Neuroengineering

David T. Eddington

David T. Eddington received a B.S. degree in materials science and engineering from the University of Illinois at Urbana-Champaign, a PhD degree in biomedical engineering from the University of Wisconsin-Madison and did a postdoc in the HST program at Harvard/MIT. He is currently an Associate Professor in the Department of Bioengineering at the University of Illinois at Chicago. His research lab focuses on developing novel solutions to current unmet experimental and clinical needs through applying simple microfabricated devices. These devices leverage beneficial phenomena (e.g. process integration, fast diffusion, or high surface to volume ratio) over multiple scales (e.g. nano, micro, and meso) to effectively leverage the power of scale without becoming overly complex.

Justin Williams

Justin Williams is the Vilas Distinguished Achievement Associate Professor of Biomedical Engineering at the University of Wisconsin-Madison. He obtained his Masters and PhD in Bioengineering from Arizona State University in 2001. He followed with postdoctoral fellowships in Neurosurgery at the University of Wisconsin and in Neuroengineering at the University of Michigan. He joined the faculty at the University of Wisconsin in 2003 as an Assistant Professor. His research program is centered around the development of implantable microtechnology for treating neurological disease and microfluidic platforms for studying basic neurobiology.

This themed issue highlights recent work on tailoring lab on a chip devices for applications in neurobiology. The goal of this series is threefold: (1) to provide an introduction to the field for readers as a point of entry for those new to the subject, (2) to uncover some of the many challenges of applying LOC technologies to neural tissue, and (3) to highlight recent advances in integrating electrical, fluidic, optical and patterning techniques to applications in neuroscience and neurobiology.

Neuroscience has enjoyed a long history that has relied on innovations in microtechnology, starting with the development of the patch-clamp pipette and continuing on to modern day multichannel microelectrode arrays.^1,2 Great strides have also occurred as a result of the adoption of powerful microelectronic devices for amplifying and analyzing the minute electrical signals that originate from individual neurons in the brain. In recent years, microelectronics technology has evolved to the point that scientists can record, amplify and analyze the activity from hundreds or even thousands of neurons simultaneously,^3,4 allowing for real time estimation of brain states that has empowered a whole new field of neural prosthetics and has enabled completely new paradigms in neural plasticity.^2,5 Most of the history of microtechnology in neuroscience has been centered around electronic devices, as deciphering neural electrical activity, ‘cracking the neural code’, has been a major target in the neuroscience field⁴ and electrical stimulation of diseased neural tissue has found a multitude of clinical applications.⁶ It has however lagged behind other biological disciplines in the development and application of microfluidic and other lab on a chip technologies. There are a number of reasons for this disparity, particularly related to the unique features of neural cells and tissues,⁷ and this series of papers helps to highlight some of the challenges inherent in working with the nervous system.

As stated above, one of the primary goals of this themed issue is to provide an introduction for readers interested in the field, and the two included review articles are good starting points. The Roy et al. review (DOI: 10.1039/C2LC41002H) provides a historical perspective on neural guidance assays that will be very useful to LOC readers looking at applying their technology to neurobiology applications. The review is focused on the biological insights that have been achieved using new techniques that attempt to mimic the spatial patterns of proteins that growth cones encounter in vivo. This is an important point to make, as most of the early techniques were born out of necessity to answer biological questions, an approach that will continue to drive the field forward. Park et al. (DOI: 10.1039/C2LC41081H) provide a different perspective with a review on the use of BioMEMS in the study of neurological disease models, electrophysiology and stem cell research. This manuscript also provides a nice overview of microfluidic platforms for neural culture, which should provide a nice starting point for researchers new to the field.

One of the inherent challenges to working with nervous tissue is that many experimental questions demand electrical access to the cells, either for recording or precise stimulation. This presents a challenge of integration of electrical sensors and stimulators with other microfluidic technologies. Several of the manuscripts in this issue have attempted to address this by developing approaches that use microfluidic channels themselves as electrical substrates. Hallfors et al. (DOI: 10.1039/C2LC40954B) use liquid metal electrodes to produce a device that can both record and stimulate individual neurons in microfluidic channels, but is made in a single step process. They accomplish this by filling small channels with liquid metal and show that the properties of these metals provide a non-toxic, stable recording interface. Scott et al. (DOI: 10.1039/C2LC40826K) use a similar approach for fabricating electrodes into a brain slice recording chamber using PDMS microchannels as salt bridges, mimicking the fluid filled micropipettes that are commonly used for local field recordings from the surface of a slice. Ahrar et al. (DOI: 10.1039/C2LC40689F) take a different approach to record from brain slices by integrating their laminar flow chamber with optical methods to utilize voltage sensitive dye recordings of electrical activity. They also show that the same technique can be used to stimulate neurons through optical uncaging of neurotransmitters.

These previous two manuscripts both utilize intact brain tissues in their preparations, which illustrates another challenge of working with the nervous system. While single neurons in culture are interesting to study and can provide answers to many biological questions, neural tissue in vivo is highly organized and the coordinated activity of many neurons leads to many types of emergent network level phenomena. While building neural networks in vitro is a lofty goal, there are many challenges to doing so. In the meantime, techniques such as those in the Scott et al. and Ahrar et al. articles illustrate how microfluidic techniques can be applied to intact brain slices, which is an important area of research in the emerging field of Organs on a Chip. One of the limitations to either growing intact 3D neural tissues or maintaining thick brain slices is the lack of blood supply. Neurons have a high metabolic rate and subsequently have large oxygen and nutrient demands. Achyuta et al. (DOI: 10.1039/C2LC41033H) demonstrate through the use of a microfluidic device with a porous dividing membrane that endothelial cells, neurons and glia can all be cultured in a way that mimics the neurovascular unit. Neurons, glia, and endothelial cells grow at much different rates, making them difficult to culture together using traditional plating methods. Due to the high oxygen demand of neural tissue and the trophic support supplied by glia, this is an important step towards establishing fully functional neural tissue mimics and organ-on-chip models of the nervous system.

Another way to circumvent the problem of maintaining intact tissue is to develop lab on a chip devices that can be used in vivo. There is a considerable body of literature on developing electrical devices to be used in the living brain, but few devices for performing microfluidic functions and a paucity of studies that have tried to do both. Rubehn et al. (DOI: 10.1039/C2LC40874K) address this by combining electrodes, fluid channels and optical waveguides, all in a single process on a flexible substrate. This is particularly relevant to the burgeoning field of optogenetics, which involves activating genetically altered neurons with light and takes advantage of flexible electronics technology to better match the elastic properties of the brain. Kuo et al. (DOI: 10.1039/C2LC40935F) also use a flexible substrate to make implantable devices that are aimed at enhancing tissue integration with recording and stimulating electrodes. This study builds upon previous success in producing neural ingrowth into a ‘Cone Electrode’ which is essentially a pulled glass pipette that is filled with a cocktail of growth factors. While successful, the Cone Electrode requires manual labor for production and is prone to low yields and reproducibility. Kuo et al. takes advantage of the properties of parylene to perform 3D shaping of the electrode substrate through thermoforming to produce a microfabricated device that has the same physical structure as the Cone Electrode.

Even though intact tissues and in vivo approaches have a number of advantages, they can be difficult to maintain and lack the experimental control that is required to answer many biological questions. Due to these limitations there is still considerable interest in developing techniques that can guide and manipulate individual neural cells in culture, and there are a number of studies in this themed issue that look at techniques for doing so. Ahmed et al. (DOI: 10.1039/C2LC41109A) apply the elastic properties of PDMS to develop methods for straining growing neurons and apply new methodologies for analyzing the effect of stretch on vesicle dynamics. This is an important coupling of techniques as axons are incredibly long, thin processes which undergo considerable stretch during development, injury and even daily movement. Accordingly, due to the exceptionally long and narrow confines of axons, active vesicle transport within cells is important and new methods for analyzing this will be important for studying both diseased and healthy neurons. Axonal growth has been traditionally studied with a stripe assay, in which cells predominantly grow along a straight line made through microstamping or other fabrication techniques. It is generally thought that axons follow lines of small dimensions, but little has been explored on the influence of line geometry on growth patterns. To address this, Hart et al. (DOI: 10.1039/C2LC41166K) modify the traditional microstamping technique to produce a simple technique for making tunable line width patterns. They show that micro-line width and periodicity dramatically affect guidance of neurite outgrowth, causing a shift from growth that follows lines to growth that is perpendicular to the line pattern. Finally, Honegger et al. (DOI: 10.1039/C2LC41000A) investigate a unique approach to guiding neurons using electrical fields. While it has been shown previously that neurons will accelerate their growth in certain types of electric fields, this study takes a unique approach by developing a technique to halt axonal growth through high frequency AC electric fields. Honegger et al. illustrate very elegantly that electrical stimulation can be used to halt growth of axons, thus producing an electrokinetic gate that can be used to dynamically control growth cone position. By using this approach to guide a simple neural connection, they illustrate its potential use in making dynamically configurable, directional neural networks in vitro.

We hope the Lab on a Chip readers enjoy this collection of studies and that it stimulates new ideas and participants in the field of Neuroengineering.

References

1. B. Sakmann and E. Neher, Patch clamp techniques for studying ionic channels in excitable membranes, Annu. Rev. Physiol., 1984, 46, 455–472.
2. A. B. Schwartz, et al., Brain-controlled interfaces: movement restoration with neural prosthetics, Neuron, 2006, 52, 205–220.
3. J. A. Wilson and J. C. Williams, Massively parallel signal processing using the graphics processing unit for real-time brain–computer interface feature extraction, Front. Neuroeng., 2009, 2, 11.
4. G. Buzsáki, Large-scale recording of neuronal ensembles, Nat. Neurosci., 2004, 7, 446–451.
5. A. Jackson, J. Mavoori and E. E. Fetz, Long-term motor cortex plasticity induced by an electronic neural implant, Nature, 2006, 444, 56–60.
6. A. L. Benabid, et al., Deep brain stimulation of the subthalamic nucleus for the treatment of Parkinson's disease, Lancet Neurol., 2009, 8, 67–81.
7. T. M. Pearce and J. C. Williams, Microtechnology: meet neurobiology, Lab Chip, 2007, 7, 30–40.

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