Effects of EEG- Microstate Neurofeedback on Attention and Impulsivity in Adult Attention-deficit/Hyperactivity Disorder (ADHD) and Neurotypical Controls (ADHDmicroNFB)

Effects of EEG- Microstate Neurofeedback on Attention and Impulsivity in Adult Attention-deficit/Hyperactivity Disorder (ADHD) and Neurotypical Controls

Effects of EEG- Microstate Neurofeedback on Attention and Impulsivity in Adult Attention-deficit/Hyperactivity Disorder (ADHD) and Neurotypical Controls

EEG neurofeedback (NFB) may represent a new therapeutic opportunity for ADHD, a neuropsychiatric disorder characterized by attentional deficits and high impulsivity. Recent research of the Geneva group has demonstrated the ability of ADHD patients to control specific features of their EEG (notably alpha desynchronization) and that this control was associated with reduced impulsivity. In addition, alterations in EEG brain microstates (i.e., recurrent stable periods of short duration) have been described in adult ADHD patients, potentially representing a biomarker of the disorder. The present study aims to use neurofeedback to manipulate EEG microstates in ADHD patients and healthy controls, in order to observe the effects on neurophysiological, clinical and behavioural parameters.

Neurofeedback (NFB) is a broadly used method that enables individuals to self-regulate one or more neurophysiological parameters. In the case of electroencephalography (EEG) the parameters most often used so far are slow cortical potentials (SCPs), coherence training and frequency training. Protocols based on these measures have been applied to many clinical populations exhibiting abnormal EEG patterns including schizophrenia, insomnia, dyslexia, drug addiction, autistic spectrum disorder and attention deficit/hyperactivity disorder (ADHD). Today, the most widely used neurofeedback protocol for the ADHD population is based on the theta/beta ratio (TBR). However more recent studies have failed to replicate this finding of elevated TBR as a diagnostic feature in ADHD, which was also confirmed in a meta-analysis. These divergent results motivate the need for research to explore new markers to diagnose and treat ADHD. In a recent study, Férat and colleagues proposed EEG microstate analysis as a new framework to study ADHD. Microstate analysis models spontaneous EEG as a sequence of states defined by recurring appearance of a given distribution of scalp potentials. The authors observed a significantly increased contribution of one specific state commonly referred to microstate D in the ADHD population compared to healthy subjects. This state is often associated with attentional functions and brain regions in the dorsal attention networks are involved . It would therefore be interesting to study the causal link between this microstate and attention by manipulating this biomarker with neurofeedback. In this context, a recent study by Hernandez and colleagues has already demonstrated that healthy participants were able to control such brain microstates by neurofeedback. The aim of the present study is to test whether patients with ADHD are also capable of self-regulating their microstate dynamics. In the light of recent findings on EEG microstate and the ADHD population, the hypothesis is that microstate D could be a potential functional biomarker of ADHD. To test it, the proposal is to modulate this microstate using a neurofeedback training protocol directly targeting microstate parameters. According to the main hypothesis, changes in microstate parameters should be correlated with change in attentional and impulsive behaviour. To answer this question, a two-session study was designed, where participants will perform a continuous performance task (CPT) before and after 30 minutes of microstate-based neurofeedback training. During one of the sessions participants will be trained to upregulate microstate parameters, while during the other one, they will be trained to downregulate the same parameters. Intra- and across-section statistical contrasts, both in terms of brain activity changes and behavioural performance, should provide evidence to evaluate the impact of microstate changes relative to behaviour. In addition, and according to a large number of studies on ERP components in ADHD patients the recording of event related potentials (ERPs) during the behavioural task could help us understand the neurophysiological changes linked to attention and impulsivity measures.

The experimental design includes three sessions: session 1 will be used to evaluate diagnostic using different targeted questionnaires. sessions 2 and 3 will be decomposed into 3 consecutives parts: Pre evaluation Neurofeedback Post evaluation

The experimental design includes three sessions: session 1 will be used to evaluate diagnostic using different targeted questionnaires. sessions 2 and 3 will be decomposed into 3 consecutives parts: Pre evaluation Neurofeedback Post evaluation

Neurofeedback training during which participant will be asked to change the size of a bar using different strategies to vary the parameters of its current brain's states (neurofeedback training) computed on the realtime EEG signals.

Difference in EEG microstate time coverage (%) between training and rest periods for each session (session 2, session 3) independently.

Difference in EEG microstate time coverage (%) between rest periods for each session (session 2, session 3) independently.

Correlations between EEG microstate time coverage (%) and task performance: error rates (%) and reaction time.

For each condition (Go/NoGo) we will investigate differences in Global map dissimilarity (GMD), amplitude and microstate segmentation between pre and post neurofeedback training tasks.

ADHD POPULATION GROUP A subject will be eligible if all the following criteria apply: Age: between 18-50 years Gender: male and female Health: general good health and normal or corrected-to-normal visual acuity Patients clinically able to stop the following psychotropic medications for 48h: psychostimulants, benzodiazepines Having provided written informed written consent A subject will not be eligible if any of the following criteria apply: Past or current history of a clinically significant central nervous system disorder, including structural brain abnormalities; cerebrovascular disease; history of other neurological disease, epilepsy, stroke or head trauma (defined as loss of consciousness > 5 min or requiring hospitalization) Impaired vision (normal or corrected acuity below 20/40) Medical illness (e.g., cardiovascular disease, renal failure, hepatic dysfunction) Comorbidities with current psychiatric disorders (bipolar disorder, borderline personality disorder, major depressive disorder, anxiety disorder) including substance use disorder as defined by the DIGS. HEALTHY POPULATION GROUP A subject will be eligible if all of the following criteria apply: Age: between 18-50 years Gender: male and female Health: general good health and normal or corrected-to-normal visual acuity Having provided written informed written consent A subject will not be eligible if any of the following criteria apply: Past or current history of ADHD Past or current history of main psychiatric disorders (bipolar disorder, borderline personality disorder, major depressive disorder, anxiety disorder), including substance use disorder as defined by the DIGS. Past or current history of a clinically significant central nervous system disorder, including structural brain abnormalities; cerebrovascular disease; history of other neurological disease, including epilepsy, stroke or head trauma (defined as loss of consciousness > 5 min or requiring hospitalization) Impaired vision (normal or corrected acuity below 20/40) Medical illness (e.g., cardiovascular disease, renal failure, hepatic dysfunction)

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(5):374-83. doi: 10.1177/1087054712460087. Epub 2012 Oct 19.

Arns M, Kenemans JL. Neurofeedback in ADHD and insomnia: vigilance stabilization through sleep spindles and circadian networks. Neurosci Biobehav Rev. 2014 Jul;44:183-94. doi: 10.1016/j.neubiorev.2012.10.006. Epub 2012 Oct 23.

Arns M, de Ridder S, Strehl U, Breteler M, Coenen A. Efficacy of neurofeedback treatment in ADHD: the effects on inattention, impulsivity and hyperactivity: a meta-analysis. Clin EEG Neurosci. 2009 Jul;40(3):180-9. doi: 10.1177/155005940904000311.

Brechet L, Brunet D, Birot G, Gruetter R, Michel CM, Jorge J. Capturing the spatiotemporal dynamics of self-generated, task-initiated thoughts with EEG and fMRI. Neuroimage. 2019 Jul 1;194:82-92. doi: 10.1016/j.neuroimage.2019.03.029. Epub 2019 Mar 19.

Arns M, Vollebregt MA, Palmer D, Spooner C, Gordon E, Kohn M, Clarke S, Elliott GR, Buitelaar JK. Electroencephalographic biomarkers as predictors of methylphenidate response in attention-deficit/hyperactivity disorder. Eur Neuropsychopharmacol. 2018 Aug;28(8):881-891. doi: 10.1016/j.euroneuro.2018.06.002. Epub 2018 Jun 22.

Breteler MH, Arns M, Peters S, Giepmans I, Verhoeven L. Improvements in spelling after QEEG-based neurofeedback in dyslexia: a randomized controlled treatment study. Appl Psychophysiol Biofeedback. 2010 Mar;35(1):5-11. doi: 10.1007/s10484-009-9105-2. Epub 2009 Aug 27. Erratum In: Appl Psychophysiol Biofeedback. 2010 Jun;35(2):187.

Britz J, Van De Ville D, Michel CM. BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage. 2010 Oct 1;52(4):1162-70. doi: 10.1016/j.neuroimage.2010.02.052. Epub 2010 Feb 24.

Cannon R, Congedo M, Lubar J, Hutchens T. Differentiating a network of executive attention: LORETA neurofeedback in anterior cingulate and dorsolateral prefrontal cortices. Int J Neurosci. 2009;119(3):404-41. doi: 10.1080/00207450802480325.

Comsa IM, Bekinschtein TA, Chennu S. Transient Topographical Dynamics of the Electroencephalogram Predict Brain Connectivity and Behavioural Responsiveness During Drowsiness. Brain Topogr. 2019 Mar;32(2):315-331. doi: 10.1007/s10548-018-0689-9. Epub 2018 Nov 29.

Custo A, Van De Ville D, Wells WM, Tomescu MI, Brunet D, Michel CM. Electroencephalographic Resting-State Networks: Source Localization of Microstates. Brain Connect. 2017 Dec;7(10):671-682. doi: 10.1089/brain.2016.0476. Epub 2017 Nov 17.

Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM, Beckmann CF. Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci U S A. 2006 Sep 12;103(37):13848-53. doi: 10.1073/pnas.0601417103. Epub 2006 Aug 31.

Deiber MP, Ammann C, Hasler R, Colin J, Perroud N, Ros T. Electrophysiological correlates of improved executive function following EEG neurofeedback in adult attention deficit hyperactivity disorder. Clin Neurophysiol. 2021 Aug;132(8):1937-1946. doi: 10.1016/j.clinph.2021.05.017. Epub 2021 Jun 11.

Deiber MP, Hasler R, Colin J, Dayer A, Aubry JM, Baggio S, Perroud N, Ros T. Linking alpha oscillations, attention and inhibitory control in adult ADHD with EEG neurofeedback. Neuroimage Clin. 2020;25:102145. doi: 10.1016/j.nicl.2019.102145. Epub 2019 Dec 24.

Diaz Hernandez L, Rieger K, Baenninger A, Brandeis D, Koenig T. Towards Using Microstate-Neurofeedback for the Treatment of Psychotic Symptoms in Schizophrenia. A Feasibility Study in Healthy Participants. Brain Topogr. 2016 Mar;29(2):308-21. doi: 10.1007/s10548-015-0460-4. Epub 2015 Nov 19.

Drechsler R, Brem S, Brandeis D, Grunblatt E, Berger G, Walitza S. ADHD: Current Concepts and Treatments in Children and Adolescents. Neuropediatrics. 2020 Oct;51(5):315-335. doi: 10.1055/s-0040-1701658. Epub 2020 Jun 19.

Ferat V, Arns M, Deiber MP, Hasler R, Perroud N, Michel CM, Ros T. Electroencephalographic Microstates as Novel Functional Biomarkers for Adult Attention-Deficit/Hyperactivity Disorder. Biol Psychiatry Cogn Neurosci Neuroimaging. 2022 Aug;7(8):814-823. doi: 10.1016/j.bpsc.2021.11.006. Epub 2021 Nov 22.

Hammer BU, Colbert AP, Brown KA, Ilioi EC. Neurofeedback for insomnia: a pilot study of Z-score SMR and individualized protocols. Appl Psychophysiol Biofeedback. 2011 Dec;36(4):251-64. doi: 10.1007/s10484-011-9165-y.

Heinrich H, Gevensleben H, Strehl U. Annotation: neurofeedback - train your brain to train behaviour. J Child Psychol Psychiatry. 2007 Jan;48(1):3-16. doi: 10.1111/j.1469-7610.2006.01665.x.

Horrell T, El-Baz A, Baruth J, Tasman A, Sokhadze G, Stewart C, Sokhadze E. Neurofeedback Effects on Evoked and Induced EEG Gamma Band Reactivity to Drug-related Cues in Cocaine Addiction. J Neurother. 2010 Jul;14(3):195-216. doi: 10.1080/10874208.2010.501498.

Katayama H, Gianotti LR, Isotani T, Faber PL, Sasada K, Kinoshita T, Lehmann D. Classes of multichannel EEG microstates in light and deep hypnotic conditions. Brain Topogr. 2007 Fall;20(1):7-14. doi: 10.1007/s10548-007-0024-3. Epub 2007 Jun 21.

Kropotov JD, Grin-Yatsenko VA, Ponomarev VA, Chutko LS, Yakovenko EA, Nikishena IS. ERPs correlates of EEG relative beta training in ADHD children. Int J Psychophysiol. 2005 Jan;55(1):23-34. doi: 10.1016/j.ijpsycho.2004.05.011.

Krylova M, Alizadeh S, Izyurov I, Teckentrup V, Chang C, van der Meer J, Erb M, Kroemer N, Koenig T, Walter M, Jamalabadi H. Evidence for modulation of EEG microstate sequence by vigilance level. Neuroimage. 2021 Jan 1;224:117393. doi: 10.1016/j.neuroimage.2020.117393. Epub 2020 Sep 21.

Mantini D, Perrucci MG, Del Gratta C, Romani GL, Corbetta M. Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci U S A. 2007 Aug 7;104(32):13170-5. doi: 10.1073/pnas.0700668104. Epub 2007 Aug 1.

Michel CM, Koenig T. EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review. Neuroimage. 2018 Oct 15;180(Pt B):577-593. doi: 10.1016/j.neuroimage.2017.11.062. Epub 2017 Dec 2.

Mottaz A, Solca M, Magnin C, Corbet T, Schnider A, Guggisberg AG. Neurofeedback training of alpha-band coherence enhances motor performance. Clin Neurophysiol. 2015 Sep;126(9):1754-60. doi: 10.1016/j.clinph.2014.11.023. Epub 2014 Dec 6.

Walker JE, Kozlowski GP. Neurofeedback treatment of epilepsy. Child Adolesc Psychiatr Clin N Am. 2005 Jan;14(1):163-76, viii. doi: 10.1016/j.chc.2004.07.009.

Walker JE. Using QEEG-guided neurofeedback for epilepsy versus standardized protocols: enhanced effectiveness? Appl Psychophysiol Biofeedback. 2010 Mar;35(1):29-30. doi: 10.1007/s10484-009-9123-0.

Zioga I, Hassan R, Luft CDB. Success, but not failure feedback guides learning during neurofeedback: An ERP study. Neuroimage. 2019 Oct 15;200:26-37. doi: 10.1016/j.neuroimage.2019.06.002. Epub 2019 Jun 12.