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Modeling the electrophysiological properties of in vitro neurobiological systems: communication in neuronal networks and collective electrophysiological activity

Under the typical perspectives of the Computational Neuroscience and Bioengineering research fields, mechanistic and computational models of the nervous system can be classified according to two distinct approaches: at one end there are large-scale theories, where a large number of interacting simplified neurons interact and determine the collective behaviour, being much richer than those of the single units. At the other end, extremely detailed models of biochemical pathways and of the molecular, subcellular as well as synaptic mechanisms for information processing can be developed and studied. In the present thesis, an algorithmic strategy is developed in order to link those two quantitative description approaches, without making any unrealistic or simplistic assumption and with the aim of simulating large networks of synaptically interacting neurons, at low computational costs (i.e. memory and CPU time resources). This is strikingly relevant for the Neuroscience community, since synaptic chemical transmission and plasticity are nowadays believed to play a fundamental role in the adaptive properties characterizing the nervous system as a whole. Areas of related interest and applications of the topics presented in this thesis include the study of biophysical mechanisms for computation in neurons, the detailed computer simulations of neuronal circuits, the models of learning, the representation of sensory information in neuronal networks, systems models of sensory-motor integration, and computational analysis of problems in biological sensing, control and perception.

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Dottorato di Ricerca in Bioingegneria (XIII ciclo) Politecnico di Milano Modeling the electrophysiological properties of in vitroneurobiological systems: communication in neuronal networks and collective electrical activity. Michele Giugliano I-6 I.2. Neuronal Physiology I.2.1 Levels of Organization and Cellular Physiology The function of the nervous system can be examined at a number of levels of organization (see fig. I.2) and in such a perspective, a highly interdisciplinary approach is required. For instance, Biochemistry and Molecular Biology investigate the properties of molecules that perform tasks important for neuronal function (e.g. the membrane ionic-permeability, the ligand-receptor dynamics, etc.). Physiology studies the characteristics of individual neurons (e.g. the features of signal propagation and attenuation of neuritic branch points, etc.) as well as of collections of cells that are functionally related (e.g. reflex arcs, chemical and electric synaptic interactions, etc.). Behavioral Psychology explores patterns of behavior and its modification-learning in experimental animals ranging from lower invertebrates to humans. Computational Neuroscience and Bioengineering attempt to put it all together, to model higher brain functions in terms of the known properties of molecules, cells, or collections of cells. Throughout the present thesis, major emphasis will be given to signaling between erve cells (i.e. inter-cellular information transfer). This kind of cell communication is essential for an organism to sen e information about its environment, to import this information into its brain where it can be processed, and to generate an appropriate behavioral response (L vitan and Kaczmarek, 1997).

Tesi di Dottorato

Dipartimento: Dipartimento di Bioingegneria

Autore: Michele Giugliano Contatta »

Composta da 198 pagine.


Questa tesi ha raggiunto 388 click dal 20/03/2004.

Disponibile in PDF, la consultazione è esclusivamente in formato digitale.