A5042087263- EEG and Brain-Computer Interfaces
- Neural Networks and Applications
- Neural dynamics and brain function
- Chaos control and synchronization
- Blind Source Separation Techniques
- Functional Brain Connectivity Studies
- Data Visualization and Analytics
- Neural Networks Stability and Synchronization
- COVID-19 epidemiological studies
- Action Observation and Synchronization
- Motor Control and Adaptation
- Cellular Automata and Applications
- Coastal and Marine Management
- Land Use and Ecosystem Services
- Nonlinear Dynamics and Pattern Formation
- Advanced Neuroimaging Techniques and Applications
- Mindfulness and Compassion Interventions
- Sustainability and Ecological Systems Analysis
- Usability and User Interface Design
- Music Therapy and Health
- Child Therapy and Development
- Transcranial Magnetic Stimulation Studies
- Muscle activation and electromyography studies
- Multisensory perception and integration
- Evolutionary Algorithms and Applications
Sony (France)
2020
Sapienza University of Rome
1996-2014
Assessing the effectiveness of non-pharmaceutical interventions (NPIs) to mitigate spread SARS-CoV-2 is critical inform future preparedness response plans. Here we quantify impact 6,068 hierarchically coded NPIs implemented in 79 territories on effective reproduction number, Rt, COVID-19. We propose a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools. validate our findings with two external datasets recording...
Non-pharmaceutical interventions (NPIs) to mitigate the spread of SARS-CoV-2 were often implemented under considerable uncertainty and a lack scientific evidence. Assessing effectiveness individual is critical inform future preparedness response plans. Here we quantify impact 4,579 NPIs in 76 territories on effective reproduction number, R t , COVID-19. We use hierarchically coded data set propose novel modelling approach that combines four computational techniques, which together allow for...
Abstract The act of listening to speech activates a large network brain areas. In the present work, novel data‐driven technique (the combination independent component analysis and Granger causality) was used extract dynamics from an fMRI study passive Words, Pseudo‐Words, Reverse‐played words. Using this method we show functional connectivity modulations among classical language regions (Broca's Wernicke's areas) inferior parietal, somatosensory, motor areas right cerebellum. Word elicited...
We present a new technique for controlling the behaviour of large system composed chaotic units by using only few control referred to as pinnings. Our model can be regarded an extension cellular neural networks cells, in this paper described Lorenz equations, locally coupled identical connections. The network is moderate size, 27 × 27. By tuning connection strength D, variety global behaviours obtained: from fully turbulent coherent spatiotemporal states. In between exhibits unstable partial...
This work presents the results of simulation fully connected networks Chua's circuits mutually coupled by nonlinear conductances derived using Hebbian learning rule. The network can be regarded as a generalization Hopfield neural built up chaotic units. Due to space-time synchronization units, studied exhibits ability pattern retrieval and decorrelation complex input patterns.
Complex pattern formation in two-dimensional cellular network of chaotic oscillators is presented the paper. The patterns are related to unstable periodic orbits dynamics and may be formed synchronization process obtained by means chaos suppression. This effect can considered as transition from turbulent phase partially synchronized network.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Incorporating novelties into deep learning systems remains a challenging problem. Introducing new information to machine system can interfere with previously stored data and potentially alter the global model paradigm, especially when dealing non-stationary sources. In such cases, traditional approaches based on validation error minimization offer limited advantages. To address this, we propose training algorithm inspired by Stuart Kauffman's notion of Adjacent Possible. This novel...
Artificial agents modeled by evolutionary neural networks have been diffusely described in the specific case of static architectures and synaptic weights coded genetic strings. At present, more attractive theories devoted to a general theory mind consider biological structural levels as necessary elements for an appropriate natural information processing. In this paper, approach has taken into account selection embedded artificial environment. Several correspondences between behavior...
A set of different algorithms was involved to analyze the anomalous motor control in four young hemi-paretic patients with pre-and perinatally acquired brain lesions. The effects a peculiar cerebral reorganization allow move paretic arm. Patients performed pinch grip using their and non-paretic hands alternatively. EMG simultaneously recorded as basis for coherence calculations. 3D mapping beta frequency range. Such approach evidenced relocation functions from lesioned (left) contralesional...