Benjamin Blankertz
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View article: Beyond beta rhythms: subthalamic aperiodic broadband power scales with Parkinson's disease severity–a cross-sectional multicentre study
Beyond beta rhythms: subthalamic aperiodic broadband power scales with Parkinson's disease severity–a cross-sectional multicentre study Open
This work was supported by Deutsche Forschungsgemeinschaft (German Research Foundation) Project ID 424778381 TRR 295 "ReTune". H.A. is supported by NIHR UCLH BRC. This work was supported by an MRC Clinician Scientist Fellowship (MR/W024810…
View article: Beyond beta rhythms: Aperiodic broadband power reflects Parkinson’s disease severity–a multicenter study
Beyond beta rhythms: Aperiodic broadband power reflects Parkinson’s disease severity–a multicenter study Open
Parkinson’s disease is linked to increased beta oscillations in the subthalamic nucleus, which correlate with motor symptoms. However, findings across studies have varied. Our standardized analysis of multicenter datasets shows that small …
View article: Multimodal fNIRS–EEG sensor fusion: Review of data-driven methods and perspective for naturalistic brain imaging
Multimodal fNIRS–EEG sensor fusion: Review of data-driven methods and perspective for naturalistic brain imaging Open
Functional near-infrared spectroscopy (fNIRS), high-density diffuse optical tomography (HD-DOT), and electroencephalography (EEG) are established, cost-effective, and non-invasive neuroimaging techniques, whose integration represents a pro…
View article: Data-driven head model individualization from digitized electrode positions or photogrammetry improves M/EEG source localization accuracy
Data-driven head model individualization from digitized electrode positions or photogrammetry improves M/EEG source localization accuracy Open
We propose a data-driven algorithm to approximate individual head anatomies to improve source localization accuracy over the widely used standard head models Colin27 and ICBM-152 when structural MRI/CT scans are not available. Based on a l…
View article: A New Canonical Log-Euclidean Kernel for Symmetric Positive Definite Matrices for EEG Analysis (Oct 2024)
A New Canonical Log-Euclidean Kernel for Symmetric Positive Definite Matrices for EEG Analysis (Oct 2024) Open
The CLE provides a good choice as a kernel in time-critical applications and fills a gap in the kernel methods of the log-euclidean framework.
View article: Desflurane is risk factor for postoperative delirium in older patients’ independent from intraoperative burst suppression duration
Desflurane is risk factor for postoperative delirium in older patients’ independent from intraoperative burst suppression duration Open
Background Postoperative Delirium (POD) is the most frequent neurocognitive complication after general anesthesia in older patients. The development of POD is associated with prolonged periods of burst suppression activity in the intraoper…
View article: Machine-learning model predicting postoperative delirium in older patients using intraoperative frontal electroencephalographic signatures
Machine-learning model predicting postoperative delirium in older patients using intraoperative frontal electroencephalographic signatures Open
Objective In older patients receiving general anesthesia, postoperative delirium (POD) is the most frequent form of cerebral dysfunction. Early identification of patients at higher risk to develop POD could provide the opportunity to adapt…
View article: Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease
Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease Open
Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson’s disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. …
View article: Author response: Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease
Author response: Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease Open
Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Brain signal decoding …
View article: Replication Data for: Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease
Replication Data for: Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease Open
This dataset contains the data required for replication of the results published in the paper titled "Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease". The abstract for th…
View article: Towards physiology-informed data augmentation for EEG-based BCIs
Towards physiology-informed data augmentation for EEG-based BCIs Open
Most EEG-based Brain-Computer Interfaces (BCIs) require a considerable amount of training data to calibrate the classification model, owing to the high variability in the EEG data, which manifests itself between participants, but also with…
View article: Cognitive Workload of Tugboat Captains in Realistic Scenarios: Adaptive Spatial Filtering for Transfer Between Conditions
Cognitive Workload of Tugboat Captains in Realistic Scenarios: Adaptive Spatial Filtering for Transfer Between Conditions Open
Changing and often class-dependent non-stationarities of signals are a big challenge in the transfer of common findings in cognitive workload estimation using Electroencephalography (EEG) from laboratory experiments to realistic scenarios …
View article: Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease
Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease Open
Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson’s disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. …
View article: Suppress Me if You Can: Neurofeedback of the Readiness Potential
Suppress Me if You Can: Neurofeedback of the Readiness Potential Open
Voluntary movements are usually preceded by a slow, negative-going brain signal over motor areas, the so-called readiness potential (RP). To date, the exact nature and causal role of the RP in movement preparation have remained heavily deb…
View article: Motor Imagery Under Distraction— An Open Access BCI Dataset
Motor Imagery Under Distraction— An Open Access BCI Dataset Open
DATA REPORT article Front. Neurosci., 19 October 2020Sec. Neural Technology Volume 14 - 2020 | https://doi.org/10.3389/fnins.2020.566147
View article: Suppress me if you can: neurofeedback of the readiness potential
Suppress me if you can: neurofeedback of the readiness potential Open
Voluntary movements are usually preceded by a slow, negative-going brain signal over motor areas, the so-called readiness potential (RP). To date, the exact nature and causal role of the RP in movement preparation have remained heavily deb…
View article: Roadmap
Roadmap Open
The main objective of this roadmap is to provide a global perspective on the BCI field now and in the future. For readers not familiar with BCIs, we introduce basic terminology and concepts. We discuss what BCIs are, what BCIs can do, and …
View article: Integrating neurophysiologic relevance feedback in intent modeling for information retrieval
Integrating neurophysiologic relevance feedback in intent modeling for information retrieval Open
The use of implicit relevance feedback from neurophysiology could deliver effortless information retrieval. However, both computing neurophysiologic responses and retrieving documents are characterized by uncertainty because of noisy signa…
View article: A large scale screening study with a SMR-based BCI: Categorization of BCI users and differences in their SMR activity
A large scale screening study with a SMR-based BCI: Categorization of BCI users and differences in their SMR activity Open
Brain-Computer Interfaces (BCIs) are inefficient for a non-negligible part of the population, estimated around 25%. To understand this phenomenon in Sensorimotor Rhythm (SMR) based BCIs, data from a large-scale screening study conducted on…
View article: Brain-Computer Interface - Motor Imagery Data
Brain-Computer Interface - Motor Imagery Data Open
We provide a data set of a BCI study using a motor imagery paradigm. In a calibration session, participants were instructed by cues to perform different types of imagined movements. The pair of classes resulting in the most promising discr…
View article: Improving the analysis of near-infrared spectroscopy data with multivariate classification of hemodynamic patterns: a theoretical formulation and validation
Improving the analysis of near-infrared spectroscopy data with multivariate classification of hemodynamic patterns: a theoretical formulation and validation Open
The results obtained suggest that the outcome of GLM analysis is highly vulnerable to violations of theoretical assumptions, and that therefore a data-driven approach such as that provided by the proposed LDA-based method is to be favored.
View article: Enhanced Classification Methods for the Depth of Cognitive Processing Depicted in Neural Signals
Enhanced Classification Methods for the Depth of Cognitive Processing Depicted in Neural Signals Open
Analyzing brain states is a difficult problem due to high variability between subjects and trials, therefore improved techniques are requested to be developed for a better discrimination between the neural components. This paper investigat…
View article: Implicit relevance feedback from electroencephalography and eye tracking in image search
Implicit relevance feedback from electroencephalography and eye tracking in image search Open
It was demonstrated that BCI methods can extract implicit user-related information in a setting of human-computer interaction. Novelties of the study are the implicit online feedback from EEG and eye tracking, the approximation to a realis…
View article: Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation
Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation Open
Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to ma…
View article: Real-time inference of word relevance from electroencephalogram and eye gaze
Real-time inference of word relevance from electroencephalogram and eye gaze Open
It was demonstrated that the interest of a reader can be inferred online from EEG and eye tracking signals, which can potentially be used in novel types of adaptive software, which enrich the interaction by adding implicit information abou…