Most people who are regular consumers of psychoactive drugs are not drug addicts, nor will they ever become addicts. In neurobiological theories, non-addictive drug consumption is acknowledged only as a “necessary” prerequisite for addiction, but not as a stable and widespread behavior in its own right. This target article proposes a new neurobiological framework theory for non-addictive psychoactive drug consumption, introducing the concept of “drug instrumentalization.” Psychoactive drugs are consumed for their effects on mental states. Humans are able to learn (...) that mental states can be changed on purpose by drugs, in order to facilitate other, non-drug-related behaviors. We discuss specific “instrumentalization goals” and outline neurobiological mechanisms of how major classes of psychoactive drugs change mental states and serve non-drug-related behaviors. We argue that drug instrumentalization behavior may provide a functional adaptation to modern environments based on a historical selection for learning mechanisms that allow the dynamic modification of consummatory behavior. It is assumed that in order to effectively instrumentalize psychoactive drugs, the establishment of and retrieval from a drug memory is required. Here, we propose a new classification of different drug memory subtypes and discuss how they interact during drug instrumentalization learning and retrieval. Understanding the everyday utility and the learning mechanisms of non-addictive psychotropic drug use may help to prevent abuse and the transition to drug addiction in the future. (shrink)

Normative thinking about addiction has traditionally been divided between, on the one hand, a medical model which sees addiction as a disease characterized by compulsive and relapsing drug use over which the addict has little or no control and, on the other, a moral model which sees addiction as a choice characterized by voluntary behaviour under the control of the addict. Proponents of the former appeal to evidence showing that regular consumption of drugs causes persistent changes in the brain structures (...) and functions known to be involved in the motivation of behavior. On this evidence, it is often concluded that becoming addicted involves a transition from voluntary, chosen drug use to non-voluntary compulsive drug use. Against this view, proponents of the moral model provide ample evidence that addictive drug use involves voluntary chosen behaviour. In this paper we argue that although they are right about something, both views are mistaken. We present a third model that neither rules out the view of addictive drug use as compulsive, nor that it involves voluntary chosen behavior. -/- . (shrink)

Withdrawal involves emotional pain that motivates much addictive behavior. In this paper, I argue that the emotional pain of withdrawal compels much addictive behavior. Researchers have noticed this possibility but it is widely underappreciated. Among philosophers, only Hanna Pickard has discussed emotional compulsion in addiction, and the emotional aspect of withdrawal has been almost completely neglected. Accounts of emotional compulsion in the philosophical literature (from Tappolet, Elster, and Furrow) probably do not capture how the distress of withdrawal compels, so I (...) propose a more suitable account of “pathodoxastic” compulsion in addiction. On this account, the emotional pain of withdrawal compels when it undermines the ability to believe that one can continue to endure it, and therefore the ability to intend abstinence. (shrink)

The computational approach to psychiatric disorders, including delusions, promises explanation and treatment. Here, we argue that an information processing approach might be misleading to understand psychopathology and requires further refinement. We explore the claim of computational psychiatry being a bridge between phenomenology and physiology while focussing on the ontological commitments and corresponding methodology computational psychiatry is based on. Interconnecting ontological claims and methodological practices, the paper illustrates the structure of theory-building and testing in computational psychiatry.First, we will explain the ontological (...) commitments computational psychiatry is grounded in, theBayesian Brain hypothesis(BBH) of unconscious inference, paired with normative deontic approaches applied to gauge psychopathology. We then turn to the steps taken in empirical paradigms, from definitions, which are used as starting points, to the operationalisation and isolation of cognitive processes and hypothesis testing based on algorithmic models, to consecutive interpretations regarding the aetiology of psychiatric disorders. We outline how experimental paradigms in computational psychiatry are specifically designed to confirm aberrations in assumed inferential processes, which are thought of as being the underlyingcore invariant features.We will illustrate a gap between the ontological commitments of computational psychiatry and the operationalisation and testing of the cognition assumed to be relevant for psychopathology. This conceptual gap is of utmost importance when designing computational paradigms and may impede a crisp understanding of the approach. Lastly, in evaluating the conceptual gap, it becomes apparent that the information processing formalism used in computational psychiatry is still grounded in rational cognitive psychology. (shrink)

In this opinionated review, I draw attention to some of the contributions reinforcement learning can make to questions in the philosophy of mind. In particular, I highlight reinforcement learning's foundational emphasis on the role of reward in agent learning, and canvass two ways in which the framework may advance our understanding of perception and motivation.

I propose that the successes and contributions of reinforcement learning urge us to see the mind in a new light, namely, to recognise that the mind is fundamentally evaluative in nature.

I argue that denial plays a central but insufficiently recognized role in addiction. The puzzle inherent in addiction is why drug use persists despite negative consequences. The orthodox conception of addiction resolves this puzzle by appeal to compulsion; but there is increasing evidence that addicts are not compelled to use but retain choice and control over their consumption in many circumstances. Denial offers an alternative explanation: there is no puzzle as to why drug use persists despite negative consequences if these (...) consequences are not straightforwardly known. I describe the nature of the causal knowledge that one's drug use is causing negative consequences; map the conceptual landscape of denial and explain how it can block such knowledge; and explore some of the processes and mechanisms that have been studied by philosophy and the cognitive sciences and which may underpin denial in addiction, including well-established information-processing biases, motivational influences on belief formation and self-deception, and cognitive deficits with respect to insight and self-awareness. I conclude by suggesting that addiction is as much a disorder of cognition as a disorder of conation. (shrink)

It is common to think of addiction as involving behavior which in some sense is ?out of control.? But does this mean addictive actions occur because of compulsion or because of ordinary weakness of will? Many philosophers argue that addictive actions occur because of weakness of will, since there is plenty of evidence suggesting that they are not caused by irresistible desires. In fact, addicts seem, in general, to perform these actions freely in the sense of having the ability to (...) refrain from doing so. In this paper I argue, first, that it is not the addiction-as-compulsion view that is mistaken, but rather the view that irresistible desires are a defining feature of compulsion. Second, drawing on some results in addiction neuroscience, I construct and defend a new analysis of compulsivity that distinguishes addictive from weak-willed actions in a way that is consistent with the view that addictive actions are performed freely. (shrink)

Recent work by Alfred Mele, Romy Jaster and Chandra Sripada recognizes that abilities come in degrees of fallibility. The rough idea is that abilities are often not surefire. They are liable to fail. The more liable an ability is to fail, the more fallible it is. Fallibility is plausibly significant for addiction, responsibility, and normative theorizing. However, we lack an adequate account of what fallibility consists in. This article addresses that problem. Perhaps the most natural approach is to say (roughly) (...) the fallibility of your ability to F is the proportion of scenarios in which you do not F, among those in which you try to F. I argue that this approach (in all plausible versions) is mistaken. I then introduce the notion of an action’s “fragility,” and propose that we use that new notion to understand fallibility. (shrink)

The broad spectrum revolution brought greater dependence on skill and knowledge, and more demanding, often social, choices. We adopt Sterelny's account of how cooperative foraging paid the costs associated with longer dependency, and transformed the problem of skill learning. Scaffolded learning can facilitate cognitive control including suppression, whereas scaffolded exchange and trade, including inter-temporal exchange, can help develop resolve.

To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within variable environments. This raises the question, how do cognitive systems achieve similarly high degrees of robustness? The aim of this study was to identify a set of mechanisms that enhance robustness (...) in cognitive systems. We identify three mechanisms that enhance robustness in biological and engineered systems: system control, redundancy, and adaptability. After surveying the psychological literature for evidence of these mechanisms, we provide simulations illustrating how each contributes to robust cognition in a different psychological domain: psychomotor vigilance, semantic memory, and strategy selection. These simulations highlight features of a mathematical approach for quantifying robustness, and they provide concrete examples of mechanisms for robust cognition. (shrink)

ABSTRACT The article begins by contrasting medical and moral views of addiction and how such views influence responsibility and policy analysis. It suggests that since addiction always involves action and action can always be morally evaluated, we must independently decide whether addicts do not meet responsibility criteria rather than begging the question and deciding by the label of ?disease? or ?moral weakness?. It then turns to the criteria for criminal responsibility and shows that the criteria for criminal responsibility, like the (...) criteria for addiction, are all folk psychological. Therefore, any scientific information about addiction must be ?translated? into the law's folk psychological criteria. Distractions about responsibility are then quickly canvassed. Then it addresses the direct relation between addiction and criminal responsibility. It argues that most addicts retain sufficient rational and control capacities at the relevant times to be held responsible, especially for crimes that are not part of the definition of addiction itself. It suggests that there is good reason to excuse or mitigate addicts for the crimes of purchase and possession for personal use. It concludes by briefly considering what contemporary science can contribute to our understanding of addiction and agency. (shrink)

The shift in the prevailing view of alcoholism from a moral paradigm towards a biomedical paradigm is often characterized as a form of biomedicalization. We will examine and critique three reasons offered for the claim that viewing alcoholism as a disease is morally problematic. The first is that the new conceptualization of alcoholism as a chronic brain disease will lead to individualization, e.g., a too narrow focus on the individual person, excluding cultural and social dimensions of alcoholism. The second claim (...) is that biomedicalization will lead to stigmatization and discrimination for both alcoholics and people who are at risk of becoming alcoholics. The third claim is that as a result of the biomedical point of view, the autonomy and responsibility of alcoholics and possibly even persons at risk may be unjustly restricted. Our conclusion is that the claims against the biomedical conceptualization of alcoholism as a chronic brain disease are neither specific nor convincing. Not only do some of these concerns also apply to the traditional moral model; above that they are not strong enough to justify the rejection of the new biomedical model altogether. The focus in the scientific and public debate should not be on some massive “biomedicalization objection” but on the various concerns underlying what is framed in terms of the biomedicalization of alcoholism. (shrink)

Though addiction is a complex empirical phenomenon, some of the most pressing questions about it concern how we should evaluate agents who are living with it. To that end, a fruitful methodology is to tease out from our best sciences consequences at the level of moral psychology. Taking account of epidemiology, behavioral science, animal studies and, chiefly, neuroscience, I argue for a view according to which addiction involves dysfunctional motivational states (which I call “hybrid intentions”) as well as cognitive distortions. (...) This argument can be made without needing to settle the traditional debate about whether addiction is a disease. (shrink)

Autonomy, the ability to make decisions for ourselves about ourselves, is among the most prized of human liberties. In this review we reconsider the key conditions necessary for autonomous decision making, long debated by moral philosophers and ethicists, in light of current neuroscientific evidence. The most widely accepted criteria for autonomy are that decisions are made by a rationally deliberative and reflective agent and that these decisions are free of undue external influences. The corpus of neuroscientific data suggest that human (...) brains are capable of the hierarchical control required for reflective thought, but that decisions conventionally perceived as autonomous may not be rational with respect to the deliberative process itself, and are rarely free from covert external influences. These findings cast doubt upon the capacity for autonomy as traditionally defined, and suggest that we reconsider valorizing the right to autonomy in order to align our moral values with neuroscientific naturalism. (shrink)

So far, the methodological debate about neuroeconomics rarely refers to original methodological positions in the neurosciences. I confront one of the most influential ones, the constitutive explanations or mechanism approach, with methodological claims that directly relate the economic model of choice with neuronal embodiments, represented by Glimcher’s influential work. Constitutive explanations are composite and non-reductionist, therefore allow for recognizing complex causal interactions between basal neuronal phenomena and cognitive structures, also involving external symbolic media. I demonstrate the power of this methodology (...) in discussing the example of money, which Glimcher posits as one of the most important research tasks in further developing neuroeconomics. Whereas Glimcher justifies neuroscientific reductionism by presenting an evolutionary rationale for deploying formal economic models on particular modules enabling choice, the case of money reveals the need for mechanistic explanations that include a substantial role for cultural evolution, though recognizing causal interactions with basal neuronal mechanisms. (shrink)

Theories of decision-making and its neural substrates have long assumed the existence of two distinct and competing valuation systems, variously described as goal-directed vs. habitual, or, more recently and based on statistical arguments, as model-free vs. model-based reinforcement-learning. Though both have been shown to control choices, the cognitive abilities associated with these systems are under ongoing investigation. Here we examine the link to cognitive abilities, and find that individual differences in processing speed covary with a shift from model-free to model-based (...) choice control in the presence of above-average working memory function. This suggests shared cognitive and neural processes; provides a bridge between literatures on intelligence and valuation; and may guide the development of process models of different valuation components. Furthermore, it provides a rationale for individual differences in the tendency to deploy valuation systems, which may be important for understanding the manifold neuropsychiatric diseases associated with malfunctions of valuation. (shrink)

The image of craving as a desire of unimaginable and irresistible force is poised to solve the puzzle of addiction: persistent drug use despite severe negative consequences. But the image is flawed. Drawing on science, philosophy, and first‐person testimony, I argue against irresistibility and develop a more nuanced, heterogeneous account of craving for drugs. Craving comes in three varieties, each corresponding to a kind of answer to the question why people crave drugs: cue‐induced, goal‐focused, and attachment‐based. This in turn grounds (...) an approach to addressing addiction that is humane and heterogeneous, moving beyond strategies that are fundamentally controlling. (shrink)

Building on an overview of dual systems theories in behavioural economics, the paper presents a methodological assessment in terms of the mechanistic explanations framework that has gained prominence in philosophy of the neurosciences. I conclude that they fail to meet the standards of causal explanations and I suggest an alternative ‘dual functions’ view based on Marr’s methodology of computational neuroscience. Recent psychological and neuroscience research undermines the case for a categorization of brain processes in terms of properties such as relative (...) speed. I defend an interpretation of dualities as functional, without assigning them to specific neurophysiological structures. (shrink)

The distinction that Ainslie draws among the triple-phenomena “suppression,” “resolve,” and “habit” is a great advance in decision making theory. But the conceptual machinery “willpower,” and its underpinning distinction between small/soon rewards as opposed to large/later rewards, provides a faulty framework to understand the triple-phenomena.