
==== Front
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Neurosci Biobehav Rev
Neurosci Biobehav Rev
Neuroscience and biobehavioral reviews
0149-7634
1873-7528

39094280
10.1016/j.neubiorev.2024.105823
nihpa2015890
Article
Neuroimaging of the effects of drug exposure or self-administration in rodents: A systematic review
Drossel Gunner ab
Heilbronner Sarah R. c
Zimmermann Jan de
Zilverstand Anna bf*
a Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN, USA
b Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
c Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
d Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
e Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
f Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, MN, USA
* Correspondence to: 717 Delaware St. SE, Minneapolis, MN 55414, USA. annaz@umn.edu (A. Zilverstand).
17 8 2024
9 2024
01 8 2024
04 9 2024
164 105823105823
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
A systematic review of functional neuroimaging studies on drug (self-) administration in rodents is lacking. Here, we summarized effects of acute or chronic drug administration of various classes of drugs on brain function and determined consistency with human literature.

We performed a systematic literature search and identified 125 studies on in vivo rodent resting-state functional magnetic resonance imaging (n = 84) or positron emission tomography (n = 41) spanning depressants (n = 27), opioids (n = 23), stimulants (n = 72), and cannabis (n = 3).

Results primarily showed alterations in the striatum, consistent with the human literature. The anterior cingulate cortex and (nonspecific) prefrontal cortex were also frequently implicated. Upregulation was most often found after shorter administration and downregulation after long chronic administration, particularly in the striatum. Importantly, results were consistent across study design, administration models, imaging method, and animal states.

Results provide evidence of altered resting-state brain function in rodents upon drug administration, implicating the brain’s reward network analogous to human studies. However, alterations were more dynamic than previously known, with dynamic adaptation depending on the length of drug administration.

Functional neuroimaging
FMRI
PET
Drug addiction
Alcohol
Opioid
Cocaine
Nicotine
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pmc1. Introduction

Substance use disorders (SUDs) are a major source of morbidity and mortality (Degenhardt et al., 2018). In the United States, SUDs and their associated mortality have been rising steadily for decades (Ritchie et al., 2022; SAMHSA, 2023). The most recent report found that 48.7 million people aged 12 or older had a SUD in the past year (SAMHSA, 2023). While treatments are available, long-term relapse rates, even for those who do start treatment, are staggeringly high at up to 85 % (Decker et al., 2017; Kadam et al., 2017; Sinha, 2011). Therefore, the search for biomarkers of addiction vulnerability to guide the development of novel treatments continues.

1.1. Brain disease model of addiction

For decades, the predominant model guiding this search has been the Brain Disease Model of Addiction, which describes the neurobiological changes underlying human substance addiction (Volkow et al., 2016). This model led to a radical shift in the understanding of addiction and the establishment of the first pharmacotherapies for SUDs, such as treatments with drug agonists or antagonists (Volkow et al., 2016). The conceptualization of addiction as a brain disease traces back to a series of groundbreaking discoveries in neuroscience starting in the late 1960s, when Pickens, Thompson and Schuster established that drugs of abuse act as reinforcers on the brain (Pickens and Thompson, 1968; Schuster and Thompson, 1969). Schultz, Wise and colleagues later showed that repeated drug use fundamentally alters the brain’s ‘reward’ system, which originally evolved to respond to natural rewards (Schultz et al., 1992, 1997; Wise, 1987, 1988). The main theory derived from these basic neuroscience experiments posits that the increased “incentive salience” of drugs, specifically a ‘hyper-sensitization’ of the reward system to drug (cues) after repeated drug use, is the primary neurobiological mechanism underlying addiction (Robinson and Berridge, 1993) (for review, see (Berridge, 2007)). Compulsive drug-seeking, a characteristic of SUDs, was conceptualized as the inability to regulate reward-seeking (Jentsch and Taylor, 1999), while negative affect and withdrawal were described as dysregulations in the affective brain system caused by chronic activation of the reward system through substance use (Koob and Volkow, 2016). These findings suggested that assessing neural functional changes related to chronic substance use and addiction is critical for the development of more effective treatments for SUDs.

1.2. Brain networks implicated in humans with SUDs

Consistent with early preclinical findings, recent reviews of task and resting-state functional magnetic resonance imaging (fMRI) studies in humans with SUDs demonstrated altered brain function primarily in the brain’s reward network, encompassing the nucleus accumbens (NAc), orbitofrontal cortex (OFC), anterior prefrontal cortex (PFC) and subgenual/rostral anterior cingulate cortex (ACC) (Zilverstand et al., 2018a). Individuals with SUDs consistently show altered connectivity between regions of the reward network (mainly the striatum and more specifically the NAc) and other non-reward brain regions/networks, along with altered activation levels and connectivity within the reward network itself (Zilverstand et al., 2018a, 2018b; Fritz et al., 2022; Ieong and Yuan, 2017; London et al., 2015; Pandria et al., 2018; Pariyadath et al., 2016; Tanabe et al., 2019; Volkow et al., 2017; Wilcox et al., 2019; Zehra et al., 2018). Across various classes of substances of abuse, including stimulants, opioids, cannabis and depressants such as alcohol, regions of the brain’s reward network were dysregulated independent of the resting-state or task paradigm used (Zilverstand et al., 2018a; Fritz et al., 2022; Pandria et al., 2018; Batalla et al., 2014; Cupo et al., 2021). Most importantly, however, the level of dysregulation of the reward network correlated with measures of drug craving, addiction severity, years of use, use frequency, and relapse status (Zilverstand et al., 2018a; Fritz et al., 2022; Pandria et al., 2018; Wilcox et al., 2019; Zehra et al., 2018). Human neuroimaging literature across substances of abuse thus contains consistent reports on alterations of regions of the reward network, namely the striatum, ACC, and PFC, and these changes are dose-dependent within those with SUD (Zilverstand et al., 2018a).

1.3. Limitations in human neuroimaging research and benefit of preclinical work

One considerable limitation is the dearth of longitudinal human research designed to distinguish which neurobehavioral factors are outcomes rather than precursors of SUDs. This limitation arises largely due to the considerable difficulty in conducting such longitudinal studies, which require substantial sample sizes and follow-ups over many years. Therefore, the main advantage of preclinical research is the ability to conduct experimental longitudinal studies, in which animals are randomized to drug use versus no drug use conditions and assessed before and after drug exposure, thereby addressing the important question of consequence versus precursors. Additional advantages of preclinical neuroimaging research include the minimization of data ‘noise’ through the use of light anesthesia to reduce head motion and the ability to use ultra-high magnetic field strengths that greatly enhance image resolution (Febo et al., 2004). Furthermore, rodent models allow for larger uniformity in environmental and genetic backgrounds, necessitating smaller sample sizes to investigate individual differences compared to studies using non-human primates or humans (Hoyer et al., 2014). fMRI in rodents can also be combined with more invasive techniques, such as transcriptomics (Mills et al., 2018), wide-field calcium imaging (Lake et al., 2020), fiber-photometry (Schlegel et al., 2018), and optogenetics (Grandjean et al., 2019). Importantly, emerging research suggest that rodents share many features of cortical network organization with humans (Liang et al., 2011, 2013; Lu et al., 2012; Ma et al., 2018; Stafford et al., 2019), enhancing their translational value. Large portions of cortico-striatal circuitry, specifically, are well conserved across rodents, non-human primates, and humans (Balsters et al., 2020; Heilbronner et al., 2016). In summary, the utilization of preclinical models in neuroimaging research to investigate the effects of substances of abuse offers numerous translational benefits, notably enabling clear distinction between precursors and substance-induced changes in the brain.

1.4. State of preclinical neuroimaging research and goal of our review

Preclinical neuroimaging studies have investigated the effects of substance use on the brain. However, previous reviews of findings from non-invasive functional neuroimaging in preclinical models of substance use are scarce. In a review on functional neuroimaging findings in Alcohol Use Disorder (AUD), it was noted that fMRI studies in preclinical models are limited, with only two resting-state fMRI studies performed in rodents, both revealing altered prefrontal and striatal circuitry (Fritz et al., 2022). We found no reviews on non-invasive, in vivo functional neuroimaging approaches in preclinical models of chronic opioid, cannabis, or stimulant use. A recent review on acute cannabis exposure (that did not find any studies using fMRI) examined three positron emission tomography (PET) studies and found no reward network-related results (Cupo et al., 2021). Additionally, there is currently no systematic review that summarizes the literature on preclinical neuroimaging across multiple classes of substances. Overall, previously published reviews have been extremely limited in their reports on fMRI and PET neuroimaging of drug administration in preclinical models. Therefore, the purpose of this review was to systematically integrate the preclinical literature in rodents that has assessed the effects of administration of substances of abuse via neuroimaging using fMRI or PET. As preclinical data currently represents the only data source available for disentangling the consequences of substance use from individual differences in brain function that precede substance exposure, we reviewed the preclinical rodent literature to delineate brain regions exhibiting altered function as a consequence of substance exposure.

2. Methods

2.1. Study selection

The literature search was conducted on PubMed and combined variations of keywords related to functional neuroimaging, substance use, and rodent species. Once data extraction was complete, we performed a manual search for relevant papers by searching the introductions of the found papers. Studies were included if they were published in English, in a peer-reviewed journal, between January 1st, 2000 and May 15th, 2024. Search Syntax: (((fMRI) OR (MEMRI) OR (PET) OR (functional magnetic resonance imaging)) AND ((mouse OR mice OR rat)) AND ((addiction OR substance use disorder OR alcohol use disorder OR cannabis use disorder OR opioid use disorder OR cocaine use disorder))). Note on study inclusion: Studies were included only if they scanned rodents in vivo following administration of a substance of abuse (depressants, opioids, stimulants, cannabis), whether self-administered (by the animal itself) or non-voluntary (e.g., administration by an experimenter). See Fig. 1 for the PRISMA Flow Diagram on the number of found and included studies.

2.2. Data extraction

We summarized the main methodological details, including drug class (e.g., depressants, opioids, or stimulants), animal model (rat or mouse), number of animals, animal sex (male or female), animal age (adolescent or adult), length of drug administration (number of days), route of drug administration (e.g., intravascular or oral), imaging method (e.g., fMRI or PET), scanner Tesla strength (if applicable), anesthetization status (anesthetized or awake), anesthesia type, drug phase, and analysis details (Supplementary Table 1). Given the absence of a field-standard for chronic administration definitions across drugs of abuse, we categorized studies as acute, chronic [short] (2–21 days), chronic [long] (21 days or more), or a combination, based on existing literature (Carnicella et al., 2014; Coffey et al., 2018; Kasanetz et al., 2010). We first summarized results from studies performing the most common analysis: comparing a group of animals administered a substance of abuse with a control group (e.g., animals administered saline, vehicle, free air, etc.) (full details in Supplementary Table 2). Then, we compared these results with findings from studies that reported other analyses (e.g., Pre- versus Post-Drug Analysis, see Supplementary Table 3).

2.3. Data analysis

We assessed whether results were dependent upon drug class, administration paradigm, length of administration, imaging method, animal sex, animal age, anesthesia status, and rodent type. We reported whether regions were upregulated or downregulated. Specifically, we classified an increase in fMRI resting state functional connectivity and a metabolic increase in PET as “upregulation”, and conversely, a decrease as “downregulation”. In categorizing regions, specific regions were denoted as authors described. Nucleus accumbens was included within striatum (ventral), as were olfactory tubercles. Striatum (dorsal) included caudate and putamen. When authors did not specify striatum subregions, it was denoted as “striatum (unspecified/nonspecific)”. Substantia nigra was included as midbrain. Ventral, medial, and lateral orbital cortex were included as OFC. Motor 1 and 2 were included as Somatomotor cortex. Perirhinal and entorhinal cortex were included as rhinal cortex. For our purposes, ACC in rodents includes prelimbic cortex, infralimbic cortex, CG1, and CG2. It is worth noting that the CG1 and CG2 are sometimes referred to as ACC, but collectively all four of these regions comprise the rodent ACC. When specified in the original paper, we differentiated between caudal-dorsal ACC (CG1 and CG2) and rostral-ventral ACC (prelimbic and infralimbic cortices). When authors used the term medial PFC or PFC without additional designations, we used their terminology and grouped these as “PFC (nonspecific)”. Importantly, in the Results section, all summarized findings were corrected for ‘spotlight effects’ by computing percentages based on the total number of studies that included a specific region in their analyses, rather than total number of studies reviewed. We discuss the most important region (i.e., the most implicated regions) for subcortical and cortical findings. Lastly, we reported whether any of the papers described correlations between brain activity and behavioral data.

3. Results

A total of 125 papers were included. A list of all included papers in alphabetical order is provided in the Supplemental Material. Fig. 2a shows the number of studies by publication year. There was an increase in studies in the past 10–12 years, as compared to the years prior. Notably, only 13 % of studies included female animals (Fig. 2b). Out of the 125 included studies, 27 focused on depressants (1 benzodiazepine, 1 phenobarbital, and 25 alcohol papers), 23 on opioids (7 heroin, 12 morphine, 4 oxycodone papers), 72 on stimulants (4 amphetamine, 35 cocaine, 1 cocaine & amphetamine, 2 cocaine & methamphetamine, 2 methylenedioxypyrovalerone, 5 methamphetamine, 8 methylphenidate, and 15 nicotine papers), and 3 papers examined tetrahydrocannabinol (THC) (Fig. 3). Significant results from each study are reported by subcortical results (Table 1) and cortical results (Table 2).

3.1. Group comparison: drug to control group

The most common analysis amongst the papers involved a group comparison between animals administered a substance and a control group (e.g., animals administered a control substance such as saline, water, vehicle, etc.), which was performed in 84 papers (Supplementary Table 2). Of these studies, 20 investigated depressants, 16 investigated opioids, and 45 investigated stimulants. Only three studies were on cannabis, which will not be discussed here, but details are included in Supplementary Tables 1-2.

Here, we focus on the most consistently implicated subcortical region, the striatum, and the most consistently implicated cortical regions, the ACC and the PFC (nonspecific), which may also include ACC. In 88 % of the 81 studies spanning depressants, opioids, and stimulants, the striatum was included in the analyses. The PFC (nonspecific) was included in 67 % of these 81 studies, and 64 % included the ACC specifically. Counts of papers by drug class that assessed each of these regions are provided in Supplementary Table 4. Correcting for spotlight effects (considering that not all papers analyzed results from all brain regions), the striatum was the only region that was implicated in more than 50 % of studies across drug classes (59 % of 17 Depressants studies, 62 % of 13 Opioids studies, and 59 % of 41 Stimulants studies) (Table 3). The striatum was upregulated 60 % of the time for depressants and 58 % for stimulants, while the directionality was mixed for opioids (Supplementary Table 5). Counts for significant cortical regions by drug class are summarized in Table 4. At the cortical level, the ACC was highly implicated, but less frequently than the striatum (for Depressants: 50 % of 12 papers; for Stimulants: 48 % of 29 papers). The ACC was upregulated in over 57 % of results for both drug classes (Supplementary Table 5). The PFC (nonspecific) was highly implicated for Stimulants only (48 % of 31 papers, 67 % upregulated) (Supplementary Table 5). For depressants and opioids, the PFC (nonspecific) was not implicated consistently. See Fig. 4a-c for a visualization of the percent of studies implicating each region prior to spotlight effect correction (Fig. 4a-b) and for the striatum, ACC, and PFC (nonspecific) following spotlight effect correction (Fig. 4c). In summary, after adjusting for spotlight effects, the brain region that was affected most consistently across drug classes was the striatum. Most commonly, the striatum was upregulated with drug administration.

3.2. Pre- versus post-drug analysis

A total of 32 papers included within-subjects comparisons that compared pre- versus post-drug administration brain function (Supplementary Table 6). Of these studies, 66 % focused on stimulants, 25 % on depressants and 9 % on opioids. In the 21 stimulant papers, all of which included the striatum in their analyses, the striatum was the only subcortical region implicated in over half (57 %) of the studies. It was upregulated in 80 % of them. Cortical results from the stimulants papers were too limited to draw general conclusions. Results from the depressants and opioids papers were also limited and could therefore not be integrated. In summary, for stimulant studies, the results comparing pre- versus post-drug administration converged with the results from drug versus control group comparisons, such that the striatum was the most frequently reported region and was, generally, upregulated following drug administration.

3.3. Self-administration versus non-voluntary administration

Eighty-six (69 %) of the total 125 papers used non-voluntary drug administration, with the remaining papers employing voluntary self-administration (Fig. 5a). Results separated by administration procedure are summarized in Supplementary Table 7. Within the 20 depressants studies, 60 % used self-administration. Correcting for spotlight effects, the striatum was implicated in 55 % of the 12 depressant self-administration studies (50 % upregulated), and in 75 % of the 6 depressant non-voluntary administration studies (75 % upregulated). The ACC was implicated in 36 % of the 11 depressant self-administration studies (75 % upregulated) and in 100 % of the 2 depressant non-voluntary administration studies (50 % upregulated). For opioid studies, 63 % of the 16 studies used non-voluntary administration. The striatum was implicated in 67 % of the 6 opioid self-administration studies, with mixed directionality, and in 57 % of the 7 opioid non-voluntary administration studies, again with mixed directionality of effects. For stimulants studies, 76 % of the 45 papers used non-voluntary administration. The striatum was implicated in 33 % of the 9 self-administration studies (33 % upregulated) and in 61 % of 31 non-voluntary administration studies (63 % upregulated). The ACC was implicated in 43 % of the 7 self-administration stimulant studies (33 % upregulated) and in 48 % of the 21 non-voluntary stimulants studies (60 % upregulated). The PFC (nonspecific) was implicated in 29 % of the 7 self-administration studies (100 % downregulated) and in 52 % of the 23 non-voluntary stimulants studies (75 % upregulated). In summary, results were consistent between self- versus non-voluntary administration procedures, with more robust results in non-voluntary administration studies.

3.4. Acute versus chronic (‘short’ and ‘long’)

Of the 125 papers, 23 % used acute administration, 45 % used chronic ‘short’ administration, and 32 % used chronic ‘long’ administration (Fig. 5b). Results separated by length of administration are reported in Supplementary Table 8. Out of the 19 depressants studies, none used acute administration, and only 2 studies used chronic ‘short’ administration. For opioids, only two out of the 16 studies used acute administration, and none used ‘chronic long’ administration. Thus, the distribution of studies across different lengths of administration were too limited for these two drug classes to allow for comparison between lengths of administration. Of the 45 stimulants papers, 24 % used acute administration, 47 % used chronic ‘short’ administration, and 29 % used chronic ‘long’ administration. The striatum was implicated in 82 % of the 11 acute stimulants studies that investigated this region, with upregulation reported in 78 % of these studies. In chronic ‘short’ studies (18 total), the striatum was implicated in 63 % and upregulated in 60 % of them. For chronic ‘long’ studies (13 total), the striatum was implicated in 38 % of studies. Contrary to acute and ‘short’ chronic studies, the striatum was downregulated in 60 % of chronic ‘long’ studies. Similarly, the ACC was implicated in 57 % of the 7 acute stimulants studies, being upregulated in 100 % of them. The ACC was implicated in 27 % of the 15 chronic ‘short’ stimulant studies, but only upregulated in 25 %. The ACC was implicated in 75 % of the 8 chronic ‘long’ stimulant studies, being upregulated in 50 %. For acute stimulants studies (8 total), the PFC (nonspecific) was implicated in 100 % of studies and upregulated in 88 % of them. The PFC (nonspecific) was implicated in 33 % of the 15 chronic ‘short’ stimulants studies and upregulated in 40 %. In the 9 chronic ‘long’ stimulants studies, the PFC (nonspecific) was implicated in 33 % and upregulated in 67 % of them. Importantly, our analysis of the length of stimulant administration revealed an effect on directionality. In summary, during acute administration, the striatum, ACC, and PFC (nonspecific) were consistently upregulated (78–100 %). This effect was weaker after chronic ‘short’ administration (25–60 % upregulated) and was partially reversed after chronic ‘long’ administration. The ACC and the PFC (nonspecific) were upregulated in 50–67 % of chronic ‘long’ administration studies, while the striatum was downregulated in 60 % of chronic ‘long’ administration studies. The reversal of striatal engagement with longer administration length suggests that these effects are not linear but dynamic over time.

3.5. fMRI versus PET

A breakdown of the number of studies using fMRI versus PET techniques are shown in Fig. 5c with results reported in Supplementary Table 9. Subcortical results were similar when separated by imaging method. The striatum was implicated in 63 % of the 8 fMRI depressants studies (50 % upregulated), and in 50 % of the 10 PET depressants studies (80 % upregulated), correcting for spotlight effects. The ACC was implicated in 71 % of the 7 fMRI depressant studies (80 % upregulated), but only in 17 % of the 6 PET depressant studies (100 % downregulated). The PFC (nonspecific) was implicated in 40 % of the 5 fMRI depressant studies (100 % downregulated), but in only 14 % the 7 PET depressants studies (100 % downregulated). The striatum was implicated in 88 % of the 8 fMRI opioid studies (57 % downregulated), but in only 20 % of the 5 PET opioid studies (100 % upregulated). The ACC was implicated in only 13 % of the 8 fMRI opioid studies that included it in analysis (100 % upregulated), but in 66 % of the 3 PET opioid studies (50 % upregulated). The PFC (nonspecific) was implicated in 25 % of the 8 fMRI opioid studies (100 % upregulated), and none of the 3 PET opioid studies. The striatum was implicated in 62 % of the 31 fMRI stimulants studies (63 % upregulated), and in 45 % of the 11 PET stimulants studies (50 % upregulated). The ACC was implicated in 50 % of the 24 fMRI stimulants studies (50 % upregulated), but in only 33 % of the 6 PET stimulants studies (100 % upregulated). The PFC (nonspecific) was implicated in 52 % of the 27 fMRI stimulants studies (64 % upregulated), but in only 40 % of 5 PET stimulants studies (100 % upregulated). Overall, effects were thus more robust for fMRI imaging studies as compared to PET imaging studies.

3.6. Results from adolescent animals

One hundred and seven (86 %) out of the 125 papers were on adult animals (Fig. 5d). The number of studies that used adolescent animals was thus too low to systematically compare results between adolescents and adults. Results separated by adults versus adolescents are reported in Supplementary Table 10). Briefly, similar to adult findings, the majority of studies conducted in adolescent animals implicated the striatum and the ACC (with mixed directionality). Only one study used male and female adolescent animals.

3.7. Results from mice

Only 18 (14.4 %) of the total 125 studies included mice. Among studies comparing drug to control, only 5 out of 20 Depressants studies, 2 out of 16 opioid studies, and 6 out of 45 stimulants studies were conducted on mice, all of which used adult animals. Significant results for the striatum, ACC, and PFC (nonspecific) were very limited within mice studies, with each of these three regions implicated in only 1–2 studies within each drug class (Supplementary Table 11).

3.8. Anesthetization

The majority of studies (89 %) reported here used anesthetized animals (Supplementary Table 12). Among the studies that used anesthetized animals and compared a drug to a control group, 63 % exclusively used isoflurane (ISO) in oxygen (at various percentages) for anesthesia. Other studies used different substances such as dexmedetomidine (DEX), halothane, or various combinations (e.g., ISO and DEX). Many studies did not list anesthesia specifics. There were no awake depressant studies comparing drug to control. There were only 2 awake studies conducted in opioids, both of which reported no cortical results but indicated downregulation of several subcortical regions, including the striatum. There were 7 awake stimulants studies comparing drug to control. The striatum was implicated in 66 % of the 6 awake stimulants studies (50 % upregulated) that included it in their analysis, the ACC was implicated in 25 % of the 4 awake stimulants studies (100 % upregulated) that investigated the ACC, and the PFC (nonspecific) was implicated in 50 % of the respective 4 awake stimulant studies (50 % upregulated) that investigated the PFC. These results were thus consistent with the results reported above.

3.9. Other comparisons and analyses

Finally, 41 papers conducted comparisons that were neither a drug to control group comparison nor a within-subjects pre- to post-drug analysis. These comparisons were varied, some assessing across animal strains or across various drug concentrations. Only 1 study in depressants and 9 studies in stimulants compared between strains (strains that are more or less susceptible to drug effects versus control strains). In these 9 stimulants studies, the striatum was the only region implicated nearly half of the time (44 %), and it was upregulated in 75 % of studies (for strains designed to be more susceptible/preferential toward drug effects) (Supplementary Table 13). Only 1 depressant, 3 opioid, and 8 stimulant studies compared between various drug concentrations (or short versus long access to drug) within animals. In the 8 stimulant studies, the striatum was implicated in 63 % of them (40 % upregulated, most often in the ventral striatum), while the ACC was implicated in 50 % of the 6 studies that investigated it (33 % upregulated). A summary of the counts of implicated regions and the directionality of effects are reported in Supplementary Table 14. Lastly, only 5 % of the 125 papers included both male and female animals; sex differences could therefore not be reviewed.

3.10. Brain and behavior correlations

Overall, only 16 papers (13 %) assessed brain-behavior correlations (see Table 5), and of these, 25 % did not provide specific correlation values. Most studies assessing brain-behavior correlations found positive correlations with drug-related behavior.

4. Discussion

The goal of this review was to systematically integrate the rodent neuroimaging literature on (self-) administration of substances of abuse across different classes of drugs and to delineate brain regions exhibiting altered function as a consequence of substance exposure. Based on both the basic neuroscience and human neuroimaging literature, we expected the brain’s reward network to be primarily affected as a direct consequence of substance (self-) administration, as measured by neuroimaging. We precisely found that.

4.1. Brain regions altered by drug exposure (group/pre-versus-post comparison)

The main reward network regions previously reported as altered in human drug addiction (striatum and ACC) were consistently found to be altered in the reviewed papers. The striatum was affected across drug classes in more than 50 % of studies independent of the study design used (drug versus control group or within-subject comparisons). Considering that not all analyses were whole-brain and that there is an inherent bias associated with region-of-interest (ROI) and seed selection analyses, we corrected for these spotlight effects. Generally, the striatum was upregulated, although administration length seemed to impact directionality. Upregulation was most frequently found after shorter administration length, whereas downregulation was more prevalent after chronic long-term administration. The differential effects observed in the striatum with longer administration periods are potentially due to the development of drug tolerance with prolonged administration (Siciliano et al., 2016). This has been reported in rodent studies with cocaine (Kohno et al., 2019), as well as in human studies of stimulant administration that revealed differential effects following acute versus chronic administration (Taylor et al., 2013). Although less frequently implicated than the striatum, the ACC was also frequently affected, particularly with acute or short-term administration, and generally showed upregulation in the studies with shorter administration. Interestingly, the OFC did not appear as frequently affected as the ACC and general PFC (nonspecific). Importantly, the same results were consistently reported independent of study design (between group comparisons or within-subject comparisons), the mode of administration used (self-administration versus non-voluntary administration), the imaging method employed (fMRI versus PET) or the state of the animal (anesthetized versus awake). Results were more robust for fMRI (versus PET) studies and for non-voluntary (versus self-) administration.

4.2. Effect of administration type

Interestingly, the results from studies using non-voluntary administration reported here were more robust compared to those using self-administration of drugs of abuse. This difference may be due to higher levels of drug administration in non-voluntary studies. Previous literature has reported marked differences between administration methods used (Levis et al., 2022), highlighting differences in the brain circuitry involved in studies with experimenter-imposed versus self-imposed drug administration (Farrell et al., 2018). While non-voluntary administration ensures high levels of drug are administered, this method removes the key aspect of human drug use, which is volition. Thus, self-administration procedures are more suitable for translatability to humans (Charlton et al., 2019). However, it may be difficult to achieve truly translational models of self-administration due to the complexity of human drug use. For example, the environments in which humans grow up are much more varied than the controlled environmental conditions that experimental animals are raised.

4.3. Impact of drug exposure length

In the human neuroimaging literature, brain regions of the reward network often display upregulation following drug exposure, also after long-term chronic substance administration. However, our findings here indicate an upregulation of core regions of the brain’s reward network with acute/short-term administration, but a downregulation with chronic (self-) administration. These discrepancies may arise from differences in the timing of imaging subjects. While rodents are generally imaged in early (and often forced) abstinence within a few days following chronic self-administration, participants in human studies are often abstinent for longer periods of time before neuroimaging takes place. Very few of the studies reviewed here imaged animals at periods exceeding 4 weeks of abstinence following more than 3 weeks of chronic administration. However, this is often the case with studies on humans with SUDs (Parvaz et al., 2022). Importantly, the literature on incubation of craving during abstinence suggests that adaptations of the reward network are ongoing even during abstinence and are particularly dynamic in the first weeks of abstinence (Parvaz et al., 2016; Zilverstand et al., 2023). Overall, the studies reviewed here support that preclinical neuroimaging is an important tool to investigate adaptations of the brain’s reward network longitudinally, with more research needed to investigate adaptations across different abstinence lengths. This may be particularly important during early abstinence when incubation of craving is most likely to occur after long chronic administration of substances.

4.4. Comparing between fMRI and PET

Studies using a variety of MRI and PET methods were included in this review. Some used fluorodeoxyglucose (FDG) PET, which uses a radio-labeled sugar molecule. Others, for example, used a version of PET which measures cholesterol transport. Regarding MRI, several studies used manganese-enhanced MRI (MEMRI), which enhances the image signal taken during the T1-weighted relaxation time (Inoue et al., 2011). One study used molecular contrast-enhanced (MCE) MRI, which generates contrast agents specific to histone deacetylase 5 (HDAC5), an enzyme that modifies chromatin and has a role in learning and memory (Liu and Liu, 2016). Lastly, one paper used Overhauser-enhanced MRI (OMRI), a double resonance technique that enhances nuclear spin signal intensity (Yamato et al., 2009) and allows the researchers to non-invasively detect redox status in mitochondria (Shiba et al., 2011). While these methods have not all been compared to each other, each has its advantages, broadly summarized by Tournier et al (Tournier et al., 2021). One previous study compared a version of PET imaging ([15O] H2O-PET] to fMRI in rats and reported differences in maximum relative signal changes, number of activated voxels, activation center location, and contrast-to-noise ratio (Wehrl et al., 2014). The paper notes that the methods could ideally be used in a complementary manner. However, our results support that the main findings remain similar regardless of the specific neuroimaging methodology used.

4.5. Notes on anesthetization

Finally, results here were largely from freely-breathing animals anesthetized using isoflurane at various percentages. Overall, awake animal studies are in the early stages, with setup, design, and data analysis still presenting challenges to researchers (Ferris, 2022). It has been shown that anesthesia can affect the functional connectivity of brains in rats and mice (Becq et al., 2020; Bukhari et al., 2017; Grandjean et al., 2014; Liu et al., 2021; Wu et al., 2017; Xie et al., 2020), with the strength of this effect depending on the specific anesthetization protocol used. Previous literature comparing awake to anesthetized animals found 1.5–2 times higher cerebral oxygen metabolism in mice when awake compared to when anesthetized, depending on the brain region (Xu et al., 2022). Crucially, however, such an effect would be similar across all brain regions, and an upregulation of the brain reward network, relative to other brain networks, would thus still be measurable. In the few awake studies that we reviewed, we found that results were generally consistent with the neuroimaging findings from anesthetized animals.

4.6. Limitations and suggestions for future studies

Other variables of interest that we hoped to review were sex, rodent type (rat vs. mice), and developmental stage (adolescent vs. adult). Details on the reasoning for the importance of these comparisons, along with the limited available findings, are described below.

4.6.1. Limited research on sex/gender

From behavioral research in rodent and human addiction, clear differences in sex and gender influence the onset and maintenance of addiction across drugs of abuse (Fattore et al., 2008; Maxwell et al., 2022; McHugh et al., 2018; Nicolas et al., 2022; Swalve et al., 2016). A recent review on the brain circuitry involved in addiction demonstrated sex differences in neurocircuitry and highlighted a separation of functional dimensions related to substance use between males and females (Maxwell et al., 2023). This underscores the need for research on sex differences in brain function related to drug administration (Maxwell et al., 2023). Notably, most rodent neuroimaging studies reviewed here only assessed males, even though NIH-funded research has expected studies to include sex as a biological variable since January 2016 (National Institutes of Health, 2015). Out of all 125 studies, only 6 included both males and females, and among these, 4 compared drug to control. Eleven studies included only females and only two of these compared drug to control. Determining the presence of sex differences across all studies reviewed was therefore not possible. Here we highlight the 4 papers that reported sex differences. Perez and colleagues injected rats with cocaine or control either acutely or for 10 days and subsequently imaged the animals via MEMRI at 3 days of withdrawal (Perez et al., 2018). Following cocaine, activity in the hippocampus and the interpeduncular nuclei of the midbrain was increased in females only, whereas activity in the VTA decreased for only males. Another study by Coleman and colleagues administered THC vapor or placebo for 28 days to adolescent mice. They found higher engagement of the thalamus, hypothalamus and the brainstem reticular activating system in males compared to females (both with THC vapor exposure) (Coleman et al., 2022). Rama-Lamanna and colleagues assessed sex differences in response to morphine withdrawal in rats. They reported that females demonstrated greater and longer-lasting alterations in global brain metabolism following morphine withdrawal than males (Lamann Rama et al., 2023). Frie and colleagues scanned rats at 9.4 T following non-voluntary nicotine vapor administration and reported lower functional connectivity in the hypothalamus, colliculus, ACC, hippocampus, and various cortical regions in female compared to male rats (Frie et al., 2024). In summary, the few included studies that assessed sex differences reported significantly different findings between males and females, further supporting the need for sex as a biological variable to always be considered in preclinical addiction neuroimaging research.

4.6.2. Limited research in adolescent animals

Another comparison to investigate are the neurofunctional results in adolescent versus adult animals following drug administration. It is known that adolescence is a period of high neuroplasticity in which the brain’s dopamine system is more functionally active and prone to be altered by substance abuse, and that large individual differences are present during this sensitive period (Ernst and Luciana, 2015; Fuhrmann et al., 2015). In humans, substance use often rises in adolescence, and can lead to long-lasting structural and functional neural effects that extend beyond adolescence, as demonstrated in rodents (Ernst and Luciana, 2015; Lees et al., 2020; Spear, 2018). However, studies on adolescents in this review were too limited in number to compare them to studies using adults. One study compared adolescent and adult rats administered nicotine vapor, and while they reported sex differences in functional connectivity (discussed above), they did not report significant differences by animal age (Frie et al., 2024). A noteworthy paper investigated Sprague-Dawley rats that began non-voluntary oral methylphenidate administration during periadolescence and were scanned at 2 and 8 months into drug administration, with acute alcohol applied at the time of the PET scan. Convergent with the literature discussed above, they found an effect in the striatum. At the 2-month time point, they found negative striatal metabolism that switched to positive at 8-months. The authors highlighted that dopamine 2 receptor expression in the striatum is sensitive to the length of drug treatment (Thanos et al., 2007), converging with our overall conclusions. This very limited comparison between adolescents and adults shows that a crucial addiction-relevant region (the striatum) demonstrates varied functional activity in response to drugs during early development. This highlights the critical importance of assessing this developmental period in rodent neuroimaging of drug administration.

4.6.3. Limited research in mice

In comparison to rat studies, mouse studies were limited in number and yielded limited results. Researchers likely prefer using rats for neuroimaging research due to the technical challenges associated with scanning smaller sized brains. The brains of mice are at least 3 times smaller than rats (Krafft et al., 2012). This typically makes the resolution of mouse brain images worse and even at the high field strengths commonly used (e.g., 4.7 T+), signal-to-noise ratios and image artifacts are increased (Denic et al., 2011). In mice, striatal volumes range from 20 to 37 mm3 (Rosen and Williams, 2001), whereas in rats, the average volume of the dorsal striatum alone is 35–56 mm3 (Andersson et al., 2002). Jonckers and colleagues compared rat with mouse rs-fMRI studies, and concluded that unilateral cortical components were more commonly implicated in mice, whereas bilateral cortical results were more common for rats (Jonckers et al., 2011). The vast brain size difference and the associated greater technical complexity likely contribute to the difficulty in mouse studies to determine specific regional activation using currently available protocols. Additionally, in many mouse studies, various strains were used, and neuroimaging results assessed by fMRI and PET have been reported to vary by strain (Shah et al., 2016). Interestingly, another group reported differences in the directionality of effects across rat strains and discussed that it may relate to the individual differences seen in people with SUDs (Soto-Montenegro et al., 2022). Future research should focus on comparing effects of drug(s) across strains within mice or rats.

Finally, limitations in the reviewed literature include the lack of rodent studies on depressants and opioids, as well as the paucity of research on cannabis administration.

5. Conclusion

Our review aimed to delineate the brain regions that demonstrated altered function as a consequence of substance exposure. Results found in rodent neuroimaging studies of drug self-administration primarily implicate the brain’s reward network, specifically the striatum. These effects correspond to those observed in the human SUD literature. Overall, the studies reviewed here provide important complementary information to human neuroimaging studies. The reviewed literature suggests that alterations in the brain’s reward network are dynamic, with upregulation found after shorter administration lengths and downregulation of core regions of the brain’s reward network observed when imaging after chronic long-term administration. These observations underscore the value of preclinical neuroimaging to elucidate these complex adaptations. Future investigations should also explore effects of depressants, opioids, and cannabis and need to include sex as a biological variable.

Supplementary Material

MMC1

Acknowledgements

We thank Andrea M. Maxwell and Leyla R. Brucar for their helpful comments on the manuscript. This work was supported by grants from the National Institute on Alcohol Abuse and Alcoholism (R01AA029406-01A1 to A.Z.), the National Institute on Drug Abuse (P30DA048742-01A1 to S.H, J.Z., A.Z. and 5T32DA007234-29 to G.D.), the National Institute on Mental Health (R01MH118257 to S.R.H.), the National Institute for Biomedical Imaging and Bioengineering (R01EB031765 and P41EB027061 to J.Z.) and the Robert and Janice McNair Foundation (to S.R.H.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Fig. 1. PRISMA Flow Diagram. Chart of systematic review process following the PRISMA flow chart.

Fig. 2. (a) Number of Studies Published by Year. Years are not included on the X-axis if no studies included in this review were published in that year. (b) Number of Animals Scanned by Sex Per Study. Female animals are represented as black bars, and male animals are represented as grey bars. Bars are stacked if the study included both females and males. One study did not report explicitly the number of animals or sex. N = 125 studies. N = 6–73 animals per sex per study.

Fig. 3. Drugs Studied. Pie chart showing the percentage of all studies assessing each drug type. Red hues represent stimulants, green hues represent opioids, blue hues represent depressants, and bright green represents cannabis. N = 125. Abbreviations: ALC = alcohol, AMPHET = amphetamine, BENZOS = benzodiazepines, CAN = cannabis, COC = cocaine, METH = methamphetamine, MDPV = methylenedioxypyrovalerone, MPH = methylphenidate, MORPH = morphine, NIC = nicotine, OXY = oxycodone.

Fig. 4. Percent of Studies Each Region Implicated. (a) Subcortical Regions and (b) Cortical Regions for Main Results (N = 81 studies that compared drug to control group). This figure corresponds to results in Tables 4 and 5. Note, 4a and 4b are not corrected for spotlight effects. (c) Main affected regions implicated (corrected for spotlight effects).

Fig. 5. (a) Method of drug administration. Pie chart showing the percentage of studies by administration type, either self-administration (by the animal itself) or non-voluntary administration (by the experimenter), or both. (b) Length of drug administration. Pie chart showing the percentage of studies using drug administration acutely (1 day), for under 3 weeks, or for 3 weeks or more. (c) Imaging technique. Pie chart showing the percentage of studies using the various neuroimaging techniques. (d) Age of animals. Pie chart showing the percentage of studies using juvenile animals (up to post-natal day 28), adolescent animals (1–2 months of age), and/or adult animals (above 2 months of age). N = 125. Abbreviations: OMRI = Overhauser Enhanced MRI, fMRI = functional MRI, PET = positron emission topography, MEMRI = manganese-enhanced MRI.

Table 1 Summary of Subcortical Results for All Included Papers (N = 125).

Author & Year	Drug	Route	Days
of
Drug	Animal	Method	Subcortical Structures	
Dudek et al. 2015	DEP [ALC]	Oral (self-admin)	42	A A	MEMRI	+ Subthalamic (ALC & Saccharin to water, persisted into early Abs)	
Haass-Koffler et al. 2016	DEP [ALC]	Oral (non-vol)	20	L E	fMRI	+ CPu (Dorsal Striatum) (with yohimbine challenge, CRHBP to SCR)	
Dudek & Hyytiä 2016	DEP [ALC]	Oral (self-admin)	42	A A & W	MEMRI	+ Brainstem (Caudal linear nucleus of raphe); − NAc Shell (Ventral Striatum) (ALC-AAs to Naive AAs & Wistars)	
Dudek et al. 2016	DEP [ALC]	Oral (self-admin)	42	A A	MEMRI	+ AMY, Subthalamus (Zona incerta), pedunc. tegmental nuc. (ALC > Water); + AMY (7d WD > Water)	
Cosa et al. 2017	DEP [ALC]	Oral (self-admin)	28	M-S	fMRI	null	
Gispert et al. 2017	DEP [ALC]	Oral (self-admin)	90 or 360	W	PET	− Cerebellum (in alc-naive, with ALC challenge); + Ventral Striatum (eg, NAc) (relative, naive to chronic)	
Hsieh et al. 2018	DEP [ALC]	IP (non-vol) or Oral (non-vol)	1 or 14	S-D	PET	− Dorsal Striatum, Cerebellum (grey & white matter), THAL (Post Acute to Pre); + Dorsal Striatum, Cerebellum, THAL (Post Chronic to Pre)	
Kim et al. 2018	DEP [ALC]	Vapor (self-admin)	42 (int.)	W	PET	null	
Broadwater et al. 2018	DEP [ALC]	IG (non-vol)	30 (int.)	S-D	fMRI	− Striatum (nonspecific) (to Frontal Ctx) (Acute ALC to Water)	
de Laat et al. 2019	DEP [ALC]	Oral (self-admin)	49	W	PET	− Striatum (unspecified); (ALC to Sacch);, − AMY (to baseline)	
Tyler et al. 2019	DEP [ALC]	Vapor (non-vol)	42-70	W	PET	null	
Scuppa et al. 2020	DEP [ALC]	Vapor (non-vol)	56 (int.)	W	fMRI	+ NAc (Ventral Striatum) (from Insular), VTA (to Cing and to CPu (Dorsal Striatum)-Antlns) (ALC vapor to normal air)	
Tournier et al. 2021b	DEP [ALC]	IP (non-vol)	14 (int.)	W	PET	+ THAL, Striatum (unspecified), Cerebellum, AMY, HYP (ALC to NaCl)	
Meinhardt et al. 2021	DEP [ALC]	Vapor (self-admin)	49 (int.)	Indiana A P& Indiana A N-P	PET	null	
Pallarés et al. 2021	DEP [ALC]	Oral (self-admin)	28	A A & msP	MEMRI	null	
Liu et al. 2021b	DEP [ALC]	Oral (self-admin)	14	P & NP	fMRI	+ NAc (Ventral Striatum) to IC, + VTA to HYP, + Olfactory Tubercle (Ventral Striatum) to HYP (nonsignif. to baseline)	
de Laat et al. 2022	DEP [ALC]	Oral (self-admin)	63 (int.)	W	PET	+ Striatum (nonspecific) (at 2 wk ALC to Water)	
Pérez-Ramírez et al. 2022	DEP [ALC]	Oral (self-admin)	30 or 37	M-S	fMRI & MEMRI	+ Striatum (nonspecific) (to prefrontocortical), − Striatum (nonspecific) (to occipital) (chronic ALC to Water, before & after WD)	
Degiorgis et al. 2022	DEP [ALC]	Oral (self-admin)	35 (int.)	C57BI/6J & 129-Sv Pas mice	fMRI	+ VTA (to NAc (Ventral Striatum), CPu (Dorsal Striatum), Habenula, Insular Ctx, Retrosplenial, & ACC) (ALC to Water); + Habenula + & AMY (central) (ALC to Baseline)	
Chen et al. 2022	DEP [ALC]	Oral (non-vol & self-admin)	61	C57BI/6J mice	PET	null (Early-stage ALD vs Ctrls), + Brainstem, Cerebellum, Midbrain (these ROIs compared to others)	
Dileep Kumar et al. 2022	DEP [ALC]	Oral (self-admin)	120 (int.)	C57BI/6J mice	PET	null	
Liu et al. 2023	DEP [ALC]	Oral (non-vol & self-admin)	61	C57BI/6J mice	PET	+Cerebellum (to AMY) (in Early-Life ALD & Ctrls)	
Ruiz-España et al. 2023	DEP [ALC]	Oral (self-admin)	30	msP	fMRI	+ Striatum (nonspecific) (ALC to BL)	
Lee et al. 2023	DEP [ALC]	IP (Non-Vol)	1	W	fMRI	+ Striatum (nonspecific), AMY (to Lateral Cortical & to DMN) (ALC to BL)	
Wank et al. 2024	DEP [ALC]	Oral (Self-Admin)	6	C57BL/6 & NSM KO mice	fMRI	+ THAL, HYP, AMY, Cerebellum, Brainstem (Chronic ALC to H20 in KO mice only); more results not listed comparing within groups (BL to ALC+ challenge)	
Silva-Rodríguez et al. 2016	DEP [BENZOS]	IV (non-vol)	28	S-D	PET	null	
Wang et al. 2021	DEP [PHB]	IG (non-vol)	90	S-D (SPF)	PET	+ AMY(bl), NAc (Ventral Striatum), & VTA (Phenobarb. to Vehicle, at both time points)	
Xu et al. 2000	OPI [HER]	IV (non-vol)	1	S-D	fMRI	n/a	
Xi et al. 2004	OPI [HER]	IV (self-admin)	9	S-D	fMRI	− CPu, NAc (Dorsal & Ventral Striatum), THAL, HYP (in both groups, less in HER)	
Luo et al. 2004	OPI [HER]	IV (self-admin)	12	S-D	fMRI	− NAc (Ventral Striatum) (in both groups, less in HER)	
Carmack et al. 2019	OPI [HER]	IV (self-admin)	21	L E	fMRI	+ AMY (m, ce, & ext), HYP (vm, PVN) (Sh COC NALX-compared to other combinations)	
Tsai et al. 2020	OPI [HER]	History	21	S-D	fMRI	null	
Luo et al. 2022	OPI [HER]	IP (non-vol)	1 or 54	S-D	MEMRI	null	
Scarlata et al. 2022	OPI [HER]	IV (self-admin)	10	L E	fMRI	− Striatum (Dorsal) (LgA to ShA)	
Lowe et al. 2002	OPI [MORPH]	SC (non-vol)	8	L-H	fMRI	null	
Sun et al. 2006	OPI [MORPH]	SC (non-vol)	12	S-D	MEMRI	n/a	
Park et al. 2017	OPI [MORPH]	IV (self-admin)	12 (int.)	S-D	PET	+ Striatum (nonspecific) (MORPH to SAL; ISO (anesthetized) only)	
Niu et al. 2017	OPI [MORPH]	IP (non-vol)	10	S-D	MEMRI	Striatum ( + Dorsal & +/− Ventral), − THAL (lateral posterior), + AMY, VTA, Central Inf. Coll., HYP, − VP (MORPH to SAL);	
Auvity et al. 2017	OPI [MORPH]	IP (non-vol)	5	S-D (SPF)	PET	null	
Chen et al. 2018	OPI [MORPH]	IP (non-vol)	9	S-D	PET	− VP (rostral] (MORPH to SAL)	
Fang 2020	OPI [MORPH]	IP (non-vol)	10	S-D	MEMRI	+ Lateral Septum, NAc (Ventral Striatum), AMY (MORPH to SAL, at 1d WD);	
LI et al. 2021	OPI [MORPH]	IP (non-vol)	5	S-D	PET	+ THAL & Midbrain (WD & Cond. Aver. groups, NALX−); − Optic Chiasm & Midbrain (Pons) (WD & Cond. Aver. groups, NALX+)	
Soto-Montenegro et al. 2022	OPI [MORPH]	IV (self-admin)	15	F344 & LEW	PET	− Brainstem, Midbrain (PAG) (Lewis to Fischer 344); − THAL (MORPH-Lewis to SAL-Lewis)	
Lamanna-Rama et al. 2023	OPI [MORPH]	IV (self-admin)	15	w	PET	+ Brainstem, LC (VH− & CP− MORPH+ F), + THAL, PAG, VTA, Habenul (CP−MORPH+ F) (Brainstem, LC, PAG, THAL maintained for CP−MORPH+ F at 6wk), − AMY (VH− & CP− MORPH+ F @ 14wk), + Cerebellum (VH−MORPH+ M) (not @ 6wk)	
Shao et al. 2023	OPI [MORPH]	IP (non-vol)	5	S-D	PET	− CPu (R Dorsal Striatum), + THAL (lat. Post.) (MORPH + CPP short to BL)	
Sourty et al. 2023	OPI [MORPH]	IP (non-vol)	6	C57BL/6 mice	fMRI	− AMY, Midbrain (MOR+ WD before CHAL); + AMY, GP, Midbrain (Dorsal Raphe) (MOR to SAL)	
Moore et al. 2016	OPI [OXY]	IP (non-vol)	1	Oprm1+/+ & Oprm1−/− mice	fMRI	− NAc, Olfactory Tubercles (both Ventral Striatum), VP, GP, HYP, AMY, Cerebellum (paramedian) (WT w/ OXY+; and to Baseline)	
Iriah et al. 2019	OPI [OXY]	IP (non-vol)	4	S-D	MEMRI	− AMY, THAL, Cerebellur; − HYP, − VP, Striatum (Ventral Medial), & Subthalamic, Olfactory tubercles (Ventral Striatum) (OXY to sal)	
Fredriksson et al. 2021	OPI [OXY]	IV (self-admin)	14	S-D	fMRI	+ Dorsal & Posterior Dorsal Striatum (OXY to food, switched direction with abstinence)	
Muelbl et al. 2022	OPI [OXY]	IV (self-admin)	14	S-D	fMRI	+ NAc (Ventral Striatum) (from PFC) (TBI by OXY effect)	
Lei et al. 2014	STIM [AMPHET]	IP (non-vol)	7	Mice	MEMRI	− Dorsal spinal cord (superficial dorsal horn) (AMPHET to SAL)	
Madularu et al. 2015	STIM [AMPHET]	IP (non-vol)	4	S-D	fMRI	+ VTA, Midbrain (Sub Nigra), VP, vmHYP, Habenula (with increased E2 & AMPHET+)	
Liu & Liu 2016	STIM [AMPHET]	IP (non-vol)	7	C57BL6 mice	MCE MRI	+ Lateral Septum, Striatum (unspecified) (AMPHET to SAL)	
Madularu et al. 2016	STIM [AMPHET]	IP(non-vol)	4	S-D (OVX)	fMRI	+ Habenula, AMY, HYP (with chronic HALO, but hormone-status dependent)	
Bifone et al. 2019	STIM [COC & AMPHET]	IV (self-admin), IP (non-vol)	5	W & msP	fMRI	+ AMY (ext) (msP to Wistar)	
Yeh et al. 2014	STIM [COC, METH]	IP or IV (non-vol)	1	BALB/C mice	PET	− Striatum (unspecified) (+ COC and METH)	
Taheri et al. 2016	STIM [COC & METH]	IV (non-vol)	1	L E	fMRI	− HYP, AMY, Striatum (unspecified) (METH to SAL)	
Marota et al. 2000	STIM [COC]	IV (non-vol)	1	S-D	fMRI	+ Dorsal medial Striatum, NAc (Ventral Striatum), THAL (dorsal) (post to pre)	
Luo et al. 2003	STIM [COC]	IV (non-vol)	1	S-D	fMRI	Nonspecific Subcortical (Higher COC to Lower COC)	
Febo et al. 2004	STIM [COC]	ICV (non-vol)	1	S-D	fMRI	+ Midbrain (Sub. Nigra), VTA, Dorsal Striatum & NAc (Ventral Striatum) (COC to Vehicle, and post to pre)	
Dixon et al. 2005	STIM [COC]	IV (non-vol)	1	S-D	fMRI	+ Striatum (nonspecific), Septum, GP, THAL, Midbrain (Inf. Coll. & PAG), Brainstem (Pontine reticular), Cerebellum (post to pre)	
Febo et al. 2005a	STIM [COC]	IP (non-vol)	5	S-D (OVX & OVX+E)	fMRI	+ NAc (Ventral), Striatum (Dorsal), VTA, (OVX > OVX+E); + NAc (Ventral Striatum), VTA, (OVX+E Chronic > Acute)	
Febo et al. 2005b	STIM [COC]	IP (non-vol)	7	S-D	fMRI	+ Midbrain, Dorsal Striatum & NAc (Ventral Striatum), THAL (Acute COC to SAL); − NAc (Ventral Striatum), VP, & THAL (dm), Midbrain (Sub. Nigra) (Chronic COC to SAL) [All w/ Challenge]	
Lu et al. 2007	STIM [COC]	IV (non-vol)	1	S-D	MEMRI	+ Olfactory tubercle & NAc (both Ventral Striatum), CPu (Dorsal Striatum), GP (COC to SAL)	
Lu et al. 2008	STIM [COC]	IV (non-vol)	1	S-D	MEMRI	same as above	
Gozzi et al. 2011	STIM [COC]	IV (self-admin and non-vol)	52	L-H	fMRI	− NAc (Ventral Striatum), THAL (COC to SAL w/ AMPHET+)	
Febo et al. 2011	STIM [COC]	ICV (non-vol)	1	LE	fMRI	+ NAc (Ventral Striatum), VP, Midbrain (Sub. Nigra), Dorsal Striatum (Non-lordotic to Lordotic); − VTA (Lordotic to Non-lordotic females)	
Perles-Barbacaru et al. 2011	STIM [COC]	IP (non-vol)	1	DATKO & C57BL/6J mice	fMRI	− NAc (Ventral Striatum) (post to pre), − NAc (Ventral Striatum), Dorsal Striatum, AMY, Midbrain (Sub. Nigra), VTA , Cerebellum (DATKO to WT)	
Lu et al. 2012a	STIM [COC]	IV (self-admin)	34	LE	fMRI	null	
Caprioli etal. 2013	STIM [COC]	IV (self-admin)	15	L-H	PET	+ Ventral Striatum (left) (HI only, post to pre), − Dorsal Striatum (left & right) (HI and LI, baseline dependent)	
Johnson etal. 2013	STIM [COC]	IP (non-vol)	10	S-D	fMRI	null	
Liu et al. 2013	STIM [COC]	IV (self-admin)	20	LE	fMRI	− Dorsal Lateral Striatum (COC to SUC and COC CS+ to CS−)	
Lu et al. 2014	STIM [COC]	IV (self-admin)	34	LE	fMRI	− GP (entopeduncular nuc.), NAc Core (Ventral Striatum) (COC to SUC)	
Perrine et al. 2015	STIM [COC]	IP (non-vol)	5	S-D	MEMRI	+ NAc (Ventral Striatum) (COC to SAL)	
Lowen et al. 2015	STIM [COC]	IP (non-vol)	2	S-D	fMRI	− AMY (bl), VTA (CD.GFPto CD.D1 w/CS), + Dorsal Striatum & NAc (Ventral Striatum), AMY (bl), VTA (CD. D1 to CD.GFP)	
Cannella etal. 2017	STIM [COC]	IV (self-admin and non-vol)	52	S-D	PET	+ CPu (Dorsal Striatum) (0Crit to Ctrl), − VTA (3Crit to OCrit)	
Nicolas etal. 2017	STIM [COC]	IV (self-admin)	20	S-D	PET	− Dorsal Lateral Striatum, + Midbrain (Mesencephalon), AMY (WD from LG vs Sh)	
Perez et al. 2018	STIM [COC]	IP (non-vol)	1 or 10	LE	MEMRI	− VTA, Midbrain (med. Raph nuc.) (F) (Acute COC to sal); + Midbrain (Interped. Nuc.) (F), − VTA (M) (Chronic COC to SAL)	
Orsini et al. 2018	STIM [COC]	IV (self-admin)	14	LE	fMRI	+ AMY, HYP, THAL, Striatum (nonspecific), L Dorsal medial Striatum, R Lateral Septum, R Mammillary Bodies, L Midbrain (Reticular nuc.), L Cerebellum (2nd lob.) (1d Abs COC to Chamber); + THAL (1d SUC to Chamber); null (COC to Sucrose)	
de Laat et al. 2018	STIM [COC]	IV (self-admin)	14	W	PET	null	
Cannella et al. 2020	STIM [COC]	IV (self-admin)	52	S-D	MEMRI	null	
Rohan et al. 2021	STIM [COC]	IP (non-vol)	2	S-D (CK.GFP or CK.D1)	fMRI	− AMY (CD.D1 w/CS+to CD.GFP)	
Becker et al. 2022	STIM [COC]	IP (non-vol)	9	C57BL6 mice	PET	+ Striatum (nonspecific) (COC to SAL, no exercise)	
Damuka et al. 2022	STIM [COC]	IV (self-admin)	35	F-344	PET	− Striatum (nonspecific) (to Baseline)	
Hanna et al. 2022	STIM [COC]	IP (non-vol)	1	Lewis	PET	+ Midbrain (Sub. Nigra (retie & compact part dorsal tier)), Cerebellum (crus 1 of ansiform lob.), + GP (entoped. nuc.), − GP (ventral entoped. nuc.) (exercise + COC vs. sedent. + COC)	
Perrine et al. 2022	STIM [COC]	IV (self-admin)	12	S-D	PET	− NAc (Ventral Striatum) (High COC Post to BL)	
Spelta et al. 2022	STIM [COC]	IP (non-vol)	1 or 10	C57BI6 mice	PET	+ Striatum (nonspecific), THAL, Cerebellum, HYP, Brainstem , Midbrain (incl. Sup. Coll), AMY, Central Gray (COC to BL) (more results not listed comparing other groups)	
Hanna et al. 2023	STIM [COC]	IP (non-vol)	4	Lewis	PET	− THAL, Midbrain, Cerebellum (COC + Exercise)	
Jones et al. 2024	STIM [COC]	IV (self-admin)	25	L-H	fMRI	− posterior dm Striatum (to PFC), NAc (at BL, predicting future COC compulsion)	
Hsu et al. 2024	STIM [COC]	IV (self-admin)	10	S-D	fMRI	+ CPu (ventral striatum) (to Salience Network (Ant INS)) (1dABS to 30d ABS)	
Urueña-Méndez et al. 2024	STIM [COC]	IV (self-admin)	21	Roman High & Low Avoid.	PET	null	
Spelta et al. 2024	STIM [COC]	IP (non-vol)	9	C57BL/6 mice	PET	+ AMY (COC to BL by Group (COC to SAL), moderated by CBD)	
Colon-Perez et al. 2016	STIM [MDPV]	IP (non-vol)	1	LE	fMRI	− HYP (to Insular Ctx), Striatum (Dorsal & Ventral) (with more MDPV)	
Colon-Perez et al. 2018	STIM [MDPV]	IP (non-vol)	1	LE	fMRI	+ HYP, AMY, Striatum (Dorsal & Ventral) (at 24h post-acute MDPV)	
Hsu et al. 2008	STIM [METH]	IP (non-vol)	4	S-D	MEMRI	+ VTA, Dorsal Medial Striatum (METH to SAL)	
Shiba et al. 2011	STIM [METH]	IP (non-vol)	7	W	OMRI	null	
den Hollander et al. 2014	STIM [METH]	IP (non-vol)	4	W	MEMRI	− NAc (Ventral Striatum), CPu (Dorsal Striatum), GP, THAL , HYP, Midbrain (Raphe Nuc. & Sup. Coll.) (METH to SAL)	
Thanos et al. 2016	STIM [METH]	IP (non-vol)	112	S-D	PET	+ THAL (vm), Brainstem eticular nuc.) (LD > Veh); − Striatum (tail, Dorsal), VP (LD < Veh); − GP, Striatum (tail, Dorsal) (HD < Veh)	
Tang et al. 2022	STIM [METH]	IV (non-vol)	1	S-D	fMRI	+ Midbrain (Sub Nigra) (METH+ vs Control & METH+ to BL)	
Hewitt et al. 2005	STIM [MPH]	IP (non-vol)	1	L-H	fMRI	+ CPu (Ventral striatum), HYP (post to pre, less in pretreated)	
Thanos et al. 2007	STIM [MPH]	Oral (non-vol)	60 and 240	S-D	PET	− Striatum (nonspecific) (2 mo. MPH to Veh), + Striatum (nonspecific) (8 mo. MPH to Veh)	
Canese et al. 2009	STIM [MPH]	IP (non-vol)	1	S-D	fMRI	+ NAc (Ventral Striatum) (MPH to SAL, Adults), − NAc (Ventral Striatum) (MPH to Sal, Adolescent MPH)	
Michaelides et al. 2010	STIM [MPH]	IP (non-vol)	1	D4 −/−, D4+/−, D4 +/− mice	PET	− Cerebellar vermis (D4−/−); + Cerebellar vermis (D4+/+, D4+/−)	
van der Marel et al. 2014	STIM [MPH]	Oral (non-vol)	21	W	fMRI	− Striatum (when comparing across ages only)	
Caprioli etal. 2015	STIM [MPH]	Oral (non-vol)	28	L-H	PET	+/− Striatum (Dorsal & Ventral) (HI rats, BL dependent)	
Arnavut et al. 2022	STIM [MPH]	Oral (non-vol)	91 (int.)	S-D	PET	+ Brainstem (Inf., Reticular Nuc., Inf. Olive, & Trigeminal Nuc.), Spinal cord (Lemniscus), Midbrain (Mesen. Retie. Form. & Inf. Coll.), & Cerebellum (HD to Ctrls - 13wks & 1 wk WD) (HD to LD results not listed here)	
Richer et al. 2022	STIM [MPH]	Oral (non-vol)	91	S-D	PET	+ Cerebellum (Lobule Simplex) (LD rats)	
Shoaib et al. 2004	STIM [NIC]	SC (non-vol)	7	L-H	fMRI	+ NAc (Ventral Striatum) (NIC/MecAMYlamine to other groups)	
Choi et al. 2006	STIM [NIC]	IV (non-vol)	1	S-D	fMRI	+ THAL (av & inter-am), NAc (Ventral Striatum), Septum, Midbrain (Interpeduncular Nuc.) (post to pre)	
Gozzi et al. 2006	STIM [NIC]	IV (non-vol)	1	S-D	fMRI	+ AMY(ce), NAc (anterior) (Ventral Striatum) (NIC+ to SAL)	
Li et al. 2008	STIM [NIC]	IV (non-vol)	4	S-D	fMRI	+ NAc (Ventral Striatum), VP , VTA (NIC pretreat + NIC chall. vs. SAL pretreat + NIC chall.)	
Suarez et al. 2009	STIM [NIC]	SC (non-vol)	1	C57BL/6J & beta2 KO mice	fMRI	+ NAc (Ventral), Midbrain (Sub. Nigra), VTA , THAL (NIC to SAL)	
Zuo et al. 2011	STIM [NIC]	IV (non-vol)	1	S-D	fMRI	+ CPu (Dorsal Striatum), THAL, Brainstem (0.1 mg/kg NIC to sal)	
Bruijnzeel et al. 2014	STIM [NIC]	IV (non-vol)	1	W	fMRI	+ NAc Shell (Ventral Striatum); Striato-Thalamo -Orbitofrontal Circuit (with more NIC)	
Huang et al. 2015	STIM [NIC]	SC (non-vol)	6	S-D	fMRI	null (24h NIC to SAL); − Interped. Nuc (Midbrain), CPu (Dorsal Striatum), VTA; + NAc (Ventral Striatum) (Pre to Post);	
Bade et al. 2017	STIM [NIC]	SC (non-vol)	1 or 7	W	MEMRI	+ NAc (Ventral Striatum), (Acute NIC to SAL and Chronic NIC to SAL)	
Poirier et al. 2017	STIM [NIC]	SC (non-vol)	1	SHR, W-K, & S-D	fMRI	+ VTA-Retrosplenial (SHR to WK or SD)	
Thompson et al. 2018	STIM [NIC]	SC (non-vol)	9	S-D	fMRI	+ VTA (NIC+menthol), +/− Dorsal Striatum w/ AMY (NIC re-admin - not signif. once adjusted)	
Mdller Herde et al. 2019	STIM [NIC]	Oral (non-vol)	250	Ag	PET	− Striatum (nonspecific), THAL, Midbrain (at d250 NIC to Water; increased in prolong. WD)	
Hsu et al. 2019	STIM [NIC]	IP (non-vol)	14 (int.)	S-D	fMRI	null (only + Striatum (nonspecific) to Insular (predicted dependence severity))	
Keeley et al. 2020	STIM [NIC]	IP (non-vol)	14 (int.)	S-D	fMRI	null, (− Striatum (nonspecific - from ACC) (predicted dependence severity; no change as function of NIC))	
Frie et al. 2024	STIM [NIC]	Vapor (non-vol)	16	S-D	fMRI	− HYP, Midbrain (Colliculus) (NIC to VEH, greater in F)	
Coleman et al. 2022	CAN [THC]	Vapor (non-vol)	28	C57BL/J6 mice	fMRI	+ THAL (CAN M to CAN F), HYP to Brainstem (reticular nuc.) (CAN males only to Placebo males & any females)	
Farra et al. 2020	CAN [THC]	Vapor (non-vol)	3	C57BL/6 mice	fMRI	− VP, Ventral Striatum (Olfactory tub.), AMY (ce, ant, bas), HYP, ( and Pituitary Gland), Brainstem (CAN to Room Air); + Brainste Ambiguus & Spinal Trigem. Nuc.), Ventral Striatum (Olfactory tub.) (CAN to Room Air)	
Ginovart et al. 2012	CAN [THC]	IP (non-vol)	21	S-D	PET	+ Dorsal Striatum (CPu), Midbrain (Sub. Nigra), VTA (CAN to Vehicle)	
Note. Summary of subcortical brain regions that demonstrated significant differences in functional activation, connectivity, or metabolism for all papers. If available, the directionality of effects was included. Regions were reported following the naming conventions as denoted in each study. For interpretability, ventral or dorsal striatum was added for subregions of the striatum, if listed. For consistency, if a particular region/nucleus existed within a larger structure/region, it was added in parentheses (eg, ‘Midbrain (Substantia Nigra)’). Repeated regions were colored for ease in visualizing results. Column 2: DEP = depressants, BENZO = Benzodiazepines, ALC = Alcohol, PHB = phenobarbital, OPI = opioids, HER = heroin, MORPH = morphine, OXY = oxycodone, STIM = stimulants, AMPHET = amphetamines, COC = cocaine, METH = methamphetamines, MPH = methylphenidate, NIC = nicotine, THC = cannabis. Column 3: IV = intravenous, IP = intraperitoneal, IG = intragastric, SC = subcutaneous. Column 5: S-D = Sprague-Dawley, A A = Alko Alcohol, L E = Long Evans, W = Wistar, M-S = Michigan-Sardinian, A P = Alcohol Preferring, N-P = non-preferring, P = preferring, msP = Michigan-Sardinian preferring, SPF = specific pathogen-free, L-H = Lister-Hooded, F344 = Fischer 344, OVX = ovariectomized, NSM = Neutral sphingomyelinase, KO = knock-out. Column 7: CPu = Caudate Putamen, NAc = Nucleus Accumbens, AMY = AMYgdala, Abs = Abstinence, THAL = THALamus, HYP = HYPoTHALamus, VTA = ventral tegmental area, PVN = paraventricular nucleus, m = medial, ce = central, ext = external, DG = dentate gyrus, VP = ventral pallidum, WD = withdrawal, PAG = periaqueductal gray, Inf. Coll. = inferior colliculus, Sub. Nigra = substantia nigra, bl = basolateral, M = Males, F = Females, v = ventral, Trigem. = trigeminal, Nuc. = nucleus, tub. = tubercle.

Table 2 Summary of cortical results for all included papers (N = 125).

Author & Year	Drug	Route	Days
of
Drug	Animal	Method	Cortical Structures	
Dudek et al. 2015	DEP [ALC]	Oral (self-admin)	42	A A	MEMRI	+ HC (ventral), Prelimbic Ctx (ACC - rostral ventral) (ALC to Water)	
Haass-Koffler et al. 2016	DEP [ALC]	Oral (non-vol)	20	L E	fMRI	n/a	
Dudek & Hyytiä 2016	DEP [ALC]	Oral (self-admin)	42	A A & W	MEMRI	null	
Dudek et al. 2016	DEP [ALC]	Oral (self-admin)	42	A A	MEMRI	+ Insular ctx, Somatosensory (1 and 2), Motor Ctx (1 and 2) (ALC > Water); - OFC (PFC), PFC (non-specific), Insular Ctx (7d WD > Water)	
Cosa et al. 2017	DEP [ALC]	Oral (self-admin)	28	M-S	fMRI	Altered parenchyma (Post, into Abs.)	
Gispert et al. 2017	DEP [ALC]	Oral (self-admin)	90 or 360	W	PET	- Parietal Ctx (in alc-naive, with ALC challenge), + Entorhinal Ctx (relative: Naive to Chronic)	
Hsieh et al. 2018	DEP [ALC]	IP (non-vol) or Oral (non-vol)	1 or 14	S-D	PET	- Frontal Assoc., Frontal Ctx, Parietal Ctx (Post Acute to Pre), + Frontal Assoc. Ctx, (Post Chronic to Pre)	
Kim et al. 2018	DEP [ALC]	Vapor (self-admin)	42 (int.)	W	PET	null	
Broadwater et al. 2018	DEP [ALC]	IG (non-vol)	30 (int.)	S-D	fMRI	- Prelimbic, IFL (both ACC - rostral medial), Oribotfrontal Ctx (PFC) (to striatal) (Acute ALC to Water)	
de Laat et al. 2019	DEP [ALC]	Oral (self-admin)	49	W	PET	- HC (ventral) (Alc to Saccharin; and to baseline)	
Tyler et al. 2019	DEP [ALC]	Vapor (non-vol)	42-70	W	PET	null	
Scuppa et al. 2020	DEP [ALC]	Vapor (non-vol)	56 (int.)	W	fMRI	Insular ctx, Cingulate Ctx (ACC - dorsal caudal) (- for rats with history; + when postdep ALC vapor to normal air)	
Tournier et al. 2021b	DEP [ALC]	IP (non-vol)	14 (int.)	W	PET	+ Whole Cortex, HC (Alc to NaCl)	
Meinhardt et al. 2021	DEP [ALC]	Vapor (self-admin)	49 (int.)	Indiana A P& Indiana A N-P	PET	- IFL Ctx (ACC - rostral medial) (ALC to Veh)	
Pallares et al. 2021	DEP [ALC]	Oral (self-admin)	28	A A & msP	MEMRI	+ Cingulate, IFL Ctx (ACC - entire), Insular Ctx, Olfactory Ctx (msP to AA)	
Liu et al. 2021b	DEP [ALC]	Oral (self-admin)	14	P & NP	fMRI	- Insular Ctx, Auditory Ctx, Diagonal Band to VLPO (part of HYP) (nonsignif. to baseline)	
de Laat et al. 2022	DEP [ALC]	Oral (self-admin)	63 (int.)	W	PET	null	
Pérez-Ramírez et al. 2022	DEP [ALC]	Oral (self-admin)	30 or 37	M-S	fMRI & MEMRI	- Occipital Ctx to Sensory-Insular Ctx/Sensorimotor (and to Striatal); + Insular Ctx (ant), Cingulate, Prelimbic, Infralimbic (ACC - entire), OFC (PFC) (all to striatum), (chronic ALC to Water, before & after WD)	
Degiorgis et al. 2022	DEP [ALC]	Oral (self-admin)	35 (int.)	C57BI/6J & 129-Sv Pas mice	fMRI	+ Insular Ctx (to Somatosensory & Motor Ctx); - Insular (to PFC); + Retrosplenial Ctx (to Somatomotor, Midbrain (Sub. Nigra & Raphe Nuc.), & THAL), + Insular Ctx, Retrosplenial, & ACC (from VTA) (ALC to Water)	
Chen et al. 2022	DEP [ALC]	Oral (non-vol & self-admin)	61	C57BI/6J mice	PET	+ Global (Early-stage ALD vs Ctrls)	
Dileep Kumar et al. 2022	DEP [ALC]	Oral (self-admin)	120 (int.)	C57BI/6J mice	PET	null	
Liu et al. 2023	DEP [ALC]	Oral (non-vol & self-admin)	61	C57BI/6J mice	PET	+ Global Ctx (to AMY), HC (In Early-stage ALD & in Ctrls)	
Ruiz-España et al. 2023	DEP [ALC]	Oral (self-admin)	30	msP	fMRI	null	
Lee et al. 2023	DEP [ALC]	IP (Non-Vol)	1	W	fMRI	+ Lateral Cortical (Sensorimotor) & Lateral Cortical to Salience (mPFC, Cingulate, anterior INS) (ALC to BL)	
Wank et al. 2024	DEP [ALC]	Oral (Self-Admin)	6	C57BL/6 & NSM KO mice	fMRI	+ Somatosensory Ctx, Motor Association Ctx, Paralimbic Ctx, - HC (Chronic ALC to H20 in KO only); more results not listed comparing within groups (BL to ALC+ challenge)	
Silva-Rodríguez et al. 2016	DEP [BENZOS]	IV (non-vol)	28	S-D	PET	- Global Ctx (Benzo vs. Control acute & chronic)	
Wang et al. 2021	DEP [PHB]	IG (non-vol)	90	S-D (SPF)	PET	+ PFC (nonspecific), HC (CA1-3) (Phenobarb. to Vehicle, at both time points)	
Xu et al. 2000	OPI [HER]	IV (non-vol)	1	S-D	fMRI	- Global Ctx (Spontaneous resp.), - Sensorimotor Ctx (Left) (Artificial resp.)	
Xi et al. 2004	OPI [HER]	IV (self-admin)	9	S-D	fMRI	+ PFC (nonspecific), Cingulate (ACC - dorsal caudal), Olfactory Ctx (in both groups, less in HER)	
Luo et al. 2004	OPI [HER]	IV (self-admin)	12	S-D	fMRI	- HC, + PFC (nonspecific) (in both groups, less in HER)	
Carmack etal. 2019	OPI [HER]	IV (self-admin)	21	LE	fMRI	n/a	
Tsai et al. 2020	OPI [HER]	History	21	S-D	fMRI	- Insula Ctx (ventral anterior); ACC - nonspecific to Retrosplenial Ctx (in WD-related cue-presenation)	
Luo et al. 2022	OPI [HER]	IP (non-vol)	1 or 54	S-D	MEMRI	+ OB, POT (AHE vs Ctrl @ 6h), + POT (HA vs Ctrl @ 6h), − OB (PHA vs Ctrl @ 6h); + OB, POT, DOT (AHE vs Ctrl @ 24h), + POT & DOT (HA vs Ctrl @ 24h), − OB, POT, DOT (PHA vs Ctrl @ 24h)	
Scarlata et al. 2022	OPI [HER]	IV (self-admin)	10	LE	fMRI	- ACC (to Striatum (Dorsal)) (LgA to ShA)	
Lowe et al. 2002	OPI [MORPH]	SC (non-vol)	8	L-H	fMRI	+ HC, Retrosplenial, Entorhinal, Insular ctx (MORPH/NALX (1 mg/kg) to other groups, post to pre too)	
Sun et al. 2006	OPI [MORPH]	SC (non-vol)	12	S-D	MEMRI	- OFC (PFC) (MORPH+ 1d, 6d and WD 1d to SAL)	
Park et al. 2017	OPI [MORPH]	IV (self-admin)	12 (int.)	S-D	PET	null	
Niu et al. 2017	OPI [MORPH]	IP (non-vol)	10	S-D	MEMRI	+ Orbitofrontal Ctx, Somatosensory 1, Motor Ctx, HC (CA2, DG, CA3) (MORPH to SAL)	
Auvity etal. 2017	OPI [MORPH]	IP (non-vol)	5	S-D (SPF)	PET	null	
Chen et al. 2018	OPI [MORPH]	IP (non-vol)	9	S-D	PET	+ Cingulate Ctx (ACC - dorsal caudal), Retrosplenial Ctx (dysgranular right) (MORPH to SAL)	
Fang 2020	OPI [MORPH]	IP (non-vol)	10	S-D	MEMRI	+ Somatosensory 1, HC (MORPH to SAL at 1d WD), - Entorhinal Ctx, + HC (MORPH to SAL at 2d WD)	
Li et al. 2021	OPI [MORPH]	IP (non-vol)	5	S-D	PET	+ Visual Ctx, HC (WD & Cond. Aver, groups, NALX-); - Sensory Ctx, Insular Ctx, Piriform Ctx, HC (left) (WD & Cond. Aver, groups, NALX+)	
Soto-Montenegro et al. 2022	OPI [MORPH]	IV (self-admin)	15	F344& LEW	PET	+ Motor Ctx, Piriform Ctx (MORPH F344 to SAL F344; in acq and WD); - Somatosensory Ctx, Cingulate Ctx (ACC - dorsal caudal) (MORPH-Lewis to SAL-Lewis)	
Lamanna-Rama et al. 2023	OPI [MORPH]	IV (self-admin)	15	W	PET	+ Global (CP & VH -MORPH+ F to M), + Global (CP-MORPH+ F to Ctrls), - Global (CP-MORPH+ M to Ctrls), + Insular Ctx, HC (CP-MORPH+ F), + Somatosensory, Motor Ctx (VH-MORPH+ M), - Piriform, Entorhinal Ctx (VH-MORPH+ F @ 14wk), - Piriform, Ectorhinal, Entorhinal, & Retrosplenial Ctx (CP-MORPH+ F @ 14wk)	
Shao et al. 2023	OPI [MORPH]	IP (non-vol)	W	S-D	PET	- Global (not pituitary) (MORPH + CPP (both long & short) to BL), - PFC (medial), Cingulate Ctx (ACC-dorsal caudal), - HC (MORPH+CPP short to BL), - Somatosensory (Primary), Cingulate Ctx (ACC - dorsal caudal), + Peduncular Ctx (dorsal) (mPFC), Auditory Ctx (R secondary), Somatosensory (primary) (MORPH+CPP sort to BL)	
Sourty et al. 2023	OPI [MORPH]	IP (non-vol)	6	C57BL/6 mice	fMRI	+ Retrosplenial Ctx, PFC (nonspecific), ACC (MOR+ WD before CHAL), + Retrosplenial Ctx (MOR to SAL)	
Moore et al. 2016	OPI [OXY]	IP (non-vol)	1	Oprm1+/+ & Oprm1−/− mice	fMRI	- Insular Ctx, Entorhinal Ctx, HC (CA1) (WT w/OXY+, and to Baseline)	
Iriah et al. 2019	OPI [OXY]	IP (non-vol)	4	S-D	MEMRI	- Ctx (global) (OXY to SAL)	
Fredriksson et al. 2021	OPI [OXY]	IV (self-admin)	14	S-D	fMRI	+ OFC (PFC) (OXY to Food, switched direction with abstinence)	
Muelbl et al. 2022	OPI [OXY]	IV (self-admin)	14	S-D	fMRI	+ OFC (PFC) & IFL (ACC - rostral medial), left PFC (nonspecific) (to NAc) (TBI by OXY)	
Lei et al. 2014	STIM [AMPHET]	IP (non-vol)	7	Mice	MEMRI	n/a	
Madularu et al. 2015	STIM [AMPHET]	IP (non-vol)	4	S-D	fMRI	+ Prelimbic (ACC - rostral ventral), Entorhinal Ctx, vHC (DG & CA1) (with increased E2 & AMPHET+)	
Liu & Liu 2016	STIM [AMPHET]	IP (non-vol)	7	C57BL6 mice	MCE MRI	null	
Madularu et al. 2016	STIM [AMPHET]	IP(non-vol)	4	S-D (OVX)	fMRI	+ HC (w/ chronic HALO, but hormone-status dependent)	
Bifone et al. 2019	STIM [COC& AMPHET]	IV (self-admin), IP (non-vol)	5	W & msP	fMRI	n/a	
Yeh et al. 2014	STIM [COC & METH]	IP or IV (non-vol)	1	BALB/C mice	PET	n/a	
Taheri et al. 2016	STIM [COC& METH]	IV (non-vol)	1	LE	fMRI	+ PFC (nonspecific) (COC to METH), - IC (Meth to SAL)	
Marota et al. 2000	STIM [COC]	IV (non-vol)	1	S-D	fMRI	+ Frontal (nonspecific), Parietal Ctx, Occipital Ctx (post to pre)	
Luo et al. 2003	STIM [COC]	IV (non-vol)	1	S-D	fMRI	- Nonspecific Ctx (Higher COC to lower COC)	
Febo et al. 2004	STIM [COC]	ICV (non-vol)	1	S-D	fMRI	+ PFC (nonspecific) (COC to Vehicle, and post to pre)	
Dixon et al. 2005	STIM [COC]	IV (non-vol)	1	S-D	fMRI	+ Retrosplenial Ctx, Entorhinal Ctx (lateral), Cingulate Ctx (ACC - dorsal caudal), Olfactory Ctx, HC (post to pre)	
Febo et al. 2005a	STIM [COC]	IP (non-vol)	5	S-D (OVX & OVX+E)	fMRI	+ PFC (nonspecific), HC (OVX > OVX+E), + HC (OVX+E Chronic > Acute)	
Febo et al. 2005b	STIM [COC]	IP (non-vol)	7	S-D	fMRI	+ PFC (medial), ACC (dorsal caudal), agInsular Ctx (Chronic COC to SAL)	
Lu et al. 2007	STIM [COC]	IV (non-vol)	1	S-D	MEMRI	+ Frontal Ctx, PFC (medial), Prelimbic & Cingulate (ACC - entire), Insular Ctx (COC to saline)	
Lu et al. 2008	STIM [COC]	IV (non-vol)	1	S-D	MEMRI	same as above	
Gozzi et al. 2011	STIM [COC]	IV (self-admin and non-vol)	52	L-H	fMRI	+ Cingulate Ctx (ACC - dorsal caudal), PFC (medial), - HC (ventral) (COC to SAL w/AMPHET+)	
Febo et al. 2011	STIM [COC]	ICV (non-vol)	1	LE	fMRI	n/a	
Perles-Barbacaru et al. 2011	STIM [COC]	IP (non-vol)	1	DATKO & C57BL/6J mice	fMRI	- Ctx (Prefrontal/Frontal/Frontoparietal; non-specific), - HC (DAT KO to WT)	
Lu et al. 2012a	STIM [COC]	IV (self-admin)	34	L E	fMRI	+ Prelimbic, IFL, ACC (entire ACC) (COC to SUC)	
Caprioli et al. 2013	STIM [COC]	IV (self-admin)	15	L-H	PET	n/a	
Johnson etal. 2013	STIM [COC]	IP (non-vol)	10	S-D	fMRI	+ Insular Ctx (COC-CS+ to CS−, COC to SAL)	
Liu et al. 2013	STIM [COC]	IV (self-admin)	20	L E	fMRI	− mPFC, Cingulate Ctx & Prelimbic Ctx (ACC - entire) (COC to SUC)	
Lu et al. 2014	STIM [COC]	IV (self-admin)	34	L E	fMRI	− Prelimbic (ACC - rostral medial), PFC (dorsal medial) (COC to SUC)	
Perrine et al. 2015	STIM [COC]	IP (non-vol)	5	S-D	MEMRI	n/a	
Lowen et al. 2015	STIM [COC]	IP (non-vol)	2	S-D	fMRI	+ Prelimbic (ACC - rostral medial) (CD.D1 to CD.GFP)	
Cannella et al. 2017	STIM [COC]	IV (self-admin and non-vol)	52	S-D	PET	+ PFC (medial) (0Crit vs Ctrl)	
Nicolas et al. 2017	STIM [COC]	IV (self-admin)	20	S-D	PET	− ACC (nonspecific), Insular Ctx, HC (WD from Lg vs. Sh)	
Perez et al. 2018	STIM [COC]	IP (non-vol)	1 or 10	L E	MEMRI	− HC (Acute COC to SAL), + HC (DG) (Chronic COC to SAL) (F)	
Orsini et al. 2018	STIM [COC]	IV (self-admin)	14	L E	fMRI	− L Perirhinal Ctx (COC to SUC), + Somatosensory Ctx (S1, S2), HC (1d Abs. COC to Chamber)	
de Laat et al. 2018	STIM [COC]	IV (self-admin)	14	W	PET	− Orbitofrontal (PFC) (from HC) (COC to SUC, and to Baseline)	
Cannella et al. 2020	STIM [COC]	IV (self-admin)	52	S-D	MEMRI	− Global Ctx (COC to naive)	
Rohan et al. 2021	STIM [COC]	IP (non-vol)	2	S-D (CK.GFP or CK.D1)	fMRI	− Insular Ctx (CD.D1 w/CS+ to CD.GFP), + PFC (medial) (CD.D1 w/ CS+ to CD.GFP)	
Becker et al. 2022	STIM [COC]	IP (non-vol)	9	C57BL6 mice	PET	n/a	
Damuka et al. 2022	STIM [COC]	IV (self-admin)	35	F-344	PET	null (COC to SAL, by sex), - Whole Brain (Control to BL & COC to BL)	
Hanna et al. 2022	STIM [COC]	IP (non-vol)	1	Lewis	PET	+ Insular Ctx (gran & dysgran), HC (subiculum (post & para)), Temporal assoc. Ctx (exercise + COC vs. sedent. + COC)	
Perrine et al. 2022	STIM [COC]	IV (self-admin)	12	S-D	PET	− HC (Low COC Post to BL)	
Spelta et al. 2022	STIM [COC]	IP (non-vol)	1 or 10	C57BL6 mice	PET	+ Whole Ctx, + Basal Forebrain, HC (Chronic Short COC to BL) (more results not listed comparing other groups)	
Hanna et al. 2023	STIM [COC]	IP (non-vol)	4	Lewis	PET	+ Secondary Visual Ctx, Lateral Area 2 (V2L) (COC + Exercise); − Primary Somatosensory Ctx (COC + Exercise)	
Jones et al. 2024	STIM [COC]	IV (self-admin)	25	L-H	fMRI	− PFC (nonspecific) (to striatum), IFL (ACC – rostral medial), ant Insula (at BL, predicting future COC compulsion)	
Hsu et al. 2024	STIM [COC]	IV (self-admin)	10	S-D	fMRI	− Retrosplenial Ctx (to ant Insula)) (1d ABS to 30d ABS)	
Urueña-Méndez et al. 2024	STIM [COC]	IV (self-admin)	21	Roman High & Low Avoid.	PET	n/a	
Spelta et al. 2024	STIM [COC]	IP (non-vol)	9	C57BL/6 mice	PET	+ Whole Ctx (COC to SAL, COC to BL, COC challenge, moderated by CBD), + HC (COC to BL)	
Colon-Perez et al. 2016	STIM [MDPV]	IP (non-vol)	1	L E	fMRI	− Prelimbic (ACC - rostral medial) to IFL Ctx (ACC - rostral medial) and Orbitofrontal Ctx (PFC); Insular Ctx (with more MDPV)	
Colon-Perez et al. 2018	STIM [MDPV]	IP (non-vol)	1	L E	fMRI	+ PFC (nonspecific), Somatosensory (at 24h post-acute MDPV)	
Hsu et al. 2008	STIM [METH]	IP (non-vol)	4	S-D	MEMRI	+ PFC (nonspecific) (METH to SAL)	
Shiba et al. 2011	STIM [METH]	IP (non-vol)	7	W	OMRI	+ Global Ctx (whole-brain) (METH to SAL)	
den Hollander et al. 2014	STIM [METH]	IP (non-vol)	4	W	MEMRI	− Cingulate Ctx & IFL & PreLimbic Ctx (ACC - entire), Frontal Assoc. Ctx., Motor (1), Orbitofrontal Ctx, Parietal Assoc. Ctx., - HC (d) (METH to SAL)	
Thanos et al. 2016	STIM [METH]	IP (non-vol)	112	S-D	PET	+ Insular Ctx, Somatosensory Ctx (LD > Veh); - Cingulate (ACC dorsal caudal) (LD < Veh); + Somatosensory (primary), Parietal Assoc.; Retrosplenial (HD > Veh); − Rhinal, HC (CA2) (HD < Veh)	
Tang et al. 2022	STIM [METH]	IV (non-vol)	1	S-D	fMRI	n/a	
Hewitt et al. 2005	STIM [MPH]	IP (non-vol)	1	L-H	fMRI	+ Frontal Ctx, HC (post to pre, less in pretreated)	
Thanos et al. 2007	STIM [MPH]	Oral (non-vol)	60 and 240	S-D	PET	n/a	
Canese et al. 2009	STIM [MPH]	IP (non-vol)	1	S-D	fMRI	+ PFC (nonspecific) (MPH to Sal, adults); - PFC (nonspecific), + HC (MPH to Sal, Adolescent MPH)	
Michaelides et al. 2010	STIM [MPH]	IP (non-vol)	1	D4 −/−, D4+/−, D4 +/− mice	PET	+ PFC (nonspecific) (D4 −/−); − PFC (nonspecific) (D4 +/+, D4 +/−)	
van der Marel et al. 2014	STIM [MPH]	Oral (non-vol)	21	W	fMRI	− ACC (nonspecific) (MPH to vehicle)	
Caprioli et al. 2015	STIM [MPH]	Oral (non-vol)	28	L-H	PET	n/a	
Arnavut et al. 2022	STIM [MPH]	Oral (non-vol)	91 (int.)	S-D	PET	null (MPH to Ctris) (HD to LD results not listed here)	
Richer et al. 2022	STIM [MPH]	Oral (non-vol)	91	S-D	PET	+ Sensorimotor Ctx (S1/M1), Cingulum (ACC - dorsal caudal), Insular Ctx, and Auditory Ctx (HD rats), + HC (LD rats)	
Shoaib et al. 2004	STIM [NIC]	SC (non-vol)	7	L-H	fMRI	− Global Ctx	
Choi et al. 2006	STIM [NIC]	IV (non-vol)	1	S-D	fMRI	+ IFL, Cingulate (ACC - entire), Insular Ctx, Piriform Ctx, Retrosplenial, HC (subiculum/DG) (post to pre)	
Gozzi et al. 2006	STIM [NIC]	IV (non-vol)	1	S-D	fMRI	+ mPFC, Cingulate Ctx (ACC - dorsal caudal), Orbitofrontal Ctx, Insular Ctx, Piriform Ctx, Rhinal Ctx, HC (v) (NIC+ to SAL)	
Li et al. 2008	STIM [NIC]	IV (non-vol)	4	S-D	fMRI	+ PFC (nonspecific), HC (NIC pretreat + NIC chall. vs. SAL pretreat + NIC chall.)	
Suarez et al. 2009	STIM [NIC]	SC (non-vol)	1	C57BL/6J & beta2 KO mice	fMRI	+ Prelimbic Ctx (ACC - rostral medial), Anterior Frontal Ctx, Somatosensory Ctx (NIC to SAL)	
Zuo et al. 2011	STIM [NIC]	IV (non-vol)	1	S-D	fMRI	+ Motor (1 and 2), mPFC, OFC (PFC), Cingualte Ctx (ACC - dorsal caudal), Retrosplenial Ctx (0.1 mg/kg NIC to sal)	
Bruijnzeel et al. 2014	STIM [NIC]	IV (non-vol)	1	W	fMRI	+ Prelimbic (ACC - rostral medial), Insular Ctx, Motor (primary & secondary) & Somatosensory Ctx (with more NIC)	
Huang et al. 2015	STIM [NIC]	SC (non-vol)	6	S-D	fMRI	null (24h NIC to SAL);- Retrosplenial Ctx, Insular Ctx; + Prelimbic, Infralimbic (ACC rostral ventral), HC (Pre to Post)	
Bade et al. 2017	STIM [NIC]	SC (non-vol)	1 or 7	W	MEMRI	+ PFC (nonspecific), Insular Ctx (Chronic NIC to SAL), + HC (Acute and/or Chronic NIC to SAL)	
Poirier et al. 2017	STIM [NIC]	SC (non-vol)	1	SHR, W-K, & S-D	fMRI	+ Retrosplenial-VTA (SHR to WK or SD)	
Thompson et al. 2018	STIM [NIC]	SC (non-vol)	9	S-D	fMRI	+ Retrosplenial Ctx (NIC+menthol)	
Müller Herde et al. 2019	STIM [NIC]	Oral (non-vol)	250	Ag	PET	− HC (at d250 NIC to Water; increased in prolong. WD)	
Hsu et al. 2019	STIM [NIC]	IP (non-vol)	14 (int.)	S-D	fMRI	null (+ Frontal-Exec-Insular Ctx & Insular Ctx-Striatum predicted dependence severity)	
Keeley et al. 2020	STIM [NIC]	IP (non-vol)	14 (int.)	S-D	fMRI	null (− ACC (to striatum) predicted subsequent dependence; no change as function of NIC)	
Frie et al. 2024	STIM [NIC]	Vapor (non-vol)	16	S-D	fMRI	− CA1 & d DG (HC), Somatosensory Ctx, Endo/piriform Ctx, Insular Ctx, ACC, Parietal Ctx, Visual Ctx, Retrosplenial Ctx (NIC to VEH, greater in F)	
Coleman et al. 2022	CAN [THC]	Vapor (non-vol)	28	C57BL/J6 mice	fMRI	− HC (M to F)	
Farra et al. 2020	CAN [THC]	Vapor (non-vol)	3	C57BL/6 mice	fMRI	− Piriform (rostral) (CAN to Room Air), + Olfactory bulb, Somatosensory, Piriform (caudal), Retrosplenial (CAN to Room Air	
Ginovart et al. 2012	CAN [THC]	IP (non-vol)	21	S-D	PET	null	
Note. Summary of cortical brain regions that demonstrated significant differences in functional activation, connectivity, or metabolism for all papers. If available, the directionality of effects was included. Regions were reported following the naming conventions as denoted in each study. For interpretability, ventral or dorsal striatum was added for subregions of the striatum, if listed. For consistency, if a particular region/nucleus existed within a larger structure/region, it was added in parentheses (eg, ‘Midbrain (Substantia Nigra)’). Repeated regions were colored for ease in visualizing results. Column 2: DEP = depressants, BENZO = Benzodiazepines, ALC = Alcohol, PHB = phenobarbital, OPI = opioids, HER = heroin, MORPH = morphine, OXY = oxycodone, STIM = stimulants, AMPHET = amphetamines, COC = cocaine, METH = methamphetamines, MPH = methylphenidate, NIC = nicotine, THC = cannabis. Column 3: IV = intravenous, IP = intraperitoneal, IG = intragastric, SC = subcutaneous. Column 5: S-D = Sprague-Dawley, A A = Alko Alcohol, L E = Long Evans, W = Wistar, M-S = Michigan-Sardinian, A P = Alcohol Preferring, N-P = non-preferring, P = preferring, msP = Michigan-Sardinian preferring, SPF = specific pathogen-free, L-H = Lister-Hooded, F344 = Fischer 344, OVX = ovariectomized, NSM = Neutral sphingomyelinase, KO = knock-out, SHR = spontaneously hyperactive, WK = Wistar Kyoto, Ag = Agouti Column 7: HC = Hippocampus, Ctx = cortex, Assoc. = association, ACC = anterior cingulate cortex, OFC = orbitofrontal cortex, PFC = prefrontal cortex, L = left, OB = olfactory bulb, POT = proximal olfactory tract, DOT = distal olfactory tract, AHE = acute heroin exposure, HA = heroin administration, PHA = prolonged heroin administration, CPP = conditioned place preference, BL = Baseline, CP = cannabinoid agonist (CP-55,940) pre-treatment.

Table 3 Subcortical regions implicated by drug class.

Subcortical Region	Depressants (n =
20 of 27)	Total for
Broad
Regions	Opioids (n =
16 of 23)	Total for
Broad
Regions	Stimulants (n =
45 of 72)	Total for
broad
Regions	
Striatum ventral	3 (15 %)	10 (50 %)	4 (25 %)	8 (50 %)	9 (20 %)	24 (53 %)	
Striatum dorsal	-		1 (6 %)		5 (11 %)		
Striatum entire	2 (10 %)		2 (13 %)		5 (11 %)		
Striatum nonspecific	5 (25 %)		1 (6 %)		5 (11 %)		
Thalamus	2 (10 %)	-	5 (31 %)	-	8 (18 %)	-	
Pallidum ventral	-	-	4 (25 %)	6 (38 %)	3 (7 %)	7 (16 %)	
Pallidum globus (ie, dorsal)	-	-	2 (13 %)	-	4 (9 %)	-	
Amygdala	4 (20 %)	-	6 (38 %)	-	4 (9 %)	-	
Midbrain	1 (5 %)	-	2 (13 %)	-	10 (22 %)	-	
Ventral Tegmental Area	3 (15 %)	-	2 (13 %)	-	6 (13 %)	-	
Hypothalamus	1 (5 %)	-	4 (25 %)	-	4 (9 %)	-	
Cerebellum	2 (10 %)	-	3 (19 %)	-	3 (7 %)	-	
Brainstem	1 (5 %)	-	1 (7 %)	-	3 (7 %)	-	
Subthalamic	2 (10 %)	-	1 (6 %)	-	-	-	
Lateral Septum	-	-	1 (7 %)	-	2 (4 %)	-	
Habenula	1 (5 %)	-	1 (7 %)	-	-	-	
Dorsal Spinal Cord	-	-	-	-	2 (4 %)	-	
Pedunculopontine Tegmental Area	1 (5 %)	-	-	-	-	-	
No significant results	7 (35 %)	-	2 (13 %)	-	11 (24 %)	-	
Note. Number of studies each region was implicated in (percentage of studies, of those that did drug to control analysis). Regions ordered by most commonly appearing across drug classes.

Table 4 Cortical regions implicated by drug class.

Cortical Region	Depressants (n = 20 of
27)	Total for Broad
Regions	Opioids (n = 16 of
23)	Total for Broad
Regions	Stimulants (n = 45 of
72)	Total for Broad
Regions	
ACC rostral medial	3 (15 %)	6 (30 %)	-	3 (19 %)	2 (4 %)	14 (31 %)	
ACC dorsal caudal	1 (5 %)		3 (19 %)		6 (13 %)		
ACC entire	1 (5 %)		-		4 (9 %)		
ACC nonspecific	1 (5 %)		-		2 (4 %)		
PFC medial	-	3 (15 %)	-	2 (13 %)	8 (18 %)	16 (35 %)	
PFC, frontal nonspecific	3 (15 %)		2 (13 %)		8 (18 %)		
Hippocampus	4 (20 %)	-	6 (38 %)	-	15 (33 %)	-	
Insular	4 (20 %)	-	3 (19 %)	-	9 (20 %)	-	
Orbitofrontal	3 (15 %)	-	3 (19 %)	-	4 (9 %)	-	
Somatosensory	2 (10 %)	-	4 (25 %)	-	5 (11 %)	-	
Sensorimotor	3 (15 %)	-	3 (19 %)	-	4 (9 %)	-	
Retrosplenial	1 (5 %)	-	4 (25 %)	-	4 (9 %)	-	
Rhinal	1 (5 %)	-	4 (25 %)	-	3 (7 %)	-	
Parietal	1 (5 %)	-	-	-	3 (7 %)	-	
Piriform	-	-	2 (13 %)	-	2 (4 %)	-	
Olfactory	-	-	2 (13 %)	-	-	-	
Occipital	1 (5 %)	-	-	-	1 (2 %)	-	
Auditory	-	-	-	-	1 (2 %)	-	
Global	3 (15 %)	-	2 (13 %)	-	5 (11 %)	-	
No significant results	7 (35 %)	-	2 (13 %)	-	8 (18 %)	-	
Note. Number of studies each region was implicated in (percentage of studies that did drug to control analysis). ACC = anterior cingulate cortex, PFC = prefrontal cortex.

Table 5 Summary of studies with brain and behavioral correlation results.

Author &
Year	Drug	Brain
Region(s)	Behavior	Correlation
Coefficient
(R, unless
specified)	
de Laat et al. 2022	DEP [ALC]	NAc (PDE10A)	ALC Consumption & Preference	−.70	
Fredriksson et al. 2021	OPI [OXY]	OFC to Dorsal Striatum & THAL	Incubation of OPI Craving in Forced & Vol. Abs.	.48 to.67 & −.48 to −.79	
Carmack et al. 2019	OPI [HER]	HYP, AMY	Withdrawal Severity	.65 (HYP),.60 (AMY)	
Luo et al. 2022	OPI [HER]	Olfactory Regions	Spatial Memory	.67	
Rohan et al. 2021	STIM [COC]	Salience Network (eg, AMY, mPFC, Insula)	Novelty-preference	−.18 to −.86 (CD.D1),.27 to.60 (CD.GFP)	
Lu et al. 2014	STIM [COC]	NAc-dmPFC	Self-Administration Escalation	.78	
de Laat et al. 2018	STIM [COC]	PFC (Glut & Gly)	Future COC Use during Drug Exposure	Positive, no R reported	
Cannella et al. 2017	STIM [COC]	VTA, R Frontal Assoc, R Medial PFC, R OFC	Reinstatement (3Crit to 0Crit), Persistence of COC Seeking	r2 = .99 (neg; VTA – Reinst.),.75 to.82 (pos; others – Persist.),.90 (neg; VTA –, Persist.)	
Gozzi et al. 2011	STIM [COC]	Ventrostriatal	Total COC SA (w/ AMPHET+)	Negative, no R reported	
Spelta et al. 2022	STIM [COC]	Whole Brain	Locomotion	−.82 to −.92	
Perrine et al. 2015	STIM [COC]	NAc	Locomotion & Behavioral Sensitization	.54	
Caprioli et al. 2015	STIM [MPH]	D2/3Rs in LV Striatum	Trait-like Impulsivity	−.73	
Hsu et al. 2019	STIM [NIC]	Insular-Frontal Ctx	NIC Dependence Severity (same data as Keeley 2020)	.70	
Keeley et al. 2020	STIM [NIC]	ILm, PrLm, & ACC (all to Striatum)	NIC Dependence Severity (signif. different peak dep. to ABS)	ILm-NAc (pos., F = 12.69), PrLm-NAc (pos., F = 15.82), ACCm – left post. CPu (neg., F = 13.30)	
Liu et al. 2013	STIM [COC]	Insular Ctx	COC Intake & COC SA Escalation	.63 (intake), 67 (escalation)	
Lei et al. 2014	STIM [AMPHET]	Superficial Dorsal Horn of Spinal Cord	Pain Sensitivity	Negative, no R reported	
Note. DEP = depressants, OPI = opioids, STIM = stimulants, ALC = alcohol, OXY = oxycodone, HER = heroin, COC = cocaine, MPH = methylphenidate, NIC = nicotine, AMPHET = amphetamine, Nac = Nucleus accumbens, PDE10A = Phosphodiesterase 10A, OFC = orbitofrontal cortex, THAL = Thalamus, HYP = hypothalamus, AMY = amygdala, mPFC = medial prefrontal cortex, dm = dorsomedial, Glut = Glutamine, Gly = Glycine, VTA = ventral tegmental area, R = right, LV = lateral ventral, Ctx = cortex, ILm = infralimbic, PrLm = prelimbic, ACC = anterior cingulate cortex, Vol. = voluntary, Abs. = abstinence, Crit = criteria, CD.D1 = , CD.GFP = , Reinst. = reinstatement, Persist. = persistence, post = posterior, CPu = caudate putamen, pos. = positive, neg. = negative

Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi: 10.1016/j.neubiorev.2024.105823.
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