46 citations · 226 across the 18 of their papers we have counts for
5 papers · 1 filter
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…
Towards biologically plausible Dreaming and Planning in recurrent spiking networks
Cristiano Capone, Pier Stanislao Paolucci
Humans and animals can learn new skills after practicing for a few hours, while current reinforcement learning algorithms require a large amount of data to achieve good performance…
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…