An observational study in Depression / Major Depressive Disorder, sponsored by University of Bonn. Not yet recruiting at 1 site in Germany. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-10-26.
Sponsored by University of Bonn · Observational
This study investigates the longitudinal effects of brain stimulation treatments on decision-making and reward learning. Here, daily assessments of reinforcement learning behavior are used in patients with depression who receive neuromodulation treatment to study potential associations between changes in decision-making and reward learning and changes in clinical symptoms.
Brain stimulation techniques are increasingly applied to treat mental disorders, especially when psychotherapy and psychopharmacotherapy fail. The efficacy of treating treatment-resistant depression has been demonstrated using electroconvulsive therapy (ECT), transcranial magnetic stimulation (TMS), and vagus nerve stimulation (VNS). With regard to transcutaneous auricular vagus nerve stimulation (taVNS), a motivation-enhancing effect has been demonstrated in individuals with depression.
It is unclear to what extent these stimulation techniques also affect cognitive processes, such as learning and decision-making behavior, and whether such changes can explain treatment success. Temporary cognitive side effects, such as memory impairments, are known to occur with ECT treatments. Initial evidence regarding learning and decision-making behavior is available for taVNS, in which the vagal auricular branch is noninvasively stimulated at the ear. Acute taVNS stimulation at the left ear showed a reduced learning rate particularly during punishment, as well as increased reward sensitivity. Additionally, TMS over the left dorsolateral prefrontal cortex was shown to alter the ratio of reward-to-punishment learning rates. However, these initial findings on learning and decision-making behavior and the underlying computational parameters relate to acute stimulation. Long-term effects of brain stimulation techniques on theses processes, as used in routine clinical practice (e.g., eight TMS sessions or daily stimulation of the vagus nerve) remain unclear to date. Likewise, the influence of fluctuations in mental state, such as mood, on learning and decision-making behavior over the course of a treatment, as well as potential changes in this influence after successful treatment, remain mostly unexplored. However, a recent study found, that fluctuations in metabolic state affected reward sensitivity and punishment learning rates in obesity. In the context of effort-based decision-making, it has been shown that fluctuations in motivation influence reward sensitivity.
It is also not yet possible to say to what extent stimulation-induced changes in clinical symptoms are reflected in possible changes in decision-making and reward learning. However, increasing evidence of altered computational mechanisms in patients points towards this potential connection. For example, higher punishment learning rates were observed in individuals with depression and anhedonia was linked to reduced reward sensitivity. Also, greater temporal discounting of future rewards was observed in individuals with depression compared to those without a diagnosis. An open question remains, that is whether, as symptoms improve, changes in cognitive processes also diminish.
Based on the above, the following objectives have been established: First, the acute and mid-term effects of the mentioned neurostimulation therapies on computational processes of decision-making and reward learning will be investigated over the course of a clinical application. It is expected, that brain stimulation lowers punishment learning rates (Hypothesis 1). Subsequently, the effects of the various stimulation methods on punishment learning rates will be compared (acutely after stimulation as well as over the course of the treatment). In addition, the influence of state fluctuations, such as mood, on computational parameters of decision-making and reward learning, such as learning rates, will be modeled. It is expected, that fluctuations in mood, motivation, and metabolic state are associated with changes in punishment learning rates (Hypothesis 2). Next, the effect of brain stimulation on working memory are investigated. It is expected, that ECT impairs working memory compared to the other treatments (Hypothesis 3). Finally, it is expected that changes in punishment learning rates predict changes in symptoms of depression, general well-being, and somatic symptoms (Hypothesis 4), as well as cognitive side effects on working memory (Hypothesis 5).
Here, daily assessments of reinforcement learning with a gamified online task are used over the course of 8 weeks to track longitudinal effects of brain stimulation on decision-making and reward learning in patients with depression who receive neuromodulation treatment (N = 100). Daily assessments are accompanied by an ecological momentary assessment (EMA) of mood and metabolic states. At least five runs of the reinforcement learning task should be played before the first stimulation as a baseline. Additionally, working memory (backward digit span task), depressive symptoms (BDI-II), well-being (WHO-5), and somatic symptoms (PHQ-15) are measured online at the start of the study before the first treatment, after 4 weeks, and after 8 weeks at the end of the study. Patients will be recruited directly from the clinic after brain stimulation treatment is indicated for them..
8,577 studies on the registry are indexed under Depression; 1,720 are open to participants now.
This study's planned enrollment of 100 is below the median of 175 across 1,257 observational studies indexed under Depression.
Browse Depression studies →University of Bonn is the lead sponsor of 39 studies on the registry; 20 are open to participants now.
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The criteria were revised on the registry on Oct 26, 2026. See what changed
The study population consists of patients in the Department of Psychiatry and Psychotherapy at the University Hospital Bonn, who receive an indication for a brain stimulation treatment (ECT, TMS, VNS, taVNS).
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Participants receive ECT as a treatment within the clinic. ECT intentionally causes a generalized seizure by passing electrical currents through the brain under anesthesia. The treatment protocol (e.g., number of treatments) is independent of study participation and follows the doctor's orders. Participants are enrolled after the treatment indication is confirmed.
Participants receive TMS as a treatment within the clinic. TMS is a non-invasive procedure in which a magnetic coil is used to induce electrical currents in the brain and thus influence cortex activity. The treatment protocol (e.g., number of treatments, type of TMS) is independent of study participation and follows the doctor's orders. Participants are enrolled after the treatment indication is confirmed.
Participants receive VNS as a treatment within the clinic. VNS is a surgical treatment in which a stimulation device is implanted that sends electrical impulses to the vagus nerve. The treatment protocol (e.g., stimulation settings) is independent of study participation and follows the doctor's orders. Participants are enrolled after the treatment indication is confirmed.
Participants receive tVNS as a treatment from the clinic for at home stimulation. To stimulate vagal afferents, the electrode will be placed at the cymba conchae of the right ear using a previously established conventional stimulation protocol (30s ON, 30s OFF; tVNS E device, tVNS Technologies GmbH, Erlangen, Germany). The stimulation can be applied for up to 4h per day and participants self-select stimulation time and duration based on the doctor's orders. Participants are enrolled after the treatment indication is confirmed.
Participants receive an indication for a stimulation treatment within the clinic, but do not make use of it. Participants are included after treatment indication.
Punishment learning rates
The primary outcome are punishment learning rate estimates from a computational reinforcement learning model. Learning rates will be compared within and between stimulation conditions. Reinforcement learning is repeatedly measured with a bandit task with fluctuating reward probabilities (reward learning task). Reward learning behavior will be collected online over up to 60 runs, each including 150 trials.
Time frame: Assessed online up to 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Stimulation-induced mid-term changes in the backward digit span
The primary outcome is the change in the backward digit span. Changes over time will be compared within conditions and between ECT and the other conditions. The backward digit span is the maximum sequence length that could be repeated correctly backwards in the digit span task (at least one out of two correct). The task runs two sequences per sequence length, starting at two digits and increasing by one digit up to eight digits. The task is terminated if both sequences of a sequence length could not be repeated correctly backwards. Scores range from 0 to 16 and are the number of correctly repeated sequences.
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (10 minutes).
Correct choices in the reward learning task
The outcome describes the percentage of correct choices (wins) collected during the reward learning task. Choices are collected in each of the 150 trials per run.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Reward sensitivity
The primary outcome is reward sensitivity estimates from a computational reinforcement learning model reflected by the inverse temperature parameters. Changes over time will be compared within and between stimulation conditions. Reinforcement learning is repeatedly measured with an bandit task with fluctuating reward probabilities (reward learning task). Reward learning behavior will be collected online over up to 60 runs, each including 150 trials.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Weighting of learned values and rewards at stake (lambda)
The primary outcome is the weighting of win probability to reward magnitude weighting (lambda) from a computational reinforcement learning model. Changes over time will be compared within and between stimulation conditions. Reinforcement learning is repeatedly measured with an bandit task with fluctuating reward probabilities (reward learning task). Reward learning behavior will be collected online over up to 60 runs, each including 150 trials.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Stimulation-induced mid-term changes in reward learning rates
The primary outcome is the change over time in reward learning rate estimates from a computational reinforcement learning model. Changes over time will be compared within and between stimulation conditions. Reinforcement learning is repeatedly measured with an bandit task with fluctuating reward probabilities (reward learning task). Reward learning behavior will be collected online over up to 60 runs, each including 150 trials.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Association between mood state and punishment learning rates
The primary outcome is the association (regression coefficient) quantifying the relationship between mood state and punishment learning rates. Punishment learning rates are measured in the reward learning task. Mood state is calculated from two 0-100 visual analog scales (state happiness minus state sadness), which are asked before every run of the reward learning task.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Association between metabolic state and punishment learning rates
The primary outcome is the association (regression coefficient) quantifying the relationship between metabolic state and punishment learning rates. Punishment learning rates are measured in the reward learning task and metabolic state is asked before every run of the reward learning task on a 0-100 visual analog scale (sated - hungry).
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Association between changes in punishment learning rates and changes in depressive symptoms
The primary outcome is the association (regression coefficient) quantifying the relationship between changes in punishment learning rates and changes in depressive symptoms. The regression model predicts changes in depressive symptoms from changes in punishment learning rates. Depressive symptoms are measured with the BDI-II (total scores, ranging from 0 to 63). Punishment learning rates are measured in the reward learning task.
Time frame: Depressive symptoms are assessed before the first stimulation treatment and after 4 and 8 weeks. Reward learning is assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Association between motivational state and punishment learning rates
The primary outcome is the association (regression coefficient) quantifying the relationship between motivational state and punishment learning rates. Punishment learning rates are measured in the reward learning task and motivational state is asked before every run of the reward learning task on a 0-100 visual analog scale (not motivated - motivated).
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Association between changes in punishment learning rates and changes in mental well-being
The primary outcome is the association (regression coefficient) quantifying the relationship between changes in punishment learning rates and changes in mental well-being. The regression model predicts changes in mental well-being from changes in punishment learning rates. Mental well being is measured with the WHO-5 (total scores, range from 0 to 30). Punishment learning rates are measured in the reward learning task.
Time frame: Mental well being is assessed before the first stimulation treatment and after 4 and 8 weeks. Reward learning is assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Association between changes in punishment learning rates and changes in somatic symptoms
The primary outcome is the association (regression coefficient) quantifying the relationship between changes in punishment learning rates and changes in somatic symptoms. The regression model predicts changes in somatic symptoms from changes in punishment learning rates. Somatic symptoms are measured with the PHQ-15 (total scores, range from 0 to 30). Punishment learning rates are measured in the reward learning task.
Time frame: Somatic symptoms are assessed before the first stimulation treatment and after 4 and 8 weeks. Reward learning is assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Association between changes in the backward digit span and changes in punishment learning rates
The primary outcome is the association (regression coefficient) quantifying the relationship between changes in the backward digit span and changes in punishment learning rates. The backward digit span is measured in the backward digit span task. Punishment learning rates are measured in the reward learning task.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Response times in the reward learning task
The outcome describes response times collected during the reward learning task. Response times (milliseconds) are collected in each of the 150 trials per run.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Backward digit span
The primary outcome is the maximum sequence length that could be repeated correctly backwards (at least one out of two correct). The task runs two sequences per sequence length, starting at two digits and increasing by one digit up to eight digits. The task is terminated if both sequences of a sequence length could not be repeated correctly backwards. Scores range from 2 to 8.
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (10 minutes).
BDI-II (Beck Depression Inventory-II)
Questionnaire assessing depressive symptoms. Will be associated with behavioral outcomes. Total scores range from 0 to 63, with higher scores indicating greater depressive symptom severity.
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (10 minutes).
WHO-5 (World Health Organization-Five Well-Being Index)
Questionnaire assessing mental well being. Will be associated with behavioral outcomes. Total scores range from 0 to 30, with higher scores indicating better mental well being.
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (3 minutes).
PHQ-15 (Patient Health Questionnaire-15)
Questionnaire assessing the severity of somatic symptoms. Will be associated with behavioral outcomes. Total scores range from 0 to 30, with higher scores indicating higher severity of somatic symptoms.
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (5 minutes).
Mood state
Ecological Momentary Assessment (EMA) using two 0-100 visual analog scales (mood state is calculated as state happiness minus state sadness), administered repeatedly across the reward learning task and lab sessions to capture mood state. We will assess changes in mood and associations with learning.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Metabolic state
Ecological Momentary Assessment (EMA) using a 0-100 visual analog scale (sated - hungry), administered repeatedly across the reward learning task and lab sessions to capture metabolic state. We will assess changes in metabolic state and associations with learning.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Motivational state
Ecological Momentary Assessment (EMA) using a 0-100 visual analog scale (unmotivated - motivated), administered repeatedly across the reward learning task and lab sessions to capture motivation. We will assess changes in motivation and associations with learning.
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Plan to share: Yes — After the publication of the key results of the study, anonymized data will be made publicly available (e.g., at osf.org).
Time frame: Anonymized data will be shared upon publication of the results
Access criteria: Until the data is publicly available, researchers may contact the lead PI to gain access.
Data sharing details ↗ · neuromadlab.com
From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
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