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Title: Metastability : an emergent phenomenon in networks of spiking neurons
Author: Bhowmik, David
ISNI:       0000 0004 5349 0525
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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It is widely recognised that different brain areas perform different specialised functions. However, it remains an open question how different brain areas coordinate with each other and give rise to global brain states and high-level cognition. Recent theories suggest that transient periods of synchronisation and desynchronisation provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Empirical evidence from human resting state networks has shown a tendency for multiple brain areas to synchronise for short amounts of time, and for different synchronous groups to appear at different times. In dynamical systems terms, this behaviour resembles metastability - an intrinsically driven movement between transient, attractor-like states. However, it remains an open question what the underlying mechanism is that gives rise to these observed phenomena. The thesis first establishes that oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in the same and different structures. The thesis next explores inter-band frequency modulation between neural oscillators. The results show that oscillations in different neural populations, and in different frequency bands, modulate each other so as to change frequency. Further to this, the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Finally, a symbiotic relationship between metastability and underlying network structure is elucidated, in which the presence of plasticity, responding to the interactions between different neural areas, will naturally form modular small-world networks that in turn further promote metastability. This seemingly inevitable drive towards metastabilty in simulation suggests that it should also be present in biological brains. The conclusion drawn is that these key network characteristics, and the metastable dynamics they promote, facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby support sophisticated cognitive processing in the brain.
Supervisor: Shanahan, Murray Sponsor: Engineering and Physical Sciences Research Council ; DTA
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral