In this work we study the formation of patterns of neuronal activity when some input are presented to the network. For this task a recently developed model of neuron is utilized. This model requires a very low computational effort but presents many characteristics of more complex models such as, spiking, bursting and sub-threshold oscillations, and therefore the realistic study of the behavior of big ensembles of neurons can be aborded, even under real time conditions. New results of the application of the wavelet transform technique to the analysis of pattern formation and the possible encoding of rhythms are presented; they show that this simple, low-computational, neuron model behaves much like more complex ones
An original simple neural mass model of a population of neurons has been used to investigate the ori...
While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiol...
This book treats wavelet networks which unify universal approximation features of neuronal networks ...
We investigate different dynamical regimes of a small neuronal circuit. This circuit includes two ce...
This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing i...
grantor: University of TorontoThis thesis explores the analysis and modeling of sensori-m...
Central pattern generators (CPGs) are localized, autonomous neuronal networks that coordinate the mu...
Abstract. Recordings of spontaneous activity of in-vitro neuronal networks reveal various phenomena ...
We present a comparative study of the performance of different basis functions for the nonparametric...
Deterministic nonlinear dynamics has been observed in experimental electrophysiological recordings p...
Abstract--There is a large class of central pattern generators that may change their rhythmic output...
Activity types of isolated neurons and their models may be generically classified as hyper- and depo...
Neurons in the brain are known to exhibit diverse bursting patterns. In this work, which combines th...
We have briefly reviewed the occurrence of the post-synaptic potentials between neurons, the relatio...
This paper describes the use of a computational tool based on the Morlet wavelet transform to invest...
An original simple neural mass model of a population of neurons has been used to investigate the ori...
While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiol...
This book treats wavelet networks which unify universal approximation features of neuronal networks ...
We investigate different dynamical regimes of a small neuronal circuit. This circuit includes two ce...
This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing i...
grantor: University of TorontoThis thesis explores the analysis and modeling of sensori-m...
Central pattern generators (CPGs) are localized, autonomous neuronal networks that coordinate the mu...
Abstract. Recordings of spontaneous activity of in-vitro neuronal networks reveal various phenomena ...
We present a comparative study of the performance of different basis functions for the nonparametric...
Deterministic nonlinear dynamics has been observed in experimental electrophysiological recordings p...
Abstract--There is a large class of central pattern generators that may change their rhythmic output...
Activity types of isolated neurons and their models may be generically classified as hyper- and depo...
Neurons in the brain are known to exhibit diverse bursting patterns. In this work, which combines th...
We have briefly reviewed the occurrence of the post-synaptic potentials between neurons, the relatio...
This paper describes the use of a computational tool based on the Morlet wavelet transform to invest...
An original simple neural mass model of a population of neurons has been used to investigate the ori...
While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiol...
This book treats wavelet networks which unify universal approximation features of neuronal networks ...