In order to better understand how the brain perceives faces, it is important to know what objective drives learning in the ventral visual stream. To answer this question, we model neural responses to faces in the macaque inferotemporal (IT) cortex wi...
To interact with real-world objects, any effective visual system must jointly code the unique features defining each object. Despite decades of neuroscience research, we still lack a firm grasp on how the primate brain binds visual features. Here we ...
Numerous theories propose a key role for brain oscillations in visual perception. Most of these theories postulate that sensory information is encoded in specific oscillatory components (e.g., power or phase) of specific frequency bands. These theori...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Mar 31, 2021
A visual object is characterized by multiple visual features, including its identity, position and size. Despite the usefulness of identity and nonidentity features in vision and their joint coding throughout the primate ventral visual processing pat...
Deep neural networks have revolutionized computer vision, and their object representations across layers match coarsely with visual cortical areas in the brain. However, whether these representations exhibit qualitative patterns seen in human percept...
Cortex; a journal devoted to the study of the nervous system and behavior
Feb 5, 2021
Our ability to recognize an object amongst many exemplars is one of our most important features, and one that putatively distinguishes humans from non-human animals and potentially from (current) computational and artificial intelligence models. We c...
Human categorization is one of the most important and successful targets of cognitive modeling, with decades of model development and assessment using simple, low-dimensional artificial stimuli. However, it remains unclear how these findings relate t...
Neural networks : the official journal of the International Neural Network Society
Sep 28, 2020
Human perception of an object's skeletal structure is particularly robust to diverse perturbations of shape. This skeleton representation possesses substantial advantages for parts-based and invariant shape encoding, which is essential for object rec...
Memories are not stored as static engrams, but as dynamic representations affected by processes occurring after initial encoding. Previous studies revealed changes in activity and mnemonic representations in visual processing areas, parietal lobe, an...
Neural networks : the official journal of the International Neural Network Society
Jul 29, 2020
The current state-of-the-art object recognition algorithms, deep convolutional neural networks (DCNNs), are inspired by the architecture of the mammalian visual system, and are capable of human-level performance on many tasks. As they are trained for...
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