Table 2.

Brief summary of preclinical behavioral models most currently used to study the neurobiology of addiction: motivation and seeking in contingent models, models including alternative rewards.

Model	Advantages	Limits
Contingent—motivation for drug taking
Progressive Ratio (PR)	Simple task Can be done several times throughout training	Direct comparisons between different reinforcers not possible Reward on-board during test
Behavioral Economics	Can measure several parameters of motivation within one session Can be done several times throughout training Direct comparisons between different reinforcers possible	Complex data analysis
DSM Related	Modeled directly from DSM criteria Good face validity	Requires the use of several different behavioral paradigms Long protocol
Contingent—drug seeking and relapse
Cued-Reinstatement	Two types: discrete and discriminative cues Simple set-up Good face validity	Action precedes the reward-cue in discrete cue-induced reinstatement (usually reverse in human population)
Context-Reinstatement	Can assess the effects of a compilation of cues on different sensory modalities on drug-seeking behavior	Complex SA procedures (i.e. multiple contexts needed)
Prime-Reinstatement	Simple set-up Good face validity	Route of administration normally different than during SA\item Reward on-board during test
Stress-Reinstatement	Environmental and interoceptive stressors can be used Shown to increase relapse across several classes of drugs	Complex training with certain stressors Difficult to model complex human psychological stressors
Contingent drug seeking in presence of alternative rewards
Any model presenting competing choice between drugs and other rewards	Good face validity: models closer to human experience (not-limited to drug exposure exclusively) Myriad of alternative rewards available (appetitive foods, social interactions, enriched environment, etc.)	Complex study of the neurobiology of each reward Might require longer training and protocols Might require larger n and additional controls