Browsing Τμήμα Πληροφορικής / Department of Computer Science by Author "Bugmann, G."
Now showing items 1-7 of 7
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Article
Coefficient of variation vs. mean interspike interval curves: What do they tell use about the brain?
Christodoulou, Chris C.; Bugmann, G. (2001)A number of models have been produced recently to explain the high variability of natural spike trains (Softky and Koch, J. Neurosci. 13 (1) (1993) 334). These models use a range of different biological mechanisms including ...
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Article
Distinguishing the causes of firing with themembrane potential slope
Koutsou, Achilleas; Christodoulou, Chris C.; Bugmann, G.; Kanev, J. (2012)In this letter, we aim to measure the relative contribution of coincidence detection and temporal integration to the firing of spikes of a simple neuron model. To this end, we develop a method to infer the degree of synchrony ...
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Article
Near Poisson-type firing produced by concurrent excitation and inhibition
Christodoulou, Chris C.; Bugmann, G. (2000)The effect of inhibition on the firing variability is examined in this paper using the biologically-inspired temporal noisy-leaky integrator (TNLI) neuron model. The TNLI incorporates hyperpolarising inhibition with negative ...
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Article
On learning time delays between the spikes from different input neurons in a biophysical model of a pyramidal neuron
Koutsou, Achilleas; Bugmann, G.; Christodoulou, Chris C. (2015)Biological systems are able to recognise temporal sequences of stimuli or compute in the temporal domain. In this paper we are exploring whether a biophysical model of a pyramidal neuron can detect and learn systematic ...
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Role of Temporal Integration and Fluctuation Detection in the Highly Irregular Firing of a Leaky Integrator Neuron Model with Partial Reset
Bugmann, G.; Christodoulou, Chris C.; Taylor, J. G. (1997)Partial reset is a simple and powerful tool for controlling the irregularity of spike trains fired by a leaky integrator neuron model with random inputs. In particular, a single neuron model with a realistic membrane time ...
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Article
A spiking neuron model: Applications and learning
Christodoulou, Chris C.; Bugmann, G.; Clarkson, T. G. (2002)This paper presents a biologically inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the model as well as its applications in Computational ...
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Article
The temporal noisy-leaky integrator neuron with additional inhibitory inputs
Christodoulou, Chris C.; Bugmann, G.; Clarkson, T. G.; Taylor, J. G. (1993)The Temporal Noisy-Leaky Integrator (TNU) neuron model with additional inhibitory inputs is presented together with its theoretical mathematical basis. The TNU is a biologically inspired hardware neuron which models ...