no code implementations • 27 May 2024 • Cory Efird, Alex Murphy, Joel Zylberberg, Alona Fyshe
Thus, our contrastive-learning methodology better characterizes new and existing visuo-semantic representations in the brain by leveraging multimodal neural network representations and a novel adaptation of clustering algorithms.
1 code implementation • 2 May 2024 • Alex Murphy, Joel Zylberberg, Alona Fyshe
Using fMRI and MEG data from the THINGS project, we show that if biased CKA is applied to representations of different sizes in the low-data high-dimensionality domain, they are not directly comparable due to biased CKA's sensitivity to differing feature-sample ratios and not stimuli-driven responses.
no code implementations • 7 Jan 2024 • Greta Tuckute, Dawn Finzi, Eshed Margalit, Joel Zylberberg, SueYeon Chung, Alona Fyshe, Evelina Fedorenko, Nikolaus Kriegeskorte, Jacob Yates, Kalanit Grill Spector, Kohitij Kar
In recent years, neuroscience has made significant progress in building large-scale artificial neural network (ANN) models of brain activity and behavior.
no code implementations • 6 Jun 2023 • Cory Efird, Alex Murphy, Joel Zylberberg, Alona Fyshe
In the final section of our analysis, we localize shared decodable concepts in the brain using a voxel-masking optimization method to produce a shared decodable concept (SDC) space.
no code implementations • 6 Sep 2022 • Cassidy Pirlot, Richard C. Gerum, Cory Efird, Joel Zylberberg, Alona Fyshe
As convolutional neural networks (CNNs) become more accurate at object recognition, their representations become more similar to the primate visual system.
1 code implementation • 22 Aug 2022 • Richard C. Gerum, Cassidy Pirlot, Alona Fyshe, Joel Zylberberg
For convolutional networks, the best $\alpha$ values depend on the task complexity and evaluation metric: lower $\alpha$ values optimized validation accuracy and robustness to adversarial attack for networks performing a simple object recognition task (categorizing MNIST images of handwritten digits); for a more complex task (categorizing CIFAR-10 natural images), we found that lower $\alpha$ values optimized validation accuracy whereas higher $\alpha$ values optimized adversarial robustness.
1 code implementation • 25 May 2019 • Callie Federer, Haoyan Xu, Alona Fyshe, Joel Zylberberg
To test this, we trained DCNNs on a composite task, wherein networks were trained to: a) classify images of objects; while b) having intermediate representations that resemble those observed in neural recordings from monkey visual cortex.
no code implementations • ICLR 2018 • Callie Federer, Joel Zylberberg
Information in working memory, however, is retained for tens of seconds, suggesting the question of how time-varying neural activities maintain stable representations.
1 code implementation • 19 Jun 2017 • William F. Kindel, Elijah D. Christensen, Joel Zylberberg
Moreover, even for the simple and complex cells-- the best-understood V1 neurons-- it is challenging to predict how they will respond to natural image stimuli.
1 code implementation • 23 Sep 2008 • Gong-Bo Zhao, Levon Pogosian, Alessandra Silvestri, Joel Zylberberg
In alternative theories of gravity, designed to produce cosmic acceleration at the current epoch, the growth of large scale structure can be modified.