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In the past five years, the use of generative and foundational AI systems has greatly improved the decoding of brain activity.
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Thomas A Carlson, Hinze Hogendoorn, Ryota Kanai, Juraj Mesik, and Jeremy Turret · 2011
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Reconstructing visual experiences from brain activity evoked by natural movies
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Resolving human object recognition in space and time
Radoslaw Martin Cichy, Dimitrios Pantazis, and Aude Oliva · 2014
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scikit-image: image processing in python
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Performance-optimized hierarchical models predict neural responses in higher visual cortex
Daniel LK Yamins, Ha Hong, Charles F Cadieu, Ethan A Solomon, Darren Seibert, and James J DiCarlo · 2014
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Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks
Radoslaw Martin Cichy, Aditya Khosla, Dimitrios Pantazis, and Aude Oliva · 2017
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Generic decoding of seen and imagined objects using hierarchical visual features
Tomoyasu Horikawa and Yukiyasu Kamitani · 2017
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Vector-based navigation using grid-like representations in artificial agents
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The temporal evolution of conceptual object representations revealed through models of behavior, semantics and deep neural networks
B.B. Bankson, M.N. Hebart, I.I.A. Groen, and C.I. Baker · 2018
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MOABB: trustworthy algorithm benchmarking for bcis
Vinay Jayaram and Alexandre Barachant · 2018
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Deep convolutional neural networks for mental load classification based on EEG data
Zhicheng Jiao, Xinbo Gao, Ying Wang, Jie Li, and Haojun Xu · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Generative adversarial networks for reconstructing natural images from brain activity
Katja Seeliger, Umut Güçlü, Luca Ambrogioni, Yagmur Güçlütürk, and Marcel AJ van Gerven · 2018
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Neural population control via deep image synthesis
Pouya Bashivan, Kohitij Kar, and James J DiCarlo · 2019
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EEG-ConvTransformer for single-trial EEG-based visual stimulus classification
Subhranil Bagchi and Deepti R Bathula · 2022
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Decoding speech from non-invasive brain recordings
Alexandre Défossez, Charlotte Caucheteux, Jérémy Rapin, Ori Kabeli, and Jean-Rémi King · 2022
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Semantic brain decoding: from fMRI to conceptually similar image reconstruction of visual stimuli
Matteo Ferrante, Tommaso Boccato, and Nicola Toschi · 2022
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A large and rich EEG dataset for modeling human visual object recognition
Alessandro T Gifford, Kshitij Dwivedi, Gemma Roig, and Radoslaw M Cichy · 2022
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A zero-shot deep metric learning approach to brain–computer interfaces for image retrieval
Ben McCartney, Barry Devereux, and Jesus Martinez-del Rincon · 2022
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Tijl Grootswagers, Amanda K Robinson, and Thomas A Carlson · 2019
Cited alongside, same era.
THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images
Martin N Hebart, Adam H Dickter, Alexis Kidder, Wan Y Kwok, Anna Corriveau, Caitlin Van Wicklin, and Chris I Baker · 2019
Cited alongside, same era.
Deep learning-based electroencephalography analysis: a systematic review
Yannick Roy, Hubert Banville, Isabela Albuquerque, Alexandre Gramfort, Tiago H Falk, and Jocelyn Faubert · 2019
Cited alongside, same era.
Reconstructing faces from fMRI patterns using deep generative neural networks
Rufin VanRullen and Leila Reddy · 2019
Cited alongside, same era.
The perils and pitfalls of block design for EEG classification experiments
Ren Li, Jared S Johansen, Hamad Ahmed, Thomas V Ilyevsky, Ronnie B Wilbur, Hari M Bharadwaj, and Jeffrey Mark Siskind · 2020
Cited alongside, same era.
Decoding brain representations by multimodal learning of neural activity and visual features
Simone Palazzo, Concetto Spampinato, Isaak Kavasidis, Daniela Giordano, Joseph Schmidt, and Mubarak Shah · 2020
Cited alongside, same era.
Artificial neural networks accurately predict language processing in the brain
Martin Schrimpf, Idan Blank, Greta Tuckute, Carina Kauf, Eghbal A Hosseini, Nancy Kanwisher, Joshua Tenenbaum, and Evelina Fedorenko · 2020
Cited alongside, same era.
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High-resolution image reconstruction with latent diffusion models from human brain activity
Yu Takagi and Shinji Nishimoto · 2022
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Self-supervised learning of brain dynamics from broad neuroimaging data
Armin Thomas, Christopher Ré, and Russell Poldrack · 2022
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Evidence of a predictive coding hierarchy in the human brain listening to speech
Charlotte Caucheteux, Alexandre Gramfort, and Jean-Rémi King · 2023
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Reconstructing visual illusory experiences from human brain activity
Fan Cheng, Tomoyasu Horikawa, Kei Majima, Misato Tanaka, Mohamed Abdelhack, Shuntaro C Aoki, Jin Hirano, and Yukiyasu Kamitani · 2023
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Decoding and synthesizing tonal language speech from brain activity
Yan Liu, Zehao Zhao, Minpeng Xu, Haiqing Yu, Yanming Zhu, Jie Zhang, Linghao Bu, Xiaoluo Zhang, Junfeng Lu, Yuanning Li, et al · 2023
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Weijian Mai and Zhijun Zhang · 2023
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A high-performance neuroprosthesis for speech decoding and avatar control
Sean L Metzger, Kaylo T Littlejohn, Alexander B Silva, David A Moses, Margaret P Seaton, Ran Wang, Maximilian E Dougherty, Jessie R Liu, Peter Wu, Michael A Berger, et al · 2023
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Natural scene reconstruction from fmri signals using generative latent diffusion
Furkan Ozcelik and Rufin VanRullen · 2023
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Reconstructing the mind’s eye: fMRI-to-image with contrastive learning and diffusion priors
Paul S Scotti, Atmadeep Banerjee, Jimmie Goode, Stepan Shabalin, Alex Nguyen, Ethan Cohen, Aidan J Dempster, Nathalie Verlinde, Elad Yundler, David Weisberg, et al · 2023
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Semantic reconstruction of continuous language from non-invasive brain recordings
Jerry Tang, Amanda LeBel, Shailee Jain, and Alexander G Huth · 2023
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A high-performance speech neuroprosthesis
Francis R Willett, Erin M Kunz, Chaofei Fan, Donald T Avansino, Guy H Wilson, Eun Young Choi, Foram Kamdar, Matthew F Glasser, Leigh R Hochberg, Shaul Druckmann, et al · 2023
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Controllable mind visual diffusion model
Bohan Zeng, Shanglin Li, Xuhui Liu, Sicheng Gao, Xiaolong Jiang, Xu Tang, Yao Hu, Jianzhuang Liu, and Baochang Zhang · 2023
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THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior
Martin N Hebart, Oliver Contier, Lina Teichmann, Adam H Rockter, Charles Y Zheng, Alexis Kidder, Anna Corriveau, Maryam Vaziri-Pashkam, and Chris I Baker · 2050
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