Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review | Paper Citation Record

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This paper cites On the Opportunities and Risks of Foundation Models.

Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review On the Opportunities and Risks of Foundation Models

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This paper cites Large-scale foundation models and generative ai for bigdata neuro- science,.

Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Large-scale foundation models and generative ai for bigdata neuro- science,

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This paper cites Brain Foundation Models: A Survey on Advancements in Neural Signal Processing and Brain Discovery.

Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Brain Foundation Models: A Survey on Advancements in Neural Signal Processing and Brain Discovery

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review A review of classification algorithms for eeg-based brain–computer interfaces,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Foundation model of neural activity predicts response to new stimulus types,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Deep learning with convolutional neural networks for eeg decoding and visualization,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Momentum contrast for unsupervised visual representation learning,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Brant: Foundation model for intracra- nial neural signal,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Bendr: Using transformers and a contrastive self-supervised learning task to learn from massive amounts of eeg data,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Brain-jepa: Brain dynamics foundation model with gradient positioning and spatiotemporal masking,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Brain–computer interfaces in 2023– 2024,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review High- performance brain-to-text communication via handwriting,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Learning transferable visual models from natural language super- vision,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Artificial intelligence for clinical decision support in neurology,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Mindbridge: A cross-subject brain decoding frame- work,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Natural scene reconstruction from fmri signals using generative latent diffusion,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Data augmentation for eeg motor imagery classification using diffusion model,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review The future of multimodal artificial intelligence models for integrating imaging and clinical metadata: A narrative review,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Multimodal integration of neuroimaging and genetic data for the diagnosis of mood disorders based on computer vision models,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review A deep learning framework for neuroscience,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Toward brain-inspired foundation model for eeg signal processing: our opinion,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Large language models surpass human experts in predicting neuro- science results,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review A million spiking-neuron integrated circuit with a scalable communication network and interface,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Loihi: A neuromorphic manycore processor with on-chip learning,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Towards spike-based machine intelligence with neuromorphic computing,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Data science opportunities of large language models for neuroscience and biomedicine,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review The neuroconnectionist research programme,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Deep neural networks as scientific models,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Recurrence is required to capture the representational dynamics of the human visual system,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Attention is all you need. neurips, 2017,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Scaling Laws for Neural Language Models

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Cbramod: A criss-cross brain foundation model for eeg decoding,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Data

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Brainsegfounder: towards 3d foundation models for neuroimage segmentation,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Anatomical foundation models for brain mris,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Alphagenome: advancing regulatory variant effect prediction with a unified dna sequence model,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Effective gene expression prediction from sequence by integrating long-range interactions,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Vsvig: Real-time video-based seizure detection via skeleton-based spatiotemporal vig,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review A brain graph foundation model: Pre-training and prompt-tuning for any atlas and disorder,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Shade-ad: An llm-based framework for synthesizing activity data of alzheimer’s patients,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review A llm-based hybrid-transformer diagnosis system in healthcare,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review DECT: Harnessing LLM-assisted Fine-Grained Linguistic Knowledge and Label-Switched and Label-Preserved Data Generation for Diagnosis of Alzheimer's Disease

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review The role of foundation models in neuro-symbolic learning and reasoning,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Centaur: a foundation model of human cognition

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Seeing beyond the brain: Condi- tional diffusion model with sparse masked modeling for vision decoding,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review EEGFormer: Towards Transferable and Interpretable Large-Scale EEG Foundation Model

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review 3D Foundation Model for Generalizable Disease Detection in Head Computed Tomography

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Pre-trained models for natural language processing: A survey,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Language models are few-shot learners,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review The Power of Scale for Parameter-Efficient Prompt Tuning

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Lora: Low-rank adaptation of large language models.,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Retrieval-augmented generation for knowledge-intensive nlp tasks,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Linking brain, mind and behavior,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Eeg source imaging,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Transfer learning in brain-computer interfaces,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Braingnn: Interpretable brain graph neural network for fmri analysis,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Self-supervised learning of brain dynamics from broad neuroimaging data,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review The prep pipeline: standardized preprocessing for large-scale eeg analysis,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Reconstructing the mind’s eye: fmri-to-image with contrastive learning and diffusion priors,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Brain network transformer,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Hierarchical spatio-temporal state-space modeling for fmri analysis,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Neuropictor: Refining fmri-to- image reconstruction via multi-individual pretraining and multi-level modulation,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review A foundation model for generalized brain mri analysis,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review A Non-contrast Head CT Foundation Model for Comprehensive Neuro-Trauma Triage

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review BrainGPT: Unleashing the Potential of EEG Generalist Foundation Model by Autoregressive Pre-training

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review FoME: A Foundation Model for EEG using Adaptive Temporal-Lateral Attention Scaling

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review CodeBrain: Bridging Decoupled Tokenizer and Multi-Scale Architecture for EEG Foundation Model

Reference 82

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Brainomni: A brain foundation model for unified eeg and meg signals,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review BrainStratify: Coarse-to-Fine Disentanglement of Intracranial Neural Dynamics

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Luna: Efficient and topology-agnostic founda- tion model for eeg signal analysis,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review CRIA: A Cross-View Interaction and Instance-Adapted Pre-training Framework for Generalizable EEG Representations

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review BrainWave: A Brain Signal Foundation Model for Clinical Applications

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review ALFEE: Adaptive Large Foundation Model for EEG Representation

Reference 88

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Lead: Large foundation model for eeg-based alzheimer’s disease detection,

Reference 90

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Multimodal foundation models are better simulators of the human brain

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review A multimodal LLM for the non-invasive decoding of spoken text from brain recordings

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Adagent: Llm agent for alzheimer’s disease analysis with collaborative coordinator,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review ASD-Chat: An Innovative Dialogue Intervention System for Children with Autism based on LLM and VB-MAPP

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Large language models surpass human experts in predicting neuro- science results,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Towards a holistic framework for multimodal llm in 3d brain ct radiology report generation,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Episemollm: A fine-tuned large language model for epileptogenic zone localization based on seizure semiology with a performance comparable to epileptologists,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Exkg-llm: Leveraging large language mod- els for automated expansion of cognitive neuroscience knowledge graphs,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Automatic generation of brain tumor diagnostic reports from multimodality mri using large language models,

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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review Mslesionllm: A tool to extract key radiological metrics from real- world multiple sclerosis datasets (p2-1.002),

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