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In neural decoding research, one of the most intriguing topics is the reconstruction of perceived natural images based on fMRI signals.
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H. & Wiesel, T. N · 1962
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Visual properties of neurons in inferotemporal cortex of the macaque
Gross, C. G., Rocha-Miranda, C. d. & Bender, D · 1972
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Visual neurones responsive to faces in the monkey temporal cortex
Perrett, D., Rolls, E. & Caan, W · 1982
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Selectivity for polar, hyperbolic, and cartesian gratings in macaque visual cortex
Gallant, J. L., Braun, J. & Van Essen, D. C · 1993
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Neural mechanisms of form and motion processing in the primate visual system
Van Essen, D. C. & Gallant, J. L · 1994
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The fusiform face area: a module in human extrastriate cortex specialized for face perception
Kanwisher, N., McDermott, J. & Chun, M. M · 1997
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A cortical representation of the local visual environment
Epstein, R. & Kanwisher, N · 1998
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Distributed and overlapping representations of faces and objects in ventral temporal cortex
Haxby, J. V. et al · 2001
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Functional magnetic resonance imaging (fmri)“brain reading”: detecting and classifying distributed patterns of fmri activity in human visual cortex
Cox, D. D. & Savoy, R. L · 2003
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Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R. & Simoncelli, E. P · 2004
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Comparative mapping of higher visual areas in monkeys and humans
Orban, G. A., Van Essen, D. & Vanduffel, W · 2004
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Decoding the visual and subjective contents of the human brain
Kamitani, Y. & Tong, F · 2005
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Predicting the orientation of invisible stimuli from activity in human primary visual cortex
Haynes, J.-D. & Rees, G · 2005
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Inverse retinotopy: inferring the visual content of images from brain activation patterns
Thirion, B. et al · 2006
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Identifying natural images from human brain activity
Kay, K. N., Naselaris, T., Prenger, R. J. & Gallant, J. L · 2008
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Visual image reconstruction from human brain activity using a combination of multiscale local image decoders
Miyawaki, Y. et al · 2008
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Imagenet: A large-scale hierarchical image database
Deng, J. et al · 2009
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Auto-encoding variational bayes
Kingma, D. P. & Welling, M · 2013
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Microsoft coco: Common objects in context
Lin, T.-Y. et al · 2014
Cited alongside, same era.
Rethinking the inception architecture for computer vision
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J. & Wojna, Z · 2016
Cited alongside, same era.
Generic decoding of seen and imagined objects using hierarchical visual features
Horikawa, T. & Kamitani, Y · 2017
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I. & Hinton, G. E · 2017
Cited alongside, same era.
Reconstructing faces from fmri patterns using deep generative neural networks
VanRullen, R. & Reddy, L · 2019
Hyperrealistic neural decoding for reconstructing faces from fmri activations via the gan latent space
Dado, T. et al · 2022
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A massive 7t fmri dataset to bridge cognitive neuroscience and artificial intelligence
Allen, E. J. et al · 2022
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Mind reader: Reconstructing complex images from brain activities
Lin, S., Sprague, T. C. & Singh, A · 2022
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Self-supervised natural image reconstruction and large-scale semantic classification from brain activity
Gaziv, G. et al · 2022
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Reconstruction of perceived images from fmri patterns and semantic brain exploration using instance-conditioned gans
Ozcelik, F., Choksi, B., Mozafari, M., Reddy, L. & VanRullen, R · 2022
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Cited alongside, same era.
Deep image reconstruction from human brain activity
Shen, G., Horikawa, T., Majima, K. & Kamitani, Y · 2019
Cited alongside, same era.
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fmri
Beliy, R. et al · 2019
Cited alongside, same era.
Efficientnet: Rethinking model scaling for convolutional neural networks
Tan, M. & Le, Q · 2019
Cited alongside, same era.
Neural population control via deep image synthesis
Bashivan, P., Kar, K. & DiCarlo, J. J · 2019
Cited alongside, same era.
Reconstructing natural scenes from fmri patterns using bigbigan
Mozafari, M., Reddy, L. & VanRullen, R · 2020
Cited alongside, same era.
Unsupervised learning of visual features by contrasting cluster assignments
Caron, M. et al · 2020
Cited alongside, same era.
Rombach, R., Blattmann, A., Lorenz, D., Esser, P. & Ommer, B · 2022
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Hierarchical text-conditional image generation with clip latents
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C. & Chen, M · 2022
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Nichol, A. Q. et al · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C. et al · 2022
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Versatile diffusion: Text, images and variations all in one diffusion model
Xu, X., Wang, Z., Zhang, E., Wang, K. & Shi, H · 2022
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Neurogen: activation optimized image synthesis for discovery neuroscience
Gu, Z. et al · 2022
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Reconstructing rapid natural vision with fmri-conditional video generative adversarial network
Wang, C. et al · 2022
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Kupershmidt, G., Beliy, R., Gaziv, G. & Irani, M · 2022
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Seeing beyond the brain: Conditional diffusion model with sparse masked modeling for vision decoding
Chen, Z., Qing, J., Xiang, T., Yue, W. L. & Zhou, J. H · 2023
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High-resolution image reconstruction with latent diffusion models from human brain activity
Takagi, Y. & Nishimoto, S · 2023
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Decoding natural image stimuli from fMRI data with a surface-based convolutional network
Gu, Z., Jamison, K., Kuceyeski, A. & Sabuncu, M. R · 2023
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Macaques recognize features in synthetic images derived from ventral stream neurons
Mueller, K. N., Carter, M. C., Kansupada, J. A. & Ponce, C. R · 2023
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