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View article: EEG power modulation in the sensorimotor regions is critical to motor tic suppression
EEG power modulation in the sensorimotor regions is critical to motor tic suppression Open
Background The neural mechanisms underlying tic suppression in chronic tic disorder (CTD) have been investigated using various neuroimaging modalities. A limitation in studying CTD is that abrupt motor action is inherent to the nature of t…
View article: Sensory Entrained TMS (seTMS) enhances motor cortex plasticity
Sensory Entrained TMS (seTMS) enhances motor cortex plasticity Open
Neural excitability fluctuates with sensory events, creating windows of opportunity to enhance brain stimulation. Repetitive transcranial magnetic stimulation (TMS), including intermittent theta burst stimulation (iTBS), is a promising tre…
View article: Sensory Entrained <scp>TMS</scp> ( <scp>seTMS</scp> ) Enhances Motor Cortex Excitability
Sensory Entrained <span>TMS</span> ( <span>seTMS</span> ) Enhances Motor Cortex Excitability Open
Transcranial magnetic stimulation (TMS) applied to the motor cortex has revolutionized the study of motor physiology in humans. Despite this, TMS‐evoked electrophysiological responses show significant fluctuation, due in part to inconsiste…
View article: Simulating Scalp EEG from Ultrahigh-Density ECoG Data Illustrates Cortex to Scalp Projection Patterns
Simulating Scalp EEG from Ultrahigh-Density ECoG Data Illustrates Cortex to Scalp Projection Patterns Open
Ultrahigh-density electrocorticography (μECoG) provides unprecedented spatial resolution for recording cortical electrical activity. This study uses simulated scalp projections from an μECoG recording to challenge the assumption that chann…
View article: EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding
EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding Open
Current electroencephalogram (EEG) decoding models are typically trained on small numbers of subjects performing a single task. Here, we introduce a large-scale, code-submission-based competition comprising two challenges. First, the Trans…
View article: Quantifying Data Requirements for EEG Independent Component Analysis Using AMICA
Quantifying Data Requirements for EEG Independent Component Analysis Using AMICA Open
Independent Component Analysis (ICA) is an important step in EEG processing for a wide-ranging set of applications. However, ICA requires well-designed studies and data collection practices to yield optimal results. Past studies have focus…
View article: The lab streaming layer for synchronized multimodal recording
The lab streaming layer for synchronized multimodal recording Open
Accurately recording the interactions of humans or other organisms with their environment and other agents requires synchronized data access via multiple instruments, often running independently using different clocks. Active, hardware-med…
View article: Cycling on the Freeway: The perilous state of open-source neuroscience software
Cycling on the Freeway: The perilous state of open-source neuroscience software Open
Most scientists need software to perform their research (Barker et al., 2020; Carver et al., 2022; Hettrick, 2014; Hettrick et al., 2014; Switters & Osimo, 2019), and neuroscientists are no exception. Whether we work with reaction times, e…
View article: End-to-End Processing of M/EEG Data with BIDS, HED, and EEGLAB
End-to-End Processing of M/EEG Data with BIDS, HED, and EEGLAB Open
Reliable and reproducible machine-learning enabled neuroscience research requires large-scale data sharing and analysis. Essential for the effective and efficient analysis of shared datasets are standardized data and metadata organization …
View article: Sensory Entrained TMS (seTMS) enhances motor cortex excitability
Sensory Entrained TMS (seTMS) enhances motor cortex excitability Open
Transcranial magnetic stimulation (TMS) applied to the motor cortex has revolutionized the study of motor physiology in humans. Despite this, TMS-evoked electrophysiological responses show significant variability, due in part to inconsiste…
View article: Automatic EEG Independent Component Classification Using ICLabel in Python
Automatic EEG Independent Component Classification Using ICLabel in Python Open
ICLabel is an important plug-in function in EEGLAB, the most widely used software for EEG data processing. A powerful approach to automated processing of EEG data involves decomposing the data by Independent Component Analysis (ICA) and th…
View article: HBN-EEG: The FAIR implementation of the Healthy Brain Network (HBN) electroencephalography dataset
HBN-EEG: The FAIR implementation of the Healthy Brain Network (HBN) electroencephalography dataset Open
The Child Mind Institute (CMI) Healthy Brain Network (HBN) project has recorded phenotypic, behavioral, and neuroimaging data from ∼5,000 children and young adults between the ages of 5 and 21. Here, we present HBN-EEG, the “analysis-ready…
View article: HED LANG – A Hierarchical Event Descriptors library extension for annotation of language cognition experiments
HED LANG – A Hierarchical Event Descriptors library extension for annotation of language cognition experiments Open
Experimental design in language cognition research often involves presenting language material whilemeasuring associated behavior and/or neural activity. To make the collected data easily and fullyanalyzable by both the original data autho…
View article: One hundred years of EEG for brain and behaviour research
One hundred years of EEG for brain and behaviour research Open
On the centenary of the first human EEG recording, more than 500 experts reflect on the impact that this discovery has had on our understanding of the brain and behaviour. We document their priorities and call for collective action focusin…
View article: Events in context—The HED framework for the study of brain, experience and behavior
Events in context—The HED framework for the study of brain, experience and behavior Open
The brain is a complex dynamic system whose current state is inextricably coupled to awareness of past, current, and anticipated future threats and opportunities that continually affect awareness and behavioral goals and decisions. Brain a…
View article: The Lab Streaming Layer for Synchronized Multimodal Recording
The Lab Streaming Layer for Synchronized Multimodal Recording Open
Accurately recording the interactions of humans or other organisms with their environment and other agents requires synchronized data access via multiple instruments, often running independently using different clocks. Active, hardware-med…
View article: Finding tau rhythms in <scp>EEG</scp>: An independent component analysis approach
Finding tau rhythms in <span>EEG</span>: An independent component analysis approach Open
Tau rhythms are largely defined by sound responsive alpha band (~8–13 Hz) oscillations generated largely within auditory areas of the superior temporal gyri. Studies of tau have mostly employed magnetoencephalography or intracranial record…
View article: This is no “ICA bug”: response to the article, “ICA's bug: how ghost ICs emerge from effective rank deficiency caused by EEG electrode interpolation and incorrect re-referencing”
This is no “ICA bug”: response to the article, “ICA's bug: how ghost ICs emerge from effective rank deficiency caused by EEG electrode interpolation and incorrect re-referencing” Open
OPINION article Front. Neuroimaging, 21 December 2023Sec. Brain Imaging Methods Volume 2 - 2023 | https://doi.org/10.3389/fnimg.2023.1331404
View article: A comparison of neuroelectrophysiology databases
A comparison of neuroelectrophysiology databases Open
As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available in…
View article: Hierarchical Event Descriptor library schema for EEG data annotation
Hierarchical Event Descriptor library schema for EEG data annotation Open
Standardizing terminology to annotate electrophysiological events can improve both computational research and clinical care. Sharing data enriched with standard terms can facilitate data exploration, from case studies to mega-analyses. The…
View article: An Exploration of Optimal Parameters for Efficient Blind Source Separation of EEG Recordings Using AMICA
An Exploration of Optimal Parameters for Efficient Blind Source Separation of EEG Recordings Using AMICA Open
EEG continues to find a multitude of uses in both neuroscience research and medical practice, and independent component analysis (ICA) continues to be an important tool for analyzing EEG. A multitude of ICA algorithms for EEG decomposition…
View article: Events in context – a framework for the study of brain, experience and behavior
Events in context – a framework for the study of brain, experience and behavior Open
The brain is a complex dynamic system whose current state is inextricably coupled to awareness of current threats and opportunities, bodily sensations, and behavioral goals and decisions in an ever-changing sensory and behavioral context u…
View article: A Comparison of Neuroelectrophysiology Databases
A Comparison of Neuroelectrophysiology Databases Open
As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available in…
View article: Correction to: Building FAIR Functionality: Annotating Events in Time Series Data Using Hierarchical Event Descriptors (HED)
Correction to: Building FAIR Functionality: Annotating Events in Time Series Data Using Hierarchical Event Descriptors (HED) Open
The original version of this article unfortunately contained typesetting errors.The texts in Examples 1, 2, 3, and 4 were captured incorrectly.The correct presentation of these examples are shown below.Example 1.A first-generation HED anno…
View article: End-to-end processing of M/EEG data with BIDS, HED, and EEGLAB
End-to-end processing of M/EEG data with BIDS, HED, and EEGLAB Open
Reliable and reproducible machine-learning enabled neuroscience research requires large-scale data sharing and analysis. Essential to the analysis of shared datasets are standardized data organization and metadata formatting, a well-docume…
View article: A Framework to Evaluate Independent Component Analysis applied to EEG signal: testing on the Picard algorithm
A Framework to Evaluate Independent Component Analysis applied to EEG signal: testing on the Picard algorithm Open
Independent component analysis (ICA), is a blind source separation method that is becoming increasingly used to separate brain and non-brain related activities in electroencephalographic (EEG) and other electrophysiological recordings. It …
View article: NEMAR: An open access data, tools, and compute resource operating on NeuroElectroMagnetic data
NEMAR: An open access data, tools, and compute resource operating on NeuroElectroMagnetic data Open
To take advantage of recent and ongoing advances in large-scale computational methods, and to preserve the scientific data created by publicly funded research projects, data archives must be created as well as standards for specifying, ide…