‘Brain Flows: How Network Dynamics Compose the Human Mind,’ an excerpt
In his new book, published today, Michael W. Cole examines how the movement of neuronal activity between neuronal populations shapes free will, intelligence and creativity. In this excerpt from Chapter 1, Cole explores why activity flows could unify efforts to map brain functions and connectivity.
Michael W. Cole's new book delves into the role of neuronal activity flow in shaping key cognitive functions such as free will, intelligence, and creativity. Activity flows refer to the movement of activity between neural populations, which serve as the driving force behind brain function and integration of diverse biophysical processes.
In the first half of the book, Cole focuses on how activity flows generate fundamental aspects of the mind, including learned associations and goal pursuit. In the second half, Cole explores more complex functions such as consciousness, intelligence, and creativity. Despite their critical role in cognitive functionality, activity flows are often underrepresented in recent neuroscience literature, with most studies focusing on mapping functions to brain regions or connectivity between brain regions.
However, activity flows have the potential to unify efforts to map brain functions and connectivity into comprehensive explanations of neural processing. The book begins with the action potential, which is central to neural processing in all organisms, from slugs to humans. The flow of action potentials from sensory inputs to motor outputs forms the basis of brain function.
Cole argues that shifting the focus towards activity flows, rather than traditional activity-amplitude-centric and connectivity-centric views, presents an opportunity to enhance our understanding of brain function. The book provides a framework for using activity flows to gain deeper insights into localized functions, such as the fusiform face area in the human visual system, which is more active when processing faces compared to other visual categories.
By leveraging knowledge of task-evoked activity and connectivity, activity flow modeling can be used to estimate activity flows and generate functions of interest, providing a more comprehensive understanding of neural processing.
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