Network design and the brain
Neural circuits have evolved to accommodate similar information processing challenges as
those faced by engineered systems. Here, we compare neural versus engineering strategies …
those faced by engineered systems. Here, we compare neural versus engineering strategies …
Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence
Previous research has demonstrated that individuals with higher intelligence are more likely
to have larger gray matter volume in brain areas predominantly located in parieto-frontal …
to have larger gray matter volume in brain areas predominantly located in parieto-frontal …
Structural plasticity for neuromorphic networks with electropolymerized dendritic PEDOT connections
Neural networks are powerful tools for solving complex problems, but finding the right
network topology for a given task remains an open question. Biology uses neurogenesis …
network topology for a given task remains an open question. Biology uses neurogenesis …
A soft-pruning method applied during training of spiking neural networks for in-memory computing applications
Inspired from the computational efficiency of the biological brain, spiking neural networks
(SNNs) emulate biological neural networks, neural codes, dynamics, and circuitry. SNNs …
(SNNs) emulate biological neural networks, neural codes, dynamics, and circuitry. SNNs …
Higher VO2max is associated with thicker cortex and lower grey matter blood flow in older adults
VO2max (maximal oxygen consumption), a validated measure of aerobic fitness, has been
associated with better cerebral artery compliance and measures of brain morphology, such …
associated with better cerebral artery compliance and measures of brain morphology, such …
Surrogate-assisted evolutionary search of spiking neural architectures in liquid state machines
Spiking neural networks (SNNs) are believed to be a powerful neural computation
framework inspired by the vivo neurons. As a class of recurrent SNNs, liquid state machines …
framework inspired by the vivo neurons. As a class of recurrent SNNs, liquid state machines …
Estimated gray matter volume rapidly changes after a short motor task
Skill learning induces changes in estimates of gray matter volume (GMV) in the human
brain, commonly detectable with magnetic resonance imaging (MRI). Rapid changes in …
brain, commonly detectable with magnetic resonance imaging (MRI). Rapid changes in …
[HTML][HTML] Structural plasticity on an accelerated analog neuromorphic hardware system
In computational neuroscience, as well as in machine learning, neuromorphic devices
promise an accelerated and scalable alternative to neural network simulations. Their neural …
promise an accelerated and scalable alternative to neural network simulations. Their neural …
Emergence of stable synaptic clusters on dendrites through synaptic rewiring
T Limbacher, R Legenstein - Frontiers in computational neuroscience, 2020 - frontiersin.org
The connectivity structure of neuronal networks in cortex is highly dynamic. This ongoing
cortical rewiring is assumed to serve important functions for learning and memory. We …
cortical rewiring is assumed to serve important functions for learning and memory. We …
[PDF][PDF] A Survey of Learning Spiking Neural P Systems and A Novel Instance.
In the last few decades membrane computing has established itself as an important branch
of natural computing. Investigating computational power, complexity aspects and real-world …
of natural computing. Investigating computational power, complexity aspects and real-world …