Separating desire from prediction of outcome value

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.

A unified theoretical framework underlying the regulation of motivated behavior

To orchestrate behaviors for survival, multiple psychological components have evolved. The current theories do not clearly distinguish the distinct components. In this article, we provide a unified theoretical framework. To optimize survival, there should be four components; (1) "need", an alarm based on a predicted deficiency. (2) "motivation", a direct behavior driver. (3) "pleasure", a teacher based on immediate outcomes. (4) "utility", a teacher based on final delayed outcomes. For behavior stability, need should be accumulated into motivation to drive behavior. Based on the immediate outcome of the behavior, the pleasure should teach whether to continue the current behavior. Based on the final delay outcome, the utility should teach whether to increase future behavior by reshaping the other three components. We provide several neural substrate candidates in the food context. The proposed theoretical framework, in combination with appropriate experiments, will unravel the neural components responsible for each theoretical component.

Needing: An Active Inference Process for Physiological Motivation

Need states are internal states that arise from deprivation of crucial biological stimuli. They direct motivation, independently of external learning. Despite their separate origin, they interact with reward processing systems that respond to external stimuli. This article aims to illuminate the functioning of the needing system through the lens of active inference, a framework for understanding brain and cognition. We propose that need states exert a pervasive influence on the organism, which in active inference terms translates to a "pervasive surprise"-a measure of the distance from the organism's preferred state. Crucially, we define needing as an active inference process that seeks to reduce this pervasive surprise. Through a series of simulations, we demonstrate that our proposal successfully captures key aspects of the phenomenology and neurobiology of needing. We show that as need states increase, the tendency to occupy preferred states strengthens, independently of external reward prediction. Furthermore, need states increase the precision of states (stimuli and actions) leading to preferred states, suggesting their ability to amplify the value of reward cues and rewards themselves. Collectively, our model and simulations provide valuable insights into the directional and underlying influence of need states, revealing how this influence amplifies the wanting or liking associated with relevant stimuli.

Rethinking dopamine-guided action sequence learning

As opposed to those requiring a single action for reward acquisition, tasks necessitating action sequences demand that animals learn action elements and their sequential order and sustain the behaviour until the sequence is completed. With repeated learning, animals not only exhibit precise execution of these sequences but also demonstrate enhanced smoothness and efficiency. Previous research has demonstrated that midbrain dopamine and its major projection target, the striatum, play crucial roles in these processes. Recent studies have shown that dopamine from the substantia nigra pars compacta (SNc) and the ventral tegmental area (VTA) serve distinct functions in action sequence learning. The distinct contributions of dopamine also depend on the striatal subregions, namely the ventral, dorsomedial and dorsolateral striatum. Here, we have reviewed recent findings on the role of striatal dopamine in action sequence learning, with a focus on recent rodent studies.

Evolutionary perspectives on substance and behavioural addictions: Distinct and shared pathways to understanding, prediction and prevention

Addiction poses significant social, health, and criminal issues. Its moderate heritability and early-life impact, affecting reproductive success, poses an evolutionary paradox: why are humans predisposed to addictive behaviours? This paper reviews biological and psychological mechanisms of substance and behavioural addictions, exploring evolutionary explanations for the origin and function of relevant systems. Ancestrally, addiction-related systems promoted fitness through reward-seeking, and possibly self-medication. Today, psychoactive substances disrupt these systems, leading individuals to neglect essential life goals for immediate satisfaction. Behavioural addictions (e.g. video games, social media) often emulate ancestrally beneficial behaviours, making them appealing yet often irrelevant to contemporary success. Evolutionary insights have implications for how addiction is criminalised and stigmatised, propose novel avenues for interventions, anticipate new sources of addiction from emerging technologies such as AI. The emerging potential of glucagon-like peptide 1 (GLP-1) agonists targeting obesity suggest the satiation system may be a natural counter to overactivation of the reward system.