40 citations · 62 across the 5 of their papers we have counts for
5 papers
Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priors
Paul S. Scotti, Atmadeep Banerjee, Jimmie Goode +9
We present MindEye, a novel fMRI-to-image approach to retrieve and reconstruct viewed images from brain activity. Our model comprises two parallel submodules that are specialized f…
Large language models can segment narrative events similarly to humans
Sebastian Michelmann, Manoj Kumar, Kenneth A. Norman +1
Humans perceive discrete events such as "restaurant visits" and "train rides" in their continuous experience. One important prerequisite for studying human event perception is the…
Shared Representational Geometry Across Neural Networks
Qihong Lu, Po-Hsuan Chen, Jonathan W. Pillow +3
Different neural networks trained on the same dataset often learn similar input-output mappings with very different weights. Is there some correspondence between these neural netwo…
Leabra7: a Python package for modeling recurrent, biologically-realistic neural networks
C. Daniel Greenidge, Noam Miller, Kenneth A. Norman
Emergent is a software package that uses the AdEx neural dynamics model and LEABRA learning algorithm to simulate and train arbitrary recurrent neural network architectures in a bi…
Mapping Between fMRI Responses to Movies and their Natural Language Annotations
Kiran Vodrahalli, Po-Hsuan Chen, Yingyu Liang +8
Several research groups have shown how to correlate fMRI responses to the meanings of presented stimuli. This paper presents new methods for doing so when only a natural language a…