A Series of Computational Neuroscience Labs Increases Comfort with MATLAB

Area of Science:

• Neuroscience
• Computational Biology
• Education

Background:

• Computational simulations offer accessible methods for teaching complex neuroscience concepts to undergraduates.
• Students lacking programming experience may find code-based simulations daunting, hindering their learning.
• Developing computational skills is increasingly crucial for addressing modern neuroscience questions.

Purpose of the Study:

• To assess the impact of computational neuroscience labs on undergraduate students' comfort levels with coding.
• To determine if a series of labs is more effective than single labs in building lasting computational confidence.
• To evaluate the utility of MATLAB in an introductory neuroscience laboratory setting.

Main Methods:

• Implemented a series of computational neuroscience labs in an introductory undergraduate course.
• Labs covered the Hodgkin-Huxley equations, Integrate-and-Fire model, and Hopfield Memory network using MATLAB.
• Administered pre- and post-lab surveys to gauge student comfort with the MATLAB environment.

Main Results:

• Student comfort levels with MATLAB significantly increased after participating in the labs.
• A majority of students transitioned from neutral or uncomfortable to comfortable working in MATLAB.
• A series of labs, rather than individual sessions, was necessary to establish sustained comfort.

Conclusions:

• Computational neuroscience labs effectively enhance undergraduate students' comfort with coding in MATLAB.
• Repeated exposure through a series of labs is key to building lasting confidence in computational skills.
• Increased comfort with coding is a foundational step for students to engage with computational neuroscience research.