Non-linear analysis was applied on MEG signals of Alzheimer Disease (AD) patients in order to inv... more Non-linear analysis was applied on MEG signals of Alzheimer Disease (AD) patients in order to investigate the underlying complexity of the brain dynamics. A Single channel SQUID was used to record the MEG signals in 9 AD patients and 5 normal individuals. The magnetic activity, for each patient, was recorded from a total of 64 points of the skull (32 points from each temporal lobe). Nonlinear analysis was applied in the abnormal MEG points of the brain. In AD patients some recorded points were found with high amplitudes and low frequencies in magnetic activity. By applying nonlinear analysis in these records low values in the correlation dimension D of the reconstructed phase space were found. SQUID obtained MEG signaling from brains of AD patients showed a lower complexity compared to the brain of normal subjects.
s 79 TMS (VISOR from ANT). The coil position and orientation for each TMS pulse is saved by VISOR... more s 79 TMS (VISOR from ANT). The coil position and orientation for each TMS pulse is saved by VISOR. These coil positions are automatically converted into the SimNIBS format and used to carry out electric field simulations for each coil position. First results from TMS-motor mapping show how the simulated electric fields can be correlated with the motor evoked potentials of individual muscles. Conclusion.— These results demonstrate that advanced electric field simulations can be applied routinely in experiments involving TMS. In addition, the application to TMS-motor mapping allows validating these simulations in a brain system that is well characterized. Reference [1] Thielscher A, Opitz A, Windhoff M. Impact of the gyral geometry on the electric field induced by transcranial magnetic stimulation. Neuroimage 2011;54:234—43. http://dx.doi.org/10.1016/j.neucli.2012.11.033
Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filt... more Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filter (CSP) as preprocessing step before feature extraction and classification. The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect. In order to reduce the amount of calibration data that is needed for a new subject, one can apply multitask (from now on called multisubject) machine learning techniques to the preprocessing phase. Here, the goal of multisubject learning is to learn a spatial filter for a new subject based on its own data and that of other subjects. This paper outlines the details of the multitask CSP algorithm and shows results on two data sets. In certain subjects a clear improvement can be seen, especially when the number of training trials is relatively low.
Brain-Computer Interfaces (BCI) are a new kind of humanmachine interfaces emerging on the horizon... more Brain-Computer Interfaces (BCI) are a new kind of humanmachine interfaces emerging on the horizon. They form a communication pathway between the brain and a machine. This can be achieved by measuring brain signals and translate them directly into control commands. Such a system allows people with severe motor disabilities to manipulate their environment in an alternative way. However there’s still a lot of work to be done to make it usable in daily life. In this contribution we give a tutorial overview of existing methods and possible applications.
Algorithmic information transfer has been theoretically shown to detect directed dependency or ca... more Algorithmic information transfer has been theoretically shown to detect directed dependency or causality in bivariate signals in an optimal way. Here its practical use in a non-ideal setting is investigated. First we show the close connection to the common tests for directed interactions. Subsequently, consequences of model non-ideality is described and a deep connection between regularization and (directed) independence tests is concluded. Thereafter, a directed independence test is constructed to detect the presence of phase coupling between two oscillators using support vector regression. Finally the algorithm is used to determine moments of interaction for dynamic-coupled harmonic oscillators, by exploiting full length information of the signals.
Motor imagery based brain-computer interfaces mostly use the common spatial pattern filter (CSP) ... more Motor imagery based brain-computer interfaces mostly use the common spatial pattern filter (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm and therefore needs subject specific training data for calibration, which is time consuming to collect. Instead of letting all that data and effort go to waste, the data of other subjects could be used to further improve results for new subjects. To this end, we employ some ideas of multitask learning and apply it to the preprocessing phase. In some of the subjects a clear improvement can be seen by using information of other subjects.
Non-linear analysis was applied on MEG signals of Alzheimer Disease (AD) patients in order to inv... more Non-linear analysis was applied on MEG signals of Alzheimer Disease (AD) patients in order to investigate the underlying complexity of the brain dynamics. A Single channel SQUID was used to record the MEG signals in 9 AD patients and 5 normal individuals. The magnetic activity, for each patient, was recorded from a total of 64 points of the skull (32 points from each temporal lobe). Nonlinear analysis was applied in the abnormal MEG points of the brain. In AD patients some recorded points were found with high amplitudes and low frequencies in magnetic activity. By applying nonlinear analysis in these records low values in the correlation dimension D of the reconstructed phase space were found. SQUID obtained MEG signaling from brains of AD patients showed a lower complexity compared to the brain of normal subjects.
s 79 TMS (VISOR from ANT). The coil position and orientation for each TMS pulse is saved by VISOR... more s 79 TMS (VISOR from ANT). The coil position and orientation for each TMS pulse is saved by VISOR. These coil positions are automatically converted into the SimNIBS format and used to carry out electric field simulations for each coil position. First results from TMS-motor mapping show how the simulated electric fields can be correlated with the motor evoked potentials of individual muscles. Conclusion.— These results demonstrate that advanced electric field simulations can be applied routinely in experiments involving TMS. In addition, the application to TMS-motor mapping allows validating these simulations in a brain system that is well characterized. Reference [1] Thielscher A, Opitz A, Windhoff M. Impact of the gyral geometry on the electric field induced by transcranial magnetic stimulation. Neuroimage 2011;54:234—43. http://dx.doi.org/10.1016/j.neucli.2012.11.033
Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filt... more Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filter (CSP) as preprocessing step before feature extraction and classification. The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect. In order to reduce the amount of calibration data that is needed for a new subject, one can apply multitask (from now on called multisubject) machine learning techniques to the preprocessing phase. Here, the goal of multisubject learning is to learn a spatial filter for a new subject based on its own data and that of other subjects. This paper outlines the details of the multitask CSP algorithm and shows results on two data sets. In certain subjects a clear improvement can be seen, especially when the number of training trials is relatively low.
Brain-Computer Interfaces (BCI) are a new kind of humanmachine interfaces emerging on the horizon... more Brain-Computer Interfaces (BCI) are a new kind of humanmachine interfaces emerging on the horizon. They form a communication pathway between the brain and a machine. This can be achieved by measuring brain signals and translate them directly into control commands. Such a system allows people with severe motor disabilities to manipulate their environment in an alternative way. However there’s still a lot of work to be done to make it usable in daily life. In this contribution we give a tutorial overview of existing methods and possible applications.
Algorithmic information transfer has been theoretically shown to detect directed dependency or ca... more Algorithmic information transfer has been theoretically shown to detect directed dependency or causality in bivariate signals in an optimal way. Here its practical use in a non-ideal setting is investigated. First we show the close connection to the common tests for directed interactions. Subsequently, consequences of model non-ideality is described and a deep connection between regularization and (directed) independence tests is concluded. Thereafter, a directed independence test is constructed to detect the presence of phase coupling between two oscillators using support vector regression. Finally the algorithm is used to determine moments of interaction for dynamic-coupled harmonic oscillators, by exploiting full length information of the signals.
Motor imagery based brain-computer interfaces mostly use the common spatial pattern filter (CSP) ... more Motor imagery based brain-computer interfaces mostly use the common spatial pattern filter (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm and therefore needs subject specific training data for calibration, which is time consuming to collect. Instead of letting all that data and effort go to waste, the data of other subjects could be used to further improve results for new subjects. To this end, we employ some ideas of multitask learning and apply it to the preprocessing phase. In some of the subjects a clear improvement can be seen by using information of other subjects.
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