activity
20222026
most citedBrain Captioning: Decoding human brain activity into images and text

13 citations · 22 across the 20 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.NI2026

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…

q-bio.NC2026

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…

q-bio.NC2026

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…

q-bio.NC2026

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.…

q-bio.NC2026

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…