Zobrazeno 1 - 10
of 832
pro vyhledávání: '"Toschi, Nicola"'
Music is a universal phenomenon that profoundly influences human experiences across cultures. This study investigates whether music can be decoded from human brain activity measured with functional MRI (fMRI) during its perception. Leveraging recent
Externí odkaz:
http://arxiv.org/abs/2406.15537
In this paper we introduce SynaptoGen, a novel framework that aims to bridge the gap between genetic manipulations and neuronal network behavior by simulating synaptogenesis and guiding the development of neuronal networks capable of solving predeter
Externí odkaz:
http://arxiv.org/abs/2402.07242
Decoding visual representations from human brain activity has emerged as a thriving research domain, particularly in the context of brain-computer interfaces. Our study presents an innovative method that employs to classify and reconstruct images fro
Externí odkaz:
http://arxiv.org/abs/2309.07149
Previous brain decoding research primarily involves single-subject studies, reconstructing stimuli via fMRI activity from the same subject. Our study aims to introduce a generalization technique for cross-subject brain decoding, facilitated by explor
Externí odkaz:
http://arxiv.org/abs/2309.00627
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 in functional magnetic resonance imaging (fMRI) have enabled scientists
Externí odkaz:
http://arxiv.org/abs/2305.11560
In this study, we explore the impact of network topology on the approximation capabilities of artificial neural networks (ANNs), with a particular focus on complex topologies. We propose a novel methodology for constructing complex ANNs based on vari
Externí odkaz:
http://arxiv.org/abs/2303.17925
Autor:
Dimitri, Giovanna Maria, Spasov, Simeon, Duggento, Andrea, Passamonti, Luca, Li`o, Pietro, Toschi, Nicola
Recently, it has become progressively more evident that classic diagnostic labels are unable to reliably describe the complexity and variability of several clinical phenotypes. This is particularly true for a broad range of neuropsychiatric illnesses
Externí odkaz:
http://arxiv.org/abs/2303.15963
Graphs are a natural representation of brain activity derived from functional magnetic imaging (fMRI) data. It is well known that clusters of anatomical brain regions, known as functional connectivity networks (FCNs), encode temporal relationships wh
Externí odkaz:
http://arxiv.org/abs/2301.11408
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 propose a novel approach to brain decoding that also relies on semantic
Externí odkaz:
http://arxiv.org/abs/2212.06726
Graph neural networks (GNNs) have demonstrated success in learning representations of brain graphs derived from functional magnetic resonance imaging (fMRI) data. However, existing GNN methods assume brain graphs are static over time and the graph ad
Externí odkaz:
http://arxiv.org/abs/2209.13513