Neuromorphic hardware enables fast and power-efficient neural network–based artificial
intelligence that is well suited to solving robotic tasks. Neuromorphic algorithms can be …

The brain is a hugely diverse, heterogeneous structure. Whether or not heterogeneity at the
neural level plays a functional role remains unclear, and has been relatively little explored in …

What any sensory neuron knows about the world is one of the cardinal questions in
Neuroscience. Information from the sensory periphery travels across synaptically coupled …

The backpropagation algorithm has promoted the rapid development of deep learning, but it
relies on a large amount of labeled data and still has a large gap with how humans learn …

Complexity is an indisputable, well-known, and broadly accepted feature of the brain.
Despite the apparently obvious and widely-spread consensus on the brain complexity …

Hetero‐modulated neural activation is vital for adaptive information processing and learning
that occurs in brain. To implement brain‐inspired adaptive processing, previously various …

Sensory information transmitted to the brain activates neurons to create a series of coping
behaviors. Understanding the mechanisms of neural computation and reverse engineering …

Spiking neural networks (SNNs) have demonstrated excellent capabilities in various
intelligent scenarios. Most existing methods for training SNNs are based on the concept of …

Short-term synaptic plasticity (STP) critically affects the processing of information in neuronal
circuits by reversibly changing the effective strength of connections between neurons on …

Inhibition plays a crucial role in neural signal processing, shaping and limiting responses. In
the auditory system, inhibition already modulates second order neurons in the cochlear …