{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T02:38:30Z","timestamp":1771295910904,"version":"3.50.1"},"reference-count":105,"publisher":"IOP Publishing","issue":"5","license":[{"start":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T00:00:00Z","timestamp":1698969600000},"content-version":"vor","delay-in-days":33,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T00:00:00Z","timestamp":1698969600000},"content-version":"tdm","delay-in-days":33,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["J. Neural Eng."],"published-print":{"date-parts":[[2023,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two commonly used non-invasive techniques for measuring brain activity in neuroscience and brain\u2013computer interfaces (BCI). <jats:italic>Objective<\/jats:italic>. In this review, we focus on the use of EEG and fMRI in neurofeedback (NF) and discuss the challenges of combining the two modalities to improve understanding of brain activity and achieve more effective clinical outcomes. Advanced technologies have been developed to simultaneously record EEG and fMRI signals to provide a better understanding of the relationship between the two modalities. However, the complexity of brain processes and the heterogeneous nature of EEG and fMRI present challenges in extracting useful information from the combined data. <jats:italic>Approach<\/jats:italic>. We will survey existing EEG\u2013fMRI combinations and recent studies that exploit EEG\u2013fMRI in NF, highlighting the experimental and technical challenges. <jats:italic>Main results<\/jats:italic>. We made a classification of the different combination of EEG-fMRI for NF, we provide a review of multimodal analysis methods for EEG\u2013fMRI features. We also survey the current state of research on EEG-fMRI in the different existing NF paradigms. Finally, we also identify some of the remaining challenges in this field. <jats:italic>Significance<\/jats:italic>. By exploring EEG-fMRI combinations in NF, we are advancing our knowledge of brain function and its applications in clinical settings. As such, this review serves as a valuable resource for researchers, clinicians, and engineers working in the field of neural engineering and rehabilitation, highlighting the promising future of EEG-fMRI-based NF.<\/jats:p>","DOI":"10.1088\/1741-2552\/ad06e1","type":"journal-article","created":{"date-parts":[[2023,10,25]],"date-time":"2023-10-25T18:32:27Z","timestamp":1698258747000},"page":"051003","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":28,"title":["Two is better? combining EEG and fMRI for BCI and neurofeedback: a systematic review"],"prefix":"10.1088","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8308-2640","authenticated-orcid":true,"given":"Mathis","family":"Fleury","sequence":"first","affiliation":[]},{"given":"Patr\u00edcia","family":"Figueiredo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9676-8599","authenticated-orcid":true,"given":"Athanasios","family":"Vourvopoulos","sequence":"additional","affiliation":[]},{"given":"Anatole","family":"L\u00e9cuyer","sequence":"additional","affiliation":[]}],"member":"266","published-online":{"date-parts":[[2023,11,3]]},"reference":[{"key":"jnead06e1bib1","doi-asserted-by":"publisher","first-page":"29","DOI":"10.3389\/fnhum.2018.00029","type":"journal-article","article-title":"EEG-informed fMRI: a review of data analysis methods","volume":"12","author":"Abreu","year":"2018","journal-title":"Front. Hum. Neurosci."},{"key":"jnead06e1bib2","doi-asserted-by":"publisher","first-page":"503","DOI":"10.3389\/fnhum.2017.00503","type":"journal-article","article-title":"Multi-modal integration of EEG-fNIRS for brain-computer interfaces \u2013 current limitations and future directions","volume":"11","author":"Ahn","year":"2017","journal-title":"Front. Hum. Neurosci."},{"key":"jnead06e1bib3","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/S0166-2236(00)01995-0","type":"journal-article","article-title":"How well do we understand the neural origins of the fMRI bold signal?","volume":"25","author":"Arthurs","year":"2002","journal-title":"Trends Neurosci."},{"key":"jnead06e1bib4","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1016\/j.neuroimage.2004.09.036","type":"journal-article","article-title":"Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function","volume":"24","author":"Babiloni","year":"2005","journal-title":"Neuroimage"},{"key":"jnead06e1bib5","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1002\/mrm.1910250220","type":"journal-article","article-title":"Time course EPI of human brain function during task activation","volume":"25","author":"Bandettini","year":"1992","journal-title":"Magn. Reson. Med."},{"key":"jnead06e1bib6","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1016\/j.neuroimage.2011.07.035","type":"journal-article","article-title":"Self-modulation of primary motor cortex activity with motor and motor imagery tasks using real-time fMRI-based neurofeedback","volume":"59","author":"Berman","year":"2012","journal-title":"Neuroimage"},{"key":"jnead06e1bib7","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1109\/RBME.2011.2170675","type":"journal-article","article-title":"Analysis of multimodal neuroimaging data","volume":"4","author":"Biessmann","year":"2011","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"jnead06e1bib8","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1002\/mrm.1910340409","type":"journal-article","article-title":"Functional connectivity in the motor cortex of resting human brain using echo-planar MRI","volume":"34","author":"Biswal","year":"1995","journal-title":"Magn. Reson. Med."},{"key":"jnead06e1bib9","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2021.622719","type":"journal-article","article-title":"Artifact reduction in simultaneous EEG-fMRI: a systematic review of methods and contemporary usage","volume":"12","author":"Bullock","year":"2021","journal-title":"Front. Neurol."},{"key":"jnead06e1bib10","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1038\/nrn3241","type":"journal-article","article-title":"The origin of extracellular fields and currents-EEG, ECoG, LFP and spikes","volume":"13","author":"Buzs\u00e1ki","year":"2012","journal-title":"Nat. Rev. Neurosci."},{"key":"jnead06e1bib11","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1002\/acn3.544","type":"journal-article","article-title":"Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis","volume":"5","author":"Cervera","year":"2018","journal-title":"Ann. Clin. Transl. Neurol."},{"key":"jnead06e1bib12","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.expneurol.2012.08.030","type":"journal-article","article-title":"MEG studies of sensorimotor rhythms: a review","volume":"245","author":"Cheyne","year":"2013","journal-title":"Exp. Neurol."},{"key":"jnead06e1bib13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3389\/fnins.2019.01451","type":"journal-article","article-title":"A sparse EEG-informed fMRI model for hybrid EEG-fMRI neurofeedback prediction","volume":"13","author":"Cury","year":"2020","journal-title":"Front. Neurosci."},{"key":"jnead06e1bib14","doi-asserted-by":"publisher","first-page":"1112","DOI":"10.1016\/j.neuron.2013.10.017","type":"journal-article","article-title":"EEG and MEG: relevance to neuroscience","volume":"80","author":"da Silva","year":"2013","journal-title":"Neuron"},{"key":"jnead06e1bib15","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.neuroimage.2007.01.044","type":"journal-article","article-title":"Symmetrical event-related EEG\/fMRI information fusion in a variational Bayesian framework","volume":"36","author":"Daunizeau","year":"2007","journal-title":"Neuroimage"},{"key":"jnead06e1bib16","first-page":"pp 511","type":"book","article-title":"EEG\u2013fMRI information fusion: biophysics and data analysis","author":"Daunizeau","year":"2009"},{"key":"jnead06e1bib17","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/0278-2626(92)90065-T","type":"journal-article","article-title":"Anterior cerebral asymmetry and the nature of emotion","volume":"20","author":"Davidson","year":"1992","journal-title":"Brain Cogn."},{"key":"jnead06e1bib18","doi-asserted-by":"publisher","first-page":"11730","DOI":"10.1523\/JNEUROSCI.3286-05.2005","type":"journal-article","article-title":"Trial-by-trial coupling of concurrent electroencephalogram and functional magnetic resonance imaging identifies the dynamics of performance monitoring","volume":"25","author":"Debener","year":"2005","journal-title":"J. Neurosci."},{"key":"jnead06e1bib19","doi-asserted-by":"publisher","first-page":"18626","DOI":"10.1073\/pnas.0505210102","type":"journal-article","article-title":"Control over brain activation and pain learned by using real-time functional MRI","volume":"102","author":"DeCharms","year":"2005","journal-title":"Proc. Natl Acad. Sci."},{"key":"jnead06e1bib20","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2022.988890","type":"journal-article","article-title":"Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback","volume":"16","author":"Dehghani","year":"2023","journal-title":"Front. Hum. Neurosci."},{"key":"jnead06e1bib21","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1038\/nrneurol.2014.162","type":"journal-article","article-title":"Modulation of brain plasticity in stroke: a novel model for neurorehabilitation","volume":"10","author":"Di Pino","year":"2014","journal-title":"Nat. Rev. Neurol."},{"key":"jnead06e1bib22","doi-asserted-by":"publisher","first-page":"56","DOI":"10.3389\/fninf.2018.00056","type":"journal-article","article-title":"Neuroscience information toolbox: an open source toolbox for EEG\u2013fMRI multimodal fusion analysis","volume":"12","author":"Dong","year":"2018","journal-title":"Front. Neuroinform."},{"key":"jnead06e1bib23","doi-asserted-by":"publisher","first-page":"2209","DOI":"10.1016\/j.neuroimage.2003.08.012","type":"journal-article","article-title":"Real-time independent component analysis of fMRI time-series","volume":"20","author":"Esposito","year":"2003","journal-title":"Neuroimage"},{"key":"jnead06e1bib24","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1161\/STROKEAHA.113.003168","type":"journal-article","article-title":"Upper limb recovery after stroke is associated with ipsilesional primary motor cortical activity: a meta-analysis","volume":"45","author":"Favre","year":"2014","journal-title":"Stroke"},{"key":"jnead06e1bib25","doi-asserted-by":"publisher","first-page":"891","DOI":"10.1109\/JPROC.2015.2413993","type":"journal-article","article-title":"Learning from more than one data source: data fusion techniques for sensorimotor rhythm-based brain\u2013computer interfaces","volume":"103","author":"Fazli","year":"2015","journal-title":"Proc. IEEE"},{"key":"jnead06e1bib26","doi-asserted-by":"publisher","first-page":"60","DOI":"10.3389\/fnhum.2020.00060","type":"journal-article","article-title":"A guide to literature informed decisions in the design of real time fMRI neurofeedback studies: a systematic review","volume":"14","author":"Fede","year":"2020","journal-title":"Front. Hum. Neurosci."},{"key":"jnead06e1bib27","doi-asserted-by":"publisher","first-page":"921","DOI":"10.1016\/j.neuroimage.2012.03.049","type":"journal-article","article-title":"A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application","volume":"63","author":"Ferrari","year":"2012","journal-title":"Neuroimage"},{"key":"jnead06e1bib28","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1038\/jcbfm.1993.4","type":"journal-article","article-title":"Functional connectivity: the principal-component analysis of large (PET) data sets","volume":"13","author":"Friston","year":"1993","journal-title":"J. Cerebral Blood Flow Metab."},{"key":"jnead06e1bib29","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2021.102859","type":"journal-article","article-title":"Amygdala electrical-finger-print (AmygEFP) neurofeedback guided by individually-tailored trauma script for post-traumatic stress disorder: Proof-of-concept","volume":"32","author":"Fruchtman-Steinbok","year":"2021","journal-title":"Neuroimage Clin."},{"key":"jnead06e1bib30","first-page":"pp 119","type":"book","article-title":"The added value of EEG-fMRI in imaging neuroscience","author":"Goebel","year":"2023"},{"key":"jnead06e1bib31","doi-asserted-by":"publisher","first-page":"758","DOI":"10.1016\/j.neuroimage.2018.11.001","type":"journal-article","article-title":"Volitional limbic neuromodulation exerts a beneficial clinical effect on fibromyalgia","volume":"186","author":"Goldway","year":"2019","journal-title":"NeuroImage"},{"key":"jnead06e1bib32","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.neubiorev.2013.09.015","type":"journal-article","article-title":"EEG-neurofeedback for optimising performance. I: a review of cognitive and affective outcome in healthy participants","volume":"44","author":"Gruzelier","year":"2014","journal-title":"Neurosci. Biobehav. Rev."},{"key":"jnead06e1bib33","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1109\/5.554205","type":"journal-article","article-title":"An introduction to multisensor data fusion","volume":"85","author":"Hall","year":"1997","journal-title":"Proc. IEEE"},{"key":"jnead06e1bib34","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1503\/jpn.140200","type":"journal-article","article-title":"Individualized real-time fMRI neurofeedback to attenuate craving in nicotine-dependent smokers","volume":"41","author":"Hartwell","year":"2016","journal-title":"J. Psychiatry Neurosci."},{"key":"jnead06e1bib35","doi-asserted-by":"publisher","first-page":"1066","DOI":"10.1016\/j.neuroimage.2009.07.056","type":"journal-article","article-title":"Neurofeedback: a promising tool for the self-regulation of emotion networks","volume":"49","author":"Johnston","year":"2010","journal-title":"Neuroimage"},{"key":"jnead06e1bib36","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.neuroimage.2013.05.114","type":"journal-article","article-title":"EEG\u2013fMRI integration for the study of human brain function","volume":"102","author":"Jorge","year":"2014","journal-title":"Neuroimage"},{"key":"jnead06e1bib37","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1038\/s42003-022-03665-6","type":"journal-article","article-title":"Basal ganglia-cortical connectivity underlies self-regulation of brain oscillations in humans","volume":"5","author":"Kasahara","year":"2022","journal-title":"Commun. Biol."},{"key":"jnead06e1bib38","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1002\/hbm.23849","type":"journal-article","article-title":"Multichannel wearable fNIRS-EEG system for long-term clinical monitoring","volume":"39","author":"Kassab","year":"2018","journal-title":"Hum. Brain Mapp."},{"key":"jnead06e1bib39","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1016\/j.biopsych.2015.12.024","type":"journal-article","article-title":"Limbic activity modulation guided by functional magnetic resonance imaging\u2013inspired electroencephalography improves implicit emotion regulation","volume":"80","author":"Keynan","year":"2016a","journal-title":"Biol. Psychiatry"},{"key":"jnead06e1bib40","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1038\/s41562-018-0484-3","type":"journal-article","article-title":"Electrical fingerprint of the amygdala guides neurofeedback training for stress resilience","volume":"3","author":"Keynan","year":"2019","journal-title":"Nat. Hum. Behav."},{"key":"jnead06e1bib41","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.neuroimage.2014.04.044","type":"journal-article","article-title":"Neural dynamics necessary and sufficient for transition into pre-sleep induced by EEG neurofeedback","volume":"97","author":"Kinreich","year":"2014","journal-title":"NeuroImage"},{"key":"jnead06e1bib42","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1016\/j.neuroimage.2016.07.014","type":"journal-article","article-title":"Dual array EEG-fMRI: an approach for motion artifact suppression in EEG recorded simultaneously with fMRI","volume":"142","author":"Klovatch-Podlipsky","year":"2016","journal-title":"Neuroimage"},{"key":"jnead06e1bib43","doi-asserted-by":"publisher","first-page":"594","DOI":"10.3389\/fnins.2020.00594","type":"journal-article","article-title":"The potential of functional near-infrared spectroscopy-based neurofeedback-a systematic review and recommendations for best practice","volume":"14","author":"Kohl","year":"2020","journal-title":"Front. Neurosci."},{"key":"jnead06e1bib44","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1016\/j.neuroimage.2010.06.052","type":"journal-article","article-title":"Decoding fMRI brain states in real-time","volume":"56","author":"LaConte","year":"2011","journal-title":"Neuroimage"},{"key":"jnead06e1bib45","first-page":"pp 377","type":"book","article-title":"Simultaneous EEG-fMRI","author":"Lei","year":"2019"},{"key":"jnead06e1bib46","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1142\/S0219635212500203","type":"journal-article","article-title":"EEG\/fMRI fusion based on independent component analysis: integration of data-driven and model-driven methods","volume":"11","author":"Lei","year":"2012","journal-title":"J. Integr. Neurosci."},{"key":"jnead06e1bib47","doi-asserted-by":"publisher","first-page":"1141","DOI":"10.1002\/hbm.21098","type":"journal-article","article-title":"fMRI functional networks for EEG source imaging","volume":"32","author":"Lei","year":"2011","journal-title":"Hum. Brain Mapp."},{"key":"jnead06e1bib48","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/j.1460-9568.2011.07923.x","type":"journal-article","article-title":"How many neurons do you have? some dogmas of quantitative neuroscience under revision","volume":"35","author":"Lent","year":"2012","journal-title":"Eur. J. Neurosci."},{"key":"jnead06e1bib49","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0038115","type":"journal-article","article-title":"Real-time self-regulation of emotion networks in patients with depression","volume":"7","author":"Linden","year":"2012","journal-title":"PLoS One"},{"key":"jnead06e1bib50","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ac291e","type":"journal-article","article-title":"The impact of neurofeedback on effective connectivity networks in chronic stroke patients: an exploratory study","volume":"18","author":"Lioi","year":"2021","journal-title":"J. Neural Eng."},{"key":"jnead06e1bib51","doi-asserted-by":"publisher","first-page":"37","DOI":"10.3389\/fnhum.2020.00037","type":"journal-article","article-title":"A multi-target motor imagery training using bimodal EEG-fMRI neurofeedback: a pilot study in chronic stroke patients","volume":"14","author":"Lioi","year":"2020","journal-title":"Front. Hum. Neurosci."},{"key":"jnead06e1bib52","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1038\/nature06976","type":"journal-article","article-title":"What we can do and what we cannot do with fMRI","volume":"453","author":"Logothetis","year":"2008","journal-title":"Nature"},{"key":"jnead06e1bib53","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1038\/35084005","type":"journal-article","article-title":"Neurophysiological investigation of the basis of the fMRI signal","volume":"412","author":"Logothetis","year":"2001","journal-title":"Nature"},{"key":"jnead06e1bib54","author":"Luck","year":"2014","type":"book"},{"key":"jnead06e1bib55","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/14\/1\/016004","type":"journal-article","article-title":"Automated selection of brain regions for real-time fMRI brain\u2013computer interfaces","volume":"14","author":"L\u00fchrs","year":"2016","journal-title":"J. Neural Eng."},{"key":"jnead06e1bib56","doi-asserted-by":"publisher","first-page":"140","DOI":"10.3389\/fnins.2017.00140","type":"journal-article","article-title":"How to build a hybrid neurofeedback platform combining EEG and fMRI","volume":"11","author":"Mano","year":"2017","journal-title":"Front. Neurosci."},{"key":"jnead06e1bib57","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.jneumeth.2016.09.012","type":"journal-article","article-title":"Real-time EEG artifact correction during fMRI using ICA","volume":"274","author":"Mayeli","year":"2016","journal-title":"J. Neurosci. Methods"},{"key":"jnead06e1bib58","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.neuroimage.2018.09.007","type":"journal-article","article-title":"The bold response in primary motor cortex and supplementary motor area during kinesthetic motor imagery based graded fMRI neurofeedback","volume":"184","author":"Mehler","year":"2019","journal-title":"NeuroImage"},{"key":"jnead06e1bib59","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0154968","type":"journal-article","article-title":"One-class fMRI-inspired EEG model for self-regulation training","volume":"11","author":"Meir-Hasson","year":"2016","journal-title":"PLoS One"},{"key":"jnead06e1bib60","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.neuroimage.2013.11.004","type":"journal-article","article-title":"An EEG finger-print of fMRI deep regional activation","volume":"102","author":"Meir-Hasson","year":"2014","journal-title":"Neuroimage"},{"key":"jnead06e1bib61","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1000097","type":"journal-article","article-title":"Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement","volume":"6","author":"(The PRISMA Group)","year":"2009","journal-title":"PLoS Med."},{"key":"jnead06e1bib62","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1002\/hbm.22623","type":"journal-article","article-title":"Electrophysiological correlates of the BOLD signal for EEG-informed fMRI","volume":"36","author":"Murta","year":"2015","journal-title":"Hum. Brain Mapp."},{"key":"jnead06e1bib63","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1016\/j.nicl.2016.07.006","type":"journal-article","article-title":"Alpha oscillation neurofeedback modulates amygdala complex connectivity and arousal in posttraumatic stress disorder","volume":"12","author":"Nicholson","year":"2016","journal-title":"NeuroImage Clin."},{"key":"jnead06e1bib64","first-page":"pp 442","type":"conference-proceedings","article-title":"Multi-modal EEG and fMRI source estimation using sparse constraints","author":"Noorzadeh","year":"2017"},{"key":"jnead06e1bib65","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1023\/A:1026683200895","type":"journal-article","article-title":"On the relationship of synaptic activity to macroscopic measurements: does co-registration of eeg with fMRI make sense?","volume":"13","author":"Nunez","year":"2000","journal-title":"Brain Topography"},{"key":"jnead06e1bib66","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.119822","type":"journal-article","article-title":"Neural and functional validation of fMRI-informed EEG model of right inferior frontal gyrus activity","volume":"266","author":"Or-Borichev","year":"2022","journal-title":"Neuroimage"},{"key":"jnead06e1bib67","doi-asserted-by":"publisher","first-page":"1270","DOI":"10.1016\/j.neuroimage.2010.12.029","type":"journal-article","article-title":"Voxel-wise information theoretic EEG-fMRI feature integration","volume":"55","author":"Ostwald","year":"2011","journal-title":"Neuroimage"},{"key":"jnead06e1bib68","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1145\/319382.319398","type":"journal-article","article-title":"Ten myths of multimodal interaction","volume":"42","author":"Oviatt","year":"1999","journal-title":"Commun. ACM"},{"key":"jnead06e1bib69","article-title":"Combining EEG and fMRI for Neurofeedback","author":"Perronnet","year":"2017","type":"other"},{"key":"jnead06e1bib70","doi-asserted-by":"publisher","DOI":"10.1101\/397729","type":"other","article-title":"Learning 2-in-1: towards integrated EEG-fMRI-neurofeedback","author":"Perronnet","year":"2020"},{"key":"jnead06e1bib71","doi-asserted-by":"publisher","first-page":"193","DOI":"10.3389\/fnhum.2017.00193","type":"journal-article","article-title":"Unimodal versus bimodal EEG-fMRI neurofeedback of a motor imagery task","volume":"11","author":"Perronnet","year":"2017","journal-title":"Front. Hum. Neurosci."},{"key":"jnead06e1bib72","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.1109\/5.939829","type":"journal-article","article-title":"Motor imagery and direct brain-computer communication","volume":"89","author":"Pfurtscheller","year":"2001","journal-title":"Proc. IEEE"},{"key":"jnead06e1bib73","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1038\/86110","type":"journal-article","article-title":"Activation of the left amygdala to a cognitive representation of fear","volume":"4","author":"Phelps","year":"2001","journal-title":"Nat. Neurosci."},{"key":"jnead06e1bib74","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1111\/nyas.13948","type":"journal-article","article-title":"The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience","volume":"1464","author":"Pinti","year":"2020","journal-title":"Ann. New York Acad. Sci."},{"key":"jnead06e1bib75","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1016\/j.jneumeth.2008.07.017","type":"journal-article","article-title":"An open-source hardware and software system for acquisition and real-time processing of electrophysiology during high field MRI","volume":"175","author":"Purdon","year":"2008","journal-title":"J. Neurosci. Methods"},{"key":"jnead06e1bib76","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.28974","type":"journal-article","article-title":"Direct modulation of aberrant brain network connectivity through real-time neurofeedback","volume":"6","author":"Ramot","year":"2017","journal-title":"Elife"},{"key":"jnead06e1bib77","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2020.108719","type":"journal-article","article-title":"Development of a combined, sequential real-time fMRI and fNIRS neurofeedback system enhance motor learning after stroke","volume":"341","author":"Rieke","year":"2020","journal-title":"J. Neurosci. Methods"},{"key":"jnead06e1bib78","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.biopsycho.2013.04.010","type":"journal-article","article-title":"Real-time fMRI brain computer interfaces: self-regulation of single brain regions to networks","volume":"95","author":"Ruiz","year":"2014","journal-title":"Biol. Psychol."},{"key":"jnead06e1bib79","article-title":"Brain network connectivity and behaviour enhancement: a fMRI-BCI study","author":"Ruiz","year":"2011","type":"conference-proceedings"},{"key":"jnead06e1bib80","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/10\/5\/056001","type":"journal-article","article-title":"Toward a fully integrated wireless wearable EEG-NIRS bimodal acquisition system","volume":"10","author":"Safaie","year":"2013","journal-title":"J. Neural Eng."},{"key":"jnead06e1bib81","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/S0920-9964(98)00085-1","type":"journal-article","article-title":"Differential amygdala activation in schizophrenia during sadness","volume":"34","author":"Schneider","year":"1998","journal-title":"Schizophrenia Res."},{"key":"jnead06e1bib82","first-page":"pp 2562","type":"conference-proceedings","article-title":"Correlated alpha activity with the facial expression processing network in a simultaneous EEG-fMRI experiment","author":"Simoes","year":"2017"},{"key":"jnead06e1bib83","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ab9a98","type":"journal-article","article-title":"How much of the BOLD-fMRI signal can be approximated from simultaneous EEG data: relevance for the transfer and dissemination of neurofeedback interventions","volume":"17","author":"Simoes","year":"2020","journal-title":"J. Neural Eng."},{"key":"jnead06e1bib84","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1038\/nrn.2016.164","type":"journal-article","article-title":"Closed-loop brain training: the science of neurofeedback","volume":"18","author":"Sitaram","year":"2017","journal-title":"Nat. Rev. Neurosci."},{"key":"jnead06e1bib85","doi-asserted-by":"publisher","DOI":"10.1016\/j.concog.2021.103264","type":"journal-article","article-title":"An investigation of awareness and metacognition in neurofeedback with the amygdala electrical fingerprint","volume":"98","author":"Stirner","year":"2022","journal-title":"Conscious. Cogn."},{"key":"jnead06e1bib86","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.nicl.2014.07.002","type":"journal-article","article-title":"Optimizing real time fMRI neurofeedback for therapeutic discovery and development","volume":"5","author":"Stoeckel","year":"2014","journal-title":"NeuroImage Clin."},{"key":"jnead06e1bib87","author":"Tatum","year":"2014","type":"book"},{"key":"jnead06e1bib88","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3389\/fnins.2020.00236","type":"journal-article","article-title":"Self-regulation of SMR power led to an enhancement of functional connectivity of somatomotor cortices in fibromyalgia patients","volume":"14","author":"Terrasa","year":"2020","journal-title":"Front. Neurosci."},{"key":"jnead06e1bib89","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1016\/j.neuroimage.2017.12.071","type":"journal-article","article-title":"Neurofeedback with fMRI: a critical systematic review","volume":"172","author":"Thibault","year":"2018","journal-title":"Neuroimage"},{"key":"jnead06e1bib90","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1037\/0021-843X.115.4.715","type":"journal-article","article-title":"Depression, anxiety and resting frontal EEG asymmetry: a meta-analytic review","volume":"115","author":"Thibodeau","year":"2006","journal-title":"J. Abnormal Psychol."},{"key":"jnead06e1bib91","first-page":"1998","type":"journal-article","article-title":"A symmetrical Bayesian model for fMRI and EEG\/MEG neuroimage fusion","volume":"3","author":"Trujillo-Barreto","year":"2001","journal-title":"Int. J. Bioelectromagn"},{"key":"jnead06e1bib92","doi-asserted-by":"publisher","first-page":"2701","DOI":"10.1002\/hbm.20704","type":"journal-article","article-title":"Model driven EEG\/fMRI fusion of brain oscillations","volume":"30","author":"Valdes-Sosa","year":"2009","journal-title":"Hum. Brain Mapp."},{"key":"jnead06e1bib93","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1002\/hbm.20022","type":"journal-article","article-title":"Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest","volume":"22","author":"van de Ven","year":"2004","journal-title":"Hum. Brain Mapp."},{"key":"jnead06e1bib94","volume":"vol 685","author":"Waltz","year":"1990","type":"book"},{"key":"jnead06e1bib95","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.cortex.2017.09.006","type":"journal-article","article-title":"The potential of real-time fMRI neurofeedback for stroke rehabilitation: a systematic review","volume":"107","author":"Wang","year":"2018","journal-title":"Cortex"},{"key":"jnead06e1bib96","doi-asserted-by":"publisher","first-page":"2262","DOI":"10.3390\/s22062262","type":"journal-article","article-title":"Simultaneous EEG-fMRI: what have we learned and what does the future hold?","volume":"22","author":"Warbrick","year":"2022","journal-title":"Sensors"},{"key":"jnead06e1bib97","doi-asserted-by":"publisher","first-page":"682","DOI":"10.1016\/j.neuroimage.2011.10.009","type":"journal-article","article-title":"Real-time fMRI and its application to neurofeedback","volume":"62","author":"Weiskopf","year":"2012","journal-title":"Neuroimage"},{"key":"jnead06e1bib98","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.cmpb.2016.01.018","type":"journal-article","article-title":"A real-time method to reduce ballistocardiogram artifacts from EEG during fMRI based on optimal basis sets (OBS)","volume":"127","author":"Wu","year":"2016","journal-title":"Comput. Methods Programs Biomed."},{"key":"jnead06e1bib99","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1016\/j.neuroimage.2015.04.020","type":"journal-article","article-title":"Real-time EEG feedback during simultaneous EEG-fMRI identifies the cortical signature of motor imagery","volume":"114","author":"Zich","year":"2015","journal-title":"NeuroImage"},{"key":"jnead06e1bib100","doi-asserted-by":"publisher","first-page":"148","DOI":"10.3389\/fnbeh.2015.00148","type":"journal-article","article-title":"fMRI neurofeedback facilitates anxiety regulation in females with spider phobia","volume":"9","author":"Zilverstand","year":"2015","journal-title":"Front. Behav. Neurosci."},{"key":"jnead06e1bib101","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0024522","type":"journal-article","article-title":"Self-regulation of amygdala activation using real-time fMRI neurofeedback","volume":"6","author":"Zotev","year":"2011","journal-title":"PLoS One"},{"key":"jnead06e1bib102","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2020.102331","type":"journal-article","article-title":"Emotion self-regulation training in major depressive disorder using simultaneous real-time fMRI and EEG neurofeedback","volume":"27","author":"Zotev","year":"2020","journal-title":"NeuroImage Clin."},{"key":"jnead06e1bib103","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.nicl.2018.04.010","type":"journal-article","article-title":"Real-time fMRI neurofeedback training of the amygdala activity with simultaneous EEG in veterans with combat-related PTSD","volume":"19","author":"Zotev","year":"2018","journal-title":"NeuroImage Clin."},{"key":"jnead06e1bib104","doi-asserted-by":"publisher","first-page":"985","DOI":"10.1016\/j.neuroimage.2013.04.126","type":"journal-article","article-title":"Self-regulation of human brain activity using simultaneous real-time fMRI and EEG neurofeedback","volume":"85","author":"Zotev","year":"2014","journal-title":"Neuroimage"},{"key":"jnead06e1bib105","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1016\/j.nicl.2016.02.003","type":"journal-article","article-title":"Correlation between amygdala bold activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression","volume":"11","author":"Zotev","year":"2016","journal-title":"NeuroImage Clin."}],"container-title":["Journal of Neural Engineering"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1","content-type":"text\/html","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"similarity-checking"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:36:46Z","timestamp":1760186206000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1741-2552\/ad06e1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,1]]},"references-count":105,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2023,11,3]]},"published-print":{"date-parts":[[2023,10,1]]}},"URL":"https:\/\/doi.org\/10.1088\/1741-2552\/ad06e1","relation":{},"ISSN":["1741-2560","1741-2552"],"issn-type":[{"value":"1741-2560","type":"print"},{"value":"1741-2552","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,1]]},"assertion":[{"value":"Two is better? combining EEG and fMRI for BCI and neurofeedback: a systematic review","name":"article_title","label":"Article Title"},{"value":"Journal of Neural Engineering","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"\u00a9 2023 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2023-03-22","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2023-10-25","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2023-11-03","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}