Browsing by Author "Birbaumer, Niels"

Now showing 1 - 13 of 13
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    A subject-independent pattern-based Brain-Computer Interface
    (2015) Ray, Andreas M.; Sitaram, Ranganatha; Rana, Mohit; Pasqualotto, Emanuele; Buyukturkoglu, Korhan; Guan, Cuntai; Ang, Kai-Keng; Tejos Núñez, Cristián Andrés; Zamorano, Francisco; Ruiz Poblete, Sergio Marcelo; Birbaumer, Niels; Aboitiz, Francisco
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    Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia
    (2013) Ruiz Poblete, Sergio Marcelo; Lee, Sangkyun; Soekadar, Surjo R.; Caria, Andrea; Veit, Ralf; Kircher, Tilo; Birbaumer, Niels; Sitaram, Ranganatha
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    Brain-Machine Interface Induced Morpho-Functional Remodeling of the Neural Motor System in Severe Chronic Stroke
    (2020) Caria, Andrea; da Rocha, Josue Luiz Dalboni; Gallitto, Giuseppe; Birbaumer, Niels; Sitaram, Ranganatha; Murguialday, Ander Ramos
    Brain-machine interfaces (BMI) permit bypass motor system disruption by coupling contingent neuroelectric signals related to motor activity with prosthetic devices that enhance afferent and proprioceptive feedback to the somatosensory cortex. In this study, we investigated neural plasticity in the motor network of severely impaired chronic stroke patients after an EEG-BMI-based treatment reinforcing sensorimotor contingency of ipsilesional motor commands. Our structural connectivity analysis revealed decreased fractional anisotropy in the splenium and body of the corpus callosum, and in the contralesional hemisphere in the posterior limb of the internal capsule, the posterior thalamic radiation, and the superior corona radiata. Functional connectivity analysis showed decreased negative interhemispheric coupling between contralesional and ipsilesional sensorimotor regions, and decreased positive intrahemispheric coupling among contralesional sensorimotor regions. These findings indicate that BMI reinforcing ipsilesional brain activity and enhancing proprioceptive function of the affected hand elicits reorganization of contralesional and ipsilesional somatosensory and motor-assemblies as well as afferent and efferent connection-related motor circuits that support the partial re-establishment of the original neurophysiology of the motor system even in severe chronic stroke.
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    Detection of Cerebral Reorganization Induced by Real-Time fMRI Feedback Training of Insula Activation: A Multivariate Investigation
    (2011) Lee, Sangkyun; Ruiz, Sergio; Caria, Andrea; Veit, Ralf; Birbaumer, Niels; Sitaram, Ranganatha
    Background. Studies with real-time functional magnetic resonance imaging (fMRI) demonstrate that humans volitionally regulate hemodynamic signals from circumscribed regions of the brain, leading to area-specific behavioral consequences. Methods to better determine the nature of dynamic functional interactions between different brain regions and plasticity due to self-regulation training are still in development. Objective. The authors investigated changes in brain states while training 6 healthy participants to self-regulate insular cortex by real-time fMRI feedback. Methods. The authors used multivariate pattern analysis to observe spatial pattern changes and a multivariate Granger causality model to show changes in temporal interactions in multiple brain areas over the course of 5 repeated scans per subject during positive and negative emotional imagery with feedback about the level of insular activation. Results. Feedback training leads to more spatially focused recruitment of areas relevant for learning and emotion. Effective connectivity analysis reveals that initial training is associated with an increase in network density; further training "prunes" presumably redundant connections and "strengthens" relevant connections. Conclusions. The authors demonstrate the application of multivariate methods for assessing cerebral reorganization during the learning of volitional control of local brain activity. The findings provide insight into mechanisms of training-induced learning techniques for rehabilitation. The authors anticipate that future studies, specifically designed with this hypothesis in mind, may be able to construct a universal index of cerebral reorganization during skill learning based on multiple similar criteria across various skilled tasks. These techniques may be able to discern recovery from compensation, dose-response curves related to training, and ways to determine whether rehabilitation training is actively engaging necessary networks.
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    Motor Intentions Decoded from fMRI Signals
    (2024) Ruiz, Sergio; Lee, Sangkyun; Dalboni da Rocha, Josue Luiz; Ramos, Ander; Pasqualotto, Emanuele; Soares, Ernesto; García, Eliana; Fetz, Eberhard; Birbaumer, Niels; Sitaram Ranganatha
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    Real-time fMRI brain computer interfaces : Self-regulation of single brain regions to networks
    (2014) Ruiz Poblete, Sergio Marcelo; Buyukturkoglu, Korhan; Rana, Mohit; Birbaumer, Niels; Sitaram, Ranganatha
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    Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS. Signals
    (2016) Robinson, Neethu; Zaidi, Ali Danish; Rana, Mohit; Prasad, Vinod A.; Guan, Cuntai; Birbaumer, Niels; Sitaram, Ranganatha
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    Real-time support vector classification and feedback of multiple emotional brain states
    (2011) Sitaram, Ranganatha; Lee, Sangkyun; Ruiz, Sergio; Rana, Mohit; Veit, Ralf; Birbaumer, Niels
    An important question that confronts current research in affective neuroscience as well as in the treatment of emotional disorders is whether it is possible to determine the emotional state of a person based on the measurement of brain activity alone. Here, we first show that an online support vector machine (SVM) can be built to recognize two discrete emotional states, such as happiness and disgust from fMRI signals, in healthy individuals instructed to recall emotionally salient episodes from their lives. We report the first application of real-time head motion correction, spatial smoothing and feature selection based on a new method called Effect mapping. The classifier also showed robust prediction rates in decoding three discrete emotional states (happiness, disgust and sadness) in an extended group of participants. Subjective reports ascertained that participants performed emotion imagery and that the online classifier decoded emotions and not arbitrary states of the brain. Offline whole brain classification as well as region-of-interest classification in 24 brain areas previously implicated in emotion processing revealed that the frontal cortex was critically involved in emotion induction by imagery. We also demonstrate an fMRI-BCI based on real-time classification of BOLD signals from multiple brain regions, for each repetition time (TR) of scanning, providing visual feedback of emotional states to the participant for potential applications in the clinical treatment of dysfunctional affect. (C) 2010 Elsevier Inc. All rights reserved.
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    Self-regulation of anterior insula with real-time fMRI and its behavioral effects in obsessive-compulsive disorder : a feasibility study
    (2015) Buyukturkoglu, Korhan; Roettgers, Hans Sommer; Jens, Rana; Mohit, Dietzsch; Leonie, Arikan; Ezgi Belkis; Veit, Ralf; Malekshahi, Rahim; Kircher, Tilo; Ruiz, Sergio; Sitaram, Ranganatha; Birbaumer, Niels
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    The hemodynamic initial-dip consists of both volumetric and oxymetric changes reflecting localized spiking activity
    (2023) Zaidi, Ali Danish; Birbaumer, Niels; Fetz, Eberhard; Logothetis, Nikos; Sitaram, Ranganatha
    The initial-dip is a transient decrease frequently observed in functional neuroimaging signals, immediately after stimulus onset, believed to originate from a rise in deoxy-hemoglobin (HbR) caused by local neural activity. It has been shown to be more spatially specific than the hemodynamic response, and is believed to represent focal neuronal activity. However, despite being observed in various neuroimaging modalities (such as fMRI, fNIRS, etc), its origins are disputed, and its precise neuronal correlates are unknown. Here we show that the initial-dip is dominated by a decrease in total-hemoglobin (HbT). We also find a biphasic response in deoxy-Hb (HbR), with an early decrease and later rebound. Both the HbT-dip and HbR-rebound were strongly correlated to highly localized spiking activity. However, HbT decreases were always large enough to counter the spiking-induced increase in HbR. We find that the HbT-dip counters spiking induced HbR increases, imposing an upper-limit to HbR concentration in the capillaries. Building on our results, we explore the possibility of active venule dilation (purging) as a possible mechanism for the HbT dip.
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    Use of Real-Time Functional Magnetic Resonance Imaging-Based Neurofeedback to Downregulate Insular Cortex in Nicotine-Addicted Smokers
    (2020) Rana, Mohit; Ruiz, Sergio; Sanchez Corzo, Andrea; Muehleck, Axel; Eck, Sandra; Salinas, Cesar; Zamorano, Francisco; Silva, Claudio; Rea, Massimiliano; Batra, Anil; Birbaumer, Niels; Sitaram, Ranganatha
    It has been more than a decade since the first functional magnetic resonance imaging (fMRI)-based neurofeedback approach was successfully implemented. Since then, various studies have demonstrated that participants can learn to voluntarily control a circumscribed brain region. Consequently, real-time fMRI (rtfMRI) provided a novel opportunity to study modifications of behavior due to manipulation of brain activity. Hence, reports of rtfMRI applications to train self-regulation of brain activity and the concomitant modifications in behavioral and clinical conditions such as neurological and psychiatric disorders [e.g., schizophrenia, obsessive compulsive Disorder (OCD), stroke] have rapidly increased.
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    Volitional control of the anterior insula in criminal psychopaths using real-time fMRI neurofeedback : A pilot study
    (2014) Sitaram, Ranganatha; Caria, Andrea; Ruiz Poblete, Sergio Marcelo; Veit, Ralf; Gaber, Tilman; Birbaumer, Niels
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    Volitional regulation of the supplementary motor area with fMRI-BCI neurofeedback in Parkinson's disease: A pilot study
    (IEEE, 2013) Buyukturkoglu, Korhan; Rana, Mohit; Ruiz Poblete, Sergio Marcelo; Hackley, Steven A.; Soekadar, Surjo R.; Birbaumer, Niels; Sitaram, Ranganatha
    It is hypothesized that a dysfunction of the supplementary motor area (SMA), secondary to a deficit of the nigrostriatal dopamine system, partially contributes to the symptomatology of Parkinson's disease (PD), i.e., akinesia. In this pilot study we investigated the effect of real-time fMRI neurofeedback based volitional up-regulation of the SMA on hand motor performance of one PD patient and 3 healthy volunteers. The effect of learned self-regulation was evaluated with speeded, bimanual, sequenced button-pressing trials, assessed immediately after each baseline and up-regulation block. Our pilot results indicate that volitional up-regulation of SMA is accompanied by slowing of sequenced button presses.