Dr. Bettina Sorger

B.SorgerDepartment of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands

Bettina Sorger, currently assistant professor at the Cognitive Neuroscience Department at the Faculty of Psychology and Neuroscience at Maastricht University (The Netherlands), studied psychology at Cologne University (Germany) and worked from 2005 to 2009 on a PhD project developing brain-computer interfaces (BCIs) based on real-time functional magnetic resonance imaging (fMRI) at Maastricht University. Subsequently, she joined the Coma Science Group at the University of Li├Ęge (Belgium). Since her return to Maastricht University in 2011, she has mainly focused on extending fMRI-based communication BCIs to various sensory modalities and transferring fMRI methods to mobile functional near-infrared spectroscopy. Another current research focus is implementing hemodynamic brain signals for neurofeedback (therapy).

Exploiting hemodynamic brain signals for motor-independent communication: from fMRI to mobile fNIRS

Human communication entirely depends on the functional integrity of the neuromuscular system. In the so-called ‘locked-in’ syndrome (LIS), severely paralyzed patients become incapable of naturally interacting with their surroundings – while being fully conscious and awake. This results in diagnostic, practical and ethical problems. Providing such patients with motor-independent means of communication therefore is of high importance. This can be realized via so-called ‘brain-computer interfaces’ (BCIs) circumventing the muscular system by using brain signals associated with preserved brain functions. For the last 25 years, BCI research has focused on implementing neuroelectric signals. Predominantly, BCIs based on electroencephalography (EEG) were developed and applied to severely motor-impaired (including LIS) patients with remarkable success. However many of these BCI systems require intensive training and not all patients achieve proficiency in EEG-based BCI control. Recently, also blood flow-based (hemodynamic) methods, such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) have been investigated regarding their BCI suitability. In this presentation, the general principles and approaches for using hemodynamic brain signals for brain-based communication will be introduced and related research will be presented. Moreover, Pros and Cons of implementing brain hemodynamics for brain-computer interfacing will be addressed. Finally, potential advancement will be discussed.