A Neural Engineering Track Within Bioengineering: Lecture and Lab Courses

2006-2510: A NEURAL ENGINEERING TRACK WITHIN BIOENGINEERING: LECTURE AND LAB COURSES

David Schneeweis, University of Illinois-Chicago J Hetling, University of Illinois-Chicago Patrick Rousche, University of Illinois-Chicago Page 11.77.1

Neural engineering as a distinct specialty within bioengineering

Neural engineering (also called neuroengineering) has recently been identified as an emerging field of specialization within the broader field of biomedical engineering, or bioengineering. (The terms “biomedical engineering” and “bioengineering” are virtually synonymous in most contexts, so “bioengineering” will be used in this article for simplicity.) Neural engineers self-identify as engineers/scientists interested in engineering challenges related to the brain and nervous system. It has been referred to as a “merger of engineering and neuroscience” [1]. Many neural engineers work on clinically oriented challenges, including for example developing sensory prostheses for the deaf and blind or designing systems to stimulate walking motion in the legs of spinal chord injury patients. But other neural engineers are interested primarily in understanding how the brain and nervous system work, or are affected by disease.

Although engineers and scientists have been doing this kind of work for decades, it is only within the last decade or so that neural engineering has become recognized as a named sub- specialty. Indeed it has only been recently that “neural engineering” has existed as a distinct subject track at the annual meeting of the Biomedical Engineering Society. But the field is rapidly growing as witnessed by the establishment of the Journal of Neural Engineering in 2004, and the holding of the 1st International IEEE EMBS Conference on Neural Engineering in 2003. Judging by the number of open faculty positions advertised for neural engineers, it would appear that representation of neural engineers on engineering faculties is increasing concomitantly.

This article will focus primarily on the neural engineering undergraduate curriculum developed in the BioEngineering Department at the authors’ institution, the University of Illinois at Chicago (UIC). Special emphasis will be placed on the laboratory component, since this is in certain ways the most important, yet the most challenging.

Training neural engineers

Many undergraduate bioengineering programs require students to select an area in which to focus their coursework during their latter undergraduate years. This so-called “tracking” is meant to give students some depth within the very broad bioengineering field. It has been argued that depth helps students to compete more successfully for jobs, but exploring a subject area in depth is also a beneficial intellectual exercise in its own right.

It is difficult to determine how many bioengineering programs now include neural engineering among their track options, but a search through the Whitaker Foundation Biomedical Engineering Curriculum Database [2]– a repository for course and curricular information in bioengineering– returns 187 courses having “neural” in the title. (According

to the web site, the database includes information for “more than 100 academic institutions” Page 11.77.2 [2].) In our own BioEngineering Department at UIC, neural engineering is one of several tracks in which undergraduates may focus their studies. Over the past three years approximately 40% of graduating seniors selected neural engineering for their track. Students concentrating in neural engineering begin their track by taking two foundational neuroscience courses offered by the Biological Sciences Department. These courses, BioS 286:Biology of the Brain and BioS 484:Neuroscience I provide much of the core content essential for understanding and working with the nervous system. The core of the neural engineering track consists of three neural engineering courses taught by BioE faculty (Fig. 1). BioE 472:Models of the Nervous System is a quantitative neurobiology course focusing on fairly classical topics in the domains of membrane physiology, signaling in excitable cells, and synaptic communication. BioE:475:Neural Engineering 1 (NE1) is a seminar style course where students explore current issues in neural engineering by critically discussing journal articles. BioE 476:Neural Engineering Lab (NE Lab) is a hands-on experience where students get exposed to current research techniques (See below). NE1 together with NE Lab constitute the capstone courses of the undergraduate neural engineering track.

Elective courses

Undergraduates in BioEngineering at UIC are required to take twelve hours of elective courses. Figure 1 graphically depicts the relationship between the neural engineering track courses and the electives that students select. Electives closer to the track are more commonly selected than courses further from the track. Figure 1 is based on anecdotal evidence, and meant to depict qualitative relationships only.

Although BioEngineering courses constitute the major fraction of elective courses taken by students in the neural engineering track, courses from other departments, and even other colleges, are not unpopular. Organic chemistry and biochemistry classes are extremely popular, in part because they are required or recommended by many medical school programs. Approximately one-third of UIC BioEngineering undergraduates are premed. Page 11.77.3

Figure 1: Neural Engineering course track at UIC A neural engineering laboratory course

The greatest challenge of the neural engineering curriculum is providing hands on training in the modern techniques used by neural engineers. This challenge is formidable for several reasons. First, the intellectual domain of neural engineering spans several traditional curricula (i.e. engineering, neurobiology, materials science), making the scope of the labs very broad. Second, the methods of the neural engineer are often technically challenging and complex, making it difficult for students to gain sufficient competence in the timeframe of typical labs. Finally, the equipment needed for neural engineering labs can be costly and not generally available in an undergraduate learning environment. A search of the Whitaker Foundation’s Biomedical Engineering Curricular Database, with the term “neural laboratory” returns 27 courses from 16 distinct institutions [2]. But a closer examination of the course descriptions reveals that only about a half dozen of the courses include a substantial emphasis on what would be considered cutting edge neural engineering research techniques.

The NE Lab course (BioE 476) at UIC was developed with the following objectives:

! Students should receive practical hands-on training in techniques used in basic and applications oriented neural engineering research ! Students should have the opportunity to interact with the nervous system at different scales (i.e. molecular, cellular, system levels) using in vivo and in vitro techniques ! Students should become aware of the unique challenges in developing hybrid technology ! Students should have opportunities to test hypotheses, and design solutions to posed challenges

The objectives of this laboratory course have been addressed using a format that combines activities in a teaching laboratory with activities in faculty research labs. Initial funding for the teaching lab came from an NSF CCLI grant awarded to establish a facility that would be jointly used by BioEngineering and Biological Science students interested in neuroscience. (Unfortunately the aim of having a lab jointly populated by BioEngineering and Biological Sciences students never materialized.)

The NE Lab course in its current form was offered in spring of 2005 to 4 students. Three neural engineering faculty divided responsibility for running the labs, and one teaching assistant (TA) helped out. Students earned two credit hours for the course, which was scheduled to meet for two hours per week, but often ran over. Assessment was based on performance in lab, and homework.

The NE Lab consists of six distinct lab modules lasting between one and three weeks. Four of these modules (see Table 2) are well developed and described in detail in the following section. The remaining two modules are briefly described in a subsequent section. Page 11.77.4 Table 1. Four Well Developed Lab Modules of the NE Lab Course 1. In vivo neural interfaces: Non-invasive recording of the electroretinogram (3 wks)

2. Bioelectrodes: Fabrication and characterization (3 wks)

3. In vivo neural interfaces: Cortical recording using implanted electrode arrays (2 wks)

4. Modeling of hybrid systems: Simulation of responses of retinal neurons to extracellular electric fields (1 wk)

Lab modules #1-4 of the NE Lab course

Lab modules #1-4 are the most developed of the six modules, and are described in some detail in this section.

Lab #1: In vivo neural interfaces: Non-invasive recording of the electroretinogram (ERG)

The first lab module involves the recording of the light-evoked electroretinogram (ERG) from rats. This activity takes place in the research lab of one of the authors, and is intended to provide students the opportunity to practice fundamental skills common to any experiment involving the study of evoked sensory responses from animals. Skills such as data acquisition, analysis and interpretation are emphasized (Fig. 2). Students assist in handling the animals, and get an appreciation for the special challenges associated with animal experiments. Specific objectives and activities are listed in Table 2.

Table 2. Lab #1: In vivo neural interfaces: ERG Objectives ! Appreciate challenges inherent in in vivo animal experiments (anesthesia, small signals, noise) ! Understand instrumentation required (electrodes, amplifiers, filters) ! Properly acquire ERG signals (set filter cutoffs, gain, sampling rate) ! Perform basic processing of raw data in order to extract useful parameters ! Fit ERG data to a model

Activities Week #1: Background ! Anatomy and physiology of retina ! Origin of ERG Week #2: ERG Recordings from rat ! Handling of animals (anesthesia, electrode placement) ! Hardware instrumentation (amplifiers, filters, flash stimulators) ! Software (data acq., sampling, protocols, data handling) ! Troubleshooting Week #3: Analysis

! Averaging Page 11.77.5 ! Measuring parameters ! Plotting results ! Modeling Raw Data 0.2

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Figure 2: Lab #1 student work: Raw light-flash-evoked ERG records (left) and offline analysis

Lab #2: Bioelectrodes: Fabrication and characterization

A substantial number of neural engineers use metal electrodes to either record neurophysiological signals or stimulate nerve or muscle cells. Understanding the properties of electrodes, and especially the electrode-tissue interface, is thus extremely important for neural engineering students. This lab module focuses on the techniques neural engineers use to characterize electrodes. Students perform impedance spectroscopy and cyclic voltametry using specialized equipment in the research lab of one of the authors (Fig. 3). Students learn to interpret their results in the context of electrical circuit models of the interface. Table 3 lists the specific objectives and activities for this lab module.

Table 3. Lab #2: Bioelectrodes: Fabrication and characterization Objectives ! Understand basic electrochemical phenomena occurring at the electrode/electrolyte interface ! Understand importance of interface reactions for neural engineering devices ! Be able to characterize electrodes using electrode impedance spectroscopy (EIS) and cyclic voltametry (CV) ! Observe how physical properties of electrodes (e.g. materials, geometry, surface coating) affect the EIS and CV

Activities Week #1: Background/Lab ! Background on electrochemistry fundamentals and EIS ! Students measure EIS on different materials and geometries Week #2: Background/Lab Page 11.77.6 ! Background on cyclic voltametry ! Students measure CVs of different materials ! Students deposit iridium oxide on gold and measure CVs Week #3: Modeling/Analysis ! Students explore circuit models of electrode/electrolyte interface using pSpice simulation

Impedance Spectrograms

Charge-Transfer

Charge Transfer Characteristics

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Figure 3: Lab #2 student work: Impedance spectrograms (top left), cyclic voltamograms (bottom left) and analysis of charge transfer

Lab #3: In vivo neural interfaces: Cortical recording using implanted electrode arrays

As a follow up to the electrode characterization activities of the second lab module, students next experience using a microelectrode array to record action potentials (i.e. spikes) from single neurons in rat cortex. Since the surgery associated with microelectrode array implantation is extremely complex, students mostly observe that part of the experiment. Students are, however, expected to understand the instrumentation and equipment, and most importantly, how the data obtained (i.e. spike trains) are analyzed (Fig. 4). This lab is conducted in the research laboratory of one of the authors. Objectives and activities of this lab are listed in Table 4. Page 11.77.7 Table 4. Lab #3: In vivo neural interfaces: Cortical recording Objectives ! Understand hardware and software requirements unique to spike train recording ! Appreciate challenges inherent to cortical implant prosthesis strategies ! Be able to do basic spike train analysis ! Be able to interpret results of basic auditory tuning curve experiments

Activities Week #1: Background ! Review of hardware and software for acquiring action potentials ! Introduction to basic analysis methods Week #2: Background/Lab ! Students observe implantation of a multielectrode array into auditory cortex ! Responses to auditory stimuli obtained Week #3: Modeling/Analysis ! Analysis/interpretation of spike train data

Spike Sorting

Time Stamps Event01 dsp003 dsp007 0 0.012042 0.012042 0.499999 0.512246 0.047514 0.999997 0.634675 0.435118 1.499996 0.886374 0.512246 1.999995 0.965059 0.706519 2.499994 0.998482 0.886784 2.999992 1.055212 0.965304 PSTHs 3.499991 1.202545 1.012531 3.99999 1.241702 1.259274 4.499988 1.512325 1.512325 4.999987 1.577288 1.896079 TONE 5.499986 1.896038 2.250793 5.999985 2.251612 2.618655 6.499983 2.50794 2.715156 6.999982 2.618655 2.848604 7.499981 2.715484 2.943304 7.99998 2.881413 3.012116 8.499978 3.012198 3.018301 8.999977 3.018301 3.511992 9.499976 3.511992 3.663094 9.999974 3.520553 3.80375 10.499973 3.663053 3.987456 Page 11.77.8 Response- Intensity Curves

Tuning Curves

Figure 4: Lab #3 student work: Spike trains were obtained from a multielectrode array, and spikes from individual cells were sorted (top). Spike data was used to generate post- stimulus-time histograms (PSTHs, middle) which could be used for quantifying neural activity.

Lab #4: Modeling of hybrid systems (1 wk)

Neural engineers typically deal with hybrid systems consisting of a biological component (e.g. tissue, organs, cells), and a synthetic component (e.g. metal electrodes, polymer scaffolds). Lab module #4 is a computer-based lab intended to provide students experience with the kind of modeling required for an understanding of how these components interact. Students learn the basics of NEURON, a popular program for modeling the biophysical properties of neurons, and through simulation explore spatial and geometric factors that are important for determining how efficiently neurons are excited by stimulating electrodes. An appreciation for these concepts is essential to designing successful hybrid systems. Because of the limited time available for learning the software, a TA created a friendly “front end” to the software that expedited the simulations. The specific goals and activities of this module are listed in Table 5.

Table 5. Lab #4: Modeling of hybrid systems Objectives ! Develop an appreciation for the importance of developing mathematical models for studying these systems ! Develop an understanding of the role that spatial relationships (between electrode and neuron) have in determining the efficacy of applied electrical stimuli ! Understand the role that various biophysical parameters have in determining cell excitability ! Become proficient in using NEURON at the basic level

Activities Page 11.77.9 ! Learned basics of the modeling software NEURON ! Formed and tested hypotheses about the role of electrode geometry in exciting a model neuron (friendly user interface created by TA) ! Formed and tested hypotheses about the effect of changing cell membrane parameters (passive and active) on cell excitation

A module involving an in vitro neural interface

In addition to the four modules described above, each year two other less well-developed modules have been incorporated as well. One of these is intended to provide students with the experience of interfacing with neural material using an in vitro model system. This lab module was conducted in a teaching lab outfitted with four basic electrophysiological recording rigs. Each rig included an electronics rack with appropriate amplifiers, filters and PC, as well as a low power microscope sufficient for viewing large cells or issue preparations. To date we have tried three different experiment models in this module.

One experiment involved students recording from single neurons in the buccal ganglion of the snail. The objectives of this lab included successfully completing a microdissection of the snail, and successfully recording from single neurons using sharp electrodes. This experiment suffered because successful recording relied heavily on obtaining a high quality dissection. Moreover, the manipulations required to successfully impale neurons without killing them proved challenging to master in a short time.

A second experimental model involved having students make patch (or sharp) electrode recordings from oocytes. By using oocytes the difficult dissection is avoided, but other activities are retained.

A third experiment tested in this module involved the students using pH sensitive electrodes to record the pH near and within retina isolated from goldfish. Objectives for this lab included fabrication and calibration of a pH electrode, and measurements of pH. This lab dealt with an important neural engineering concept not addressed by the others– namely the need to sense and measure local physiological variables.

All three experimental models described have merits and drawbacks. The difficulty for us in making any of them an unqualified success is that none of the three techniques is within the area of core expertise of the neural engineering course instructors.

A module involving the engineering of neural interfaces

The final component of the lab course is a lab module in which students engineer a neural interface. Using techniques of soft lithography, students pattern a glass coverslip with a protein that promotes cell survival, adhesion and outgrowth. By exploring different patterns of their own design, students achieve one of the primary objectives of appreciating the various factors involved in creating a successful interface. The other main objective for this module is that students become knowledgeable in the practical skills (e.g. cell culture, pattern stamping) required for micropatterning so that they can use them in novel situations.

The micropatterning lab module is not described in more detail since it is still being Page 11.77.10 optimized. Summary and future of the NE lab

At this time no formal assessment has been done on the NE Lab course. Of the four objectives for the course, all are certainly being met to some extent. Improvement could certainly be made on the final objective of providing opportunities to test hypotheses, and design solutions to posed challenges.

Anecdotal feedback from the small number of students who took the most current version of the NE Lab was overwhelmingly positive. They perceived the experience as extremely exciting and cutting edge, no doubt in part because much of the time they worked inside research laboratories with faculty and other research staff. Of course these very same reasons made the NE Lab resource intensive. As long as the number of students enrolled is relatively small, the burden on a research lab is tolerable. If enrollment is to increase, however, it will be necessary to identify a different model. One possibility is to develop core facilities that are by design jointly used for teaching and research activities.

Another difficulty with the present model is that some of the lab activities– particularly the ones involving animal experiments– are centered about a single experiment setup. In this case– or in any situation where equipment is limiting– it can be challenging to design activities that engage all students. Finally, experiments containing multiple complex components can easily go wrong. A lab that does not work is often worse than no lab at all.

Discussion

All of the UIC neural engineering courses described in this article are open to both undergraduates and graduate students. Currently we offer two additional courses, Neural Prostheses, and Introduction to Neural Coding, that are designated as graduate level (Fig. 1). Although there is sometimes a disparity in the skill and knowledge levels between the undergraduates and graduate students, this is typically not a problem. In fact many graduate students naturally assume more of a mentorship role and help the undergrads as needed. This is particularly true in the laboratories where the amount of data manipulation can be significant.

Although there is little question that neural engineering will in the long term contribute enormously to our ability to repair, replace and even augment nervous system function– to enormous clinical benefit– it is less clear how, and especially when– neural engineering concepts should be taught to students. There is no arguing that neural engineering belongs in the graduate curriculum, but is it an appropriate concentration or track for undergraduates? At UIC approximately one third of the BioE undergraduates go on to medical school. Approximately a third go on to graduate school, and about a third find jobs in industry. This distribution is fairly representative of the national trend. The two-thirds of the students enrolling in medical and graduate school probably benefit from training in neural engineering, but what about the students going into industry? Unfortunately, the emergent nature of neural engineering means that the job market for neural engineers is rather soft.

There are few companies hiring specifically neural engineers, and those that are typically Page 11.77.11 seek students with higher degrees. Over the next several years it will be important to follow our neural engineering track graduates and determine where their careers lead them. References

1. Bellamkonda, RV, Potter, Steve, & Kipke, D (2005). Neuroengineering: What, Why and How? White paper, Whitaker Foundation Biomedical Engineering Education Summit, 2005. 2. http://www.whitaker.org/academic/database/index.html The Whitaker Foundation Bioengineering Curriculum Database Page 11.77.12