Skip to main content

Advertisement

Log in

Evaluation of artifact-corrected electroencephalographic (EEG) training: a pilot study

  • Psychiatry and Preclinical Psychiatric Studies - Original Article
  • Published:
Journal of Neural Transmission Aims and scope Submit manuscript

Abstract

This double-blind study examined the effect of electromyographical (EMG) artifacts, which contaminate electroencephalographical (EEG) signals, by comparing artifact-corrected (AC) and non-artifact-corrected (NAC) neurofeedback (NF) training procedures. 14 unmedicated college students were randomly assigned to two groups: AC (n = 7) or NAC (n = 7). Both groups received 12 sessions of NF and were trained using identical NF treatment protocols to reduce their theta/beta power ratios (TBPR). Outcomes on a continuous performance test revealed that the AC group had statistically significant increases across measures of auditory and visual attention. The NAC group showed smaller gains that only reached statistical significance on measures of visual attention. Only the AC group reduced their TBPR, the NAC group did not. AC NF appears to play an important role during training that leads to improvements in both auditory and visual attention. Additional research is required to confirm the results of this study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Adler LA, Kessler RC, Spencer T (2003) Adult ADHD Self-Report Scale-V1.1 (ASRS-V1.1) Symptoms Checklist. World Health Organization, New York

    Google Scholar 

  • American Academy of Pediatrics (2011) ADHD: clinical practice guideline for the diagnosis, evaluation, and treatment of attention-deficit/hyperactivity disorder in children and adolescents. Pediatrics 128(5):1007–1022. https://doi.org/10.1542/peds.2011-2654

    Article  Google Scholar 

  • Arns M, de Ridder S, Strehl U, Breteler M, Coenen A (2009) Efficacy of neurofeedback treatment in ADHD: the effects on inattention, impulsivity and hyperactivity: a meta-analysis. Clin EEG Neurosci 40(3):180–189. https://doi.org/10.1177/155005940904000311

    Article  PubMed  Google Scholar 

  • Arns M, Conners CK, Kraemer HC (2013) A decade of EEG theta/beta ratio research in ADHD: a meta-analysis. J Atten Disord 17(5):374–383. https://doi.org/10.1177/1087054712460087

    Article  PubMed  Google Scholar 

  • Arns M, Heinrich H, Strehl U (2014) Evaluation of neurofeedback in ADHD: the long and winding road. Biol Psychol 95:108–115. https://doi.org/10.1016/j.biopsycho.2013.11.013

    Article  PubMed  Google Scholar 

  • Bentivoglio AR, Bressman SB, Cassetta E, Carretta D, Tonali P, Albanese A (1997) Analysis of blink rate patterns in normal subjects. Mov Disord 12(6):1028–1034. https://doi.org/10.1002/mds.870120629

    Article  PubMed  CAS  Google Scholar 

  • Bresnahan SM, Barry RJ (2002) Specificity of quantitative EEG analysis in adults with attention deficit hyperactivity disorder. Psychiatry Res 112(2):133–144

    Article  PubMed  Google Scholar 

  • Brunner D, Vasko R, Detka C, Monahan J, Reynolds C III, Kupfer D (1996) Muscle artifacts in the sleep EEG: automated detection and effect on all-night EEG power spectra. J Sleep Res 5(3):155–164. https://doi.org/10.1046/j.1365-2869.1996.00009.x

    Article  PubMed  CAS  Google Scholar 

  • Brunner P, Bianchi L, Guger C, Cincotti F, Schalk G (2011) Current trends in hardware and software for brain–computer interfaces (BCIs). J Neural Eng 8:1–7. https://doi.org/10.1088/1741-2560/8/2/025001

    Article  Google Scholar 

  • Bush G, Frazier JA, Rauch SL, Seidman LJ, Whalen PJ, Jenike MA, Rosen BR, Biederman J (1999) Anterior cingulate cortex dysfunction in attention-deficit/hyperactivity disorder revealed by fMRI and the Counting Stroop. Biol Psychiatry 45(12):1542–1552

    Article  PubMed  CAS  Google Scholar 

  • Cohen J (1988) Statistical power analysis for the behavioral sciences. Lawrence Earlbaum Associates, Hillsdale

    Google Scholar 

  • De Luca CJ (2002) Surface electromyography: detection and recording. DelSys Incorporated

  • Demos J (2005) Getting started with neurofeedback. WW Norton and Company, New York

    Google Scholar 

  • Fulton BD, Scheffler RM, Hinshaw SP, Levine P, Stone S, Brown TT, Modrek S (2009) National variation of ADHD diagnostic prevalence and medication use: health care providers and education policies. Psychiatr Serv 60(8):1075–1083

    Article  PubMed  Google Scholar 

  • Gloss D, Varma JK, Pringsheim T, Nuwer MR (2016) Practice advisory: the utility of EEG theta/beta power ratio in ADHD diagnosis: report of the guideline development, dissemination, and implementation subcommittee of the American Academy of Neurology. Neurology 87(22):2375–2379. https://doi.org/10.1212/WNL.0000000000003265

    Article  PubMed  PubMed Central  Google Scholar 

  • Goncharova II, McFarland DJ, Vaughan TM, Wolpaw JR (2003) EMG contamination of EEG: spectral and topographical characteristics. Clin Neurophysiol 114:1580–1593. https://doi.org/10.1016/S1388-2457(03)00093-2

    Article  PubMed  CAS  Google Scholar 

  • Hammond DC, Walker J, Hoffman D, Lubar JF, Trudeau D, Gurnee R, Horvat J (2004) Standards for the use of quantitative electroencephalography (QEEG) in neurofeedback: a position paper of the International Society for Neuronal Regulation. J Neurother 8(1):5–27

    Article  Google Scholar 

  • Jasper HH, Solomon P, Bradley C (1938) Electroencephalographic analyses of behavior problem children. Am J Psychiatry 95(3):641–658. https://doi.org/10.1176/ajp.95.3.641

    Article  Google Scholar 

  • Kaiser DA, Sterman MB (2000) Automatic artifact detection, overlapping windows, and state transitions. J Neurother 4(3):85–92

    Article  Google Scholar 

  • Kessler RC, Adler L, Ames M, Demler O, Faraone S, Hiripi E, Howes MJ, Jin R, Secnik K, Spencer T (2005) The World Health Organization Adult ADHD Self-Report Scale (ASRS): a short screening scale for use in the general population. Psychol Med 35(02):245–256

    Article  PubMed  Google Scholar 

  • Kessler RC, Adler LA, Gruber MJ, Sarawate CA, Spencer T, Van Brunt DL (2007) Validity of the World Health Organization Adult ADHD Self-Report Scale (ASRS) Screener in a representative sample of health plan members. Int J Methods Psychiatr Res 16(2):52–65. https://doi.org/10.1002/mpr.208

    Article  PubMed  PubMed Central  Google Scholar 

  • La Marca JP (2018) Historical overview of attention deficit-hyperactivity disorder and neurofeedback: implications for academic achievement, assessment, and intervention in schools. Contemp Sch Psychol 22(1):1–17. https://doi.org/10.1007/s40688-017-0155-9

    Article  Google Scholar 

  • La Marca JP, O’Connor RE (2016) Neurofeedback as an intervention to improve reading achievement in students with attention deficit hyperactivity disorder, inattentive subtype. NeuroRegulation 3(2):55–77. https://doi.org/10.15540/nr.3.2.55

    Article  Google Scholar 

  • Lakens D (2013) Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front Psychol. https://doi.org/10.3389/fpsyg.2013.00863

    Article  PubMed  PubMed Central  Google Scholar 

  • Linden M, Habib T, Radojevic V (1996) A controlled study of the effects of EEG biofeedback on cognition and behavior of children with attention deficit disorder and learning disabilities. Biofeedback Self-regulation 21(1):35–49. https://doi.org/10.1007/BF02214148

    Article  PubMed  CAS  Google Scholar 

  • Lofthouse N, Arnold LE, Hersch S, Hurt E, DeBeus R (2012) A review of neurofeedback treatment for pediatric ADHD. J Atten Disord 16(5):351–372. https://doi.org/10.1177/1087054711427530

    Article  PubMed  Google Scholar 

  • Loo SK, Barkley RA (2005) Clinical utility of EEG in attention deficit hyperactivity disorder. Appl Neuropsychol 12(2):64–76. https://doi.org/10.1207/s15324826an1202_2

    Article  PubMed  Google Scholar 

  • St. Louis E, Frey LE (eds) (2016) Electroencephalography (EEG): an introductory text and atlas of normal and abnormal findings in adults, children, and infants. American Epilepsy Society, Chicago. https://doi.org/10.5698/978-0-9979756-0-4

  • Lubar JF (1991) Discourse on the development of EEG diagnostics and biofeedback for attention-deficit/hyperactivity disorders. Biofeedback Self-Regulation 16(3):201–225. https://doi.org/10.1007/BF01000016

    Article  PubMed  CAS  Google Scholar 

  • Lubar JF, Lubar JO (1999) Neurofeedback assessment and treatment for attention deficit/hyperactivity disorders. In: Evans J, Abarbanel A (eds) Introduction to quantitative EEG and neurofeedback. Academic Press, San Diego, pp 103–146

    Chapter  Google Scholar 

  • Lubar JF, Shouse MN (1976) EEG and behavioral changes in a hyperkinetic child concurrent with training of the sensorimotor rhythm (SMR). Biofeedback Self-Regulation 1(3):293–306. https://doi.org/10.1007/bf01001170

    Article  PubMed  CAS  Google Scholar 

  • Lubar JF, Swartwood MO, Swartwood JN, Timmermann DL (1995) Quantitative EEG and auditory event-related potentials in the evaluation of attention-deficit/hyperactivity disorder: effects of methylphenidate and implications for neurofeedback training. J Psychoeduc Assess 98:143–160

    Google Scholar 

  • Maddux CD (2010) Review of the IVA + Plus: integrated visual and auditory continuous performance test. In: Spies RA, Carlson JF, Geisinger KF (eds) The eighteenth mental measurements yearbook. Buros Institute of Mental Measurements, Lincoln, pp 434–437

    Google Scholar 

  • Monastra VJ, Lubar JF, Linden M, VanDeusen P, Green G, Wing W, Phillips A, Fenger TN (1999) Assessing attention deficit hyperactivity disorder via quantitative electroencephalography: an initial validation study. Neuropsychology 13(3):424–433. https://doi.org/10.1037/0894-4105.13.3.424

    Article  PubMed  Google Scholar 

  • Monastra VJ, Lynn S, Linden M, Lubar JF, Gruzelier J, La Vaque TJ (2005) Electroencephalographic biofeedback in the treatment of attention-deficit/hyperactivity disorder. Appl Psychophysiol Biofeedback 30(2):95–114. https://doi.org/10.1007/s10484-005-4305-x

    Article  PubMed  Google Scholar 

  • Montgomery DD (2001) Change: detection and modification. Appl Psychophysiol Biofeedback 26(3):215–226

    Article  PubMed  CAS  Google Scholar 

  • Rossiter T, La Vaque TJ (1995) A comparison of EEG biofeedback and psychostimulants in treating attention deficit/hyperactivity disorders. J Neurother 1(1):48–59. https://doi.org/10.1300/J184v01n01_07

    Article  Google Scholar 

  • Sandford JA (2015) SmartMind-3. BrainTrain Inc, Richmond

    Google Scholar 

  • Sandford JA, Sandford SE (2014) Integrated Visual and Auditory Continuous Performance Test (IVA-2). BrainTrain Inc, Richmond

    Google Scholar 

  • Sandford JA, Sandford SE (2017) BrainTrain IVA-2 Integrated Visual and Auditory Continuous Performance Test Manual. BrainTrain Inc, Richmond

    Google Scholar 

  • Sawilowsky SS (2009) New effect size rules of thumb. J Mod Appl Stat Methods 8(2):597–599

    Article  Google Scholar 

  • Sime W (2010) Review of the IVA + Plus: Integrated Visual and Auditory Continuous Performance Test. In: Spies RA, Carlson JF, Geisinger KF (eds) The eighteenth mental measurements yearbook. Buros Institute of Mental Measurements, Lincoln, pp 437–439

    Google Scholar 

  • Snyder SM, Quintana H, Sexson SB, Knott P, Haque A, Reynolds DA (2008) Blinded, multi-center validation of EEG and rating scales in identifying ADHD within a clinical sample. Psychiatry Res 3(159):346–358

    Article  Google Scholar 

  • Thompson L, Thompson M (1998) Neurofeedback combined with training in metacognitive strategies: effectiveness in students with ADD. Appl Psychophysiol Biofeedback 23(4):243–263. https://doi.org/10.1023/A:1022213731956

    Article  PubMed  CAS  Google Scholar 

  • Tinius TP (2003) The Integrated Visual and Auditory Continuous Performance Test as a neuropsychological measure. Arch Clin Neuropsychol 18(5):199–214. https://doi.org/10.1093/arclin/18.5.439

    Article  PubMed  Google Scholar 

  • van Boxtel A (2001) Optimal signal bandwidth for the recording of surface EMG activity of facial, jaw, oral, and neck muscles. Psychophysiology 38(1):22–34

    Article  PubMed  Google Scholar 

  • Weber E, Köberl A, Frank S, Doppelmayr M (2011) Predicting successful learning of SMR neurofeedback in healthy participants: methodological considerations. Appl Psychophysiol Biofeedback 36(1):37–45. https://doi.org/10.1007/s10484-010-9142-x

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jeffry P. La Marca.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

La Marca, J.P., Cruz, D., Fandino, J. et al. Evaluation of artifact-corrected electroencephalographic (EEG) training: a pilot study. J Neural Transm 125, 1087–1097 (2018). https://doi.org/10.1007/s00702-018-1877-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00702-018-1877-1

Keywords

Navigation