Computational Neuroscience
专业介绍
This multidisciplinary concentration spans many fields, including computer science, neuroscience, cognitive science, applied math, and data science.
Students studying Computational Neuroscience will learn to use computational models of the brain and nervous system to study complex biological processes and overcome the limitations of human experimentation. They will also learn to use the brain and nervous system as a model to improve the power and efficiency of artificial systems. Concentrators will think critically about the impact of their work on society and understand how biases can negatively influence computational models.
Student Goals
Students in this concentration will:
- Develop a strong foundation in computational skills (through a lens of coding, math, and theory) in order to develop a computational mindset
- Understand key neuroscience concepts and learn how variation in nervous system structure relates to behavior and cognition
- Construct new (and improve existing) computational algorithms in ways that are inspired by neuroscience
- Connect computational skills with experimental procedure by creating, manipulating, and fitting models of the nervous system to empirical data
- Develop communication skills to work with an explain results to various stakeholders including computational, experimental, and theoretical neuroscientists, data scientists, and the public
- Promote fairness, accountability, and validity in the field of computational neuroscience by developing an understanding of the consequences of data selection and algorithms and their application, including the goals that they achieve, but also the biases that they elicit
- Reflect on the learning of computational neuroscience concepts and ideas and understand how these concepts and ideas can be applied to new areas of specialization within this emerging field