Depression / Major Depressive DisorderNCT07823218
Longitudinal Effects of Brain Stimulation on Decision-Making and Reward Learning
An observational study of Depression / Major Depressive Disorder, run by University of Bonn at 1 site in Germany.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Depression / Major Depressive Disorder
- How many people
- 100 participants
- Where
- 1 siteGermany
- Study dates
- Sep 2026to Aug 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: 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).
Who may be able to join
- Indication for a brain stimulation treatment (ECT, TMS, VNS, taVNS) in the Department of Psychiatry and Psychotherapy at the University Hospital Bonn
- Major Depressive Disorder
- Be able and willing to provide informed consent.
Who cannot join
- Non-German speakers
- Unclear ability to give consent to the study participation
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Germany1 site
Section of Medical Psychology, Department of Psychiatry & Psychotherapy, Faculty of Medicine, University of Bonn
Bonn, 53127
Prof. Dr. rer. nat. Nils B Kroemer, +49 228 28719123, nkroemer@uni-bonn.de
About this study
Official title: Longitudinal Effects of Brain Stimulation Techniques (ECT, TMS, VNS, taVNS) on Decision-Making and Reward Learning
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.
Read the detailed description
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..
- Conditions
- Depression / Major Depressive Disorder
- Keywords
- Brain Stimulation, Reinforcement Learning, ECT, repetitive transcranial magnetic stimulation, VNS, tVNS, Depression
- Medical subject headings
- Depression, Depressive Disorder, Major
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Electroconvulsive therapy (ECT) | 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. | |
| Transcranial magnetic stimulation (TMS) | 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. | |
| invasive vagus nerve stimulation (VNS) | 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. | |
| transcutaneous vagus nerve stimulation (tVNS) | 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. | |
| Control | Participants receive an indication for a stimulation treatment within the clinic, but do not make use of it. Participants are included after treatment indication. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Assessed online up to 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Secondary outcomes (17)
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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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).
Measured: 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.
Measured: 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).
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: Assessed before the first stimulation treatment and after 4 and 8 weeks (5 minutes).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Sep 2026
- Study startSep 2026 (estimated)
- Primary completionAug 2028 (estimated)
- Study completionAug 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (16)Papers the sponsor has linked to this study.
- Other trials for Depression / Major Depressive DisorderStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Bonn
- Sponsor type
- University, hospital or other
- Collaborators
- Department of Psychiatry University of Bonn
- Responsible party
- Principal investigator, Dr. Nils B. Kroemer, University Hospital, Bonn
- Investigators
- Nils B Kroemer, Prof. Dr., Principal investigator, Section of Medical Psychology, Department of Psychiatry & Psychotherapy, Faculty of Medicine, University of Bonn
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07823218
- Sponsor's protocol ID
- BON009
- Status last verified
- Oct 2026
- First submitted
- 10 Sep 2026
- Last updated
- 26 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: After the publication of the key results of the study, anonymized data will be made publicly available (e.g., at osf.org).
Publications
Neuser MP, Kuhnel A, Krautlein F, Teckentrup V, Svaldi J, Kroemer NB. Reliability of gamified reinforcement learning in densely sampled longitudinal assessments. PLOS Digit Health. 2023 Sep 6;2(9):e0000330. doi: 10.1371/journal.pdig.0000330. eCollection 2023 Sep.
PubMed 37672521Huys QJM, Browning M. A Computational View on the Nature of Reward and Value in Anhedonia. Curr Top Behav Neurosci. 2022;58:421-441. doi: 10.1007/7854_2021_290.
PubMed 34935117Kuehnel A, Zietz J, Theuer JK, Neuser MP, Kroemer NB; Dense sampling of choices links high learning rates to obesity and low reward sensitivity to binge eating; medRxiv; 2025 Jun 20
Weber I, Niehaus H, Krause K, Molitor L, Peper M, Schmidt L, Hakel L, Timmermann L, Menzler K, Knake S, Oehrn CR. Trust your gut: vagal nerve stimulation in humans improves reinforcement learning. Brain Commun. 2021 Mar 14;3(2):fcab039. doi: 10.1093/braincomms/fcab039. eCollection 2021.
PubMed 33928247Trapp NT, Purgianto A, Taylor JJ, Singh MK, Oberman LM, Mickey BJ, Youssef NA, Solzbacher D, Zebley B, Cabrera LY, Conroy S, Cristancho M, Richards JR, Flood MJ, Barbour T, Blumberger DM, Taylor SF, Feifel D, Reti IM, McClintock SM, Lisanby SH, Husain MM; National Network of Depression Centers Neuromodulation Task Group. Consensus review and considerations on TMS to treat depression: A comprehensive update endorsed by the National Network of Depression Centers, the Clinical TMS Society, and the International Federation of Clinical Neurophysiology. Clin Neurophysiol. 2025 Feb;170:206-233. doi: 10.1016/j.clinph.2024.12.015. Epub 2024 Dec 19.
PubMed 39756350Subramanian S, Lopez R, Zorumski CF, Cristancho P. Electroconvulsive therapy in treatment resistant depression. J Neurol Sci. 2022 Mar 15;434:120095. doi: 10.1016/j.jns.2021.120095. Epub 2021 Dec 18.
PubMed 34979372Pike AC, Robinson OJ. Reinforcement Learning in Patients With Mood and Anxiety Disorders vs Control Individuals: A Systematic Review and Meta-analysis. JAMA Psychiatry. 2022 Apr 1;79(4):313-322. doi: 10.1001/jamapsychiatry.2022.0051.
PubMed 35234834Landry M, Moreno A, Patry S, Potvin S, Lemasson M. Current Practices of Electroconvulsive Therapy in Mental Disorders: A Systematic Review and Meta-Analysis of Short and Long-Term Cognitive Effects. J ECT. 2021 Jun 1;37(2):119-127. doi: 10.1097/YCT.0000000000000723.
PubMed 33009218Kuhnel A, Teckentrup V, Neuser MP, Huys QJM, Burrasch C, Walter M, Kroemer NB. Stimulation of the vagus nerve reduces learning in a go/no-go reinforcement learning task. Eur Neuropsychopharmacol. 2020 Jun;35:17-29. doi: 10.1016/j.euroneuro.2020.03.023. Epub 2020 May 11.
PubMed 32404279Kamel LY, Xiong W, Gott BM, Kumar A, Conway CR. Vagus nerve stimulation: An update on a novel treatment for treatment-resistant depression. J Neurol Sci. 2022 Mar 15;434:120171. doi: 10.1016/j.jns.2022.120171. Epub 2022 Jan 29.
PubMed 35158102Hewitt SRC, Norbury A, Huys QJM, Hauser TU. Day-to-day fluctuations in motivation drive effort-based decision-making. Proc Natl Acad Sci U S A. 2025 Mar 25;122(12):e2417964122. doi: 10.1073/pnas.2417964122. Epub 2025 Mar 17.
PubMed 40096607Ferstl M, Kuhnel A, Klaus J, Lin WM, Kroemer NB. Non-invasive vagus nerve stimulation conditions increased invigoration and wanting in depression. Compr Psychiatry. 2024 Jul;132:152488. doi: 10.1016/j.comppsych.2024.152488. Epub 2024 Apr 16.
PubMed 38657358Espinoza RT, Kellner CH. Electroconvulsive Therapy. N Engl J Med. 2022 Feb 17;386(7):667-672. doi: 10.1056/NEJMra2034954. No abstract available.
PubMed 35172057Conroy SK, Holtzheimer PE. Neuromodulation Strategies for the Treatment of Depression. Am J Psychiatry. 2021 Dec;178(12):1082-1088. doi: 10.1176/appi.ajp.2021.21101034.
PubMed 34855452Biernacki K, Myers CE, Cole S, Cavanagh JF, Baker TE. Prefrontal transcranial magnetic stimulation boosts response vigour during reinforcement learning in healthy adults. Eur J Neurosci. 2023 Feb;57(4):680-691. doi: 10.1111/ejn.15905. Epub 2022 Dec 30.
PubMed 36550631
Study at a glance
From the registry record, last updated by the sponsor on 26 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Longitudinal Effects of Brain Stimulation Techniques (ECT, TMS, VNS, taVNS) on Decision-Making and Reward Learning
- ClinicalTrials.gov ID
- NCT07823218
- Acronym / sponsor ID
- BON009
- Conditions
- Depression / Major Depressive Disorder
- Keywords
- Brain Stimulation, Reinforcement Learning, ECT, repetitive transcranial magnetic stimulation, VNS, tVNS, Depression
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- University of BonnUniversity, hospital or other
- Collaborators
- Department of Psychiatry University of Bonn
- Study start
- Sep 2026 (estimated)
- Primary completion
- Aug 2028 (estimated)
- Study completion
- Aug 2028 (estimated)
- First posted
- 16 Sep 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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..
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Number of arms
- 5
| Arm | Type | Receives |
|---|---|---|
| Electroconvulsive therapy (ECT) | – | –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. |
| Transcranial magnetic stimulation (TMS) | – | –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. |
| invasive vagus nerve stimulation (VNS) | – | –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. |
| transcutaneous vagus nerve stimulation (tVNS) | – | –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. |
| Control | – | –Participants receive an indication for a stimulation treatment within the clinic, but do not make use of it. Participants are included after treatment indication. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- 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).
Key inclusion criteria (3 listed)
- Indication for a brain stimulation treatment (ECT, TMS, VNS, taVNS) in the Department of Psychiatry and Psychotherapy at the University Hospital Bonn
- Major Depressive Disorder
- Be able and willing to provide informed consent.
Key exclusion criteria (2 listed)
- Non-German speakers
- Unclear ability to give consent to the study participation
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Punishment learning rates
Time frame: Assessed online up to 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
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.
17 secondary outcomes
Stimulation-induced mid-term changes in the backward digit span
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (10 minutes).
Correct choices 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).
Reward sensitivity
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)
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
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
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
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
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
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
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
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
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
Time frame: Assessed online at least 5 times before the first stimulation treatment and daily throughout the study (8 weeks).
Backward digit span
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (10 minutes).
BDI-II (Beck Depression Inventory-II)
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)
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (3 minutes).
PHQ-15 (Patient Health Questionnaire-15)
Time frame: Assessed before the first stimulation treatment and after 4 and 8 weeks (5 minutes).
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Oct 2026.
- Background: PubMed 37672521Neuser MP, Kuhnel A, Krautlein F, Teckentrup V, Svaldi J, Kroemer NB. Reliability of gamified reinforcement learning in densely sampled longitudinal assessments. PLOS Digit Health. 2023 Sep 6;2(9):e0000330. doi: 10.1371/journal.pdig.0000330. eCollection 2023 Sep.
- Background: PubMed 34935117Huys QJM, Browning M. A Computational View on the Nature of Reward and Value in Anhedonia. Curr Top Behav Neurosci. 2022;58:421-441. doi: 10.1007/7854_2021_290.
- BackgroundKuehnel A, Zietz J, Theuer JK, Neuser MP, Kroemer NB; Dense sampling of choices links high learning rates to obesity and low reward sensitivity to binge eating; medRxiv; 2025 Jun 20
- Background: PubMed 33928247Weber I, Niehaus H, Krause K, Molitor L, Peper M, Schmidt L, Hakel L, Timmermann L, Menzler K, Knake S, Oehrn CR. Trust your gut: vagal nerve stimulation in humans improves reinforcement learning. Brain Commun. 2021 Mar 14;3(2):fcab039. doi: 10.1093/braincomms/fcab039. eCollection 2021.
- Background: PubMed 39756350Trapp NT, Purgianto A, Taylor JJ, Singh MK, Oberman LM, Mickey BJ, Youssef NA, Solzbacher D, Zebley B, Cabrera LY, Conroy S, Cristancho M, Richards JR, Flood MJ, Barbour T, Blumberger DM, Taylor SF, Feifel D, Reti IM, McClintock SM, Lisanby SH, Husain MM; National Network of Depression Centers Neuromodulation Task Group. Consensus review and considerations on TMS to treat depression: A comprehensive update endorsed by the National Network of Depression Centers, the Clinical TMS Society, and the International Federation of Clinical Neurophysiology. Clin Neurophysiol. 2025 Feb;170:206-233. doi: 10.1016/j.clinph.2024.12.015. Epub 2024 Dec 19.
- Background: PubMed 34979372Subramanian S, Lopez R, Zorumski CF, Cristancho P. Electroconvulsive therapy in treatment resistant depression. J Neurol Sci. 2022 Mar 15;434:120095. doi: 10.1016/j.jns.2021.120095. Epub 2021 Dec 18.
- Background: PubMed 35234834Pike AC, Robinson OJ. Reinforcement Learning in Patients With Mood and Anxiety Disorders vs Control Individuals: A Systematic Review and Meta-analysis. JAMA Psychiatry. 2022 Apr 1;79(4):313-322. doi: 10.1001/jamapsychiatry.2022.0051.
- Background: PubMed 33009218Landry M, Moreno A, Patry S, Potvin S, Lemasson M. Current Practices of Electroconvulsive Therapy in Mental Disorders: A Systematic Review and Meta-Analysis of Short and Long-Term Cognitive Effects. J ECT. 2021 Jun 1;37(2):119-127. doi: 10.1097/YCT.0000000000000723.
- Background: PubMed 32404279Kuhnel A, Teckentrup V, Neuser MP, Huys QJM, Burrasch C, Walter M, Kroemer NB. Stimulation of the vagus nerve reduces learning in a go/no-go reinforcement learning task. Eur Neuropsychopharmacol. 2020 Jun;35:17-29. doi: 10.1016/j.euroneuro.2020.03.023. Epub 2020 May 11.
- Background: PubMed 35158102Kamel LY, Xiong W, Gott BM, Kumar A, Conway CR. Vagus nerve stimulation: An update on a novel treatment for treatment-resistant depression. J Neurol Sci. 2022 Mar 15;434:120171. doi: 10.1016/j.jns.2022.120171. Epub 2022 Jan 29.
- Background: PubMed 40096607Hewitt SRC, Norbury A, Huys QJM, Hauser TU. Day-to-day fluctuations in motivation drive effort-based decision-making. Proc Natl Acad Sci U S A. 2025 Mar 25;122(12):e2417964122. doi: 10.1073/pnas.2417964122. Epub 2025 Mar 17.
- Background: PubMed 38657358Ferstl M, Kuhnel A, Klaus J, Lin WM, Kroemer NB. Non-invasive vagus nerve stimulation conditions increased invigoration and wanting in depression. Compr Psychiatry. 2024 Jul;132:152488. doi: 10.1016/j.comppsych.2024.152488. Epub 2024 Apr 16.
- Individual participant dataSharing planned: Yes. After the publication of the key results of the study, anonymized data will be made publicly available (e.g., at osf.org).
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Nils B Kroemer, Prof. Dr. principal investigator
Section of Medical Psychology, Department of Psychiatry & Psychotherapy, Faculty of Medicine, University of Bonn
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Depression / Major Depressive Disorder, run by University of Bonn at 1 site in Germany.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 26 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Germany. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Nils B Kroemer, Prof. Dr. (+49 228 287 11151, nkroemer@uni-bonn.de), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Punishment learning rates (time frame: Assessed online up to 5 times before the first stimulation treatment and daily throughout the study (8 weeks).). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07823218, which also lists 16 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Oct 2026.