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Building and delivering integrative education in brain science across neurobiology, psychology, and engineering


The fields of biology, psychology, and biomedical engineering have generated exciting new advances in the study of neural systems underlying behavior. Individually, these disciplines have individually provided novel insights into brain function and provide opportunities for improved understanding of disorders of the nervous system, healthy and disordered development, and communication. However, the rapid advancement of scientific progress has been limited by the boundaries surrounding the disciplines. Moreover, neuroscientists that are firmly grounded in an array of approaches used by biologists, psychologists, and engineers will best advance new research technologies such as non-invasive functional imaging and neural prosthetics. A training model that is thoroughly interdisciplinary is needed. At Washington University, we have developed such a model: The Cognitive, Computational, and Systems Neuroscience (CCSN) Pathway produces rigorously trained independent investigators that will lead a new generation of scientists who study the brain in truly integrated interdisciplinary investigations. CCSN serves students from the PhD programs in Biomedical Engineering, Psychology, and Neuroscience. The core of CCSN is a two-year curriculum that emphasizes interdisciplinarity, collaboration, and project-based instruction. In the first year, students take courses that bring them up to speed on the core concepts and methods in Cognitive Psychology, Biological Neural Computation, and Neural Systems. In the second year, students participate in two unique courses that have been specially designed as the capstone to the CCSN pathway Advanced CCSN and Project Building in CCSN. Advanced CCSN consists of a series of interdisciplinary case studies in cutting-edge brain science topics. Each topic is presented as a module by a faculty team drawn from the three home programs. Modules include team-based projects and peer review as well as primary source readings and classroom lectures and discussions. Project Building in CCSN is a fully student-driven course. In collaboration with the faculty leader, each student designs an independent interdisciplinary research project. The faculty leader helps them to assemble an interdisciplinary faculty advising team, to whom they present their project multiple times throughout the semester. Faculty advising is complemented by peer advising including written peer review, culminating in a research grant-style project proposal.

Surrounding the core CCSN curriculum is a rich penumbra of activities. These are designed to provide intellectual training and to build a cohort of scientists with the identification and social skills necessary to conduct research in interdisciplinary teams. Formal coursework is provided in Mathematics and Statistics of Experimental Neuroscience, and by an intensive minicourse preceding Advanced CCSN. Immersive Encounters with distinguished visiting scientists provide high-intensity exposure to cutting-edge research. In collaboration with the Saint Louis Science Center, CCSN trains students to communicate with the public and helps them build programs and presentations to teach children and adults about the brain and mind.

Address Goals

CCSN has built on the prodigious departmental strengths in the Departments of Psychology and Biomedical Engineering and in the Program in Neuroscience at Washington University to address the limitations of discipline-based training and to enable our students to thrive in interdisciplinary research of their own design. We do this by providing a unique curriculum in the form of a curriculum “pathway” that is available to PhD students in each of the three disciplines, and is integrated with their core training. The curriculum pathway approach allows us to address two critical shortcomings of discipline-based training.

First, there is a barrier of understanding between behavioral and biological approaches. Rich communities involved in human brain imaging and non-human primate neurophysiology are identifying important relationships between neural activity and behavior. These communities, however, are strongly tied to intellectual traditions of psychology and neurobiology, respectively. These two disciplines speak in different terminologies and develop hypotheses and experiments from very different foundational ideas and classic literatures. By bringing together students with excellent training from their home disciplines and providing them a rigorously taught common body of shared knowledge, we have forged a cohort that speaks a common language.

Second, there is a barrier between experimental and theoretical neuroscientific studies. The emerging discipline of neural engineering seeks to experimentally “reverse engineer” neural systems, as well as to develop detailed mathematical models of these systems. Many engineers, however, lack the fundamental biological and cognitive science background needed to best apply their engineering approaches. Conversely, many experimental scientists address quantitative hypotheses, but are not equipped to formalize these hypotheses into fully developed mathematical models which can rigorously inform the design of novel experiments.

We have trained and continue to train engineers in biological and cognitive brain sciences, and experimentalists in the mathematics of simulation and reverse engineering. Overcoming these barriers has substantively improved our training and the breadth and depth of the science generated by our trainees.