4 papers
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…
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…
Bridging Auditory Perception and Language Comprehension through MEG-Driven Encoding Models
Matteo Ciferri, Matteo Ferrante, Nicola Toschi
Understanding the neural mechanisms behind auditory and linguistic processing is key to advancing cognitive neuroscience. In this study, we use Magnetoencephalography (MEG) data to…
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…