Voluntary Brain Regulation and Communication with ECoG-Signals (2008)
Hinterberger, T., Widmann, G., Lal, T.N., Hill, J., Tangermann, M., Rosenstiel, W., ...
Brain–computer interfaces (BCIs) can be used for communication in writing without muscular activity or for learning to control seizures by voluntary regulation of brain signals such as the...
Voluntary Brain Regulation and Communication with ECoG-Signals (2008)
Hinterberger, T., Widmann, G., Lal, T.N., Hill, J., Tangermann, M., Rosenstiel, W., ...
Braincomputer interfaces (BCIs) can be used for communication in writing without muscular activity or for learning to control seizures by voluntary regulation of brain signals such as the...
Brain Computer Interfaces for Communication in Paralysis: a Clinical-Experimental Approach (2007)
Hinterberger, T., Nijboer, F., Kübler, A., Matuz, T., Furdea, A., Mochty, U., ...
An overview of different approaches to brain-computer interfaces (BCIs) developed in our laboratory is given. An important clinical application of BCIs is to enable communication or environmental...
Lal, T.N., Chapelle, O., Weston, J., Elisseeff, A., Guyon, I., Gunn, S., ...
Embedded methods are a relatively new approach to feature selection. Unlike filter methods, which do not incorporate learning, and wrapper approaches, which can be used with arbitrary classifiers, in...
Combining a Filter Method with SVMs (2006)
Lal, T.N., Chapelle, O., Schölkopf, B., Guyon, I., Gunn, S., Nikravesh, M., ...
Our goal for the competition (feature selection competition NIPS 2003) was to evaluate the usefulness of simple machine learning techniques. We decided to use the correlation criteria as a feature...
Time-Dependent Demixing of Task-Relevant EEG Signals (2006)
Hill, N.J., Farquhar, J., Lal, T.N., Schölkopf, B.
Given a spatial filtering algorithm that has allowed us to identify task-relevant EEG sources, we present a simple approach for monitoring the activity of these sources while remaining relatively...
Regularised CSP for Sensor Selection in BCI (2006)
Farquhar, J., Hill, N.J., Lal, T.N., Schölkopf, B.
The Common Spatial Pattern (CSP) algorithm is a highly successful method for efficiently calculating spatial filters for brain signal classification. Spatial filtering can improve classification...
Hill, N.J., Lal, T.N., Schröder, M., Hinterberger, T., Wilhelm, B., Nijboer, F., ...
We summarize results from a series of related studies that aim to develop a motor-imagery-based brain-computer interface using a single recording session of EEG or ECoG signals for each subject. We...
Methods Towards Invasive Human Brain Computer Interfaces (2005)
Lal, T.N., Hinterberger, T., Widman, G., Schröder, M., Hill, J., Rosenstiel, W., ...
During the last ten years there has been growing interest in the development of Brain Computer Interfaces (BCIs). The field has mainly been driven by the needs of completely paralyzed patients to...
Robust EEG Channel Selection Across Subjects for Brain Computer Interfaces (2005)
Schröder, M., Lal, T.N., Hinterberger, T., Bogdan, M., Hill, J., Birbaumer, N., ...
Most EEG-based Brain Computer Interface (BCI) paradigms come along with specific electrode positions, e.g.~for a visual based BCI electrode positions close to the primary visual cortex are used. For...
An Auditory Paradigm for Brain--Computer Interfaces (2005)
Hill, N.J., Lal, T.N., Bierig, K., Birbaumer, N., Schölkopf, B., Saul, L.K., ...
Motivated by the particular problems involved in communicating with "locked-in" paralysed patients, we aim to develop a brain-computer interface that uses auditory stimuli. We describe a paradigm...
A Brain Computer Interface with Online Feedback based on Magnetoencephalography (2005)
Lal, T.N., Schröder, M., Hill, J., Preissl, H., Hinterberger, T., Mellinger, J., ...
The aim of this paper is to show that machine learning techniques can be used to derive a classifying function for human brain signal data measured by magnetoencephalography (MEG), for the use in a...
Learning with Local and Global Consistency (2004)
Zhou,D., Bousquet,O., Lal,T.N., Weston,J., Schölkopf,B.
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised...
Hilbertian Metrics on Probability Measures and their Application in SVM's (2004)
Hein,H., Lal,T.N., Bousquet,O.
The goal of this article is to investigate the field of Hilbertian metrics on probability measures. Since they are very versatile and can therefore be applied in various problems they are of great...
Selective Attention to Auditory Stimuli: A Brain-Computer Interface Paradigm (2004)
Hill,N.J., Lal,T.N., Schröder,M., Hinterberger,T., Birbaumer,N., Schölkopf,B.
Attentional Modulation of Auditory Event-Related Potentials in a Brain-Computer Interface (2004)
Hill,N.J., Lal,T.N., Bierig,K., Birbaumer,N., Schölkopf,B.
Motivated by the particular problems involved in communicating with "locked-in" paralysed patients, we aim to develop a brain-computer interface that uses auditory stimuli. We describe a paradigm...
Support Vector Channel Selection in BCI (2004)
Lal,T.N., Schröder,M., Hinterberger,T., Weston,J., Bogdan,M., Birbaumer,N., ...
Designing a Brain Computer Interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying...
Learning with Local and Global Consistency (2004)
Zhou, D., Bousquet, O., Lal, T.N., Weston, J., Schölkopf, B., Thrun, S., ...
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised...
Hilbertian Metrics on Probability Measures and their Application in SVM's (2004)
Hein, H., Lal, T.N., Bousquet, O., Rasmussen, C. E., Bülthoff, H. H., Giese, M., ...
The goal of this article is to investigate the field of Hilbertian metrics on probability measures. Since they are very versatile and can therefore be applied in various problems they are of great...
EEG Channel Selection for Brain Computer Interface Systems Based on Support Vector Methods (2004)
Schröder, M., Lal, T.N., Bogdan, M., Schölkopf, B., Bülthoff, H.H., Mallot, H.A., ...
Selective Attention to Auditory Stimuli: A Brain-Computer Interface Paradigm (2004)
Hill, N.J., Lal, T.N., Schröder, M., Hinterberger, T., Birbaumer, N., Schölkopf, B., ...
Attentional Modulation of Auditory Event-Related Potentials in a Brain-Computer Interface (2004)
Hill, N.J., Lal, T.N., Bierig, K., Birbaumer, N., Schölkopf, B.
Motivated by the particular problems involved in communicating with "locked-in" paralysed patients, we aim to develop a brain-computer interface that uses auditory stimuli. We describe a paradigm...
Support Vector Channel Selection in BCI (2004)
Lal, T.N., Schröder, M., Hinterberger, T., Weston, J., Bogdan, M., Birbaumer, N., ...
Designing a Brain Computer Interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying...