% % This file was created by the TYPO3 extension % bib % --- Timezone: CET % Creation date: 2024-03-28 % Creation time: 11-42-24 % --- Number of references % 16 % @Phdthesis { Kohl2013, title = {Blind separation of dependent source signals for MEG sensory stimulation experiments}, year = {2013}, tags = {8.42,Gehirn,SingleTrial}, school = {TU Berlin}, type = {PhD Thesis}, author = {Kohl, F} } @Article { Kohl2010, title = {Shifted factor analysis for the separation of evoked dependent MEG signals}, journal = {Physics in medicine and biology}, year = {2010}, volume = {55}, number = {15}, pages = {4219--30}, abstract = {Decomposition of evoked magnetoencephalography (MEG) data into their underlying neuronal signals is an important step in the interpretation of these measurements. Often, independent component analysis (ICA) is employed for this purpose. However, ICA can fail as for evoked MEG data the neuronal signals may not be statistically independent. We therefore consider an alternative approach based on the recently proposed shifted factor analysis model, which does not assume statistical independence of the neuronal signals. We suggest the application of this model in the time domain and present an estimation procedure based on a Taylor series expansion. We show in terms of synthetic evoked MEG data that the proposed procedure can successfully separate evoked dependent neuronal signals while standard ICA fails. Latency estimation of neuronal signals is an inherent part of the proposed procedure and we demonstrate that resulting latency estimates are superior to those obtained by a maximum likelihood method.}, keywords = {Evoked Potentials,Humans,Magnetoencephalography,Magnetoencephalography: methods,Models, Statistical,Neurons,Neurons: cytology,SingleTrial}, tags = {8.42, Gehirn, SingleTrial}, web_url = {http://iopscience.iop.org/article/10.1088/0031-9155/55/15/002}, publisher = {IOP Publishing}, language = {en}, ISSN = {1361-6560}, DOI = {10.1088/0031-9155/55/15/002}, author = {Kohl, F and W{\"u}bbeler, G and Kolossa, D and B{\"a}r, M and Orglmeister, R and Elster, C} } @Article { Leistner2010, title = {Magnetoencephalography discriminates modality-specific infraslow signals less than 0.1 Hz}, journal = {NeuroReport}, year = {2010}, volume = {21}, number = {3}, pages = {196--200}, tags = {8.42, Gehirn}, author = {Leistner, S and Sander, T and W{\"u}bbeler, G and Link, A and Elster, C and Curio, G and Trahms, L and Mackert, B M} } @Article { Sander2010, title = {Recent advances in modeling and analysis of bioelectric and biomagnetic sources}, journal = {Biomedizinische Technik. Biomedical engineering}, year = {2010}, volume = {55}, number = {2}, pages = {65--76}, abstract = {Determining the centers of electrical activity in the human body and the connectivity between different centers of activity in the brain is an active area of research. To understand brain function and the nature of cardiovascular diseases requires sophisticated methods applicable to non-invasively measured bioelectric and biomagnetic data. As it is difficult to solve for all unknown parameters at once, several strains of data analysis have been developed, each trying to solve a different part of the problem and each requiring a different set of assumptions. Current trends and results from major topics of electro- and magnetoencephalographic data analysis are presented here together with the aim of stimulating research into the unification of the different approaches. The following topics are discussed: source reconstruction using detailed finite element modeling to locate sources deep in the brain; connectivity analysis for the quantification of strength and direction of information flow between activity centers, preferably incorporating an inverse solution; the conflict between the statistical independence assumption of sources and a possible connectivity; the verification and validation of results derived from non-invasively measured data through animal studies and phantom measurements. This list already indicates the benefits of a unified view.}, keywords = {Action Potentials,Action Potentials: physiology,Animals,Brain,Brain Mapping,Brain Mapping: methods,Brain Mapping: trends,Brain: physiology,Computer Simulation,Electroencephalography,Electroencephalography: methods,Electroencephalography: trends,Electromagnetic Fields,Humans,Models,Neurological,Radiometry,Radiometry: methods,Radiometry: trends,SingleTrial}, tags = {8.42, Gehirn}, web_url = {http://www.degruyter.com/view/j/bmte.2010.55.issue-2/bmt.2010.027/bmt.2010.027.xml}, ISSN = {1862-278X}, DOI = {10.1515/BMT.2010.027}, author = {Sander, T H and Kn{\"o}sche, T R and Schl{\"o}gl, A and Kohl, F and Wolters, C H and Haueisen, J and Trahms, L} } @Article { Link2007c, title = {Comparing a template approach and complex bandpass filtering for single-trial analysis of auditory evoked M100}, journal = {Biomedizinische Technik. Biomedical engineering}, year = {2007}, volume = {52}, number = {1}, pages = {106--10}, abstract = {Two methods for single-trial analysis were compared, an established parametric template approach and a recently proposed non-parametric method based on complex bandpass filtering. The comparison was carried out by means of pseudo-real simulations based on magnetoencephalography measurements of cortical responses to auditory signals. The comparison focused on amplitude and latency estimation of the M100 response. The results show that both methods are well suited for single-trial analysis of the auditory evoked M100. While both methods performed similarly with respect to latency estimation, the non-parametric approach was observed to be more robust for amplitude estimation. The non-parametric approach can thus be recommended as an additional valuable tool for single-trial analysis.}, keywords = {Algorithms,Auditory,Auditory: physiology,Computer-Assisted,Computer-Assisted: methods,Diagnosis, Computer-Assisted,Diagnosis, Computer-Assisted: methods,Electroencephalography,Electroencephalography: methods,Evoked Potentials, Auditory,Evoked Potentials, Auditory: physiology,Likelihood Functions,Reproducibility of Results,Sample Size,Sensitivity and Specificity,Signal Processing, Computer-Assisted}, tags = {8.42, Gehirn}, web_url = {http://www.ncbi.nlm.nih.gov/pubmed/17313344}, ISSN = {0013-5585}, DOI = {10.1515/BMT.2007.020}, author = {Link, A and Burghoff, M and Salajegheh, A and Poeppel, D and Trahms, L and Elster, C} } @Article { Wubbeler2007a, title = {Latency analysis of single auditory evoked M100 responses by spatio-temporal filtering}, journal = {Physics in medicine and biology}, year = {2007}, volume = {52}, number = {15}, pages = {4383--92}, abstract = {Appropriate spatial filtering followed by temporal filtering is well suited for the single-trial analysis of multi-channel magnetoencephalogram or electroencephalogram recordings. This is demonstrated by the results of a single-trial latency analysis obtained for auditory evoked M100 responses from nine subjects using two different stimulation frequencies. Spatial filters were derived automatically from the data via noise-adjusted principle component analysis, and single-trial latencies were estimated from the signal phase after complex bandpass filtering. For each of the two stimulation frequencies, estimated single-trial latencies were consistent with results obtained from a standard approach using averaged evoked responses. The quality of the estimated single-trial latencies was additionally assessed by their ability to separate between the two different stimulation frequencies. As a result, more than 80{\%} of the single trials can be classified correctly by their estimated latencies.}, keywords = {Acoustic Stimulation,Acoustic Stimulation: methods,Algorithms,Diagnosis, Computer-Assisted,Diagnosis, Computer-Assisted: methods,Evoked Potentials, Auditory,Evoked Potentials, Auditory: physiology,Humans,Magnetoencephalography,Magnetoencephalography: methods,Pitch Perception,Pitch Perception: physiology,Reaction Time,Reaction Time: physiology,Reproducibility of Results,Sensitivity and Specificity}, tags = {8.42, Gehirn}, web_url = {http://www.ncbi.nlm.nih.gov/pubmed/17634639}, ISSN = {0031-9155}, DOI = {10.1088/0031-9155/52/15/002}, author = {W{\"u}bbeler, G and Link, A and Burghoff, M and Trahms, L and Elster, C} } @Article { Leistner2006, title = {Tonic neuronal activation during simple and complex finger movements analyzed by DC-magnetoencephalography}, journal = {Neuroscience letters}, year = {2006}, volume = {394}, number = {1}, pages = {42--7}, abstract = {Functional neuroimaging techniques map neuronal activation indirectly via local concomitant cortical vascular/metabolic changes. In a complementary approach, DC-magnetoencephalography measures neuronal activation dynamics directly, notably in a time range of the slow vascular/metabolic response. Here, using this technique neuronal activation dynamics and patterns for simple and complex finger movements are characterized intraindividually: in 6/6 right-handed subjects contralateral prolonged (30 s each) complex self-paced sequential finger movements revealed stronger field amplitudes over the pericentral sensorimotor cortex than simple movements. A consistent lateralization for contralateral versus ipsilateral finger movements was not found (4/6). A subsequent sensory paradigm focused on somatosensory afferences during the motor tasks and the reliability of the measuring technique. In all six subjects stable sustained neuronal activation during electrical median nerve stimulation was recorded. These neuronal quasi-tonic activation characteristics provide a new non-invasive neurophysiological measure to interpret signals mapped by functional neuroimaging techniques.}, keywords = {Adult,Brain Mapping,Evoked Potentials, Somatosensory,Evoked Potentials, Somatosensory: physiology,Evoked Potentials, Somatosensory: radiation effect,Female,Fingers,Fingers: physiology,Functional Laterality,Functional Laterality: physiology,Humans,Magnetoencephalography,Male,Motor Cortex,Motor Cortex: physiology,Motor Cortex: radiation effects,Movement,Movement: physiology,Movement: radiation effects,Psychomotor Performance,Psychomotor Performance: physiology,Psychomotor Performance: radiation effects,Somatosensory,Somatosensory: physiology,Somatosensory: radiation effect}, tags = {8.42, Gehirn}, web_url = {http://www.sciencedirect.com/science/article/pii/S0304394005011523}, ISSN = {0304-3940}, DOI = {10.1016/j.neulet.2005.10.004}, author = {Leistner, S and W{\"u}bbeler, G and Trahms, L and Curio, G and Mackert, B M} } @Inproceedings { Wuebbeler2006c, title = {Single-trial latency analysis of the auditory evoked M100 improved by spatial filtering}, year = {2006}, tags = {8.42, Gehirn}, booktitle = {Proc. Biomed. Tech.}, author = {W{\"u}bbeler, G and Link, A and Burghoff, M and Trahms, L and Elster, C} } @Article { Burghoff2005, title = {A template-free approach for determining the latency of single events of auditory evoked M100}, journal = {Physics in medicine and biology}, year = {2005}, volume = {50}, number = {3}, pages = {N43--8}, abstract = {The phase of the complex output of a narrow band Gaussian filter is taken to define the latency of the auditory evoked response M100 recorded by magnetoencephalography. It is demonstrated that this definition is consistent with the conventional peak latency. Moreover, it provides a tool for reducing the number of averages needed for a reliable estimation of the latency. Single-event latencies obtained by this procedure can be used to improve the signal quality of the conventional average by latency adjusted averaging.}, keywords = {Evoked Potentials, Auditory,Magnetoencephalography,Magnetoencephalography: methods,Models, Theoretical,Normal Distribution,Time Factors}, tags = {8.42, Gehirn}, web_url = {http://www.ncbi.nlm.nih.gov/pubmed/15773733}, ISSN = {0031-9155}, DOI = {10.1088/0031-9155/50/3/N04}, author = {Burghoff, M and Link, A and Salajegheh, A and Elster, C and Poeppel, D and Trahms, L} } @Article { Link2004c, title = {Vergleich von Template- und komplexem Filteransatz bei der Analyse evozierter Einzelereignisse}, journal = {Biomedizinische Technik}, year = {2004}, volume = {49}, number = {2}, pages = {306}, tags = {8.42, Gehirn}, url = {http://www.zbmed.de/ccmedimages/2004/47249.pdf}, author = {Link, A and Elster, C and Burghoff, M and Trahms, L} } @Article { Salajegheh2004, title = {Systematic latency variation of the auditory evoked M100: from average to single-trial data}, journal = {NeuroImage}, year = {2004}, volume = {23}, number = {1}, pages = {288 - 295}, abstract = {Standard analyses of neurophysiologically evoked response data rely on signal averaging across many epochs associated with specific events. The amplitudes and latencies of these averaged events are subsequently interpreted in the context of the given perceptual, motor, or cognitive tasks. Can such critical timing properties of event-related responses be recovered from single-trial data? Here, we make use of the {M100} latency paradigm used in previous magnetoencephalography (MEG) research to evaluate a novel single-trial analysis approach. Specifically, the latency of the auditory evoked {M100} varies systematically with stimulus frequency over a well-defined time range (lower frequencies, e.g., 125 Hz, yield up to 25 ms longer latencies than higher frequencies, e.g., 1000 Hz). Here, we show that the complex filtering approach to single-trial analysis recovers this key characteristic of the {M100} response, as well as some other important response properties relating to lateralization. The results illustrate (i) the utility of the complex filtering method and (ii) the potential of the {M100} latency to be used for stimulus encoding, since the relevant variation can be observed in single trials.}, keywords = {Single-trial EP analysis}, tags = {8.42, Gehirn}, web_url = {http://www.sciencedirect.com/science/article/pii/S1053811904003015}, ISSN = {1053-8119}, DOI = {10.1016/j.neuroimage.2004.05.022}, author = {Salajegheh, A and Link, A and Elster, C and Burghoff, M and Sander, T and Trahms, L and Poeppel, D} } @Article { Link2003, title = {Analyse von Amplitude und Latenz visuell stimulierter MEG Signale}, journal = {Biomedizinische Technik}, year = {2003}, volume = {48}, number = {1}, tags = {8.42, Gehirn}, url = {http://dx.doi.org/10.1515/bmte.2003.48.s1.182}, DOI = {10.1515/bmte.2003.48.s1.182}, author = {Link, A and Elster, C and Sander, T and Lueschow, A and Curio, G and Trahms, L} } @Article { Link2002, title = {MEG-Analysis using the Hilbert transform}, journal = {Biomedizinische Technik}, year = {2002}, volume = {47}, number = {1}, tags = {8.42, Gehirn}, DOI = {10.1515/bmte.2002.47.s1b.577}, author = {Link, A and Elster, C and Sander, T and Lueschow, A and Curio, G and Trahms, L} } @Article { Mackert2001, title = {Non-invasive 'single-trial' monitoring of human movement-related brain activation based on DC- magnetoen cephalography}, journal = {Neuroreport}, year = {2001}, volume = {12}, number = {8}, pages = {1689-92}, tags = {8.42,Gehirn}, DOI = {10.1097/00001756-200106130-00034}, author = {Mackert, B M and W{\"u}bbeler, G and Leistner, S and Trahms, L and Curio, G} } @Article { Wuebbeler2000, title = {Independent component analysis of noninvasively recorded cortical magnetic DC-fields in humans}, journal = {Biomedical Engineering, IEEE Transactions on}, year = {2000}, volume = {47}, number = {5}, pages = {594-599}, abstract = {We apply a recently developed multivariate statistical data analysis technique-so called blind source separation (BSS) by independent component analysis-to process magnetoencephalogram recordings of near-DC fields. The extraction of near-DC fields from MEG recordings has great relevance for medical applications since slowly varying DC-phenomena have been found, e.g., in cerebral anoxia and spreading depression in animals. Comparing several BSS approaches, it turns out that an algorithm based on temporal decorrelation successfully extracted a DC-component which was induced in the auditory cortex by presentation of music. The task is challenging because of the limited amount of available data and the corruption by outliers, which makes it an interesting real-world testbed for studying the robustness of ICA methods.}, keywords = {decorrelation;feature extraction;hearing;magnetoencephalography;medical signal processing;music;statistical analysis;DC-component;ICA method robustness;MEG recordings;animals;auditory cortex;blind source separation;cerebral anoxia;humans;independent component analysis;magnetoencephalogram recordings;medical applications;multivariate statistical data analysis technique;music;near-DC field extraction;noninvasively recorded cortical magnetic DC-fields;outlier;real-world testbed;slowly varying DC-phenomena;spreading depression;temporal decorrelation;Blind source separation;Data analysis;Data mining;Humans;Independent component analysis;Magnetic analysis;Magnetic recording;Magnetic separation;Medical services;Source separation;Acoustic Stimulation;Algorithms;Artifacts;Auditory Cortex;Evoked Potentials, Auditory;Humans;Magnetoencephalography;Signal Processing, Computer-Assisted}, tags = {8.42, Gehirn}, ISSN = {0018-9294}, DOI = {10.1109/10.841331}, author = {W{\"u}bbeler, G and Ziehe, A and Mackert, B-M and M{\"u}ller, K-R and Trahms, L and Curio, C} } @Article { Mackert1999, title = {Non-invasive long-term recordings of cortical ''direct current'' activity in humans using magnetoencephalography}, journal = {Neuroscience Letters}, year = {1999}, volume = {273}, number = {3}, pages = {159--162}, abstract = {Recently, biomagnetic fields below 0.1 Hz arising from nerve or muscle injury currents have been measured non-invasively using superconducting quantum interference devices (SQUIDs). Here we report first long-term recordings of cortical direct current (DC) fields in humans based on a horizontal modulation (0.4 Hz) of the body and, respectively, head position beneath the sensor array: near-DC fields with amplitudes between 90 and 540 fT were detected in 5/5 subjects over the auditory cortex throughout prolonged stimulation periods (here: 30 s) during which subjects were listening to concert music. These results prove the feasibility to record non-invasively low amplitude near-DC magnetic fields of the human brain and open the perspective for studies on DC-phenomena in stroke, such as anoxic depolarization or peri-infarct depolarization, and in migraine patients.}, keywords = {Anoxic depolarization,Auditory cortex,Direct current-magnetoencephalography,Music,Spreading depression,Superconducting quantum interference device,Sustained fields}, tags = {8.42, Gehirn}, web_url = {http://www.sciencedirect.com/science/article/pii/S0304394099006576}, ISSN = {03043940}, DOI = {10.1016/S0304-3940(99)00657-6}, author = {Mackert, B M and W{\"u}bbeler, G and Burghoff, M and Marx, P and Trahms, L and Curio, G} }