Affective Brain-Computer Interface

Contact: Stefan Ehrlich

Description

Emotions and related brain processes have long been neglected in neuroscience and are yet not well understood. Contemporary theories and models are often contradictive and strongly depending on the scientific context. With the rise of potential applications in purely engineering areas both, the fields of neuroscience and engineering have recently gained substantial interest in gaining a better understanding of emotions (e.g. to introduce emphatic abilities into machines; ref. Affective Computing).

Furthermore, emotions are strongly interrelated with cognitive brain processes and play a fundamental role in decision making and reasoning. Emotions are therefore a significantly important part to understand and model higher-order brain processes in general. This research area focuses on a better fundamental understanding of emotions and related brain processes. Modern neuroimaging technologies, such as Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) can be used to detect links between emotions and relating neural correlates.

Due to EEG’s high temporal resolution, it is particularly promising to establish real-time Brain-Computer Interfaces (BCI). BCI technology provides an interesting novel avenue to study human affect in a closed-loop fashion by providing affective feedback. This research area is located on the verge of several disciplines bridging cognitive neuroscience and biomedical engineering.

Research Topics

  • Fundamental research on emotions and its formulation in theoretical/mathematical/computational models building links to relating brain mechanisms
  • Establishing affective interaction between humans and machines through BCI technology
  • BCI-based medical applications with a focus on affective and developmental disorders (e.g. depression, schizophrenia, autism).