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 David Mehler

David Mehler

Research student, Psychological Medicine & Clinical Neurosciences, School of Medicine

Research summary

My PhD has focused on clinical applications of neurofeedback training for psychiatric and neurological conditions. One main project focused on mental imagery based neurofeedback training in patients suffering from depression.

In other projects we have investigated the feasibility of motor imagery based neurofeedback training to improve motor rehabilitation outcomes in stroke survivors and Parkinson’s disease patients.

I am also interested in techniques and ways that will improve the way we do science such as Open Science methods. Our work in this area was recently highlighted in a News article published in Nature.

Research interests

Research topics and related papers

1) Neurofeedback training
My main interest is testing the feasibility and clinical efficacy of neurofeedback  training for the rehabilitation and treatment of psychiatric and neurological  conditions. During neurofeedback training patients engage in mental imagery  while being provided with a feedback signal, for instance a thermometer display,  that represents the activity of a certain brain region or network that is being trained. Thereby, patients can learn to control this activity. Recent trials of real-time fMRI neurofeedback suggest that this technique may improve clinical symptoms. For instance, patients suffering from Parkinson’s disease have shown better motor outcomes (Subramanian et al., 2017), and patients suffering from depression have shown improvement in mood (Mehler et al.,  2018).

We have recently published one of the first randomized controlled trials (RCTs) of real-time fMRI neurofeedback training in depressed patients (Mehler et al., 2018). Patients in this trial used positive and relaxing mental imagery to self-regulate activity in selected brain areas, which was associated with substantial clinical improvements. The study has been featured on the blogs of the National Centre for Mental Health (NCMH) and the Cognitive Neuroscience Society (CNS), where we explain our findings and give more information about the background of this work in an accessible language. 

Motor imagery based neurofeedback training represnts another potential clinical application, in particular of neurofeedback is motor imagery based training for motor rehabilitation. In cooperation with collaborators we are currently conducting clinical studies for motor rehabilitation. This includes a feasibility study of real-time  fMRI neurofeedback training with stroke patients (Prof Duncan Turner, University of East London). The protocol of this study is pre-registered and publicly accessible on the Open Science Framework. We are also  involved in a trial of EEG neurofeedback training for motor rehabilitation in Parkinson’s disease ( in collaboration with Dr John Hindle, Bangor University).

Mehler DMA, Sokunbi MO, Habes I, ..., Linden DEJ (2018). Targeting the affective brain—a randomized controlled trial of real-time fMRI neurofeedback in patients with depression. Neuropsychopharmacology. doi:10.1038/s41386-018-0126-5

Subramanian L, Busse Morri  M, Brosnan M, …, Linden DEJ (2016).  Functional  Magnetic Resonance Imaging Neurofeeedback-guided Motor Imagery Training and  Motor  Training for Parkinson’s Disease: Randomized Trial. Frontiers in Behavioral Neuroscience, 10:111. doi:  10.3389/fnbeh.2016.00111

2) Motor learning in redundant systems
The biomechanics of the human limbs equip us with more joints than we would  need to fulfil a motor task in the 3-dimensional space that we live in. To date  we know very little about the learning principles that can describe and predict how the brain learns new movements when being confronted with a redundant task setting. This becomes especially relevant when joint control is  impaired due to neural loss (e.g. after stroke) and patients need to “re-learn”  physiological movements involving multiple joints. A better understanding  of the relevant learning principles will enable us to design more efficient and specific neurorehabilitation regimes. We have recently published work conducted in healthy participants that suggests that the motor system can re-learn executing movements without participant's conscious awareness (Mehler et al., 2017). Other recent work has provided insights into the neural correlates of movement variability (Mehler and Reschechtko, 2018), which may inform future interventions.

Mehler DMA, Reichenbach A, Klein J, Diedrichsen J (2017). Minimizing endpoint variability through reinforcement learning during reaching movements involving shoulder, elbow and wrist. PLoS One. 2017;12. doi:10.1371/journal.pone.0180803

Mehler DMA, Reschechtko S (2018). Movement Variability Is Processed Bilaterally by Inferior Parietal Lobule. J Neurosci. 2018;38: 2413–2415. doi:10.1523/JNEUROSCI.3224-17.2018

3) Meta-research and public understanding of science

Through my research, outreach work, and medical studies I have increasingly become interested in statistics, research on research practices (meta-research), and ways how science can be communicated in a better way to the general public. For instance, in collaboration with Johannes Algermissen (Nijmegen University, Netherlands) I have written a short review on statistical power in neuroscience. Statistical power is key to robust science and recent work suggests that more needs to be done in this area. We present key insights and perspectives in a Journal of Neurophysiology podcast episode where we also highlight the role of open science.

Open science is a transformative way to conduct research in a more robust way. In collaboration with Dr Chris Allen (Cardiff University) I have recently discussed "Open Science challenges, benefits and tips in early career and beyond". Our opinion paper also contains the first (exploratory) analysis on the prevalence of null findings for registered reports, suggesting that this open science publishing format effectively reduces publication bias. This analysis was recently highlighted in a feature published in Nature.

Another interest is science communication. For instnace, I am writing articles and conducting interviews for various science blogs (see media section below). In recent work with Dr. Paul Hanel (University of Bath) I have investigated how science findings can be reported in a more informative way to members of the general public. In ongoing work we explore how better presentation of findings and results can enhance understanding of science.

Media Activities

In my role as Communications Committee member at the Organization for Human Brain Mapping (OHBM), I regularly write blog articles and conduct interviews on topics around open science and neuroimaging for the OHBM blog as well as my own blog channel on Medium. I am also a guest science writer for the Plos Neuro blog and the Cognitive Neuroscience Society (CNS).

Closing the loop for brain imaging in depression: What have we learned and where are we heading? PLOS Neuro blog, 2018

Taking control of your brain activity. I was interviewed by Lisa Munoz at the CNS blog, 2018

Open Science: Sharing is caring, but is privacy theft? PLOS Neuro blog, 2018

Q&A with Mark Humphries. OHBM blog 2018

Brain Computer Interfaces for neurological patients – tools to support rehabilitation and communication. Medium, 2017

Turbo-Launching OHBM 2017 and Future of Translational Stroke Imaging – Interview with Prof Lara Boyd. OHBM blog, 2017

Making Neuroscience More Reproducible – Interview with Prof Russell Poldrack. OHBM blog, 2017

Neurofeedback Training – Where Imaging and Therapy Converge. CNS blog, 2017

Debunking the Myth that fMRI Studies are Invalid. CNS blog, 2016

Journal Club on “Cluster Failure: Why fMRI Inferences for Spatial Extent Have Inflated False-Positive Rates”. CNS blog, 2016


Health and Care Research Wales. £ 59.000

Internal Research collaborators

Prof  David Linden, CUBRIC & Maastricht University
Prof  Richard Wise, CUBRIC
Dr  Joseph Whittaker, CUBRIC
Dr  Chris Allen,  CUBRIC
Dr  James Kolasinski, CUBRIC

External collaborators

Prof  Duncan Turner, Neurorehabilitation Unit, University of East London
Dr  John Hindle,  School of Medical Sciences, Bangor University
Dr  Paul Hanel,  Department of Psychology, University of Bath

Prof  Jörn Diedrichsen, Brain and Mind Institute, University of Western  Ontario, Canada
Prof  Konrad Kording, Department of Bioengineering, University of  Pennsylvania, USA
Prof  Alexandra Reichenbach, Department for Computer Science, Heilbronn University of  Applied Science, Germany
Prof  Rainer Goebel, Brain Innovation B.V.  & Maastricht University, Netherlands
Prof  Patricia Ohrmann, Department of Psychiatry & Psychotherapy, University Hospital Münster, Germany
Prof  Udo Dannlowski, Department of Psychiatry & Psychotherapy, University Hospital Münster, Germany
Prof  Tim Hahn, Department of Psychiatry & Psychotherapy, University Hospital Münster, Germany
Prof  Samuel Schwarzkopf, Optometry and Vision Sciences, University of Auckland, New Zealand
Dr  Florian Krause , Donders Institute for  Brain Cognition and Behavior, Radboud University, Nijmegen, Netherlands
Dr  Michael Luehrs , Brain Innovation B.V.  & Maastricht University, Netherlands
Dr  Robert Thibault, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
Johannes Algermissen, Donders Institute for  Brain Cognition and Behavior, Radboud University, Nijmegen, Netherlands

Undergraduate education

Exchange year in Clinical Medicine, Cardiff University School of Medicine

Part-time distance studies in Psychology (selected courses), Fernuniversität in Hagen, Germany

Studies in Medicine (interrupted for MD and PhD), University of Münster, Germany

Postgraduate education

MD dissertation project (2012/13), motor control group, Institute of Cognitive Neuroscience, University College London

Thesis title: Robot assisted motor reinforcement learning – reducing natural motor variability in a redundant reaching task.

Awards (selected)

Junior Researcher of the Year, 2nd year PhD prize (2017). Awarded by Cardiff University School of Psychology
Young Investigator award (2017). Awarded by the International Society for Cerebral Blood Flor and Metabolism
Travel bursary for Autumn School in Cognitive neuroscience (2016). Awarded by the Department of experiemental Psychology,  University of Oxford


Project funding

Reproducible Science Workshop for Early Career Scientists (2017), awarded by GW4 doctoral training scheme (Universities of Bath, Bristol, Cardiff, Exeter). £ 2,000
Perspectives of Bayesian Statistics for the Life Sciences (2017), awarded by Cardiff University Doctoral Academy. £ 1,000

Studentships (selected)

2010 – 2014: Heinrich Böll Foundation, studentship

2012 – 2014: ERASMUS studentship (London, Cardiff)

2012: German Academic Exchange Service (DAAD), travel grant

External commitees

Executive Board Member at the European MD/PhD Association (EMPA), 2017 - 2018

Associate Editor at the Journal for European Psychology Students (JEPS), 2017 - present

Communications Committee member at the Organization for Human Brain Mapping (OHBM), 2017 - present


2015 – 2018: PS2025 – I was statistics tutor for 2nd year Psychology students (coordination Dr. Richard Morey).

2014 – 2016: PS1018 – I provided tutorials for 1st year Psychology students (basic statistics, report writing)  and mark their course work.

Both positions involved teaching (small groups and large groups), as well as marking and providing feedback based on assginments and written examinations.

2010 – 2012: Tutor for 1st and 2nd year medical students in Neuroanatomy, Histology and Biochemistry, University of Münster, Germany


Clinical Applications for real-time fMRI Neurofeedback Training - Premises, Promises, and Pitfalls

Neurofeedback training represents a form of biofeedback training with a history of over 50 years. During neurofeedback training participants aim to gain control over a feedback signal that represents the activity of a brain region or network of interest. As such, it holds promise for clinical translation as an add-on treatment for psychiatric and neurological conditions. Yet, currently available evidence for its therapeutic efficacy remains limited. Originally provided based on cortical signals measured with electroencephalography (EEG), methodological developments have allowed providing neurofeedback based on (cortical and subcortical) brain signals acquired from functional magnetic resonance imaging (fMRI). The aim of this thesis was to test the feasibility and clinical efficacy of fMRI neurofeedback (fMRI-NF) training in a psychiatric population and to develop protocols that allow translating the technique to motor rehabilitation. Specifically, this thesis summarises the clinical and neuroimaging results from a randomised controlled trial conducted in patients suffering from depression. Depression represents a leading cause of disability in adults and epidemiological data indicates that up to one third of patients remain depressed after treatment. Another focus was the development of a motor imagery-based fMRI-NF protocol in healthy participants. This work has informed a proof-of-concept study for motor rehabilitation in stroke survivors, for which the methodology was preregistered on a public platform before data collection started to increase transparency. The thesis aims to address problematic research practices that have been attributed to the replication crisis in many areas of science, including a clear separation of planned and exploratory hypotheses and the use and adaptation of alternative statistical methods. A review chapter discusses potential electrophysiological target signatures for EEG-NF to improve motor symptoms in Parkinson’s disease patients. The thesis concludes with a discussion of current premises, promises, and pitfalls in clinical applications of neurofeedback training and considerations for clinical trials development.

Funding source

Health and Care Research Wales

Professor Richard Wise

Professor Richard Wise

Professor, Head of Magnetic Resonance Imaging