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Learning Personal Representations from fMRI by Predicting Neurofeedback Performance [chapter]

Jhonathan Osin, Lior Wolf, Guy Gurevitch, Jackob Nimrod Keynan, Tom Fruchtman-Steinbok, Ayelet Or-Borichev, Talma Hendler
2020 Lecture Notes in Computer Science  
Moreover, this personal representation, learned solely from fMRI images, yields good performance in linear prediction of psychiatric traits, which is better than performing such a prediction based on clinical  ...  We present a deep neural network method for learning a personal representation for individuals that are performing a self neuromodulation task, guided by functional MRI (fMRI).  ...  Acknowledgments This project has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant ERC CoG 725974).  ... 
doi:10.1007/978-3-030-59728-3_46 fatcat:ggo6dhpmerfn3nzi7uqvvmv2c4

fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits [article]

Rotem Leibovitz, Jhonathan Osin, Lior Wolf, Guy Gurevitch, Talma Hendler
2022 arXiv   pre-print
The predictive power of the obtained signature is stronger than previous approaches for obtaining a personal signature from fMRI neurofeedback and provides an indication that a person's learning pattern  ...  We obtain a personal signature of a person's learning progress in a self-neuromodulation task, guided by functional MRI (fMRI).  ...  This learned representation is later used to predict the subject's criteria [17] .  ... 
arXiv:2112.11014v2 fatcat:37oq2flnarhrhc6w4zjli7636e

Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity? [article]

Amelie Haugg, Ronald Sladky, Stavros Skouras, Amalia McDonald, Cameron Craddock, Matthias Kirschner, Marcus Herdener, Yury Koush, Marina Papoutsi, Jackob N Keynan, Talma Hendler, Kathrin Cohen Kadosh (+27 others)
2020 bioRxiv   pre-print
However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success.  ...  in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success.  ...  Predicting neurofeedback learning success Overall, we were not able to predict neurofeedback learning success from pre-training activity levels.  ... 
doi:10.1101/2020.01.15.906388 fatcat:6r2uoywmx5exlouer7s3rhpryq

Current Status of Neurofeedback for Post-traumatic Stress Disorder: A Systematic Review and the Possibility of Decoded Neurofeedback

Toshinori Chiba, Tetsufumi Kanazawa, Ai Koizumi, Kentarou Ide, Vincent Taschereau-Dumouchel, Shuken Boku, Akitoyo Hishimoto, Miyako Shirakawa, Ichiro Sora, Hakwan Lau, Hiroshi Yoneda, Mitsuo Kawato
2019 Frontiers in Human Neuroscience  
With neurofeedback, patients can unconsciously self-regulate brain activity via real-time monitoring and feedback of the EEG or fMRI signals.  ...  With conventional neurofeedback methods, however, it is difficult to induce neural representation related to specific trauma because the feedback is based on the neural signals averaged within specific  ...  TC, KI, and MS performed the research. TC, AK, and VT-D analyzed the data. TC, TK, AK, VT-D, SB, AH, IS, HL, HY, and MK wrote the paper.  ... 
doi:10.3389/fnhum.2019.00233 pmid:31379538 pmcid:PMC6650780 fatcat:g3al355leffotb7ubi3cvf2w3q

A Sparse EEG-Informed fMRI Model for Hybrid EEG-fMRI Neurofeedback Prediction

Claire Cury, Pierre Maurel, Rémi Gribonval, Christian Barillot
2020 Frontiers in Neuroscience  
While NF-EEG (in which real-time neurofeedback scores are computed from EEG signals) has been explored for a very long time, NF-fMRI (in which real-time neurofeedback scores are computed from fMRI signals  ...  Using fMRI and EEG simultaneously for bi-modal neurofeedback sessions (NF-EEG-fMRI, in which real-time neurofeedback scores are computed from fMRI and EEG) is very promising for the design of brain rehabilitation  ...  Neurinfo receives grants from the European Union (FEDER), the French State, the Brittany Council, Rennes Metropole, Inria, Inserm, and the University Hospital of Rennes.  ... 
doi:10.3389/fnins.2019.01451 pmid:32076396 pmcid:PMC7006471 fatcat:i5k7ekglubc7xi562yongavoqq

Neurofeedback: One of today's techniques in psychiatry?

M. Arns, J.-M. Batail, S. Bioulac, M. Congedo, C. Daudet, D. Drapier, T. Fovet, R. Jardri, M. Le-Van-Quyen, F. Lotte, D. Mehler, J.-A. Micoulaud-Franchi (+2 others)
2017 L'Encephale  
L'étude des processus d'apprentissage 30 constitue un élément clé autour duquel les futures recherches devront se focaliser. 31 Mots clefs 32 Neurofeedback ; Électroencéphalographie ; imagerie fonctionnelle  ...  As controls improved during learning, induced oscillatory activity at the 3 target electrode became functionally decoupled from distant sites, which predicted the 4 individual session-to-session performance  ...  Nevertheless, there is no fundamental 15 constraint preventing neurofeedback from using machine learning as BCIs do, and future 16 neurofeedback approaches could benefit from machine learning algorithms  ... 
doi:10.1016/j.encep.2016.11.003 pmid:28041692 fatcat:3tlltsyxdbfodez2ss7f26y2la

Decoding brain states using functional magnetic resonance imaging

Dongha Lee, Bumhee Park, Changwon Jang, Hae-Jeong Park
2011 Biomedical Engineering Letters  
Among new fMRI applications, brain decoding is an emerging research area, which infers mental states from fMRI signals.  ...  Most leading research in basic and clinical neuroscience has been carried out by functional magnetic resonance imaging (fMRI), which detects the blood oxygenation level dependent signals associated with  ...  Similarly, selfcontrol of one's own local brain activity can be learned by rt-fMRI feedback [33] . rt-fMRI neurofeedback can also be used to enhance speech processing, which results in the brain connectivity  ... 
doi:10.1007/s13534-011-0021-z fatcat:kxp7bsgscfc3hkn73nbgt6sfea

Neural Correlates of Success and Failure Signals During Neurofeedback Learning

Joaquim Radua, Teodora Stoica, Dustin Scheinost, Christopher Pittenger, Michelle Hampson
2018 Neuroscience  
representations of success and failure.  ...  The intensity of the latter deactivations predicted the efficacy of the neurofeedback intervention in the reduction of anxiety.  ...  Only data from the real neurofeedback subgroup are analyzed here, as no neurofeedback learning occurred under the sham condition.  ... 
doi:10.1016/j.neuroscience.2016.04.003 pmid:27063101 pmcid:PMC5537049 fatcat:invg2su4d5fzxf5r52audyiq7y

Sculpting New Visual Concepts into the Human Brain [article]

Marius Cătălin Iordan, Victoria J.H. Ritvo, Kenneth A. Norman, Nicholas B Turk-Browne, Jonathan D. Cohen
2020 bioRxiv   pre-print
Learning requires changing the brain. This typically occurs through experience, study, or instruction.  ...  We report a new way of acquiring conceptual knowledge by directly sculpting activity patterns in the human brain.  ...  (A) The experiment extended over 9-10 days for each participant: one behavioral pre-test (2AFC along each diameter from Fig. 1 ), two localizer fMRI sessions, 5-6 real-time fMRI neurofeedback training  ... 
doi:10.1101/2020.10.14.339853 fatcat:73g75grsqbe5regr4dzjpgmgdm

Targeting default mode network connectivity with mindfulness-based fMRI neurofeedback: A pilot study among adolescents with affective disorder history [article]

Jiahe Zhang, Jovicarole Raya, Francesca Morfini, Zoi Urban, David Pagliaccio, Anastasia Yendiki, Randy P Auerbach, Clemens C.C. Bauer, Susan Whitfield-Gabrieli
2022 bioRxiv   pre-print
Directly addressing this gap, we developed a mindfulness-based fMRI neurofeedback (mbNF) for adolescents that targets default mode network (DMN) hyperconnectivity, which has been implicated in the onset  ...  using a resting state fMRI localizer.  ...  Acknowledgements This study was supported by the NIMH R56MH121426 (SWG, AY, RPA) and R61/R33MH113751-01A1 (SWG), the Poitras Center for Psychiatric Disorders Research at Massachusetts Institute of Technology  ... 
doi:10.1101/2022.08.22.504796 fatcat:owzv3oky5ngrxi2lwmslel34ou

fMRI neurofeedback facilitates anxiety regulation in females with spider phobia

Anna Zilverstand, Bettina Sorger, Pegah Sarkheil, Rainer Goebel
2015 Frontiers in Behavioral Neuroscience  
The presented study investigated if neurofeedback derived from functional magnetic resonance imaging (fMRI) would facilitate anxiety regulation by cognitive reappraisal, using spider phobia as a model  ...  Importantly, within the neurofeedback group, achieved changes in insula activation levels during training predicted long-term anxiety reduction.  ...  Acknowledgments We would like to thank Valentin Kemper and Federico De Martino for their support with optimizing fMRI data acquisition, Michael Lührs, Joel Reithler, and Jan Zimmermann for providing custom  ... 
doi:10.3389/fnbeh.2015.00148 pmid:26106309 pmcid:PMC4458693 fatcat:r73z7lr3drgrjavh7le2v4j22y

Individual differences in the mechanistic control of the dopaminergic midbrain [article]

Lydia Hellrung, Matthias Kirschner, James Sulzer, Ronald Sladky, Frank Scharnowski, Marcus Herdener, Philippe N. Tobler
2019 bioRxiv   pre-print
Successful learning to regulate was accompanied by decreasing prefrontal prediction error signals and increased prefrontal reward sensitivity in the MID task.  ...  The link of dopaminergic self-regulation with individual differences in prefrontal prediction error and reward sensitivity indicates that reinforcement learning contributes to successful top-down control  ...  This project was supported by the European Union's Horizon  ... 
doi:10.1101/863639 fatcat:ckxidbkzjrgovgj6cwe7udkrzu

Towards a common template for neural reinforcement of finger individuation

Justin Kilmarx, Ethan Oblak, James Sulzer, Jarrod Lewis-Peacock
2021 Scientific Reports  
Functional MRI neurofeedback can monitor neural activity and reinforce it towards a healthy template to restore function.  ...  We employed multi-voxel pattern analyses to assess the prediction accuracy and robustness to missing data of pre-trained functional templates corresponding to individual finger presses.  ...  This material is based upon work supported by the National Sci-  ... 
doi:10.1038/s41598-020-80166-8 pmid:33441742 fatcat:grroowfwkrc3vluyradqauh26e

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

Samantha J. Fede, Sarah F. Dean, Thushini Manuweera, Reza Momenan
2020 Frontiers in Human Neuroscience  
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.  ...  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  ...  Algorithms and Sources of Neurofeedback Signal Rt-fMRI neurofeedback works by providing a representation of hemodynamic response in the brain compared to some baseline, allowing subjects to implicitly  ... 
doi:10.3389/fnhum.2020.00060 pmid:32161529 pmcid:PMC7052377 fatcat:wogshfx7hrewjn4rn7ceeeauhy

Voluntary Enhancement of Neural Signatures of Affiliative Emotion Using fMRI Neurofeedback

Jorge Moll, Julie H. Weingartner, Patricia Bado, Rodrigo Basilio, João R. Sato, Bruno R. Melo, Ivanei E. Bramati, Ricardo de Oliveira-Souza, Roland Zahn, Michelle Hampson
2014 PLoS ONE  
Such improvement was not observed in a control group performing the same fMRI task without neurofeedback.  ...  We found that participants were able to use visual feedback based on decoded fMRI patterns as a neurofeedback signal to increase brain activation characteristic of tenderness/affection relative to pride  ...  Acknowledgments The authors are thankful to Fernanda Meirelles, Fernanda Tovar-Moll and Fernando Paiva for their help with fMRI scanning, technical advice and helpful discussions at earlier stages of this  ... 
doi:10.1371/journal.pone.0097343 pmid:24847819 pmcid:PMC4029815 fatcat:6cdeubmdzjhpvfq7uaakeqd6xq
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