Visual neurons respond selectively to features that become increasingly complex from the eyes to the cortex. Retinal neurons prefer flashing spots of light, primary visual cortical (V1) …
The rapid development and open-source release of highly performant computer vision models offers new potential for examining how different inductive biases impact …
L Taylor, A King, NS Harper - Advances in Neural …, 2024 - proceedings.neurips.cc
The adaptive leaky integrate-and-fire (ALIF) model is fundamental within computational neuroscience and has been instrumental in studying our brains $\textit {in silico} $. Due to …
Q Zhou, C Du, H He - Machine Intelligence Research, 2022 - Springer
Nowadays, deep neural networks (DNNs) have been equipped with powerful representation capabilities. The deep convolutional neural networks (CNNs) that draw inspiration from the …
L Huang, Z Ma, L Yu, H Zhou, Y Tian - Proceedings of the AAAI …, 2023 - ojs.aaai.org
Deep artificial neural networks (ANNs) play a major role in modeling the visual pathways of primate and rodent. However, they highly simplify the computational properties of neurons …
Studies of the mouse visual system have revealed a variety of visual brain areas that are thought to support a multitude of behavioral capacities, ranging from stimulus-reward …
Y Han, TA Poggio, B Cheung - International Conference on …, 2023 - proceedings.mlr.press
Artificial neural networks are being proposed as models of parts of the brain. The networks are compared to recordings of biological neurons, and good performance in reproducing …
Rapid simultaneous advances in machine vision and cognitive neuroimaging present an unparalleled opportunity to (re) assess the current state of artificial models of the human …
Previous work has shown that commonly-used metrics for comparing representations between neural networks overestimate similarity due to correlations between data points …