Abstract
Appetitive conditioning—the process by which neutral cues acquire positive value through repeated pairing with rewards—is fundamental to adaptive behaviour. Disturbances in this process may contribute to psychiatric symptoms, yet unlike fear conditioning, it has been relatively underexplored in clinical populations. We systematically reviewed PubMed, Embase/MEDLINE, and PsycINFO (August 2025) for studies examining appetitive conditioning in psychiatric disorders. Of 7077 records, only five met inclusion criteria,: two on ADHD, two on compulsive sexual behaviour, and one on major depressive disorder. Patients demonstrated differences in reward-related neural and behavioural responses compared with controls, including reduced striatal activation during reward anticipation and heightened responses to reward receipt in ADHD, increased amygdala activation and disrupted striatal–prefrontal connectivity in compulsive sexual behaviour, and impaired probabilistic reward learning and decision-making in depression. None of the studies directly assessed de novo appetitive learning; instead, appetitive conditioning was employed as a preliminary paradigm to probe downstream reward processes. Thus, it remains unclear whether, or which, psychiatric disorders involve abnormalities in the formation of conditioned reward associations. Future controlled experiments that explicitly and directly test the learning processes associated with appetitive conditioning are needed to clarify its role in psychopathology and its potential as a target for intervention.
Keywords
1. Introduction
1.1. Rationale
Appetitive conditioning is a fundamental process in learning and behaviour and plays a pivotal role in shaping adaptive human responses to environmental stimuli. The capacity to acquire positively valanced associations and initiate appropriate goal-directed approach behaviours is both evolutionarily conserved cross-species, and critical to survival (Panksepp, 1998). Appetitive conditioning, a type of Pavlovian conditioning, occurs when an originally-neutral stimulus is paired with an unconditioned stimulus (UCS; one that directly elicits positive responses) enough times to elicit a positively valenced response. The originally neutral stimulus, to which there is a newly-formed positive response, then becomes known as the conditioned stimulus (CS). Appetitive conditioning is distinct from operant conditioning in that the latter refers to a process by which a reversible behaviour is reinforced by a particular response or the timing of a previous stimulus or reinforcement (Staddon & Cerutti, 2003).
Within the context of psychiatric disorders, disturbances in appetitive conditioning may be involved in the etiology, maintenance, and/or exacerbation of a multitude of psychiatric symptoms. This could include disorders previously characterized by disturbances in reward processing, such as major depressive disorder, attention-deficit hyperactivity disorder, schizophrenia, eating disorders, and/or substance use disorders (Haynos et al., 2020; Kenny, 2007; Ng et al., 2019; Zamora et al., 2025; Zeng et al., 2022). Disturbances in appetitive conditioning could manifest as excessive or deficient responses to rewarding stimuli, impairments in decision-making related to reward-seeking behaviours, and alterations in neural responses to reward; all of these aspects of reward, themselves, have been implicated to potentially play a role in multiple psychiatric disorders (Webber et al., 2021; Zald & Treadway, 2017).
Despite the potential for the translational importance of appetitive conditioning across psychiatric disorders, there has been little research focused on appetitive conditioning aberrancies and their causal connection to disordered symptoms. As a result, the exact, disorder-specific patterns of neural and behavioural aberrancies in appetitive conditioning are unclear.
The goal of this systematic review is to gather existing behavioural, neural, and physiological evidence on appetitive conditioning aberrant in psychiatric disorders, to explore evidence of disturbances in appetitive conditioning compared with healthy controls or associated with symptom dimensions. The review also aims to identify any evidence for neural or physiological mechanisms of conditioning disturbance across different disorders. To our knowledge, there have been no systematic reviews or other reviews published on this topic to-date.
1.2. Objectives
To describe the current state of research on appetitive conditioning in psychiatric disorders, identify abnormalities in appetitive conditioning in individuals with psychiatric disorders compared with healthy control populations, and to synthesize and qualitatively describe similarities and differences in appetitive processes across disorders.
2. Methods
2.1. Protocol and Registration
This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (Page et al., 2021) reporting guidelines. The review protocol was pre-registered on the International Prospective Register of Systematic Reviews, PROSPERO (ID CRD42022295971). The pre-registration can be accessed through the following link: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023476615.
2.2. Search Strategy
A literature search was conducted by one author on PubMed, PsycINFO (EBSCO), and the Embase/MEDLINE (Ovid) databases on August 6, 2025 to identify external papers on appetitive conditioning in psychiatric disorders. The search strategy included the following terms synonymous with, or closely related to, appetitive conditioning: appetitive conditioning, classical conditioning, pavlovian conditioning, associative learning, reward learning, and reward based learning AND the following terms synonymous with, or related to, psychiatric disorders: psychiatric disorder, psychiatry, psychopathology, mental disorder, and mental disease or diagnosis.
2.3. Study Eligibility Criteria
The inclusion criteria were as follows: 1) primary research studies on appetitive conditioning in a psychiatric condition, 2) studies with human participants meeting defined clinical criteria for a psychiatric, personality or addiction/substance use disorder and a matched control group (healthy; i.e. no psychiatric, personality or addiction/substance use disorders), and 3) studies with participants of any age, gender or ethnicity. The exclusion criteria were as follows: a) studies with individuals who only self-reported their diagnosis, b) records in languages other than English, animal studies, case studies, non-peer reviewed articles, conference papers, abstracts, review articles, meta-analyses, and letters to the editor, c) Studies including fewer than 5 individuals at follow-up assessment, d) studies exclusively of healthy controls which did not reference a psychiatric or personality disorder, and e) studies that used operant (behaviour) conditioning before classical conditioning.
2.4. Selection Process/Data Extraction
We used COVIDENCE to collect all chosen records for screening from the PubMed, PsycINFO (EBSCO), and the Embase/MEDLINE (Ovid) electronic databases. Two independent raters (two authors) screened the papers’ titles and abstracts against the inclusion criteria, and any conflict was resolved by a third independent rater/author.
The primary author then conducted a full-text review of the remaining studies in order to make the final selection. Two authors independently reviewed the included and excluded studies in the full text review and voted to reach a consensus on the included studies. After the eligible studies were selected, the data were extracted in a separate spreadsheet (Excel) according to the following aspects: Condition, Sample, Aim, Inclusion/Exclusion Criteria, fMRI/ROI (if applicable), Primary Outcome, Secondary Outcome, Design, Key Results.
2.5. Study Risk of Bias Assessment
Since we assessed the methodological quality of quantitative, non-randomized controlled trials, we used the Joanna Briggs Institute (JBI) Critical Appraisal Tool for quasi-experimental studies (Barker et al., 2023). The tool contains nine questions that assess several study aspects, including internal validity (e.g., bias related to temporal precedence or confound variables, questions 1-4), bias in terms of assessment, detection, and measurement of an outcome (question 5-7) and participant retention (question 8), and validity of statistical conclusions (question 9). The answer to each question was either “yes”, “no”, “unclear”, or “NA,” whether the study followed the specific guideline for a methodologically non-biased study.
The first author completed the checklist for each study, and arrived at a conclusion on the reliability and validity of the study, and thus whether to include/exclude it for review.
2.6. Study Synthesis
Only the studies that met the inclusion criteria and passed the JBI assessment were included for study synthesis. A narrative approach was used to synthesize the data from selected studies. The synthesis aimed to describe the existing literature on appetitive conditioning in psychiatric disorders and to identify similarities and/or differences in appetitive processes across the disorders. Since our synthesis followed a narrative approach, we qualitatively compared and contrasted reported differences in outcomes across the studies.
3. Results
3.1. Study Selection
7077 studies were imported from the PubMed, PsycINFO (EBSCO), and the Embase/MEDLINE (Ovid) databases that matched the keywords. 3997 studies were included for screening after duplicates were removed. See Figure 1. Of these, 42 studies passed the inclusion/exclusion criteria. Thirty eight of the 42 studies were excluded for reasons outlined in the figure, leaving five studies that were included for review. PRISMA flow diagram
Of note, many of the studies that mentioned appetitive conditioning in the title and/or abstract were ultimately excluded at the “Records screened” stage due to having experimental designs that used an operant conditioning component before classical conditioning.
3.2. Characteristics of Included Studies
One study examined neural responses to monetary reward anticipation and reward receipt in a sample of medical students with ADHD (n=14) and healthy controls (n=15) (Furukawa et al., 2014). They used a simple conditioning paradigm in which neutral stimuli were paired with either monetary reward (coins), or no-reward, as an fMRI task.
A second study by the same group conducted an fMRI investigation in 20 patients with ADHD and 20 healthy controls using non-monetary rewards (social affiliative stimuli, food stimulus) as the unconditioned stimuli that were paired with one of three initially neutral cues (Furukawa et al., 2022). Both this study and the Furukawa et al. (2014) study focused on brain activity in the striatum, given its dopaminergic-mediated involvement in reward learning, and because of previous evidence of its involvement in reward sensitivity in ADHD (Hoogman et al., 2011; Scheres et al., 2007).
The third study used a conditioning task paradigm during fMRI that paired an initially neutral stimulus (coloured squares) with highly erotic scenes (unconditioned stimuli; UCS) or non-sexual stimuli in 20 individuals with compulsive sexual behaviour who met proposed criteria for hypersexuality disorder (Kafka, 2014), and 20 controls (Klucken et al., 2016). The study focused on amygdala responses to conditioned cues, given its role in learning and emotion processing. Skin conductance responses were also measured.
The fourth study (Banca et al., 2016) used a conditioning fMRI task that paired an initially neutral stimulus (visual patterns) with sexual images, monetary images, or neutral grey boxes in 20 individuals who met criteria for compulsive sexual behaviour (specifically, meeting proposed criteria for Hypersexual Disorder and criteria for sexual addiction; Carnes et al., 2009; Kafka, 2010; Reid et al., 2012) and 40 healthy controls. They performed a whole-brain analysis and a dorsal anterior cingular cortex (dACC) ROI analysis. Pavlovian conditioning was followed by an instrumental conditioning task which is not discussed here.
The fifth study (Rupprechter et al., 2018) examined behavioural conditioning in 15 participants with major depressive disorder (MDD) and 17 healthy controls. The task was a probabilistic reward learning task where participants observed fractal stimuli paired with either a reward (a pound [£] symbol) or no reward (blank screen). Between these stimuli, there were decision screens in which participants were instructed to choose between observed fractals and an explicit numeric probability value. The authors included another dataset for validation purposes, consisting of 3 MDD patients and 21 control participants who did the same task. The authors obtained brain activation data using fMRI during the task, but reported only behavioural results in this paper.
Characteristics of the Included Studies
Legend: HC= Healthy Control; ADHD= Attention Deficit Disorder; CSB=Compulsive Sexual Behaviour; HC: Healthy Control; CS+: Conditioned Stimuli; CS-: Conditioned Stimuli.
Four of the five studies used neuroimaging (Banca et al., 2016; Furukawa et al., 2014; Furukawa et al., 2016; Klucken et al., 2016) and relied on neural responses as the main outcome measure, although they used different regions of interest (ROIs). Three neuroimaging studies (Furukawa et al., 2014; Furukawa et al., 2014; Klucken et al., 2016 used subjective measures to ensure that conditioning occurred while Banca et al., 2016 used behavioral button presses to ensure conditioning occurred. None however, used subjective measures as an indicator of differential appetitive conditioning between groups. The study by Rupprechter et al., 2018, on the other hand, focused on decision-making as the main outcome measure of conditioning.
3.3. Risk of Bias From Included Studies
All of the JBI checklist items were applicable to the studies, except for question 8 about long-term follow-up. All five papers passed all the criteria on the checklist and were eligible for inclusion, as they met the JBI criteria for a methodologically non-biased study. (It is important to note that the JBI criteria assess methodological soundness in terms of appropriate study design, conduct, and analysis (Barker et al., 2023) but do not address the conceptual adequacy or theoretical informativeness of the studies).
3.4. Results of Individual Studies
Furukawa et al. (2014) found distinct neural responses to monetary reward anticipation and reward delivery between the ADHD and control groups. Group X Condition interaction analyses showed a significant effect of group (ADHD vs control) and condition (reward delivery) on responses in the bilateral ventral striatum and the left dorsal striatum. During reward anticipation, ADHD showed significantly lower activation in the right ventral striatum and left dorsal striatum compared to the control group. The ADHD group however showed greater activation in the right and left ventral striatum and the left dorsal striatum in response to reward delivery. In addition, weaker bold signals in the left ventral caudate during reward anticipation, and stronger activation in the left ventral putamen during reward delivery, were significantly associated with severity of ADHD symptoms.
Fukuwara et al., 2022 also investigated reward anticipation and reward delivery in individuals with ADHD and healthy controls using a classical conditioning paradigm, but this time using rewarding stimuli consisting of social affiliative (pictures of two people engaging with each others) and food pictures. They found results for the affiliative but not food rewards that were consistent with the Fukuwara et al., 2014 study results using monetary stimuli. Specifically, the ADHD group showed reduced activation compared with controls to affiliative reward cues (anticipation) compared to neutral cues in bilateral ventral and dorsal striatal regions. In terms of rewarded outcome responses, the ADHD group showed greater magnitude neural responses in the right ventral striatum to affiliative reward vs. neutral outcomes compared to the control group. There were no group differences in response to food reward cues and outcomes vs. neutral cues and outcomes. Interaction analyses confirmed that there was a greater group difference for affiliative than for food cues in the right ventral striatum and the left dorsal striatum. In these regions, for reward cues, there was a main effect of group whereby controls showed greater responses than the ADHD group. No significant interaction or main effects of group were observed for reward outcomes.
Klucken et al., 2016; Banca et al., 2016 studied the neural correlates of reward responses after appetitive conditioning in men with compulsive sexual behaviour and matched controls using an fMRI task involving erotic pictures. Klucken et al., 2016 found that the CS+ (conditioned stimulus) was rated as significantly more positive, arousing, and sexually arousing than the CS- (non-conditioned stimulus) after the acquisition phase, indicating successful conditioning in both groups. There were no group differences in positive or negative valence or arousal ratings of the UCS, or with skin conductance responses towards the UCS or the CS+. In terms of the fMRI responses, there was increased amygdala activity in the compulsive sexual behaviour group compared to the control group for the CS+ vs the CS-. Furthermore, they conducted a psychophysiological interaction analysis to examine function connectivity among the ventral striatum, amygdala, and the ventromedial prefrontal cortex (vmPFC). Using the ventral striatum and the amygdala as seed regions, whole-brain analyses revealed decreased connectivity between the ventral striatum and the left prefrontal and right lateral prefrontal cortices in the compulsive sexual behaviour group compared to controls for CS+ vs. CS-. An additional, specific region of interest analysis of the vmPFC showed decreased connectivity between the ventral striatum and vmPFC in the compulsive sexual behaviour group compared with controls.
Banca et al., 2016 found increased brain activity, particularly in the occipital cortex, putamen, and thalamus to reward-predicting vs. neutral cues in both the compulsive sexual behaviour and healthy control groups during the conditioning and extinction phase. Furthermore, both groups showed reduced ventral striatal activity when sexual or monetary cues were unexpectedly omitted during extinction. The compulsive sexual behaviour group, however, showed a steeper decline in activity (faster habituation) in the dACC and inferior temporal cortex in the acquisition phase to sexual outcomes compared to controls. Faster habituation in the dACC was correlated with higher self-reported preference for sexual novelty, regardless of group. The authors also conducted a functional connectivity analysis for early versus late sexual outcomes between groups. Findings showed strong dACC connectivity in the right ventral striatum and bilateral hippocampus in early vs late trials in the control group, whereas the compulsive sexual behaviour group showed stronger connectivity in late versus early trials.
Ruppchreter et al., 2018 examined the use of reward values in decision-making in individuals with major depressive disorder (MDD) and healthy controls in an experiment that involved appetitive conditioning. Using a probabilistic reward learning task and computational modelling, they found evidence of worse learning ability in those with MDD compared with healthy controls, as well as impaired decision-making based on internal value estimations. Further, those with MDD compared with controls had decreased memory of the observed awards. Correlation analysis between model parameters and questionnaires showed that neuroticism was correlated with more variable decision-making across groups.
4. Discussion
This systematic review revealed only five studies that involved appetitive conditioning in psychiatric disorders in controlled research settings. Two studies were of adults with ADHD, two included adults with compulsive sexual behaviour, and one included adults with major depressive disorder. Notably, there were no studies on appetitive conditioning in populations with substance use disorders, eating disorders, or schizophrenia, where disturbance in appetitive learning have been most commonly implicated. None showed evidence of bias, using the JBI criteria. All 5 studies studies showed a disturbance in reward responses in the patient populations compared to controls. In five studies, reward-related neural activation as measured with fMRI was the primary outcome variable (Banca et al., 2016; Furukawa et al., 2014, 2022; Klucken et al., 2016) while for the fifth (Rupprechter et al., 2018) it was behavioural performance. However, while these five studies tested the effects of appetitive conditioning as part of the experiments, none explicitly studied the appetitive conditioning process itself in the clinical groups compared to healthy controls. Rather, the focus of these studies was on reward anticipation (Furukawa et al., 2014, 2022) and/or response to reward delivery (Furukawa et al., 2014, 2022; Klucken et al., 2016) or reinforcement learning and decision-making in the context of reward (Rupprechter et al., 2018), after the participants underwent classical (appetitive) conditioning. Because of the heterogeneity in design, outcome measures, regions of interest, and outcome measures and the small sample size of included studies, we will briefly compare and discuss the results, qualitatively.
The Furukawa et al., 2014; 2022 studies used dorsal and ventral striatal regions of interest, given evidence of their involvement in reward valence and processing from a previous meta-analysis (Liu et al., 2011). The studies revealed reduced activation in participants with ADHD compared with controls for reward anticipation but greater activation in response to reward delivery, both for monetary (Furukawa et al., 2014) and social affiliative (Furukawa et al., 2022) rewards. The authors interpreted the heightened response to reward delivery as potentially explaining ADHD patients’ tendency for immediate reward and difficulty delaying gratification. Further, for monetary rewards, Furukawa et al. (2014) found a significant, inverse correlation between activation in the left ventral caudate during reward anticipation, and number of ADHD hyperactivity/impulsivity symptoms. Further, there was a significant positive correlation between left ventral putamen activation during reward delivery and number of ADHD hyperactivity/impulsivity symptoms. Both studies examined reward anticipation and response to reward receipt, which are indirect effects of appetitive conditioning. Neither explicitly measured the learning process during appetitive conditioning.
Klucken et al., 2016 studied the amygdala and ventral striatum in the context of conditioning in patients with compulsive sexual behaviour. These regions of interest were chosen based on previous evidence of abnormal activity and connectivity in those with compulsive sexual behaviour when presented with sexual cues (Politis et al., 2013; Voon et al., 2014) and in general for their involvement in studies of those with addictive disorders and deficits of impulse control (Chase et al., 2011; Kühn & Gallinat, 2011). In the Klucken et al., 2016 study, the compulsive sexual behaviour group showed increased amygdala activity compared with the control group during conditioning; this is consistent with previous studies showing increased amygdala activity in addiction disorders (Koob, 2009; Luo, Xue, Shen, & Lu, 2013Luo et al., 2013). The known role of the amygdala in learning (Chau & Galvez, 2012), and its increased activity in the compulsive sexual behaviour group compared to healthy controls during appetitive conditioning using sexual stimuli, may indicate enhanced reward learning for sexual stimuli. The authors also found relative decoupling between the ventral striatum and ventromedial prefrontal cortex in compulsive sexual behaviour patients relative to controls, which may reflect impairments in inhibition and motor control.
Banca et al., 2016 also looked at conditioning responses to sexual stimuli in individuals with compulsive sexual behaviour versus controls, but they focused on reward receipt rather than reward anticipation like Klucken et al., 2016. They found that the compulsive sexual behaviour group showed faster habituation in the dACC to repeated sexual outcomes, along with increased functional connectivity between the dACC, ventral striatum, and hippocampus for later compared with earlier trials (the opposite pattern as seen in the controls). This suggests that, even though activation in regulatory regions like the dACC drops more quickly, people with compulsive sexual behaviour may be differentially engaging a reward–memory–learning network when processing sexual stimuli.
Compared to Klucken et al., 2016 who found increased amygdala and ventral striatum activity during the reward anticipation phase and reduced connectivity with ventromedial prefrontal cortex, Banca et al. highlight changes in the rewarded outcome phase rather than the anticipatory phase. Together, the studies suggest that neural mechanisms in those with compulsive sexual behaviour might be characterized by both heightened cue-reactivity and altered reward learning, with overlapping engagement of regions like the dACC and ventral striatum, but at different points in the conditioning process.
These two studies, examining a similar group of individuals with compulsive sexual behaviours meeting (proposed) criteria for hypersexuality disorder did, indeed, evaluate subjective responses directly related to appetitive conditioning (valence ratings) and directly measured neural activation during the appetitive conditioning learning period. However, neither explicitly evaluated the appetitive conditioning learning process as they did not employ, e.g., a computational model of learning over the course of the task. Rather, Klucken et al., 2016 examined averaged CS+ responses contrasted with averaged CS- responses and Banca et al., 2016 examined responses to sexual outcomes over repeated trials. Nevertheless, both studies provide indirect evidence for the possibility of differential neural involvement of the ventral striatum, and of ventral striatum-prefrontal cortex connectivity, during the appetitive conditioning process and beyond.
The Rupprechter et al. study was primarily focused on decision-making, which indirectly related to the effects of a prior appetitive (Pavlovian) conditioning phase, during which conditioned stimuli were paired with reward and no choices were made. The subsequent decision-making phase was thus (although not explicitly stated in the manuscript) contingent on successful conditioning from the Pavlovian phase. A main finding of the study that those with MDD showed impaired learning, which the authors attributed to possible deficits in working memory; however, this could have theoretically been confounded by differences from healthy controls in appetitive conditioning. This remains speculative, however, as it was not tested directly.
The five studies reviewed here, thus, utilized appetitive conditioning in their experiments; two (Banca et al., 2016; Klucken et al., 2016;) measured direct effects and three (Furukawa et al., 2014, 2022; Rupprechter et al., 2018) measured indirect effects. However, none specifically tested how associations with hedonic stimuli are learned de novo in these psychiatric conditions. Although studied extensively in animals (Martin-Soelch et al., 2007; Ricker & Boutoun, 1996Ricker & Bouton, 1996; Wood et al., 2006), there have been fewer studies of appetitive conditioning in humans, even in healthy controls. While the neural circuitry in humans may involve the striatum, amygdala, anterior cingulate cortex, and orbitofrontal cortex, many of these studies have only one aspect of appetitive conditioning: discriminative learning (responses to CS+ vs CS-; Tapia León et al., 2018) and reviewed in (Martin-Soelch, Linthicum, & Ernst, 2007Martin-Soelch et al., 2007). While the studies in this review that examined functional neural responses to reward found differences in clinical groups vs. healthy controls) in the striatum Furukawa et al. (2014); Furukawa et al., 2022 and the amygdala (Klucken et al., 2016) and dACC (Banca et al., 2016), these regions are also a part of reward circuits that commonly are found to subserve other reward processes. Thus, while it is possible that aberrant neural functioning in nodes of circuits involved in appetitive conditioning could have produced these results, it remains unclear since the studies did not isolate and examine neural responses during the conditioning phase.
4.1. Limitations
The main limitation of this review was that only five studies met the inclusion criteria. Further, none of the studies actually investigated de novo learning as part of appetitive conditioning, but rather performed appetitive conditioning as an initial step to investigate other reward phases. While many aspects of reward-related learning are critically implicated in psychiatric illnesses, the absence of any independent assessment of specific perturbations in do novo appetitive conditioning across psychiatric disorders is an important gap. Thus, we could not derive specific information about whether differences exist in appetitive conditioning, behaviourally, physiologically, or neurally, in individuals with psychiatric conditions compared with healthy controls. Furthermore, while our inclusion criteria was for all ages, our five studies included only adults. The reported results thus do not account for any developmental differences in appetitive outcomes.
5. Conclusions and Future Directions
This systematic review highlights the scarcity of research involving appetitive conditioning in psychiatric disorders, with only five eligible studies identified. In contrast to fear conditioning, which has been extensively studied across psychiatric populations (Duits et al., 2015; Trent et al., 2025), and has informed a multitude of therapeutic interventions for clinical populations (Inslicht et al., 2021; Maples-Keller et al., 2022), the dearth of appetitive conditioning studies is noteworthy. Moreover, and while all studies reported disturbances in reward responses among clinical populations, none explicitly investigated the appetitive conditioning process itself. Instead, the studies examined reward delivery after conditioning. Key findings included altered striatal activation in ADHD, heightened amygdala activity and enhanced habituation in dACC in those with compulsive sexual behaviour, and potential learning deficits in MDD affecting decision-making. While these findings theoretically could have contributions from aberrant appetitive conditioning, it cannot be determined from these studies. Thus, the question about how individuals with psychiatric disorders form and modify associations with hedonic stimuli remains open.
Future controlled experiments that explicitly and directly test the learning processes associated with appetitive conditioning are needed to clarify its role in psychopathology and its potential as a target for intervention. Such experiments could systematically test the different phases of appetitive conditioning, including acquisition, extinction, recall, and reinstatement (Bouton, 2004). They could also apply computational modelling of behaviour, physiology, and neural responses associated with learning rates and cue-reward association strengths, for example with the Recorla-Wagner model (Recorla & Wagner, 1972).
Appetitive conditioning has a well-established role in animal models of reward learning. In addition, secondary reward processing (that is, other than primary rewards that inherently reinforce and satisfy biological needs such as food, water, sex, or social affiliation (Schultz, 2015) and including, e.g., money, grades, and work accolades) drives many human behaviours, and is contingent with appetitive conditioning. Both primary and secondary rewards are both critical to survival and well-being in modern human life. Thus, studying the nature of disruptions in psychiatric populations could expand our theoretical knowledge of the causes of diminished or excessive experiences of reward that might contribute to the development of psychopathology and/or maintenance or persistence of symptoms. This, in turn, would aid in identification of treatment targets to, e.g., remediate underlying aberrant neural circuitry. Or, different strategies could provide compensatory approaches such as counter-conditioning to improve hedonic responses in individuals who have developed aversive conditioning to typically-rewarding stimuli such as food in those with anorexia nervosa or social interactions in those with social anxiety disorder, body dysmorphic disorder, or depression (Cameron et al., 2023; Garcia-Burgos et al., 2023; Hildebrandt et al., 2015; Keller et al., 2020).
Footnotes
Ethical Considerations
There are no human participants in this article and informed consent is not required.
Author Contributions
ZB: Conceptualization, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing. JF: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing. SM: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Data Availability Statement
Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.