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Neuere Ansätze im Neurofeedbacktraining

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Zusammenfassung

Durch den rasanten Fortschritt in der Computertechnologie – der sich sowohl in der Hardware als auch in der Softwareentwicklung in immer schnelleren Rechnern mit größeren Speicherkapazitäten, besserer visueller Darstellung des Feedbacks und komplexen Softwaremodulen widerspiegelt – ist es seit wenigen Jahren möglich geworden, auch neue, aufwändige Bio- und Neurofeedbackanwendungen in den therapeutischen Praxen einzusetzen.

Weiterführende Literatur

Allgemein

  1. Sherlin L, Arns M, Lubar J, Sokhadze E (2010) A position paper on Neurofeedback for the treatment of ADHD. J Neurotherapy 14(2):66–78Google Scholar

QEEG

  1. Collura TF (2013) Technical foundations of neurofeedback, 1. Aufl. Routledge, New YorkGoogle Scholar
  2. Hoffman DA, Lubar JF, Thatcher RW, Sterman B, Rosenfeld P, Striefel S, Trudeau D, Stockdale S (1999) Limitations of the American Academy of Neurology and American Clinical Neurophysiology Society paper on qEEG. J Neurophysiol Clin Neurosci 11:401–407Google Scholar
  3. Thatcher RW, Lubar JF (2009) History of the scientific standards of QEEG normative databases. Introd Quant EEG Neurofeedback 2009:29–59.  https://doi.org/10.1016/b978-0-12-374534-7.00002-2 CrossRefGoogle Scholar
  4. Thatcher RW, Walker R, Biver C, North D, Curtin R (2003) Sensitivity and specificity of an EEG normative database: validation and clinikcal correlation. J Neurotherapy 7(3/4):87–121Google Scholar

Z-Wert-Training

  1. Collura TF (2008a) Whole-head normalization using live Z-scores for connectivity training (Part 2). NeuroConnections Newsl:9–12Google Scholar
  2. Collura TF (2008b) Whole-head normalization using live Z-scores for connectivity training, Part 1. NeuroConnections Newsl 18–19 (S 12, 15)Google Scholar
  3. Collura TF (2009) Neuronal dynamics in relation to normative electroencephalography assessment and training. Biofeedback 36:134–139Google Scholar
  4. Collura TF, Guan J, Tarrant J, Bailey J, Starr F (2010) EEG biofeedback case studies using live Z-score training and a normative database. J Neurotherapy 14(1):22–46Google Scholar
  5. Smith M (2008) A father finds a solution: Z-score training. NeuroConnections Newsl 24–25 (S 22)Google Scholar
  6. Thatcher RW (2008) Z-score EEG biofeedback: conceptual foundations. NeuroConnections Newsl 20 (S 9, 11)Google Scholar

LORETA-Neurofeedback

  1. Brodmann K (1909) Vergleichende Lokalisationslehre der Grosshirnrinde. In ihren Principien dargestellt auf Grund des Zellenbaues. Johann Ambrosius Barth Verlag, LeipzigGoogle Scholar
  2. Buckner RL, Andrews-Hanna JR, Schacter DL (2008) The brain’s default network – anatomy, function, and relevance to disease. Ann N Y Acad Sci 1124:1–38Google Scholar
  3. Cannon R, Lubar J (2007) EEG spectral power and coherence: Differentiating effects of spatial-specific neuro-operant learning (SSNOL) utilizing LORETA neurofeedback training in the anterior cingulate and bilateral dorsolateral prefrontal cortices. J Neurotherapy 11(3):25–44Google Scholar
  4. Cannon R, Lubar J, Thornton K, Wilson S, Congedo M (2005) Limbic beta activation and LORETA: can hippocampal and related limbic activity be recorded and changes visualized using LORETA in an affective memory condition? J Neurotherapy 8(4):5–24Google Scholar
  5. Cannon R, Lubar J, Gerke A, Thornton K, Hutchens T, McCammon V (2006) EEG spectral-power and coherence: LORETA neurofeedback training in the anterior cingulate gyrus. J Neurotherapy 10(1):5–31Google Scholar
  6. Cannon R, Lubar J, Congedo M, Thornton K, Towler K, Hutchens T (2007) The effects of neurofeedback training in the cognitive division of the anterior cingulate gyrus. Int J Neurosci 117(3):337–357PubMedGoogle Scholar
  7. Cannon R, Lubar J, Sokhadze E, Baldwin D (2008) LORETA neurofeedback for addiction and the possible neurophysiology of psychological processes influenced: a case study and region of interest analysis of LORETA neurofeedback in right anterior cingulate cortex. J Neurotherapy 12(4):227–241Google Scholar
  8. Cannon R, Congredo M, Lubar J, Hutchens T (2009) Differentiating a network of executive attention: LORETA neurofeedback in anterior cingulate and dorsolateral prefrontal cortices. Int J Neurosci 119(3):404–441PubMedGoogle Scholar
  9. Congedo M, Lubar JF, Joffe D (2004) Low-resolution electromagnetic tomography neurofeedback. IEEE Trans Neural Syst Rehabil Eng 12(4):387–397PubMedGoogle Scholar
  10. Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ et al (2008) Mapping the structural core of human cerebral cortex. PLoS Biol 6(7):e159.  https://doi.org/10.1371/journal.pbio.0060159 CrossRefPubMedPubMedCentralGoogle Scholar
  11. Hebb D (1949) The organisation of behaviour. Wiley, New YorkGoogle Scholar
  12. Jatoi MA, Kamel N, Malik AS, Faye I (2014) EEG based brain source localization comparison of sLORETA and eLORETA. Australas Phys Eng Sci Med 37:713–721PubMedGoogle Scholar
  13. Koberda JL (2012) Autistic spectrum disorder (ASD) as a potential target of Z-score LORETA neurofeedback. The Neuroconnection- winter 2012, edition (ISNR), S 24Google Scholar
  14. Koberda JL, Moses A, Koberda L, Koberda P (2012) Cognitive enhancement using19-electrode Z-score neurofeedback. J Neurotherapy 16(3):224–230Google Scholar
  15. Koberda JL, Koberda L. Koberda P. Moses A. Bienkiewicz A. (2013a) Alzheimer’s dementia as a potential targer of Z-score LORETA 19-electrode neurofeedback. Neuroconnection, S 30–32, Winter 2013Google Scholar
  16. Koberda JL, Koberda P, Bienkiewicz A, Moses A, Koberda L (2013b) Pain management using 19-electrode Z-score LORETA neurofeedback. J Neurotherapy 17:179–190Google Scholar
  17. Koberda JL, Koberda P, Moses A, Winslow J, Bienkiewicz A, Koberda L (2014a) Z-score LORETA Neurofeedback as a potential therapy of ADHD. –summer-Special Edition-Biofeedback MagazineGoogle Scholar
  18. Koberda JL, Koberda P, Moses A, Winslow J, Bienkiewicz A, Koberda L (2014b) Z-score LORETA Neurofeedback as a Potential Therapy in Depression and Anxiety. Spring-Neuroconnection, S 52–55Google Scholar
  19. Laird AR, Fox PM, Eickhoff SB et al (2011) Behavioral interpretations of intrinsic connectivity networks. J Cogn Neurosci 23:4022–4037PubMedPubMedCentralGoogle Scholar
  20. Leong SL, Vanneste S, Lim J, Smith M, Manning P, De Ridder D (2018) A randomised, double-blind, placebo-controlled parallel trial of closed-loop infraslow brain training in food addiction. Sci Rep 8:11659.  https://doi.org/10.1038/s41598-018-30181-7 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Lubar J, Congedo M, Askew JH (2003) Low-resolution electromagnetic tomography (LORETA) of cerebral activity in chronic depressive disorder. Int J Psychophysiol 49(3):175–185PubMedGoogle Scholar
  22. Mille KJ, Weaver KE, Ojemann JG (2009) Direct electrophysiological measurement of human default network areas. PNAS 106(29):12174Google Scholar
  23. Palva JM, Palva S (2012) Infra-slow fluctuations in electrophysiological recordings, blood-oxygenation-level-dependent signals, and psychophysical time series. Neuroimage 62(4):2201–2211PubMedGoogle Scholar
  24. Park HJ, Friston K (2013) Structural and functional brain networks: from connections to cognition. Science 342:1238411.  https://doi.org/10.1126/science.1238411 CrossRefGoogle Scholar
  25. Pascual-Marqui RD (1999) Review of methods for solving the EEG inverse problem. Int J Bioelectromagnetism 1(1):75–86Google Scholar
  26. Pascual-Marqui RD (2002) Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol 24(Suppl D):5–12Google Scholar
  27. Pascual-Marqui RD (2007) Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization. arXiv: 0710.3341. http://arxiv.org/pdf/0710.3341
  28. Pascual-Marqui RD (2009) Theory of the EEG inverse problem. In: Tong S, Thakor NV (Hrsg) Quantitative EEG analysis: methods and clinical applications. Artech House, Boston, S 121–140Google Scholar
  29. Pascual-Marqui RD, Michel CM, Lehmann D (1994) Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 18(1):49–65Google Scholar
  30. Pascual-Marqui RD, Lehmann D, Koukkou M, Kochi K, Anderer P, Saletu B, Tanaka H, Hirata K, John ER, Prichep L, Biscay-Lirio R, Kinoshita T (2011) Assessing interactions in the brain with exact low-resolution electromagnetic tomography. Philos Trans A Math Phys Eng Sci 369(1952):3768–3784PubMedGoogle Scholar
  31. Pascual-Marqui RD, Biscay R, Bosch-Bayard J, Lehmann D, Kochi K, Yamada N, Kinoshita T, Sadato, N (2014a) Isolated effective coherence (iCoh): causal information flow excluding indirect paths. arXiv preprint arXiv:1402.4887. http://arxiv.org/abs/1402.4887
  32. Pascual-Marqui RD, Biscay R, Bosch-Bayard J, Lehmann D, Kochi K, Yamada N, Kinoshita T, Sadato N (2014b) Assessing direct paths of intracortical causal information flow of oscillatory activity with the isolated effective coherence (iCoh). Front Hum Neurosci 8, 448  https://doi.org/10.3389/fnhum.2014.00448.eCollection2014.
  33. Pascual-Marqui, Faber, Ikeda, Ishii, Kinoshita, Kitaura, Kochi, Milz, Nishida, Yoshimura (2017) The cross-frequency mediation mechanism of intracortical information transactions. arxiv.org/abs/1703.07654.  https://doi.org/10.1101/119362
  34. Petersen SE, Sporns O (2015) Brain networks and cognitive architectures. Neuron 88(1):207–219PubMedPubMedCentralGoogle Scholar
  35. Raichle ME, Snyder AZ (2007) A default mode of brain function: a brief history of an evolving idea. Neuroimage 37:1083–1090Google Scholar
  36. Thatcher RW (2008) Z-score EEG biofeedback: conceptual foundations. NeuroConnections Newsl 20 (S 9, 11)Google Scholar

Phänotyp-geleitetes Neurofeedbacktraining

  1. Arns M, Gunkelman J, Breteler M, Spronk D (2008) EEG phenotypes predict treatment outcome to stimulants in children with ADHD. J Integr Neurosci 7:421–438PubMedGoogle Scholar
  2. Coben R, Linden M, Myers TE (2010) Neurofeedback for autistic spectrum disorder: a review of literature. Appl Psychophysiol Biofeedback 35:83–105PubMedGoogle Scholar
  3. Falkai P, Wittchen HU (2018) Diagnostisches und statistisches Manual Psychischer Störungen DSM-5. Hogrefe.Google Scholar
  4. Gunkelman J (2006) Transcend the DSM using phenotypes. Biofeedback 34(3):95–98Google Scholar
  5. Johnstone J, Gunkelman J, Lunt J (2005) Clinical database development: characterization of EEG phenotypes. Clin EEG Neurosci 36(2):99–107PubMedGoogle Scholar

Neurostimulation

  1. Antal A, Herrmann CS (2016) Transcranial alternating current and random noise stimulation: possible mechanisms. Neural Plast 2016:3616807PubMedPubMedCentralGoogle Scholar
  2. Antal A, Paulus W (2013) Transcranial alternating current stimulation (tACS). Front Hum Neurosci 7:317PubMedPubMedCentralGoogle Scholar
  3. Aust S, Palm U, Padberg F, Bajbouj M (2015) Transkranielle Gleichstromstimulation bei depressiven Störungen. Nervenarzt 86:1492–1499PubMedGoogle Scholar
  4. Bikson M, Grossman P, Thomas C, Zannou AL, Jiang J, Adnan T, Mourdoukoutas A, Kronberg G, Truong D, Boggio P, Brunoni A, Charvet L, Fregni F, Frisch B, Gillick B, Hamilton R, Hampstead B, Jankord R, Kirton A, Knotkova H, Liebetanz D, Liu A, Loo C, Nitsche M, Reis J, Richardson J, Rotenberg A, Turkeltaub P, Woods A (2016) Safety of transcranial direct current stimulation: evidence based update 2016. Brain Stimul 9:641–661PubMedPubMedCentralGoogle Scholar
  5. Das S, Holland P, Frens MA, Donchin O (2016) Impact of transcranial direct current stimulation (tDCS) on neuronal functions. Front Neurosci 10:550PubMedPubMedCentralGoogle Scholar
  6. Funk R (2017) Does electromagnetic therapy meet an equivalent counterpart within the organism? J Transl Sci 3:1–6Google Scholar
  7. Hamblin M (2016) Shining light on the head: photobiomodulation for brain disorders. Biochom Biophys Acta Clin 6:113–124Google Scholar
  8. Hennessy M, Hamblin M (2016) Photobiomodulation and the brain: a new paradigm. J Opt 19:013003PubMedPubMedCentralGoogle Scholar
  9. Kunze T, Hunold A, Haueisen J, Jirsa V, Spiegler A (2016) Transcranial direct current stimulation changes resting state functional connectivity: a large-scale brain network modeling study. Neuroimage 140:174–187.  https://doi.org/10.1016/j.neuroimage.2016.02.015 CrossRefPubMedGoogle Scholar
  10. Martiny K, Lunde M, Bech P (2010) Transcranial low voltage pulsed electromagnetic fields in patients with treatment-resistant depression. Biol Psychiatry 68:163–169.  https://doi.org/10.1016/j.biopsych.2010.02.017 CrossRefPubMedGoogle Scholar
  11. Matsumoto H, Ugawa Y (2016) Adverse events of tDCS and tACS: a review. Clin Neurophysiol Pract 2:19–25.  https://doi.org/10.1016/j.cnp.2016.12.003 CrossRefPubMedPubMedCentralGoogle Scholar
  12. Monai H, Ohkura M, Tanaka M, Oe Y, Konno A, Hirai H, Mikoshiba K, Itohara S, Nakai J, Iwai Y, Hirase H (2016) Calcium imaging reveals glial involvement in transcranial direct current stimulation-induced plasticity in mouse brain. Nat Commun 7:11100.  https://doi.org/10.1038/ncomms11100 CrossRefPubMedPubMedCentralGoogle Scholar
  13. Nitsche M, Paulus W (2000) Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. J Physiol 527:633–639PubMedPubMedCentralGoogle Scholar
  14. Palm U, Reisinger E, Keeser D, Kuo M, Pogarell O, Leicht G, Mulert C, Nitsche M, Padberg F (2013) Evaluation of sham transcranial direct current stimulation for randomized, placebo-controlled clinical trials. Brain Stimul 6:690–695PubMedGoogle Scholar
  15. Robertson JA, Théberge J, Weller J, Drost DJ, Prato FS, Thomas AW (2009) Low-frequency pulsed electromagnetic field exposure can alter neuroprocessing in humans. J Roy Soc Interf 7:467–473Google Scholar
  16. Roche N, Geiger M, Bussel B (2015) Mechanisms underlying the effects of transcranial direct current stimulation. Ann Phys Rehabil Med 58:214–219.  https://doi.org/10.1016/j.rehab.2015.04.009 CrossRefPubMedGoogle Scholar
  17. Vosskuhl J, Strüber D, Herrmann CS (2018) Non-invasive brain stimulation: a paradigm shift in understanding brain oscillations. Front Hum Neurosci 12:211.  https://doi.org/10.3389/fnhum.2018.00211 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Woods A, Antal A, Bikson M, Boggio P, Brunoni A, Celnik P, Cohen L, Fregni F, Herrmann CS, Kappenman E, Knotkova H, Liebetanz D, Miniussi C, Miranda P, Paulus W, Priori A, Reato D, Stagg C, Wenderoth N, Nitsche M (2016) A technical guide to tDCS, and related non-invasive brain stimulation tools. Clin Neurophysiol 127:1031–1048Google Scholar

HEG-Biofeedback

  1. Carmen JA (2004) Passive infrared hemoencephalography: four years and 100 migraines. J Neurotherapy 8(3):23–51Google Scholar
  2. Coben R, Pudolsky I (2007) Infrared imaging and neurofeedback: initial reliability and validity. J Neurotherapy 11(3):3–13Google Scholar
  3. Friedes D, Aberbach L (2003) Exploring hemispheric differences in infrared brain emissions. J Neurotherapy 8(3):53–61Google Scholar
  4. Mize W (2004) Hemoencephalography a new therapy for attention deficit hyperactivity disorder (ADHD): case report. J Neurotherapy 8(3):77–97Google Scholar
  5. Sherrill R (2004) Effects of hemoencephalography (HEG) training at three prefrontal locations using EEG ratios at Cz. J Neurotherapy 8(3):63–76Google Scholar
  6. Toomim H, Mize W, Kwong PC, Toomim M, Marsh R, Kozlowski GP, Kimball M, Remond A (2004) Intentional increase of cerebral blood oxygenation using hemoencephalography (HEG). J Neurotherapy 8(3):5–21Google Scholar

fMRT-Neurofeedback

  1. Bray S, Shimojo S, O’Doherty JP (2007) Direct instrumental conditioning of neural activity using functional magnetic resonance imagingderived reward feedback. J Neurosci 27:7498–7507PubMedPubMedCentralGoogle Scholar
  2. Caria A, Veit R, Sitaram R, Lotze M, Weiskopf N, Grodd W, Birbaumer N (2007) Regulation of anterior insular cortex activity using real-time fMRI. Neuroimage 35:1238–1246Google Scholar
  3. Caria A, Sitaram R, Veit R, Begliomini C, Birbaumer N (2010) Volitional control of anterior insula activity modulates the response to aversive stimuli. A real-time functional magnetic resonance imaging study. Biol Psychiatry 68(5):425–432PubMedGoogle Scholar
  4. DeCharms RC (2007) Reading and controlling human brain activation using real-time functional magnetic resonance imaging. Trends Cogn Sci 11:473–481PubMedGoogle Scholar
  5. DeCharms RC (2008) Applications of real-time fMRI. Nat Neurosci 9:720–729Google Scholar
  6. DeCharms RC, Christoff K, Glover G, Pauly J, Whitfield S, Gabrieli J (2004) Learned regulation of spatially localized brain activation using real-time fMRI. Neuroimage 21:436–443PubMedGoogle Scholar
  7. DeCharms RC, Maeda F, Glover GH, Ludlow D, Pauly JM, Soneji D, Gabrieli JD, Mackey SC (2005) Control over brain activation and pain learned by using realtime functional MRI. Proc Natl Acad Sci 102:18626–18631PubMedGoogle Scholar
  8. Fetz EE (2007) Volitional control of neural activity: implications for brain-computer interfaces. J Physiol 579:571–579PubMedPubMedCentralGoogle Scholar
  9. Johnston SJ, Boehm SG, Healy D, Goebel R, Linden DEJ (2010) Neurofeedback: a promising tool for the self-regulation of emotion networks. Neuroimage 49(1):1066–1072PubMedGoogle Scholar
  10. Rota G, Sitaram R, Veit R, Erb M, Weiskopf N, Dogil G, Birbaumer N (2009) Self-regulation of regional cortical activity using real-time fMRI: the right inferior frontal gyrus and linguistic processing. Hum Brain Mapp 30:1605–1614PubMedGoogle Scholar
  11. Sitaram R, Caria A, Veit R, Gaber T, Ruiz S, Birbaumer N (2014) Volitional control of the anterior insula in criminal psychopaths using real-time fMRI neurofeedback: a pilot study. Front Behav Neurosci 8:344PubMedPubMedCentralGoogle Scholar
  12. Weiskopf N, Veit R, Erb M, Mathiak K, Grodd W, Goebel R, Birbaumer N (2003) Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data. Neuroimage 19:577–586PubMedGoogle Scholar
  13. Weiskopf N, Scharnowski F, Veit R, Goebel R, Birbaumer N, Mathiak K (2004) Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI). J Physiol Paris 98:357–373PubMedGoogle Scholar
  14. Weiskopf N, Sitaram R, Josephs O, Veit R, Scharnowski F, Goebel R, Birbaumer N, Deichmann R, Mathiak K (2007) Real-time functional magnetic resonance imaging: methods and applications. Magn Reson Imaging 25:989–1003PubMedGoogle Scholar
  15. Yoo S, Jolesz FA (2002) Functional MRI for neurofeedback: feasibility study on a hand motor task. Neuroreport 13:1377–1381PubMedGoogle Scholar
  16. Yoo S, O’Leary H, Fairneny T, Chen N, Panych L, Park H, Jolesz F (2006) Increasing cortical activity in auditory areas through neurofeedback functional magnetic resonance imaging. Neuroreport 17:1273–1278PubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2020

Authors and Affiliations

  1. 1.Praxis für ErgotherapieLandauDeutschland
  2. 2.LustadtDeutschland
  3. 3.NeuroFit GmbH Therapie-und Trainings-AkademieKrefeldDeutschland
  4. 4.Praxis für Neurofeedback, Biofeedback und ErgotherapieStuttgartDeutschland
  5. 5.HeidelbergDeutschland
  6. 6.Praxis für Neurofeedback und HypnoseStuttgartDeutschland
  7. 7.LandauDeutschland

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