• Publications
  • Influence
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory.
Competitive Hebbian learning through spike-timing-dependent synaptic plasticity
In modeling studies, it is found that this form of synaptic modification can automatically balance synaptic strengths to make postsynaptic firing irregular but more sensitive to presynaptic spike timing.
Synaptic plasticity: taming the beast
This work reviews three Hebbian forms of plasticity—synaptic scaling, spike-timing dependent plasticity and synaptic redistribution—and discusses their functional implications.
Synaptic Depression and Cortical Gain Control
Modeling work based on experimental measurements indicates that short-term depression of intracortical synapses provides a dynamic gain-control mechanism that allows equal percentage rate changes on rapidly and slowly firing afferents to produce equal postsynaptic responses.
The Effect of Correlated Variability on the Accuracy of a Population Code
Contrary to widespread belief, correlations in the variabilities of neuronal firing rates do not limit the increase in coding accuracy provided by using large populations of encoding neurons.
A Quantitative Description of Short-Term Plasticity at Excitatory Synapses in Layer 2/3 of Rat Primary Visual Cortex
The results indicate that firing evoked by visual stimuli is likely to cause significant depression at cortical synapses, and synaptic depression may be an important determinant of the temporal features of visual cortical responses.
Signal Propagation and Logic Gating in Networks of Integrate-and-Fire Neurons
  • T. Vogels, L. Abbott
  • Computer Science, Medicine
    The Journal of Neuroscience
  • 16 November 2005
This work investigates the factors affecting transmission and shows that multiple signals can propagate simultaneously along different pathways and shows how different types of logic gates can arise within the architecture of the random network through the strengthening of specific synapses.