25 citations · 78 across the 14 of their papers we have counts for
14 papers
An Attention Mechanism for Robust Multimodal Integration in a Global Workspace Architecture
Roland Bertin-Johannet, Lara Scipio, Leopold Maytié +1
Robust multimodal systems must remain effective when some modalities are noisy, degraded, or unreliable. Existing multimodal fusion methods often learn modality selection jointly w…
Wave propagation phenomena in nonlinear hierarchical neural networks with predictive coding feedback dynamics
Andrea Alamia, Léa Dalliès, Grégory Faye +1
We propose a mathematical framework to systematically explore the propagation properties of a class of continuous in time nonlinear neural network models comprising a hierarchy of…
Modality-Agnostic fMRI Decoding of Vision and Language
Mitja Nikolaus, Milad Mozafari, Nicholas Asher +2
Previous studies have shown that it is possible to map brain activation data of subjects viewing images onto the feature representation space of not only vision models (modality-sp…
Leveraging Self-Supervised Instance Contrastive Learning for Radar Object Detection
Colin Decourt, Rufin VanRullen, Didier Salle +1
In recent years, driven by the need for safer and more autonomous transport systems, the automotive industry has shifted toward integrating a growing number of Advanced Driver Assi…
Through their eyes: multi-subject Brain Decoding with simple alignment techniques
Matteo Ferrante, Tommaso Boccato, Nicola Toschi
Previous brain decoding research primarily involves single-subject studies, reconstructing stimuli via fMRI activity from the same subject. Our study aims to introduce a generaliza…
Brain Captioning: Decoding human brain activity into images and text
Matteo Ferrante, Furkan Ozcelik, Tommaso Boccato +2
Every day, the human brain processes an immense volume of visual information, relying on intricate neural mechanisms to perceive and interpret these stimuli. Recent breakthroughs i…
Mathematical derivation of wave propagation properties in hierarchical neural networks with predictive coding feedback dynamics
Grégory Faye, Guilhem Fouilhé, Rufin VanRullen
Sensory perception (e.g. vision) relies on a hierarchy of cortical areas, in which neural activity propagates in both directions, to convey information not only about sensory input…
Natural scene reconstruction from fMRI signals using generative latent diffusion
Furkan Ozcelik, Rufin VanRullen
In neural decoding research, one of the most intriguing topics is the reconstruction of perceived natural images based on fMRI signals. Previous studies have succeeded in re-creati…
Learning Functional Transduction
Mathieu Chalvidal, Thomas Serre, Rufin VanRullen
Research in machine learning has polarized into two general approaches for regression tasks: Transductive methods construct estimates directly from available data but are usually p…
A recurrent CNN for online object detection on raw radar frames
Colin Decourt, Rufin VanRullen, Didier Salle +1
Automotive radar sensors provide valuable information for advanced driving assistance systems (ADAS). Radars can reliably estimate the distance to an object and the relative veloci…
Reconstruction of Perceived Images from fMRI Patterns and Semantic Brain Exploration using Instance-Conditioned GANs
Furkan Ozcelik, Bhavin Choksi, Milad Mozafari +2
Reconstructing perceived natural images from fMRI signals is one of the most engaging topics of neural decoding research. Prior studies had success in reconstructing either the low…
Meta-Reinforcement Learning with Self-Modifying Networks
Mathieu Chalvidal, Thomas Serre, Rufin VanRullen
Deep Reinforcement Learning has demonstrated the potential of neural networks tuned with gradient descent for solving complex tasks in well-delimited environments. However, these n…
Multimodal neural networks better explain multivoxel patterns in the hippocampus
Bhavin Choksi, Milad Mozafari, Rufin VanRullen +1
The human hippocampus possesses "concept cells", neurons that fire when presented with stimuli belonging to a specific concept, regardless of the modality. Recently, similar concep…
Deep Learning and the Global Workspace Theory
Rufin VanRullen, Ryota Kanai
Recent advances in deep learning have allowed Artificial Intelligence (AI) to reach near human-level performance in many sensory, perceptual, linguistic or cognitive tasks. There i…