Beyond simple tests of value: measuring addiction as a heterogeneous disease of computation-specific valuation processes

Abstract

Addiction is considered to be a neurobiological disorder of learning and memory because addiction is capable of producing lasting changes in the brain. Recovering addicts chronically struggle with making poor decisions that ultimately lead to relapse, suggesting a view of addiction also as a neurobiological disorder of decision-making information processing. How the brain makes decisions depends on how decision-making processes access information stored as memories in the brain. Advancements in circuit-dissection tools and recent theories in neuroeconomics suggest that neurally dissociable valuation processes access distinct memories differently, and thus are uniquely susceptible as the brain changes during addiction. If addiction is to be considered a neurobiological disorder of memory, and thus decision-making, the heterogeneity with which information is both stored and processed must be taken into account in addiction studies. Addiction etiology can vary widely from person to person. We propose that addiction is not a single disease, nor simply a disorder of learning and memory, but rather a collection of symptoms of heterogeneous neurobiological diseases of distinct circuit-computation-specific decision-making processes.

Figure 1.

Tasks design matters when probing memory versus decision-making processes. (A) Memory and decision-making are thought to exist as duals of each other. How information is stored changes how it is processed. Different decision-making mechanisms access stored information traded off in different ways, and thus, select actions by fundamentally distinct computational algorithms. (B) Tasks that interrogate processes on varying time scales are better suited to probe memory versus decision-making computations. (C) Tasks designed measuring behaviors on those longer time scales (days) versus shorter time scales (within trial) are better suited to probe memory mechanisms (information storage, consolidation, updating) versus decision-making mechanisms (information processing and action-selection valuations). (D) Two task examples better suited to probe either memory processes (traditional paradigm: self-administration task) and decision-making processes (neuroeconomic paradigm: restaurant row task), both of which are capable of investigating aspects of reward-related self-control. (Top) In traditional operant chamber paradigms, principal or initial reward valuations (for food or drug) are measured during an acquisition learning period (usually across trials or days, estimated via break point on a progressive ratio lever-press sequence). Extinction periods can probe rates with which new valuation processes are learned that suppress principal valuations (across days). Active maintenance of extinction learning, or susceptibility to lose suppression following reinstatement, implies principal valuation memories coexist with extinction memories yet such competing computations are not accessible in traditional operant paradigms. (Bottom) In neuroeconomic paradigms, reward value can be calculated a number of ways within a single trial. In this version of the restaurant row task, hungry mice are trained to forage for food rewards of varying costs (delay, cued tone pitch) and subjective value (flavor, spatial contexts or restaurants) while on a limited time budget. Decisions are deconstructed into discrete stages in separate offer zones and wait zones on each trial in each restaurant. Each action-selection process reflects a valuation computation, each of which reflect different economic algorithms (choose between entering versus skipping in the offer zone, deciding to opt out and quit versus remain patient until earning in the wait zone, taking time to consume a pellet and linger in a conditioned place versus leave and advance to the next trial). In each of these action-selection processes, decision conflict and self-control can be separately captured between highly desired although expensive reward opportunities.

Figure 2.

Neuromodulation intervention strategy in combination with task design matters. (A,B) Online neuromodulation manipulations (e.g., circuit-specific optogenetic stimulation) describe those where stimulation (either activation of excitatory opsins like channelrhodopsin-2 [ChR2] or inhibitory opsins like halorhodopsin [HaloR]) is delivered during on-going behaviors of interest. This could be time-locked to cue or lever-presentation in traditional paradigms (A) where extinction maintenance or reinstatement susceptibility can be assessed. This could also be time-locked to distinct decision-making action-selection processes in neuroeconomic paradigms (B) during reevaluative change of mind decisions, for instance, only in high-conflict economic scenarios. However, in either (A) or (B), endogenous neural activity is disrupted. While this can reveal important information regarding on-going neural dynamics necessary or sufficient for certain behaviors, on-line neuromodulation actually reveals little regarding the functional consequences of synaptic plasticity in relation to addiction-related changes in neural circuitry. (C,D) Off-line neuromodulation interventions are capable of directly manipulating circuit-specific plasticity. For instance, well-characterized plasticity-inducing stimulation protocols (induction of long-term-depression in glutamatergic cortical pyramidal projections into the nucleus accumbens following 10 min of 10 Hz stimulation via ChR2) can be delivered acutely outside of behavioral testing. By observing lasting changes in behavior at later time points, the functional consequences of synaptic remodeling can be realized (e.g., mimicking disease states or reversing them). (C) By applying this approach in traditional paradigms, the functional consequences of circuit-specific synaptic remodeling on memory-related processes can be realized. (D) By applying this approach in neuroeconomic paradigms, the functional consequences of circuit-synaptic synaptic remodeling on separable decision-making computational processes can be realized.

Figure 3.

On addiction heterogeneity: Classes of plausible dysfunctions. (A) All drug use can be subdivided into casual drug use (majority) versus problematic drug use. (B) Individuals with problematic drug use can be divided into those with pathologies (originating cause) due to external, social factors versus pathologies rooted within the individual either via a predisposing vulnerability or a direct change induced by an ingested substance. (C) Internal pathologies can be divided into those with primary changes in neurons versus nonneuronal players (e.g., glia). (D) Neuronal changes, or plasticity, can be divided into changes that come about from normal mechanisms of learning and memory or a dysfunctional breakdown of such processes that normally do not occur. (E) Normal mechanisms of learning and memory can be driven in reward-related circuits by dopamine-mediated processes or non-dopamine-mediated processes (e.g., endocannabinoid signaling). Blue arrows in between nodes indicate interaction pathologies that could have either unidirectional or bidirectional influences on each other. (F) Any resultant changes in the brain that arise from internal pathologies, regardless of the underlying primary mechanism, can each induce failure modes in dissociable neural circuits, each of which can give rise to fundamentally distinct addiction etiologies in separable neural computations.