| Home > Departments > Center for Experimental Medicine > Department of Neurophysiology and Pathophysiology > Reasearch Groups > Computational Modeling and BCI
Research Group:
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| [head of group:] | |
| Dr.rer.nat. Alexander Maye | |
| [group members:] | |
| Dr.med. Jens Kleesiek Doctoral candidate (Dr.rer.nat.), |
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| Johannes Möller Diploma student, |
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| Malte Groth Bachelor student, |
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| Malte Sengelmann Bachelor student, |
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| [research topics:] | |
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| [Brain-Computer Interfaces (BCI):] | |
| [Neurofeedback:] | |
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Neurofeedback allows a person to observe his or her own brain activity by
giving visual or auditory feedback. This allows the user to develop strategies
to adjust the own mental activity. This can be employed to bring the person
into a desired cognitive or physiological state (e.g., relaxing), or to
control a computer. Currently we investigate the potential of neurofeedback as
a training method for BCI systems. |
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| [Computational models of oscillatory brain dynamics:] | |
| Oscillatory dynamics of neuronal activity is a commonly observed phenomenon in neurophysiological experiments. The properties of networks of coupled oscillators have been investigated in a number of computational models. Current hypotheses about the functional roles of oscillations consider it as a gating mechanism, a mechanism for modulating sensory processing, or a system of internal reference clocks. Still there are many open questions about mechanisms of information processing in oscillator networks and the role of oscillations for generating behavior. Our projects in this area aim at elucidating computational mechnaisms of oscillatory networks, developing network activity analysis methods, and modelling oscillatory effects found in EEG experiments on size perception. | |
| [Computational models of cognition:] | |
| As part of several cooperations supported by the EU, we are involved in projects implementing robot systems that combine visual and auditory information processing to achieve orienting behaviour, object recognition, navigation, and memory formation. The projects combine a synthetic biorobotics approach with neurophysiological experiments in humans, and computational modeling that allows to identify relevant information processing principles. | |
| [Computational models of spiking activity in basal ganglia:] | |
| In collaboration with the [Basal Ganglia Physiology link] research group we investigate the oscillatory activity of the basal ganglia using computational models. (Patho-)physiological data derived from intraoperative microelectrode recordings from patients suffering from Parkinson's disease are incorporated into the models to obtain biological realistic simulations. Furthermore, e.g. varying neurotransmitter concentration or connectivity of neuron populations can be used to test and valid hypotheses regarding the feedback loop of the diseased basal ganglia. | |
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