Limbic Activity Modulation Guided by Functional Magnetic Resonance Imaging–Inspired Electroencephalography Improves Implicit Emotion Regulation

Keynan, Jackob Nimrod; Meir-Hasson, Yehudit; Gilam, Gadi; Cohen, Avihay; Jackont, Gilan; Kinreich, Sivan; Ikar, Limor; Or-Borichev, Ayelet; Etkin, Amit; Gyurak, Anett; Klovatch, Ilana; Intrator, Nathan; Hendler, Talma

doi:10.1016/j.biopsych.2015.12.024

Cited by 93 publications

(110 citation statements)

References 26 publications

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“…For example, one study trained participants on less expensive, portable EEG after initially calibrating the location of the signal with spatially precise fMRI of the amygdala 26 (this approach is innovative, as EEG by itself cannot determine where activation occurs in deeper brain regions such as the amygdala). The participants downregulated the EEG correlates of amygdala blood-oxygenlevel-dependent (BOLD) activation in the presence of visual stimuli.…”

Section: Coherencementioning

confidence: 99%

Closed-loop brain training: the science of neurofeedback

et al. 2016

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Section: Coherencementioning

confidence: 99%

Closed-loop brain training: the science of neurofeedback

et al. 2016

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“…If rtfMRI‐NF proves to be a successful treatment for ADHD, it could also be transferred to the cheaper NIRS‐NF which has already been piloted in ADHD [Marx et al, 2014] or to fMRI‐inspired EEG‐NF methods, which use concurrent fMRI‐EEG‐NF to establish the EEG correlates of localized fMRI BOLD activity for a better spatially informed EEG‐NF [Keynan et al, 2016; Meir‐Hasson et al, 2016]. …”

Section: Discussionmentioning

confidence: 99%

Real‐time fMRI neurofeedback in adolescents with attention deficit hyperactivity disorder

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Wulff

Brinson

et al. 2017

Human Brain Mapping

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Attention Deficit Hyperactivity Disorder (ADHD) is associated with poor self‐control, underpinned by inferior fronto‐striatal deficits. Real‐time functional magnetic resonance neurofeedback (rtfMRI‐NF) allows participants to gain self‐control over dysregulated brain regions. Despite evidence for beneficial effects of electrophysiological‐NF on ADHD symptoms, no study has applied the spatially superior rtfMRI‐NF neurotherapy to ADHD. A randomized controlled trial tested the efficacy of rtfMRI‐NF of right inferior prefrontal cortex (rIFG), a key region that is compromised in ADHD and upregulated with psychostimulants, on improvement of ADHD symptoms, cognition, and inhibitory fMRI activation. To control for region‐specificity, an active control group received rtfMRI‐NF of the left parahippocampal gyrus (lPHG). Thirty‐one ADHD boys were randomly allocated and had to learn to upregulate their target brain region in an average of 11 rtfMRI‐NF runs over 2 weeks. Feedback was provided through a video‐clip of a rocket that had to be moved up into space. A transfer session without feedback tested learning retention as a proximal measure of transfer to everyday life. Both NF groups showed significant linear activation increases with increasing number of runs in their respective target regions and significant reduction in ADHD symptoms after neurotherapy and at 11‐month follow‐up. Only the group targeting rIFG, however, showed a transfer effect, which correlated with ADHD symptom reductions, improved at trend level in sustained attention, and showed increased IFG activation during an inhibitory fMRI task. This proof‐of‐concept study demonstrates for the first time feasibility, safety, and shorter‐ and longer‐term efficacy of rtfMRI‐NF of rIFG in adolescents with ADHD. Hum Brain Mapp 38:3190–3209, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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“…EEG data recorded from electrode Pz at a given time-point is multiplied by the coefficient matrix to produce the predicted amygdala fMRI-BOLD activity at this point. Keynan et al (2016) validated the reliability of the amyg-EFP in predicting amygdala BOLD activity by conducting further simultaneous EEG-fMRI recordings using a new sample not originally used to develop the model. For further specification, see Meir-Hasson et al (2014 and Keynan et al (2016).…”

Section: The Amyg-efp Modelmentioning

confidence: 99%

“…NF training in the current work targeted downregulation of limbic activity using a novel fMRI-inspired EEG model termed the "amygdala electrical finger print" (amyg-EFP). The amyg-EFP was recently developed in our laboratory to enable accessible limbic targeted NF by applying advanced machine learning algorithms on EEG data acquired simultaneously with fMRI (Meir-Hasson et al, 2014Keynan et al, 2016). We examined whether relative to a standard 2D TM visualization, learning via an interface of complex multi-modal 3D scenario will result in a more effective NF learning as measured by three parameters: (a) learning effect size (b) sustainability, and (c) transferability.…”

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confidence: 99%

“…The introduction of real-time functional magnetic resonance imaging (rt-fMRI) has generated a growing interest in the clinical and behavioral benefits of the procedure, as it made it possible to target specific anatomical areas, including subcortical regions, such as the amygdala (Johnston et al, 2010). The majority of the research done so far, particularly in fMRI-NF, focused in proving the feasibility of learning to volitionally regulate localized brain activity in different areas (Hamilton et al, 2011;McCaig et al, 2011;Zotev et al, 2011;Lawrence et al, 2014;MacInnes et al, 2016) with some also showing behavioral changes following the NF procedure (Scheinost et al, 2013;Young et al, 2014;Keynan et al, 2016). While importantly proving that individuals can obtain volitional regulation of local blood oxygen level-dependent (BOLD) activity, the research so far has paid little attention to substantial theoretical aspects regarding the learning mechanisms underlying NF training (Sulzer et al, 2013a,b;Thibault et al, 2016).…”

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Multi-modal Virtual Scenario Enhances Neurofeedback Learning

et al. 2016

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In the past decade neurofeedback (NF) has become the focus of a growing body of research. With real-time functional magnetic resonance imaging (fMRI) enabling online monitoring of emotion-related areas, such as the amygdala, many have begun testing its therapeutic benefits. However, most existing NF procedures still use monotonic unimodal interfaces, thus possibly limiting user engagement and weakening learning efficiency. The current study tested a novel multi-sensory NF animated scenario (AS) aimed at enhancing user experience and improving learning. We examined whether relative to a simple uni-modal 2D interface, learning via an interface of complex multi-modal 3D scenario will result in improved NF learning. As a neural-probe, we used the recently developed fMRI-inspired EEG model of amygdala activity ("amygdala-EEG finger print"; amygdala-EFP), enabling low-cost and mobile limbic NF training. Amygdala-EFP was reflected in the AS by the unrest level of a hospital waiting room in which virtual characters become impatient, approach the admission desk and complain loudly. Successful downregulation was reflected as an ease in the room unrest level. We tested whether relative to a standard uni-modal 2D graphic thermometer (TM) interface, this AS could facilitate more effective learning and improve the training experience. Thirty participants underwent two separated NF sessions (1 week apart) practicing downregulation of the amygdala-EFP signal. In the first session, half trained via the AS and half via a TM interface. Learning efficiency was tested by three parameters: (a) effect size of the change in amygdala-EFP following training, (b) sustainability of the learned downregulation in the absence of online feedback, and (c) transferability to an unfamiliar context. Comparing amygdala-EFP signal amplitude between the last and the first NF trials revealed that the AS produced a higher effect size. In addition, NF via the AS showed better sustainability, as indicated by a no-feedback trial conducted in session 2 and better transferability to a new unfamiliar interface. Lastly, participants reported that the AS was more engaging and more motivating than the TM. Together, these results demonstrate the promising potential of integrating realistic virtual environments in NF to enhance learning and improve user's experience.

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Limbic Activity Modulation Guided by Functional Magnetic Resonance Imaging–Inspired Electroencephalography Improves Implicit Emotion Regulation

Cited by 93 publications

References 26 publications

Closed-loop brain training: the science of neurofeedback

Closed-loop brain training: the science of neurofeedback

Real‐time fMRI neurofeedback in adolescents with attention deficit hyperactivity disorder

Multi-modal Virtual Scenario Enhances Neurofeedback Learning

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