Open multimodal iEEG-fMRI dataset from naturalistic stimulation with a short audiovisual film
on003688 · 39 high-confidence citations
- Advances in human intracranial electroencephalography research, guidelines and good practices
- A synchronized multimodal neuroimaging dataset for studying brain language processing
- Open multimodal iEEG-fMRI dataset from naturalistic stimulation with a short audiovisual film
- Physiological signal analysis using explainable artificial intelligence: A systematic review
- Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition
- Feasibility of decoding visual information from EEG
- BELT: Bootstrapped EEG-to-Language Training by Natural Language Supervision
- Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli
- A large-scale fMRI dataset for human action recognition
- Emo-FilM: A multimodal dataset for affective neuroscience using naturalistic stimuli
- A neuroimaging dataset during sequential color qualia similarity judgments with and without reports
- A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning
- A comparison of EEG encoding models using audiovisual stimuli and their unimodal counterparts
- BELT: Bootstrapping Electroencephalography-to-Language Decoding and Zero-Shot Sentiment Classification by Natural Language Supervision
- Open multi-center intracranial electroencephalography dataset with task probing conscious visual perception
- How Does Artificial Intelligence Contribute to iEEG Research?
- Unraveling gender-specific structural brain differences in drug-resistant epilepsy using advanced deep learning techniques
- The Brain, Body, and Behavior Dataset (BBBD): Multimodal Recordings during Educational Videos
- Towards Decoding Brain Activity During Passive Listening of Speech
- Bimodal pilot study on inner speech decoding reveals the potential of combining EEG and fMRI
- Forecasting fMRI images from video sequences: linear model analysis
- A Comprehensive Review of Deep Learning Methodologies for Alzheimer’s Disease Diagnosis by Neuroimaging
- Anatomically distinct cortical tracking of music and speech by slow (1–8Hz) and fast (70–120Hz) oscillatory activity
- Inferring neural sources from electroencephalography: foundations and frontiers
- Omni-iEEG: A Large-Scale, Comprehensive iEEG Dataset and Benchmark for Epilepsy Research
- Open multimodal iEEG-fMRI dataset from naturalistic stimulation with a short audiovisual film
- Enhancing Auditory BCI Performance: Incorporation of Connectivity Analysis
- A Combined Channel Approach for Decoding Intracranial EEG Signals: Enhancing Accuracy Through Spatial Information Integration
- Cardiovascular Artifact Removal for Unbiased Analysis of Intracortical EEG Signals
- Temporal propagation of neural state boundaries in naturalistic context
- Neural coding of spectrotemporal modulations in the auditory cortex supports speech and music categorization
- NEvo: Neural-Guided Evolutionary Video Synthesis for Dynamic Visual Selectivity
- SPIDER -- Stitched Power-spectra for Inferring Directed information flow from incomplete and asynchronous Experimental Recordings
- Nonlinear Dynamical Modeling of Human Intracranial Brain Activity with Flexible Inference
- Integrated Noninvasive Brain Imaging Advancements: A Multimodal Approach
- A Combined Channel Approach for Decoding Intracranial EEG Signals: Enhancing Accuracy through Spatial Information Integration
- Linguistic structure and probability are jointly encoded in high gamma power
- Mapping Epilepsy-specific Functional MRI Network Properties in Refractory Epilepsy Using Intracranial EEG Locations
- SPIDER -- Stitched Power-spectra for Inferring Directed information flow from incomplete and asynchronous Experimental Recordings
No citations of that kind for this dataset.
14 lower-confidence citations (not counted)
- Workshops of the eighth international brain–computer interface meeting: BCIs: the next frontier
- Diverse Perceptual Representations Across Visual Pathways Emerge from A Single Objective
- Noninvasive brain–computer interfaces for children with neurodevelopmental disorders: Attention deficit hyperactivity disorder and autism spectrum disorder
- Tensor-powered insights into neural dynamics
- The representation of facial emotion expands from sensory to prefrontal cortex with development
- Using computational semantics to study meaning in the brain
- Big Brain Data
- Neurolinguistic justification and validation of the methodology of receptive skills development with the help of an audiobook
- Rail Surface Defect Detection and Severity Analysis Using CNNs on Camera and Axle Box Acceleration Data
- The representation of facial emotion expands from sensory to prefrontal cortex with development
- Author response: The representation of facial emotion expands from sensory to prefrontal cortex with development
- Reviewer #2 (Public review): The representation of facial emotion expands from sensory to prefrontal cortex with development
- Reviewer #1 (Public review): The representation of facial emotion expands from sensory to prefrontal cortex with development
- None: The representation of facial emotion expands from sensory to prefrontal cortex with development