EEG-based local brain activity feedback training – tomographic neurofeedback
Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on ‘EEG-based Local Brain Activity (LBA...
Ausführliche Beschreibung
Autor*in: |
Herbert eBauer [verfasserIn] Avni ePllana [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2014 |
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Übergeordnetes Werk: |
In: Frontiers in Human Neuroscience - Frontiers Media S.A., 2008, 8(2014) |
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Übergeordnetes Werk: |
volume:8 ; year:2014 |
Links: |
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DOI / URN: |
10.3389/fnhum.2014.01005 |
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Katalog-ID: |
DOAJ002065444 |
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10.3389/fnhum.2014.01005 doi (DE-627)DOAJ002065444 (DE-599)DOAJe66fd496796d4c52898b2793fbc570d8 DE-627 ger DE-627 rakwb eng RC321-571 Herbert eBauer verfasserin aut EEG-based local brain activity feedback training – tomographic neurofeedback 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on ‘EEG-based Local Brain Activity (LBA-) feedback training’ developed by Bauer et al (2011). LBA-feedback has the advantage over other sLORETA-based approaches in the way that feedback is exclusively controlled by EEG-generating sources within a selected cortical region of training (ROT): feedback is suspended if there is no source. In this way the influence of sources in the vicinity of the ROT is excluded. First applications have yielded promising results: aiming to enhance activity in left hemispheric linguistic areas, 5 experimental subjects increased significantly the feedback rate whereas 5 controls receiving sham feedback did not, both after 13 training runs (U-test, p < 0.01). Preliminary results of another study that aims to document effects of LBA-feedback training of the ACC and DLPFC by fMRI revealed more local ACC-activity after successful training (Radke et al., 2014). sLORETA neurofeedback (NF) tomographic neurofeedback EEG-based Local Brain Activity (LBA-) feedback training rtfMRI neurofeedback Neurosciences. Biological psychiatry. Neuropsychiatry Avni ePllana verfasserin aut In Frontiers in Human Neuroscience Frontiers Media S.A., 2008 8(2014) (DE-627)56601243X (DE-600)2425477-0 16625161 nnns volume:8 year:2014 https://doi.org/10.3389/fnhum.2014.01005 kostenfrei https://doaj.org/article/e66fd496796d4c52898b2793fbc570d8 kostenfrei http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.01005/full kostenfrei https://doaj.org/toc/1662-5161 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2014 |
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10.3389/fnhum.2014.01005 doi (DE-627)DOAJ002065444 (DE-599)DOAJe66fd496796d4c52898b2793fbc570d8 DE-627 ger DE-627 rakwb eng RC321-571 Herbert eBauer verfasserin aut EEG-based local brain activity feedback training – tomographic neurofeedback 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on ‘EEG-based Local Brain Activity (LBA-) feedback training’ developed by Bauer et al (2011). LBA-feedback has the advantage over other sLORETA-based approaches in the way that feedback is exclusively controlled by EEG-generating sources within a selected cortical region of training (ROT): feedback is suspended if there is no source. In this way the influence of sources in the vicinity of the ROT is excluded. First applications have yielded promising results: aiming to enhance activity in left hemispheric linguistic areas, 5 experimental subjects increased significantly the feedback rate whereas 5 controls receiving sham feedback did not, both after 13 training runs (U-test, p < 0.01). Preliminary results of another study that aims to document effects of LBA-feedback training of the ACC and DLPFC by fMRI revealed more local ACC-activity after successful training (Radke et al., 2014). sLORETA neurofeedback (NF) tomographic neurofeedback EEG-based Local Brain Activity (LBA-) feedback training rtfMRI neurofeedback Neurosciences. Biological psychiatry. Neuropsychiatry Avni ePllana verfasserin aut In Frontiers in Human Neuroscience Frontiers Media S.A., 2008 8(2014) (DE-627)56601243X (DE-600)2425477-0 16625161 nnns volume:8 year:2014 https://doi.org/10.3389/fnhum.2014.01005 kostenfrei https://doaj.org/article/e66fd496796d4c52898b2793fbc570d8 kostenfrei http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.01005/full kostenfrei https://doaj.org/toc/1662-5161 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2014 |
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10.3389/fnhum.2014.01005 doi (DE-627)DOAJ002065444 (DE-599)DOAJe66fd496796d4c52898b2793fbc570d8 DE-627 ger DE-627 rakwb eng RC321-571 Herbert eBauer verfasserin aut EEG-based local brain activity feedback training – tomographic neurofeedback 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on ‘EEG-based Local Brain Activity (LBA-) feedback training’ developed by Bauer et al (2011). LBA-feedback has the advantage over other sLORETA-based approaches in the way that feedback is exclusively controlled by EEG-generating sources within a selected cortical region of training (ROT): feedback is suspended if there is no source. In this way the influence of sources in the vicinity of the ROT is excluded. First applications have yielded promising results: aiming to enhance activity in left hemispheric linguistic areas, 5 experimental subjects increased significantly the feedback rate whereas 5 controls receiving sham feedback did not, both after 13 training runs (U-test, p < 0.01). Preliminary results of another study that aims to document effects of LBA-feedback training of the ACC and DLPFC by fMRI revealed more local ACC-activity after successful training (Radke et al., 2014). sLORETA neurofeedback (NF) tomographic neurofeedback EEG-based Local Brain Activity (LBA-) feedback training rtfMRI neurofeedback Neurosciences. Biological psychiatry. Neuropsychiatry Avni ePllana verfasserin aut In Frontiers in Human Neuroscience Frontiers Media S.A., 2008 8(2014) (DE-627)56601243X (DE-600)2425477-0 16625161 nnns volume:8 year:2014 https://doi.org/10.3389/fnhum.2014.01005 kostenfrei https://doaj.org/article/e66fd496796d4c52898b2793fbc570d8 kostenfrei http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.01005/full kostenfrei https://doaj.org/toc/1662-5161 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2014 |
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10.3389/fnhum.2014.01005 doi (DE-627)DOAJ002065444 (DE-599)DOAJe66fd496796d4c52898b2793fbc570d8 DE-627 ger DE-627 rakwb eng RC321-571 Herbert eBauer verfasserin aut EEG-based local brain activity feedback training – tomographic neurofeedback 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on ‘EEG-based Local Brain Activity (LBA-) feedback training’ developed by Bauer et al (2011). LBA-feedback has the advantage over other sLORETA-based approaches in the way that feedback is exclusively controlled by EEG-generating sources within a selected cortical region of training (ROT): feedback is suspended if there is no source. In this way the influence of sources in the vicinity of the ROT is excluded. First applications have yielded promising results: aiming to enhance activity in left hemispheric linguistic areas, 5 experimental subjects increased significantly the feedback rate whereas 5 controls receiving sham feedback did not, both after 13 training runs (U-test, p < 0.01). Preliminary results of another study that aims to document effects of LBA-feedback training of the ACC and DLPFC by fMRI revealed more local ACC-activity after successful training (Radke et al., 2014). sLORETA neurofeedback (NF) tomographic neurofeedback EEG-based Local Brain Activity (LBA-) feedback training rtfMRI neurofeedback Neurosciences. Biological psychiatry. Neuropsychiatry Avni ePllana verfasserin aut In Frontiers in Human Neuroscience Frontiers Media S.A., 2008 8(2014) (DE-627)56601243X (DE-600)2425477-0 16625161 nnns volume:8 year:2014 https://doi.org/10.3389/fnhum.2014.01005 kostenfrei https://doaj.org/article/e66fd496796d4c52898b2793fbc570d8 kostenfrei http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.01005/full kostenfrei https://doaj.org/toc/1662-5161 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2014 |
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Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on ‘EEG-based Local Brain Activity (LBA-) feedback training’ developed by Bauer et al (2011). LBA-feedback has the advantage over other sLORETA-based approaches in the way that feedback is exclusively controlled by EEG-generating sources within a selected cortical region of training (ROT): feedback is suspended if there is no source. In this way the influence of sources in the vicinity of the ROT is excluded. First applications have yielded promising results: aiming to enhance activity in left hemispheric linguistic areas, 5 experimental subjects increased significantly the feedback rate whereas 5 controls receiving sham feedback did not, both after 13 training runs (U-test, p < 0.01). Preliminary results of another study that aims to document effects of LBA-feedback training of the ACC and DLPFC by fMRI revealed more local ACC-activity after successful training (Radke et al., 2014). |
abstractGer |
Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on ‘EEG-based Local Brain Activity (LBA-) feedback training’ developed by Bauer et al (2011). LBA-feedback has the advantage over other sLORETA-based approaches in the way that feedback is exclusively controlled by EEG-generating sources within a selected cortical region of training (ROT): feedback is suspended if there is no source. In this way the influence of sources in the vicinity of the ROT is excluded. First applications have yielded promising results: aiming to enhance activity in left hemispheric linguistic areas, 5 experimental subjects increased significantly the feedback rate whereas 5 controls receiving sham feedback did not, both after 13 training runs (U-test, p < 0.01). Preliminary results of another study that aims to document effects of LBA-feedback training of the ACC and DLPFC by fMRI revealed more local ACC-activity after successful training (Radke et al., 2014). |
abstract_unstemmed |
Along with the development of distributed EEG source modeling methods, basic approaches to local brain activity (LBA-) neurofeedback have been suggested. Meanwhile several attempts using LORETA and sLORETA have been published. This article specifically reports on ‘EEG-based Local Brain Activity (LBA-) feedback training’ developed by Bauer et al (2011). LBA-feedback has the advantage over other sLORETA-based approaches in the way that feedback is exclusively controlled by EEG-generating sources within a selected cortical region of training (ROT): feedback is suspended if there is no source. In this way the influence of sources in the vicinity of the ROT is excluded. First applications have yielded promising results: aiming to enhance activity in left hemispheric linguistic areas, 5 experimental subjects increased significantly the feedback rate whereas 5 controls receiving sham feedback did not, both after 13 training runs (U-test, p < 0.01). Preliminary results of another study that aims to document effects of LBA-feedback training of the ACC and DLPFC by fMRI revealed more local ACC-activity after successful training (Radke et al., 2014). |
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|
score |
7.3989725 |