A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input
AN Burkitt - Biological cybernetics, 2006 - Springer
The integrate-and-fire neuron model is one of the most widely used models for analyzing the
behavior of neural systems. It describes the membrane potential of a neuron in terms of the …
behavior of neural systems. It describes the membrane potential of a neuron in terms of the …
Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding
The brain is a highly modular structure. To exploit modularity, it is necessary that spiking
activity can propagate from one module to another while preserving the information it …
activity can propagate from one module to another while preserving the information it …
Neural network dynamics
Neural network modeling is often concerned with stimulus-driven responses, but most of the
activity in the brain is internally generated. Here, we review network models of internally …
activity in the brain is internally generated. Here, we review network models of internally …
Fractals in the nervous system: conceptual implications for theoretical neuroscience
G Werner - Frontiers in physiology, 2010 - frontiersin.org
This essay is presented with two principal objectives in mind: first, to document the
prevalence of fractals at all levels of the nervous system, giving credence to the notion of …
prevalence of fractals at all levels of the nervous system, giving credence to the notion of …
The role (s) of astrocytes and astrocyte activity in neurometabolism, neurovascular coupling, and the production of functional neuroimaging signals
CR Figley, PW Stroman - European Journal of Neuroscience, 2011 - Wiley Online Library
Data acquired with functional magnetic resonance imaging (fMRI) and positron emission
tomography (PET) are often interpreted in terms of the underlying neuronal activity, despite …
tomography (PET) are often interpreted in terms of the underlying neuronal activity, despite …
Maximizing information exchange between complex networks
BJ West, EL Geneston, P Grigolini - Physics Reports, 2008 - Elsevier
Science is not merely the smooth progressive interaction of hypothesis, experiment and
theory, although it sometimes has that form. More realistically the scientific study of any …
theory, although it sometimes has that form. More realistically the scientific study of any …
Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo–like input currents
A Rauch, G La Camera, HR Luscher… - Journal of …, 2003 - journals.physiology.org
In the intact brain neurons are constantly exposed to intense synaptic activity. This heavy
barrage of excitatory and inhibitory inputs was recreated in vitro by injecting a noisy current …
barrage of excitatory and inhibitory inputs was recreated in vitro by injecting a noisy current …
[图书][B] Computational neuroscience: a comprehensive approach
J Feng - 2003 - taylorfrancis.com
How does the brain work? After a century of research, we still lack a coherent view of how
neurons process signals and control our activities. But as the field of computational …
neurons process signals and control our activities. But as the field of computational …
Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses
RJ Vogelstein, U Mallik, JT Vogelstein… - IEEE transactions on …, 2007 - ieeexplore.ieee.org
A mixed-signal very large scale integration (VLSI) chip for large scale emulation of spiking
neural networks is presented. The chip contains 2400 silicon neurons with fully …
neural networks is presented. The chip contains 2400 silicon neurons with fully …
Scaling up dynamic graph representation learning via spiking neural networks
Recent years have seen a surge in research on dynamic graph representation learning,
which aims to model temporal graphs that are dynamic and evolving constantly over time …
which aims to model temporal graphs that are dynamic and evolving constantly over time …