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Dendritic Morphology Predicts Pattern Recognition Performance in Multi-compartmental Model Neurons with and without Active Conductances
(2015-04-01)
In this paper we examine how a neuron’s dendritic morphology can affect its pattern recognition performance. We use two different algorithms to systematically explore the space of dendritic morphologies: an algorithm that ...
Combining machine learning and simulations of a morphologically realistic model to study modulation of neuronal activity in cerebellar nuclei
(2014-07-21)
Epileptic absence seizures are characterized by synchronized oscillatory activity in the cerebral cortex that can be recorded as so-called spike-and-wave discharges (SWDs) by electroencephalogram. Although the cerebral ...
Characterising the performance of balanced memory networks
(2013)
Poster presented at CNS 2013
A potential role for the cerebellar nuclei in absence seizures
(2013)
Poster presented ar CNS 2013
Determinants of associative memory performance in spiking and non-spiking neural networks with different synaptic plasticity regimes
(2012)
Poster presented at CNS 2012
Clustering predicts memory performance in networks of spiking and non-spiking neurons
(2011)
The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in ...
The effect of dendritic morphology on pattern recognition in the presence of active conductances
(2011)
Poster presented at CNS 2011
Optimization of neuronal morphologies for pattern recognition
(2010)
Poster presented at CNS 2010
The effect of non-specific LTD on pattern recognition in cerebellar Purkinje cells
(2010)
Poster presented at CNS 2010