Semester.ly

Johns Hopkins University | EN.580.422

Systems Bioengineering II

4.0

credits

Average Course Rating

(3.89)

A quantitative, model-oriented approach to the study of the nervous system. Topics include functional anatomy of the central and autonomic nervous systems, neurons and networks, learning and memory, structure and function of the auditory and visual systems, motor systems, and neuro-engineering. Prerequisites: EN.580.221 (Molecules and Cells), EN.580.222 (Systems and Controls), EN.580.223 (Models and Simulations), AS.110.302 (Differential Equations), EN.580.421 (Physiological Foundations I). Coreq: EN.580.424 (Physiological Foundations Laboratory II).

Spring 2013

(3.79)

Spring 2014

(3.87)

Spring 2015

(4.0)

Spring 2013

Professor: Eileen Haase, Xiaoqin Wang

(3.79)

The best aspects of this course included the interesting and engaging lectures, the exposure to a wide variety of topics without much repetition, and the opportunity to learn from multiple lecturers. Some students felt the quality between the various lecturers was astounding and that the 50 minute midterm was excessive. One student felt that, for an engineering course, there wasn’t enough math involved. Suggestions included eliminating the final as cumulative, creating homework assignments that mirror the exam questions, and reducing the amount of questions for some of the labs. Prospective students should have some MATLAB experience and be prepared to use it outside of class; also, they should find a reliable partner with whom to complete the labs, otherwise they may find themselves doing all of the work. 35

Spring 2014

Professor: Eileen Haase, Xiaoqin Wang

(3.87)

This course was highlighted by fascinating lectures presented through interesting material. There was a good deal of information covered in one semester, and many students thought the TA did an excel ent job of breaking down the more complex ideas during section. Additional y, the lectures were recorded and available online. The worst aspects of the course were the disorganization between various lecturers, the memorization required for the exams, and the homework was difficult, time consuming, and did not always correspond to the lecture. Some suggestions for improving the course include more continuity between lecturers, homework that corresponds to the exams, and providing slides from lectures as PowerPoint files rather than PDFs. Prospective students should know the course is composed of several instructors, some better than others. This is a difficult but rewarding class.

Spring 2015

Professor: Eileen Haase, Xiaoqin Wang

(4.0)

The best aspects of this course included the helpful TA’s, the interesting and diverse material presented, and the incorporation of neuroscience. Students felt that the course was disorganized due to the number of instructors giving lectures, and that memorization of information was required too often. Homework was tedious, time consuming and unrelated to course work. Suggestions for improvement included having fewer instructors, creating more continuity between lecture topics, and having only one professor write exams and homework. Prospective students should al ocate time to study and start assignments as early as possible. Attending lecture and TA sections is beneficial as well as having a strong understanding of MATLAB coding.