Integrating Model-Based Approaches into a Neuroscience Curriculum-An Interdisciplinary Neuroscience Course in Engineering.

Contribution: This paper demonstrates curricular modules that incorporate engineering model-based approaches, including concepts related to circuits, systems, modeling, electrophysiology, programming, and software tutorials that enhance learning in undergraduate neuroscience courses. These modules can also be integrated into other neuroscience courses.

Background: Educators in biological and physical sciences urge incorporation of computation and engineering approaches into biology.

Open Source Software Tools for Teaching Neuroscience.

We developed an interdisciplinary course in computational neuroscience to address the need for students trained in both biological/psychological and quantitative sciences. Increasingly, exposure to advanced math and physics is important to stay on the cutting edge of developments and research in neuroscience. Additionally, the ability to work in multidisciplinary teams will continue to be an asset as the field develops.

Distinct current modules shape cellular dynamics in model neurons.

Numerous intrinsic currents are known to collectively shape neuronal membrane potential dynamics, or neuronal signatures. Although how sets of currents shape specific signatures such as spiking characteristics or oscillations has been studied individually, it is less clear how a neuron's suite of currents jointly shape its entire set of signatures. Biophysical conductance-based models of neurons represent a viable tool to address this important question.