Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Unsupervised neural network models of the ventral visual stream
Chengxu Zhuang, Siming Yan, Aran Nayebi, et al.
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 3
Open Access | Times Cited: 259

Showing 1-25 of 259 citing articles:

The neuroconnectionist research programme
Adrien Doerig, Rowan P. Sommers, Katja Seeliger, et al.
Nature reviews. Neuroscience (2023) Vol. 24, Iss. 7, pp. 431-450
Open Access | Times Cited: 130
An ecologically motivated image dataset for deep learning yields better models of human vision
Johannes Mehrer, Courtney J. Spoerer, Emer C. Jones, et al.
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 8
Open Access | Times Cited: 110
Using artificial neural networks to ask ‘why’ questions of minds and brains
Nancy Kanwisher, Meenakshi Khosla, Katharina Dobs
Trends in Neurosciences (2023) Vol. 46, Iss. 3, pp. 240-254
Open Access | Times Cited: 108
Deep problems with neural network models of human vision
Jeffrey S. Bowers, Gaurav Malhotra, Marin Dujmović, et al.
Behavioral and Brain Sciences (2022) Vol. 46
Open Access | Times Cited: 106
Brain-like functional specialization emerges spontaneously in deep neural networks
Katharina Dobs, Julio Martinez, Alexander J.E. Kell, et al.
Science Advances (2022) Vol. 8, Iss. 11
Open Access | Times Cited: 96
A self-supervised domain-general learning framework for human ventral stream representation
Talia Konkle, George A. Alvarez
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 79
Brain-inspired learning in artificial neural networks: A review
Samuel Schmidgall, Rojin Ziaei, Jascha Achterberg, et al.
APL Machine Learning (2024) Vol. 2, Iss. 2
Open Access | Times Cited: 35
Task-driven neural network models predict neural dynamics of proprioception
Alessandro Marin Vargas, Axel Bisi, Alberto Silvio Chiappa, et al.
Cell (2024) Vol. 187, Iss. 7, pp. 1745-1761.e19
Open Access | Times Cited: 15
Qualitative similarities and differences in visual object representations between brains and deep networks
Georgin Jacob, R. T. Pramod, Harish Katti, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 102
SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective
Jessica Sullivan, Michelle Mei, Andrew Perfors, et al.
Open Mind (2021) Vol. 5, pp. 20-29
Open Access | Times Cited: 92
Computational models of category-selective brain regions enable high-throughput tests of selectivity
N. Apurva Ratan Murty, Pouya Bashivan, Alex Abate, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 82
A computational neuroethology perspective on body and expression perception
Béatrice de Gelder, Marta Poyo Solanas
Trends in Cognitive Sciences (2021) Vol. 25, Iss. 9, pp. 744-756
Open Access | Times Cited: 71
Feature-space selection with banded ridge regression
Tom Dupré la Tour, Michael Eickenberg, Anwar O. Núñez-Elizalde, et al.
NeuroImage (2022) Vol. 264, pp. 119728-119728
Open Access | Times Cited: 53
Multiple cortical visual streams in humans
Edmund T. Rolls, Gustavo Deco, Chu‐Chung Huang, et al.
Cerebral Cortex (2022) Vol. 33, Iss. 7, pp. 3319-3349
Closed Access | Times Cited: 42
Texture-like representation of objects in human visual cortex
Akshay Jagadeesh, Justin L. Gardner
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 17
Open Access | Times Cited: 41
The Dorsal Visual Pathway Represents Object-Centered Spatial Relations for Object Recognition
Vladislav Ayzenberg, Marlene Behrmann
Journal of Neuroscience (2022) Vol. 42, Iss. 23, pp. 4693-4710
Open Access | Times Cited: 41
Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signals
Timo Flesch, Dávid Nagy, Andrew Saxe, et al.
PLoS Computational Biology (2023) Vol. 19, Iss. 1, pp. e1010808-e1010808
Open Access | Times Cited: 37
Drawing as a versatile cognitive tool
Judith E. Fan, Wilma Bainbridge, Rebecca Chamberlain, et al.
Nature Reviews Psychology (2023) Vol. 2, Iss. 9, pp. 556-568
Open Access | Times Cited: 35
Dissecting neural computations in the human auditory pathway using deep neural networks for speech
Yuanning Li, Gopala K. Anumanchipalli, Abdelrahman Mohamed, et al.
Nature Neuroscience (2023) Vol. 26, Iss. 12, pp. 2213-2225
Open Access | Times Cited: 32
Brain-optimized deep neural network models of human visual areas learn non-hierarchical representations
Ghislain St-Yves, Emily J. Allen, Yihan Wu, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 30
Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions
Greta Tuckute, Jenelle Feather, Dana Boebinger, et al.
PLoS Biology (2023) Vol. 21, Iss. 12, pp. e3002366-e3002366
Open Access | Times Cited: 25
The developmental trajectory of object recognition robustness: Children are like small adults but unlike big deep neural networks
Lukas S. Huber, Robert Geirhos, Felix A. Wichmann
Journal of Vision (2023) Vol. 23, Iss. 7, pp. 4-4
Open Access | Times Cited: 24
Deep Neural Networks and Visuo-Semantic Models Explain Complementary Components of Human Ventral-Stream Representational Dynamics
Kamila M. Jozwik, Tim C. Kietzmann, Radoslaw M. Cichy, et al.
Journal of Neuroscience (2023) Vol. 43, Iss. 10, pp. 1731-1741
Open Access | Times Cited: 23
Modeling naturalistic face processing in humans with deep convolutional neural networks
Guo Jiahui, Ma Feilong, Matteo Visconti di Oleggio Castello, et al.
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 43
Open Access | Times Cited: 22
High-performing neural network models of visual cortex benefit from high latent dimensionality
Eric Elmoznino, Michael Bonner
PLoS Computational Biology (2024) Vol. 20, Iss. 1, pp. e1011792-e1011792
Open Access | Times Cited: 14
Page 1 - Next Page

Scroll to top