Conductance-based integrate-and-fire models
Neural Computation
Image segmentation based on oscillatory correlation
Neural Computation
Synchronization of Locally Coupled Neural Oscillators
Neural Processing Letters
Linearization of F-1 curves by adaptation
Neural Computation
Detailed Parallel Simulation of a Biological Neuronal Network
IEEE Computational Science & Engineering
The influence of limit cycle topology on the phase resetting curve
Neural Computation
Emergent neural computational architectures based on neuroscience
Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing
Characterization of subthreshold voltage fluctuations in neuronal membranes
Neural Computation
Minimal Models of Adapted Neuronal Response to In Vivo–lLike Input Currents
Neural Computation
Realistically Coupled Neural Mass Models Can Generate EEG Rhythms
Neural Computation
Neural correlation via random connections
Neural Computation
Study on the role of GABAergic synapses in synchronization
Neurocomputing
Recognition of partially occluded and rotated images with a network of spiking neurons
IEEE Transactions on Neural Networks
Power laws for spontaneous neuronal activity in hippocampal CA3 slice culture
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
Information coding in a laminar computational model of cat primary visual cortex
Journal of Computational Neuroscience
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Journal of Computational Neuroscience
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From the Publisher:The questions of how a large population of neurons in the brain functions, how synchronized firing of neurons is achieved, and what factors regulate how many and which neurons fire under different conditions form the central theme of this book. Using a combined experimental-theoretical approach unique in neuroscience, the authors present important new techniques for the physiological reconstruction of a large biological neuronal network. They begin by discussing experimental studies of the CA3 hippocampal region in vitro, focusing on single-cell and synaptic electrophysiology, particularly the effects a single neuron exerts on its neighbors. This is followed by a description of a computer model of the system, first for individual cells then for the entire detailed network, and the model is compared with experiments under a variety of conditions. The results shed significant light into the mechanisms of epilepsy, electroencephalograms, and biological oscillations and provide an excellent test case for theories of neural networks.