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Neuronal firing activities have attracted a lot of attention since a large population of spatiotemporal patterns in the brain is the basis for adaptive behavior and can also reveal the signs for various neurological disorders including Alzheimers, schizophrenia, epilepsy and others. Here, we study the dynamics of a simple neuronal network using different sets of settings on a neuromorphic chip. We observed three different types of collective neuronal firing activities, which agree with the clinical data taken from the brain. We constructed a brain phase diagram and showed that within the weak noise region, the brain is operating in an expected noise-induced phase (N-phase) rather than at a so-called self-organized critical boundary. The significance of this study is twofold: first, the deviation of neuronal activities from the normal brain could be symptomatic of diseases of the central nervous system, thus paving the way for new diagnostics and treatments; second, the normal brain states in the N-phase are optimal for computation and information processing. The latter may provide a way to establish powerful new computing paradigm using collective behavior of networks of spiking neurons.
We present two novel methods for performing logic operations. Our methods are based on using the time dimension for programming and data representation. The first method is based on varying the sampling moment in time of a neuronal action potential,
Stimulation of target neuronal populations using optogenetic techniques during specific sleep stages has begun to elucidate the mechanisms and effects of sleep. To conduct closed-loop optogenetic sleep studies in untethered animals, we designed a ful
Chimera states---the coexistence of synchrony and asynchrony in a nonlocally-coupled network of identical oscillators---are often used as a model framework for epileptic seizures. Here, we explore the dynamics of chimera states in a network of modifi
We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we combine a ge
The brain can be understood as a collection of interacting neuronal oscillators, but the extent to which its sustained activity is due to coupling among brain areas is still unclear. Here we study the joint dynamics of two cortical columns described