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The Effect of Different Forms of Synaptic Plasticity on Pattern Recognition in the Cerebellar Cortex
(2009)
Many cerebellar learning theories assume that long-term depression (LTD) of synapses between parallel fibres (PFs) and Purkinje cells (PCs) provides the basis for pattern recognition in the cerebellum. Previous work has ...
Connection Strategies in Associative Memory Models
(2009)
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 results in artificial ...
Decoding of Purkinje cell pauses by deep cerebellar nucleus neurons
(BioMed Central (BMC), 2009)
The recognition of parallel fibre (PF) input patterns by Purkinje cells has been suggested to underlie cerebellar learning [1,2]. A candidate mechanism for the recognition of PF patterns is the long-term depression (LTD) ...
The role of lateral inhibition in the sensory processing in a simulated spiking neural controller for a robot
(Institute of Electrical and Electronics Engineers (IEEE), 2009)
Visual adaptation is the process that allows animals to be able to see over a wide range of light levels. This is achieved partially by lateral inhibition in the retina which compensates for low/high light levels. Neural ...
Evolution of bilateral symmetry in agents controlled by spiking neural networks
(Institute of Electrical and Electronics Engineers (IEEE), 2009)
We present in this paper three novel developmental models allowing information to be encoded in space and time, using spiking neurons placed on a 2D substrate. In two of these models, we introduce neural development that ...
Connectivity graphs and the performance of sparse associative memory models
(Institute of Electrical and Electronics Engineers (IEEE), 2008)
Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks
(2008)
We created a neural architecture that can use two different types of information encoding strategies depending on the environment. The goal of this research was to create a simulated agent that could react to two different ...
Optimal noise in spiking neural networks for the detection of chemicals by simulated agents
(MIT Press, 2008)
We created a spiking neural controller for an agent that could use two different types of information encoding strategies depending on the level of chemical concentration present in the environment. The first goal of this ...
Encoding sensory information in spiking neural network for the control of autonomous agents
(2008)
The goal of the work presented here was to find a model of a spiking sensory neuron that could cope with small variations of a simulated pheromone concentration and also the whole range of concentrations. We tried many ...
Receptor response and soma leakiness in a simulated spiking neural controller for a robot
(INSTICC (Inst. Syst. Technologies Information Control and Communication), 2008)
This paper investigates different models of leakiness for the soma of a simulated spiking neural controller for a robot exhibiting negative photo-taxis. It also investigates two models of receptor response to stimulus ...