7 papers
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: a 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…
A Differentiable Model for Optimizing the Genetic Drivers of Synaptogenesis
Tommaso Boccato, Matteo Ferrante, Nicola Toschi
There is growing consensus among neuroscientists that neural circuits critical for survival are the result of genomic decompression processes. We introduce SynaptoGen, a novel comp…
Transforming Multimodal Models into Action Models for Radiotherapy
Matteo Ferrante, Alessandra Carosi, Rolando Maria D Angelillo +1
Radiotherapy is a crucial cancer treatment that demands precise planning to balance tumor eradication and preservation of healthy tissue. Traditional treatment planning (TP) is ite…