The human brain is undoubtedly the most complex product of evolution.
Understanding how complex behaviour is generated by the intricacy of hundred
billion of neurons and synapses fascinated scientists and philosophers
for millennia. The multiscale trait of the central nervous system is a hallmark
of its architecture and brain functions emerge from the interaction
of its components at di erent temporal and spatial scales. A full understanding
cannot be achieved unless we approach this complexity at these
di erent scales, with techniques that are sensitive to these various levels
of organization. Here we propose a convergent approach to scale up from
local to global organization of the brain that relies on experimental, computational
and behavioral methods, mainly focusing on the cerebellum and
the neocortex. Through electrophysiological, neuro-prosthetic and behavioral
studies on a reduced animal preparation, we provide further evidence
about the central role of the climbing bre signal in precisely modulating
the overall activity and ne{tuning the learning process in a basic functional
cerebellar microcircuit. Having identi ed the properties of a single microcircuit,
how could the computational principles be extended to a larger scale
that includes also the polysynaptic connectivity with the neocortex? To
tackle this question, we propose a computational approach that integrates
reconstruction of anatomical structural data of the neocortex with biophysical
neuronal dynamics, that we employed to infer patterns of neuronal
activation in healthy and simulated disease. However, the brain operates
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in a natural environment that is continuously evolving. To reconcile the
reductionist approach with the real demands of an operating brain, while
maintaining a high degree of control, we propose an hybrid approach that
mixes virtual{reality with wearable devices that we validated in a conditioning
task. We show that such approach can overcome the limitations of the
classical laboratory settings thus providing a more ecological framework to
infer functional principles. Altogether, this thesis work advances our understanding
of the cerebellar mechanisms involved during the acquisition of
adaptive motor behaviors. Moreover, it paves the way for using a convergence
of computational and experimental approaches that o er complementary
views of brain organization to address questions about functions in health
and disease, which cannot be reduced to a single observational scale or
method.
| Identifer | oai:union.ndltd.org:TDX_UPF/oai:www.tdx.cat:10803/286228 |
| Date | 13 February 2015 |
| Creators | Zucca, Riccardo |
| Contributors | Verschure, Paul F. M. J., Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions |
| Publisher | Universitat Pompeu Fabra |
| Source Sets | Universitat Pompeu Fabra |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis, info:eu-repo/semantics/publishedVersion |
| Format | 185 p., application/pdf |
| Source | TDX (Tesis Doctorals en Xarxa) |
| Rights | L'accés als continguts d'aquesta tesi queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by-nd/3.0/es/, info:eu-repo/semantics/openAccess |
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