The Neurobiology of Impulsive Decision-Making and Reinforcement Learning in Nonhuman Animals

Altered Impulsivity Across Drug-Naïve Parkinsonism, Isolated Rapid Eye Movement Sleep Behavior Disorder, and Their High-Risk Relatives

OBJECTIVE

To determine multidimensional impulsivity levels across different early stages of α-synucleinopathy.

METHODS

This cross-sectional study investigated motor and decisional impulsivity levels using a panel of computerized tasks among drug-naïve parkinsonism patients, isolated/idiopathic rapid eye movement sleep behavior disorder (iRBD) patients and their first-degree relatives (iRBD-FDRs), and control participants. Trait impulsivity and impulse control behaviors were assessed by self-reported questionnaires.

RESULTS

A total of 27 drug-naïve parkinsonism patients, 157 iRBD patients, 66 iRBD-FDRs, and 82 control participants were recruited. Parkinsonism and iRBD patients had fewer numbers of extracted beads in beads task 1 and 2 (both p < 0.001), and a higher rate of irrational choice in task 1 (p = 0.046) before making decisions, and fewer numbers of pumps of unexploded blue balloons in the balloon analog risk task (p = 0.004) than control participants, indicating a higher level of reflection impulsivity and a lower level of risk taking, respectively. iRBD patients had more no-go errors in the go/no-go task than control participants (padjusted  = 0.036), suggesting a higher level of motor impulsivity. iRBD-FDRs with dream-enactment behaviors had fewer numbers of extracted beads (p = 0.047) in beads task 2 than FDRs without dream-enactment behaviors, suggesting a possible higher level of reflection impulsivity.

INTERPRETATION

A complex construct of altered impulsivity with decreased risk taking, but increased reflection and motor impulsivity, has already occurred at the prodromal and early stages of α-synucleinopathy, which have implications for underlying pathophysiology and clinical management of α-synucleinopathy, especially for impulse control behaviors upon dopaminergic drug treatment. ANN NEUROL 2024;95:544-557.

Environmental uncertainty and the advantage of impulsive choice strategies

Choice impulsivity is characterized by the choice of immediate, smaller reward options over future, larger reward options, and is often thought to be associated with negative life outcomes. However, some environments make future rewards more uncertain, and in these environments impulsive choices can be beneficial. Here we examined the conditions under which impulsive vs. non-impulsive decision strategies would be advantageous. We used Markov Decision Processes (MDPs) to model three common decision-making tasks: Temporal Discounting, Information Sampling, and an Explore-Exploit task. We manipulated environmental variables to create circumstances where future outcomes were relatively uncertain. We then manipulated the discount factor of an MDP agent, which affects the value of immediate versus future rewards, to model impulsive and non-impulsive behavior. This allowed us to examine the performance of impulsive and non-impulsive agents in more or less predictable environments. In Temporal Discounting, we manipulated the transition probability to delayed rewards and found that the agent with the lower discount factor (i.e. the impulsive agent) collected more average reward than the agent with a higher discount factor (the non-impulsive agent) by selecting immediate reward options when the probability of receiving the future reward was low. In the Information Sampling task, we manipulated the amount of information obtained with each sample. When sampling led to small information gains, the impulsive MDP agent collected more average reward than the non-impulsive agent. Third, in the Explore-Exploit task, we manipulated the substitution rate for novel options. When the substitution rate was high, the impulsive agent again performed better than the non-impulsive agent, as it explored the novel options less and instead exploited options with known reward values. The results of these analyses show that impulsivity can be advantageous in environments that are unexpectedly uncertain.

The Neuromodulatory Role of the Noradrenergic and Cholinergic Systems and Their Interplay in Cognitive Functions: A Focused Review

The noradrenergic and cholinergic modulation of functionally distinct regions of the brain has become one of the primary organizational principles behind understanding the contribution of each system to the diversity of neural computation in the central nervous system. Decades of work has shown that a diverse family of receptors, stratified across different brain regions, and circuit-specific afferent and efferent projections play a critical role in helping such widespread neuromodulatory systems obtain substantial heterogeneity in neural information processing. This review briefly discusses the anatomical layout of both the noradrenergic and cholinergic systems, as well as the types and distributions of relevant receptors for each system. Previous work characterizing the direct and indirect interaction between these two systems is discussed, especially in the context of higher order cognitive functions such as attention, learning, and the decision-making process. Though a substantial amount of work has been done to characterize the role of each neuromodulator, a cohesive understanding of the region-specific cooperation of these two systems is not yet fully realized. For the field to progress, new experiments will need to be conducted that capitalize on the modular subdivisions of the brain and systematically explore the role of norepinephrine and acetylcholine in each of these subunits and across the full range of receptors expressed in different cell types in these regions.

The effects of early life stress on impulsivity

Elevated impulsivity is a symptom shared by various psychiatric disorders such as substance use disorder, bipolar disorder, and attention-deficit/hyperactivity disorder. However, impulsivity is not a unitary construct and impulsive behaviors fall into two subcategories: impulsive action and impulsive choice. Impulsive choice refers to the tendency to prefer immediate, small rewards over delayed, large rewards, whereas impulsive action involves difficulty inhibiting rash, premature, or mistimed behaviors. These behaviors are mediated by the mesocorticolimbic dopamine (DA) system, which consists of projections from the ventral tegmental area to the nucleus accumbens and prefrontal cortex. Early life stress (ELS) alters both impulsive choice and impulsive action in rodents. ELS also changes DA receptor expression, transmission, and activity within the mesocorticolimbic system. This review integrates the dopamine, impulsivity, and ELS literature to provide evidence that ELS alters impulsivity via inducing changes in the mesocorticolimbic DA system. Understanding how ELS affects brain circuits associated with impulsivity can help advance treatments aimed towards reducing impulsivity symptoms in a variety of psychiatric disorders.

A method for studying reinforcement factors controlling impulsive choice for use in behavioral neuroscience

Although procedures originating within the experimental analysis of behavior commonly are used in behavioral neuroscience to produce behavioral endpoints, they are used less often to analyze the behavioral processes involved, particularly at the level of individual organisms (see Soto, 2020). Concurrent-chains procedures have been used extensively to study choice and to quantify relations between various dimensions of reinforcement and preference. Unfortunately, parametric analysis of those relations using traditional steady-state, single-subject experimental designs can be time-consuming, often rendering these procedures impractical for use in behavioral neuroscience. The purpose of this paper is to describe how concurrent-chains procedures can be adapted to allow for parametric examination of effects of the reinforcement dimensions involved in impulsive choice (magnitude and delay) within experimental sessions in rats. Data are presented indicating that this procedure can produce relatively consistent within-session estimates of sensitivity to reinforcement in individual subjects, and that these estimates can be modified by neurobiological manipulation (drug administration). These data suggest that this type of procedure offers a promising approach to the study of neurobiological mechanisms of complex behavior in individual organisms, which could facilitate a more fruitful relationship between behavior analysis and behavioral neuroscience.

Computational theory-driven studies of reinforcement learning and decision-making in addiction: What have we learned?

Computational psychiatry provides a powerful new approach for linking the behavioral manifestations of addiction to their precise cognitive and neurobiological substrates. However, this emerging area of research is still limited in important ways. While research has identified features of reinforcement learning and decision-making in substance users that differ from health, less emphasis has been placed on capturing addiction cycles/states dynamically, within-person. In addition, the focus on few behavioral variables at a time has precluded more detailed consideration of related processes and heterogeneous clinical profiles. We propose that a longitudinal and multidimensional examination of value-based processes, a type of dynamic "computational fingerprint", will provide a more complete understanding of addiction as well as aid in developing better tailored and timed interventions.

Introducing the PLOS ONE Collection on the neuroscience of reward and decision making

The survival of an organism depends on the ability to make adaptive decisions to achieve the needs of the organism: where to get food, who to mate with, and how to evade predators. Decision-making is a term used to describe a collection of behavioral and/or computational functions that guide the selection of an option amongst a set of alternatives. Some of these functions may include calculating the costs and benefits of a particular action, evaluating differences in value of each of the alternative outcomes and the likelihood of receiving a particular outcome, using past experiences to generate predictions or expectations about action-outcome associations, and/or integration of past experiences to make novel inferences that can be used in new environments. There is considerable interest in understanding the neurobiological mechanisms that mediate these decision-making functions and recent advances in behavioral approaches, neuroscience techniques, and neuroimaging measures have begun to develop mechanistic links between biology, reward, and decision making. This multidisciplinary work holds great promise for elucidating the biological mechanisms mediating decision-making deficits in normal and abnormal states. The multidisciplinary studies included in this Collection provide new insights into the neuroscience of decision making and reward.