[HTML][HTML] Using artificial neural networks to ask 'why'questions of minds and brains

N Kanwisher, M Khosla, K Dobs - Trends in Neurosciences, 2023 - cell.com
Neuroscientists have long characterized the properties and functions of the nervous system,
and are increasingly succeeding in answering how brains perform the tasks they do. But the …

Understanding human object vision: a picture is worth a thousand representations

S Bracci, HP Op de Beeck - Annual review of psychology, 2023 - annualreviews.org
Objects are the core meaningful elements in our visual environment. Classic theories of
object vision focus upon object recognition and are elegant and simple. Some of their …

Better models of human high-level visual cortex emerge from natural language supervision with a large and diverse dataset

AY Wang, K Kay, T Naselaris, MJ Tarr… - Nature Machine …, 2023 - nature.com
High-performing neural networks for vision have dramatically advanced our ability to
account for neural data in biological systems. Recently, further improvement in performance …

Color appearance and the end of Hering's Opponent-Colors Theory

BR Conway, S Malik-Moraleda, E Gibson - Trends in Cognitive Sciences, 2023 - cell.com
Abstract Hering's Opponent-Colors Theory has been central to understanding color
appearance for 150 years. It aims to explain the phenomenology of colors with two linked …

Selectivity for food in human ventral visual cortex

N Jain, A Wang, MM Henderson, R Lin… - Communications …, 2023 - nature.com
Visual cortex contains regions of selectivity for domains of ecological importance. Food is an
evolutionarily critical category whose visual heterogeneity may make the identification of …

Color-biased regions in the ventral visual pathway are food selective

IML Pennock, C Racey, EJ Allen, Y Wu, T Naselaris… - Current Biology, 2023 - cell.com
Color-biased regions have been found between face-and place-selective areas in the
ventral visual pathway. To investigate the function of the color-biased regions in a pathway …

The neural code for “face cells” is not face-specific

K Vinken, JS Prince, T Konkle, MS Livingstone - Science Advances, 2023 - science.org
Face cells are neurons that respond more to faces than to non-face objects. They are found
in clusters in the inferotemporal cortex, thought to process faces specifically, and, hence …

Incorporating natural language into vision models improves prediction and understanding of higher visual cortex

AY Wang, K Kay, T Naselaris, MJ Tarr, L Wehbe - BioRxiv, 2022 - biorxiv.org
We hypothesize that high-level visual representations contain more than the representation
of individual categories: they represent complex semantic information inherent in scenes …

Neural wave machines: learning spatiotemporally structured representations with locally coupled oscillatory recurrent neural networks

TA Keller, M Welling - International Conference on Machine …, 2023 - proceedings.mlr.press
Traveling waves have been measured at a diversity of regions and scales in the brain,
however a consensus as to their computational purpose has yet to be reached. An intriguing …

Spikiness and animacy as potential organizing principles of human ventral visual cortex

DD Coggan, F Tong - Cerebral Cortex, 2023 - academic.oup.com
Considerable research has been devoted to understanding the fundamental organizing
principles of the ventral visual pathway. A recent study revealed a series of 3–4 …