46 citations · 226 across the 18 of their papers we have counts for
15 papers · 1 filter
Optimal stimulation sites are not the most affected: personalised models of resting-state fMRI in Alzheimer's disease
Cristiano Capone, Enza Cece, Andrea Ciardiello +3
Resting-state functional connectivity (FC) is altered in Alzheimer's disease (AD), widely regarded as a distributed network process; whether its signature reduces to a few focal si…
Multiscale dynamical characterization of cortical brain states: from synchrony to asynchrony
Maria V. Sanchez-Vives, Arnau Manasanch, Andrea Pigorini +17
The cerebral cortex spontaneously displays different patterns of activity that evolve over time according to the brain state. Sleep, wakefulness, resting states, and attention are…
Beyond spiking networks: the computational advantages of dendritic amplification and input segregation
Cristiano Capone, Cosimo Lupo, Paolo Muratore +1
The brain can efficiently learn a wide range of tasks, motivating the search for biologically inspired learning rules for improving current artificial intelligence technology. Most…
Comparing apples to apples -- Using a modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets
Robin Gutzen, Giulia De Bonis, Chiara De Luca +11
Neuroscience is moving towards a more integrative discipline, where understanding brain function requires consolidating the accumulated evidence seen across experiments, species, a…
NREM and REM: cognitive and energetic gains in thalamo-cortical sleeping and awake spiking model
Chiara De Luca, Leonardo Tonielli, Elena Pastorelli +8
Sleep is essential for learning and cognition, but the mechanisms by which it stabilizes learning, supports creativity, and manages the energy consumption of networks engaged in po…
Burst-dependent plasticity and dendritic amplification support target-based learning and hierarchical imitation learning
Cristiano Capone, Cosimo Lupo, Paolo Muratore +1
The brain can learn to solve a wide range of tasks with high temporal and energetic efficiency. However, most biological models are composed of simple single compartment neurons an…
Error-based or target-based? A unifying framework for learning in recurrent spiking networks
Cristiano Capone, Paolo Muratore, Pier Stanislao Paolucci
Learning in biological or artificial networks means changing the laws governing the network dynamics in order to better behave in a specific situation. In the field of supervised l…
Simulations Approaching Data: Cortical Slow Waves in Inferred Models of the Whole Hemisphere of Mouse
Cristiano Capone, Chiara De Luca, Giulia De Bonis +11
Thanks to novel, powerful brain activity recording techniques, we can create data-driven models from thousands of recording channels and large portions of the cortex, which can imp…
Thalamo-cortical spiking model of incremental learning combining perception, context and NREM-sleep-mediated noise-resilience
Bruno Golosio, Chiara De Luca, Cristiano Capone +5
The brain exhibits capabilities of fast incremental learning from few noisy examples, as well as the ability to associate similar memories in autonomously-created categories and to…
Target spiking patterns enable efficient and biologically plausible learning for complex temporal tasks
Paolo Muratore, Cristiano Capone, Pier Stanislao Paolucci
Recurrent spiking neural networks (RSNN) in the human brain learn to perform a wide range of perceptual, cognitive and motor tasks very efficiently in terms of energy consumption a…
Sleep-like slow oscillations improve visual classification through synaptic homeostasis and memory association in a thalamo-cortical model
Cristiano Capone, Elena Pastorelli, Bruno Golosio +1
The occurrence of sleep passed through the evolutionary sieve and is widespread in animal species. Sleep is known to be beneficial to cognitive and mnemonic tasks, while chronic sl…
Cholinergic switch between two types of slow waves in cerebral cortex
Trang-Anh E. Nghiem, Núria Tort-Colet, Tomasz Górski +8
Sleep slow waves are known to participate in memory consolidation, yet slow waves occurring under anesthesia present no positive effects on memory. Here, we shed light onto this pa…
State equation from the spectral structure of human brain activity
Trang-Anh Nghiem, Jean-Marc Lina, Matteo di Volo +4
Neural electromagnetic (EM) signals recorded non-invasively from individual human subjects vary in complexity and magnitude. Nonetheless, variation in neural activity has been diff…
Spontaneous activity emerging from an inferred network model captures complex temporal dynamics of spiking data
Cristiano Capone, Guido Gigante, Paolo Del Giudice
The combination of new recording techniques in neuroscience and powerful inference methods recently held the promise to recover useful effective models, at the single neuron or net…
Inferring Synaptic Structure in presence of Neural Interaction Time Scales
Cristiano Capone, Carla Filosa, Guido Gigante +2
Biological networks display a variety of activity patterns reflecting a web of interactions that is complex both in space and time. Yet inference methods have mainly focused on rec…