Anterior cingulate cortex and its input to the basolateral amygdala control innate fear response
Nature Communications, 2018 Brain circuits that control innate fear response are essential for an animal’s survival. Here, the authors report how the anterior cingulate cortex and its projection to amygdala control the innate fear response in mice.
Jinho Jhang +5 more
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Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network [PDF]
Journal of Physical Chemistry A, 2020 Chemical reactions occur in energy, environmental, biological, and many other natural systems, and the inference of the reaction networks is essential to understand and design the chemical processes in engineering and life sciences.
Weiqi Ji, Sili Deng
semanticscholar +1 more source
On the role of synaptic stochasticity in training low-precision neural networks [PDF]
, 2018 Stochasticity and limited precision of synaptic weights in neural network models are key aspects of both biological and hardware modeling of learning processes.
Baldassi, Carlo +6 more
core +4 more sources
ARTIFICIAL NEURAL NETWORK FOR MODELS OF HUMAN OPERATOR
Acta Polytechnica CTU Proceedings, 2017 This paper presents a new approach to mental functions modeling with the use of artificial neural networks. The artificial neural networks seems to be a promising method for the modeling of a human operator because the architecture of the ANN is directly
Martin Ruzek
doaj +1 more source
Exploiting Device Mismatch in Neuromorphic VLSI Systems to Implement Axonal Delays [PDF]
, 2012 Sheik S, Chicca E, Indiveri G. Exploiting Device Mismatch in Neuromorphic VLSI Systems to Implement Axonal Delays. Presented at the International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia.Axonal delays are used in neural ...
Chicca, Elisabetta +2 more
core +4 more sources
Cellular computation and cognition
Frontiers in Computational Neuroscience, 2023 Contemporary neural network models often overlook a central biological fact about neural processing: that single neurons are themselves complex, semi-autonomous computing systems.
W. Tecumseh Fitch
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Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor [PDF]
, 2018 Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent parallelism make neuromorphic computing a promising paradigm for building ...
Glatz, Sebastian +4 more
core +1 more source
Predefined-time synchronization of inertial memristive neural networks
Nantong Daxue xuebao. Ziran kexue ban, 2023 Based on a novel control protocol, the synchronization problem of predefined-time of neural networks with inertia and memristor is studied. The network model considered in this paper can be widely used to simulate biological synapses, and has good ...
JIANG Zhuyan; LIU Xiaoyang
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A Biohybrid Setup for Coupling Biological and Neuromorphic Neural Networks
Frontiers in Neuroscience, 2019 Developing technologies for coupling neural activity and artificial neural components, is key for advancing neural interfaces and neuroprosthetics. We present a biohybrid experimental setting, where the activity of a biological neural network is coupled ...
Hanna Keren +6 more
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Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons
Sensors, 2023 A spiking neural network (SNN) is a type of artificial neural network that operates based on discrete spikes to process timing information, similar to the manner in which the human brain processes real-world problems.
Geunbo Yang +7 more
doaj +1 more source