The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models ap...
Acetylcholine (ACh) plays an important role in a wide variety of cognitive tasks, such as perception, selective attention, associative learning, and memory. Extensive experimental...
The self-organising map (SOM) has been successfully employed as a nonparametric method for dimensionality reduction and data visualisation. However, for visualisation the SOM requ...
We present a model for the attentional neuromodulation of decision and selection processes. The model assumes that phasic responses in the brain nucleus Locus Coeruleus modulate, ...
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
The problem of designing the regularization term and regularization parameter for linear regression models is discussed. Previously, we derived an approximation to the generalizat...
In this paper we implement a computational model of a neuromodulatory system in an autonomous robot. The output of the neuromodulatory system acts as a value signal, modulating wi...
Knowledge of the effect of dopamine on corticostriatal synaptic plasticity has advanced rapidly over the last 5 years. We consider this new knowledge in relation to three factors ...
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow