2 citations · 2 across the 4 of their papers we have counts for
8 papers
Mean field theory for a balanced hypercolumn model of orientation selectivity in primary visual cortex
A. Lerchner, G. Sterner, J. Hertz +1
We present a complete mean field theory for a balanced state of a simple model of an orientation hypercolumn. The theory is complemented by a description of a numerical procedure f…
High conductance states in a mean field cortical network model
Alexander Lerchner, Mandana Ahmadi, John Hertz
Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than…
Mean field methods for cortical network dynamics
John Hertz, Alexander Lerchner, Mandana Ahmadi
We review the use of mean field theory for describing the dynamics of dense, randomly connected cortical circuits. For a simple network of excitatory and inhibitory leaky integrate…
Response variability in balanced cortical networks
Alexander Lerchner, Cristina Ursta, John Hertz +2
We study the spike statistics of neurons in a network with dynamically balanced excitation and inhibition. Our model, intended to represent a generic cortical column, comprises ran…
Anomalous Response Variability in a Balanced Cortical Network Model
John Hertz, Barry Richmond, Kristian Nilsen
We use mean field theory to study the response properties of a simple randomly-connected model cortical network of leaky integrate-and-fire neurons with balanced excitation and inh…
Hebbian imprinting and retrieval in oscillatory neural networks
Silvia Scarpetta, Zhaoping Li, John Hertz
We introduce a model of generalized Hebbian learning and retrieval in oscillatory neural networks modeling cortical areas such as hippocampus and olfactory cortex. Recent experimen…