6 papers · 1 filter
PCDT: A Predictive Cognitive Digital Twin Framework for Intelligent and Autonomous 6G Network Ecosystems
John Sengendo, Andreas Kassler, Fabrizio Granelli
Future 6G networks are expected to operate as intelligent and autonomous ecosystems where monitoring, prediction, and control are integrated into continuous self-optimization loops…
Hierarchical Pooling for Sheaf Neural Networks
Dionisia Naddeo, Carlo Abate, Pietro Liò +2
Sheaf Neural Networks (SNNs) generalize Graph Neural Networks (GNNs) by replacing scalar node signals with stalk-valued signals and by using restriction maps to measure compatibili…
Retrieval-Based Brain Decoding by Alignment, not Complexity
Matteo Ciferri, Matteo Ferrante, Nicola Toschi
A prominent theory in cognitive science suggests that concepts in the brain are organized as high-dimensional vectors, with semantic meaning captured by directions and relative ang…
Mapping Whisper Representations to Human ECoG Responses with Interpretable Time-Resolved Neural Encoding
Matteo Ciferri, Tommaso Boccato, Michal Olak +2
Understanding how speech foundation models relate to human cortical activity is a key challenge for computational neuroscience. Here, we investigate how internal representations fr…
Seeing the imagined: latent functional alignment in visual imagery decoding from fMRI data
Fabrizio Spera, Tommaso Boccato, Michal Olak +5
Recent progress in visual brain decoding from fMRI has been enabled by large-scale datasets such as the Natural Scenes Dataset (NSD) and powerful diffusion-based generative models.…
Simple Models, Rich Representations: Visual Decoding from Primate Intracortical Neural Signals
Matteo Ciferri, Matteo Ferrante, Nicola Toschi
Understanding how neural activity gives rise to perception is a central challenge in neuroscience. We address the problem of decoding visual information from high-density intracort…