8 papers
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.…
Decoding the decoder: Contextual sequence-to-sequence modeling for intracortical speech decoding
Michal Olak, Tommaso Boccato, Matteo Ferrante
Speech brain--computer interfaces require decoders that translate intracortical activity into linguistic output while remaining robust to limited data and day-to-day variability. W…
BrainWhisperer: Leveraging Large-Scale ASR Models for Neural Speech Decoding
Tommaso Boccato, Michal Olak, Matteo Ferrante
Decoding continuous speech from intracortical recordings is a central challenge for brain-computer interfaces (BCIs), with transformative potential for individuals with conditions…
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…
Training Neural Networks by Optimizing Neuron Positions
Laura Erb, Tommaso Boccato, Alexandru Vasilache +2
The high computational complexity and increasing parameter counts of deep neural networks pose significant challenges for deployment in resource-constrained environments, such as e…