Search results for "Neuronal network"

Graph-theoretical derivation of brain structural connectivity

2020

Brain connectivity at the single neuron level can provide fundamental insights into how information is integrated and propagated within and between brain regions. However, it is almost impossible to adequately study this problem experimentally and, despite intense efforts in the field, no mathematical description has been obtained so far. Here, we present a mathematical framework based on a graph-theoretical approach that, starting from experimental data obtained from a few small subsets of neurons, can quantitatively explain and predict the corresponding full network properties. This model also changes the paradigm with which large-scale model networks can be built, from using probabilisti…

Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy

2017

Neuronal networks are often characterized by their spiking and bursting statistics. Previously, we introducedan adaptive burst analysis methodwhich enhances the analysis power for neuronal networks with highly varying firing dynamics. The adaptation is based on single channels analyzing each element of a network separately. Such kind of analysis was adequate for the assessment of local behavior, where the analysis focuses on the neuronal activity in the vicinity of a single electrode. However, the assessment of the whole network may be hampered, if parts of the network are analyzed using different rules. Here, we test how using multiple channels and measurement time points affect adaptive b…

Spectral entropy based neuronal network synchronization analysis based on microelectrode array measurements

2016

Synchrony and asynchrony are essential aspects of the functioning of interconnected neuronal cells and networks. New information on neuronal synchronization can be expected to aid in understanding these systems. Synchronization provides insight in the functional connectivity and the spatial distribution of the information processing in the networks. Synchronization is generally studied with time domain analysis of neuronal events, or using direct frequency spectrum analysis, e.g., in specific frequency bands. However, these methods have their pitfalls. Thus, we have previously proposed a method to analyze temporal changes in the complexity of the frequency of signals originating from differ…

Neuronal Cytoskeleton in Intellectual Disability: From Systems Biology and Modeling to Therapeutic Opportunities

2021

Intellectual disability (ID) is a pathological condition characterized by limited intellectual functioning and adaptive behaviors. It affects 1–3% of the worldwide population, and no pharmacological therapies are currently available. More than 1000 genes have been found mutated in ID patients pointing out that, despite the common phenotype, the genetic bases are highly heterogeneous and apparently unrelated. Bibliomic analysis reveals that ID genes converge onto a few biological modules, including cytoskeleton dynamics, whose regulation depends on Rho GTPases transduction. Genetic variants exert their effects at different levels in a hierarchical arrangement, starting from the molecular lev…

Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

2012

In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing s…

Noise influence on correlated activities in a modular neuronal network: From synapses to functional connectivity

2008

In this work we propose taking noise into account when modeling the neuronal activity in a correlation-based type network. Volume transmission effects on connectivity are considered. As a result, an individual module can be set in an "activated" state via noise produced by the remaining modules. The stochastic approach could provide a new insight into the relation between functional and anatomical connectivity.

rTMS evidence of different delay and decision processes in a fronto-parietal neuronal network activated during spatial working memory.

2003

The existence of a specific and widely distributed network for spatial working memory (WM) in humans, involving the posterior parietal cortex and the prefrontal cortex, is supported by a number of neuroimaging studies. We used a repetitive transcranial magnetic stimulation (rTMS) approach to investigate the temporal dynamics and the reciprocal interactions of the different areas of the parieto-frontal network in normal subjects performing a spatial WM task, with the aim to compare neural activity of the different areas in the delay and decision phases of the task. Trains of rTMS at 25 Hz were delivered over the posterior parietal cortex (PPC), the premotor cortex (SFG) and the dorsolateral …

Corrigendum: Spectral Entropy Based Neuronal Network Synchronization Analysis Based on Microelectrode Array Measurements

2020

An Original Convolution Model to analyze Graph Network Distribution Features

2022

Modern Graph Theory is a newly emerging field that involves all of those approaches that study graphs differently from Classic Graph Theory. The main difference between Classic and Modern Graph Theory regards the analysis and the use of graph's structures (micro/macro). The former aims to solve tasks hosted on graph nodes, most of the time with no insight into the global graph structure, the latter aims to analyze and discover the most salient features characterizing a whole network of each graph, like degree distributions, hubs, clustering coefficient and network motifs. The activities carried out during the PhD period concerned, after a careful preliminary study on the applications of the…

Aligned microcontact printing of biomolecules on microelectronic device surfaces

2001

Microcontact printing (/spl mu/CP) of extracellular matrix proteins is a fascinating approach to control cell positioning and outgrowth, which is essential in the development of applications ranging from cellular biosensors to tissue engineering. Microelectronic devices can be used to detect the activity from a large number of recording sites over the long term. However, signals from cells can only be recorded at small sensitive spots. Here, the authors present an innovative setup to perform aligned /spl mu/CP of extracellular matrix proteins on microelectronic devices in order to guide the growth of electrogenic cells specifically to these sensitive spots. The authors' system is based on t…