Sharing neurophysiology data from the Allen Brain Observatory
Nullius in verba ('trust no one'), chosen as the motto of the Royal Society in 1660, implies
that independently verifiable observations—rather than authoritative claims—are a defining …
that independently verifiable observations—rather than authoritative claims—are a defining …
Hierarchical temporal prediction captures motion processing along the visual pathway
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) …
eyes to the cortex. Retinal neurons prefer flashing spots of light, primary visual cortical (V1) …
What can 1.8 billion regressions tell us about the pressures shaping high-level visual representation in brains and machines?
The rapid development and open-source release of highly performant computer vision
models offers new potential for examining how different inductive biases impact …
models offers new potential for examining how different inductive biases impact …
Addressing the speed-accuracy simulation trade-off for adaptive spiking neurons
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 …
neuroscience and has been instrumental in studying our brains $\textit {in silico} $. Due to …
Exploring the brain-like properties of deep neural networks: A neural encoding perspective
Nowadays, deep neural networks (DNNs) have been equipped with powerful representation
capabilities. The deep convolutional neural networks (CNNs) that draw inspiration from the …
capabilities. The deep convolutional neural networks (CNNs) that draw inspiration from the …
Deep spiking neural networks with high representation similarity model visual pathways of macaque and mouse
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 …
primate and rodent. However, they highly simplify the computational properties of neurons …
System identification of neural systems: If we got it right, would we know?
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 …
are compared to recordings of biological neurons, and good performance in reproducing …
[PDF][PDF] Large-scale benchmarking of diverse artificial vision models in prediction of 7T human neuroimaging data
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 …
unparalleled opportunity to (re) assess the current state of artificial models of the human …
If you've trained one you've trained them all: inter-architecture similarity increases with robustness
Previous work has shown that commonly-used metrics for comparing representations
between neural networks overestimate similarity due to correlations between data points …
between neural networks overestimate similarity due to correlations between data points …
What can 5.17 billion regression fits tell us about artificial models of the human visual system?
Rapid simultaneous advances in machine vision and cognitive neuroimaging present an
unparalleled opportunity to assess the current state of artificial models of the human visual …
unparalleled opportunity to assess the current state of artificial models of the human visual …