Biomedical subjects

Nicolangelo Iannella

Publications and source records attributed to Nicolangelo Iannella.

3 recordsLinked to original sources

PubMed2006

Synaptic efficacy cluster formation across the dendrite via STDP.

The role of spike-timing-dependent plasticity (STDP) in shaping the strength of a synapse located on the dendritic tree has gained recent interest. Previous theoretical studies using STDP have mostly used simplified integrate-and-fire models to investigate the evolution of synaptic efficacy with time. Such studies usually show that the final weight distribution is unimodal or bimodal resulting from a multiplicative or additive STDP rule, respectively. However, very little is known about how STDP shapes the spatial organization of synaptic efficacies. Here, for the first time, we demonstrate that spatial clustering of synaptic efficacies can occur on the dendrite via STDP, where changes in synaptic efficacy are driven by timing differences between synaptic inputs and the generation of local dendritic spikes. Specifically, when the model neuron is stimulated by two independent groups of correlated afferent inputs, the synaptic efficacies from each group, are not only spatially clustered on the dendrite but also spatially complementary to each other.

Action Potentials↗

PubMed2006

Analytical solutions for nonlinear cable equations with calcium dynamics. I: Derivations.

The interaction between membrane potential and internal calcium concentration plays many important roles in regulating synaptic integration and neuronal firing. In order to gain a better theoretical understanding between the voltage-calcium interaction, a nonlinear cable equation with calcium dynamics is solved analytically. This general reaction-diffusion system represents a model of a cylindrical dendritic segment in which calcium diffuses internally in the presence of buffers, pumps and exchangers, and where ion channels are sparsely distributed over the membrane,in the form of hotspots, acting as point current sources along the dendritic membrane. In order to proceed, the reaction-diffusion system is recast into a system of coupled nonlinear integral equations, with which a perturbative expansion in dimensionless voltage and calcium concentration are used to find analytical solutions to this general system. The resulting solutions can be used to investigate, the interaction between the membrane potential and underlying calcium dynamics in a natural (non-discretized) setting.

Animals↗

PubMedDate not supplied

Firing properties of a stochastic PDE model of a rat sensory cortex layer 2/3 pyramidal cell.

We have developed a non-linear stochastic PDE (partial differential equation) model of a rat layer 2/3 somatosensory pyramidal neuron which approximates several of the dynamical properties of these cells. The model distinguishes telodendrites, a myelinated axon, initial segment, hillock, soma and a simplified dendritic tree. Distributions and properties of excitatory and inhibitory synapses were included, in accordance with recent anatomical and physiological findings. Using simulation methods, we aim to show that the spatial separation between regions of spatially distributed randomly activated excitatory and inhibitory synaptic inputs may be an important parameter which can influence neuronal firing properties. Due to the complexity of the problem, with respect to configurations of spatially and temporally activated excitatory and inhibitory synaptic inputs, we consider two simple configurations in which the spatial region of activated excitatory and inhibitory synaptic inputs overlap and when they are far from each. In the first, denoted configuration A, activated excitatory and inhibitory synapses were located close to the soma. In the second, denoted configuration B, active inhibitory synapses were close the soma, while active excitatory synapses were located on distal regions of the dendrite. For the first configuration, we find that increases in the mean rate of inhibition results in an increase in the width of the firing rate tuning curves, and that for particular mean input frequencies of excitation, increasing the mean input rate of inhibition does not always imply that the neuron fires at a slower rate. Furthermore, we observed for mean input frequencies of excitation between 15 and 60 (Hz), that increasing the mean rate of inhibition resulted in the linearization of the firing rate over this interval. For configuration B, no increase in width nor a linearization effect via inhibition was observed. These differences indicate that the distance between regions of active excitatory and inhibitory synapses may be an important factor to consider in determining how the interaction between excitation and inhibition contributes to neuronal firing.

Animals↗