Fetching the paper…
Reading the bibliography…
The exploration of brain activity and its decoding from fMRI data has been a longstanding pursuit, driven by its potential applications in brain-computer interfaces, medical diagnostics, and virtual reality.
Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation
Kenneth K Kwong, John W Belliveau, David A Chesler, Inna E Goldberg, Robert M Weisskoff, Brigitte P Poncelet, David N Kennedy, Bernice E Hoppel, Mark S Cohen, and Robert Turner · 1992
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
Earlier work this paper cites.
Pearson correlation coefficient
Israel Cohen, Yiteng Huang, Jingdong Chen, Jacob Benesty, Jacob Benesty, Jingdong Chen, Yiteng Huang, and Israel Cohen · 2009
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Decoding brain states from fmri connectivity graphs
Jonas Richiardi, Hamdi Eryilmaz, Sophie Schwartz, Patrik Vuilleumier, and Dimitri Van De Ville · 2011
Earlier work this paper cites.
The minimal preprocessing pipelines for the human connectome project
Matthew F Glasser, Stamatios N Sotiropoulos, J Anthony Wilson, Timothy S Coalson, Bruce Fischl, Jesper L Andersson, Junqian Xu, Saad Jbabdi, Matthew Webster, Jonathan R Polimeni, et al · 2013
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
Pycortex: an interactive surface visualizer for fmri
James S Gao, Alexander G Huth, Mark D Lescroart, and Jack L Gallant · 2015
Earlier work this paper cites.
A multi-modal parcellation of human cerebral cortex
Matthew F. Glasser, Timothy S. Coalson, Emma C. Robinson, Carl D. Hacker, John Harwell, Essa Yacoub, Kamil Ugurbil, Jesper Andersson, Christian F. Beckmann, Mark Jenkinson, Stephen M. Smith, and David C. Van Essen · 2016
Earlier work this paper cites.
Multimodal population brain imaging in the uk biobank prospective epidemiological study
Karla L Miller, Fidel Alfaro-Almagro, Neal K Bangerter, David L Thomas, Essa Yacoub, Junqian Xu, Andreas J Bartsch, Saad Jbabdi, Stamatios N Sotiropoulos, Jesper LR Andersson, et al · 2016
Earlier work this paper cites.
Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
Earlier work this paper cites.
Generic decoding of seen and imagined objects using hierarchical visual features
Tomoyasu Horikawa and Yukiyasu Kamitani · 2017
Earlier work this paper cites.
Neural networks for efficient bayesian decoding of natural images from retinal neurons
Nikhil Parthasarathy, Eleanor Batty, William Falcon, Thomas Rutten, Mohit Rajpal, EJ Chichilnisky, and Liam Paninski · 2017
Earlier work this paper cites.
Robust inter-subject audiovisual decoding in functional magnetic resonance imaging using high-dimensional regression
Gal Raz, Michele Svanera, Neomi Singer, Gadi Gilam, Maya Bleich Cohen, Tamar Lin, Roee Admon, Tal Gonen, Avner Thaler, Roni Y Granot, et al · 2017
Earlier work this paper cites.
Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
Earlier work this paper cites.
Image processing and quality control for the first 10,000 brain imaging datasets from uk biobank
Fidel Alfaro-Almagro, Mark Jenkinson, Neal K Bangerter, Jesper LR Andersson, Ludovica Griffanti, Gwenaëlle Douaud, Stamatios N Sotiropoulos, Saad Jbabdi, Moises Hernandez-Fernandez, Emmanuel Vallee, et al · 2018
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
Across-subject offline decoding of motor imagery from meg and eeg
Hanna-Leena Halme and Lauri Parkkonen · 2018
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
Cited alongside, same era.
Interpreting and utilising intersubject variability in brain function
Mohamed L Seghier and Cathy J Price · 2018
Cited alongside, same era.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
Cited alongside, same era.
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fmri
Roman Beliy, Guy Gaziv, Assaf Hoogi, Francesca Strappini, Tal Golan, and Michal Irani · 2019
Cited alongside, same era.
End-to-end deep image reconstruction from human brain activity
Guohua Shen, Kshitij Dwivedi, Kei Majima, Tomoyasu Horikawa, and Yukiyasu Kamitani · 2019
Cited alongside, same era.
Adaptive neural network classifier for decoding meg signals
Florence: A new foundation model for computer vision
Lu Yuan, Dongdong Chen, Yi-Ling Chen, Noel Codella, Xiyang Dai, Jianfeng Gao, Houdong Hu, Xuedong Huang, Boxin Li, Chunyuan Li, et al · 2021
Later among the works it cites.
A massive 7t fmri dataset to bridge cognitive neuroscience and artificial intelligence
Emily J Allen, Ghislain St-Yves, Yihan Wu, Jesse L Breedlove, Jacob S Prince, Logan T Dowdle, Matthias Nau, Brad Caron, Franco Pestilli, Ian Charest, et al · 2022
Later among the works it cites.
Maskgit: Masked generative image transformer
Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T. Freeman · 2022
Later among the works it cites.
Seeing beyond the brain: Conditional diffusion model with sparse masked modeling for vision decoding
Zijiao Chen, Jiaxin Qing, Tiange Xiang, Wan Lin Yue, and Juan Helen Zhou · 2022
Later among the works it cites.
Decoding natural image stimuli from fmri data with a surface-based convolutional network
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ivan Zubarev, Rasmus Zetter, Hanna-Leena Halme, and Lauri Parkkonen · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
Cited alongside, same era.
Reconstructing natural scenes from fmri patterns using bigbigan
Milad Mozafari, Leila Reddy, and Rufin VanRullen · 2020
Cited alongside, same era.
Deep learning based inter-subject continuous decoding of motor imagery for practical brain-computer interfaces
Sujit Roy, Anirban Chowdhury, Karl McCreadie, and Girijesh Prasad · 2020
Cited alongside, same era.
Inter-subject pattern analysis: A straightforward and powerful scheme for group-level mvpa
Qi Wang, Bastien Cagna, Thierry Chaminade, and Sylvain Takerkart · 2020
Cited alongside, same era.
An empirical evaluation of functional alignment using inter-subject decoding
Thomas Bazeille, Elizabeth Dupre, Hugo Richard, Jean-Baptiste Poline, and Bertrand Thirion · 2021
Cited alongside, same era.
Zijin Gu, Keith Jamison, Amy Kuceyeski, and Mert Sabuncu · 2022
Later among the works it cites.
Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
Later among the works it cites.
Mind reader: Reconstructing complex images from brain activities
Sikun Lin, Thomas Sprague, and Ambuj K Singh · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
Self-supervised learning of brain dynamics from broad neuroimaging data
Armin Thomas, Christopher Ré, and Russell Poldrack · 2022
Later among the works it cites.
Coca: Contrastive captioners are image-text foundation models
Jiahui Yu, Zirui Wang, Vijay Vasudevan, Legg Yeung, Mojtaba Seyedhosseini, and Yonghui Wu · 2022
Later among the works it cites.
Brainlm: A foundation model for brain activity recordings
Josue Ortega Caro, Antonio H. de O. Fonseca, Christopher Averill, Syed A. Rizvi, Matteo Rosati, James L. Cross, Prateek Mittal, Emanuele Zappala, Daniel Levine, Rahul M. Dhodapkar, Chadi G. Abdallah, and David van Dijk · 2023
Closest in time.
Cinematic mindscapes: High-quality video reconstruction from brain activity
Zijiao Chen, Jiaxin Qing, and Juan Helen Zhou · 2023
Closest in time.
Decoding visual neural representations by multimodal learning of brain-visual-linguistic features
Changde Du, Kaicheng Fu, Jinpeng Li, and Huiguang He · 2023
Closest in time.
The algonauts project 2023 challenge: How the human brain makes sense of natural scenes
Alessandro T Gifford, Benjamin Lahner, Sari Saba-Sadiya, Martina G Vilas, Alex Lascelles, Aude Oliva, Kendrick Kay, Gemma Roig, and Radoslaw M Cichy · 2023
Closest in time.
Yulong Liu, Yongqiang Ma, Wei Zhou, Guibo Zhu, and Nanning Zheng · 2023
Closest in time.
Brain-diffuser: Natural scene reconstruction from fmri signals using generative latent diffusion
Furkan Ozcelik and Rufin VanRullen · 2023
Closest in time.
Joint fmri decoding and encoding with latent embedding alignment
Xuelin Qian, Yikai Wang, Yanwei Fu, Xinwei Sun, Jianfeng Feng, and Xiangyang Xue · 2023
Closest in time.
High-resolution image reconstruction with latent diffusion models from human brain activity
Yu Takagi and Shinji Nishimoto · 2023
Closest in time.