• Pazooki, K., Leibetseder, M., Renner, W. et al. Neurofeedback Treatment of Negative Symptoms in Schizophrenia: Two Case Reports. Appl Psychophysiol Biofeedback (2019) 44: 31. https://doi.org/10.1007/s10484-018-9417-1 LINK
Ongoing Reserach:
- QEEG bases rTMS treatment of Obsessive Compulsive Disorder with Major-Depression
- QEEG bases rTMS treatment of ADHD

NeuroAcademy Luxembourg is pleased to announce that its clinical trial regarding the qEEG assessment of the trauma therapy method CRM has been completed. The method was neuroscientifically verified, its benefits could not be confirmed by QEEG yet.

The full text of the study will be published shortly.

Arns, M., Bruder, G., Hegerl, U., Spooner, C., Palmer, D. M., Etkin, A., Fallahpour, K., Gatt, J.M., Hirshberg, L. & Gordon, E. (2015). EEG alpha asymmetry as a gender-specific predictor of outcome to acute treatment with different antidepressant medications in the randomized iSPOT-D study. Clinical Neurophysiology. doi:http://dx.doi.org/10.1016/j.clinph.2015.05.032
Arns, M., Etkin, A., Hegerl, U., Williams, L.M., DeBattista, C., Palmer, D.M., Fitzgerald, P.B., Harris, A., deBeuss, R. & Gordon, E. (2015) Frontal and rostral anterior cingulate (rACC) theta EEG in depression: Implications for treatment outcome? European Neuropsychopharmacology.
Arns, M. (2015). First EEG results of the iSPOT study in depression: EEG alpha asymmetry as a gender specific predictor of SSRI treatment outcome. Brain Stimulation, 8(2), 337. 
Arns, M., Swatzyna, R.J., Gunkelman, J & Olbrich, S. (In Press) Sleep maintenance, spindling excessive beta and impulse control: An RDoC arousal and regulatory systems approach? Neuropsychiatric Electrophysiology.



Arns, M. (2014). Open access is tiring out peer reviewers. Nature, 515, 467.


Arns, M., & Gordon, E. (2014). Quantitative EEG (QEEG) in psychiatry: Diagnostic or prognostic use? Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology. doi:10.1016/j.clinph.2014.01.014


Arns, M., & Kenemans, J. L. (2014). Neurofeedback in ADHD and insomnia: Vigilance stabilization through sleep spindles and circadian networks. Neuroscience and Biobehavioral Reviews, 183-194. doi:10.1016/j.neubiorev.2012.10.006


Arns, M., & Olbrich, S. (2014). Personalized medicine in ADHD and depression: Use of pharmaco-EEG. Current Topics in Behavioral Neurosciences. doi:10.1007/7854_2014_295


Arns, M., Heinrich, H., & Strehl, U. (2014). Evaluation of neurofeedback in ADHD: The long and winding road. Biological Psychology, 95, 108-15. doi:10.1016/j.biopsycho.2013.11.013


van der Star, S. & Arns, M. (2014) Neurofeedback bij de behandeling van ADHD: Een richtingenstrijd? De Psycholoog.


Van Dinteren, R., Arns, M., Jongsma, M., & Kessels, R. (2014). Combined frontal and parietal P300 amplitudes indicate compensated cognitive processing across the lifespan. Frontiers in Aging Neuroscience, 6, 294. 


van Dinteren, R., Arns, M., Jongsma, M. L. A., & Kessels, R. P. C. (2014). P300 development across the lifespan: A systematic review and meta-analysis. PloS One, 9(2), e87347. doi:10.1371/journal.pone.0087347


van Tricht, M. J., Ruhrmann, S., Arns, M., Müller, R., Bodatsch, M., Velthorst, E., . . . Nieman, D. H. (2014). Can quantitative EEG measures predict clinical outcome in subjects at clinical high risk for psychosis? A prospective multicenter study. Schizophrenia Research. doi:10.1016/j.schres.2014.01.019


Veth, C. P., Arns, M., Drinkenburg, W., Talloen, W., Peeters, P. J., Gordon, E., & Buitelaar, J. K. (2014). Association between COMT val158met genotype and EEG alpha peak frequency tested in two independent cohorts. Psychiatry Research, 219, 221-224. doi:10.1016/j.psychres.2014.05.021



Arns M, Cerquera A, Gutiérrez RM, Hasselman F, Freund JA. Non-linear EEG analyses predict non-response to rtms treatment in major depressive disorder. Clinical Neurophysiology 2013


Arns M, Conners CK, Kraemer HC. A decade of EEG theta/beta ratio research in ADHD: A meta-analysis. J Atten Disord 2013, Jul;17:374-83. doi:10.1177/1087054712460087


Arns M, van der Heijden KB, Arnold LE & Kenemans JL. (2013): Geographic variation in the prevalence of attention-deficit/hyperactivity disorder: The sunny perspective. Biological Psychiatry: DOI: 10.1016/j.biopsych.2013.02.010


Arns, M., van der Heijden, K. B., Arnold, L. E., & Kenemans, J. L. (2013). Reply to: The geographic variation in the prevalence of attention-deficit/hyperactivity disorder in the U.S. Is likely due to geographical variations of solar ultraviolet-b doses and race. Biological Psychiatry. doi:http://dx.doi.org/10.1016/j.biopsych.2013.05.033


Arns, M., van der Heijden, K. B., Eugene Arnold, L., Swanson, J. M., & Leon Kenemans, J. (2013). Reply to: Attention-Deficit/hyperactivity disorder and solar irradiance: A cloudy perspective. Biological Psychiatry.doi: http://dx.doi.org/10.1016/j.biopsych.2013.09.033


Arns, M. & Strehl. U. (2013) Evidence for efficacy of Neurofeedback in ADHD? A comment on "Sonuga-Barke et al. Nonpharmacological interventions for ADHD: Systematic Review and meta-analyses of randomized controlled trials of dietary and psychological treatments." American Journal of Psychiatry,170, 799A-800.


Arns, M., & Olbrich, S. (2013). Two EEG channels do not make a ‘quantitative EEG (QEEG)Ù: A response to widge, avery and zarkowski (2013). Brain Stimulation. doi:doi:10.1016/j.brs.2013.09.009


Arns, M. (2013). De rol van slaap bij adhd: Mogelijkheden voor preventie van adhd? Tijdschrift Voor Psychiatrie, 55(10).


Olbrich, S., & Arns, S. M. (2013). EEG biomarkers in major depressive disorder: Discriminative power and prediction of treatment response. International Review of Psychiatry, 25(5), 604-618. doi:10.3109/09540261.2013.816269


Spronk DB, Veth CP, Arns M, Schofield PR, Dobson-Stone C, Ramaekers JG, et al.. DBH -1021C>T and COMT val108/158met genotype are not associated with the P300 ERP in an auditory oddball task. Clin Neurophysiol 2013, May;124:909-15. http://dx.doi.org/10.1016/j.clinph.2012.11.008


The Collaborative Neurofeedback Group (Arnold, L.E., Arns, M., Conners, K., DeBeus, R., Hirshberg, L., Kerson, C., Kraemer, H., Lofthouse, N., Lubar, J., McBurnett, K. & Monastra, V.) (In Press) A proposed multi-site double-blind randomized clinical trial of neurofeedback for ADHD: Need, rationale and strategy. Journal of Attention Disorders. doi: 10.1177/1087054713482580


de Vries, M., Wilder-Smith, O. H. G., Jongsma, M. L. A., van den Broeke, E. N., Arns, M., van Goor, H., & van Rijn, C. M. (2013). Altered resting state EEG in chronic pancreatitis patients: Toward a marker for chronic pain. Journal of Pain Research.


Zoon, H.F.A., Veth, C.P.M., Arns, M. Drinkenburg, W.H.I.M., Talloen, W., Peeters, P.J. & Kenemans, J.L. (2013) EEG Alpha Power as an intermediate measure between BDNF Val66Met and Depression severity in patients with Major Depressive Disorder. Journal of Clinical Neurophysiology, 30 (3), 261-267.



Arns, M., Drinkenburg, W. H. I. M., Fitzgerald, P. B., & Kenemans, J. L. (2012). Neurophysiological predictors of treatment outcome to rTMS in depression. Brain Stimulation.


Arns, M., Drinkenburg, W.H.I.M. & Kenemans, J.L. (2012). The effects of QEEG-informed neurofeedback in ADHD: An open label pilot studyApplied Psychophysiology and Biofeedback.


Arns, M. (2012). EEG Based Personalized Medicine in ADHD: Individual alpha peak frequency as an endophenotype associated with non-response. Journal of Neurotherapy, 16, 123-241.


Cerquera Soacha, A., Arns, M. Bolivar, E.B., Salamanca, R.M.G. & Freund, J.A. (2012) Nonlinear Dynamics Measures Applied to EEG Recordings of Patients with Attention Deficit/Hyperactivity Disorder: Quantifying the Effects of a Neurofeedback Treatment. 34th Annual International IEEE EMBS Conference

Winkelmolen, D., Kruiver, V. & Arns, M. (2012) Neurofeedback treatment in a client with ADHD and ODD. Biofeedback, 40, 102-108.
Further Studies

Here is an overview of current and previous studies. The full texts of these studies can be found in all major university libraries or state libraries. Please note: the studies do not necessarily reflect current scientific opinion, nor do they necessarily reflect the opinion of the NeuroAcademy Luxembourg.



Efficacy of Neurofeedback treatment in ADHD: A meta-analysis

About ... the impact on inattention, impulsivity and hyperactivity

In recent research, 15 published studies were evaluated through meta-analysis. The results of this research confirmed the value of Neurofeedback as a therapeutic procedure. The analysis is based on data from 1,200 patients’ therapies - of which 60% were children and 40% adults.



Motor Imagery and Neurofeedback in stroke patients

There is now sufficient evidence that the use of motor imagery (MI) in conjunction with specific physical exercises leads to a functional recovery of paralyzed limbs in stroke patients. An example of motor imagery (MI) is mirror therapy, in which a patient sits in front of a mirror which reflects his damaged arm or leg. Touching the healthy and reflective body parts will eventually be interpreted by the brain as stimuli of the damaged body part, so that optimum results may be obtained with reduced doses of medication, without reducing positive effects of treatment.

However, there are often difficulties in engagement by the patientduring an MI without an online measuring system to ensure. Here, a system based on an EEG Brain Computer Interface (BCI), can offer support via Neurofeedback, which increases the chance of getting good therapeutic results and supports the patient to better focus on the tasks in the context of MI treatment. In a pilot study, the medical researchers Girijesh Prasad, Pawel Herman, Damien Coyle, Suzanne McDonough and Jacqueline Crosbie investigated the influence of such a BCI system for a computer-based Neurofeedback in stroke patients during the motor imagery (MI) part of their therapy.


Improvements in at least one of the measured parameters by Neurofeedback were observed in all patients who took part, while the improvements in the ARAT reached a minimal clinically important difference (MCID) ...  The overall conclusion was that the support of MI by a Brain -computer Interface (BCI) is a useful intervention in a post-stroke therapy that combines the physical and motor imagery exercises for rehabilitation.