Abstract
Electroencephalography (EEG)-based neurofeedback (NF) is a safe, non-invasive, non-painful method for treating various conditions. Current NF systems enable the selection of only one NF parameter, so that two parameters cannot be feedback simultaneously. Consequently, the ability to individually-tailor the treatment to a patient is limited, and treatment efficiency may therefore be compromised. We aimed to design, implement and test an all-in-one, novel, computerized platform for closed-loop NF treatment, based on principles from learning theories. Our prototype performs numeric evaluation based on quantifying resting EEG and event-related EEG responses to various sensory stimuli. The NF treatment was designed according to principles of efficient learning, and implemented as a gradual, patient-adaptive 1D or 2D computer game, that utilizes automatic EEG feature extraction. Verification was performed as we compared the mean area under curve (AUC) of the theta band of a dozen subjects staring at a wall or performing the NF. Most of the subjects (75%) increased their theta band AUC during the NF session compared with the trial staring at the wall (p = 0.041). Our system enables multiple feature selection and its machine learning capabilities allow an accurate discovery of patient-specific biomarkers and treatment targets. Its novel characteristics may allow for improved evaluation of patients and treatment outcomes.
Similar content being viewed by others
References
Alkoby, O., A. Abu-Rmileh, O. Shriki, and D. Todder. Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning. Neuroscience 378:155–164, 2018.
Arns, M., S. de Ridder, U. Strehl, M. Breteler, and A. Coenen. Efficacy of neurofeedback treatment in ADHD: the effects on inattention, impulsivity and hyperactivity: a meta-analysis. Clin. EEG Neurosci. 40:180–189, 2009.
Arns, M., and J. L. Kenemans. Neurofeedback in ADHD and insomnia: vigilance stabilization through sleep spindles and circadian networks. Neurosci. Biobehav. Rev. 44:183–194, 2014.
Baehr, E., J. P. Rosenfeld, and R. Baehr. The clinical use of an alpha asymmetry protocol in the neurofeedback treatment of depression. J. Neurother. 2:10–23, 1997.
Blankertz, B., G. Dornhege, M. Krauledat, K.-R. Muller, V. Kunzmann, F. Losch, and G. Curio. The Berlin brain–computer interface: EEG-based communication without subject training. IEEE Trans. Neural Syst. Rehabil. Eng. 14:147–152, 2006.
Boecker, R., N. E. Holz, A. F. Buchmann, D. Blomeyer, M. M. Plichta, I. Wolf, S. Baumeister, A. Meyer-Lindenberg, T. Banaschewski, D. Brandeis, and M. Laucht. Impact of early life adversity on reward processing in young adults: EEG–fMRI results from a prospective study over 25 years. PLoS ONE 9:e104185, 2014.
Calderon, K. S., and W. W. Thompson. Biofeedback relaxation training: a rediscovered mind–body tool in public health. Am. J. Health Stud. 19:185–194, 2004.
Choobforoushzadeh, A., H. T. Neshat-Doost, H. Molavi, and M. R. Abedi. Effect of neurofeedback training on depression and fatigue in patients with multiple sclerosis. Appl. Psychophysiol. Biofeedback 40:1–8, 2015.
deBeus, R. J., and D. A. Kaiser. Neurofeedback with children with attention deficit hyperactivity disorder: a randomized double-blind placebo-controlled study. In: Neurofeedback and Neuromodulation Techniques and Applications, edited by R. Coben, and J. R. Evans. New York: Academic, 2011, pp. 127–152.
Egner, T., and J. H. Gruzelier. Ecological validity of neurofeedback: modulation of slow wave EEG enhances musical performance. Neuroreport 14:1221–1224, 2003.
Friedrich, E. V. C., G. Wood, R. Scherer, and C. Neuper. Mind over brain, brain over mind: cognitive causes and consequences of controlling brain activity. Front. Hum. Neurosci. 8:348, 2014.
Friel, P. N. EEG biofeedback in the treatment of attention deficit hyperactivity disorder. Altern. Med. Rev. 12:146–151, 2007.
Gevensleben, H., B. Holl, B. Albrecht, C. Vogel, D. Schlamp, O. Kratz, P. Studer, A. Rothenberger, G. H. Moll, and H. Heinrich. Is neurofeedback an efficacious treatment for ADHD? A randomised controlled clinical trial. J. Child Psychol. Psychiatry 50:780–789, 2009.
Gevensleben, H., G. H. Moll, A. Rothenberger, and H. Heinrich. Neurofeedback in attention-deficit/hyperactivity disorder—different models, different ways of application. Front. Hum. Neurosci. 8:846, 2014.
Gevensleben, H., A. Rothenberger, G. H. Moll, and H. Heinrich. Neurofeedback in children with ADHD: validation and challenges. Expert Rev. Neurother. 12:447–460, 2012.
Gruzelier, J. H. EEG-neurofeedback for optimising performance. II: creativity, the performing arts and ecological validity. Neurosci. Biobehav. Rev. 44:142–158, 2014.
Gruzelier, J. H. EEG-neurofeedback for optimising performance. I: a review of cognitive and affective outcome in healthy participants. Neurosci. Biobehav. Rev. 44:124–141, 2014.
Heinrich, H., H. Gevensleben, and U. Strehl. Annotation: neurofeedback—train your brain to train behaviour. J. Child Psychol. Psychiatry 48:3–16, 2007.
Hurt, E., L. E. Arnold, and N. Lofthouse. Quantitative EEG neurofeedback for the treatment of pediatric attention-deficit/hyperactivity disorder, autism spectrum disorders, learning disorders, and epilepsy. Child Adolesc. Psychiatr. Clin. N. Am. 23:465–486, 2014.
Klimesch, W. EEG-alpha rhythms and memory processes. Int. J. Psychophysiol. 26:319–340, 1997.
Kropotov, J. Event-Related Potentials and Neurotherapy. San Diego: Academic, 2009.
Kubik, A., and A. Biedroń. Neurofeedback therapy in patients with acute and chronic pain syndromes—literature review and own experience. Prz. Lek. 70:440–442, 2013.
Lackner, N., H.-F. Unterrainer, D. Skliris, S. Shaheen, M. Dunitz-Scheer, G. Wood, P. J. Z. Scheer, S. J. Wallner-Liebmann, and C. Neuper. EEG neurofeedback effects in the treatment of adolescent anorexia nervosa. Eat. Disord. 24:354–374, 2016.
Landers, D. M., S. J. Petruzzello, W. Salazar, D. J. Crews, K. A. Kubitz, T. L. Gannon, and M. Han. The influence of electrocortical biofeedback on performance in pre-elite archers. Med. Sci. Sports Exerc. 23:123–129, 1991.
Marzbani, H., H. R. Marateb, and M. Mansourian. Neurofeedback: a comprehensive review on system design, methodology and clinical applications. Basic Clin. Neurosci. 7:143–158, 2016.
May, G., R. Benson, R. Balon, and N. Boutros. Neurofeedback and traumatic brain injury: a literature review. Ann. Clin. Psychiatry 25:289–296, 2013.
Monastra, V. Electroencephalographic biofeedback (neurotherapy) as a treatment for attention deficit hyperactivity disorder: rationale and empirical foundation. Child Adolesc. Psychiatr. Clin. N. Am. 14:55–82, 2005.
Perreau-Linck, E., N. Lessard, J. Lévesque, and M. Beauregard. Effects of neurofeedback training on inhibitory capacities in ADHD children: a single-blind, randomized, placebo-controlled study. J. Neurother. 14:229–242, 2010.
Platt, J. C., and J. C. Platt. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Adv. Large Margin Classif. 61–74, 1999. http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.41.1639.
Reiner, M., J. Gruzelier, P. D. Bamidis, and T. Auer. The science of neurofeedback: learnability and effects. Neuroscience 378:1–10, 2018.
Rozengurt, R., A. Barnea, S. Uchida, and D. A. Levy. Theta EEG neurofeedback benefits early consolidation of motor sequence learning. Psychophysiology 53:965–973, 2016.
Sherlin, L. H., M. Arns, J. Lubar, H. Heinrich, U. Strehl, and M. B. Sterman. Neurofeedback and basic learning theory: implications for research and practice. 2011. https://doi.org/10.1080/10874208.2011.623089.
Sitaram, R., T. Ros, L. Stoeckel, S. Haller, F. Scharnowski, J. Lewis-Peacock, N. Weiskopf, M. L. Blefari, M. Rana, E. Oblak, N. Birbaumer, and J. Sulzer. Closed-loop brain training: the science of neurofeedback. Nat. Rev. Neurosci. 18:86–100, 2017.
Vernon, D. J. Can neurofeedback training enhance performance? An evaluation of the evidence with implications for future research. Appl. Psychophysiol. Biofeedback 30:347–364, 2005.
Vernon, D., T. Egner, N. Cooper, T. Compton, C. Neilands, A. Sheri, and J. Gruzelier. The effect of training distinct neurofeedback protocols on aspects of cognitive performance. Int. J. Psychophysiol. 47:75–85, 2003.
Vidaurre, C., C. Sannelli, K.-R. Müller, and B. Blankertz. Machine-learning-based coadaptive calibration for brain–computer interfaces. Neural Comput. 23:791–816, 2011.
Wang, T., D. Mantini, and C. R. Gillebert. The potential of real-time fMRI neurofeedback for stroke rehabilitation: a systematic review. Cortex 2017. https://doi.org/10.1016/j.cortex.2017.09.006.
Author information
Authors and Affiliations
Corresponding author
Additional information
Associate Editor Joel Stitzel oversaw the review of this article.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Issachar, G., Bar-Shalita, T., Baruch, Y. et al. Design and Implementation of a Novel Subject-Specific Neurofeedback Evaluation and Treatment System. Ann Biomed Eng 47, 1203–1211 (2019). https://doi.org/10.1007/s10439-019-02228-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10439-019-02228-x