Literature DB >> 10378738

Negative potential shifts and the prediction of the outcome of neurofeedback therapy in epilepsy.

B Kotchoubey1, U Strehl, S Holzapfel, V Blankenhorn, W Fröscher, N Birbaumer.   

Abstract

About two-thirds of epilepsy patients who learn to control their slow cortical potential shifts (SCP) reduce their seizure rate, but the remaining third does not demonstrate clinical improvement. In the present study, this finding was replicated in a group of 27 patients with focal epilepsy. We found that patients who consistently produced larger negative SCP in all conditions during the first phase of treatment, showed no decrease in seizure frequency during the six-month follow-up, as compared with the three-month baseline phase. The large negative SCP explained about one-third of the variance of the clinical outcome. Age, medication, seizure history, or the localization of focus were found to be unrelated to clinical improvement.

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Year:  1999        PMID: 10378738     DOI: 10.1016/s1388-2457(99)00005-x

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  11 in total

Review 1.  Biofeedback and epilepsy.

Authors:  Yoko Nagai
Journal:  Curr Neurol Neurosci Rep       Date:  2011-08       Impact factor: 5.081

2.  [Neurofeedback-based EEG alpha and EEG beta training. Effectiveness in patients with chronically decompensated tinnitus].

Authors:  S Schenk; K Lamm; H Gündel; K-H Ladwig
Journal:  HNO       Date:  2005-01       Impact factor: 1.284

3.  A multimodal brain-based feedback and communication system.

Authors:  Thilo Hinterberger; Nicola Neumann; Mirko Pham; Andrea Kübler; Anke Grether; Nadine Hofmayer; Barbara Wilhelm; Herta Flor; Niels Birbaumer
Journal:  Exp Brain Res       Date:  2003-11-29       Impact factor: 1.972

4.  Learning to modulate one's own brain activity: the effect of spontaneous mental strategies.

Authors:  Silvia E Kober; Matthias Witte; Manuel Ninaus; Christa Neuper; Guilherme Wood
Journal:  Front Hum Neurosci       Date:  2013-10-18       Impact factor: 3.169

5.  The morphology of midcingulate cortex predicts frontal-midline theta neurofeedback success.

Authors:  Stefanie Enriquez-Geppert; René J Huster; Robert Scharfenort; Zacharais N Mokom; Johannes Vosskuhl; Christian Figge; Jörg Zimmermann; Christoph S Herrmann
Journal:  Front Hum Neurosci       Date:  2013-08-09       Impact factor: 3.169

Review 6.  Are treatment effects of neurofeedback training in children with ADHD related to the successful regulation of brain activity? A review on the learning of regulation of brain activity and a contribution to the discussion on specificity.

Authors:  Agnieszka Zuberer; Daniel Brandeis; Renate Drechsler
Journal:  Front Hum Neurosci       Date:  2015-03-27       Impact factor: 3.169

Review 7.  Assessing the Effectiveness of Neurofeedback Training in the Context of Clinical and Social Neuroscience.

Authors:  Franklin Orndorff-Plunkett; Fiza Singh; Oriana R Aragón; Jaime A Pineda
Journal:  Brain Sci       Date:  2017-08-07

8.  Neurofunctional and behavioural measures associated with fMRI-neurofeedback learning in adolescents with Attention-Deficit/Hyperactivity Disorder.

Authors:  Sheut-Ling Lam; Marion Criaud; Analucia Alegria; Gareth J Barker; Vincent Giampietro; Katya Rubia
Journal:  Neuroimage Clin       Date:  2020-05-26       Impact factor: 4.881

9.  Resting and Initial Beta Amplitudes Predict Learning Ability in Beta/Theta Ratio Neurofeedback Training in Healthy Young Adults.

Authors:  Wenya Nan; Feng Wan; Mang I Vai; Agostinho C Da Rosa
Journal:  Front Hum Neurosci       Date:  2015-12-21       Impact factor: 3.169

10.  Resting alpha activity predicts learning ability in alpha neurofeedback.

Authors:  Feng Wan; Wenya Nan; Mang I Vai; Agostinho Rosa
Journal:  Front Hum Neurosci       Date:  2014-07-14       Impact factor: 3.169

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