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Neuroscience

D-Index
51
Citations
17678
World Ranking
5435
National Ranking
319

Overview

Martin J. McKeown is affiliated with the University of British Columbia in Canada. Their research primarily spans the fields of Medicine and Neuroscience, with significant contributions to subfields such as Neurology, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, and Computer Vision and Pattern Recognition.

The scientist's research topics cover a variety of specialized areas including:

  • Neurological disorders and treatments
  • Parkinson's Disease Mechanisms and Treatments
  • EEG and Brain-Computer Interfaces
  • Functional Brain Connectivity Studies
  • Advanced Neuroimaging Techniques and Applications
  • Vestibular and auditory disorders
  • Advanced MRI Techniques and Applications

Martin J. McKeown has published extensively in multiple academic venues. The most frequent publication outlets include:

  • arXiv (Cornell University)
  • Frontiers in Neurology
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Sensors
  • Brain Stimulation

Collaborations have been an important part of McKeown's work, with frequent co-authors including:

  • Maryam S. Mirian
  • Soojin Lee
  • Z. Jane Wang
  • Aiping Liu
  • Xun Chen

Recent papers authored or co-authored by Martin J. McKeown demonstrate their focus on neural signal processing and neurological disorder treatment methodologies. These include:

  • A convolutional-recurrent neural network approach to resting-state EEG classification in Parkinson's disease, 2021, Journal of Neuroscience Methods
  • Toward Open-World Electroencephalogram Decoding Via Deep Learning: A comprehensive survey, 2022, IEEE Signal Processing Magazine
  • Semi-dilated convolutional neural networks for epileptic seizure prediction, 2021, Neural Networks
  • Repetitive transcranial magnetic stimulation improves Parkinson's freezing of gait via normalizing brain connectivity, 2020, npj Parkinson's Disease
  • A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data, 2021, Sensors

Best Publications

  • Removing electroencephalographic artifacts by blind source separation.

    Tzyy-Ping Jung;Tzyy-Ping Jung;Scott Makeig;Colin Humphries;Te-Won Lee;Te-Won Lee

  • Analysis of fMRI data by blind separation into independent spatial components

    Martin J. Mckeown;Scott Makeig;Greg G. Brown;Tzyy-Ping Jung

  • Imaging brain dynamics using independent component analysis

    T.-P. Jung;S. Makeig;M.J. McKeown;A.J. Bell

  • Extended ICA Removes Artifacts from Electroencephalographic Recordings

    Tzyy-Ping Jung;Colin Humphries;Te-Won Lee;Scott Makeig

  • Independent Component Analysis of fMRI Data: Examining the Assumptions

    Martin J. McKeown;Terrence J. Sejnowski;Terrence J. Sejnowski

  • Spatially independent activity patterns in functional MRI data during the Stroop color-naming task

    Martin J. McKeown;Tzyy-Ping Jung;Scott Makeig;Greg Brown

  • Independent component analysis of functional MRI: what is signal and what is noise?

    Martin J McKeown;Lars Kai Hansen;Terrence J Sejnowsk;Terrence J Sejnowsk

  • Brain activity evoked by the perception of human walking: controlling for meaningful coherent motion.

    Kevin A. Pelphrey;Teresa V. Mitchell;Martin J. McKeown;Jeremy Goldstein

  • Polysensory Interactions along Lateral Temporal Regions Evoked by Audiovisual Speech

    Tarra M. Wright;Kevin A. Pelphrey;Truett Allison;Martin J. McKeown

  • 3D CNN Based Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Using Functional and Structural MRI

    Liang Zou;Jiannan Zheng;Chunyan Miao;Martin J. Mckeown

  • Removing electroencephalographic artifacts: comparison between ICA and PCA

    T.-P. Jung;C. Humphries;T.-W. Lee;S. Makeig

  • Detection of consistently task-related activations in fMRI data with hybrid independent component analysis.

    Martin J. McKeown

  • Exercise increases caudate dopamine release and ventral striatal activation in Parkinson's disease.

    Matthew A. Sacheli;Jason L. Neva;Bimal Lakhani;Danielle K. Murray

  • INDEPENDENT COMPONENT ANALYSIS OF BIOMEDICAL SIGNALS

    Tzyy-Ping Jung;Scott Makeig;Te-Won Lee;Martin J. McKeown

  • Task specific influences of Parkinson’s disease on the striato-thalamo-cortical and cerebello-thalamo-cortical motor circuitries

    M.M. Lewis;C.G. Slagle;A.B. Smith;Y. Truong

  • The Use of Multivariate EMD and CCA for Denoising Muscle Artifacts From Few-Channel EEG Recordings

    Xun Chen;Xueyuan Xu;Aiping Liu;Martin J. McKeown

  • Advances in imaging in Parkinson's disease

    A Jon Stoessl;WR Wayne Martin;Martin J McKeown;Vesna Sossi

  • Acute and persistent pain modulation of attention-related anterior cingulate fMRI activations

    Angela L.H. Buffington;Colleen A. Hanlon;Martin J. McKeown

  • Linking Hemodynamic and Electrophysiological Measures of Brain Activity: Evidence from Functional MRI and Intracranial Field Potentials

    Scott A. Huettel;Martin J. McKeown;Allen W. Song;Sarah Hart

  • Removing Muscle Artifacts From EEG Data: Multichannel or Single-Channel Techniques?

    Xun Chen;Aiping Liu;Joyce Chiang;Z. Jane Wang

Frequent Co-Authors

A. Jon Stoessl
A. Jon Stoessl University of British Columbia
Terrence J. Sejnowski
Terrence J. Sejnowski Salk Institute for Biological Studies
Xuemei Huang
Xuemei Huang Pennsylvania State University
Tzyy-Ping Jung
Tzyy-Ping Jung University of California, San Diego
Scott Makeig
Scott Makeig University of California, San Diego
Mechelle M. Lewis
Mechelle M. Lewis Penn State Milton S. Hershey Medical Center
Yi Liu
Yi Liu Lawrence Berkeley National Laboratory
Matthew J. Farrer
Matthew J. Farrer University of Florida
Mark G. Carpenter
Mark G. Carpenter University of British Columbia
Richard B. Mailman
Richard B. Mailman Pennsylvania State University

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