A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines

Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural networks is the vector-matrix multiply when inputs are multiplied by the neural network weights. Conventional processing architectures are not well suited for simulating neural networks, often requiring large amounts of energy and time. Additionally, synapses in biological neural networks are not binary connections, but exhibit a nonlinear response function as neurotransmitters are emitted and diffuse between neurons. Inspired by neuroscience principles, we present a digital neuromorphic architecture, the Spiking Temporal Processing Unit (STPU), capable of modeling arbitrary complex synaptic response functions without requiring additional hardware components. We consider the paradigm of spiking neurons with temporally coded information as opposed to non-spiking rate coded neurons used in most neural networks. In this paradigm we examine liquid state machines applied to speech recognition and show how a liquid state machine with temporal dynamics maps onto the STPU-demonstrating the flexibility and efficiency of the STPU for instantiating neural algorithms.Comment: 8 pages, 4 Figures, Preprint of 2017 IJCN

''Intraventricular'' hemorrhage and cystic periventricular leukomalacia in preterm infants: how are they related?

Contains fulltext : 76138.pdf (publisher's version ) (Closed access)Intraventricular hemorrhage and cystic periventricular leukomalacia are often co-occurring characteristics of brain damage in preterm infants. Using data from 1016 infants born before 30 completed weeks' gestational age, we sought to clarify the relationship between severe intraventricular hemorrhage and cystic periventricular leukomalacia, with special emphasis on common antecedents and potential confounding. After comparing risk factors for intraventricular hemorrhage grades 1 through 4 and cystic periventricular leukomalacia, it appears the risk patterns for intraventricular hemorrhage grade 3, intraventricular hemorrhage grade 4, and cystic periventricular leukomalacia differ. The association between intraventricular hemorrhage grade 3 and cystic periventricular leukomalacia differs appreciably from the association between intraventricular hemorrhage grade 4 and cystic periventricular leukomalacia, supporting the notion that intraventricular hemorrhage grade 3 and intraventricular hemorrhage grade 4 are different entities. The presence of intraventricular hemorrhage grade 3 and intraventricular hemorrhage grade 4 increases the risk of cystic periventricular leukomalacia, even after adjusting for potential confounders. This raises the possibility that intraventricular hemorrhage grade 3 and intraventricular hemorrhage grade 4 cause cystic periventricular leukomalacia