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Article

Correlations Between the Opioid System, Imidazoline Receptors, and EEG: An Investigation of Acquired Drug-Seeking Behaviors in Different Environments

by
Gabriela Rusu-Zota
1,
Dan Trofin
2,*,
Cristina Gales
3 and
Elena Porumb-Andrese
4,*
1
Department of Pharmacology, Clinical Pharmacology and Algesiology, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 16 Universitatii Street, 700115 Iasi, Romania
2
Department of Biomedical Sciences, Faculty of Medical Bioengineering, University of Medicine and Pharmacy “Grigore T. Popa”, 700454 Iasi, Romania
3
Department of Histology, “Grigore T. Popa” University of Medicine and Pharmacy, Universitatii Street 16, 700115 Iasi, Romania
4
Department of Medical Specialties (III)—Disciplines of Dermatology, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 16 Universitatii Street, 700115 Iasi, Romania
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2025, 15(15), 8437; https://doi.org/10.3390/app15158437
Submission received: 19 May 2025 / Revised: 6 July 2025 / Accepted: 18 July 2025 / Published: 29 July 2025
(This article belongs to the Section Applied Neuroscience and Neural Engineering)
Browse Figures
Versions Notes

Abstract

The investigation of the reward system is a fascinating domain with future applications for pain therapy and understanding addiction. We investigated interactions between tramadol use and the imidazoline system, through the modulatory effects of imidazoline receptor blockers, by behavior analysis and electroencephalography (EEG). Thirty-six male Wistar rats were placed within a conditioned place preference (CCP) setting using a three-compartment box apparatus. The transition of the six groups of subjects from one compartment to another was constantly monitored, related to preconditioning for one day, conditioning for eight days, and post-conditioning testing on day 10. During the conditioning phase, the groups received: a saline solution, efaroxan, idazoxan, tramadol, tramadol + efaroxan, and tramadol + idazoxan, respectively. The administration of efaroxan, idazoxan, or a saline solution in the non-preferred compartment did not alter the time spent by rats there. On the other hand, the administration of tramadol alone in the non-preferred compartment significantly increased the time spent by animals there (151.66 ± 11.69 s) post-conditioning as compared to preconditioning (34.5 ± 5.31 s) (p < 0.01), while the combination of efaroxan and tramadol significantly reduced its effect. After the combination with idazoxan, the effect of tramadol on increasing the time spent by the animal in the non-preferred compartment remained significantly higher than in the preconditioning phase. A significant increase in time spent in the non-preferred compartment demonstrates the existence of a CPP induction effect (by changing the preference). The effects of tramadol on the reward system can cause changes in the brain’s neuroplasticity, potentially leading to learned behaviors that promote drug seeking in previous non-preferred environments.

1. Introduction

Imidazoline receptors (IR) were initially described as a family of non-adrenergic binding sites with affinity for compounds containing an imidazoline moiety; however, this definition has proven reductive, as none of the proposed endogenous ligands possess such a structural motif, and their chemical diversity suggests a broader pharmacological profile. Three subtypes, designated I1, I2, and I3, have been proposed, each with varying degrees of molecular and functional characterization, reflecting the complex and evolving understanding of this receptor family. I1 receptors contribute to the central hypotensive effects of clonidine-like drugs, and newer agents such as moxonidine, rilmenidine, and LNP599 offer improved therapeutic profiles through greater selectivity, with potential applications in the treatment of hypertension and metabolic syndrome. I2 receptors, although not yet fully defined at the molecular level, are associated with central effects such as antinociception and neuroprotection; notably, the I2 agonist CR4056 has shown promising analgesic activity in phase II clinical trials, positioning it as a potential first-in-class non-opioid analgesic. In contrast, I3 receptors are the least understood but may modulate insulin secretion via ATP-sensitive potassium channels in pancreatic β-cells. Despite the incomplete characterization of their molecular targets, IR, particularly I1 and I2 (Figure 1), represent a promising focus for drug development aimed at managing hypertension, metabolic disorders, and chronic pain [1].
The components of the imidazoline system play pivotal roles in various physiological functions, particularly within the central nervous system (CNS) [1]. IR exerts its influence across normal states and diverse diseases, as well as analgesia, tolerance, and dependence [2,3]. Among the drugs that work with these receptors, tramadol is notable because it acts on the central nervous system to relieve pain and has both opioid and non-opioid effects [4].
Tramadol (trans-2-[(dimethylamino)methyl]-1-(3-methoxyphenyl)cyclohexanol hydrochloride) is a centrally acting analgesic with opioid and non-opioid actions [5]. Tramadol (Figure 2) is a synthetic substance, a 4-phenyl-piperidine analogue of codeine, and also a racemic mixture of two enantiomers [6]. These two have different affinities for µ receptors and elicit different actions. The + enantiomer is a µ receptor agonist and strongly inhibits serotonin reuptake, while -tramadol inhibits noradrenaline reuptake. The action is synergistic, and both contribute to the analgesic effect of this drug [7].
Tramadol, widely recognized for its effective analgesic properties coupled with a lower potential for addiction relative to traditional opioids, has attracted considerable clinical and research interest. It is characterized by a synergistic effect with other drugs used in the treatment of chronic pain, such as acetaminophen and gabapentin [8,9]. Another synergistic association is tramadol + etoricoxib against mechanical hyperalgesia of spinal cord injury [10]. Tramadol pretreatment is also known to enhance ketamine-induced antidepressant effects [11]. Recent studies have shed light on its complex interaction with the brain’s reward circuitry, revealing significant modulation of key neuroanatomical regions, including the locus coeruleus, amygdala, hippocampus, ventral tegmental area, prefrontal cortex, basal ganglia, and nucleus accumbens [12,13]. These findings underscore the multifaceted mechanism of action and its influence on both pain perception and neurobehavioral pathways associated with reward and dependence [14,15].
Furthermore, it is known that after oral administration, tramadol’s bioavailability is 68%, and the maximum serum concentration is reached within 2 h, with the half-life situated at 5.1 h. Tramadol is metabolized by cytochrome P450 (CYP) enzymes CYP2D6 and CYP3A4 [16]. One of the metabolites, (+)-O-desmethyl-tramadol (the (+)-M1 metabolite), has an affinity for µ receptors 700 times greater than that of tramadol [17]. Along with its metabolites, it is eliminated mainly by the kidneys [18]. It is also noteworthy that in adults, the volume of distribution per kilogram of body weight (Vd/kg) is 0.71 L/kg [19].
Tramadol enhances the reward system and induces rewarding effects corresponding to psychological dependence [20,21]. Unlike morphine, which is a potent µ receptor stimulant, tramadol stimulates µ receptors but also inhibits the reuptake of serotonin and norepinephrine. Although it induces conditioned place preference (CPP) in rats, its abuse potential in humans is considered to be so far reduced [22].
CPP is an experimental prototype widely used to evaluate the reward or aversion effects of exposure to a drug in laboratory animals [23]. The animals associate the reward effect with different sensory features from the external environment that become conditioned stimuli, a process dependent on learning and memory. Several relevant studies have examined the CPP effects of tramadol and are worth mentioning. According to Sprague JE et al., tramadol at 37.5 and 75 mg/kg intraperitoneal (ip) produced CPP at a magnitude comparable to the effect of morphine (5 mg/kg subcutaneous) (sc), concluding that tramadol may possess a higher abuse potential than initially assumed [24]. A later study found that co-administration of naloxone (0.215 mg/kg sc.) during conditioning blocked the effect of tramadol at doses of 3.16–14.7 mg/kg ip [25]. Later, Ide et al. found that when they gave mice a high dose of 80 mg/kg tramadol, it only showed a slight and not very important trend towards conditioned place preference (CPP), which was different from the strong pain relief seen in other tests using the same dose [12].
Electroencephalography (EEG) plays a pivotal role in the diagnosis of epilepsy and is extensively utilized to monitor the efficacy of anticonvulsant therapies, but also for other pharmacological interventions. Quantitative EEG can provide an in-depth look at the frequency on different bands, making it possible to further appreciate brain coherence (the normalized linear correlation that exists between two pairs of EEG channels and informs their common frequency components) [26,27].
Our research aims to explore the complex relationship between tramadol use and the imidazoline system, particularly how idazoxan and efaroxan affect this relationship, by looking at changes in brain activity with EEG.

2. Materials and Methods

The experiment was conducted on six groups of Wistar rats, each comprising six individuals. For clarity and organization, the groups were designated numerically, from Group 1 to Group 6. The rats, aged 10–14 weeks and weighing between 250 and 300 g, were individually housed in cages maintained under controlled conditions at 21 ± 2.0 °C with a relative humidity of 50–70%. The rats experienced a 12:12 h light/dark cycle and had unlimited access to food and water, except during the experimental procedures.
The rats’ well-being was ensured, and no factors were present that could disrupt their behavior. We measured the rats’ weights daily and adjusted the substance doses based on their weight variations. We conducted all experimental procedures under standard illumination conditions and at the same time of day.
The study adhered to ethical standards and received approval from the Ethics Committee on Research of the “Grigore T. Popa” University of Medicine and Pharmacy, Iasi, Romania (No. 1716/2022).
Idazoxan, efaroxan, tramadol, xylazine, and ketamine were purchased from Sigma-Aldrich, Germany. All drugs were dissolved in distilled water to obtain the final concentrations.

2.1. EEG Procedure

The EEG was performed in each group to test the effect of efaroxan and idazoxan on the reward system in naive rats and rats that received tramadol. We conducted the EEG prior to CPP for the identification of specific neurophysiological changes that may underlie conditioned preferences observed with CPP.
First, the rats were each weighed and anesthetized with ketamine (40–90 mg per kg of body weight) and xylazine (5–10 mg per kg of body weight given intraperitoneally). The animals were placed in a dorsoventral decubitus position. The examinations were performed with an 8-channel digital Neurofax electroencephalograph system (Nihon Kohden®, Tokyo, Japan), and the traces were analyzed using the appropriate software. To acquire EEG traces, we subcutaneously positioned subdermal electrodes (needle-based) with a resistant connector of 0.22 × 12 mm length and 1.5 m stainless steel cable (NE-224S EEG, Nihon Kohden, Tokyo, Japan) under anesthesia.
We used the following EEG recording parameters: sensitivity 10 µV, time constant 0.3 s, filter pass 35 Hz, filtering pass 0.5 Hz, and electrode impedance < 10 Ω. We performed an EEG for 10 min on each animal, using a 3-electrode method where we placed the C3 electrode on the left side of the brain near the basal ganglia, the C4 electrode on the right side over the thalamus, and the Cz electrode (the reference electrode) in the cerebellum, keeping a distance of 5–7 mm between them.

2.2. CPP Procedure

In order to avoid anesthesia-induced artifacts that would complicate the interpretation of EEG signals, we insisted on appropriate grounding techniques and real-time monitoring of EEG data. This way we distinguished between genuine electrophysiological changes and rare artifacts induced by the anesthetic. We also assured the technical adjustments for these artifacts, ensuring that the reported increases in the waves recorded are reflective of true neural activity rather than anesthetic interferences.
By the CPP method we tested the drug’s effect on the reward system using a three-compartment box apparatus (PanLAB Harvard Apparatus). The equal-sized Plexiglas squares of about 25 cm × 30 cm × 30 cm are distributed in one with a white inner surface and the other with a black inner surface separated by a grey central area connected to the compartments by two guillotine doors. The guillotine doors could have one or the other of the two positions: open or closed. The compartments have different floor surface materials. All compartments had the same standard lighting.
The positions of the animals and the transition from one compartment to another were constantly monitored and recorded using a system of infrared light beams connected to the computer (the software and computer have the same producer as the apparatus).
The CPP method consisted of three phases: preconditioning for one day, conditioning for eight days, and post-conditioning testing on day 10, as presented in Figure 3. Prior to the preconditioning phase, there was a two-day habituation period in which all the animals were placed in the device and had free access to all compartments for half an hour.

2.3. The Preconditioning Phase

On the first day (the preconditioning phase) of the trials, each rat without any administration was separately placed into the center compartment with the guillotine doors open and allowed to move freely between both compartments for 15 min. The time spent in each compartment was recorded. The white or black compartment in which the animals spent more time was the preferred compartment, and the compartment with less time was referred to as the non-preferred compartment for the respective animal. The placement of the animals in each compartment was determined by the position of their front paws and heads. Following preconditioning, we divided the animals into six groups, each containing six rats.

2.4. The Conditioning Phase

This phase consisted of 40 min conditioning sessions held on eight successive days, during which the rats were restricted to the considered compartment by isolating it using a guillotine door. On days 2, 4, 6, and 8 of the experiment, the rats received drugs. Animals were placed in the non-preferred compartment, and we administered Tramadol immediately before that. We also administered efaroxan and idazoxan two hours prior to tramadol. On days 3, 5, 7, and 9 of the experiment, all animals received saline solutions (1 mL/kg body weight), and immediately after, we placed them in the preferred compartment (Figure 1).
During the conditioning phase, we determined the groups based on the treatments they received on days 2, 4, 6, and 8:
  • − Group 1: saline solution (NaCl 0.9%), 1 mL/kg bw ip;
  • − Group 2: efaroxan (1 mg/kg bw ip);
  • − Group 3: idazoxan (0.3 mg/kg bw ip);
  • − Group 4: tramadol (40 mg/kg bw ip);
  • − Group 5: tramadol (40 mg/kg bw ip) and efaroxan (1 mg/kg bw ip);
  • − Group 6: tramadol (40 mg/kg bw ip) and idazoxan (0.3 mg/kg bw ip).
All the injected solutions were prepared so that each animal received 1 mL solution/kg IP at every administration for 12 days. The weight of the animals was determined daily, and the doses were adapted to the animals’ weight variations during the experiment.

2.5. The Post-Conditioning Phase

On the 10th day (post-conditioning) of the trials, the guillotine doors were raised, and the animals in a drug-free state were placed in the apparatus for 15 min (900 s), with free access to both compartments. The time spent in each compartment was recorded. The results obtained were statistically interpreted to compare the post-conditioning time with the preconditioning time in each group (Figure 3). A significant increase in time spent in the non-preferred (conditioning) compartment demonstrates the existence of a CPP induction effect (by changing the preference). This behavioral change results from the association of the rewarding effect of substance administration with the place in which the drug was administered.

2.6. Statistical Analysis

The conditioning scores represented the time spent in the drug-paired compartment (the white compartment). All the results were presented as mean conditioning scores ± SEM. Statistical analyses between the groups were conducted using ANOVA and non-parametric Mann–Whitney U tests. We considered the value of p < 0.05 significant.

3. Results

In the efaroxan and tramadol administration (group 5), the EEG activity at the level of the basal ganglia and in the left cerebral hemisphere was null, as the distributions of the waveforms are the same in the two investigated groups (the control group and the one with stimulant CNS administration), both for amplitude and frequency as shown in Table 1 and Figure 4.
From the data collected with electrodes in the thalamus on the right side of the brain, the Mann–Whitney U test showed that the group given CNS stimulants did not support the null hypothesis. The distribution of waves differs significantly between the two groups for both amplitude and frequency (p < 0.001).
The recorded data obtained from the group that received tramadol showed that the null hypothesis is also rejected. The wave distribution varies noticeably between the two groups in terms of both amplitude and frequency (p < 0.001 for the left hemisphere and p < 0.002 for the right hemisphere).
The EEG pattern we observed in the group that received CNS stimulants indicates that tramadol has an influence at the cerebral level, particularly in the right hemisphere within the thalamus, when compared to the control group, and it also affects the reward system in rats (Figure 5).
All the laboratory animals showed a native preference for the compartment with a black inner surface in the preconditioning phase. The other white compartment represents the drug-paired compartment. The administration of efaroxan, idazoxan, or a saline solution in the non-preferred compartment on days 2, 4, 6, and 8 did not alter the time spent by rats in the non-preferred compartment from a statistical perspective (Figure 4A). Figure 6A compares the time rats spent in the non-preferred compartment during the preconditioning phase and post-conditioning phase.
The administration of tramadol alone in the white compartment (the non-preferred compartment) significantly increased the time spent by animals in the non-preferred compartment (151.66 ± 11.69 s) post-conditioning as compared to preconditioning (34.5 ± 5.31 s) (p < 0.01). The combination of efaroxan and tramadol significantly reduced its effect. After combining with idazoxan, tramadol still caused the animals to spend a lot more time in the non-preferred compartment compared to before the conditioning, as shown in Figure 6B.
The EEG recordings highlighted the fact that in the efaroxan and tramadol administration (group 5), the electrical activity at the level of the basal ganglia and in the left cerebral hemisphere is also null; the distributions of the β waves are the same in the control group and the one with stimulant CNS administration, both for amplitude and frequency (p-value of 0.425) (Table 1 and Figure 6). Efaroxan blocked the acquisition of tramadol-induced CPP, while idazoxan did not produce a significant effect.
CNS stimulants affect tramadol’s impact on the brain, particularly in the right hemisphere and thalamus, which influences the reward system.

4. Discussion

Through behavioral analysis and a brief neurophysiological approach, our study aims to offer nuanced insights into the intricate pharmacodynamic interactions within the CNS, expanding our comprehension of tramadol’s effects beyond its recognized analgesic profile and emphasizing its wider neuropharmacological ramifications.
Within the design of this study, we used only male animals for the differences between the sexes regarding the action of µ receptor agonist substances between the sexes [28,29]. Since one of the mechanisms of action of tramadol is the stimulation of µ receptors, we chose to work only with male animals as a standardized approach.
We also aligned the work protocol with the current literature on the topic. Therefore, the dose of efaroxan is considered 1 mg/kg, while the doses of idazoxan used in rats are situated between 0.1 and 1 mg/kg [30,31]. The doses of tramadol used in rat experiments are between 20 and 100 mg/kg/day [32,33,34]. The working methodology was in accordance with the techniques for CPP in rats used by various authors [35,36].
Tramadol, a potent antinociceptive drug, is still of interest and debate at this moment, as it diverges significantly from morphine in its mechanism of action. As a racemic mixture, it is composed of two enantiomers, one of them acting as a weak agonist on morphine μ-receptors and inhibiting serotonin reuptake, while the other, the (−) enantiomer, serves as a norepinephrine uptake inhibitor [37]. Nonetheless, despite its modest impact on μ-opioid receptors, tramadol’s primary pharmacodynamic activities involve weak receptor activation and monoamine reuptake inhibition, portraying a complex modulatory profile [38].
Beyond its antinociceptive effects, tramadol extends its influence to G protein-coupled receptors (GPCRs) and ion channels. Additionally, it acts as an inhibitor of both noradrenaline and serotonin transporters, which contributes to its antinociceptive effects by impeding norepinephrine reuptake [24]. The primary metabolite, O-desmethyltramadol, further augments analgesia through norepinephrine uptake inhibition, emphasizing the multifaceted nature of its mechanism [39].
The relevance of this topic remains open to discussion, particularly because tramadol use has rapidly increased worldwide over the past few decades for conditions such as acute postoperative pain, musculoskeletal pain, epidermolysis bullosa, and Stevens–Johnson syndrome [22,40,41,42]. On the other hand, the addictive potential of tramadol is still under debate, with limited reports of abuse worldwide.
Tramadol’s reward-inducing effect, associated with increased dopamine levels in the nucleus accumbens, is subject to modulation by nalbuphine, a kappa-opioid agonist and μ-opioid partial antagonist [22]. Additionally, within the intricate reward system, neurotransmitters like dopamine, glutamate, and NMDA receptors orchestrate a complex interplay. IR, particularly the I1 subtype, is present in critical reward system structures such as the nucleus accumbens and locus coeruleus. These receptors stimulate locus coeruleus neuron activity and interact with NMDA receptors, contributing to the nuanced modulation of the reward system [43,44,45]. This led to conclusions that tramadol induces CPP at doses of 20 mg/kg ip or more [46].
Our study possesses certain limitations that warrant consideration. The limitations of our findings are the relatively small sample size, which may have restricted our capacity to identify minor effects; therefore, we did not focus more on biochemical or immunohistochemical analyses. The validity of the data provided is primarily based on behavioral testing in relationship with tramadol’s reward implications, rather than modulation of pain, as one may have expected. Moreover, evaluation of specific physical activity in terms of intensity, aerobic capacity, or anaerobic threshold was not the purpose of the study; additional research is necessary to investigate these specific physical implications concerning CPP, particularly as we align to the tendency to consider that CPP would not be typically influenced by such factors. For all that, we placed much greater emphasis on a basic pattern of electrical activity in the brain as a direct response to substance influence, which, although simple in our protocol, reveals the influence of CNS stimulants on the cerebral effects of tramadol, particularly pronounced in the right hemisphere at the level of the thalamus. This adds to the knowledge of the modulation of the reward system in Wistar rats. Of course, dedicated EEG studies could provide much better insights towards specific EEG parameters to follow, other than signal amplitude and assessment of β waveforms, as in our case, but more related to spectral power or frequency bands.
The results did show that efaroxan blocked the acquisition of tramadol-induced CPP, while idazoxan did not produce a significant effect. Because efaroxan is an I1 antagonist, while idazoxan is an I2 antagonist, and both act as ∝2 antagonists, the imidazoline I1 receptor may be responsible for this effect, but we cannot rule out the possible partial involvement of ∝2 antagonist activity. We consider that these findings provide enough evidence supporting the involvement of the imidazoline system in tramadol stimulation of the reward system and in cases of tramadol dependence. The conclusion that I1 receptors mediate the tramadol reward effect is, however, only a hypothesis. There is already available data showing that I1 receptors (IRAS/Nischarin receptors in mice) modulate morphine reward [47]. Morphine produces this effect by stimulating µ receptors. Tramadol acts as an agonist of µ receptors and an inhibitor of serotonin reuptake [48]. We also only consider as a hypothesis the I1/I2 receptors having a role in the antagonism at the alpha 2 receptor level. There would be the possibility of a partial modulatory effect of I1 receptor antagonists (e.g., efaroxan) on the CPP-stimulating action of tramadol.
The lack of positive control (CPP to morphine) and negative control is also a limitation of this study. However, there is documented data showing that morphine stimulates conditioned place preference (CPP) [48]. Additionally, in our case, the significantly longer duration spent by the tramadol + efaroxan group in preconditioning (Figure 6), approximately 150 s, which is over three times longer than other preconditioning groups, we consider can only be attributed to the complex interplay of tramadol’s effects on the brain and its interaction with IR. The synergistic effect increases dopaminergic activity, which often corresponds with greater time spent in environments linked to rewarding effects, hence the observed behavior.
Tramadol’s antinociceptive effects are still understood as predominantly mediated via its interaction with μ-opioid receptors (MOR) and the regulation of neurotransmitters such as serotonin and norepinephrine [49,50]. Our study is of actuality and of interest, especially since tramadol has been demonstrated to induce seizures in animal models due to the excessive activation of opioid receptors [51,52]. EEG investigations frequently demonstrate spike-and-wave discharges or other seizure-associated patterns during tramadol-induced convulsions, indicating a distinct neurophysiological effect that can be analyzed utilizing EEG technology [53]. By all that, our subjects did not present such patterns.
IR can coexist with opioid systems in brain areas critical for pain perception [54]. The regulation of these receptors by drugs like moxonidine and tramadol may impact neuronal stability and the response to excitatory stimuli, considerably altering the EEG waveforms related to seizures [55,56]. Activation of IR may modify GABAergic synaptic transmission, directly affecting seizure susceptibility and EEG recording patterns [56].
Moreover, substances that influence IR, such as agmatine, may provide further valuable information for addressing withdrawal symptoms from opioids like tramadol by modulating receptor interactions in the CNS [57]. This indicates that employing imidazoline receptor modulators could decrease the negative neurological consequences, potentially detectable by EEG alterations after withdrawal or excessive exposure to tramadol [58]. EEG can provide important data regarding the brain dopaminergic systems in normal and pathological situations [59,60,61]. EEG can also provide important data in both human addiction and experimental addiction research [62,63].
By focusing on amplitude and frequency distributions, rather than on coherence, or time-frequency analysis, we directly assessed the excitability of the neural networks, in order to demonstrate noteworthy shifts in response to the administered treatment. Moreover, we considered that amplitude-based metrics offer a more comprehensive picture of the excitatory and inhibitory balance within the cortical networks during depressive states. This distinction may be crucial as the alterations we investigated in the recorded patterns correlate with behavioral outcomes.
An increasing body of evidence suggests that CPP experiments demonstrate that tramadol can induce rewarding effects, as seen by alterations in EEG patterns linked to dopaminergic activity within the mesolimbic system [64]. The visualization of alterations in dopamine levels using EEG is therefore crucial, as it offers insight into the neurological foundations of tramadol’s propensity for dependency and addiction.
The regulation of EEG activity concerning tramadol covers its long-term effects and combinations with other substances. The co-administration of nalbuphine, an opioid antagonist, has been demonstrated to reduce tramadol’s rewarding effects while augmenting its analgesic characteristics, indicating that EEG alterations can monitor the complicated relationship between pain relief and reward pathways [42]. The dynamics of neurotransmitters assessed via EEG can provide insights into the behavioral manifestations of these interactions, underscoring the further need of employing EEG in pharmacological investigations of tramadol to comprehend its overall impact on the CNS.
Another future direction would be the integration of EEG patterns within imagistic exploratory protocols. IR ligands may affect central pain processing, and these effects could potentially be detected with magnetic resonance imaging (MRI) as alterations in brain activity patterns that are linked to pain perception [65,66]. As imaging modalities like functional MRI (fMRI) advance, the capacity to visualize receptor interactions and their effects on pain pathways will improve.
Over the last decades, MRI scans have been essential in measuring the physiological impacts of tramadol and evaluating its effectiveness in modifying brain processes. In a recent study, Larsen et al. used baseline MRI images to monitor alterations in gastrointestinal motility induced by tramadol, illustrating the efficacy of MRI in detecting neurological and physiological modifications caused by medication [67]. We also consider that further integration of MRI in chronic pain research alongside EEG monitoring will clarify the structural and functional alterations in the brain linked to extended tramadol consumption while offering improved understanding of the function of IR in pain regulation.
Tramadol may also enhance mood, likely due to its interaction with monoamine neurotransmitter systems and IR, highlighting the risk for dependence [68]. Improved comprehension of these connections using MRI can better elucidate how tramadol affects brain networks associated with mood and reward. Positron emission tomography (PET), along with MRI scans, combined with receptor binding studies, can eventually clarify the neurophysiological basis of tramadol’s impact on mood disorders and dependency risks, emphasizing a clinical approach to reducing addiction through targeted therapies that adjust IR activity [65].
Furthermore, the combination of MRI with alternative neuroimaging techniques, such as PET scanning, is developing into a comprehensive framework for evaluating medication effects at the receptor level. This multimodal approach improves our comprehension of the interactions between tramadol, its metabolites, and imidazoline receptors in vivo, potentially uncovering pathways that facilitate both analgesic and psychotropic effects [24]. These discoveries reiterate the potential for creating medications that reduce dependency concerns while enhancing therapeutic effectiveness through the activation of IR.

5. Conclusions

The intention of the research has been carried out by studying the effects of tramadol on the reward system and evaluating its impact on the brain’s adaptability. The administration of CNS stimulants affects the cerebral impact of tramadol, particularly in the right hemisphere at the thalamic level, hence influencing the reward system in Wistar rats. The exploration of learned behaviors that encourage drug seeking in previously non-preferred environments is both entertaining and challenging for the years to come.
We conclude that tramadol’s effects on the reward system can induce modifications in the brain, leading to learned behaviors that promote drug seeking under specific settings. We suggest that EEG may thus operate as an essential instrument for comprehending the adaptive alterations in brain function induced by tramadol and will be useful in future settings aiming towards parameters to follow.
Larger studies aiming towards correlations via more complex EEG monitoring algorithms during reward tasks and even associations with standardized pain tests may elucidate significant alterations indicative of both the immediate and long-term effects of tramadol on reward-seeking behavior and its propensity for dependence, with interest towards practical applicability in pain therapy and addictions.

Author Contributions

Conceptualization, G.R.-Z.; methodology, G.R.-Z.; software, E.P.-A. and C.G.; validation, G.R.-Z., E.P.-A. and C.G.; formal analysis, G.R.-Z.; investigation, G.R.-Z.; resources, C.G. and D.T.; data curation, G.R.-Z.; writing—original draft preparation, E.P.-A. and D.T.; writing—review and editing, D.T.; visualization, D.T.; supervision, E.P.-A.; project administration, G.R.-Z. and C.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and all animal procedures and the protocols of the present investigation were approved by the Ethics Committee on Research of the “Grigore T. Popa” University of Medicine and Pharmacy, Iași, Romania (No. 1716/2022).

Informed Consent Statement

Not applicable.

Data Availability Statement

Dataset available on request from the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
IRImidazoline receptors
CNSCentral nervous system
EEGElectroencephalography
CPPConditioned place preference
GPCRsG protein-coupled receptors
MORμ-opioid receptors
MRIMagnetic resonance imaging
fMRIFunctional MRI
PETPositron emission tomography

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Applsci 15 08437 g001
Figure 1. I1 receptor antagonists (left) and I2 receptor antagonists (right).
Figure 1. I1 receptor antagonists (left) and I2 receptor antagonists (right).
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Figure 2. Tramadol structure.
Figure 2. Tramadol structure.
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Figure 3. Schematic illustration of the experimental protocol adopted. EFR: efaroxan, IDZ: idazoxan, TRM: tramadol.
Figure 3. Schematic illustration of the experimental protocol adopted. EFR: efaroxan, IDZ: idazoxan, TRM: tramadol.
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Figure 4. Mann–Whitney U test in the case of administration stimulators CNS-C3CZ (A), CNS-C4CZ (B), and Tramadol-C4CZ (C).
Figure 4. Mann–Whitney U test in the case of administration stimulators CNS-C3CZ (A), CNS-C4CZ (B), and Tramadol-C4CZ (C).
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Figure 5. (A). Distribution of the β wave with CNS stimulators (in terms of amplitude and frequency). (B). Distribution of the β wave with tramadol administration.
Figure 5. (A). Distribution of the β wave with CNS stimulators (in terms of amplitude and frequency). (B). Distribution of the β wave with tramadol administration.
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Figure 6. (A): The impact of saline solution, efaroxan, and idazoxan on the conditioned place preference. Each bar indicates the mean conditioning score (s) (time spent in the non-preferred compartment). In all cases, the effect of each substance on the time spent in the non-preferred compartment was not significant (NS). (B): Effect of tramadol, tramadol and efaroxan, and tramadol and idazoxan on conditioned place preference. Each bar indicates the mean conditioning score (s) (time spent in the non-preferred compartment). (** for p < 0.01; * for p < 0.0).
Figure 6. (A): The impact of saline solution, efaroxan, and idazoxan on the conditioned place preference. Each bar indicates the mean conditioning score (s) (time spent in the non-preferred compartment). In all cases, the effect of each substance on the time spent in the non-preferred compartment was not significant (NS). (B): Effect of tramadol, tramadol and efaroxan, and tramadol and idazoxan on conditioned place preference. Each bar indicates the mean conditioning score (s) (time spent in the non-preferred compartment). (** for p < 0.01; * for p < 0.0).
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Table 1. Results of independent-sample Mann–Whitney U tests in the case of the administration of stimulators CNS-C3CZ (p = 0.425, the identical distributions of wave amplitudes across the two groups), CNS-C4CZ (p < 0.001, the distributions of wave amplitudes across the two groups differ significantly), and Tramadol-C4CZ (p < 0.001, the distributions of wave amplitudes across the two groups are significantly distinct).
Table 1. Results of independent-sample Mann–Whitney U tests in the case of the administration of stimulators CNS-C3CZ (p = 0.425, the identical distributions of wave amplitudes across the two groups), CNS-C4CZ (p < 0.001, the distributions of wave amplitudes across the two groups differ significantly), and Tramadol-C4CZ (p < 0.001, the distributions of wave amplitudes across the two groups are significantly distinct).
ParametersA (CNS-C3CZ)B (CNS-C4CZ)C (Tramadol-C4CZ)
Total N182722442491
Mann–Whitney U425,567.000445,894.500857,224.000
Wilcoxon W877,292.000865,880.5001457,284.000
Test Statistic425,567.000445,894.500857,224.000
Standard Error11,265.27015,085.17917,816.429
Standardized Test Statistic0.798−10.7615.215
Asymptotic Sig.
(2-sided test)		0.425<0.001<0.001
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Rusu-Zota, G.; Trofin, D.; Gales, C.; Porumb-Andrese, E. Correlations Between the Opioid System, Imidazoline Receptors, and EEG: An Investigation of Acquired Drug-Seeking Behaviors in Different Environments. Appl. Sci. 2025, 15, 8437. https://doi.org/10.3390/app15158437

AMA Style

Rusu-Zota G, Trofin D, Gales C, Porumb-Andrese E. Correlations Between the Opioid System, Imidazoline Receptors, and EEG: An Investigation of Acquired Drug-Seeking Behaviors in Different Environments. Applied Sciences. 2025; 15(15):8437. https://doi.org/10.3390/app15158437

Chicago/Turabian Style

Rusu-Zota, Gabriela, Dan Trofin, Cristina Gales, and Elena Porumb-Andrese. 2025. "Correlations Between the Opioid System, Imidazoline Receptors, and EEG: An Investigation of Acquired Drug-Seeking Behaviors in Different Environments" Applied Sciences 15, no. 15: 8437. https://doi.org/10.3390/app15158437

APA Style

Rusu-Zota, G., Trofin, D., Gales, C., & Porumb-Andrese, E. (2025). Correlations Between the Opioid System, Imidazoline Receptors, and EEG: An Investigation of Acquired Drug-Seeking Behaviors in Different Environments. Applied Sciences, 15(15), 8437. https://doi.org/10.3390/app15158437

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