The neuroconnectionist research programme
A Doerig, RP Sommers, K Seeliger… - Nature Reviews …, 2023 - nature.com
Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …
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 …
object vision focus upon object recognition and are elegant and simple. Some of their …
Getting aligned on representational alignment
I Sucholutsky, L Muttenthaler, A Weller, A Peng… - ar** 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 …
A large-scale examination of inductive biases sha** high-level visual representation in brains and machines
The rapid release of high-performing computer vision models offers new potential to study
the impact of different inductive biases on the emergent brain alignment of learned …
the impact of different inductive biases on the emergent brain alignment of learned …
High-performing neural network models of visual cortex benefit from high latent dimensionality
E Elmoznino, MF Bonner - PLoS computational biology, 2024 - journals.plos.org
Geometric descriptions of deep neural networks (DNNs) have the potential to uncover core
representational principles of computational models in neuroscience. Here we examined the …
representational principles of computational models in neuroscience. Here we examined the …
Degrees of algorithmic equivalence between the brain and its DNN models
Deep neural networks (DNNs) have become powerful and increasingly ubiquitous tools to
model human cognition, and often produce similar behaviors. For example, with their …
model human cognition, and often produce similar behaviors. For example, with their …
[HTML][HTML] Neurobiological mechanisms for language, symbols and concepts: clues from brain-constrained deep neural networks
F Pulvermüller - Progress in Neurobiology, 2023 - Elsevier
Neural networks are successfully used to imitate and model cognitive processes. However,
to provide clues about the neurobiological mechanisms enabling human cognition, these …
to provide clues about the neurobiological mechanisms enabling human cognition, these …
[HTML][HTML] Skeletal representations of shape in the human visual cortex
Shape perception is crucial for object recognition. However, it remains unknown exactly how
shape information is represented and used by the visual system. Here, we tested the …
shape information is represented and used by the visual system. Here, we tested the …
Diverse task-driven modeling of macaque V4 reveals functional specialization towards semantic tasks
Responses to natural stimuli in area V4—a mid-level area of the visual ventral stream—are
well predicted by features from convolutional neural networks (CNNs) trained on image …
well predicted by features from convolutional neural networks (CNNs) trained on image …