7 papers
AI-guided stimuli discovery and generation to optimize facial emotion perception studies in autism
Kushin Mukherjee, Na Yeon Kim, Maren Wehrheim +2
Understanding perceptual differences between autistic and neurotypical adults requires behavioral assays that are sensitive, reliable, and mechanistically informative. Facial emoti…
The macaque IT cortex but not current artificial vision networks encode object position in perceptually aligned coordinates
Elizaveta Yakubovskaya, Hamidreza Ramezanpour, Matteo Dunnhofer +1
Efficient interaction with the visual world requires not only accurate object identification but also precise localization of objects in space. While spatial ("where") processing h…
Modeling Dynamic Computations in the Primate Ventral Visual Stream
Matteo Dunnhofer, Maren Wehrheim, Hamidreza Ramezanpour +2
A major goal of computational neuroscience has been to explain how the primate ventral visual stream (VVS) transforms visual input into temporally evolving neural representations t…
Better, But Not Sufficient: Testing Video ANNs Against Macaque IT Dynamics
Matteo Dunnhofer, Christian Micheloni, Kohitij Kar
Feedforward artificial neural networks (ANNs) trained on static images remain the dominant models of the the primate ventral visual stream, yet they are intrinsically limited to st…
MAPS: Masked Attribution-based Probing of Strategies- A computational framework to align human and model explanations
Sabine Muzellec, Yousif Kashef Alghetaa, Simon Kornblith +1
Human core object recognition depends on the selective use of visual information, but the strategies guiding these choices are difficult to measure directly. We present MAPS (Maske…
How to optimize neuroscience data utilization and experiment design for advancing brain models of visual and linguistic cognition?
Greta Tuckute, Dawn Finzi, Eshed Margalit +8
In recent years, neuroscience has made significant progress in building large-scale artificial neural network (ANN) models of brain activity and behavior. However, there is no cons…