ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-09262018-152801


Tipo di tesi
Tesi di laurea magistrale
Autore
SAPONATI, MATTEO
URN
etd-09262018-152801
Titolo
Neural Oscillations and Information Transmission in a Thalamocortical Network Model
Dipartimento
FISICA
Corso di studi
FISICA
Relatori
relatore Prof. Cataldo, Enrico
correlatore Dott. Mazzoni, Alberto
Parole chiave
  • Statistical Analysis
  • Mathematical Modeling
  • Computational Neuroscience
  • Complex Systems
  • Statistical Physics
Data inizio appello
17/10/2018
Consultabilità
Completa
Riassunto
From the point of view of Physics, the brain is a macroscopic system formed by non-linear elements (neurons) interacting in an intricate fashion. Its behavior is studied in the portrait of dynamical system theory. With this approach, cognition processes are modeled as dynamical paths in complex phase spaces. Computational as well as statistical analysis are needed to characterize the emerging collective phenomena. In the present thesis we follow this approach in the study of communication processes between two areas of the brain: the thalamus and the cerebral cortex. In particular, we study how these two systems interact creating dynamical coupling for transferring and processing of information. We develop a scaled model of the system to study temporal dynamics and rhythmical patterns. Actually, an open problem in neuroscience is how neural networks choose to filter out or let pass specific frequencies of oscillatory activity and therefore have a gating role for the dynamics. Our purpose is to shade new light on the functional role of thalamus within sensory information processing in this sense. We stress that thalamocortical system is a complex anatomical structure hard to describe in its entirety. For our purposes, we focus on coupling between a local first order thalamic network and a local cortical circuitry of the respective primary cortical area.
Our model is able to reproduce typical collective oscillations of thalamocortical system. In particular, thalamic model dynamics is characterized by spindle oscillations in the 7-14 Hz range enclosed into slower δ-rhythms in the 1-4 Hz range. On the other hand, cortical model exhibits typical fast γ-oscillations in response to sustained external perturbations. We study if and how thalamus is able to modulate cortical activity through its intrinsic rhythms. We firstly study thalamocortical system in the isolated regime, i.e. when there is no external input influencing the system. We call this regime asleep state because it models an isolated state of the brain when external influences can be neglected. We find out that in a certain region of parameter space the cortical model embodies the slow δ-rhythms while filtering out the spindle oscillations. Such a phenomenon happens also during the awake state, i.e. when external informative perturbations influence the dynamics. We study the underlying pro- cesses of spindle-filtering with several investigations. Moreover, we do a statistical analysis to characterize possible functional roles of frequency-couplings between networks. From a first-order correlation analysis we find that networks show non-vanishing correlation only in the δ-rhythms with a certain degree of phase-locking. Furthermore an higher-order correlation analysis based on mutual information shows that networks multiplex information into two main pathways. The first is determined by low δ-rhythms while the second by cortical γ-rhythms encoding input strength. In this scenario spindle oscillations are filtered out by the cortex and remain and internal intrinsic thalamic mechanisms.
Our model is general and can be used to study every local thalamocortical network (for instance of every sensory system) respecting our approximations. Further developments of this work would regard the inclusion of cortical feedback which has a crucial role for several cognitive processes. This would possibly extend the number of processes described by our model.
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