Copertina

BrainBits: How Much of the Brain are Generative Reconstruction Methods Using?

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mayo, David, Wang, Christopher, Harbin, Asa, Alabdulkareem, Abdulrahman, Shaw, Albert Eaton, Katz, Boris, Barbu, Andrei
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Signal Processing Neurons and Cognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

How Does a Single EEG Channel Tell Us About Brain States in Brain-Computer Interfaces ?
di: Ajra, Zaineb, et al.
Pubblicazione: (2024)

Decoding Saccadic Eye Movements from Brain Signals Using an Endovascular Neural Interface
di: Rasheed, Suleman, et al.
Pubblicazione: (2025)

Neuroprobe: Evaluating Intracranial Brain Responses to Naturalistic Stimuli
di: Zahorodnii, Andrii, et al.
Pubblicazione: (2025)

Sub-Scalp EEG for Sensorimotor Brain-Computer Interface
di: Mahoney, Timothy B, et al.
Pubblicazione: (2025)

Continuous Energy Landscape Model for Analyzing Brain State Transitions
di: Tran, Triet M., et al.
Pubblicazione: (2026)

Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli
di: Wang, Christopher, et al.
Pubblicazione: (2024)

BTTDA: Block-Term Tensor Discriminant Analysis for Brain-Computer Interfacing
di: Kerchove, Arne Van Den, et al.
Pubblicazione: (2025)

The Hydraulic Brain: Understanding as Constraint-Release Phase Transition in Whole-Body Resonance
di: Eldin, Ahmed Gamal
Pubblicazione: (2025)

Multimodal Higher-Order Brain Networks: A Topological Signal Processing Perspective
di: Bispo, Breno C., et al.
Pubblicazione: (2026)

Brain Age Group Classification Based on Resting State Functional Connectivity Metrics
di: Singh, Prerna, et al.
Pubblicazione: (2025)

Presurgical Neural Energy Landscapes Predict Postoperative Working Memory Outcome After Brain Tumor Resection
di: Tran, Triet M., et al.
Pubblicazione: (2025)

PiEEG-16 to Measure 16 EEG Channels with Raspberry Pi for Brain-Computer Interfaces and EEG devices
di: Rakhmatulin, Ildar
Pubblicazione: (2024)

How Much is Brain Data Worth for Machine Learning?
di: Lewis, Lane, et al.
Pubblicazione: (2026)

Revealing Vision-Language Integration in the Brain with Multimodal Networks
di: Subramaniam, Vighnesh, et al.
Pubblicazione: (2024)

Sparse Bayesian Correntropy Learning for Robust Muscle Activity Reconstruction from Noisy Brain Recordings
di: Li, Yuanhao, et al.
Pubblicazione: (2024)

Time-Domain Classification of the Brain Reward System: Analysis of Natural and Drug Reward Driven Local Field Potential Signals in Hippocampus and Nucleus Accumbens
di: Kalbasi, AmirAli, et al.
Pubblicazione: (2022)

Functional Connectivity-Guided Band Selection for Motor Imagery Brain-Computer Interfaces
di: Carmo, Natália Araújo do, et al.
Pubblicazione: (2026)

Comparison of Epilepsy Induced by Ischemic Hypoxic Brain Injury and Hypoglycemic Brain Injury using Multilevel Fusion of Data Features
di: Kadem, Sameer, et al.
Pubblicazione: (2024)

THD-BAR: Topology Hierarchical Derived Brain Autoregressive Modeling for EEG Generic Representations
di: Yang, Wenchao, et al.
Pubblicazione: (2025)

Form Follows Function: A Method of Discovering How Neurons Are Connected To Process Information
di: Yoder, Lane
Pubblicazione: (2023)

Group-level Brain Decoding with Deep Learning
di: Csaky, Richard, et al.
Pubblicazione: (2022)

Graph Convolutional Neural Networks to Model the Brain for Insomnia
di: Monteiro, Kevin, et al.
Pubblicazione: (2025)

BrainStratify: Coarse-to-Fine Disentanglement of Intracranial Neural Dynamics
di: Zheng, Hui, et al.
Pubblicazione: (2025)

Analyzing Brain Activity During Learning Tasks with EEG and Machine Learning
di: Cho, Ryan, et al.
Pubblicazione: (2024)

EEG-Deformer: A Dense Convolutional Transformer for Brain-computer Interfaces
di: Ding, Yi, et al.
Pubblicazione: (2024)

Brain-OF: An Omnifunctional Foundation Model for fMRI, EEG and MEG
di: Guo, Hanning, et al.
Pubblicazione: (2026)

IMU-Enhanced EEG Motion Artifact Removal with Fine-Tuned Large Brain Models
di: Zhang, Yuhong, et al.
Pubblicazione: (2025)

DeeperBrain: A Neuro-Grounded EEG Foundation Model Towards Universal BCI
di: Wang, Jiquan, et al.
Pubblicazione: (2026)

Investigating Brain Connectivity and Regional Statistics from EEG for early stage Parkinson's Classification
di: Sahota, Amarpal, et al.
Pubblicazione: (2024)

BrainWave: A Brain Signal Foundation Model for Clinical Applications
di: Yuan, Zhizhang, et al.
Pubblicazione: (2024)

BiND: A Neural Discriminator-Decoder for Accurate Bimanual Trajectory Prediction in Brain-Computer Interfaces
di: Robert, Timothee, et al.
Pubblicazione: (2025)

Population Transformer: Learning Population-level Representations of Neural Activity
di: Chau, Geeling, et al.
Pubblicazione: (2024)

convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data
di: Koshkin, Roman, et al.
Pubblicazione: (2024)

When Does Your Brain Know You? Segment Length and Its Impact on EEG-based Biometric Authentication Accuracy
di: Alzahab, Nibras Abo, et al.
Pubblicazione: (2024)

High-Density EEG Enables the Fastest Visual Brain-Computer Interfaces
di: Ming, Gege, et al.
Pubblicazione: (2025)

BrainCognizer: Brain Decoding with Human Visual Cognition Simulation for fMRI-to-Image Reconstruction
di: Sun, Guoying, et al.
Pubblicazione: (2025)

Comparative Analysis of Deep Learning Approaches for Harmful Brain Activity Detection Using EEG
di: Bhatti, Shivraj Singh, et al.
Pubblicazione: (2024)

Bibliometric-enhanced Systematic Literature Review of EEG in Education: Learning Concepts, Computational Methods, and Research Opportunities
di: Wijaya, Adi, et al.
Pubblicazione: (2025)

Quantifying Data Requirements for EEG Independent Component Analysis Using AMICA
di: Frank, Gwenevere, et al.
Pubblicazione: (2025)

Spatial Craving Patterns in Marijuana Users: Insights from fMRI Brain Connectivity Analysis with High-Order Graph Attention Neural Networks
di: Ding, Jun-En, et al.
Pubblicazione: (2024)