Article

Shared Hierarchical Representations Explain Temporal Correspondence Between Brain Activity and Deep Neural Networks

2025-05-21

Abstract excerpt

The visual cortex and artificial neural networks both process images hierarchically, progressing from low-level features to high-level semantic representations. We investigated the temporal correspondence between activations from multiple convolutional and transformer-based neural network models (AlexNet, MoCo, ResNet-50, VGG-19, and ViT) and human EEG responses recorded during visual perception tasks. Leveraging...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 8dda334c-d72a-5c55-89c1-1ead0e4c338a
DOI: 10.1101/2025.05.19.655003

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Shared Hierarchical Representations Explain Temporal Correspondence Between Brain Activity and Deep Neural NetworksDOI 10.1101/2025.05.19.655003Read

The Human Brain encodes a Chronicle of Visual Events at each Instant of TimeSemantic proximity Read

A large and rich EEG dataset for modeling human visual object recognitionSemantic proximity Read

Cortical response to naturalistic stimuli is largely predictable with deep neural networksSemantic proximity Read

Deep neural networks and visuo-semantic models explain complementary components of human ventral-stream representational dynamicsSemantic proximity Read

The representational dynamics of visual objects in rapid serial visual processing streamsSemantic proximity Read

Comprehensive Neural Representations of Naturalistic Stimuli through Multimodal Deep LearningSemantic proximity Read

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene CategorizationSemantic proximity Read

Temporal Dynamics of EEG Decoding for Continuously Changing Visual StimuliSemantic proximity Read

Encoding neural representations of time-continuous stimulus-response transformations in the human brain with advanced deep neural networksSemantic proximity Read

Recent advances in understanding object recognition in the human brain: deep neural networks, temporal dynamics, and contextSemantic proximity Read

Predicting brain activity using TransformersSemantic proximity Read

Evidence for a deep, distributed and dynamic semantic code in human ventral anterior temporal cortexSemantic proximity Read