The explosion of “big data” applications imposes severe challenges of speed and scalability
on traditional computer systems. As the performance of traditional Von Neumann machines …

We examine the challenging “marriage” between computational efficiency and biological
plausibility—A crucial node in the domain of spiking neural networks at the intersection of …

The olfactory bulb receives rich glutamatergic projections from the piriform cortex. However,
the dynamics and importance of these feedback signals remain unknown. Here, we use …

The implementation of neuromorphic methods has delivered promising results for vision and
auditory sensors. These methods focus on mimicking the neuro-biological architecture to …

Discriminating similar molecules remains a very challenging problem for semiconductor gas
sensors. Here, we report a method to achieve precise gas discrimination of similar chemical …

Abstract The Artificial Neural Networks (ANNs), like CNN/DNN and LSTM, are not
biologically plausible. Despite their initial success, they cannot attain the cognitive …

The implementation of synaptic plasticity in neural simulation or neuromorphic hardware is
usually very resource-intensive, often requiring a compromise between efficiency and …

The perception of odours is the result of the complex processing of a signal, which initiates
at peripheral receptors and ends in the brain. Along this pathway, olfactory signal …

SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale
spiking neural networks at speeds close to biological real-time. Rather than using bespoke …

The brain enables animals to behaviorally adapt in order to survive in a complex and
dynamic environment, but how reward-oriented behaviors are achieved and computed by its …