Literature DB >> 31983375

Efficacy of Neurofeedback Interventions for Cognitive Rehabilitation Following Brain Injury: Systematic Review and Recommendations for Future Research.

Jordan I Ali1,2, Jeremy Viczko1, Colette M Smart1,2.   

Abstract

OBJECTIVES: Interest in neurofeedback therapies (NFTs) has grown exponentially in recent years, encouraged both by escalating public interest and the financial support of health care funding agencies. Given NFTs' growing prevalence and anecdotally reported success in treating common effects of acquired brain injury (ABI), a systematic review of the efficacy of NFTs for the rehabilitation of ABI-related cognitive impairment is warranted.
METHODS: Eligible studies included adult samples (18+ years) with ABI, the use of neurofeedback technology for therapeutic purposes (as opposed to assessment), the inclusion of a meaningful control group/condition, and clear cognitive-neuropsychological outcomes. Initial automated search identified n = 86 candidate articles, however, only n = 4 studies met the stated eligibility criteria.
RESULTS: Results were inconsistent across studies and cognitive domains. Methodological and theoretical limitations precluded robust and coherent conclusions with respect to the cognitive rehabilitative properties of NFTs. We take the results of these systematic analyses as a reflection of the state of the literature at this time. These results offer a constructive platform to further discuss a number of methodological, theoretical, and ethical considerations relating to current and future NFT-ABI research and clinical intervention.
CONCLUSIONS: Given the limited quantity and quality of the available research, there appears to be insufficient evidence to comment on the efficacy of NFTs within an ABI rehabilitation context at this time. It is imperative that future work increase the level of theoretical and methodological rigour if meaningful advancements are to be made understanding and evaluating NFT-ABI applications.

Entities:  

Keywords:  Brain injuries; Brain–computer interfaces; Cognitive dysfunction; Neurofeedback; Rehabilitation; Stroke; Traumatic

Mesh:

Year:  2020        PMID: 31983375     DOI: 10.1017/S1355617719001061

Source DB:  PubMed          Journal:  J Int Neuropsychol Soc        ISSN: 1355-6177            Impact factor:   2.892


  2 in total

1.  The Frequency Effect of the Motor Imagery Brain Computer Interface Training on Cortical Response in Healthy Subjects: A Randomized Clinical Trial of Functional Near-Infrared Spectroscopy Study.

Authors:  Qiang Lin; Yanni Zhang; Yajie Zhang; Wanqi Zhuang; Biyi Zhao; Xiaomin Ke; Tingting Peng; Tingting You; Yongchun Jiang; Anniwaer Yilifate; Wei Huang; Lingying Hou; Yaoyao You; Yaping Huai; Yaxian Qiu; Yuxin Zheng; Haining Ou
Journal:  Front Neurosci       Date:  2022-03-31       Impact factor: 4.677

2.  Neurofeedback in patients with frontal brain lesions: A randomized, controlled double-blind trial.

Authors:  Christine Annaheim; Kerstin Hug; Caroline Stumm; Maya Messerli; Yves Simon; Margret Hund-Georgiadis
Journal:  Front Hum Neurosci       Date:  2022-09-15       Impact factor: 3.473

  2 in total

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