Modulation of functional network with real-time fMRI feedback training of right premotor cortex activity

Hui, Mingqi; Zhang, Hang; Ge, Ruiyang; Yao, Li; Long, Zhiling

doi:10.1016/j.neuropsychologia.2014.07.012

Cited by 29 publications

(46 citation statements)

References 75 publications

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“…Beyond the ACC and insula, training motor areas can improve motor control in both healthy participants (Hui et al, 2014) and individuals diagnosed with Parkinson's disease (Subramanian et al, 2011); however, in the former study the control group also demonstrated improved finger-tapping speed while the latter experiment used no sham-feedback control condition. Altering prefrontal blood flow can improve detection of emotional prosodic intonations (Rota et al, 2009) and verbal working memory ; however, again, the latter experiment demonstrated that sham-neurofeedback enhanced performance on four of the five working memory tasks, even while impairing the ability of participants to modulate target brain regions.…”

Section: Fmrimentioning

confidence: 88%

“…Whereas EEG-nf requires many sessions to alter electrical activity, with rtfMRI-nf individuals can selectively modify fMRI BOLD signal within 30 minutes of training and sometimes even sooner (Brühl et al, 2014;Canterberry et al, 2013;Greer, Trujillo, Glover, & Knutson, 2014;Gröne et al, 2015;Hui, Zhang, Ge, Yao, & Long, 2014;Lawrence et al, 2014;Paret et al, 2014;. This striking difference between EEG-nf and rtfMRI-nf deserves further discussion.…”

Section: Fmrimentioning

confidence: 99%

“…Out of over 70 published rtfMRI-nf studies, very few reported that participants were unable to modulate brain hemodynamics (Berman, Horovitz, Venkataraman, & Hallett, 2011;Hampson et al, 2011). Other experiments using rtfMRI-nf, using sham-feedback as control, demonstrated that participants increased their ability to modulate a particular brain region throughout training Caria, Sitaram, Veit, Begliomini, & Birbaumer, 2010;Chiew, Laconte, & Graham, 2012;Hui et al, 2014;Lawrence et al, 2014;McCaig, Dixon, Keramatian, Liu, & Christoff, 2011;Rota et al, 2009;Rota, Handjaras, Sitaram, Birbaumer, & Dogil, 2011;Yoo, Lee, O'Leary, Panych, & Jolesz, 2008;Young et al, 2014;Zotev, Phillips, Young, Drevets, & Bodurka, 2013;Zotev et al, 2011). Many other studies often lacked necessary controls or appropriate analyses to determine that veritable neurofeedback was the primary factor accounting for the observed brain alterations (Thibault et al, 2015); Figure 2 depicts some common control conditions.…”

Section: Fmrimentioning

confidence: 99%

“…One study reported a link connecting functional connectivity, rtfMRI-nf, and behavior (Hui et al, 2014). Compared to sham-feedback controls, veritable neurofeedback altered brain connectivity in experimental participants: they improved their ability to modulate the premotor cortex and increased finger tapping speed (Hui et al, 2014).…”

Section: Functional Connectivitymentioning

confidence: 99%

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

Thibault

Lifshitz

Raz

2016

Cortex

206

198

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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.

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Section: Fmrimentioning

confidence: 88%

Section: Fmrimentioning

confidence: 99%

Section: Fmrimentioning

confidence: 99%

Section: Functional Connectivitymentioning

confidence: 99%

See 2 more Smart Citations

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

Thibault

Lifshitz

Raz

2016

Cortex

206

198

View full text Add to dashboard Cite

show abstract

“…The uses of NF are diverse, ranging across a variety of motor and sensory tasks (1)(2)(3)(4), investigation of cortical plasticity and attention (5)(6)(7)(8)(9), to treatment of chronic pain, depression, and mood control (10)(11)(12)(13).…”

mentioning

confidence: 99%

Covert neurofeedback without awareness shapes cortical network spontaneous connectivity

Ramot

Grossman

Friedman

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Recent advances in blood oxygen level-dependent-functional MRI (BOLD-fMRI)-based neurofeedback reveal that participants can modulate neuronal properties. However, it is unknown whether such training effects can be introduced in the absence of participants' awareness that they are being trained. Here, we show unconscious neurofeedback training, which consequently produced changes in functional connectivity, introduced in participants who received positive and negative rewards that were covertly coupled to activity in two category-selective visual cortex regions. The results indicate that brain networks can be modified even in the complete absence of intention and awareness of the learning situation, raising intriguing possibilities for clinical interventions.neurofeedback | training | reward | spontaneous activity | functional connectivity T here has been a growing interest in the field of neuroscience in the use of neurofeedback (NF) as a tool to both study and treat various clinical conditions. The uses of NF are diverse, ranging across a variety of motor and sensory tasks (1-4), investigation of cortical plasticity and attention (5-9), to treatment of chronic pain, depression, and mood control (10-13).Recent advances in functional MRI (fMRI) techniques and hardware have made real-time fMRI (rtfMRI) a viable method for NF (14). This enables more anatomically specific training compared with methods such as EEG. This enhanced localization additionally allows to provide feedback to differential activation patterns (6, 15, 16), beyond simple up/down-regulation of a specific region/frequency.Another advance in the field of NF is the finding by several recent studies that participants are able to learn to successfully perform the NF paradigm, even without being given an explicit strategy (8,16). This form of implicit learning is intriguing, both because there have been reports indicating certain advantages to implicit over explicit learning (17,18), but mostly because this opens up previously unidentified pathways for therapeutic intervention, for cases for which there are no specific explicit strategies available (for instance, control over complex networks, such as in epilepsy, or over brain regions whose function is not fully elucidated).However, an important common factor in all previous NF studies was the fact that participants were aware that they were being trained, and received specific goals for this training. A fundamental question that therefore remains unanswered is whether targeted brain networks can still be modulated even in the complete absence of participants' awareness that a training process is taking place. Theories of closed-loop learning provide evidence that such implicit learning through reward cues is possible (19,20). This is an important issue, because it may open the way for NF training even in severe clinical cases such as minimally conscious or vegetative state, where such awareness is absent.In the present study, we examined this question in fMRI experiments in which participants were i...

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The Spiritual Brain: Science and Religious Experience

Newberg

2017

The Physics of the Mind and Brain Disorders

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Modulation of functional network with real-time fMRI feedback training of right premotor cortex activity

Cited by 29 publications

References 75 publications

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

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

Covert neurofeedback without awareness shapes cortical network spontaneous connectivity

The Spiritual Brain: Science and Religious Experience

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