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1.  A Coaxial Optrode As Multifunction Write-Read Probe for Optogenetic Studies in Non-Human Primates 
Journal of neuroscience methods  2013;219(1):142-154.
Advances in optogenetics have led to first reports of expression of light-gated ion-channels in non-human primates (NHPs). However, a major obstacle preventing effective application of optogenetics in NHPs and translation to optogenetic therapeutics is the absence of compatible multifunction optoelectronic probes for (1) precision light delivery, (2) low-interference electrophysiology, (3) protein fluorescence detection, and (4) repeated insertion with minimal brain trauma.
New Method
Here we describe a novel brain probe device, a “coaxial optrode”, designed to minimize brain tissue damage while microfabricated to perform simultaneous electrophysiology, light delivery and fluorescence measurements in the NHP brain. The device consists of a tapered, gold-coated optical fiber inserted in a polyamide tube. A portion of the gold coating is exposed at the fiber tip to allow electrophysiological recordings in addition to light delivery/collection at the tip.
Coaxial optrode performance was demonstrated by experiments in rodents and NHPs, and characterized by computational models. The device mapped opsin expression in the brain and achieved precisely targeted optical stimulation and electrophysiology with minimal cortical damage.
Comparison with Existing Methods
Overall, combined electrical, optical and mechanical features of the coaxial optrode allowed a performance for NHP studies which was not possible with previously existing devices.
Coaxial optrode is currently being used in two NHP laboratories as a major tool to study brain function by inducing light modulated neural activity and behavior. By virtue of its design, the coaxial optrode can be extended for use as a chronic implant and multisite neural stimulation/recording.
PMCID: PMC3789534  PMID: 23867081
optogenetics; optoelectronic devices; non-human primates; fluorescence detection; tissue heating; light propagation in tissue
2.  In vivo optical modulation of neural signals using monolithically integrated two-dimensional neural probe arrays 
Scientific Reports  2015;5:15466.
Integration of stimulation modalities (e.g. electrical, optical, and chemical) on a large array of neural probes can enable an investigation of important underlying mechanisms of brain disorders that is not possible through neural recordings alone. Furthermore, it is important to achieve this integration of multiple functionalities in a compact structure to utilize a large number of the mouse models. Here we present a successful optical modulation of in vivo neural signals of a transgenic mouse through our compact 2D MEMS neural array (optrodes). Using a novel fabrication method that embeds a lower cladding layer in a silicon substrate, we achieved a thin silicon 2D optrode array that is capable of delivering light to multiple sites using SU-8 as a waveguide core. Without additional modification to the microelectrodes, the measured impedance of the multiple microelectrodes was below 1 MΩ at 1 kHz. In addition, with a low background noise level (±25 μV), neural spikes from different individual neurons were recorded on each microelectrode. Lastly, we successfully used our optrodes to modulate the neural activity of a transgenic mouse through optical stimulation. These results demonstrate the functionality of the 2D optrode array and its potential as a next-generation tool for optogenetic applications.
PMCID: PMC4616027  PMID: 26494437
3.  High fidelity optogenetic control of individual prefrontal cortical pyramidal neurons in vivo  
F1000Research  2012;1:7.
Precise spatial and temporal manipulation of neural activity in specific genetically defined cell populations is now possible with the advent of optogenetics. The emerging field of optogenetics consists of a set of naturally-occurring and engineered light-sensitive membrane proteins that are able to activate (e.g. channelrhodopsin-2, ChR2) or silence (e.g. halorhodopsin, NpHR) neural activity. Here we demonstrate the technique and the feasibility of using novel adeno-associated viral (AAV) tools to activate (AAV-CaMKllα-ChR2-eYFP) or silence (AAV-CaMKllα-eNpHR3.0-eYFP) neural activity of rat prefrontal cortical prelimbic (PL) pyramidal neurons  in vivo.  In vivo single unit extracellular recording of ChR2-transduced pyramidal neurons showed that delivery of brief (10 ms) blue (473 nm) light-pulse trains up to 20 Hz via a custom fiber optic-coupled recording electrode (optrode) induced spiking with high fidelity at 20 Hz for the duration of recording (up to two hours in some cases). To silence spontaneously active neurons, we transduced them with the NpHR construct and administered continuous green (532 nm) light to completely inhibit action potential activity for up to 10 seconds with 100% fidelity in most cases. These versatile photosensitive tools, combined with optrode recording methods, provide experimental control over activity of genetically defined neurons and can be used to investigate the functional relationship between neural activity and complex cognitive behavior.
PMCID: PMC3894804  PMID: 24555016
4.  A 3D glass optrode array for optical neural stimulation 
Biomedical Optics Express  2012;3(12):3087-3104.
This paper presents optical characterization of a first-generation SiO2 optrode array as a set of penetrating waveguides for both optogenetic and infrared (IR) neural stimulation. Fused silica and quartz discs of 3-mm thickness and 50-mm diameter were micromachined to yield 10 × 10 arrays of up to 2-mm long optrodes at a 400-μm pitch; array size, length and spacing may be varied along with the width and tip angle. Light delivery and loss mechanisms through these glass optrodes were characterized. Light in-coupling techniques include using optical fibers and collimated beams. Losses involve Fresnel reflection, coupling, scattering and total internal reflection in the tips. Transmission efficiency was constant in the visible and near-IR range, with the highest value measured as 71% using a 50-μm multi-mode in-coupling fiber butt-coupled to the backplane of the device. Transmittance and output beam profiles of optrodes with different geometries was investigated. Length and tip angle do not affect the amount of output power, but optrode width and tip angle influence the beam size and divergence independently. Finally, array insertion in tissue was performed to demonstrate its robustness for optical access in deep tissue.
PMCID: PMC3521295  PMID: 23243561
(170.3890) Medical optics instrumentation; (220.4610) Optical fabrication; (230.7380) Waveguides, channeled; (170.3660) Light propagation in tissues
5.  An integrated multi-electrode-optrode array for in vitro optogenetics 
Scientific Reports  2016;6:20353.
Modulation of a group of cells or tissue needs to be very precise in order to exercise effective control over the cell population under investigation. Optogenetic tools have already demonstrated to be of great value in the study of neuronal circuits and in neuromodulation. Ideally, they should permit very accurate resolution, preferably down to the single cell level. Further, to address a spatially distributed sample, independently addressable multiple optical outputs should be present. In current techniques, at least one of these requirements is not fulfilled. In addition to this, it is interesting to directly monitor feedback of the modulation by electrical registration of the activity of the stimulated cells. Here, we present the fabrication and characterization of a fully integrated silicon-based multi-electrode-optrode array (MEOA) for in vitro optogenetics. We demonstrate that this device allows for artifact-free electrical recording. Moreover, the MEOA was used to reliably elicit spiking activity from ChR2-transduced neurons. Thanks to the single cell resolution stimulation capability, we could determine spatial and temporal activation patterns and spike latencies of the neuronal network. This integrated approach to multi-site combined optical stimulation and electrical recording significantly advances today’s tool set for neuroscientists in their search to unravel neuronal network dynamics.
PMCID: PMC4735812  PMID: 26832455
6.  25th Annual Computational Neuroscience Meeting: CNS-2016 
Sharpee, Tatyana O. | Destexhe, Alain | Kawato, Mitsuo | Sekulić, Vladislav | Skinner, Frances K. | Wójcik, Daniel K. | Chintaluri, Chaitanya | Cserpán, Dorottya | Somogyvári, Zoltán | Kim, Jae Kyoung | Kilpatrick, Zachary P. | Bennett, Matthew R. | Josić, Kresimir | Elices, Irene | Arroyo, David | Levi, Rafael | Rodriguez, Francisco B. | Varona, Pablo | Hwang, Eunjin | Kim, Bowon | Han, Hio-Been | Kim, Tae | McKenna, James T. | Brown, Ritchie E. | McCarley, Robert W. | Choi, Jee Hyun | Rankin, James | Popp, Pamela Osborn | Rinzel, John | Tabas, Alejandro | Rupp, André | Balaguer-Ballester, Emili | Maturana, Matias I. | Grayden, David B. | Cloherty, Shaun L. | Kameneva, Tatiana | Ibbotson, Michael R. | Meffin, Hamish | Koren, Veronika | Lochmann, Timm | Dragoi, Valentin | Obermayer, Klaus | Psarrou, Maria | Schilstra, Maria | Davey, Neil | Torben-Nielsen, Benjamin | Steuber, Volker | Ju, Huiwen | Yu, Jiao | Hines, Michael L. | Chen, Liang | Yu, Yuguo | Kim, Jimin | Leahy, Will | Shlizerman, Eli | Birgiolas, Justas | Gerkin, Richard C. | Crook, Sharon M. | Viriyopase, Atthaphon | Memmesheimer, Raoul-Martin | Gielen, Stan | Dabaghian, Yuri | DeVito, Justin | Perotti, Luca | Kim, Anmo J. | Fenk, Lisa M. | Cheng, Cheng | Maimon, Gaby | Zhao, Chang | Widmer, Yves | Sprecher, Simon | Senn, Walter | Halnes, Geir | Mäki-Marttunen, Tuomo | Keller, Daniel | Pettersen, Klas H. | Andreassen, Ole A. | Einevoll, Gaute T. | Yamada, Yasunori | Steyn-Ross, Moira L. | Alistair Steyn-Ross, D. | Mejias, Jorge F. | Murray, John D. | Kennedy, Henry | Wang, Xiao-Jing | Kruscha, Alexandra | Grewe, Jan | Benda, Jan | Lindner, Benjamin | Badel, Laurent | Ohta, Kazumi | Tsuchimoto, Yoshiko | Kazama, Hokto | Kahng, B. | Tam, Nicoladie D. | Pollonini, Luca | Zouridakis, George | Soh, Jaehyun | Kim, DaeEun | Yoo, Minsu | Palmer, S. E. | Culmone, Viviana | Bojak, Ingo | Ferrario, Andrea | Merrison-Hort, Robert | Borisyuk, Roman | Kim, Chang Sub | Tezuka, Taro | Joo, Pangyu | Rho, Young-Ah | Burton, Shawn D. | Bard Ermentrout, G. | Jeong, Jaeseung | Urban, Nathaniel N. | Marsalek, Petr | Kim, Hoon-Hee | Moon, Seok-hyun | Lee, Do-won | Lee, Sung-beom | Lee, Ji-yong | Molkov, Yaroslav I. | Hamade, Khaldoun | Teka, Wondimu | Barnett, William H. | Kim, Taegyo | Markin, Sergey | Rybak, Ilya A. | Forro, Csaba | Dermutz, Harald | Demkó, László | Vörös, János | Babichev, Andrey | Huang, Haiping | Verduzco-Flores, Sergio | Dos Santos, Filipa | Andras, Peter | Metzner, Christoph | Schweikard, Achim | Zurowski, Bartosz | Roach, James P. | Sander, Leonard M. | Zochowski, Michal R. | Skilling, Quinton M. | Ognjanovski, Nicolette | Aton, Sara J. | Zochowski, Michal | Wang, Sheng-Jun | Ouyang, Guang | Guang, Jing | Zhang, Mingsha | Michael Wong, K. Y. | Zhou, Changsong | Robinson, Peter A. | Sanz-Leon, Paula | Drysdale, Peter M. | Fung, Felix | Abeysuriya, Romesh G. | Rennie, Chris J. | Zhao, Xuelong | Choe, Yoonsuck | Yang, Huei-Fang | Mi, Yuanyuan | Lin, Xiaohan | Wu, Si | Liedtke, Joscha | Schottdorf, Manuel | Wolf, Fred | Yamamura, Yoriko | Wickens, Jeffery R. | Rumbell, Timothy | Ramsey, Julia | Reyes, Amy | Draguljić, Danel | Hof, Patrick R. | Luebke, Jennifer | Weaver, Christina M. | He, Hu | Yang, Xu | Ma, Hailin | Xu, Zhiheng | Wang, Yuzhe | Baek, Kwangyeol | Morris, Laurel S. | Kundu, Prantik | Voon, Valerie | Agnes, Everton J. | Vogels, Tim P. | Podlaski, William F. | Giese, Martin | Kuravi, Pradeep | Vogels, Rufin | Seeholzer, Alexander | Podlaski, William | Ranjan, Rajnish | Vogels, Tim | Torres, Joaquin J. | Baroni, Fabiano | Latorre, Roberto | Gips, Bart | Lowet, Eric | Roberts, Mark J. | de Weerd, Peter | Jensen, Ole | van der Eerden, Jan | Goodarzinick, Abdorreza | Niry, Mohammad D. | Valizadeh, Alireza | Pariz, Aref | Parsi, Shervin S. | Warburton, Julia M. | Marucci, Lucia | Tamagnini, Francesco | Brown, Jon | Tsaneva-Atanasova, Krasimira | Kleberg, Florence I. | Triesch, Jochen | Moezzi, Bahar | Iannella, Nicolangelo | Schaworonkow, Natalie | Plogmacher, Lukas | Goldsworthy, Mitchell R. | Hordacre, Brenton | McDonnell, Mark D. | Ridding, Michael C. | Zapotocky, Martin | Smit, Daniel | Fouquet, Coralie | Trembleau, Alain | Dasgupta, Sakyasingha | Nishikawa, Isao | Aihara, Kazuyuki | Toyoizumi, Taro | Robb, Daniel T. | Mellen, Nick | Toporikova, Natalia | Tang, Rongxiang | Tang, Yi-Yuan | Liang, Guangsheng | Kiser, Seth A. | Howard, James H. | Goncharenko, Julia | Voronenko, Sergej O. | Ahamed, Tosif | Stephens, Greg | Yger, Pierre | Lefebvre, Baptiste | Spampinato, Giulia Lia Beatrice | Esposito, Elric | et Olivier Marre, Marcel Stimberg | Choi, Hansol | Song, Min-Ho | Chung, SueYeon | Lee, Dan D. | Sompolinsky, Haim | Phillips, Ryan S. | Smith, Jeffrey | Chatzikalymniou, Alexandra Pierri | Ferguson, Katie | Alex Cayco Gajic, N. | Clopath, Claudia | Angus Silver, R. | Gleeson, Padraig | Marin, Boris | Sadeh, Sadra | Quintana, Adrian | Cantarelli, Matteo | Dura-Bernal, Salvador | Lytton, William W. | Davison, Andrew | Li, Luozheng | Zhang, Wenhao | Wang, Dahui | Song, Youngjo | Park, Sol | Choi, Ilhwan | Shin, Hee-sup | Choi, Hannah | Pasupathy, Anitha | Shea-Brown, Eric | Huh, Dongsung | Sejnowski, Terrence J. | Vogt, Simon M. | Kumar, Arvind | Schmidt, Robert | Van Wert, Stephen | Schiff, Steven J. | Veale, Richard | Scheutz, Matthias | Lee, Sang Wan | Gallinaro, Júlia | Rotter, Stefan | Rubchinsky, Leonid L. | Cheung, Chung Ching | Ratnadurai-Giridharan, Shivakeshavan | Shomali, Safura Rashid | Ahmadabadi, Majid Nili | Shimazaki, Hideaki | Nader Rasuli, S. | Zhao, Xiaochen | Rasch, Malte J. | Wilting, Jens | Priesemann, Viola | Levina, Anna | Rudelt, Lucas | Lizier, Joseph T. | Spinney, Richard E. | Rubinov, Mikail | Wibral, Michael | Bak, Ji Hyun | Pillow, Jonathan | Zaho, Yuan | Park, Il Memming | Kang, Jiyoung | Park, Hae-Jeong | Jang, Jaeson | Paik, Se-Bum | Choi, Woochul | Lee, Changju | Song, Min | Lee, Hyeonsu | Park, Youngjin | Yilmaz, Ergin | Baysal, Veli | Ozer, Mahmut | Saska, Daniel | Nowotny, Thomas | Chan, Ho Ka | Diamond, Alan | Herrmann, Christoph S. | Murray, Micah M. | Ionta, Silvio | Hutt, Axel | Lefebvre, Jérémie | Weidel, Philipp | Duarte, Renato | Morrison, Abigail | Lee, Jung H. | Iyer, Ramakrishnan | Mihalas, Stefan | Koch, Christof | Petrovici, Mihai A. | Leng, Luziwei | Breitwieser, Oliver | Stöckel, David | Bytschok, Ilja | Martel, Roman | Bill, Johannes | Schemmel, Johannes | Meier, Karlheinz | Esler, Timothy B. | Burkitt, Anthony N. | Kerr, Robert R. | Tahayori, Bahman | Nolte, Max | Reimann, Michael W. | Muller, Eilif | Markram, Henry | Parziale, Antonio | Senatore, Rosa | Marcelli, Angelo | Skiker, K. | Maouene, M. | Neymotin, Samuel A. | Seidenstein, Alexandra | Lakatos, Peter | Sanger, Terence D. | Menzies, Rosemary J. | McLauchlan, Campbell | van Albada, Sacha J. | Kedziora, David J. | Neymotin, Samuel | Kerr, Cliff C. | Suter, Benjamin A. | Shepherd, Gordon M. G. | Ryu, Juhyoung | Lee, Sang-Hun | Lee, Joonwon | Lee, Hyang Jung | Lim, Daeseob | Wang, Jisung | Lee, Heonsoo | Jung, Nam | Anh Quang, Le | Maeng, Seung Eun | Lee, Tae Ho | Lee, Jae Woo | Park, Chang-hyun | Ahn, Sora | Moon, Jangsup | Choi, Yun Seo | Kim, Juhee | Jun, Sang Beom | Lee, Seungjun | Lee, Hyang Woon | Jo, Sumin | Jun, Eunji | Yu, Suin | Goetze, Felix | Lai, Pik-Yin | Kim, Seonghyun | Kwag, Jeehyun | Jang, Hyun Jae | Filipović, Marko | Reig, Ramon | Aertsen, Ad | Silberberg, Gilad | Bachmann, Claudia | Buttler, Simone | Jacobs, Heidi | Dillen, Kim | Fink, Gereon R. | Kukolja, Juraj | Kepple, Daniel | Giaffar, Hamza | Rinberg, Dima | Shea, Steven | Koulakov, Alex | Bahuguna, Jyotika | Tetzlaff, Tom | Kotaleski, Jeanette Hellgren | Kunze, Tim | Peterson, Andre | Knösche, Thomas | Kim, Minjung | Kim, Hojeong | Park, Ji Sung | Yeon, Ji Won | Kim, Sung-Phil | Kang, Jae-Hwan | Lee, Chungho | Spiegler, Andreas | Petkoski, Spase | Palva, Matias J. | Jirsa, Viktor K. | Saggio, Maria L. | Siep, Silvan F. | Stacey, William C. | Bernar, Christophe | Choung, Oh-hyeon | Jeong, Yong | Lee, Yong-il | Kim, Su Hyun | Jeong, Mir | Lee, Jeungmin | Kwon, Jaehyung | Kralik, Jerald D. | Jahng, Jaehwan | Hwang, Dong-Uk | Kwon, Jae-Hyung | Park, Sang-Min | Kim, Seongkyun | Kim, Hyoungkyu | Kim, Pyeong Soo | Yoon, Sangsup | Lim, Sewoong | Park, Choongseok | Miller, Thomas | Clements, Katie | Ahn, Sungwoo | Ji, Eoon Hye | Issa, Fadi A. | Baek, JeongHun | Oba, Shigeyuki | Yoshimoto, Junichiro | Doya, Kenji | Ishii, Shin | Mosqueiro, Thiago S. | Strube-Bloss, Martin F. | Smith, Brian | Huerta, Ramon | Hadrava, Michal | Hlinka, Jaroslav | Bos, Hannah | Helias, Moritz | Welzig, Charles M. | Harper, Zachary J. | Kim, Won Sup | Shin, In-Seob | Baek, Hyeon-Man | Han, Seung Kee | Richter, René | Vitay, Julien | Beuth, Frederick | Hamker, Fred H. | Toppin, Kelly | Guo, Yixin | Graham, Bruce P. | Kale, Penelope J. | Gollo, Leonardo L. | Stern, Merav | Abbott, L. F. | Fedorov, Leonid A. | Giese, Martin A. | Ardestani, Mohammad Hovaidi | Faraji, Mohammad Javad | Preuschoff, Kerstin | Gerstner, Wulfram | van Gendt, Margriet J. | Briaire, Jeroen J. | Kalkman, Randy K. | Frijns, Johan H. M. | Lee, Won Hee | Frangou, Sophia | Fulcher, Ben D. | Tran, Patricia H. P. | Fornito, Alex | Gliske, Stephen V. | Lim, Eugene | Holman, Katherine A. | Fink, Christian G. | Kim, Jinseop S. | Mu, Shang | Briggman, Kevin L. | Sebastian Seung, H. | Wegener, Detlef | Bohnenkamp, Lisa | Ernst, Udo A. | Devor, Anna | Dale, Anders M. | Lines, Glenn T. | Edwards, Andy | Tveito, Aslak | Hagen, Espen | Senk, Johanna | Diesmann, Markus | Schmidt, Maximilian | Bakker, Rembrandt | Shen, Kelly | Bezgin, Gleb | Hilgetag, Claus-Christian | van Albada, Sacha Jennifer | Sun, Haoqi | Sourina, Olga | Huang, Guang-Bin | Klanner, Felix | Denk, Cornelia | Glomb, Katharina | Ponce-Alvarez, Adrián | Gilson, Matthieu | Ritter, Petra | Deco, Gustavo | Witek, Maria A. G. | Clarke, Eric F. | Hansen, Mads | Wallentin, Mikkel | Kringelbach, Morten L. | Vuust, Peter | Klingbeil, Guido | De Schutter, Erik | Chen, Weiliang | Zang, Yunliang | Hong, Sungho | Takashima, Akira | Zamora, Criseida | Gallimore, Andrew R. | Goldschmidt, Dennis | Manoonpong, Poramate | Karoly, Philippa J. | Freestone, Dean R. | Soundry, Daniel | Kuhlmann, Levin | Paninski, Liam | Cook, Mark | Lee, Jaejin | Fishman, Yonatan I. | Cohen, Yale E. | Roberts, James A. | Cocchi, Luca | Sweeney, Yann | Lee, Soohyun | Jung, Woo-Sung | Kim, Youngsoo | Jung, Younginha | Song, Yoon-Kyu | Chavane, Frédéric | Soman, Karthik | Muralidharan, Vignesh | Srinivasa Chakravarthy, V. | Shivkumar, Sabyasachi | Mandali, Alekhya | Pragathi Priyadharsini, B. | Mehta, Hima | Davey, Catherine E. | Brinkman, Braden A. W. | Kekona, Tyler | Rieke, Fred | Buice, Michael | De Pittà, Maurizio | Berry, Hugues | Brunel, Nicolas | Breakspear, Michael | Marsat, Gary | Drew, Jordan | Chapman, Phillip D. | Daly, Kevin C. | Bradle, Samual P. | Seo, Sat Byul | Su, Jianzhong | Kavalali, Ege T. | Blackwell, Justin | Shiau, LieJune | Buhry, Laure | Basnayake, Kanishka | Lee, Sue-Hyun | Levy, Brandon A. | Baker, Chris I. | Leleu, Timothée | Philips, Ryan T. | Chhabria, Karishma
BMC Neuroscience  2016;17(Suppl 1):54.
Table of contents
A1 Functional advantages of cell-type heterogeneity in neural circuits
Tatyana O. Sharpee
A2 Mesoscopic modeling of propagating waves in visual cortex
Alain Destexhe
A3 Dynamics and biomarkers of mental disorders
Mitsuo Kawato
F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons
Vladislav Sekulić, Frances K. Skinner
F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains
Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári
F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.
Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić
O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators
Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona
O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain
Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi
O3 Modeling auditory stream segregation, build-up and bistability
James Rankin, Pamela Osborn Popp, John Rinzel
O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields
Alejandro Tabas, André Rupp, Emili Balaguer-Ballester
O5 A simple model of retinal response to multi-electrode stimulation
Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin
O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task
Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer
O7 Input-location dependent gain modulation in cerebellar nucleus neurons
Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker Steuber
O8 Analytic solution of cable energy function for cortical axons and dendrites
Huiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo Yu
O9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal network
Jimin Kim, Will Leahy, Eli Shlizerman
O10 Is the model any good? Objective criteria for computational neuroscience model selection
Justas Birgiolas, Richard C. Gerkin, Sharon M. Crook
O11 Cooperation and competition of gamma oscillation mechanisms
Atthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan Gielen
O12 A discrete structure of the brain waves
Yuri Dabaghian, Justin DeVito, Luca Perotti
O13 Direction-specific silencing of the Drosophila gaze stabilization system
Anmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby Maimon
O14 What does the fruit fly think about values? A model of olfactory associative learning
Chang Zhao, Yves Widmer, Simon Sprecher,Walter Senn
O15 Effects of ionic diffusion on power spectra of local field potentials (LFP)
Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen, Gaute T. Einevoll
O16 Large-scale cortical models towards understanding relationship between brain structure abnormalities and cognitive deficits
Yasunori Yamada
O17 Spatial coarse-graining the brain: origin of minicolumns
Moira L. Steyn-Ross, D. Alistair Steyn-Ross
O18 Modeling large-scale cortical networks with laminar structure
Jorge F. Mejias, John D. Murray, Henry Kennedy, Xiao-Jing Wang
O19 Information filtering by partial synchronous spikes in a neural population
Alexandra Kruscha, Jan Grewe, Jan Benda, Benjamin Lindner
O20 Decoding context-dependent olfactory valence in Drosophila
Laurent Badel, Kazumi Ohta, Yoshiko Tsuchimoto, Hokto Kazama
P1 Neural network as a scale-free network: the role of a hub
B. Kahng
P2 Hemodynamic responses to emotions and decisions using near-infrared spectroscopy optical imaging
Nicoladie D. Tam
P3 Phase space analysis of hemodynamic responses to intentional movement directions using functional near-infrared spectroscopy (fNIRS) optical imaging technique
Nicoladie D.Tam, Luca Pollonini, George Zouridakis
P4 Modeling jamming avoidance of weakly electric fish
Jaehyun Soh, DaeEun Kim
P5 Synergy and redundancy of retinal ganglion cells in prediction
Minsu Yoo, S. E. Palmer
P6 A neural field model with a third dimension representing cortical depth
Viviana Culmone, Ingo Bojak
P7 Network analysis of a probabilistic connectivity model of the Xenopus tadpole spinal cord
Andrea Ferrario, Robert Merrison-Hort, Roman Borisyuk
P8 The recognition dynamics in the brain
Chang Sub Kim
P9 Multivariate spike train analysis using a positive definite kernel
Taro Tezuka
P10 Synchronization of burst periods may govern slow brain dynamics during general anesthesia
Pangyu Joo
P11 The ionic basis of heterogeneity affects stochastic synchrony
Young-Ah Rho, Shawn D. Burton, G. Bard Ermentrout, Jaeseung Jeong, Nathaniel N. Urban
P12 Circular statistics of noise in spike trains with a periodic component
Petr Marsalek
P14 Representations of directions in EEG-BCI using Gaussian readouts
Hoon-Hee Kim, Seok-hyun Moon, Do-won Lee, Sung-beom Lee, Ji-yong Lee, Jaeseung Jeong
P15 Action selection and reinforcement learning in basal ganglia during reaching movements
Yaroslav I. Molkov, Khaldoun Hamade, Wondimu Teka, William H. Barnett, Taegyo Kim, Sergey Markin, Ilya A. Rybak
P17 Axon guidance: modeling axonal growth in T-Junction assay
Csaba Forro, Harald Dermutz, László Demkó, János Vörös
P19 Transient cell assembly networks encode persistent spatial memories
Yuri Dabaghian, Andrey Babichev
P20 Theory of population coupling and applications to describe high order correlations in large populations of interacting neurons
Haiping Huang
P21 Design of biologically-realistic simulations for motor control
Sergio Verduzco-Flores
P22 Towards understanding the functional impact of the behavioural variability of neurons
Filipa Dos Santos, Peter Andras
P23 Different oscillatory dynamics underlying gamma entrainment deficits in schizophrenia
Christoph Metzner, Achim Schweikard, Bartosz Zurowski
P24 Memory recall and spike frequency adaptation
James P. Roach, Leonard M. Sander, Michal R. Zochowski
P25 Stability of neural networks and memory consolidation preferentially occur near criticality
Quinton M. Skilling, Nicolette Ognjanovski, Sara J. Aton, Michal Zochowski
P26 Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems
Sheng-Jun Wang, Guang Ouyang, Jing Guang, Mingsha Zhang, K. Y. Michael Wong, Changsong Zhou
P27 Neurofield: a C++ library for fast simulation of 2D neural field models
Peter A. Robinson, Paula Sanz-Leon, Peter M. Drysdale, Felix Fung, Romesh G. Abeysuriya, Chris J. Rennie, Xuelong Zhao
P28 Action-based grounding: Beyond encoding/decoding in neural code
Yoonsuck Choe, Huei-Fang Yang
P29 Neural computation in a dynamical system with multiple time scales
Yuanyuan Mi, Xiaohan Lin, Si Wu
P30 Maximum entropy models for 3D layouts of orientation selectivity
Joscha Liedtke, Manuel Schottdorf, Fred Wolf
P31 A behavioral assay for probing computations underlying curiosity in rodents
Yoriko Yamamura, Jeffery R. Wickens
P32 Using statistical sampling to balance error function contributions to optimization of conductance-based models
Timothy Rumbell, Julia Ramsey, Amy Reyes, Danel Draguljić, Patrick R. Hof, Jennifer Luebke, Christina M. Weaver
P33 Exploration and implementation of a self-growing and self-organizing neuron network building algorithm
Hu He, Xu Yang, Hailin Ma, Zhiheng Xu, Yuzhe Wang
P34 Disrupted resting state brain network in obese subjects: a data-driven graph theory analysis
Kwangyeol Baek, Laurel S. Morris, Prantik Kundu, Valerie Voon
P35 Dynamics of cooperative excitatory and inhibitory plasticity
Everton J. Agnes, Tim P. Vogels
P36 Frequency-dependent oscillatory signal gating in feed-forward networks of integrate-and-fire neurons
William F. Podlaski, Tim P. Vogels
P37 Phenomenological neural model for adaptation of neurons in area IT
Martin Giese, Pradeep Kuravi, Rufin Vogels
P38 ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experiment
Alexander Seeholzer, William Podlaski, Rajnish Ranjan, Tim Vogels
P39 Temporal input discrimination from the interaction between dynamic synapses and neural subthreshold oscillations
Joaquin J. Torres, Fabiano Baroni, Roberto Latorre, Pablo Varona
P40 Different roles for transient and sustained activity during active visual processing
Bart Gips, Eric Lowet, Mark J. Roberts, Peter de Weerd, Ole Jensen, Jan van der Eerden
P41 Scale-free functional networks of 2D Ising model are highly robust against structural defects: neuroscience implications
Abdorreza Goodarzinick, Mohammad D. Niry, Alireza Valizadeh
P42 High frequency neuron can facilitate propagation of signal in neural networks
Aref Pariz, Shervin S. Parsi, Alireza Valizadeh
P43 Investigating the effect of Alzheimer’s disease related amyloidopathy on gamma oscillations in the CA1 region of the hippocampus
Julia M. Warburton, Lucia Marucci, Francesco Tamagnini, Jon Brown, Krasimira Tsaneva-Atanasova
P44 Long-tailed distributions of inhibitory and excitatory weights in a balanced network with eSTDP and iSTDP
Florence I. Kleberg, Jochen Triesch
P45 Simulation of EMG recording from hand muscle due to TMS of motor cortex
Bahar Moezzi, Nicolangelo Iannella, Natalie Schaworonkow, Lukas Plogmacher, Mitchell R. Goldsworthy, Brenton Hordacre, Mark D. McDonnell, Michael C. Ridding, Jochen Triesch
P46 Structure and dynamics of axon network formed in primary cell culture
Martin Zapotocky, Daniel Smit, Coralie Fouquet, Alain Trembleau
P47 Efficient signal processing and sampling in random networks that generate variability
Sakyasingha Dasgupta, Isao Nishikawa, Kazuyuki Aihara, Taro Toyoizumi
P48 Modeling the effect of riluzole on bursting in respiratory neural networks
Daniel T. Robb, Nick Mellen, Natalia Toporikova
P49 Mapping relaxation training using effective connectivity analysis
Rongxiang Tang, Yi-Yuan Tang
P50 Modeling neuron oscillation of implicit sequence learning
Guangsheng Liang, Seth A. Kiser, James H. Howard, Jr., Yi-Yuan Tang
P51 The role of cerebellar short-term synaptic plasticity in the pathology and medication of downbeat nystagmus
Julia Goncharenko, Neil Davey, Maria Schilstra, Volker Steuber
P52 Nonlinear response of noisy neurons
Sergej O. Voronenko, Benjamin Lindner
P53 Behavioral embedding suggests multiple chaotic dimensions underlie C. elegans locomotion
Tosif Ahamed, Greg Stephens
P54 Fast and scalable spike sorting for large and dense multi-electrodes recordings
Pierre Yger, Baptiste Lefebvre, Giulia Lia Beatrice Spampinato, Elric Esposito, Marcel Stimberg et Olivier Marre
P55 Sufficient sampling rates for fast hand motion tracking
Hansol Choi, Min-Ho Song
P56 Linear readout of object manifolds
SueYeon Chung, Dan D. Lee, Haim Sompolinsky
P57 Differentiating models of intrinsic bursting and rhythm generation of the respiratory pre-Bötzinger complex using phase response curves
Ryan S. Phillips, Jeffrey Smith
P58 The effect of inhibitory cell network interactions during theta rhythms on extracellular field potentials in CA1 hippocampus
Alexandra Pierri Chatzikalymniou, Katie Ferguson, Frances K. Skinner
P59 Expansion recoding through sparse sampling in the cerebellar input layer speeds learning
N. Alex Cayco Gajic, Claudia Clopath, R. Angus Silver
P60 A set of curated cortical models at multiple scales on Open Source Brain
Padraig Gleeson, Boris Marin, Sadra Sadeh, Adrian Quintana, Matteo Cantarelli, Salvador Dura-Bernal, William W. Lytton, Andrew Davison, R. Angus Silver
P61 A synaptic story of dynamical information encoding in neural adaptation
Luozheng Li, Wenhao Zhang, Yuanyuan Mi, Dahui Wang, Si Wu
P62 Physical modeling of rule-observant rodent behavior
Youngjo Song, Sol Park, Ilhwan Choi, Jaeseung Jeong, Hee-sup Shin
P64 Predictive coding in area V4 and prefrontal cortex explains dynamic discrimination of partially occluded shapes
Hannah Choi, Anitha Pasupathy, Eric Shea-Brown
P65 Stability of FORCE learning on spiking and rate-based networks
Dongsung Huh, Terrence J. Sejnowski
P66 Stabilising STDP in striatal neurons for reliable fast state recognition in noisy environments
Simon M. Vogt, Arvind Kumar, Robert Schmidt
P67 Electrodiffusion in one- and two-compartment neuron models for characterizing cellular effects of electrical stimulation
Stephen Van Wert, Steven J. Schiff
P68 STDP improves speech recognition capabilities in spiking recurrent circuits parameterized via differential evolution Markov Chain Monte Carlo
Richard Veale, Matthias Scheutz
P69 Bidirectional transformation between dominant cortical neural activities and phase difference distributions
Sang Wan Lee
P70 Maturation of sensory networks through homeostatic structural plasticity
Júlia Gallinaro, Stefan Rotter
P71 Corticothalamic dynamics: structure, number of solutions and stability of steady-state solutions in the space of synaptic couplings
Paula Sanz-Leon, Peter A. Robinson
P72 Optogenetic versus electrical stimulation of the parkinsonian basal ganglia. Computational study
Leonid L. Rubchinsky, Chung Ching Cheung, Shivakeshavan Ratnadurai-Giridharan
P73 Exact spike-timing distribution reveals higher-order interactions of neurons
Safura Rashid Shomali, Majid Nili Ahmadabadi, Hideaki Shimazaki, S. Nader Rasuli
P74 Neural mechanism of visual perceptual learning using a multi-layered neural network
Xiaochen Zhao, Malte J. Rasch
P75 Inferring collective spiking dynamics from mostly unobserved systems
Jens Wilting, Viola Priesemann
P76 How to infer distributions in the brain from subsampled observations
Anna Levina, Viola Priesemann
P77 Influences of embedding and estimation strategies on the inferred memory of single spiking neurons
Lucas Rudelt, Joseph T. Lizier, Viola Priesemann
P78 A nearest-neighbours based estimator for transfer entropy between spike trains
Joseph T. Lizier, Richard E. Spinney, Mikail Rubinov, Michael Wibral, Viola Priesemann
P79 Active learning of psychometric functions with multinomial logistic models
Ji Hyun Bak, Jonathan Pillow
P81 Inferring low-dimensional network dynamics with variational latent Gaussian process
Yuan Zaho, Il Memming Park
P82 Computational investigation of energy landscapes in the resting state subcortical brain network
Jiyoung Kang, Hae-Jeong Park
P83 Local repulsive interaction between retinal ganglion cells can generate a consistent spatial periodicity of orientation map
Jaeson Jang, Se-Bum Paik
P84 Phase duration of bistable perception reveals intrinsic time scale of perceptual decision under noisy condition
Woochul Choi, Se-Bum Paik
P85 Feedforward convergence between retina and primary visual cortex can determine the structure of orientation map
Changju Lee, Jaeson Jang, Se-Bum Paik
P86 Computational method classifying neural network activity patterns for imaging data
Min Song, Hyeonsu Lee, Se-Bum Paik
P87 Symmetry of spike-timing-dependent-plasticity kernels regulates volatility of memory
Youngjin Park, Woochul Choi, Se-Bum Paik
P88 Effects of time-periodic coupling strength on the first-spike latency dynamics of a scale-free network of stochastic Hodgkin-Huxley neurons
Ergin Yilmaz, Veli Baysal, Mahmut Ozer
P89 Spectral properties of spiking responses in V1 and V4 change within the trial and are highly relevant for behavioral performance
Veronika Koren, Klaus Obermayer
P90 Methods for building accurate models of individual neurons
Daniel Saska, Thomas Nowotny
P91 A full size mathematical model of the early olfactory system of honeybees
Ho Ka Chan, Alan Diamond, Thomas Nowotny
P92 Stimulation-induced tuning of ongoing oscillations in spiking neural networks
Christoph S. Herrmann, Micah M. Murray, Silvio Ionta, Axel Hutt, Jérémie Lefebvre
P93 Decision-specific sequences of neural activity in balanced random networks driven by structured sensory input
Philipp Weidel, Renato Duarte, Abigail Morrison
P94 Modulation of tuning induced by abrupt reduction of SST cell activity
Jung H. Lee, Ramakrishnan Iyer, Stefan Mihalas
P95 The functional role of VIP cell activation during locomotion
Jung H. Lee, Ramakrishnan Iyer, Christof Koch, Stefan Mihalas
P96 Stochastic inference with spiking neural networks
Mihai A. Petrovici, Luziwei Leng, Oliver Breitwieser, David Stöckel, Ilja Bytschok, Roman Martel, Johannes Bill, Johannes Schemmel, Karlheinz Meier
P97 Modeling orientation-selective electrical stimulation with retinal prostheses
Timothy B. Esler, Anthony N. Burkitt, David B. Grayden, Robert R. Kerr, Bahman Tahayori, Hamish Meffin
P98 Ion channel noise can explain firing correlation in auditory nerves
Bahar Moezzi, Nicolangelo Iannella, Mark D. McDonnell
P99 Limits of temporal encoding of thalamocortical inputs in a neocortical microcircuit
Max Nolte, Michael W. Reimann, Eilif Muller, Henry Markram
P100 On the representation of arm reaching movements: a computational model
Antonio Parziale, Rosa Senatore, Angelo Marcelli
P101 A computational model for investigating the role of cerebellum in acquisition and retention of motor behavior
Rosa Senatore, Antonio Parziale, Angelo Marcelli
P102 The emergence of semantic categories from a large-scale brain network of semantic knowledge
K. Skiker, M. Maouene
P103 Multiscale modeling of M1 multitarget pharmacotherapy for dystonia
Samuel A. Neymotin, Salvador Dura-Bernal, Alexandra Seidenstein, Peter Lakatos, Terence D. Sanger, William W. Lytton
P104 Effect of network size on computational capacity
Salvador Dura-Bernal, Rosemary J. Menzies, Campbell McLauchlan, Sacha J. van Albada, David J. Kedziora, Samuel Neymotin, William W. Lytton, Cliff C. Kerr
P105 NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks
Salvador Dura-Bernal, Benjamin A. Suter, Samuel A. Neymotin, Cliff C. Kerr, Adrian Quintana, Padraig Gleeson, Gordon M. G. Shepherd, William W. Lytton
P107 Inter-areal and inter-regional inhomogeneity in co-axial anisotropy of Cortical Point Spread in human visual areas
Juhyoung Ryu, Sang-Hun Lee
P108 Two bayesian quanta of uncertainty explain the temporal dynamics of cortical activity in the non-sensory areas during bistable perception
Joonwon Lee, Sang-Hun Lee
P109 Optimal and suboptimal integration of sensory and value information in perceptual decision making
Hyang Jung Lee, Sang-Hun Lee
P110 A Bayesian algorithm for phoneme Perception and its neural implementation
Daeseob Lim, Sang-Hun Lee
P111 Complexity of EEG signals is reduced during unconsciousness induced by ketamine and propofol
Jisung Wang, Heonsoo Lee
P112 Self-organized criticality of neural avalanche in a neural model on complex networks
Nam Jung, Le Anh Quang, Seung Eun Maeng, Tae Ho Lee, Jae Woo Lee
P113 Dynamic alterations in connection topology of the hippocampal network during ictal-like epileptiform activity in an in vitro rat model
Chang-hyun Park, Sora Ahn, Jangsup Moon, Yun Seo Choi, Juhee Kim, Sang Beom Jun, Seungjun Lee, Hyang Woon Lee
P114 Computational model to replicate seizure suppression effect by electrical stimulation
Sora Ahn, Sumin Jo, Eunji Jun, Suin Yu, Hyang Woon Lee, Sang Beom Jun, Seungjun Lee
P115 Identifying excitatory and inhibitory synapses in neuronal networks from spike trains using sorted local transfer entropy
Felix Goetze, Pik-Yin Lai
P116 Neural network model for obstacle avoidance based on neuromorphic computational model of boundary vector cell and head direction cell
Seonghyun Kim, Jeehyun Kwag
P117 Dynamic gating of spike pattern propagation by Hebbian and anti-Hebbian spike timing-dependent plasticity in excitatory feedforward network model
Hyun Jae Jang, Jeehyun Kwag
P118 Inferring characteristics of input correlations of cells exhibiting up-down state transitions in the rat striatum
Marko Filipović, Ramon Reig, Ad Aertsen, Gilad Silberberg, Arvind Kumar
P119 Graph properties of the functional connected brain under the influence of Alzheimer’s disease
Claudia Bachmann, Simone Buttler, Heidi Jacobs, Kim Dillen, Gereon R. Fink, Juraj Kukolja, Abigail Morrison
P120 Learning sparse representations in the olfactory bulb
Daniel Kepple, Hamza Giaffar, Dima Rinberg, Steven Shea, Alex Koulakov
P121 Functional classification of homologous basal-ganglia networks
Jyotika Bahuguna,Tom Tetzlaff, Abigail Morrison, Arvind Kumar, Jeanette Hellgren Kotaleski
P122 Short term memory based on multistability
Tim Kunze, Andre Peterson, Thomas Knösche
P123 A physiologically plausible, computationally efficient model and simulation software for mammalian motor units
Minjung Kim, Hojeong Kim
P125 Decoding laser-induced somatosensory information from EEG
Ji Sung Park, Ji Won Yeon, Sung-Phil Kim
P126 Phase synchronization of alpha activity for EEG-based personal authentication
Jae-Hwan Kang, Chungho Lee, Sung-Phil Kim
P129 Investigating phase-lags in sEEG data using spatially distributed time delays in a large-scale brain network model
Andreas Spiegler, Spase Petkoski, Matias J. Palva, Viktor K. Jirsa
P130 Epileptic seizures in the unfolding of a codimension-3 singularity
Maria L. Saggio, Silvan F. Siep, Andreas Spiegler, William C. Stacey, Christophe Bernard, Viktor K. Jirsa
P131 Incremental dimensional exploratory reasoning under multi-dimensional environment
Oh-hyeon Choung, Yong Jeong
P132 A low-cost model of eye movements and memory in personal visual cognition
Yong-il Lee, Jaeseung Jeong
P133 Complex network analysis of structural connectome of autism spectrum disorder patients
Su Hyun Kim, Mir Jeong, Jaeseung Jeong
P134 Cognitive motives and the neural correlates underlying human social information transmission, gossip
Jeungmin Lee, Jaehyung Kwon, Jerald D. Kralik, Jaeseung Jeong
P135 EEG hyperscanning detects neural oscillation for the social interaction during the economic decision-making
Jaehwan Jahng, Dong-Uk Hwang, Jaeseung Jeong
P136 Detecting purchase decision based on hyperfrontality of the EEG
Jae-Hyung Kwon, Sang-Min Park, Jaeseung Jeong
P137 Vulnerability-based critical neurons, synapses, and pathways in the Caenorhabditis elegans connectome
Seongkyun Kim, Hyoungkyu Kim, Jerald D. Kralik, Jaeseung Jeong
P138 Motif analysis reveals functionally asymmetrical neurons in C. elegans
Pyeong Soo Kim, Seongkyun Kim, Hyoungkyu Kim, Jaeseung Jeong
P139 Computational approach to preference-based serial decision dynamics: do temporal discounting and working memory affect it?
Sangsup Yoon, Jaehyung Kwon, Sewoong Lim, Jaeseung Jeong
P141 Social stress induced neural network reconfiguration affects decision making and learning in zebrafish
Choongseok Park, Thomas Miller, Katie Clements, Sungwoo Ahn, Eoon Hye Ji, Fadi A. Issa
P142 Descriptive, generative, and hybrid approaches for neural connectivity inference from neural activity data
JeongHun Baek, Shigeyuki Oba, Junichiro Yoshimoto, Kenji Doya, Shin Ishii
P145 Divergent-convergent synaptic connectivities accelerate coding in multilayered sensory systems
Thiago S. Mosqueiro, Martin F. Strube-Bloss, Brian Smith, Ramon Huerta
P146 Swinging networks
Michal Hadrava, Jaroslav Hlinka
P147 Inferring dynamically relevant motifs from oscillatory stimuli: challenges, pitfalls, and solutions
Hannah Bos, Moritz Helias
P148 Spatiotemporal mapping of brain network dynamics during cognitive tasks using magnetoencephalography and deep learning
Charles M. Welzig, Zachary J. Harper
P149 Multiscale complexity analysis for the segmentation of MRI images
Won Sup Kim, In-Seob Shin, Hyeon-Man Baek, Seung Kee Han
P150 A neuro-computational model of emotional attention
René Richter, Julien Vitay, Frederick Beuth, Fred H. Hamker
P151 Multi-site delayed feedback stimulation in parkinsonian networks
Kelly Toppin, Yixin Guo
P152 Bistability in Hodgkin–Huxley-type equations
Tatiana Kameneva, Hamish Meffin, Anthony N. Burkitt, David B. Grayden
P153 Phase changes in postsynaptic spiking due to synaptic connectivity and short term plasticity: mathematical analysis of frequency dependency
Mark D. McDonnell, Bruce P. Graham
P154 Quantifying resilience patterns in brain networks: the importance of directionality
Penelope J. Kale, Leonardo L. Gollo
P155 Dynamics of rate-model networks with separate excitatory and inhibitory populations
Merav Stern, L. F. Abbott
P156 A model for multi-stable dynamics in action recognition modulated by integration of silhouette and shading cues
Leonid A. Fedorov, Martin A. Giese
P157 Spiking model for the interaction between action recognition and action execution
Mohammad Hovaidi Ardestani, Martin Giese
P158 Surprise-modulated belief update: how to learn within changing environments?
Mohammad Javad Faraji, Kerstin Preuschoff, Wulfram Gerstner
P159 A fast, stochastic and adaptive model of auditory nerve responses to cochlear implant stimulation
Margriet J. van Gendt, Jeroen J. Briaire, Randy K. Kalkman, Johan H. M. Frijns
P160 Quantitative comparison of graph theoretical measures of simulated and empirical functional brain networks
Won Hee Lee, Sophia Frangou
P161 Determining discriminative properties of fMRI signals in schizophrenia using highly comparative time-series analysis
Ben D. Fulcher, Patricia H. P. Tran, Alex Fornito
P162 Emergence of narrowband LFP oscillations from completely asynchronous activity during seizures and high-frequency oscillations
Stephen V. Gliske, William C. Stacey, Eugene Lim, Katherine A. Holman, Christian G. Fink
P163 Neuronal diversity in structure and function: cross-validation of anatomical and physiological classification of retinal ganglion cells in the mouse
Jinseop S. Kim, Shang Mu, Kevin L. Briggman, H. Sebastian Seung, the EyeWirers
P164 Analysis and modelling of transient firing rate changes in area MT in response to rapid stimulus feature changes
Detlef Wegener, Lisa Bohnenkamp, Udo A. Ernst
P165 Step-wise model fitting accounting for high-resolution spatial measurements: construction of a layer V pyramidal cell model with reduced morphology
Tuomo Mäki-Marttunen, Geir Halnes, Anna Devor, Christoph Metzner, Anders M. Dale, Ole A. Andreassen, Gaute T. Einevoll
P166 Contributions of schizophrenia-associated genes to neuron firing and cardiac pacemaking: a polygenic modeling approach
Tuomo Mäki-Marttunen, Glenn T. Lines, Andy Edwards, Aslak Tveito, Anders M. Dale, Gaute T. Einevoll, Ole A. Andreassen
P167 Local field potentials in a 4 × 4 mm2 multi-layered network model
Espen Hagen, Johanna Senk, Sacha J. van Albada, Markus Diesmann
P168 A spiking network model explains multi-scale properties of cortical dynamics
Maximilian Schmidt, Rembrandt Bakker, Kelly Shen, Gleb Bezgin, Claus-Christian Hilgetag, Markus Diesmann, Sacha Jennifer van Albada
P169 Using joint weight-delay spike-timing dependent plasticity to find polychronous neuronal groups
Haoqi Sun, Olga Sourina, Guang-Bin Huang, Felix Klanner, Cornelia Denk
P170 Tensor decomposition reveals RSNs in simulated resting state fMRI
Katharina Glomb, Adrián Ponce-Alvarez, Matthieu Gilson, Petra Ritter, Gustavo Deco
P171 Getting in the groove: testing a new model-based method for comparing task-evoked vs resting-state activity in fMRI data on music listening
Matthieu Gilson, Maria AG Witek, Eric F. Clarke, Mads Hansen, Mikkel Wallentin, Gustavo Deco, Morten L. Kringelbach, Peter Vuust
P172 STochastic engine for pathway simulation (STEPS) on massively parallel processors
Guido Klingbeil, Erik De Schutter
P173 Toolkit support for complex parallel spatial stochastic reaction–diffusion simulation in STEPS
Weiliang Chen, Erik De Schutter
P174 Modeling the generation and propagation of Purkinje cell dendritic spikes caused by parallel fiber synaptic input
Yunliang Zang, Erik De Schutter
P175 Dendritic morphology determines how dendrites are organized into functional subunits
Sungho Hong, Akira Takashima, Erik De Schutter
P176 A model of Ca2+/calmodulin-dependent protein kinase II activity in long term depression at Purkinje cells
Criseida Zamora, Andrew R. Gallimore, Erik De Schutter
P177 Reward-modulated learning of population-encoded vectors for insect-like navigation in embodied agents
Dennis Goldschmidt, Poramate Manoonpong, Sakyasingha Dasgupta
P178 Data-driven neural models part II: connectivity patterns of human seizures
Philippa J. Karoly, Dean R. Freestone, Daniel Soundry, Levin Kuhlmann, Liam Paninski, Mark Cook
P179 Data-driven neural models part I: state and parameter estimation
Dean R. Freestone, Philippa J. Karoly, Daniel Soundry, Levin Kuhlmann, Mark Cook
P180 Spectral and spatial information processing in human auditory streaming
Jaejin Lee, Yonatan I. Fishman, Yale E. Cohen
P181 A tuning curve for the global effects of local perturbations in neural activity: Mapping the systems-level susceptibility of the brain
Leonardo L. Gollo, James A. Roberts, Luca Cocchi
P182 Diverse homeostatic responses to visual deprivation mediated by neural ensembles
Yann Sweeney, Claudia Clopath
P183 Opto-EEG: a novel method for investigating functional connectome in mouse brain based on optogenetics and high density electroencephalography
Soohyun Lee, Woo-Sung Jung, Jee Hyun Choi
P184 Biphasic responses of frontal gamma network to repetitive sleep deprivation during REM sleep
Bowon Kim, Youngsoo Kim, Eunjin Hwang, Jee Hyun Choi
P185 Brain-state correlate and cortical connectivity for frontal gamma oscillations in top-down fashion assessed by auditory steady-state response
Younginha Jung, Eunjin Hwang, Yoon-Kyu Song, Jee Hyun Choi
P186 Neural field model of localized orientation selective activation in V1
James Rankin, Frédéric Chavane
P187 An oscillatory network model of Head direction and Grid cells using locomotor inputs
Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy
P188 A computational model of hippocampus inspired by the functional architecture of basal ganglia
Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy
P189 A computational architecture to model the microanatomy of the striatum and its functional properties
Sabyasachi Shivkumar, Vignesh Muralidharan, V. Srinivasa Chakravarthy
P190 A scalable cortico-basal ganglia model to understand the neural dynamics of targeted reaching
Vignesh Muralidharan, Alekhya Mandali, B. Pragathi Priyadharsini, Hima Mehta, V. Srinivasa Chakravarthy
P191 Emergence of radial orientation selectivity from synaptic plasticity
Catherine E. Davey, David B. Grayden, Anthony N. Burkitt
P192 How do hidden units shape effective connections between neurons?
Braden A. W. Brinkman, Tyler Kekona, Fred Rieke, Eric Shea-Brown, Michael Buice
P193 Characterization of neural firing in the presence of astrocyte-synapse signaling
Maurizio De Pittà, Hugues Berry, Nicolas Brunel
P194 Metastability of spatiotemporal patterns in a large-scale network model of brain dynamics
James A. Roberts, Leonardo L. Gollo, Michael Breakspear
P195 Comparison of three methods to quantify detection and discrimination capacity estimated from neural population recordings
Gary Marsat, Jordan Drew, Phillip D. Chapman, Kevin C. Daly, Samual P. Bradley
P196 Quantifying the constraints for independent evoked and spontaneous NMDA receptor mediated synaptic transmission at individual synapses
Sat Byul Seo, Jianzhong Su, Ege T. Kavalali, Justin Blackwell
P199 Gamma oscillation via adaptive exponential integrate-and-fire neurons
LieJune Shiau, Laure Buhry, Kanishka Basnayake
P200 Visual face representations during memory retrieval compared to perception
Sue-Hyun Lee, Brandon A. Levy, Chris I. Baker
P201 Top-down modulation of sequential activity within packets modeled using avalanche dynamics
Timothée Leleu, Kazuyuki Aihara
Q28 An auto-encoder network realizes sparse features under the influence of desynchronized vascular dynamics
Ryan T. Philips, Karishma Chhabria, V. Srinivasa Chakravarthy
PMCID: PMC5001212  PMID: 27534393
7.  Characterization of a 3D optrode array for infrared neural stimulation 
Biomedical Optics Express  2012;3(9):2200-2219.
This paper characterizes the Utah Slant Optrode Array (USOA) as a means to deliver infrared light deep into tissue. An undoped crystalline silicon (100) substrate was used to fabricate 10 × 10 arrays of optrodes with rows of varying lengths from 0.5 mm to 1.5 mm on a 400-μm pitch. Light delivery from optical fibers and loss mechanisms through these Si optrodes were characterized, with the primary loss mechanisms being Fresnel reflection, coupling, radiation losses from the tapered shank and total internal reflection in the tips. Transmission at the optrode tips with different optical fiber core diameters and light in-coupling interfaces was investigated. At λ = 1.55μm, the highest optrode transmittance of 34.7%, relative to the optical fiber output power, was obtained with a 50-μm multi-mode fiber butt-coupled to the optrode through an intervening medium of index n = 1.66. Maximum power is directed into the optrodes when using fibers with core diameters of 200 μm or less. In addition, the output power varied with the optrode length/taper such that longer and less tapered optrodes exhibited higher light transmission efficiency. Output beam profiles and potential impacts on physiological tests were also examined. Future work is expected to improve USOA efficiency to greater than 64%.
PMCID: PMC3447562  PMID: 23024914
(170.3890) Medical optics instrumentation; (220.4610) Optical fabrication; (230.7380) Waveguides, channeled; (260.3060) Infrared
8.  Shielded Coaxial Optrode Arrays for Neurophysiology 
Recent progress in the study of the brain has been greatly facilitated by the development of new tools capable of minimally-invasive, robust coupling to neuronal assemblies. Two prominent examples are the microelectrode array (MEA), which enables electrical signals from large numbers of neurons to be detected and spatiotemporally correlated, and optogenetics, which enables the electrical activity of cells to be controlled with light. In the former case, high spatial density is desirable but, as electrode arrays evolve toward higher density and thus smaller pitch, electrical crosstalk increases. In the latter, finer control over light input is desirable, to enable improved studies of neuroelectronic pathways emanating from specific cell stimulation. Here, we introduce a coaxial electrode architecture that is uniquely suited to address these issues, as it can simultaneously be utilized as an optical waveguide and a shielded electrode in dense arrays. Using optogenetically-transfected cells on a coaxial MEA, we demonstrate the utility of the architecture by recording cellular currents evoked from optical stimulation. We also show the capability for network recording by radiating an area of seven individually-addressed coaxial electrode regions with cultured cells covering a section of the extent.
PMCID: PMC4899445  PMID: 27375415
multielectrode array; extracellular; optogenetics; nanotechnology; neuroelectronic; optrode
9.  Design, fabrication, and packaging of an integrated, wirelessly-powered optrode array for optogenetics application 
The recent development of optogenetics has created an increased demand for advancing engineering tools for optical modulation of neural circuitry. This paper details the design, fabrication, integration, and packaging procedures of a wirelessly-powered, light emitting diode (LED) coupled optrode neural interface for optogenetic studies. The LED-coupled optrode array employs microscale LED (μLED) chips and polymer-based microwaveguides to deliver light into multi-level cortical networks, coupled with microelectrodes to record spontaneous changes in neural activity. An integrated, implantable, switched-capacitor based stimulator (SCS) system provides high instantaneous power to the μLEDs through an inductive link to emit sufficient light and evoke neural activities. The presented system is mechanically flexible, biocompatible, miniaturized, and lightweight, suitable for chronic implantation in small freely behaving animals. The design of this system is scalable and its manufacturing is cost effective through batch fabrication using microelectromechanical systems (MEMS) technology. It can be adopted by other groups and customized for specific needs of individual experiments.
PMCID: PMC4422027  PMID: 25999823
optrode array; implantable neural interface; optogenetics; microelectromechanical systems; switched-capacitor based stimulators; wireless power transfer
10.  A Wireless Implantable Switched-Capacitor Based Optogenetic Stimulating System 
This paper presents a power-efficient implantable optogenetic interface using a wireless switched-capacitor based stimulating (SCS) system. The SCS efficiently charges storage capacitors directly from an inductive link and periodically discharges them into an array of micro-LEDs, providing high instantaneous power without affecting wireless link and system supply voltage. A custom-designed computer interface in LabVIEW environment wirelessly controls stimulation parameters through the inductive link, and an optrode array enables simultaneous neural recording along with optical stimulation. The 4-channel SCS system prototype has been implemented in a 0.35-μm CMOS process and combined with the optrode array. In vivo experiments involving light-induced local field potentials verified the efficacy of the SCS system. An implantable version of the SCS system with flexible hermetic sealing is under development for chronic experiments.
PMCID: PMC4454608  PMID: 25570099
11.  Optical Measurements of Intramural Action Potentials in Isolated Porcine Hearts Using Optrodes 
Measurements of intramural Vm would greatly increase knowledge of cardiac arrhythmias and defibrillation. Optrodes offer the possibility for three-dimensional Vm mapping but their signal quality has been inadequate.
The objectives of this work were to improve optrode signal quality and use optrodes to measure intramural distribution of action potentials and shock-induced Vm changes in porcine hearts.
Optrodes were made from seven optical fibers 225 or 325 μm in diameter. Fiber ends were polished at 45° angle which improved light collection and allowed their insertion without a needle. Fluorescent measurements were performed in isolated porcine hearts perfused with Tyrode’s solution or blood using Vm-sensitive dye RH-237 and a 200-W Hg/Xe lamp.
The signal-to-noise ratio for 325-μm fibers was 44±23 in blood-perfused hearts (n=5) and 106±45 in Tyrode-perfused hearts (n=3), which represents a ≈4-fold improvement over previously reported data. There was close correspondence between optical and electrical measurements of activation times and action potential duration (APD). No significant intramural APD gradients were observed at cycle lengths up to 4 s and in the presence of dofetilide or d-sotalol. Application of shocks (5–50 V/cm) produced large intramural Vm changes (up to ≈200%APA) possibly reflecting a combined effect of tissue discontinuities and optrode geometry.
A substantial improvement of optrode signal quality was achieved. Optical measurements of APD and activation times matched electrical measurements. Optrode measurements revealed no significant intramural APD gradients. Application of shocks caused large intramural Vm changes that could be influenced by the optrode geometry.
PMCID: PMC2098877  PMID: 17954403
cardiac excitation; action potentials; defibrillation; virtual electrodes; optical mapping; fiber optics
12.  Temporal Resolution of ChR2 and Chronos in an Optogenetic-based Auditory Brainstem Implant Model: Implications for the Development and Application of Auditory Opsins 
Hearing research  2015;322:235-241.
The contemporary auditory brainstem implant (ABI) performance is limited by reliance on electrical stimulation with its accompanying channel cross talk and current spread to non-auditory neurons. A new generation ABI based on optogenetic-technology may ameliorate limitations fundamental to electrical neurostimulation. The most widely studied opsin is channelrhodopsin-2 (ChR2); however, its relatively slow kinetic properties may prevent the encoding of auditory information at high stimulation rates. In the present study, we compare the temporal resolution of light-evoked responses of a recently developed fast opsin, Chronos, to ChR2 in a murine ABI model. Viral mediated gene transfer via a posterolateral craniotomy was used to express Chronos or ChR2 in the mouse nucleus (CN). Following a four to six week incubation period, blue light (473 nm) was delivered via an optical fiber placed directly on the surface of the infected CN, and neural activity was recorded in the contralateral inferior colliculus (IC). Both ChR2 and Chronos evoked sustained responses to all stimuli, even at high driven rates. In addition, optical stimulation evoked excitatory responses throughout the tonotopic axis of the IC. Synchrony of the light-evoked response to stimulus rates of 14–448 pulses/s was higher in Chronos compared to ChR2 mice (p<0.05 at 56, 168, and 224 pulses/s). Our results demonstrate that Chronos has the ability to drive the auditory system at higher stimulation rates than ChR2 and may be a more ideal opsin for manipulation of auditory pathways in future optogenetic-based neuroprostheses.
PMCID: PMC4465525  PMID: 25598479
optogenetics; auditory brainstem implant; channelrhodopsin-2; Chronos; neuroprostheses; Lasker Award
13.  Optical Stimulation of Neurons 
Current Molecular Imaging  2014;3(2):162-177.
Our capacity to interface with the nervous system remains overwhelmingly reliant on electrical stimulation devices, such as electrode arrays and cuff electrodes that can stimulate both central and peripheral nervous systems. However, electrical stimulation has to deal with multiple challenges, including selectivity, spatial resolution, mechanical stability, implant-induced injury and the subsequent inflammatory response. Optical stimulation techniques may avoid some of these challenges by providing more selective stimulation, higher spatial resolution and reduced invasiveness of the device, while also avoiding the electrical artefacts that complicate recordings of electrically stimulated neuronal activity. This review explores the current status of optical stimulation techniques, including optogenetic methods, photoactive molecule approaches and infrared neural stimulation, together with emerging techniques such as hybrid optical-electrical stimulation, nanoparticle enhanced stimulation and optoelectric methods. Infrared neural stimulation is particularly emphasised, due to the potential for direct activation of neural tissue by infrared light, as opposed to techniques that rely on the introduction of exogenous light responsive materials. However, infrared neural stimulation remains imperfectly understood, and techniques for accurately delivering light are still under development. While the various techniques reviewed here confirm the overall feasibility of optical stimulation, a number of challenges remain to be overcome before they can deliver their full potential.
PMCID: PMC4541079  PMID: 26322269
Infrared neural stimulation; neural engineering; neural stimulation; optical stimulation; optogenetics.
14.  Physical principles for scalable neural recording 
Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power–bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices.
PMCID: PMC3807567  PMID: 24187539
neural recording; brain activity mapping; electrical recording; optical methods; magnetic resonance imaging; molecular recording; embedded electronics
15.  In Vivo Optogenetic Control of Striatal and Thalamic Neurons in Non-Human Primates 
PLoS ONE  2012;7(11):e50808.
Electrical and pharmacological stimulation methods are commonly used to study neuronal brain circuits in vivo, but are problematic, because electrical stimulation has limited specificity, while pharmacological activation has low temporal resolution. A recently developed alternative to these methods is the use of optogenetic techniques, based on the expression of light sensitive channel proteins in neurons. While optogenetics have been applied in in vitro preparations and in in vivo studies in rodents, their use to study brain function in nonhuman primates has been limited to the cerebral cortex. Here, we characterize the effects of channelrhodopsin-2 (ChR2) transfection in subcortical areas, i.e., the putamen, the external globus pallidus (GPe) and the ventrolateral thalamus (VL) of rhesus monkeys. Lentiviral vectors containing the ChR2 sequence under control of the elongation factor 1α promoter (pLenti-EF1α -hChR2(H134R)-eYFP-WPRE, titer 109 particles/ml) were deposited in GPe, putamen and VL. Four weeks later, a probe combining a conventional electrode and an optic fiber was introduced in the previously injected brain areas. We found light-evoked responses in 31.5% and 32.7% of all recorded neurons in the striatum and thalamus, respectively, but only in 2.5% of recorded GPe neurons. As expected, most responses were time-locked increases in firing, but decreases or mixed responses were also seen, presumably via ChR2-mediated activation of local inhibitory connections. Light and electron microscopic analyses revealed robust expression of ChR2 on the plasma membrane of cell somas, dendrites, spines and terminals in the striatum and VL. This study demonstrates that optogenetic experiments targeting the striatum and basal ganglia-related thalamic nuclei can be successfully achieved in monkeys. Our results indicate important differences of the type and magnitude of responses in each structure. Experimental conditions such as the vector used, the number and rate of injections, or the light stimulation conditions have to be optimized for each structure studied.
PMCID: PMC3511281  PMID: 23226390
16.  Arrays of MicroLEDs and Astrocytes: Biological Amplifiers to Optogenetically Modulate Neuronal Networks Reducing Light Requirement 
PLoS ONE  2014;9(9):e108689.
In the modern view of synaptic transmission, astrocytes are no longer confined to the role of merely supportive cells. Although they do not generate action potentials, they nonetheless exhibit electrical activity and can influence surrounding neurons through gliotransmitter release. In this work, we explored whether optogenetic activation of glial cells could act as an amplification mechanism to optical neural stimulation via gliotransmission to the neural network. We studied the modulation of gliotransmission by selective photo-activation of channelrhodopsin-2 (ChR2) and by means of a matrix of individually addressable super-bright microLEDs (μLEDs) with an excitation peak at 470 nm. We combined Ca2+ imaging techniques and concurrent patch-clamp electrophysiology to obtain subsequent glia/neural activity. First, we tested the μLEDs efficacy in stimulating ChR2-transfected astrocyte. ChR2-induced astrocytic current did not desensitize overtime, and was linearly increased and prolonged by increasing μLED irradiance in terms of intensity and surface illumination. Subsequently, ChR2 astrocytic stimulation by broad-field LED illumination with the same spectral profile, increased both glial cells and neuronal calcium transient frequency and sEPSCs suggesting that few ChR2-transfected astrocytes were able to excite surrounding not-ChR2-transfected astrocytes and neurons. Finally, by using the μLEDs array to selectively light stimulate ChR2 positive astrocytes we were able to increase the synaptic activity of single neurons surrounding it. In conclusion, ChR2-transfected astrocytes and μLEDs system were shown to be an amplifier of synaptic activity in mixed corticalneuronal and glial cells culture.
PMCID: PMC4180921  PMID: 25265500
17.  Computational Optogenetics: Empirically-Derived Voltage- and Light-Sensitive Channelrhodopsin-2 Model 
PLoS Computational Biology  2013;9(9):e1003220.
Channelrhodospin-2 (ChR2), a light-sensitive ion channel, and its variants have emerged as new excitatory optogenetic tools not only in neuroscience, but also in other areas, including cardiac electrophysiology. An accurate quantitative model of ChR2 is necessary for in silico prediction of the response to optical stimulation in realistic tissue/organ settings. Such a model can guide the rational design of new ion channel functionality tailored to different cell types/tissues. Focusing on one of the most widely used ChR2 mutants (H134R) with enhanced current, we collected a comprehensive experimental data set of the response of this ion channel to different irradiances and voltages, and used these data to develop a model of ChR2 with empirically-derived voltage- and irradiance- dependence, where parameters were fine-tuned via simulated annealing optimization. This ChR2 model offers: 1) accurate inward rectification in the current-voltage response across irradiances; 2) empirically-derived voltage- and light-dependent kinetics (activation, deactivation and recovery from inactivation); and 3) accurate amplitude and morphology of the response across voltage and irradiance settings. Temperature-scaling factors (Q10) were derived and model kinetics was adjusted to physiological temperatures. Using optical action potential clamp, we experimentally validated model-predicted ChR2 behavior in guinea pig ventricular myocytes. The model was then incorporated in a variety of cardiac myocytes, including human ventricular, atrial and Purkinje cell models. We demonstrate the ability of ChR2 to trigger action potentials in human cardiomyocytes at relatively low light levels, as well as the differential response of these cells to light, with the Purkinje cells being most easily excitable and ventricular cells requiring the highest irradiance at all pulse durations. This new experimentally-validated ChR2 model will facilitate virtual experimentation in neural and cardiac optogenetics at the cell and organ level and provide guidance for the development of in vivo tools.
Author Summary
Optogenetics, the use of light-sensitive ion channels for stimulation of mammalian cells and tissues, offers specificity and superior precision of control compared to traditional chemical or electrical means of stimulation. In particular, Channelrhodospin-2 (ChR2), a light-sensitive ion channel, originally derived from algae, has found wide-spread application in neuroscience for controlled stimulation of different brain regions. More recently, this work was extended to other organs, including the heart, where it opens the possibility for a new generation of optical pacemakers. The development of new optogenetic tools that allow for more efficient optical stimulation can be guided by computational prediction of the response of different cells and tissues to light. In this report, we provide a new computational model of ChR2 that was empirically validated and can be inserted into different cell types – neurons or heart cells – for virtual optical stimulation and prediction of optimal light-delivery arrangements, minimum energy needs etc. Overall, virtual optogenetics can accelerate the development of new optical stimulation tools for better understanding and control of brain and heart function.
PMCID: PMC3772068  PMID: 24068903
18.  Control of REM Sleep by Ventral Medulla GABAergic Neurons 
Nature  2015;526(7573):435-438.
Rapid eye movement (REM) sleep is a distinct brain state characterized by activated electroencephalogram (EEG) and complete skeletal muscle paralysis, and it is associated with vivid dreams1-3. Transection studies by Jouvet first demonstrated that the brainstem is both necessary and sufficient for REM sleep generation2, and the neural circuits in the pons have since been studied extensively4-8. The medulla also contains neurons that are active during REM sleep9-13, but whether they play a causal role in REM sleep generation remains unclear. Here we show that a GABAergic pathway originating from the ventral medulla (vM) powerfully promotes REM sleep. Optogenetic activation of vM GABAergic neurons rapidly and reliably initiated REM sleep episodes and prolonged their durations, whereas inactivating these neurons had the opposite effects. Optrode recordings from channelrhodopsin 2 (ChR2)-tagged vM GABAergic neurons showed that they were most active during REM sleep (REM-max), and during wakefulness they were preferentially active during eating and grooming. Furthermore, dual retrograde tracing showed that the rostral projections to the pons and midbrain and caudal projections to the spinal cord originate from separate vM neuron populations. Activating the rostral GABAergic projections was sufficient for both the induction and maintenance of REM sleep, which are likely mediated in part by inhibition of REM-suppressing GABAergic neurons in the ventrolateral periaqueductal gray (vlPAG). These results identify a key component of the pontomedullary network controlling REM sleep. The capability to induce REM sleep on command may offer a powerful tool for investigating its functions.
PMCID: PMC4852286  PMID: 26444238
19.  Fiberless multicolor neural optoelectrode for in vivo circuit analysis 
Scientific Reports  2016;6:30961.
Maximizing the potential of optogenetic approaches in deep brain structures of intact animals requires optical manipulation of neurons at high spatial and temporal resolutions, while simultaneously recording electrical data from those neurons. Here, we present the first fiber-less optoelectrode with a monolithically integrated optical waveguide mixer that can deliver multicolor light at a common waveguide port to achieve multicolor modulation of the same neuronal population in vivo. We demonstrate successful device implementation by achieving efficient coupling between a side-emitting injection laser diode (ILD) and a dielectric optical waveguide mixer via a gradient-index (GRIN) lens. The use of GRIN lenses attains several design features, including high optical coupling and thermal isolation between ILDs and waveguides. We validated the packaged devices in the intact brain of anesthetized mice co-expressing Channelrhodopsin-2 and Archaerhodopsin in pyramidal cells in the hippocampal CA1 region, achieving high quality recording, activation and silencing of the exact same neurons in a given local region. This fully-integrated approach demonstrates the spatial precision and scalability needed to enable independent activation and silencing of the same or different groups of neurons in dense brain regions while simultaneously recording from them, thus considerably advancing the capabilities of currently available optogenetic toolsets.
PMCID: PMC4971539  PMID: 27485264
20.  An implantable neural probe with monolithically integrated dielectric waveguide and recording electrodes for optogenetics applications 
Journal of neural engineering  2013;10(5):056012.
Optogenetics promises exciting neuroscience research by offering optical stimulation of neurons with unprecedented temporal resolution, cell-type specificity and the ability to excite as well as to silence neurons. This work provides the technical solution to deliver light to local neurons and record neural potentials, facilitating local circuit analysis and bridging the gap between optogenetics and neurophysiology research.
We have designed and obtained the first in vivo validation of a neural probe with monolithically integrated electrodes and waveguide. High spatial precision enables optical excitation of targeted neurons with minimal power and recording of single-units in dense cortical and subcortical regions.
Main results
The total coupling and transmission loss through the dielectric waveguide at 473 nm was 10.5 ± 1.9 dB, corresponding to an average output intensity of 9400 mW mm−2 when coupled to a 7 mW optical fiber. Spontaneous field potentials and spiking activities of multiple Channelrhodopsin-2 expressing neurons were recorded in the hippocampus CA1 region of an anesthetized rat. Blue light stimulation at intensity of 51 mW mm−2 induced robust spiking activities in the physiologically identified local populations.
This minimally invasive, complete monolithic integration provides unmatched spatial precision and scalability for future optogenetics studies at deep brain regions with high neuronal density.
PMCID: PMC4056669  PMID: 23985803
21.  A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina 
PLoS Computational Biology  2016;12(4):e1004849.
Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.
Author Summary
Implantable multi-electrode arrays (MEAs) are used to record neurological signals and stimulate the nervous system to restore lost function (e.g. cochlear implants). MEAs that can combine both sensing and stimulation will revolutionize the development of the next generation of devices. Simple models that can accurately characterize neural responses to electrical stimulation are necessary for the development of future neuroprostheses controlled by neural feedback. We demonstrate a model that accurately predicts neural responses to concurrent stimulation across multiple electrodes. The model is simple to evaluate, making it an appropriate model for use with neural feedback. The methods described are applicable to a wide range of neural prostheses, thus greatly assisting future device development.
PMCID: PMC4818105  PMID: 27035143
22.  Optrodes for combined optogenetics and electrophysiology in live animals 
Neurophotonics  2015;2(3):031205.
Optical tissue properties limit visible light depth penetration in tissue. Because of this, the recent development of optogenetic tools was quickly followed by the development of light delivery devices for in vivo optogenetics applications. We summarize the efforts made in the last decade to design neural probes that combine conventional electrophysiological recordings and optical channel(s) for optogenetic activation, often referred to as optodes or optrodes. Several aspects including challenges for light delivery in living brain tissue, the combination of light delivery with electrophysiological recordings, probe designs, multimodality, wireless implantable system, and practical considerations guiding the choice of configuration depending on the questions one seeks to address are presented.
PMCID: PMC4489589  PMID: 26158014
fiber optics; neuroscience; genetically-encoded sensors; opsins; light-tissue interactions
23.  Effects of Optogenetic Activation of Corticothalamic Terminals in the Motor Thalamus of Awake Monkeys 
The Journal of Neuroscience  2016;36(12):3519-3530.
The role of the corticothalamic projection in the ventral motor thalamus remains poorly understood. Therefore, we studied the electrophysiological responses of neurons in the basal ganglia and cerebellar receiving-territories of the motor thalamus (BGMT and CbMT, respectively) using optogenetic activation of corticothalamic projections in awake rhesus macaques. After injections of viral vectors carrying the excitatory opsins ChR2 or C1V1 into the primary motor and premotor cortices of two monkeys, we used optrodes to light activate opsin-expressing neurons in cortex or their terminals in the thalamus while simultaneously recording the extracellular activity of neurons in the vicinity of the stimulation sites. As expected, light activation of opsins in the cerebral cortex evoked robust, short-latency increases in firing of cortical neurons. In contrast, light stimulation of corticothalamic terminals induced small-amplitude, long-latency increases and/or decreases of activity in thalamic neurons. In postmortem material, opsins were found to be expressed in cell bodies and dendrites of cortical neurons and along their corticothalamic projections. At the electron microscopic level, opsin labeling was confined to unmyelinated preterminal axons and small terminals that formed asymmetric synapses with dendrites of projection neurons or GABAergic interneurons in BGMT and CbMT and with neurons in the reticular thalamic nucleus. The morphological features of the transfected terminals, along with the long latency and complex physiological responses of thalamic neurons to their activation, suggest a modulatory role of corticothalamic afferents upon the primate ventral motor thalamus.
SIGNIFICANCE STATEMENT This study provides the first analysis of the physiological effects of cortical inputs on the activity of neurons in the primate ventral motor thalamus using light activation of opsin-containing corticothalamic terminals in awake monkeys. We found that selective light activation of corticothalamic terminals in contact with distal dendrites of thalamocortical neurons and GABAergic interneurons elicits complex patterns of slowly developing excitatory and inhibitory effects in thalamic neurons of the basal ganglia- and cerebellar-receiving regions of the motor thalamus. Our observations suggest a modulatory (instead of a “driver”) role of the corticothalamic system in the primate ventral motor thalamus.
PMCID: PMC4804009  PMID: 27013680
C1V1; ChR2; motor cortex; motor thalamus; optogenetics; single unit recording
24.  Optical mapping of optogenetically shaped cardiac action potentials 
Scientific Reports  2014;4:6125.
Light-mediated silencing and stimulation of cardiac excitability, an important complement to electrical stimulation, promises important discoveries and therapies. To date, cardiac optogenetics has been studied with patch-clamp, multielectrode arrays, video microscopy, and an all-optical system measuring calcium transients. The future lies in achieving simultaneous optical acquisition of excitability signals and optogenetic control, both with high spatio-temporal resolution. Here, we make progress by combining optical mapping of action potentials with concurrent activation of channelrhodopsin-2 (ChR2) or halorhodopsin (eNpHR3.0), via an all-optical system applied to monolayers of neonatal rat ventricular myocytes (NRVM). Additionally, we explore the capability of ChR2 and eNpHR3.0 to shape action-potential waveforms, potentially aiding the study of short/long QT syndromes that result from abnormal changes in action potential duration (APD). These results show the promise of an all-optical system to acquire action potentials with precise temporal optogenetics control, achieving a long-sought flexibility beyond the means of conventional electrical stimulation.
PMCID: PMC4137261  PMID: 25135113
25.  Saccade Modulation by Optical and Electrical Stimulation in the Macaque Frontal Eye Field 
The Journal of Neuroscience  2013;33(42):16684-16697.
Recent studies have demonstrated that strong neural modulations can be evoked with optogenetic stimulation in macaque motor cortex without observing any evoked movements (Han et al., 2009, 2011; Diester et al., 2011). It remains unclear why such perturbations do not generate movements and if conditions exist under which they may evoke movements. In this study, we examine the effects of five optogenetic constructs in the macaque frontal eye field and use electrical microstimulation to assess whether optical perturbation of the local network leads to observable motor changes during optical, electrical, and combined stimulation. We report a significant increase in the probability of evoking saccadic eye movements when low current electrical stimulation is coupled to optical stimulation compared with when electrical stimulation is used alone. Experiments combining channelrhodopsin 2 (ChR2) and electrical stimulation with simultaneous fMRI revealed no discernible fMRI activity at the electrode tip with optical stimulation but strong activity with electrical stimulation. Our findings suggest that stimulation with current ChR2 optogenetic constructs generates subthreshold activity that contributes to the initiation of movements but, in most cases, is not sufficient to evoke a motor response.
PMCID: PMC3797379  PMID: 24133271

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