by optogenetic stimulation of AgRP or LHLepR neurons. Our study provides a normative modeling framework that explains how hypothalamic neurons separately encode need and motivation in the mammalian brain.

Mating proximity blinds threat perception

Romantic engagement can bias sensory perception. This 'love blindness' reflects a common behavioural principle across organisms: favouring pursuit of a coveted reward over potential risks1. In the case of animal courtship, such sensory biases may support reproductive success but can also expose individuals to danger, such as predation2,3. However, how neural networks balance the trade-off between risk and reward is unknown. Here we discover a dopamine-governed filter mechanism in male Drosophila that reduces threat perception as courtship progresses. We show that during early courtship stages, threat-activated visual neurons inhibit central courtship nodes via specific serotonergic neurons. This serotonergic inhibition prompts flies to abort courtship when they see imminent danger. However, as flies advance in the courtship process, the dopaminergic filter system reduces visual threat responses, shifting the balance from survival to mating. By recording neural activity from males as they approach mating, we demonstrate that progress in courtship is registered as dopaminergic activity levels ramping up. This dopamine signalling inhibits the visual threat detection pathway via Dop2R receptors, allowing male flies to focus on courtship when they are close to copulation. Thus, dopamine signalling biases sensory perception based on perceived goal proximity, to prioritize between competing behaviours.

Distinct roles of prefrontal cortex neurons in set shifting

Cognitive flexibility, the ability to adjust behavioral strategies in response to changing environmental contingencies, requires adaptive processing of internal states and contextual cues to guide goal-oriented behavior, and is dependent on prefrontal cortex (PFC) functions. However, the neurophysiological underpinning of how the PFC supports cognitive flexibility is not well understood and has been under active investigation. We recorded spiking activity from single PFC neurons in mice performing the attentional set-shifting task, where mice learned to associate different contextually relevant sensory stimuli to reward. We identified subgroups of PFC neurons encoding task context, choice and trial outcome. Putative fast-spiking neurons were more involved in representing outcome and choice than putative regular-spiking neurons. Regression model further revealed that task context and trial outcome modulated the activity of choice-encoding neurons in rule-dependent and cell type-dependent manners. Together, our data provide new evidence to elucidate PFC's role in cognitive flexibility, suggesting differential cell type-specific engagement during set shifting, and that both contextual rule representation and trial outcome monitoring underlie PFC's unique capacity to support flexible behavioral switching.

Dopamine biases decisions by limiting temporal integration

Motivations bias our responses to stimuli, producing behavioural outcomes that match our needs and goals. Here we describe a mechanism behind this phenomenon: adjusting the time over which stimulus-derived information is permitted to accumulate towards a decision. As a Drosophila copulation progresses, the male becomes less likely to continue mating through challenges1-3. We show that a set of copulation decision neurons (CDNs) flexibly integrates information about competing drives to mediate this decision. Early in mating, dopamine signalling restricts CDN integration time by potentiating Ca2+/calmodulin-dependent protein kinase II (CaMKII) activation in response to stimulatory inputs, imposing a high threshold for changing behaviours. Later into mating, the timescale over which the CDNs integrate termination-promoting information expands, increasing the likelihood of switching behaviours. We suggest scalable windows of temporal integration at dedicated circuit nodes as a key but underappreciated variable in state-based decision-making.

The Nested States Model: A Phenomenologically-Grounded Model of the Mind

BACKGROUND

Subjective experience is central to the nature of mental illness, yet it has not played a central role in most empirical approaches to psychopathology. While phenomenological perspectives in psychiatry have seen a recent resurgence, there remains a need for more detailed models of psychopathological processes based on explicit phenomenological and enactive foundations.

SUMMARY

We present a framework derived from the Nested States Model (NSM) through which such phenomenologically-grounded models might be constructed. The NSM describes the dynamic structure of subjective experience as a system of nested states that reciprocally influence one another across hierarchical layers. Here, we show how the NSM provides a scheme for characterizing patterns of experience that comprise various psychopathological processes. We demonstrate the utility of this scheme both for clinical practice and for building our knowledge of psychopathological processes more broadly.

KEY MESSAGES

The NSM can advance three aims that we see as critical for the lasting integration of phenomenological approaches to psychopathology within psychiatry. First, we show that the NSM provides a means for constructing clinical formulations and treatment considerations that center squarely on an individual's subjective experiences. Second, the NSM supplies a framework for organizing findings from clinical-phenomenological research that can guide the construction of broader phenomenologically-grounded models of psychopathological processes. Lastly, the NSM aligns our perspective on subjective experience with emerging perspectives on brain dynamics, helping to bridge phenomenological work with ongoing neurophysiological research.

INGEsT: An Open-Source Behavioral Setup for Studying Self-motivated Ingestive Behavior and Learned Operant Behavior

Ingestive behavior is driven by negative internal hunger and thirst states, as well as by positive expected rewards. Although the neural substrates underlying feeding and drinking behaviors have been widely investigated, they have primarily been studied in isolation, even though eating can also trigger thirst, and vice versa. Thus, it is still unclear how the brain encodes body states, recalls the memory of food and water reward outcomes, generates feeding/drinking motivation, and triggers ingestive behavior. Here, we developed an INstrument for Gauging Eating and Thirst (INGEsT), a custom-made behavioral chamber which allows for precise measurement of both feeding and drinking by combining a FED3 food dispenser, lickometers for dispensing liquid, a camera for behavioral tracking, LED light for optogenetics, and calcium imaging miniscope. In addition, in vivo calcium imaging, optogenetics, and video recordings are well synchronized with animal behaviors, e.g., nose pokes, pellet retrieval, and water licking, by using a Bpod microprocessor and timestamping behavioral and imaging data. The INGEsT behavioral chamber enables many types of experiments, including free feeding/drinking, operant behavior to obtain food or water, and food/water choice behavior. Here, we tracked activity of insular cortex and mPFC Htr3a neurons using miniscopes and demonstrate that these neurons encode many aspects of ingestive behavior during operant learning and food/water choice and that their activity can be tuned by internal state. Overall, we have built a platform, consisting of both hardware and software, to precisely monitor innate ingestive, and learned operant, behaviors and to investigate the neural correlates of self-motivated and learned feeding/drinking behaviors.

Molecular control of temporal integration matches decision-making to motivational state

Motivations bias our responses to stimuli, producing behavioral outcomes that match our needs and goals. We describe a mechanism behind this phenomenon: adjusting the time over which stimulus-derived information is permitted to accumulate toward a decision. As a Drosophila copulation progresses, the male becomes less likely to continue mating through challenges. We show that a set of Copulation Decision Neurons (CDNs) flexibly integrates information about competing drives to mediate this decision. Early in mating, dopamine signaling restricts CDN integration time by potentiating CaMKII activation in response to stimulatory inputs, imposing a high threshold for changing behaviors. Later into mating, the timescale over which the CDNs integrate termination-promoting information expands, increasing the likelihood of switching behaviors. We suggest scalable windows of temporal integration at dedicated circuit nodes as a key but underappreciated variable in state-based decision-making.