IU Indianapolis ScholarWorks :: Browsing by Subject "Computational neuroscience"

Browsing by Subject "Computational neuroscience"

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25th Annual Computational Neuroscience Meeting: CNS-2016
(BioMed Central, 2016-08-18) Sharpee, Tatyana O.; Destexhe, Alain; Kawato, Mitsuo; Sekulić, Vladisla; 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; Ju, Huiwen; Hines, Michael L.; Chen, Liang; Kim, Jimin; Leahy, Will; Shlizerman, Eli; Birgolias, Justas; Gerkin, Richard C.; Crook, Sharon M.; Viriyopase, Atthaphon; Memmeshei, Raol-Martin; Dabaghian, Yuri; DeVuti, Justin; Perotti, Luca; Kim, Ammo J.; Fenk, Lisa M.; Lyu, Cheng; Malmon, Gabby; Zhao, Chang; Widmer, Yves; Sprecher, Simon; Halnes, Geir; Tuomo, Maki-Martun; Keller, Daniel; Petterson, Klas H.; Andreassen, Ole A.; Elnevoll, Gaute T.; Yamada, Yasnori; Steyn-Ross, Moira L.; Steyn-Ross, D. Alistair; Meijas, Jorge F.; Murray, John D.; Kennedy, Henry; Kruscha, Alexandra; Grewe, Jan; Lidner, Benjamin; Badel, Laurent; Kasumi, Ohta; 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; Merriosn-Hort, Robert; Borisyuk, Roman; Kim, Chang Sub; Tezuka, Taro; Joo, Pangyu; Young-Ah, Rho; Burton, Shawn D.; Bard, G.; Marsalek, Petr; Kim, Hoon-Hee; Moon, Seok-hun; Lee, Do-won; Molkov, Yaroslav I.; Hamade, Khaldoun; Teka, Wondimu; Barnett, William H.; Kim, Taegyo; Markin, Sergey; Rybak, Ilya A.; Forrow, Csaba; Demutz, Harald; Demkó, László; Vörös, János; Dabaghian, Yuri; Babichev, Andrey; Huang, Haiping; Metzner, Christoph; Schwikard, Achim; Zurowski, Bartosz; Roach, James P.; Sander, Leonard M.; Zochowski, Michal R.; Skilling, Quinton M.; Ognjanovski, Nicolette; Aton, Sara J.; Zochowski, Michal; Wang, Sheng-Ju; Ouyang, Guang; Zhang, Mingsha; Wong, Michael; Zhou, Changsong; Robinson, Peter A.; Sanz-Leon, Paula; Drysdale, Peter M.; Fung, Felix; Abeysuriya, Romesh G.; Rennle, Chris J.; Zhao, Xuelong; Choe, Yoonsuck; Yang, Huei-Fang; Mi, Yuanyuan; Lin, Xiahoan; Wu, Si; Liedtke, Joscha; Schottdorf, Manual; Wolf, Fred; Yamamura, Yorkio; Wickens, Jeffery R.; Rumbell, Timothy; Ramsey, Julia; Reyes, Amy; Draguljić, Daniel; 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.; Giese, Martin; Kuravi, Pradeep; Vogels, Rufin; Seeholzer, Alexander; Podlaski, William; Ranjan, Rajnish; Vogels, Tim; Torres, Joaquin J.; Baroni, Fabiano; Latorre, Roberto; Varona, Pablo; Gips, Bart; Lowet, Eric; Roberts, Mark J.; de Weerd, Peter; Jensen, Ole; van der Eerden, Jan; Goodarzinic, Abdorreza; Niry, Mohammad; Valizadeh, Alireza; Pariz, Aref; Parsi, Shervin S.; Valizadeh, Alireza; Warburton, Julia M.; Marucci, Lucia; Tamagnini, Francesco; Brown, John; 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.; Trisch, Jochen; Zaptocky, 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; Kiser, Seth A.; Howard Jr., James H.; Tang, Yi-Yuan; Goncharenko, Julia; Davey, Neil; Schilstra, Marla; Steuber, Volker; Voronenko, Sergej O.; Linder, Benjamin; Ahamed, Tosif; Stephens, Greg; Yger, Pierre; Lefebvre, Baptiste; Spampinato, Giulia Lia Beatrice; Esposito, Elric; Stimberg, Marcel; Marre, Olivier; Choi, Hansol; Song, Min-Ho; Chung, SueYeon; Lee, Dan D.; Sompolinsky, Haim; Phillips, Ryan S.; Smith, Jeffrey; Chatzikalymniou, Alexandra Pierri; Ferguson, Katie; Skinner, Frances K.; Gajic, N. Alex Cayco; Clopath, Claudia; Silver, R. Angus; Gleeson, Padraig; Marin, Boris; Sadeh, Sadra; Quintana, Adrian; Cantarelli, Matteo; Dura‑Bernal, Salvador; Lytton, William W.; Davison, Andrew; Silver, Angus; Li, Luozheng; Zhang, Wenhao; Mi, Yuanyuan; Wang, Dahui; Wu, Sl; Song, Youngjo; Park, Sol; Choi, Ilhwan; Jeong, Jaeseung; Shin, Hee‑sup; Choi, Hannah; Pasupathy, Anitha; Shea-Brown, Eric; Huh, Dongsung; Sejnowski, Terrence J.; Vogt, Simon M.; Kumar, Arvind; Schmidt, Robert; Werdt, Stephen Van; Schiff, Steven J.; Veale, Richard; Scheutz, Matthias; Lee, Sang Wan; Gallinaro, Júlia; Rotter, Stefan; Sanz‑Leon, Paula; Robinson, Peter A.; Rubchinsky, Leonid L.; Cheung, Chung Ching; Ratnadurai‑Giridharan, Shivakeshavan; Shomali, Safura Rashid; Ahmadabadi, Majid Nili; Shimazaki, Hideaki; Rasuli, Nader; Zhao, Xiaochen; Rasch, Malte J.; Witting, Jens; Priesemann, Viola; Levina, Anna; Priesemann, Viola; Lizler, Joseph T.; Spinney, Richard E.; Rubinov, Mikail; Wibral, Michael; Bak, Ji Hyun; Pillow, Jonathan; Zaho, Yuan; Park, Memming; Kang, Jiyoung; Park, Hae‑Jeong; Jang, Jaeson; Paik, Se-Bum; Choi, Woochul; Lee, Changju; Jang, Jaeson; Paik, Se‑Bum; Song, Min; Lee, Hyeonsu; Yilmaz, Ergin; Baysal, Velt; Ozer, Mahmut; Koren, Veronika; Obermayer, Klaus; Saska, Daniel; Nowotny, Thomas; Chan, Ho Ka; Diamond, Alan; Hermann, Christoph S.; Murray, Micha M.; Ionta, Silvlo; Hutt, Axel; Lefebvre, Jérémie; Weidel, Philipp; Duarte, Renato; Morrison, Abigail; Iyer, Ramakrishnan; Mihalas, Stefan; 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.; Grayden, David B.; Kerr, Robert R.; Tahayori, Bahman; Meffin, Hamish; Moezzi, Bahar; Iannella, Nicolangelo; McDonnell, Mark D.; Nolte, Max; Reimann, Michael W.; Muler, Eilif; Markram, Henry; Parziale, Antonio; Senatore, Rosa; Marcelli, Angelo; Maouene, M.; Skiker, K.; Neymotin, Samuel A.; Dura‑Bernal, Salvador; Seidenstein, Alexandra; Lakatos, Peter; Sanger, Terence D.; Lytton, William W.; Dura‑Bernal, Salvador; Menzies, Rosemary J.; McLauchlan, Campbell; van Albada, Sacha J.; Kedziora, David J.; Neymotin, Samuel; Kerr, Cliff C.; Ryu, Juhyoung; Lee, Sang-Hun; Lee, Joonwon; Lee, Hyang Jung; Lim, Daeseob; Lee, Jung H.; Wang, Jisung; Lee, Heonsoo; Jung, Nam; Quang, Le Anh; Maeng, Seung Eu; 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; Kwag, Jeehyun; Liang, Guangsheng; Jang, Hyun Jae; Filipovi, Marko; Reig, Ramon; Aertsen, Ad; Silberberg, Gilad; Kumar, Arvind; 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; Lee, Chungho; Kim, Sung-Phil; Spiegler, Andreas; Petkoski, Spase; Palva, Matias J.; Jirsa, Viktor K.; Saggio, Maria L.; Siep, Silvan F.; Stacey, William C.; Bernard, Christophe; Choung, Oh‑hyeon; Jeong, Yong; Lee, Yong‑il; Jeong, Jaesung; Kim, Su Hyun; Lee, Jeungmin; Kwon, Jaehyung; Kralik, Jerald D.; Hwang, Dong‑Uk; Park, Sang-Min; Kim, Seongkyun; Kim, Hyoungkyu; Lim, Sewoong; Yoon, Sangsup; Park, Choongseok; Miller, Thomas; Clements, Katie; Hye Jr., Eoon; 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.; Kameneva, Tatiana; Graham, Bruce P.; Kale, Penelope J.; Gollo, Leonardo L.; Stern, Merav; Abbott, L.F.; Fedorov, Leonid A.; Giese, Martin A.; Ardestani, Mohammad Hovaidi; Giese, Martin; Chakravarthy, V.Srinivasa; Chhabria, Karishma; Philips, Ryan T.; Ardestani, Mohammad Hovaidi; Faraji, Mohammad Java; Preuschoff, Kerstin; Gerstner, Wulfram; 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.; Stacey, William C.; Holman, Katherine A.; Fink, Christian G.; Kim, Jinseop; Mu, Shang; Briggman, Kevin L; Seung, H. Sebastian; Wegener, Detlef; Bohnenkamp, Lisa; Ernst, Udo A.; Mäki‑Marttunen, Tuomo; Halnes, Geir; Devor, Anna; Dale, Anders M.; Andreassen, Ole A.; Einevoll, Gaute T.; Hagen, Espen; Lines, Glenn T.; Edwards, Andy; Tveito, Aslak; Senk, Johanna; van Albada, Sacha J; Diesmann, Markus; Schmidt, Maximilian; Bakker, Rembrandt; Shen, Kelly; Bezgin`, Gleb; Hilgetag`, Claus‑Christian; 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; Schutter, Erik De; Chen, Weiliang; Hong, Sungho; Takashima, Akira; Zamora, Criseida; Gallimore, Andrew R.; Karoly, Philippa J.; Freestone, Dean R.; Soundry, Daniel; Kuhlmann, Levin; Paninski, Liam; Cook, Mark; Lee, Jaejin; Fishman, Yonatan I.; Cohen, Yale E.; Cocchi, Luca; Sweeney, Yann; Lee, Soohyun; Jung, Woo-Sung; Kim, Bowon; Kim, Youngsoo; Jung, Younginha; Rankin, James; Chavane, Frédéric; Soman, Karthik; Muralidharan, Vignesh; Shivkumar, Sabyasach; Mandall, Alekhya; Priyadharsini, B. Praga; Mehta, Hima; Brinkman, Braden A.; Kekona, Tyler; Rieke, Fred; Shea‑Brown, Eric; Buice, Michael; Pittà, Maurizio De; Berry, Hugues; Brunel, Nicolas; Breakspear, Michael; Marsat, Gary; Drew, Jordan; Chapman, Phillip D.; Daly, Kevin C.; Bradley, Samual P.; Seo, Sat Byul; Su, Jianzhong; Kavalali, Enge T.; Blackwell, Justin; Shiau, LieJune; Buhry, Laure; Basnayake, Kanishka; Lee, Sue-Hyun; Levy, Brandon A.; Baker, Chris I.; Leleu, Timothée; Aihara, Kazuyuki; Department of Mathematical Sciences, School of Science
Automatic comprehensive radiological reports for clinical acute stroke MRIs
(Springer Nature, 2023-07-10) Liu, Chin-Fu; Zhao, Yi; Yedavalli, Vivek; Leigh, Richard; Falcao, Vito; STIR and VISTA Imaging investigators; Miller, Michael I.; Hillis, Argye E.; Faria, Andreia V.; Biostatistics and Health Data Science, School of Medicine
Background: Although artificial intelligence systems that diagnosis among different conditions from medical images are long term aims, specific goals for automation of human-labor, time-consuming tasks are not only feasible but equally important. Acute conditions that require quantitative metrics, such as acute ischemic strokes, can greatly benefit by the consistency, objectiveness, and accessibility of automated radiological reports. Methods: We used 1,878 annotated brain MRIs to generate a fully automated system that outputs radiological reports in addition to the infarct volume, 3D digital infarct mask, and the feature vector of anatomical regions affected by the acute infarct. This system is associated to a deep-learning algorithm for segmentation of the ischemic core and to parcellation schemes defining arterial territories and classically-identified anatomical brain structures. Results: Here we show that the performance of our system to generate radiological reports was comparable to that of an expert evaluator. The weight of the components of the feature vectors that supported the prediction of the reports, as well as the prediction probabilities are outputted, making the pre-trained models behind our system interpretable. The system is publicly available, runs in real time, in local computers, with minimal computational requirements, and it is readily useful for non-expert users. It supports large-scale processing of new and legacy data, enabling clinical and translational research. Conclusion: The generation of reports indicates that our fully automated system is able to extract quantitative, objective, structured, and personalized information from stroke MRIs.
High-throughput segmentation of unmyelinated axons by deep learning
(Springer Nature, 2022-01-24) Plebani, Emanuele; Biscola, Natalia P.; Havton, Leif A.; Rajwa, Bartek; Shemonti, Abida Sanjana; Jaffey, Deborah; Powley, Terry; Keast, Janet R.; Lu, Kun‑Han; Dundar, M. Murat; Computer and Information Science, School of Science
Axonal characterizations of connectomes in healthy and disease phenotypes are surprisingly incomplete and biased because unmyelinated axons, the most prevalent type of fibers in the nervous system, have largely been ignored as their quantitative assessment quickly becomes unmanageable as the number of axons increases. Herein, we introduce the first prototype of a high-throughput processing pipeline for automated segmentation of unmyelinated fibers. Our team has used transmission electron microscopy images of vagus and pelvic nerves in rats. All unmyelinated axons in these images are individually annotated and used as labeled data to train and validate a deep instance segmentation network. We investigate the effect of different training strategies on the overall segmentation accuracy of the network. We extensively validate the segmentation algorithm as a stand-alone segmentation tool as well as in an expert-in-the-loop hybrid segmentation setting with preliminary, albeit remarkably encouraging results. Our algorithm achieves an instance-level F1 score of between 0.7 and 0.9 on various test images in the stand-alone mode and reduces expert annotation labor by 80% in the hybrid setting. We hope that this new high-throughput segmentation pipeline will enable quick and accurate characterization of unmyelinated fibers at scale and become instrumental in significantly advancing our understanding of connectomes in both the peripheral and the central nervous systems.
Spatial cell type composition in normal and Alzheimers human brains is revealed using integrated mouse and human single cell RNA sequencing
(Nature Publishing Group, 2020-10-22) Johnson, Travis S.; Xiang, Shunian; Helm, Bryan R.; Abrams, Zachary B.; Neidecker, Peter; Machiraju, Raghu; Zhang, Yan; Huang, Kun; Zhang, Jie; Medicine, School of Medicine
Single-cell RNA sequencing (scRNA-seq) resolves heterogenous cell populations in tissues and helps to reveal single-cell level function and dynamics. In neuroscience, the rarity of brain tissue is the bottleneck for such study. Evidence shows that, mouse and human share similar cell type gene markers. We hypothesized that the scRNA-seq data of mouse brain tissue can be used to complete human data to infer cell type composition in human samples. Here, we supplement cell type information of human scRNA-seq data, with mouse. The resulted data were used to infer the spatial cellular composition of 3702 human brain samples from Allen Human Brain Atlas. We then mapped the cell types back to corresponding brain regions. Most cell types were localized to the correct regions. We also compare the mapping results to those derived from neuronal nuclei locations. They were consistent after accounting for changes in neural connectivity between regions. Furthermore, we applied this approach on Alzheimer’s brain data and successfully captured cell pattern changes in AD brains. We believe this integrative approach can solve the sample rarity issue in the neuroscience.

Browsing by Subject "Computational neuroscience"

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