The parametrized dynamics of a standard nonlinear model neuron with self-interaction is discussed. For units with a self-excitatory connection a hysteresis effect is observed, and the underlying mechanism is identified as that of a cusp catastrophe. This is true for discrete as well as for continuous dynamics. For the discrete dynamics of self-inhibiting units there appear period-doubling bifur...

Behavioral study of linear model i.e. Integrate and fire model is compared with non-linear model i.e. Hodgkin-Huxley model. Both the models output are affected by Poisson inputs that are correlated positively. Responses of Integrate and fire model and Hodgkin-Huxley models differ in terms of correlated inputs. Linear Integrate and fire model is better for correlated inputs. Non-Linear model dis...

Basal ganglia circuits are known to have role in a wide range of behaviour spanning from movement initiation to high order cognitive processes as reward related learning. Here, the intention is to have a biophysically realistic model of basal ganglia circuit for voluntary motor action selection. The ultimate aim is to provide a framework for models which could help comprehension of complex proc...

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 Neuroscience are demonstrated and a learning algorithm based on postsynaptic delays is proposed. The TNLI incorporates temporal dynamics at the neuron level by modelling...

In this paper we present a functional model of spiking neuron intended for hardware implementation. The model allows the design of speedand/or area-optimized architectures. Some features of biological spiking neurons are abstracted, while preserving the functionality of the network, in order to define an architecture easily implementable in hardware, mainly in field programmable gate arrays (FP...

Independent Component Analysis (ICA) and related algorithms provide a model for explaining how sensory information is encoded in our brains. However, it remains unclear how neural network uses its biological plasticity to achieve this ICA-like processing: maximization of information transmission or minimization of redundancy. Here, we consider a neuron model proposed by Savin, Joshi, and Triesc...

Introduction: Profilin1 (PFN1) is a ubiquitously expressed protein known for its function as a regulator of actin polymerization and dynamics. A recent discovery linked mutant PFN1 to Amyotrophic Lateral Sclerosis (ALS), which is a fatal and progressive motor neuron disease. We have also demonstrated that Gly118Val mutation in PFN1 is a cause of ALS, and the formation of aggregates containing m...

In this paper we adopt a temporal coding approach to neuronal modeling of the visual cortex, using oscillations. We propose a hierarchy of three processing modules corresponding to di erent levels of representation. The rst layer encodes the input image (stimulus) into an array of units, while the second layer consists of a network of FitzHugh-Nagumo oscillators. The dynamical behaviour of the ...