Research Article
Measuring the Gamma Band Entropy Variance is a Novel Method to Compare the Efficacy of Neurofeedback in the Left Temporal Region and in The Right Temporal Region For Dyslexia: Pilot Study
Abstract
Background/aim: The smartphone application called Auto Train Brain aims to improve reading comprehension and speed for people with dyslexia through neurofeedback. Clinical trials have been conducted to examine the efficacy of neurofeedback on dyslexia. However, accurately measuring long-term outcomes with rapidly changing EEG data can be challenging without the use of psychometric tests. To overcome this issue, a novel measurement method was developed using the sample entropy variance calculated in the gamma band to compare different sessions.
Materials and methods: 40 children with dyslexia aged 7 to 10 consisted of the experimental group that was randomly assigned and they used Auto Train Brain for six months.
Results: Results of the study showed that after 100 sessions, the 14-channel neurofeedback with Auto Train Brain was more effective in increasing the gamma band entropy variance in the left temporal lobe (T7) compared to that of the right temporal lobe (T8).
Conclusion: Using the measurement of gamma band entropy variance was identified as a suitable approach to assess the success of neurofeedback.
Keywords: Neurofeedback, sample entropy, Auto Train Brain, learning disorders, dyslexia, EEG.
References
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Year 2024,
, 342 - 348, 01.10.2024
Abstract
References
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- 3. Francks C, MacPhie IL, et al. The genetic basis of dyslexia. The Lancet Neurology. 2002; 1(8): 483-490.
- 4. Van Bergen E, De Jong, PF, Plakas, A, et al. Child and parental literacy levels within families with a history of dyslexia. Journal of Child Psychology and Psychiatry. 2012; 53(1): 28-36.
- 5. Kuhl U, Neef NE, Kraft I, et al. The emergence of dyslexia in the developing brain. Neuroimage. 2020 May 1;211:116633.
- 6. McDougall S, Hulme C, Ellis A, et al. Learning to read: The role of short-term memory and phonological skills. Journal of experimental child psychology. 1994 Aug 1;58(1):112-33.
- 7. Paulesu E, Frith U, Snowling M, et al. Is developmental dyslexia a disconnection syndrome? Evidence from PET scanning. Brain. 1996 Feb 1;119(1):143-57.
- 8. Sowell ER, Peterson BS, Thompson PM, et al. Mapping cortical change across the human life span. Nature neuroscience. 2003 Mar 1;6(3):309-15.
- 9. Schulte-Körne G, Bruder J. Clinical neurophysiology of visual and auditory processing in dyslexia: A review. Clinical neurophysiology. 2010 Nov 1;121(11):1794-809.
- 10. Klimesch W, Doppelmayr M, Yonelinas A, et al. Theta synchronization during episodic retrieval: neural correlates of conscious awareness. Cognitive Brain Research. 2001 Aug 1;12(1):33-8.
- 11. Rippon G, Brunswick N. Trait and state EEG indices of information processing in developmental dyslexia. International Journal of Psychophysiology. 2000 Jun 1;36(3):251-65.
- 12. Arns M, Peters S, Breteler R, et al. Different brain activation patterns in dyslexic children: evidence from EEG power and coherence patterns for the double-deficit theory of dyslexia. Journal of integrative neuroscience. 2007 Mar;6(01):175-90.
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- 20. Wing K. Effect of neurofeedback on motor recovery of a patient with brain injury: A case study and its implications for stroke rehabilitation. Topics in stroke rehabilitation. 2001 Oct 1;8(3):45-53.
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- 27. Wu Y, Feng G, Yan X, et al. Reduced pattern similarity in brain activation during orthographic processing in children with developmental dyslexia. Brain and Language. 2022 Dec 1;235:105201.
- 28. Nazari MA, Mosanezhad E, Hashemi T, et al. The effectiveness of neurofeedback training on EEG coherence and neuropsychological functions in children with reading disability. Clinical EEG and neuroscience. 2012 Oct;43(4):315-22.
- 29. Coben R, Wright EK, Decker SL, et al. The impact of coherence neurofeedback on reading delays in learning disabled children: A randomized controlled study. NeuroRegulation. 2015 Dec 8;2(4):168-.
There are 29 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Neurology and Neuromuscular Diseases |
| Journal Section | Research Articles |
| Authors | |
| Early Pub Date | September 17, 2024 |
| Publication Date | October 1, 2024 |
| Submission Date | April 11, 2023 |
| Published in Issue | Year 2024 |