MEA technology We design a novel planar microelectrode array (MEA) system that can be used to study neurobiology and neurophysiology. For this purpose, microchannel devices or agaorse hydrogel microstructures have been integrated to design novel MEA systems for high-throughput cell-based biosensor platform.
In Vitro Neural Recording by Microelectrode Arrays, book chapter in Stretchable Bioelectronics for Medical Devices and Systems, Springer. (link) (pdf)
Electrochemical layer-by-layer approach to fabricate mechanically stable platinum black microelectrodes using a mussel-inspired polydopamine adhesive, J Neural Eng. 2015. (Link) (pdf)
Surface-modified microelectrode array with flake nanostructure for neural recording and stimulation, Nanotechnology, 2010. (Link)
Recent trends in microelectrode array technology for in vitro neural interface platform, Biomed Eng Lett. 2014. (Link) (pdf)
Material considerations for in vitro neural interface technology, MRS Bulletin 2012. (pdf) (Link)
In vitro microelectrode array technology and neural recordings, Crit Rev Biomed Eng. 2011. (Link) (pdf)
Brain-on-a-Chip technology We want to build live biological neuronal networks in vitro with ordered structures. We believe that the cultured neuronal network is a good model system to study basic principles of learning and memory at a network level. Micro-contact printing technique is the major method to print biomolecules that can either promote or prohibit neuronal growth. Surface chemical cues and topographical cues are the design rules for the guided neural growth in vitro. We are interested in discovering new physical and chemical guidance cues that lead to neuronal polarization and migration.
Kang et al., Lab Chip 2009
Jang and Nam, J Neural Eng 2012
Effects of ECM protein micropatterns on the migration and differentiation of adult neural stem cells, Scientific Reports, 2015. (Link)
In vitro neurite guidance effects induced by polylysine pin-stripe micropatterns with polylysine background, J Biomed Mater Res A, 2015. (Link) (pdf)
Surface-printed microdot array chips for the quantification of axonal collateral branching of a single neuron in vitro, Lab Chip. 2014. (Link) (pdf)
Geometric effect of cell adhesive polygonal micropatterns on neuritogenesis and axon guidance, J Neural Eng, 2012. (Link) (pdf)
Neuronal micro-culture engineering by microchannel devices of cellular scale dimensions, Biomed. Eng. Lett. 2011. (pdf)
Generation of patterned neuronal networks on cell-repellant poly(oligo(ethylene glycol) methacrylate) films, Chem Asian J, 2010. (Link)
Agarose microwell based neuronal micro-circuit arrays on microelectrode arrays for high throughput drug testing, Lab Chip, 2009. (Link)
Photothermal neural interfaces We use nano-transducers (e.g. gold nanorods) to design photothermal neural interfaces for controlling neural spiking activity. Photothermal conversion was successfully implemented to induce reversible inhibition of spiking activity for more than tens of minutes. Using the novel inhibition effect, the regulation of spiking activity will be possible for hyperactive neural circuits in the future.
Yoo et al., ACS Nano, 2014
Yoo et al., ACS Nano, 2016
Photothermal Inhibition of Neural Activity with Near-Infrared-Sensitive Nanotransducers, ACS Nano. 2014.(Link) (pdf)
[KAIST Breakthroughs] Photothermal neural interface technology: Controlling neural activity using light and heat (link)
Neurons-on-Nanomaterials We study nano-scale neural interfaces by growing primary neurons on various nano-topographical surfaces including carbon nano-tubes, anodised aluminium oxides (AAO), self-assembled silica nanobeads, and vertically grown silicon nanowire. We focused on effects of surface properties on the early neuronal developments such as growth cone formation, axon formation, neuritogensis, etc. So far, we found that nano-scale topographical features affect neurite formation and neuronal maturation.
Kang et al., Angew Chem Int Ed Engl 2010 (left), 2012 (center), 2014 (right)
Axon-First Neuritogenesis on Vertical Nanowires, Nano Lett., Accepted. (Link)
Cytoskeletal Actin Dynamics are Involved in Pitch-Dependent Neurite Outgrowth on Bead Monolayers, Angew Chem Int Ed Engl. 2014. (Link) (pdf)
In vitro developmental acceleration of hippocampal neurons on nanostructures of self-assembled silica beads in filopodium-size ranges, Angew Chem Int Ed Engl, 2012. (Link)
Pitch-dependent acceleration of neurite outgrowth on nanostructured anodized aluminum oxide substrates, Angew Chem Int Ed Engl, 2010. (Link)
Directional neurite growth using carbon nanotube patterned substrates as a biomimetic cue, Nanotechnology, 2010. (Link)
Bio-functionalization of neural interfaces In order to grow neurons in vitro, we design the cell-surface interface using chemical functionalization approaches and surface micro patterning. In addition, we are actively searching for a simple and effective cell-adhesive or -repellent substrates. So far, we have pioneered in using a mussel-inspired polymer coating ('polydopamine') in MEA for covalently linking cell-adhesive biomolecules on metal and insulator.
Kang et al., Biomaterials, 2011
Jang and Nam, Macromol Biosci, 2015
Electrochemically driven, electrode-addressable formation of functionalized polydopamine films for neural interfaces, Angew Chem Int Ed Engl, 2012. (Link) (pdf)
A biofunctionalization scheme for neural interfaces using polydopamine polymer, Biomaterials, 2011. (Link)
Aqueous micro-contact printing of cell-adhesive biomolecules for patterning neuronal cell cultures, BioChip J, 2012. (Link) (pdf)
Neurons on Parafilm: versatile elastic substrates for neuronal cell cultures, J Neurosci Methods, 2012. (Link)
Multichannel neural information analysis We are interested in the relation between network structures and information processing in neuronal network. Microelectrode array and optical imaging are two major platforms to access multiple neurons simultaneously. Recently, we have developed a large-scale optophysiological data processing software, NeuroCa (link), that can efficiently handle a big data problem in neuroinformatics.
Dong et. al, Bioinformatics, 2009
Jang et al., Neurophotonics, 2015
NeuroCa: Integrated framework for systematic analysis of spatio-temporal neuronal activity patterns from large-scale optical recording data, Neurophoton., 2(3), 035003 (2015). (Link) (pdf) (NeuroCa)
Inference of combinatorial neuronal synchrony with Bayesian networks, J Neurosci Methods, 2010. (Link)
Systematic analysis of synchronized oscillatory neuronal networks reveals an enrichment for coupled direct and indirect feedback motifs, Bioinformatics, 2009. (Link)
* Funding sources: KAIST, National Research Foundation, Samsung Science & Technology Foundation
291 Daehak-ro, Yuseong-gu Daejeon, South Korea 34141