Scholars Award: Explaining Cognition Mechanistically

University Of Missouri-Saint Louis, Saint Louis MO

Investigators

Abstract

General Audience Summary This award supports research to develop an account of how cognitive neuroscientists should develop an explanation of cognition. A central goal of the field is to provide such an explanation, but there is no adequate view as to how this should be done. The researcher proposes an interdisciplinary approach; he will provide a mechanistic explanation of cognition that integrates key elements from philosophy, neuroscience, and psychology. Specifically, he proposes to articulate a comprehensive framework of multilevel neurocognitive mechanisms that perform neural computations. The framework will enable scientists and philosophers to compare, evaluate, and integrate theories from different areas of cognitive science. He will make use of the results of his research in his courses in Philosophy of Mind and Philosophy of Cognitive Science, which are enrolled in by both undergraduate and graduate students in philosophy, psychology, and neuroscience. These courses will be redesigned to facilitate the training of students to think and explain cognitive phenomena in terms of mechanisms spanning multiple levels and drawing from different fields. The PI will describe the results of his research in an accessible way for the general public; he will write a series of blog posts explaining the results of his research in clear, accessible terms on philosophyofbrains.com, and he will also rewrite his public lecture on how cognitive neuroscience explains cognition to include the results of this project. Technical Summary Developing an account of multilevel neurocognitive mechanisms is an important step toward unifying the sciences of the mind. The core of the proposed research consists of three theses. First, levels of organization (organism, nervous system, brain, cortical area, neural network, neuron, etc.) are ontologically on a par, meaning that lower levels are not more fundamental than higher levels, nor vice versa. Second, it is necessary to include the ways in which offline processing increases the representational power of mental models; this thesis contrasts with traditional accounts of mental representation, which focus primarily on mental representations that correlate with the environment in real time. Third, phenomenal consciousness has a functional nature without being (wholly) computational. The account just characterized will build on work in philosophy of science regarding mechanistic explanation, neural computation, and neural representation. The proposed framework will allow researchers in cognitive neuroscience working across different levels of organization to understand how their findings contribute to a unified science of cognition. Understanding the relationship between the mind and the nervous system more deeply has the potential to transform the debate about the place of the mind in the physical world in both science and humanities disciplines.