Biomedical subjects

Maria Elisabetta Ruaro

Publications and source records attributed to Maria Elisabetta Ruaro.

3 recordsLinked to original sources

PubMed2006

Embryonic stem cell-derived neurons form functional networks in vitro.

Embryonic stem (ES) cells provide a flexible and unlimited source for a variety of neuronal types. Because mature neurons establish neuronal networks very easily, we tested whether ES-derived neurons are capable of generating functional networks and whether these networks, generated in vitro, are capable of processing information. Single-cell electrophysiology with pharmacological antagonists demonstrated the presence of both excitatory and inhibitory synaptic connections. Extracellular recording with planar multielectrode arrays showed that spontaneous bursts of electrical activity are present in ES-derived networks with properties remarkably similar to those of hippocampal neurons. When stimulated with extracellular electrodes, ES-derived neurons fired action potentials, and the evoked electrical activity spread throughout the culture. A statistical analysis indicated that ES-derived networks discriminated between stimuli of different intensity at a single trial level, a key feature for an efficient information processing. Thus, ES-derived neurons provide a novel in vitro strategy to create functional networks with defined computational properties.

6-Cyano-7-nitroquinoxaline-2,3-dione↗

PubMed2005

Toward the neurocomputer: image processing and pattern recognition with neuronal cultures.

Information processing in the nervous system is based on parallel computation, adaptation and learning. These features cannot be easily implemented on conventional silicon devices. In order to obtain a better insight of how neurons process information, we have explored the possibility of using biological neurons as parallel and adaptable computing elements for image processing and pattern recognition. Commercially available multielectrode arrays (MEAs) were used to record and stimulate the electrical activity from neuronal cultures. By mapping digital images, i.e., arrays of pixels, into the stimulation of neuronal cultures, a low and bandpass filtering of images could be quickly and easily obtained. Responses to specific spatial patterns of stimulation were potentiated by an appropriate training (tetanization). Learning allowed pattern recognition and extraction of spatial features in processed images. Therefore, neurocomputers, (i.e., hybrid devices containing man-made elements and natural neurons) seem feasible and may become a new generation of computing devices, to be developed by a synergy of Neuroscience and Material Science.

Animals↗

PubMed2005

Statistical properties of information processing in neuronal networks.

Information processing and coding were analysed in dissociated hippocampal cultures, grown on multielectrode arrays. Multisite stimulation was used to activate different neurons and pathways of the network. The neural activity was binned into firing rates and the variability of the firing of individual neurons and of the whole population was analysed. In individual neurons, the timing of the first action potential (AP) was rather precise from trial to trial, whereas the timing of later APs was much more variable. Pooling APs in an ensemble of neurons reduced the variability of the response and allowed stimuli varying in intensity to be distinguished reliably in a single trial. A similar decrease of variability was observed pooling the first evoked APs in an ensemble of neurons. The size of the neuronal pool (approximately 50-100 neurons) and the time bin (approximately 20 ms) necessary to provide reproducible responses are remarkably similar to those obtained in in vivo preparations and in small nervous systems. Blockage of excitatory synaptic pathways mediated by NMDA receptors improved the mutual information between the evoked response and stimulus properties. When inhibitory GABAergic pathways were blocked by bicuculline the opposite effect was obtained. These results show how ensemble averages and an appropriate balance between inhibition and excitation allow neuronal networks to process information in a fast and reliable way.

Action Potentials↗