Neural networks : the official journal of the International Neural Network Society
Sep 12, 2017
Supervised learning algorithms in a spiking neural network either learn a spike-train pattern for a single neuron receiving input spike-train from multiple input synapses or learn to output the first spike time in a feedforward network setting. In th...
Journal of computational neuroscience
Sep 12, 2017
Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of ...
Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can dir...
In this paper, we study a network of Izhikevich neurons to explore what it means for a brain to be at the edge of chaos. To do so, we first constructed the phase diagram of a single Izhikevich excitatory neuron, and identified a small region of the p...
Adapting motor output based on environmental forces is critical for successful locomotion in the real world. Arthropods use at least two neural mechanisms to adjust muscle activation while walking based on detected forces. Mechanism 1 uses negative f...
Human memory is capable of retrieving similar memories to a just retrieved one. This associative ability is at the base of our everyday processing of information. Current models of memory have not been able to underpin the mechanism that the brain co...
Dynamics of a reverberating neural net is studied by means of computer simulation. The net, which is composed of 9 leaky integrate-and-fire (LIF) neurons arranged in a square lattice, is fully connected with interneuronal communication delay proporti...
Neural networks : the official journal of the International Neural Network Society
Jul 24, 2017
Recordings of neural network activity in vitro are increasingly being used to assess the development of neural network activity and the effects of drugs, chemicals and disease states on neural network function. The high-content nature of the data der...
Recent studies on the theoretical performance of latency and rate code in single neurons have revealed that the ultimate accuracy is affected in a nontrivial way by aspects such as the level of spontaneous activity of presynaptic neurons, amount of n...
Journal of computational neuroscience
Jun 29, 2017
We propose a mathematical model of a continuous attractor network that controls social behaviors. The model is examined with bifurcation analysis and computer simulations. The results show that the model exhibits stable steady states and thresholds f...