13 citations · 22 across the 20 of their papers we have counts for
5 papers · 1 filter
Towards Neural Foundation Models for Vision: Aligning EEG, MEG, and fMRI Representations for Decoding, Encoding, and Modality Conversion
Matteo Ferrante, Tommaso Boccato, Grigorii Rashkov +1
This paper presents a novel approach towards creating a foundational model for aligning neural data and visual stimuli across multimodal representationsof brain activity by leverag…
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…
Semantic Brain Decoding: from fMRI to conceptually similar image reconstruction of visual stimuli
Matteo Ferrante, Tommaso Boccato, Nicola Toschi
Brain decoding is a field of computational neuroscience that uses measurable brain activity to infer mental states or internal representations of perceptual inputs. Therefore, we p…
VAESim: A probabilistic approach for self-supervised prototype discovery
Matteo Ferrante, Tommaso Boccato, Simeon Spasov +2
In medicine, curated image datasets often employ discrete labels to describe what is known to be a continuous spectrum of healthy to pathological conditions, such as e.g. the Alzhe…
Contrastive learning for unsupervised medical image clustering and reconstruction
Matteo Ferrante, Tommaso Boccato, Simeon Spasov +2
The lack of large labeled medical imaging datasets, along with significant inter-individual variability compared to clinically established disease classes, poses significant challe…