A. Schlögl

发表

Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters.

G Pfurtscheller, A Schlögl, C Neuper, 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

Lexical memory search during N400: cortical couplings in auditory comprehension

G. Pfurtscheller, A. Schlögl, H. Petsche, 2004, Neuroreport.

An E-Health Solution for Automatic Sleep Classification according to Rechtschaffen and Kales: Validation Study of the Somnolyzer 24 × 7 Utilizing the Siesta Database

A. Schlögl, P. Rappelsberger, P. Anderer, 2005, Neuropsychobiology.

Interrater reliability between scorers from eight European sleep laboratories in subjects with different sleep disorders

A. Schlögl, J. Röschke, G. Dorffner, 2004, Journal of sleep research.

The BCI competition 2003: progress and perspectives in detection and discrimination of EEG single trials

Klaus-Robert Müller, Christa Neuper, Gert Pfurtscheller, 2004, IEEE Transactions on Biomedical Engineering.

Enhancement of left-right sensorimotor EEG differences during feedback-regulated motor imagery.

G. Pfurtscheller, C. Neuper, A. Schlögl, 1999, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

Directed Cortical Information Flow during Human Object Recognition: Analyzing Induced EEG Gamma-Band Responses in Brain's Source Space

Matthias M. Müller, A. Schlögl, T. Gruber, 2007, PloS one.

Quality control of polysomnographic sleep data by histogram and entropy analysis

G. Pfurtscheller, A. Schlögl, G. Dorffner, 1999, Clinical Neurophysiology.

Recent advances in modeling and analysis of bioelectric and biomagnetic sources

Lutz Trahms, Jens Haueisen, Thomas R Knösche, 2010, Biomedizinische Technik. Biomedical engineering.

ARTEFACT DETECTION IN SLEEP EEG BY THE USE OF KALMAN FILTERING

Stephen J. Roberts, Alois Schlögl, Peter Anderer, 2007 .

Artifact Processing in Computerized Analysis of Sleep EEG – A Review

A. Schlögl, P. Rappelsberger, P. Anderer, 1999, Neuropsychobiology.

Robustly estimating the flow direction of information in complex physical systems.

K. Müller, A. Schlögl, A. Ziehe, 2007, Physical review letters.

Fast signaling and focal connectivity of PV+ interneurons ensure efficient pattern separation by lateral inhibition in a full-scale dentate gyrus network model

Benjamin A. Suter, A. Schlögl, P. Jonas, 2019, bioRxiv.

Spindle Filter Optimisation with Receiver Operating Characteristics-Curves

Gert Pfurtscheller, Alois Schlögl, Peter Rappelsberger, 1999 .

Towards self-paced ( asynchronous ) Brain-Computer Communication : Navigation through virtual worlds

Reinhold Scherer, Gert Pfurtscheller, Alois Schlögl, 2006 .

Selective Routing of Spatial Information Flow from Input to Output in Hippocampal Granule Cells

A. Schlögl, P. Jonas, Xiaomin Zhang, 2020, Neuron.

Graz-Brain-Computer Interface: State of Research

Selina Wriessnegger, Christa Neuper, Gernot R. Müller-Putz, 2007 .

Hemodynamic and autonomic changes induced by Ironman: prediction of competition time by blood pressure variability.

A. Schlögl, F. Skrabal, W. Urban, 2005, Journal of applied physiology.

Adaptive autoregressive parameters used in BCI research

G. Pfurtscheller, C. Neuper, A. Schlögl, 2001 .

Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks

Clemens Brunner, Gert Pfurtscheller, F. H. Lopes da Silva, 2006, NeuroImage.

A fully automated correction method of EOG artifacts in EEG recordings

G. Pfurtscheller, R. Scherer, C. Keinrath, 2007, Clinical Neurophysiology.

Selective Routing of Spatial Information Flow from Input to Output in Hippocampal Granule Cells

A. Schlögl, P. Jonas, Xiaomin Zhang, 2020, Neuron.

BioSig - an open source software library for BCI research

Clemens Brunner, Reinhold Scherer, Alois Schlögl, 2007 .

Sequential effects in continued visual search: Using fixation-related potentials to compare distractor processing before and after target detection

Christa Neuper, Alois Schlögl, Christof Körner, 2014, Psychophysiology.

Frontiers in Computational Neuroscience Computational Neuroscience

Nikos K. Logothetis, Alois Schlögl, Gregor Rainer, 2022 .

Review of the BCI Competition IV

Ad Aertsen, Hubert Preissl, Clemens Brunner, 2012, Front. Neurosci..

Time Domain Parameters as a feature for EEG-based Brain-Computer Interfaces

Nicole Krämer, Benjamin Blankertz, Carmen Vidaurre, 2009, Neural Networks.

The Electroencephalogram and the Adaptive Autoregressive Model: Theory and Applications

Alois Schlögl, A. Schlögl, 2000 .

Artifact processing of the sleep EEG in the "SIESTA"-project

Gert Pfurtscheller, Stephen J. Roberts, Georg Dorffner, 1999 .

A comparison of multivariate autoregressive estimators

Alois Schlögl, A. Schlögl, 2006, Signal Process..

How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network

Benjamin A. Suter, A. Schlögl, P. Jonas, 2021, Nature Computational Science.

BioSig: The Free and Open Source Software Library for Biomedical Signal Processing

Carmen Vidaurre, Alois Schlögl, Tilmann Heinrich Sander, 2011, Comput. Intell. Neurosci..

The Self-Paced Graz Brain-Computer Interface: Methods and Applications

Horst Bischof, Reinhold Scherer, Gert Pfurtscheller, 2007, Comput. Intell. Neurosci..

Current trends in Graz Brain-Computer Interface (BCI) research.

G Pfurtscheller, C Guger, H Ramoser, 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

Stimfit: quantifying electrophysiological data with Python

Alois Schlögl, Christoph Schmidt-Hieber, Segundo Jose Guzman, 2013, Front. Neuroinform..

Analyzing event-related EEG data with multivariate autoregressive parameters.

Alois Schlögl, Gernot Supp, A. Schlögl, 2006, Progress in brain research.

The History and Challenges of SCP-ECG: The Standard Communication Protocol for Computer-Assisted Electrocardiography

Danilo Pani, Alpo Värri, Alois Schlögl, 2021, Hearts.

Synaptic mechanisms of pattern completion in the hippocampal CA3 network

Alois Schlögl, Segundo Jose Guzman, Michael Frotscher, 2016, Science.

Characterization of four-class motor imagery EEG data for the BCI-competition 2005

Gert Pfurtscheller, Alois Schlögl, Horst Bischof, 2005, Journal of neural engineering.

A deconvolution-based method with high sensitivity and temporal resolution for detection of spontaneous synaptic currents in vitro and in vivo.

Alois Schlögl, Yvonne Stickler, Peter Jonas, 2012, Biophysical journal.

SHORT COMMUNICATIONS: Semantic memory retrieval: cortical couplings in object recognition in the N400 window

Gert Pfurtscheller, Alois Schlögl, Gabriella Vigliocco, 2005, The European journal of neuroscience.

Adaptive Methods in BCI Research - An Introductory Tutorial

Klaus-Robert Müller, Carmen Vidaurre, Alois Schlögl, 2009 .

Toward Self-Paced Brain–Computer Communication: Navigation Through Virtual Worlds

Horst Bischof, Reinhold Scherer, Gert Pfurtscheller, 2008, IEEE Transactions on Biomedical Engineering.

BioSig: A Free and Open Source Software Library for BCI Research

Clemens Brunner, Alois Schlögl, A. Schlögl, 2008, Computer.

Standards for biomedical signal databases.

T Penzel, B Kemp, A Värri, 2001, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

Estimating the Mutual Information of an EEG-based Brain-Computer Interface

G Pfurtscheller, A Schlögl, C Neuper, 2002, Biomedizinische Technik. Biomedical engineering.

EOG AND ECG MINIMIZATION BASED ON REGRESSION ANALYSIS

G. Pfurtscheller, A. Schlögl, G. Pfurtscheller, 2001 .

Autonomic dysfunction in PD during sleep

A. Schlögl, P. Anderer, G. Dorffner, 2012, Movement disorders : official journal of the Movement Disorder Society.

Directed Coupling in Local Field Potentials of Macaque V4 During Visual Short-Term Memory Revealed by Multivariate Autoregressive Models

N. Logothetis, A. Schlögl, S. Liebe, 2010, Front. Comput. Neurosci..

SCP-ECG V3.0: An enhanced standard communication protocol for computer-assisted electrocardiography

Danilo Pani, Alois Schlögl, Jocelyne Fayn, 2016, 2016 Computing in Cardiology Conference (CinC).

Comparison of Evaluation Metrics in Classification Applications with Imbalanced Datasets

Gary E. Birch, Rabab Kreidieh Ward, Jane E. Huggins, 2008, 2008 Seventh International Conference on Machine Learning and Applications.

Feature Mapping using PCA , Locally Linear Embedding and Isometric Feature Mapping for EEG-based Brain Computer Interface

Horst Bischof, Reinhold Scherer, Gert Pfurtscheller, 2004 .

A fully on-line adaptive BCI

Reinhold Scherer, Gert Pfurtscheller, Carmen Vidaurre, 2006, IEEE Transactions on Biomedical Engineering.

GDF - A GENERAL DATAFORMAT FOR BIOSIGNALS VERSION 1.25

Gert Pfurtscheller, Alois Schlögl, Herbert Ramoser, 1999 .

MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo

Alois Schlögl, Xiaomin Zhang, David Vandael, 2020, Journal of Neuroscience Methods.

Rapid prototyping of an EEG-based brain-computer interface (BCI)

G. Pfurtscheller, C. Neuper, A. Schlogl, 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Describing the sleep EEG with an Adaptive Autoregressive Model

Gert Pfurtscheller, Alois Schlögl, Michael Woertz, 2000 .

Describing the sleep EEG with an Adaptive

G. Pfurtscheller, A. Schlögl, M. Woertz, 2000 .

Study of On-Line Adaptive Discriminant Analysis for EEG-Based Brain Computer Interfaces

Reinhold Scherer, Gert Pfurtscheller, Carmen Vidaurre, 2007, IEEE Transactions on Biomedical Engineering.

SHORT COMMUNICATIONS: Semantic memory retrieval: cortical couplings in object recognition in the N400 window

G. Pfurtscheller, A. Schlögl, C. Fiebach, 2005, The European journal of neuroscience.

Considerations on Adaptive Autoregressive Modelling in EEG Analysis

Gert Pfurtscheller, Alois Schlögl, G. Pfurtscheller, 1998 .

How connectivity rules and synaptic properties shape the efficacy of pattern 11 separation in the entorhinal cortex–dentate gyrus–CA3 network

A. Schlögl, S. J. Guzman, Xiaomin Zhang, 2021 .