What is Neurofeedback: An Update

Hammond, D. Corydon

doi:10.1080/10874208.2011.623090

Cited by 211 publications

(196 citation statements)

References 239 publications

(229 reference statements)

Supporting

Mentioning

172

Contrasting

Unclassified

Order By: Relevance

“…Beyond EEG-nf, the advent of new technologies for imaging the living human brain has vastly expanded the scope of neurofeedback, which today includes more novel methods such as functional magnetic resonance imaging (fMRI), functional near infrared spectroscopy (fNIRS), and magnetoencephalography (MEG) (TIMELINE and Table 1). Thus, current-day neurofeedback draws on diverse imaging methods to help drive volitional control over electromagnetic and hemodynamic alterations in brain activity (Cannon, 2015;Hammond, 2011;Thibault, Lifshitz, Birbaumer, & Raz, 2015). Within each imaging modality, moreover, researchers have developed distinct neurofeedback protocols that target different brain signals and their concomitant physiological processes (Hammond, 2011;Sulzer, Haller, et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…While EEG-nf proponents purport to effectively treat a range of psychological and neurological disorders (Arns, Heinrich, & Strehl, 2014;Cannon, 2015;Hammond, 2011;Tan et al, 2009), it appears that influences other than the feedback itself bring about improvements in clinical endpoints across a range of disorders (Thibault, Lifshitz, Birbaumer, et al, 2015). For example, in the most researched application of EEG-nf -treatment of attention deficit hyperactivity disorder (ADHD) -all double-blind (Arnold et al, 2013;Lansbergen et al, 2011;Vollebregt, van Dongen-Boomsma, Buitelaar, et al, 2014), and multiple single-blind (PerreauLinck et al, 2010;Van Dongen-Boomsma et al, 2013), sham-controlled studies demonstrate comparable clinical outcomes in patients receiving veritable-feedback compared with shamfeedback.…”

Section: Introductionmentioning

confidence: 99%

“…A number of reviews and meta-analyses have addressed the literature regarding EEG-nf treatment for ADHD (Arns et al, 2014;Arns, Ridder, & Strehl, 2009;Lofthouse et al, 2012;Sonuga-Barke et al, 2013), epilepsy (Tan et al, 2009), depression and anxiety (Hammond, 2005), Parkinson's disease (Esmail & Linden, 2014), and a slew of other disorders (Hammond, 2011). Some of these accounts highlight the dearth of convincing evidence (Esmail & Linden, 2014;Lofthouse et al, 2012;Sonuga-Barke et al, 2013) while others rely on single-blinding, subpar control groups, non-peer-reviewed publications, and case studies to support EEG-nf (see Thibault et al, 2015 for a more in-depth exposition).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The self-regulating brain and neurofeedback: Experimental science and clinical promise

Thibault

Lifshitz

Raz

2016

Cortex

198

View full text Add to dashboard Cite

Neurofeedback, one of the primary examples of self-regulation, designates a collection of techniques that train the brain and help to improve its function. Since coming on the scene in the 1960s, electroencephalography-neurofeedback has become a treatment vehicle for a host of mental disorders; however, its clinical effectiveness remains controversial. Modern imaging technologies of the living human brain (e.g., real-time functional magnetic resonance imaging) and increasingly rigorous research protocols that utilize such methodologies begin to shed light on the underlying mechanisms that may facilitate more effective clinical applications. In this paper we focus on recent technological advances in the field of human brain imaging and discuss how these modern methods may influence the field of neurofeedback. Toward this end, we outline the state of the evidence and sketch out future directions to further explore the potential merits of this contentious therapeutic prospect.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The self-regulating brain and neurofeedback: Experimental science and clinical promise

Thibault

Lifshitz

Raz

2016

Cortex

198

View full text Add to dashboard Cite

show abstract

“…Neurofeedback is a brainwave biofeedback technique (Hammond, 2011) based onoperant conditioning that might be a promising treatment tool to regulate brain plasticity in a natural, non-invasive and painless way (Ros et al, 2010) but it is not widely accepted due to its limited use (Dehghani-Arani et al, 2013). Demos (2005) defined neurofeedback as a therapeutic method that is designed for mind and body optimal training resulting in cognitive, physical, emotional and behavioral improvement.…”

Section: Future Outlookmentioning

confidence: 99%

Resting-state Abnormalities in Heroin-dependent Individuals

Pandria

Kovatsi

Vivas³

et al. 2018

Neuroscience

View full text Add to dashboard Cite

Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) eprints@whiterose.ac.uk https://eprints.whiterose.ac.uk/ Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. AbstractDrug addiction is a major health problem worldwide. Recent neuroimaging studies have shed light into the underlying mechanisms of drug addiction as well as its consequences to the human brain. The most vulnerable, to heroin addiction, brain regions have been reported to be specific regions in the prefrontal, parietal, occipital, and temporal lobes, as well as, some subcortical regions.The brain regions involvedare linked with reward, motivation/drive, memory/learning, inhibition as well as emotional control andseem to form circuitsthat interact with each other. So, along with neuroimaging studies, recent advances in resting-state dynamics might allow further assessments upon the multilayer complexity of addiction. In the current manuscript, we comprehensively reviewand discuss all the existing resting-state neuroimaging findings classified into three overlapping and interconnected groups: functional connectivity alterations, structural deficits and abnormal topological properties. Moreover, behavioral traits of heroin-addicted individuals as well as the limitations of the currently available studies are also reviewed. Finally, in need of a contemporary therapya multimodal therapeutic approach is suggested using classical treatment practices along with current neurotechonologies, such as neurofeedback and goal-oriented video-games Keywords:Heroin addiction, resting-state, functional and structural connectivity, small-world properties, behavioral traits of heroin-dependent individuals. Radial Diffusivity (RD) 5 Drug addiction or substance dependence (Koob and Le Moal, 2005)is defined as a multifaceted neuropsychiatric disorder resulting from complex interactions between neurobiological, environmental, genetic and pharmacological variables (Sutherland et al., 2012).It affects both cognitive as well as emotional processes . Furthermore, the compulsive seeking and taking of the drug despite the negative consequences, (including downward social mobility (Denier et al., 2013b)), constitutes its behavioral phenotype (Volkow ...

show abstract

“…Since this initial exploratory and applied research, a plethora of research ranging from single-subject design studies to meta-analyses reported the efficacy and the effectiveness of NFB for psychological and physiological disorders. Yucha and Montgomery (2008) presented a framework and findings for evidence-based NFB, whereas Hammond (2011) provided a NFB description and a review of NFB research findings. Despite these research advancements, exploration of NFB practitioner variables influencing outcomes is still in a nascent phase.…”

Section: Introductionmentioning

confidence: 99%