Scott Makeig
University of California, San Diego
PhysicsStimulus (physiology)InfomaxArtificial intelligencePsychologyNeuroscienceCognitionPattern recognitionCognitive psychologyElectrophysiologyScalpSpeech recognitionEEGLABMathematicsComputer scienceBrain mappingIndependent component analysisElectroencephalographyAudiologyEvent-related potential
319Publications
88H-index
42.7kCitations
Publications 316
Newest
#1Dung TruongH-Index: 1
Last. Arnaud DelormeH-Index: 44
view all 4 authors...
The success of deep learning in computer vision has inspired the scientific community to explore new analysis methods. Within the field of neuroscience, specifically in electrophysiological neuroimaging, researchers are starting to explore leveraging deep learning to make predictions on their data without extensive feature engineering. This paper compares deep learning using minimally processed EEG raw data versus deep learning using EEG spectral features using two different deep convolutional n...
#1Kay A. Robbins (UTSA: University of Texas at San Antonio)H-Index: 24
#2Dung Truong (UCSD: University of California, San Diego)H-Index: 1
Last. Scott Makeig (UCSD: University of California, San Diego)H-Index: 88
view all 5 authors...
Because of the central role that event-related data analysis plays in EEG and MEG (MEEG) experiments, choices about which events to report and how to annotate their full natures can significantly influence the reliability, reproducibility, and value of MEEG datasets for further analysis. Current, more powerful annotation strategies combine robust event description with details of experiment design and metadata in a human-readable as well as machine-actionable form, making event annotation releva...
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This article outlines a set of plug-in tools running on MATLAB to automatically import, preprocess, and evaluate the quality of electro-encephalography (EEG) data stored using the Brain Imaging Data Structure BIDS-EEG standard. As a proof of concept, we apply several possible data quality metrics to 30 EEG studies (sets of compatible datasets) currently available in BIDS-EEG format on the OpenNeuro.org platform. The bids-matlab-tools plug-in for EEGLAB (sccn.ucsd.edu/EEGLAB) checks for the prese...
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#1Joseph Jurgiel (Semel Institute for Neuroscience and Human Behavior)H-Index: 2
#2Makoto Miyakoshi (UCSD: University of California, San Diego)H-Index: 18
Last. Sandra K. Loo (Semel Institute for Neuroscience and Human Behavior)H-Index: 53
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Chronic tic disorders, including Tourette syndrome, are typically thought to have deficits in cognitive inhibition and top down cognitive control due to the frequent and repetitive occurrence of tics, yet studies reporting task performance results have been equivocal. Despite similar behavioural performance, individuals with chronic tic disorder have exhibited aberrant patterns of neural activation in multiple frontal and parietal regions relative to healthy controls during inhibitory control pa...
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#1Makoto Miyakoshi (UCSD: University of California, San Diego)H-Index: 18
#2Lukas Gehrke (Technical University of Berlin)H-Index: 4
Last. John R. Iversen (UCSD: University of California, San Diego)H-Index: 19
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Spatial navigation is one of the fundamental cognitive functions central to survival in most animals. Studies in humans investigating the neural foundations of spatial navigation traditionally use stationary, desk-top protocols revealing the hippocampus, parahippocampal place area (PPA), and retrosplenial complex to be involved in navigation. However, brain dynamics while freely navigating the real world remain poorly understood. To address this issue, we developed a novel paradigm, the Audiomaz...
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#1Takahiro Kagawa (Aichi Institute of Technology)H-Index: 8
#2Scott Makeig (UCSD: University of California, San Diego)H-Index: 88
Last. Makoto Miyakoshi (UCSD: University of California, San Diego)H-Index: 18
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A periodically reversing optic flow animation, experienced while standing, induces an involuntary sway termed visually induced postural sway (VIPS). Interestingly, VIPS is suppressed during light f...
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#1Cyril Pernet (Edin.: University of Edinburgh)H-Index: 37
#2Ramon Martinez-Cancino (University of California, Berkeley)
Last. Arnaud Delorme (University of Toulouse)H-Index: 1
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Reproducibility is a cornerstone of scientific communication without which one cannot build upon each other's work. Because modern human brain imaging relies on many integrated steps with a variety of possible algorithms, it has however become impossible to report every detail of a data processing workflow. In response to this analytical complexity, community recommendations are to share data analysis pipelines (scripts that implement workflows). Here we show that this can easily be done using E...
1 CitationsSource
#1Ramón Martínez-Cancino (UCSD: University of California, San Diego)H-Index: 5
#2Arnaud Delorme (UCSD: University of California, San Diego)H-Index: 44
Last. Scott Makeig (UCSD: University of California, San Diego)H-Index: 88
view all 9 authors...
Abstract EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety of neuroscience-related software on high-performance computing (HPC) resources in the U.S. XSEDE network. We have reported recently ( Delorme et al., 2019 ) on the Open EEGLAB Portal expansion of the free NSG services to allow the neuroscienc...
6 CitationsSource
#1Kay A. RobbinsH-Index: 24
#2Dung TruongH-Index: 1
Last. Scott MakeigH-Index: 88
view all 0 authors...
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#1Yumi Shikauchi (Japan Society for the Promotion of Science)H-Index: 4
#2Makoto Miyakoshi (UCSD: University of California, San Diego)H-Index: 18
Last. John R. Iversen (UCSD: University of California, San Diego)H-Index: 19
view all 4 authors...
We investigated Bayesian modelling of human whole-body motion capture data recorded during an exploratory real-space navigation task in an "Audiomaze" environment (see the companion paper by Miyakoshi et al. in the same volume) to study the effect of map learning on navigation behaviour. There were three models, a feedback-only model (no map learning), a map resetting model (single-trial limited map learning), and a map updating model (map learning accumulated across three trials). The estimated...
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