FRIEND Engine Framework: a real time neurofeedback client-server system for neuroimaging studies

Basílio, Rodrigo; Garrido, Griselda J.; Sato, João Ricardo; Hoefle, Sebastian; Melo, Bruno; Pamplona, Fabrício A.; Zahn, Roland; Moll, Jorge

doi:10.3389/fnbeh.2015.00003

Cited by 13 publications

(19 citation statements)

References 22 publications

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“…Our study employed a freely available rt-fMRI software (FRIEND 6 ; Sato et al, 2013 ; Basilio et al, 2015 ). This may contribute for expansion of the NFB fMRI use and allow a better comparability across studies, which is fundamental for future applications in clinical research.…”

Section: Discussionmentioning

confidence: 99%

“…During MI (“GO” blocks), participants received either real NFB or random visual stimuli. Continuous online neurofeedback data was performed using FRIEND (Functional Real-time Interactive Endogenous Neuromodulation and Decoding) toolbox 1 ( Sato et al, 2013 ; Basilio et al, 2015 ), which is a home-built toolbox for fMRI NFB. First, a linear registration between the EPI image (RFI) and a MNI template brain was obtained.…”

Section: Methodsmentioning

confidence: 99%

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Enhancing Motor Network Activity Using Real-Time Functional MRI Neurofeedback of Left Premotor Cortex

Marins

Rodrigues

Engel

et al. 2015

Front. Behav. Neurosci.

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Neurofeedback by functional magnetic resonance imaging (fMRI) is a technique of potential therapeutic relevance that allows individuals to be aware of their own neurophysiological responses and to voluntarily modulate the activity of specific brain regions, such as the premotor cortex (PMC), important for motor recovery after brain injury. We investigated (i) whether healthy human volunteers are able to up-regulate the activity of the left PMC during a right hand finger tapping motor imagery (MI) task while receiving continuous fMRI-neurofeedback, and (ii) whether successful modulation of brain activity influenced non-targeted motor control regions. During the MI task, participants of the neurofeedback group (NFB) received ongoing visual feedback representing the level of fMRI responses within their left PMC. Control (CTL) group participants were shown similar visual stimuli, but these were non-contingent on brain activity. Both groups showed equivalent levels of behavioral ratings on arousal and MI, before and during the fMRI protocol. In the NFB, but not in CLT group, brain activation during the last run compared to the first run revealed increased activation in the left PMC. In addition, the NFB group showed increased activation in motor control regions extending beyond the left PMC target area, including the supplementary motor area, basal ganglia and cerebellum. Moreover, in the last run, the NFB group showed stronger activation in the left PMC/inferior frontal gyrus when compared to the CTL group. Our results indicate that modulation of PMC and associated motor control areas can be achieved during a single neurofeedback-fMRI session. These results contribute to a better understanding of the underlying mechanisms of MI-based neurofeedback training, with direct implications for rehabilitation strategies in severe brain disorders, such as stroke.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Enhancing Motor Network Activity Using Real-Time Functional MRI Neurofeedback of Left Premotor Cortex

Marins

Rodrigues

Engel

et al. 2015

Front. Behav. Neurosci.

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“…html; Weiskopf et al, 2004), a BioImageSuite extension (bisweb. yale.edu; Scheinost et al, 2013a), a FSL based toolbox, FRIEND (nitrc.org/projects/friend/; Sato et al, 2013;Basilio et al, 2015), and an SPM/Matlab based toolbox OpenNFT (opennft.org; Koush et al, 2017). Many groups use custom implementations or extensions of these toolboxes and plugins.…”

Section: Artifacts and Technical Problemsmentioning

confidence: 99%

A Guide to Literature Informed Decisions in the Design of Real Time fMRI Neurofeedback Studies: A Systematic Review

Fede

Dean

Manuweera

et al. 2020

Front. Hum. Neurosci.

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Background: Although biofeedback using electrophysiology has been explored extensively, the approach of using neurofeedback corresponding to hemodynamic response is a relatively young field. Real time functional magnetic resonance imaging-based neurofeedback (rt-fMRI-NF) uses sensory feedback to operantly reinforce patterns of neural response. It can be used, for example, to alter visual perception, increase brain connectivity, and reduce depression symptoms. Within recent years, interest in rt-fMRI-NF in both research and clinical contexts has expanded considerably. As such, building a consensus regarding best practices is of great value. Objective: This systematic review is designed to describe and evaluate the variations in methodology used in previous rt-fMRI-NF studies to provide recommendations for rt-fMRI-NF study designs that are mostly likely to elicit reproducible and consistent effects of neurofeedback. Methods: We conducted a database search for fMRI neurofeedback papers published prior to September 26th, 2019. Of 558 studies identified, 146 met criteria for inclusion. The following information was collected from each study: sample size and type, task used, neurofeedback calculation, regulation procedure, feedback, whether feedback was explicitly related to changing brain activity, feedback timing, control group for active neurofeedback, how many runs and sessions of neurofeedback, if a follow-up was conducted, and the results of neurofeedback training. Results: rt-fMRI-NF is typically upregulation practice based on hemodynamic response from a specific region of the brain presented using a continually updating thermometer display. Most rt-fMRI-NF studies are conducted in healthy samples and half evaluate its effect on immediate changes in behavior or affect. The most popular control group method is to provide sham signal from another region; however, many studies do not compare use a comparison group. Conclusions: We make several suggestions for designs of future rt-fMRI-NF studies. Researchers should use feedback calculation methods that consider neural response across regions (i.e., SVM or connectivity), which should be conveyed as intermittent, Fede et al. Neurofeedback Guide auditory feedback. Participants should be given explicit instructions and should be assessed on individual differences. Future rt-fMRI-NF studies should use clinical samples; effectiveness of rt-fMRI-NF should be evaluated on clinical/behavioral outcomes at follow-up time points in comparison to both a sham and no feedback control group.

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“…the spiral-in/out sequence by Glover and Law, 2001), only 1 study from the 128 reported incorporating postacquisition distortion correction into their real-time algorithm (Marxen et al, 2016). Although open source software solutions like AFNI's real-time plugin (Cox et al 1995), BART (Hellrung et al, 2015), FRIEND (Basilio et al, 2015) and OpenNFT counter some of these concerns, we find additionally that minimal evidence exists for open data and methods sharing. Specifically, apart from a large dataset on default-modenetwork neurofeedback shared publicly by McDonald et al 2017, and further useful supplementary data shared in some cases (e.g.…”

Section: Denoising In Real-time Fmri Neurofeedback Studiesmentioning

confidence: 81%

“…Most other rtfMRI-NF toolboxes or custom software implementations allow some form of 3D volume realignment, e.g. OpenNFT which uses a faster version of SPM12's spm_realign routine (SPM, www.fil.ion.ucl.ac.uk/spm), or FRIEND (Basilio et al, 2015) that incorporates FSL's MCFLIRT algorithm (FSL, https://fsl.fmrib.ox.ac.uk/fsl).…”

Section: D Volume Realignmentmentioning

confidence: 99%

Quality and denoising in real-time fMRI neurofeedback: a methods review

Heunis¹,

Lamerichs²,

Zinger³

et al. 2018

Preprint

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Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localized and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. Maximization of neurofeedback learning effects in accordance with operant conditioning requires the feedback signal to be closely contingent on real brain activity, which necessitates the use of effective real-time fMRI denoising methods to prevent sham feedback. In this work, we present the first extensive review of acquisition, data processing and quality reporting methods available to improve the quality of the rtfMRI neurofeedback signal. Furthermore, we investigated the state of denoising and quality control practices in a set of 128 recently published rtfMRI-NF studies. We found: (i) that less than a third of the studies reported implementing standard real-time fMRI denoising steps; (ii) significant room for improvement with regards to methods reporting; and (iii) the need for methodological studies quantifying and comparing the contribution of denoising steps to the quality of the neurofeedback signal. Advances in the field of rtfMRI-NF research depend on reproducibility of methods and results. To this end, we recommend that future rtfMRI-NF studies: (i) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (https://osf.io/kjwhf/); (ii) ensure the quality of the neurofeedback signal by calculating and reporting community-informed quality metrics and applying offline control checks; and (iii) strive to adopt transparent principles in the form of methods and data sharing and the support of open-source rtfMRI-NF software.

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FRIEND Engine Framework: a real time neurofeedback client-server system for neuroimaging studies

Cited by 13 publications

References 22 publications

Enhancing Motor Network Activity Using Real-Time Functional MRI Neurofeedback of Left Premotor Cortex

Enhancing Motor Network Activity Using Real-Time Functional MRI Neurofeedback of Left Premotor Cortex

A Guide to Literature Informed Decisions in the Design of Real Time fMRI Neurofeedback Studies: A Systematic Review

Quality and denoising in real-time fMRI neurofeedback: a methods review

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