Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long
been considered an important component of learning and memory. Computational and …

Recent work has revealed that the neural activity patterns correlated with sensation,
cognition, and action often are not stable and instead undergo large scale changes over …

Newly generated excitatory synapses in the mammalian cortex lack sufficient AMPA-type
glutamate receptors to mediate neurotransmission, resulting in functionally silent synapses …

Nanowire networks (NWNs) mimic the brain's neurosynaptic connectivity and emergent
dynamics. Consequently, NWNs may also emulate the synaptic processes that enable …

Memory formation in matter is a theme of broad intellectual relevance; it sits at the
interdisciplinary crossroads of physics, biology, chemistry, and computer science. Memory …

With the current research impetus on neuromorphic computing hardware, realizing efficient
drift and diffusive memristors are considered critical milestones for the implementation of …

Classical Hebbian learning puts the emphasis on joint pre-and postsynaptic activity, but
neglects the potential role of neuromodulators. Since neuromodulators convey information …

Several analog and digital brain-inspired electronic systems have been recently proposed
as dedicated solutions for fast simulations of spiking neural networks. While these …

The synapse is a crucial element in biological neural networks, but a simple electronic
equivalent has been absent. This complicates the development of hardware that imitates …

Synaptic plasticity is a key component of the learning machinery in the brain. It is vital that
such plasticity be tightly regulated so that it occurs to the proper extent at the proper time …