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Using specific EEG biomarkers in methamphetamine-dependent individuals, this study systematically probes closed-loop continuous Theta-burst Stimulation (cTBS) based on brain states, assessing dosage, neurologic and behavioral effects, while comparing its efficacy with traditional open-loop cTBS methods.
The current study delineates a robust correlation between prefrontal cortex EEG signals and the psychological craving associated with methamphetamine usage. Dependents exhibit heightened β oscillation energy in the MPFC region and diminished γ oscillation energy across the DLPFC-MPFC region. Previously, through the implementation of rTMS interventions on the left DLPFC, the investigators have successfully reduced the craving levels in users when exposed to relevant cues, coupled with observed decreases in β oscillation energy and increases in γ oscillation energy in the MPFC region. This indicates that both β and γ oscillation energies are instrumental in representing the involvement of MPFC and DLPFC during craving episodes, and neuromodulatory technologies can modulate these energy levels, consequently reducing cravings. Furthermore, the investigators identified a significant augmentation in the theta energy in the occipital lobe when MA dependents are confronted with drug-related cue imagery, signifying a potential crucial neural marker for addiction-induced brain activity. Therefore, the investigators intend to employ the non-invasive continuous Theta-burst Stimulation (cTBS) , predicated upon biomarkers of addiction states, to administer specific frequency stimulations to targeted brain regions, aiming to achieve therapeutic objectives in addiction treatment.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Closed-loop cTBS stimulation based on addiction-induced states | Experimental | In the initial phase of this study, participants will be subjected to individual closed-loop cTBS interventions at varying frequencies for one-week intervals. Concurrently, they will be exposed to MA-related cue paradigms to induce brain addiction states, while scalp EEG signals are collected. Stimulation will be initiated only upon identifying specific neural signals associated with MA cues, aiming to ascertain the optimal frequency for single-session closed-loop cTBS stimulation that could elicit individual neurological responses. Subsequently, we will embark on a longitudinal closed-loop cTBS intervention control study for MA dependents at one-week intervals, which involves addiction-induced closed-loop cTBS stimulation, random time-point stimulation, and traditional continuous stimulation, to rectify potential sequence effects and delineate the disparities in neurological and behavioral impacts between discrete and continuous stimulations based on brain states. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Closed-loop cTBS stimulation based on addiction induced states | Device | We conducted a longitudinal controlled study of closed-loop cTBS interventions among MA dependents.This involved implementing interventions based on addiction-induced states through closed loop cTBS stimulation, randomized time-point stimulation, and traditional continuous stimulation. |
| Measure | Description | Time Frame |
|---|---|---|
| Change of Craving assessed by Visual Analog Scale (VAS) | The intensity of psychological craving in MA dependents was assessed using the Visual Analogue Scale (VAS), where individuals rated their cravings on a scale from 0 to 10, with higher scores indicating greater levels of craving. The VAS scores were utilized based on two conditions: during a resting state and when subjected to cue induction involving images associated with methamphetamine, serving as the criteria for evaluation. individuals rated their cravings on a scale from 0 to 10, with higher scores indicating greater levels of craving. The VAS scores were utilized based on two conditions: during a resting state and when subjected to cue induction involving images associated with methamphetamine, serving as the criteria for evaluation. | through study completion, an average of 1 month |
| Measure | Description | Time Frame |
|---|---|---|
| Changes of electroencephalogram power spectrum | Resting-state EEG can be used to extract power spectra and electrode functional connectivity; on-task EEG can be used to isolate time-frequency features during non-stimulated trials to extract alpha, beta, theta, and gamma band energy of the parietal and occipital electrodes. Both can be used to assess changes in neural activity before, during, and after their restimulation. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Min Zhao, PhD | Contact | 64387250 | drminzhao@gmail.com | |
| Hang Su, PhD | Contact | 64387250 | drminzhao@gmail.com |
| Name | Affiliation | Role |
|---|---|---|
| Min Zhao, PhD | Shanghai Mental Health Center | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Min Zhao, PhD | Recruiting | Shanghai | Shanghai Municipality | 200000 | China |
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| through study completion, an average of 1 month |
| Probabilistic inversion learning task | The matching of symbols and colours was reversed without informing the subjects and their cognitive flexibility in the reversed condition was assessed | through study completion, an average of 1 month |
| Anxiety | The reduction rate in the Beck Anxiety Inventory (BAI) scores was calculated before and after intervention to assess the rate of decrease in anxiety levels among MA dependents. | through study completion, an average of 1 month |
| Depression | The reduction rate in the Beck Depression Inventory (BDI) scores was calculated before and after the intervention to evaluate the rate of reduction in their levels of depression. | through study completion, an average of 1 month |
| sleep quality | Improvement in subjects' sleep before and after the intervention as assessed by the Pittsburgh Sleep Quality Index scale (PSQI) | through study completion, an average of 1 month |