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Birbaumer N.,University of Tubingen | Ruiz S.,University of Tubingen | Ruiz S.,Bernardo OHiggins University | Sitaram R.,University of Tubingen | And 2 more authors.
Trends in Cognitive Sciences

Self-regulation and voluntary control of circumscribed brain regions using real-time functional MRI (rt-fMRI) allows the establishment of a causal functional link between localized brain activity and behavior and cognition. A long tradition of research has clearly shown the brain's ability to learn volitional control of its own activity and effects on behavior. Yet, the underlying neural mechanism of self-regulation is still not fully understood. Here, we propose that self-regulation of brain activity is akin to skill learning and thus may depend on an intact subcortical motor system. We elaborate on the critical role of the basal ganglia in skill learning and neurofeedback, and clarify that brain-self-regulation need not be an explicit and conscious process as often mistakenly held. © 2013. Source

Kallappa Parameshwarappa S.,P.A. College | Mandjiny N.,P.A. College | Kavumkal Rajagopalan B.,P.A. College | Radhakrishnan N.,P.A. College | And 2 more authors.
Annals of Vascular Surgery

A 35-year-old male fisherman was admitted with complaints of increasing back pain and abdominal discomfort of 1-year duration. Physical examination revealed a prominently visible, expansile, pulsatile, well-defined, nontender abdominal mass in the epigastric, umbilical and both lumbar areas. Computed tomographic (CT) angiography revealed a large juxtarenal aortic aneurysm with a maximum transverse diameter of 14.7 cm with bi-iliac extensions. Anatomy of the aneurysm did not permit endovascular aneurysm repair (EVAR). The patient underwent open surgical inclusion repair using an aorto-bi-iliac, 16 mm × 8 mm, collagen-impregnated, bifurcated Dacron graft. Postoperative recovery was uncomplicated and he left the hospital on postoperative day 5 in good health and has remained so up to the most recent 8-month follow-up. Histopathologic study showed signature features of Takayasu arteritis. © 2013 Elsevier Inc. All rights reserved. Source

Rea M.,University of Tubingen | Rana M.,University of Tubingen | Lugato N.,University of Tubingen | Terekhin P.,University of Tubingen | And 8 more authors.
Neurorehabilitation and Neural Repair

Background. Thus far, most of the brain-computer interfaces (BCIs) developed for motor rehabilitation used electroencephalographic signals to drive prostheses that support upper limb movement. Only few BCIs used hemodynamic signals or were designed to control lower extremity prostheses. Recent technological developments indicate that functional near-infrared spectroscopy (fNIRS)-BCI can be exploited in rehabilitation of lower limb movement due to its great usability and reduced sensitivity to head motion artifacts. Objective. The aim of this proof of concept study was to assess whether hemodynamic signals underlying lower limb motor preparation in stroke patients can be reliably measured and classified. Methods. fNIRS data were acquired during preparation of left and right hip movement in 7 chronic stroke patients. Results. Single-trial analysis indicated that specific hemodynamic changes associated with left and right hip movement preparation can be measured with fNIRS. Linear discriminant analysis classification of totHB signal changes in the premotor cortex and/or posterior parietal cortex indicated above chance accuracy in discriminating paretic from nonparetic movement preparation trials in most of the tested patients. Conclusion. The results provide first evidence that fNIRS can detect brain activity associated with single-trial lower limb motor preparation in stroke patients. These findings encourage further investigation of fNIRS suitability for BCI applications in rehabilitation of patients with lower limb motor impairment after stroke. © The Author(s) 2013. Source

Ruiz S.,University of Santiago de Chile | Ruiz S.,University of Tubingen | Birbaumer N.,University of Tubingen | Sitaram R.,University of Tubingen | And 2 more authors.
Frontiers in Psychiatry

Considering that single locations of structural and functional abnormalities are insufficient to explain the diverse psychopathology of schizophrenia, new models have postulated that the impairments associated with the disease arise from a failure to integrate the activity of local and distributed neural circuits: the "abnormal neural connectivity hypothesis." In the last years, new evidence coming from neuroimaging have supported and expanded this theory. However, despite the increasing evidence that schizophrenia is a disorder of neural connectivity, so far there are no treatments that have shown to produce a significant change in brain connectivity, or that have been specifically designed to alleviate this problem. Brain-Computer Interfaces based on real-time functional Magnetic Resonance Imaging (fMRI-BCI) are novel techniques that have allowed subjects to achieve self-regulation of circumscribed brain regions. In recent studies, experiments with this technology have resulted in new findings suggesting that this methodology could be used to train subjects to enhance brain connectivity, and therefore could potentially be used as a therapeutic tool in mental disorders including schizophrenia. The present article summarizes the findings coming from hemodynamics-based neuroimaging that support the abnormal connectivity hypothesis in schizophrenia, and discusses a new approach that could address this problem. © 2013 Ruiz, Birbaumer and Sitaram. Source

Varkuti B.,University of Tubingen | Varkuti B.,Institute for Infocomm Research | Guan C.,Institute for Infocomm Research | Pan Y.,Institute for Infocomm Research | And 9 more authors.
Neurorehabilitation and Neural Repair

Background. Robot-Assisted training may improve motor function in some hemiparetic patients after stroke, but no physiological predictor of rehabilitation progress is reliable. Resting state functional magnetic resonance imaging (RS-fMRI) may serve as a method to assess and predict changes in the motor network. Objective. The authors examined the effects of upper-extremity robot-Assisted rehabilitation (MANUS) versus an electroencephalography-based brain computer interface setup with motor imagery (MI EEG-BCI) and compared pretreatment and posttreatment RS-fMRI. Methods. In all, 9 adults with upper-extremity paresis were trained for 4 weeks with a MANUS shoulder-elbow robotic rehabilitation paradigm. In 3 participants, robot-Assisted movement began if no voluntary movement was initiated within 2 s. In 6 participants, MI-BCI-based movement was initiated if motor imagery was detected. RS-fMRI and Fugl-Meyer (FM) upper-extremity motor score were assessed before and after training. Results. The individual gain in FM scores over 12 weeks could be predicted from functional connectivity changes (FCCs) based on the pre-post differences in RS-fMRI measurements. Both the FM gain and FCC were numerically higher in the MI-BCI group. Increases in FC of the supplementary motor area, the contralesional and ipsilesional motor cortex, and parts of the visuospatial system with mostly association cortex regions and the cerebellum correlated with individual upper-extremity function improvement. Conclusion. FCC may predict the steepness of individual motor gains. Future training could therefore focus on directly inducing these beneficial increases in FC. Evaluation of the treatment groups suggests that MI is a potential facilitator of such neuroplasticity. © 2013 The Author(s). Source

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