Papers
and pre-prints
Here
are links to papers that use NSD data.
- Fractional Ridge Regression: a
Fast, Interpretable Reparameterization of Ridge
Regression.
Rokem,
A. & Kay, K.
GigaScience (2020).
- Extensive sampling for complete
models of individual brains.
Naselaris,
T., Allen, E., & Kay, K.
Current Opinion in Behavioral
Sciences (2021).
- A massive 7T fMRI dataset to bridge
cognitive neuroscience and artificial intelligence.
Allen,
St-Yves, Wu, Breedlove, Prince, Dowdle, Nau, Caron,
Pestilli, Charest, Hutchinson, Naselaris*, & Kay*.
Nature Neuroscience (2022).
- NeuroGen: activation optimized
image synthesis for discovery neuroscience.
Gu,
Z., Jamison, K.W., Khosla, M., Allen, E.J., Wu, Y.,
Naselaris, T., Kay, K., Sabuncu, M.R., Kuceyeski, A.
NeuroImage (2022).
- Non-Neural Factors Influencing BOLD
Response Magnitudes within Individual Subjects.
Kurzawski, J.W., Gulban, O.F., Jamison, K., Winawer,
J.*, Kay, K.*
Journal of Neuroscience
(2022).
- Improving the accuracy of
single-trial fMRI response estimates using
GLMsingle.
Prince, J.S., Charest, I., Kurzawski, J.W., Pyles,
J.A., Tarr, M.J., Kay, K.N.
eLife (2022).
- Personalized visual encoding model
construction with small data.
Zijin Gu, Keith Jamison, Mert Sabuncu, and Amy
Kuceyeski
Communications Biology
(2022).
- Selectivity for food in human
ventral visual cortex.
Nidhi Jain, Aria Wang, Margaret M. Henderson, Ruogu
Lin, Jacob S. Prince, Michael J. Tarr, and Leila Wehbe
Communications Biology (2023).
- Short-term plasticity in the human
visual thalamus.
Jan W Kurzawski, Claudia Lunghi, Laura Biagi, Michela
Tosetti, Maria Concetta Morrone, Paola Binda
eLife (2022).
- Color-biased regions in the ventral
visual pathway are food selective.
Pennock, I.M.L., Racey, C., Allen, E.J., Wu, Y.,
Naselaris, T., Kay, K.N., Franklin, A., Bosten, J.M.
Current Biology (2022).
- Multiple Traces and Altered
Signal-to-Noise in Systems Consolidation:
Complementary Evidence from the 7T fMRI Natural
Scenes Dataset.
Vanasse, T.J., Boly, M., Allen, E.J., Wu, Y.,
Naselaris, T., Kay, K., Cirelli, C., Tononi, G.
PNAS (2022).
- The risk of bias in data denoising
methods: examples from neuroimaging.
Kay, K.
PLoS One (2022).
- A Highly Selective Response to Food
in Human Visual Cortex Revealed by Hypothesis-Free
Voxel Decomposition.
Meenakshi Khosla, N. Apurva Ratan
Murty, Nancy G Kanwisher
Current Biology (2022).
- Low-level tuning biases in higher
visual cortex reflect the semantic informativeness
of visual features.
Margaret Henderson, Michael J. Tarr, Leila Wehbe
Journal of Vision (2023).
- Re-expression of CA1 and entorhinal
activity patterns preserves temporal context memory
at long timescales.
Futing Zou, Wanjia Guo, Emily J. Allen, Yihan Wu, Ian
Charest, Thomas Naselaris, Kendrick Kay, Brice A.
Kuhl, J. Benjamin Hutchinson, Sarah DuBrow
Nature Communications (2023).
- A texture statistics encoding model
reveals hierarchical feature selectivity across
human visual cortex.
Margaret M. Henderson, Michael J. Tarr,
Leila Wehbe
Journal of Neuroscience
(2023).
- Natural scene sampling reveals
reliable coarse-scale orientation tuning in human
V1.
Roth, Z.N., Kay, K.*, Merriam, E.P.*
Nature Communications
(2022).
- Representations in human primary
visual cortex drift over time.
Roth, Z.N., Merriam, E.P.
Nature Communications
(2023).
- Human brain responses are modulated
when exposed to optimized natural images or
synthetically generated images
Zijin Gu, Keith Jamison, Mert R. Sabuncu, and Amy
Kuceyeski
Communications Biology
(2023).
- Brain-optimized
deep neural networks of human visual areas learn
non-hierarchical representations.
St-Yves, G., Allen, E.J., Wu, Y., Kay, K.*, Naselaris,
T.*
Nature Communications (2023).
- Natural scene reconstruction from
fMRI signals using generative latent diffusion
Furkan Ozcelik and Rufin VanRullen.
Scientific Reports (2023).
- Better models of human high-level
visual cortex emerge from natural language
supervision with a large and diverse dataset.
Wang, A.Y., Kay, K., Naselaris, T., Tarr, M.J., Wehbe,
L.
Nature Machine Intelligence
(2023).
Here
are links to conference papers and pre-prints that use
NSD data.
- What can 5.17 billion regression
fits tell us about artificial models of the human
visual system?
Colin Conwell, Jacob S. Prince, George A. Alvarez,
Talia Konkle
NeurIPS SVRHM workshop
(2021).
- Large-Scale Benchmarking of Diverse
Artificial Vision Models in Prediction of 7T Human
Neuroimaging Data.
Colin Conwell, Jacob S. Prince, George A.
Alvarez, Talia Konkle
bioRxiv (2022).
- High-level visual areas act like
domain-general filters with strong selectivity and
functional specialization.
Meenakshi Khosla, Leila Wehbe
bioRxiv (2022).
- Semantic scene descriptions as an
objective of human vision
Doerig, A., Kietzmann, T.C., Allen, E., Wu, Y.,
Naselaris, T., Kay, K., Charest, I.
arXiv (2022).
- Mind Reader: Reconstructing complex
images from brain activities.
Sikun Lin, Thomas Sprague, Ambuj K Singh.
arXiv (2022).
- High-resolution image
reconstruction with latent diffusion models from
human brain activity.
Takagi, Y., Nishimoto, S.
bioRxiv (2022).
- Decoding natural image stimuli from
fMRI data with a surface-based convolutional
network.
Zijin Gu, Keith Jamison, Amy
Kuceyeski, Mert Sabuncu
arXiv (2022).
- Sample Reweighting for Label
Denoising of Neural Activity Data
Dongfang Xu, Rong Chen
IEEE/EMBS Conference on Neural
Engineering (2023)
- The Algonauts Project 2023
Challenge: How the Human Brain Makes Sense of
Natural Scenes.
A.T. Gifford, B. Lahner, S. Saba-Sadiya, M.G. Vilas,
A. Lascelles, A. Oliva, K. Kay, G. Roig, R.M. Cichy.
arXiv (2023).
- Neural Selectivity for Real-World
Object Size In Natural Images
Andrew F. Luo, Leila Wehbe, Michael
J. Tarr, Margaret M. Henderson
bioRxiv (2023)
- MindDiffuser: Controlled Image
Reconstruction from Human Brain Activity with
Semantic and Structural Diffusion
Yizhuo Lu, Changde Du, Dianpeng Wang, Huiguang He
arXiv (2023).
- The transition from vision to
language: distinct patterns of functional
connectivity for sub-regions of the visual word form
area
Maya Yablonski, Iliana
I Karipidis, Emily Kubota, Jason
D Yeatman
bioRxiv (2023).
- Reconstructing seen images from
human brain activity via guided stochastic search
Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves, Thomas
Naselaris
arXiv (2023).
- BrainCLIP: Bridging Brain and
Visual-Linguistic Representation Via CLIP for
Generic Natural Visual Stimulus Decoding
Yulong Liu, Yongqiang Ma, Wei Zhou, Guibo Zhu, Nanning
Zheng
arXiv (2023).
- Brain Captioning: Decoding human
brain activity into images and text
Matteo Ferrante, Furkan Ozcelik, Tommaso Boccato,
Rufin VanRullen, Nicola Toschi
arXiv (2023).
- A Unifying Principle for the
Functional Organization of Visual Cortex
Eshed Margalit, Hyodong Lee, Dawn Finzi, James J.
DiCarlo, Kalanit Grill-Spector, Daniel L. K. Yamins
arXiv (2023).
- 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, Kenneth A. Norman*, and Tanishq Mathew
Abraham*
arXiv (2023).
- Brain Dissection: fMRI-trained
Networks Reveal Spatial Selectivity in the
Processing of Natural Images
Gabriel H. Sarch, Michael J. Tarr, Katerina
Fragkiadaki, Leila Wehbe
arXiv (2023).
- Second Sight: Using brain-optimized
encoding models to align image distributions with
human brain activity
Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves, Thomas
Naselaris
arXiv (2023).
- Brain Diffusion for Visual
Exploration: Cortical Discovery using Large Scale
Generative Models.
Andrew F. Luo, Margaret M. Henderson, Leila Wehbe,
Michael J. Tarr
arXiv (2023). [NeurIPS
2023 (Oral)].
- Improving visual image
reconstruction from human brain activity using
latent diffusion models via multiple decoded inputs.
Yu Takagi, Shinji Nishimoto
arXiv (2023).
- DreamCatcher: Revealing the
Language of the Brain with fMRI using GPT Embedding
Subhrasankar Chatterjee, Debasis Samanta
arXiv (2023).
- What can 1.8 billion regressions
tell us about the pressures shaping high-level
visual representation in brains and machines?
Colin Conwell, Jacob S. Prince, Kendrick N. Kay,
George A. Alvarez, Talia Konkle
bioRxiv (2023)
- THE ALGONAUTS PROJECT 2023
CHALLENGE: UARK-UALBANY TEAM SOLUTION
Xuan Bac Nguyen, Xudong Liu, Xin Li, Khoa Luu
arXiv (2023)
- Memory Encoding Model
Huzheng Yang, James Gee, Jianbo Shi
arXiv (2023)
- Applicability of scaling laws to
vision encoding models
Takuya Matsuyama, Kota S Sasaki, Shinji Nishimoto
arXiv (2023).
- A contrastive coding account of
category selectivity in the ventral visual stream
Jacob S. Prince, George A. Alvarez,
Talia Konkle
bioRxiv (2023).
- Predicting brain activity using
Transformers
Hossein Adeli, Sun Minni, Nikolaus Kriegeskorte
bioRxiv (2023).
- A Parameter-efficient Multi-subject
Model for Predicting fMRI Activity
Connor Lane, Gregory Kiar
arXiv (2023).
- Expansion of a frontostriatal
salience network in individuals with depression
Charles J. Lynch, I. Elbau, Tommy Ng, Aliza Ayaz,
Shasha Zhu, Nicola Manfredi, Megan A. Johnson, Daniel
L Wolk, Jonathan D. Power, E. Gordon, Kendrick Norris
Kay, A. Aloysi, Stefano Moia, C. Caballero-Gaudes, L.
Victoria, N. Solomonov, E. Goldwaser, Benjamin Zebley,
L. Grosenick, J. Downar, F. Vila-Rodriguez, Z.
Daskalakis, D. Blumberger, N. Williams, F. Gunning, C.
Liston
bioRxiv (2023).
- UniBrain: Unify Image
Reconstruction and Captioning All in One Diffusion
Model from Human Brain Activity
Weijian Mai, Zhijun Zhang
arXiv (2023).
- A Multimodal Visual Encoding Model
Aided by Introducing Verbal Semantic Information
Ma Shuxiao, Wang Linyuan, Yan Bin
arXiv (2023).
- Through their eyes: multi-subject
Brain Decoding with simple alignment techniques
Matteo Ferrante, Tommaso Boccato, and Nicola Toschi
arXiv (2023).
- Direct
perception of affective valence from vision
Saeedeh Sadeghi, Zijin Gu, Eve DeRosa, Amy Kuceyeski,
Adam K. Anderson
psyArXiv (2023).
- Dissociable contributions of the
medial parietal cortex to recognition memory
Seth R. Koslov, Joseph W. Kable, & Brett L. Foster
bioRxiv (2023).
- UNIDIRECTIONAL BRAIN-COMPUTER
INTERFACE: ARTIFICIAL NEURAL NETWORK ENCODING
NATURAL IMAGES TO fMRI RESPONSE IN THE VISUAL CORTEX
Ruixing Liang, Xiangyu Zhang, Qiong Li, Lai Wei, Hexin
Liu, Avisha Kumar, Kelley M. Kempski Leadingham,
Joshua Punnoose, Leibny Paola Garcia, Amir Manbachi
arXiv (2023).
- Cortical and subcortical brain
networks predict prevailing heart rate
Amy Isabella Sentis,
Javier Rasero, Peter
J. Gianaros, Timothy D. Verstynen
bioRxiv (2023).
- DREAM: Visual Decoding from
REversing HumAn Visual SysteM
Weihao Xia, Raoul de Charette, Cengiz Oztireli,
Jing-Hao Xue
arXiv (2023).
- BrainSCUBA: Fine-Grained Natural
Language Captions of Visual Cortex Selectivity
Andrew F. Luo, Margaret M. Henderson, Michael J. Tarr,
Leila Wehbe
arXiv (2023).
- IDENTIFYING INTERPRETABLE VISUAL
FEATURES IN
ARTIFICIAL AND BIOLOGICAL NEURAL
SYSTEMS
David Klindt, Sophia Sanborn, Francisco Acosta, Fr ́ed
́eric Poitevin, Nina Miolane
arXiv (2023).
- fMRI-PTE: A Large-scale fMRI
Pretrained Transformer Encoder for Multi-Subject
Brain Activity Decoding
Xuelin Qian, Yun Wang, Jingyang Huo, Jianfeng Feng,
Yanwei Fu
arXiv (2023).
- BRAIN DECODING: TOWARD REAL-TIME
RECONSTRUCTION OF VISUAL PERCEPTION
Yohann Benchetrit, Hubert Banville, Jean-Remi King
arXiv (2023).
- Soft Matching Distance: A metric on
neural representations that captures single-neuron
tuning
Meenakshi Khosla, Alex H. Williams
arXiv (2023).
- Brainformer: Modeling MRI Brain
Functions to Machine Vision
Xuan-Bac Nguyen , Xin Li, Samee U. Khan, Khoa Luu
arXiv (2023)
- Brain Decodes Deep Nets
Huzheng Yang, James Gee*, Jianbo Shi*
arXiv (2023)
- OneLLM: One Framework to Align All
Modalities with Language
Jiaming Han, Kaixiong Gong, Yiyuan Zhang, Jiaqi Wang,
Kaipeng Zhang,
Dahua Lin, Yu Qiao, Peng Gao, Xiangyu Yue
arXiv (2023).
- Lite-Mind: Towards Efficient and
Versatile Brain Representation Network
Zixuan Gong, Qi Zhang, Duoqian Miao, Guangyin Bao,
Liang Hu
arXiv (2023).
- Multimodal decoding of human brain
activity into images and text
Matteo Ferrante, Tommaso Boccato, Furkan Ozcelik,
Rufin VanRullen, Nicola Toschi
NeurIPS (2023).
- ALIGNING BRAIN FUNCTIONS BOOSTS THE
DECODING OF VISUAL SEMANTICS IN NOVEL SUBJECTS
Alexis Thual, Yohann Benchetrit, Felix Geilert, Jeremy
Rapin, Iurii Makarov, Hubert Banville, Jean-Remi King
arXiv (2023).
- Brain-optimized inference improves
reconstructions of fMRI brain activity
Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves, Thomas
Naselaris
arXiv (2023).
- Body Cosmos: An Immersive
Experience Driven by Real-Time Bio-Data
Rem RunGu Lin; Yongen Ke; Kang Zhang
IEEE VIS Arts Program (VISAP)
(2023).
- MinD-3D: Reconstruct High-quality
3D objects in Human Brain
Jianxiong Gao, Yuqian Fu, Yun Wang, Xuelin Qian,
Jianfeng Feng, Yanwei Fu
arXiv (2023).
- A single computational objective
drives specialization of streams in visual cortex
Dawn Finzi, Eshed Margalit, Kendrick Kay, Daniel L. K.
Yamins, Kalanit Grill-Spector
bioRxiv (2023).
- Evaluation of Representational
Similarity Scores Across Human Visual Cortex
Francisco Acosta, Colin Conwell, Sophia
Sanborn, David A. Klindt, Nina Miolane
NeurIPS (2023).
- A randomized algorithm to solve
reduced rank operator regression
Giacomo Turri*, Vladimir Kostic*, Pietro Novelli*, and
Massimiliano Pontil
arXiv (2023).
- Aligned with LLM: a new multi-modal
training paradigm for encoding fMRI activity in
visual cortex
Shuxiao Ma, Linyuan Wang, Senbao Hou, Bin Yan
arXiv (2024).
- Recent statistics shift object
representations in parahippocampal cortex
Solomon, S.H., Kay, K., & Schapiro, A.C.
bioRxiv (2024).
- Parsing Brain Network
Specialization: A Replication and Expansion of Wang
et al. (2014)
Madeline Peterson, Dorothea L. Floris, and Jared A.
Nielsen
bioRxiv (2024).
- CLIP-MUSED: CLIP-GUIDED
MULTI-SUBJECT VISUAL NEURAL INFORMATION SEMANTIC
DECODING
Qiongyi Zhou, Changde Du, Shengpei Wang and Huiguang
He
ICLR (2024).
- NeuralDiffuser: Controllable fMRI
Reconstruction with Primary Visual Feature Guided
Diffusion
Haoyu Li, Hao Wu, Badong Chen
arXiv (2024).
- Visual Image Reconstruction from
Human Brain Activity using Linear Image Decoders
plus Nonlinear Noise Suppression
Qiang Li
bioRxiv (2024).
Sample data acquired on the 8 subjects:
T1-weighted 0.8-mm isotropic MRI,
T2-weighted 0.8-mm isotropic MRI,
T2*-weighted (EPI) 1.8-mm isotropic fMRI