Abstract
How can cognitive behavior be decoded through the brain? Can we understand mental states by using the traditional strategy of localizationism? Can the network-centric perspective bridge the gap between the brain and behavior? For decades, cognitive neuroscience has centered on the idea that specific cognitive functions can be pinpointed to precise brain regions or rhythms. This view, known as localizationism, has helped researchers understand brain structure and function. However, this approach often falls short in accounting for the complexity of human cognition and behavior, which are dynamic and multifaceted. Even a brief examination of the field highlights contradictory findings and variations among explanations.Over the past decade, groundbreaking progress in the interdisciplinary field of network science has unveiled a robust framework for deciphering the intricate structure and functioning of human brain networks. Recent advancements in analytical techniques have substantially enhanced our ability to represent and quantify brain connectivity across multiple scales, ranging from individual synaptic connections to complex communities and extensive networks. This granular view into the brain’s intricate connectivity has led to a paradigm shift in neuroscience, where interactions among distributed brain regions are now understood to form the foundational basis of cognitive behaviors. These insights emphasize the importance of network dynamics in orchestrating brain functions and suggest that cognitive processes and behavioral outputs emerge not from isolated neural components but from the coordinated activity across these interconnected systems.
The network perspective allows for a comprehensive understanding of brain dynamics. It underscores the potential for developing sophisticated models of brain function that can effectively explain the variability and complexity of human cognition and behavior. Thus, the present study aims to reveal the limitations of localizability in explaining cognitive processes and behavior comprehensively. Through a series of empirical studies integrating experimental and analytical methodologies, this work demonstrates that cognitive functions cannot be fully understood by examining individual brain regions in isolation. Instead, they emerge from intricate interactions within functional networks of brain regions.
This thesis presents an in-depth analysis of how functional brain networks, characterized by their complex connectivity patterns, provide a highly robust framework for understanding cognitive behavior. Dynamic functional interactions are mapped within these networks and correlated with behavioral outcomes in various contexts. Our findings show that brain networks adapt and reorganize in response to different cognitive demands, thereby offering a more flexible and accurate explanation of cognitive processes than the localization approach. Furthermore, we discuss the implications of our findings to developing therapeutic strategies and enhancing brain–computer interfaces, which rely on a nuanced understanding of how cognitive functions are distributed across the functional brain connectivity. By shifting the focus from individual regions or specific brain rhythms to comprehensive network dynamics, this thesis substantially contributes to the evolving field of cognitive neuroscience and opens new avenues for research in understanding the neural foundations of human behavior.
| Date of Award | 20 Aug 2025 |
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| Original language | English |
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| Supervisor | L H Leanne CHAN (Supervisor) |