Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI)

By Nikolaus Weiskopf, Klaus Mathiak, S. Bock, F. Scharnowski, Ralf Veit, Wolfgang Grodd, Rainer Goebel, Niels Birbaumer. IEEE Transactions on Biomedical Engineering, 2004

452 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/78476231c02c1da3d70f0cba120ca6e2d97c1f74

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In Cognitive Neuroscience

Citations in the corpus

fNIRS-based brain-computer interfaces: a review (2015, methodology): “…(MEG) (Mellinger et al., 2007; Buch et al., 2008; Sardouie and Shamsollahi, 2012), functional magnetic resonance imaging (fMRI) (Weiskopf et al., 2004; LaConte, 2011; van der Heiden et al., 2014), and fNIRS (Ferrari et al., 1985, 2004; Kato et al., 1993; Hu et al., 2013; Bhutta…”
Regulation of anterior insular cortex activity using real-time fMRI (2007, methodology): “…different cortical and subcortical areas: the sensorimotor cortex (deCharms et al., 2004; Yoo and Jolesz, 2002), the supplementary motor area (SMA; Weiskopf et al., 2004a), the parahippocampal place area (PPA; Weiskopf et al., 2004a), the anterior cingulate cortex (ACC) (Weiskopf et al., 2003),…”
Ten simple rules for predictive modeling of individual differences in neuroimaging (2019, background): “…et al., 2012), requires interpretable models to define the target; whereas other applications, such as brain–computer interfaces (Ruiz et al., 2014; Weiskopf et al., 2004), may pursue the best prediction performance regardless of model interpretability and, in this case, treating the model as a…”
Cognitive motor processes: the role of motor imagery in the study of motor representations. (2009, background): “Moreover, neural activation during motor imagery may serve as a control device for brain-machine interfaces (deCharms, 2007; Lebedev and Nicolelis, 2006; Weiskopf et al., 2004).”
Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects (2009, background): “In recent years, there has been growing interest in BCIs based on metabolic signals derived from the brain [57-69].”
Real-time fMRI and its application to neurofeedback (2012, methodology): “…regions studied by rtfMRI neurofeedback includedmotor areas (Bray et al., 2007; deCharms et al., 2004; LaConte et al., 2007; Sitaram et al., 2012;Weiskopf et al., 2004a; Yoo and Jolesz, 2002; Yoo et al., 2004), somatosensory cortex (Bray et al., 2007; deCharms et al., 2004; Yoo and Jolesz,…”
A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals (2007, background): “(4) Designs that use functional magnetic resonance imaging (fMRI) (Weiskopf et al 2003, 2004, Yoo et al 2004), magneto-encephalography (MEG) signals (Georgopoulos et al 2005), near-infra-red spectrum (NIRS), auditory evoked potentials (Hill et al 2004, Su Ryu et al 1999) and somatosensory evoked…”
Brain Computer Interfaces, a Review (2012, background): “Additionally, the hemodynamic response introduces a physiological delay from 3 to 6 seconds [84].”
Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation. (2017, methodology): “For example, as illustrated in FIGURE 5A, large variety of brain signals, ranging from single units (114, 124, 466, 583, 852), to local field potentials (LFPs) (264, 670, 750), electrocorticography (ECoG) (483, 484, 697, 759, 837, 839, 856), electroencephalography (EEG) (7, 71, 141, 169, 358, 412, 6”
Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation (2020, unknown): “…meth-ods, functional MRI (fMRI) reaches the highest range of spatial resolution. fMRI can assess the whole brain and image the hemodynamic processes at the layered and columnar levels of the human cortex, under the condition of a high-intensity magnetic ﬁeld (i.e., submillimeter level) [14] .”