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Alessandro Gifford@alessandrogifford.bsky.social · last yr.

Vision Deep Neural Networks and Large Language Models complement each other in predicting EEG responses to images, providing a more accurate model of the time course of visuo-semantic processing in the human brain. #NeuroAI #CompNeuro #neuroscience #AI arxiv.org/abs/2506.19497

The time course of visuo-semantic representations in the human brain is captured by combining vision and language models

The human visual system provides us with a rich and meaningful percept of the world, transforming retinal signals into visuo-semantic representations. For a model of these representations, here we lev...

arxiv.org

Nature Human Behaviour@nathumbehav.nature.com · last yr.

Using in silico neuroscience, @alessandrogifford.bsky.social et al. developed a neural control algorithm to modulate the representational relationships between visual cortical areas, revealing how these areas jointly represent the world as an interconnected network. www.nature.com/articles/s41...

In silico discovery of representational relationships across visual cortex - Nature Human Behaviour

Using in silico neuroscience, Gifford et al. developed a neural control algorithm to modulate the representational relationships between visual cortical areas, revealing how these areas jointly repres...

nature.com

Alessandro Gifford@alessandrogifford.bsky.social · 2y ago

(6/7) Out-of-distribution generalization tests on NSD-synthetic reveal differences between brain models that are not detected by in-distribution tests => self-supervised deep neural networks better explain neural responses than their task-supervised counterparts.

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@ccnberlin.bsky.social · last yr.

The Control seminar series begins 05.05 at Freie Universität with Sören Krach und David Stolz - Universität zu Lübeck Title of Talk: Elements of Control in Human Affective Neuroscience Hope to see you there!

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Alessandro Gifford@alessandrogifford.bsky.social · 2y ago

(1/7) NSD-synthetic is out! NSD-synthetic enables strict out-of-distribution generalization tests critical for the development of more robust models of visual processing and the formulation of more accurate theories of human vision. #NeuroAI #CompNeuro #neuroscience #AI doi.org/10.48550/arX...

A 7T fMRI dataset of synthetic images for out-of-distribution modeling of vision

Large-scale visual neural datasets such as the Natural Scenes Dataset (NSD) are boosting NeuroAI research by enabling computational models of the brain with performances beyond what was possible just ...

doi.org

Rasmus Bruckner@rasmusbruckner.bsky.social · 2y ago

In our new @commspsychol.bsky.social review, we explore how humans adjust learning to different types of uncertainty, why biases arise, and what this reveals about learning and psychiatric conditions. 📖 Read more: nature.com/articles/s44... With Matt Nassar & @haukeren.bsky.social

Understanding learning through uncertainty and bias - Communications Psychology

Flexible learning requires humans to adjust their behaviour to uncertainty. While normative learning models explain many adaptive behaviours, systematic biases-arising from inaccurate assumptions or c...

nature.com