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1.  Frequency-Invariant Representation of Interaural Time Differences in Mammals 
PLoS Computational Biology  2011;7(3):e1002013.
Interaural time differences (ITDs) are the major cue for localizing low-frequency sounds. The activity of neuronal populations in the brainstem encodes ITDs with an exquisite temporal acuity of about . The response of single neurons, however, also changes with other stimulus properties like the spectral composition of sound. The influence of stimulus frequency is very different across neurons and thus it is unclear how ITDs are encoded independently of stimulus frequency by populations of neurons. Here we fitted a statistical model to single-cell rate responses of the dorsal nucleus of the lateral lemniscus. The model was used to evaluate the impact of single-cell response characteristics on the frequency-invariant mutual information between rate response and ITD. We found a rough correspondence between the measured cell characteristics and those predicted by computing mutual information. Furthermore, we studied two readout mechanisms, a linear classifier and a two-channel rate difference decoder. The latter turned out to be better suited to decode the population patterns obtained from the fitted model.
Author Summary
Neuronal codes are usually studied by estimating how much information the brain activity carries about the stimulus. On a single cell level, the relevant features of neuronal activity such as the firing rate or spike timing are readily available. On a population level, where many neurons together encode a stimulus property, finding the most appropriate activity features is less obvious, particularly because the neurons respond with a huge cell-to-cell variability. Here, using the example of the neuronal representation of interaural time differences, we show that the quality of the population code strongly depends on the assumption — or the model — of the population readout. We argue that invariances are useful constraints to identify “good” population codes. Based on these ideas, we suggest that the representation of interaural time differences serves a two-channel code in which the difference between the summed activities of the neurons in the two hemispheres exhibits an invariant and linear dependence on interaural time difference.
doi:10.1371/journal.pcbi.1002013
PMCID: PMC3060160  PMID: 21445227
2.  Resolution of interaural time differences in the avian sound localization circuit—a modeling study 
Interaural time differences (ITDs) are a main cue for sound localization and sound segregation. A dominant model to study ITD detection is the sound localization circuitry in the avian auditory brainstem. Neurons in nucleus laminaris (NL) receive auditory information from both ears via the avian cochlear nucleus magnocellularis (NM) and compare the relative timing of these inputs. Timing of these inputs is crucial, as ITDs in the microsecond range must be discriminated and encoded. We modeled ITD sensitivity of single NL neurons based on previously published data and determined the minimum resolvable ITD for neurons in NL. The minimum resolvable ITD is too large to allow for discrimination by single NL neurons of naturally occurring ITDs for very low frequencies. For high frequency NL neurons (>1 kHz) our calculated ITD resolutions fall well within the natural range of ITDs and approach values of below 10 μs. We show that different parts of the ITD tuning function offer different resolution in ITD coding, suggesting that information derived from both parts may be used for downstream processing. A place code may be used for sound location at frequencies above 500 Hz, but our data suggest the slope of the ITD tuning curve ought to be used for ITD discrimination by single NL neurons at the lowest frequencies. Our results provide an important measure of the necessary temporal window of binaural inputs for future studies on the mechanisms and development of neuronal computation of temporally precise information in this important system. In particular, our data establish the temporal precision needed for conduction time regulation along NM axons.
doi:10.3389/fncom.2014.00099
PMCID: PMC4143899  PMID: 25206329
sound localization; interaural time differences; avian brainstem; nucleus laminaris; ITD resolution
3.  The Neural Representation of Interaural Time Differences in Gerbils Is Transformed from Midbrain to Cortex 
The Journal of Neuroscience  2014;34(50):16796-16808.
Interaural time differences (ITDs) are the dominant cue for the localization of low-frequency sounds. While much is known about the processing of ITDs in the auditory brainstem and midbrain, there have been relatively few studies of ITD processing in auditory cortex. In this study, we compared the neural representation of ITDs in the inferior colliculus (IC) and primary auditory cortex (A1) of gerbils. Our IC results were largely consistent with previous studies, with most cells responding maximally to ITDs that correspond to the contralateral edge of the physiological range. In A1, however, we found that preferred ITDs were distributed evenly throughout the physiological range without any contralateral bias. This difference in the distribution of preferred ITDs in IC and A1 had a major impact on the coding of ITDs at the population level: while a labeled-line decoder that considered the tuning of individual cells performed well on both IC and A1 responses, a two-channel decoder based on the overall activity in each hemisphere performed poorly on A1 responses relative to either labeled-line decoding of A1 responses or two-channel decoding of IC responses. These results suggest that the neural representation of ITDs in gerbils is transformed from IC to A1 and have important implications for how spatial location may be combined with other acoustic features for the analysis of complex auditory scenes.
doi:10.1523/JNEUROSCI.2432-14.2014
PMCID: PMC4261102  PMID: 25505332
auditory cortex; inferior colliculus; interaural time differences; population coding; spatial hearing
4.  Preservation of Spectrotemporal Tuning Between the Nucleus Laminaris and the Inferior Colliculus of the Barn Owl 
Journal of neurophysiology  2007;97(5):3544-3553.
Performing sound recognition is a task that requires an encoding of the time-varying spectral structure of the auditory stimulus. Similarly, computation of the interaural time difference (ITD) requires knowledge of the precise timing of the stimulus. Consistent with this, low-level nuclei of birds and mammals implicated in ITD processing encode the ongoing phase of a stimulus. However, the brain areas that follow the binaural convergence for the computation of ITD show a reduced capacity for phase locking. In addition, we have shown that in the barn owl there is a pooling of ITD-responsive neurons to improve the reliability of ITD coding. Here we demonstrate that despite two stages of convergence and an effective loss of phase information, the auditory system of the anesthetized barn owl displays a graceful transition to an envelope coding that preserves the spectrotemporal information throughout the ITD pathway to the neurons of the core of the central nucleus of the inferior colliculus.
doi:10.1152/jn.01162.2006
PMCID: PMC2532515  PMID: 17314241
5.  Asymmetric Excitatory Synaptic Dynamics Underlie Interaural Time Difference Processing in the Auditory System 
PLoS Biology  2010;8(6):e1000406.
In order to localize sounds in the environment, the auditory system detects and encodes differences in signals between each ear. The exquisite sensitivity of auditory brain stem neurons to the differences in rise time of the excitation signals from the two ears allows for neuronal encoding of microsecond interaural time differences.
Low-frequency sound localization depends on the neural computation of interaural time differences (ITD) and relies on neurons in the auditory brain stem that integrate synaptic inputs delivered by the ipsi- and contralateral auditory pathways that start at the two ears. The first auditory neurons that respond selectively to ITD are found in the medial superior olivary nucleus (MSO). We identified a new mechanism for ITD coding using a brain slice preparation that preserves the binaural inputs to the MSO. There was an internal latency difference for the two excitatory pathways that would, if left uncompensated, position the ITD response function too far outside the physiological range to be useful for estimating ITD. We demonstrate, and support using a biophysically based computational model, that a bilateral asymmetry in excitatory post-synaptic potential (EPSP) slopes provides a robust compensatory delay mechanism due to differential activation of low threshold potassium conductance on these inputs and permits MSO neurons to encode physiological ITDs. We suggest, more generally, that the dependence of spike probability on rate of depolarization, as in these auditory neurons, provides a mechanism for temporal order discrimination between EPSPs.
Author Summary
Animals can locate the source of a sound by detecting microsecond differences in the arrival time of sound at the two ears. Neurons encoding these interaural time differences (ITDs) receive an excitatory synaptic input from each ear. They can perform a microsecond computation with excitatory synapses that have millisecond time scale because they are extremely sensitive to the input's “rise time,” the time taken to reach the peak of the synaptic input. Current theories assume that the biophysical properties of the two inputs are identical. We challenge this assumption by showing that the rise times of excitatory synaptic potentials driven by the ipsilateral ear are faster than those driven by the contralateral ear. Further, we present a computational model demonstrating that this disparity in rise times, together with the neurons' sensitivity to excitation's rise time, can endow ITD-encoding with microsecond resolution in the biologically relevant range. Our analysis also resolves a timing mismatch. The difference between contralateral and ipsilateral latencies is substantially larger than the relevant ITD range. We show how the rise time disparity compensates for this mismatch. Generalizing, we suggest that phasic-firing neurons—those that respond to rapidly, but not to slowly, changing stimuli—are selective to the temporal ordering of brief inputs. In a coincidence-detection computation the neuron will respond more robustly when a faster input leads a slower one, even if the inputs are brief and have similar amplitudes.
doi:10.1371/journal.pbio.1000406
PMCID: PMC2893945  PMID: 20613857
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
doi:10.1186/s12868-016-0283-6
PMCID: PMC5001212  PMID: 27534393
7.  Physiology and anatomy of neurons in the medial superior olive of the mouse 
Journal of Neurophysiology  2016;116(6):2676-2688.
The medial superior olive (MSO) is an important brain center that computes sound location by comparing small differences in arrival time at the two ears. The MSO is investigated for its specializations for processing with extreme temporal precision. In mice, the MSO is small and difficult to study; thus utilization of genetic methods in MSO studies has been lacking. We present the first comprehensive study of the murine MSO and show that most features are consistent with more heavily investigated species.
In mammals with good low-frequency hearing, the medial superior olive (MSO) computes sound location by comparing differences in the arrival time of a sound at each ear, called interaural time disparities (ITDs). Low-frequency sounds are not reflected by the head, and therefore level differences and spectral cues are minimal or absent, leaving ITDs as the only cue for sound localization. Although mammals with high-frequency hearing and small heads (e.g., bats, mice) barely experience ITDs, the MSO is still present in these animals. Yet, aside from studies in specialized bats, in which the MSO appears to serve functions other than ITD processing, it has not been studied in small mammals that do not hear low frequencies. Here we describe neurons in the mouse brain stem that share prominent anatomical, morphological, and physiological properties with the MSO in species known to use ITDs for sound localization. However, these neurons also deviate in some important aspects from the typical MSO, including a less refined arrangement of cell bodies, dendrites, and synaptic inputs. In vitro, the vast majority of neurons exhibited a single, onset action potential in response to suprathreshold depolarization. This spiking pattern is typical of MSO neurons in other species and is generated from a complement of Kv1, Kv3, and IH currents. In vivo, mouse MSO neurons show bilateral excitatory and inhibitory tuning as well as an improvement in temporal acuity of spiking during bilateral acoustic stimulation. The combination of classical MSO features like those observed in gerbils with more unique features similar to those observed in bats and opossums make the mouse MSO an interesting model for exploiting genetic tools to test hypotheses about the molecular mechanisms and evolution of ITD processing.
doi:10.1152/jn.00523.2016
PMCID: PMC5133312  PMID: 27655966
medial superior olive; auditory brain stem; Kv1; Kv3; mouse
8.  Spatial cue reliability drives frequency tuning in the barn Owl's midbrain 
eLife  null;3:e04854.
The robust representation of the environment from unreliable sensory cues is vital for the efficient function of the brain. However, how the neural processing captures the most reliable cues is unknown. The interaural time difference (ITD) is the primary cue to localize sound in horizontal space. ITD is encoded in the firing rate of neurons that detect interaural phase difference (IPD). Due to the filtering effect of the head, IPD for a given location varies depending on the environmental context. We found that, in barn owls, at each location there is a frequency range where the head filtering yields the most reliable IPDs across contexts. Remarkably, the frequency tuning of space-specific neurons in the owl's midbrain varies with their preferred sound location, matching the range that carries the most reliable IPD. Thus, frequency tuning in the owl's space-specific neurons reflects a higher-order feature of the code that captures cue reliability.
DOI: http://dx.doi.org/10.7554/eLife.04854.001
eLife digest
The ability to locate where a sound is coming from is an essential survival skill for both prey and predator species. A major cue used by the brain to infer the sound's location is the difference in arrival time of the sound at the left and right ears; for example, a sound coming from the left side will reach the left ear before the right ear.
We are exposed to a variety of sounds of different intensities (loud or soft), and pitch (high or low) emitted from many different directions. The cacophony that surrounds us makes it a challenge to detect where individual sounds come from because other sounds from different directions corrupt the signals coming from the target. This background noise can profoundly affect the reliability of the sensory cue.
When sounds reach the ears, the head and external ears transform the sound in a direction-dependent manner so that some pitches are amplified more than other pitches for specific directions. However, the consequence of this filtering is that the directional information about a sound may be altered. For example, if two sounds of a similar pitch but from different locations are heard at the same time, they will add up at the ears and change the directional information. The group of neurons that respond to that range of pitches will be activated by both sounds so they cannot provide reliable information about the direction of the individual sounds. The degree to which the directional information is altered depends on the pitch that is being detected by the neurons; therefore detection of a different pitch within the sound may be a more reliable cue.
Cazettes et al. used the known filtering properties of the owl's head to predict the reliability of the timing cue for sounds coming from different directions in a noisy environment. This analysis showed that for each direction, there was a range of pitches that carried the most reliable cues. The study then focused on whether the neurons that represent hearing space in the owl's brain were sensitive to this range.
The experiments found a remarkable correlation between the pitch preferred by each neuron and the range that carried the most reliable cue for each direction. This finding challenges the common view of sensory neurons as simple processors by showing that they are also selective to high-order properties relating to the reliability of the cue.
Besides selecting the cues that are likely to be the most reliable, the brain must capture changes in the reliability of the sensory cues. In addition, this reliability must be incorporated into the information carried by neurons and used when deciding how best to act in uncertain situations. Future research will be required to unravel how the brain does this.
DOI: http://dx.doi.org/10.7554/eLife.04854.002
doi:10.7554/eLife.04854
PMCID: PMC4291741  PMID: 25531067
barn owl; neural coding; cue reliability; sound localization; other
9.  The Neural Code for Auditory Space Depends on Sound Frequency and Head Size in an Optimal Manner 
PLoS ONE  2014;9(11):e108154.
A major cue to the location of a sound source is the interaural time difference (ITD)–the difference in sound arrival time at the two ears. The neural representation of this auditory cue is unresolved. The classic model of ITD coding, dominant for a half-century, posits that the distribution of best ITDs (the ITD evoking a neuron’s maximal response) is unimodal and largely within the range of ITDs permitted by head-size. This is often interpreted as a place code for source location. An alternative model, based on neurophysiology in small mammals, posits a bimodal distribution of best ITDs with exquisite sensitivity to ITDs generated by means of relative firing rates between the distributions. Recently, an optimal-coding model was proposed, unifying the disparate features of these two models under the framework of efficient coding by neural populations. The optimal-coding model predicts that distributions of best ITDs depend on head size and sound frequency: for high frequencies and large heads it resembles the classic model, for low frequencies and small head sizes it resembles the bimodal model. The optimal-coding model makes key, yet unobserved, predictions: for many species, including humans, both forms of neural representation are employed, depending on sound frequency. Furthermore, novel representations are predicted for intermediate frequencies. Here, we examine these predictions in neurophysiological data from five mammalian species: macaque, guinea pig, cat, gerbil and kangaroo rat. We present the first evidence supporting these untested predictions, and demonstrate that different representations appear to be employed at different sound frequencies in the same species.
doi:10.1371/journal.pone.0108154
PMCID: PMC4220907  PMID: 25372405
10.  Neural and Behavioral Sensitivity to Interaural Time Differences Using Amplitude Modulated Tones with Mismatched Carrier Frequencies 
Bilateral cochlear implantation is intended to provide the advantages of binaural hearing, including sound localization and better speech recognition in noise. In most modern implants, temporal information is carried by the envelope of pulsatile stimulation, and thresholds to interaural time differences (ITDs) are generally high compared to those obtained in normal hearing observers. One factor thought to influence ITD sensitivity is the overlap of neural populations stimulated on each side. The present study investigated the effects of acoustically stimulating bilaterally mismatched neural populations in two related paradigms: rabbit neural recordings and human psychophysical testing. The neural coding of interaural envelope timing information was measured in recordings from neurons in the inferior colliculus of the unanesthetized rabbit. Binaural beat stimuli with a 1-Hz difference in modulation frequency were presented at the best modulation frequency and intensity as the carrier frequencies at each ear were varied. Some neurons encoded envelope ITDs with carrier frequency mismatches as great as several octaves. The synchronization strength was typically nonmonotonically related to intensity. Psychophysical data showed that human listeners could also make use of binaural envelope cues for carrier mismatches of up to 2–3 octaves. Thus, the physiological and psychophysical data were broadly consistent, and suggest that bilateral cochlear implants should provide information sufficient to detect envelope ITDs even in the face of bilateral mismatch in the neural populations responding to stimulation. However, the strongly nonmonotonic synchronization to envelope ITDs suggests that the limited dynamic range with electrical stimulation may be an important consideration for ITD encoding.
doi:10.1007/s10162-007-0088-5
PMCID: PMC2538436  PMID: 17657543
sound localization; binaural; inferior colliculus; psychophysics
11.  A Physiologically Based Model of Interaural Time Difference Discrimination 
Interaural time difference (ITD) is a cue to the location of sounds containing low frequencies and is represented in the inferior colliculus (IC) by cells that respond maximally at a particular best delay (BD). Previous studies have demonstrated that single ITD-sensitive cells contain sufficient information in their discharge patterns to account for ITD acuity on the midline (ITD = 0). If ITD discrimination were based on the activity of the most sensitive cell available (“lower envelope hypothesis”), then ITD acuity should be relatively constant as a function of ITD. In response to broadband noise, however, the ITD acuity of human listeners degrades as ITD increases. To account for these results, we hypothesize that pooling of information across neurons is an essential component of ITD discrimination. This report describes a neural pooling model of ITD discrimination based on the response properties of ITD-sensitive cells in the IC of anesthetized cats.
Rate versus ITD curves were fit with a cross-correlation model of ITD sensitivity, and the parameters were used to constrain a population model of ITD discrimination. The model accurately predicts ITD acuity as a function of ITD for broadband noise stimuli when responses are pooled across best frequency (BF). Furthermore, ITD tuning based solely on a system of internal delays is not sufficient to predict ITD acuity in response to 500 Hz tones, suggesting that acuity is likely refined by additional mechanisms. The physiological data confirms evidence from the guinea pig that BD varies systematically with BF, generalizing the observation across species.
doi:10.1523/JNEUROSCI.0762-04.2004
PMCID: PMC2041891  PMID: 15306644
auditory; binaural; hearing; inferior colliculus; localization; psychophysics
12.  Neuronal specializations for the processing of interaural difference cues in the chick 
Sound information is encoded as a series of spikes of the auditory nerve fibers (ANFs), and then transmitted to the brainstem auditory nuclei. Features such as timing and level are extracted from ANFs activity and further processed as the interaural time difference (ITD) and the interaural level difference (ILD), respectively. These two interaural difference cues are used for sound source localization by behaving animals. Both cues depend on the head size of animals and are extremely small, requiring specialized neural properties in order to process these cues with precision. Moreover, the sound level and timing cues are not processed independently from one another. Neurons in the nucleus angularis (NA) are specialized for coding sound level information in birds and the ILD is processed in the posterior part of the dorsal lateral lemniscus nucleus (LLDp). Processing of ILD is affected by the phase difference of binaural sound. Temporal features of sound are encoded in the pathway starting in nucleus magnocellularis (NM), and ITD is processed in the nucleus laminaris (NL). In this pathway a variety of specializations are found in synapse morphology, neuronal excitability, distribution of ion channels and receptors along the tonotopic axis, which reduces spike timing fluctuation in the ANFs-NM synapse, and imparts precise and stable ITD processing to the NL. Moreover, the contrast of ITD processing in NL is enhanced over a wide range of sound level through the activity of GABAergic inhibitory systems from both the superior olivary nucleus (SON) and local inhibitory neurons that follow monosynaptic to NM activity.
doi:10.3389/fncir.2014.00047
PMCID: PMC4023016  PMID: 24847212
brainstem auditory nucleus; interaural difference cues; SON; tonic inhibition; phasic inhibition
13.  Difference in response reliability predicted by spectrotemporal tuning in the cochlear nuclei of barn owls 
The brainstem auditory pathway is obligatory for all aural information. Brainstem auditory neurons must encode the level and timing of sounds, as well as their time-dependent spectral properties, the fine structure and envelope, which are essential for sound discrimination. This study focused on envelope coding in the two cochlear nuclei of the barn owl, nucleus angularis (NA) and nucleus magnocellularis (NM). NA and NM receive input from bifurcating auditory nerve fibers and initiate processing pathways specialized in encoding interaural time (ITD) and level (ILD) differences, respectively. We found that NA neurons, though unable to accurately encode stimulus phase, lock more strongly to the stimulus envelope than NM units. The spectrotemporal receptive fields (STRFs) of NA neurons exhibit a pre-excitatory suppressive field. Using multilinear regression analysis and computational modeling, we show that this feature of STRFs can account for enhanced across-trial response reliability, by locking spikes to the stimulus envelope. Our findings indicate a dichotomy in envelope coding between the time and intensity processing pathways as early as at the level of the cochlear nuclei. This allows the ILD processing pathway to encode envelope information with greater fidelity than the ITD processing pathway. Furthermore, we demonstrate that the properties of the neurons’ STRFs can be quantitatively related to spike timing reliability.
doi:10.1523/JNEUROSCI.5422-10.2011
PMCID: PMC3059808  PMID: 21368035
Nucleus angularis; STRF; spectrotemporal tuning; cochlear nuclei; barn owl; response reliability
14.  Effects of reverberation on the directional sensitivity of auditory neurons across the tonotopic axis: Influences of ITD and ILD 
In reverberant environments, acoustic reflections interfere with the direct sound arriving at a listener’s ears, distorting the binaural cues for sound localization. We investigated the effects of reverberation on the directional sensitivity of single neurons in the inferior colliculus (IC) of unanesthetized rabbits. We find that reverberation degrades the directional sensitivity of single neurons, although the amount of degradation depends on the characteristic frequency (CF) and the type of binaural cues available. When interaural time differences (ITD) are the only available directional cue, low-CF cells sensitive to ITD in the waveform fine time structure maintain better directional sensitivity in reverberation than high-CF cells sensitive to ITD in the envelope induced by cochlear filtering. On the other hand, when both ITD and interaural level difference (ILD) cues are available, directional sensitivity in reverberation is comparable throughout the tonotopic axis of the IC. This result suggests that, at high frequencies, ILDs provide better directional information than envelope ITDs, emphasizing the importance of the ILD-processing pathway for sound localization in reverberation.
doi:10.1523/JNEUROSCI.5517-09.2010
PMCID: PMC2896784  PMID: 20534831
directional sensitivity; interaural level difference; inferior colliculus; interaural time difference; reverberation; sound localization
15.  Maps of interaural time difference in the chicken’s brainstem nucleus laminaris 
Biological cybernetics  2008;98(6):541-559.
Animals, including humans, use interaural time differences (ITDs) that arise from different sound path lengths to the two ears as a cue of horizontal sound source location. The nature of the neural code for ITD is still controversial. Current models differentiate between two population codes: either a map-like rate-place code of ITD along an array of neurons, consistent with a large body of data in the barn owl, or a population rate code, consistent with data from small mammals. Recently, it was proposed that these different codes reflect optimal coding strategies that depend on head size and sound frequency. The chicken makes an excellent test case of this proposal because its physical pre-requisites are similar to small mammals, yet it shares a more recent common ancestry with the owl. We show here that, like in the barn owl, the brainstem nucleus laminaris in mature chickens displayed the major features of a place code of ITD. ITD was topographically represented in the maximal responses of neurons along each isofrequency band, covering approximately the contralateral acoustic hemisphere. Furthermore, the represented ITD range appeared to change with frequency, consistent with a pressure gradient receiver mechanism in the avian middle ear. At very low frequencies, below400 Hz, maximal neural responses were symmetrically distributed around zero ITD and it remained unclear whether there was a topographic representation. These findings do not agree with the above predictions for optimal coding and thus revive the discussion as to what determines the neural coding strategies for ITDs.
doi:10.1007/s00422-008-0220-6
PMCID: PMC3170859  PMID: 18491165
Auditory; Hearing; Sound localization; Sensory
16.  Change in the coding of interaural time difference along the tonotopic axis of the chicken nucleus laminaris 
Interaural time differences (ITDs) are an important cue for the localization of sounds in azimuthal space. Both birds and mammals have specialized, tonotopically organized nuclei in the brain stem for the processing of ITD: medial superior olive in mammals and nucleus laminaris (NL) in birds. The specific way in which ITDs are derived was long assumed to conform to a delay-line model in which arrays of systematically arranged cells create a representation of auditory space with different cells responding maximally to specific ITDs. This model was supported by data from barn owl NL taken from regions above 3 kHz and from chicken above 1 kHz. However, data from mammals often do not show defining features of the Jeffress model such as a systematic topographic representation of best ITDs or the presence of axonal delay lines, and an alternative has been proposed in which neurons are not topographically arranged with respect to ITD and coding occurs through the assessment of the overall response of two large neuron populations, one in each hemisphere. Modeling studies have suggested that the presence of different coding systems could be related to the animal’s head size and frequency range rather than their phylogenetic group. Testing this hypothesis requires data from across the tonotopic range of both birds and mammals. The aim of this study was to obtain in vivo recordings from neurons in the low-frequency range (<1000 Hz) of chicken NL. Our data argues for the presence of a modified Jeffress system that uses the slopes of ITD-selective response functions instead of their peaks to topographically represent ITD at mid- to high frequencies. At low frequencies, below several 100 Hz, the data did not support any current model of ITD coding. This is different to what was previously shown in the barn owl and suggests that constraints in optimal ITD processing may be associated with the particular demands on sound localization determined by the animal’s ecological niche in the same way as other perceptual systems such as field of best vision.
doi:10.3389/fncir.2015.00043
PMCID: PMC4542463  PMID: 26347616
interaural time differences; chickens; auditory brainstem; nucleus laminaris; in vivo electrophysiology
17.  Congenital and Prolonged Adult-Onset Deafness Cause Distinct Degradations in Neural ITD Coding with Bilateral Cochlear Implants 
Bilateral cochlear implant (CI) users perform poorly on tasks involving interaural time differences (ITD), which are critical for sound localization and speech reception in noise by normal-hearing listeners. ITD perception with bilateral CI is influenced by age at onset of deafness and duration of deafness. We previously showed that ITD coding in the auditory midbrain is degraded in congenitally deaf white cats (DWC) compared to acutely deafened cats (ADC) with normal auditory development (Hancock et al., J. Neurosci, 30:14068). To determine the relative importance of early onset of deafness and prolonged duration of deafness for abnormal ITD coding in DWC, we recorded from single units in the inferior colliculus of cats deafened as adults 6 months prior to experimentation (long-term deafened cats, LTDC) and compared neural ITD coding between the three deafness models. The incidence of ITD-sensitive neurons was similar in both groups with normal auditory development (LTDC and ADC), but significantly diminished in DWC. In contrast, both groups that experienced prolonged deafness (LTDC and DWC) had broad distributions of best ITDs around the midline, unlike the more focused distributions biased toward contralateral-leading ITDs present in both ADC and normal-hearing animals. The lack of contralateral bias in LTDC and DWC results in reduced sensitivity to changes in ITD within the natural range. The finding that early onset of deafness more severely degrades neural ITD coding than prolonged duration of deafness argues for the importance of fitting deaf children with sound processors that provide reliable ITD cues at an early age.
doi:10.1007/s10162-013-0380-5
PMCID: PMC3642270  PMID: 23462803
binaural hearing; congenital deafness; inferior colliculus; cochlear implants; ITD
18.  Dichotic sound localization properties of duration-tuned neurons in the inferior colliculus of the big brown bat 
Electrophysiological studies on duration-tuned neurons (DTNs) from the mammalian auditory midbrain have typically evoked spiking responses from these cells using monaural or free-field acoustic stimulation focused on the contralateral ear, with fewer studies devoted to examining the electrophysiological properties of duration tuning using binaural stimulation. Because the inferior colliculus (IC) receives convergent inputs from lower brainstem auditory nuclei that process sounds from each ear, many midbrain neurons have responses shaped by binaural interactions and are selective to binaural cues important for sound localization. In this study, we used dichotic stimulation to vary interaural level difference (ILD) and interaural time difference (ITD) acoustic cues and explore the binaural interactions and response properties of DTNs and non-DTNs from the IC of the big brown bat (Eptesicus fuscus). Our results reveal that both DTNs and non-DTNs can have responses selective to binaural stimulation, with a majority of IC neurons showing some type of ILD selectivity, fewer cells showing ITD selectivity, and a number of neurons showing both ILD and ITD selectivity. This study provides the first demonstration that the temporally selective responses of DTNs from the vertebrate auditory midbrain can be selective to binaural cues used for sound localization in addition to having spiking responses that are selective for stimulus frequency, amplitude, and duration.
doi:10.3389/fphys.2014.00215
PMCID: PMC4050336  PMID: 24959149
auditory neurophysiology; binaural hearing; dichotic stimulation; Eptesicus fuscus; sound localization
19.  The representation of sound localization cues in the barn owl's inferior colliculus 
The barn owl is a well-known model system for studying auditory processing and sound localization. This article reviews the morphological and functional organization, as well as the role of the underlying microcircuits, of the barn owl's inferior colliculus (IC). We focus on the processing of frequency and interaural time (ITD) and level differences (ILD). We first summarize the morphology of the sub-nuclei belonging to the IC and their differentiation by antero- and retrograde labeling and by staining with various antibodies. We then focus on the response properties of neurons in the three major sub-nuclei of IC [core of the central nucleus of the IC (ICCc), lateral shell of the central nucleus of the IC (ICCls), and the external nucleus of the IC (ICX)]. ICCc projects to ICCls, which in turn sends its information to ICX. The responses of neurons in ICCc are sensitive to changes in ITD but not to changes in ILD. The distribution of ITD sensitivity with frequency in ICCc can only partly be explained by optimal coding. We continue with the tuning properties of ICCls neurons, the first station in the midbrain where the ITD and ILD pathways merge after they have split at the level of the cochlear nucleus. The ICCc and ICCls share similar ITD and frequency tuning. By contrast, ICCls shows sigmoidal ILD tuning which is absent in ICCc. Both ICCc and ICCls project to the forebrain, and ICCls also projects to ICX, where space-specific neurons are found. Space-specific neurons exhibit side peak suppression in ITD tuning, bell-shaped ILD tuning, and are broadly tuned to frequency. These neurons respond only to restricted positions of auditory space and form a map of two-dimensional auditory space. Finally, we briefly review major IC features, including multiplication-like computations, correlates of echo suppression, plasticity, and adaptation.
doi:10.3389/fncir.2012.00045
PMCID: PMC3394089  PMID: 22798945
sound localization; central nucleus of the inferior colliculus; auditory; plasticity; adaptation; interaural time difference; interaural level difference; frequency tuning
20.  Responses of Auditory Nerve and Anteroventral Cochlear Nucleus Fibers to Broadband and Narrowband Noise: Implications for the Sensitivity to Interaural Delays 
The quality of temporal coding of sound waveforms in the monaural afferents that converge on binaural neurons in the brainstem limits the sensitivity to temporal differences at the two ears. The anteroventral cochlear nucleus (AVCN) houses the cells that project to the binaural nuclei, which are known to have enhanced temporal coding of low-frequency sounds relative to auditory nerve (AN) fibers. We applied a coincidence analysis within the framework of detection theory to investigate the extent to which AVCN processing affects interaural time delay (ITD) sensitivity. Using monaural spike trains to a 1-s broadband or narrowband noise token, we emulated the binaural task of ITD discrimination and calculated just noticeable differences (jnds). The ITD jnds derived from AVCN neurons were lower than those derived from AN fibers, showing that the enhanced temporal coding in the AVCN improves binaural sensitivity to ITDs. AVCN processing also increased the dynamic range of ITD sensitivity and changed the shape of the frequency dependence of ITD sensitivity. Bandwidth dependence of ITD jnds from AN as well as AVCN fibers agreed with psychophysical data. These findings demonstrate that monaural preprocessing in the AVCN improves the temporal code in a way that is beneficial for binaural processing and may be crucial in achieving the exquisite sensitivity to ITDs observed in binaural pathways.
doi:10.1007/s10162-011-0268-1
PMCID: PMC3123442  PMID: 21567250
coincidence detection; interaural time difference; discrimination; binaural; sound localization
21.  Responses of Auditory Nerve and Anteroventral Cochlear Nucleus Fibers to Broadband and Narrowband Noise: Implications for the Sensitivity to Interaural Delays 
The quality of temporal coding of sound waveforms in the monaural afferents that converge on binaural neurons in the brainstem limits the sensitivity to temporal differences at the two ears. The anteroventral cochlear nucleus (AVCN) houses the cells that project to the binaural nuclei, which are known to have enhanced temporal coding of low-frequency sounds relative to auditory nerve (AN) fibers. We applied a coincidence analysis within the framework of detection theory to investigate the extent to which AVCN processing affects interaural time delay (ITD) sensitivity. Using monaural spike trains to a 1-s broadband or narrowband noise token, we emulated the binaural task of ITD discrimination and calculated just noticeable differences (jnds). The ITD jnds derived from AVCN neurons were lower than those derived from AN fibers, showing that the enhanced temporal coding in the AVCN improves binaural sensitivity to ITDs. AVCN processing also increased the dynamic range of ITD sensitivity and changed the shape of the frequency dependence of ITD sensitivity. Bandwidth dependence of ITD jnds from AN as well as AVCN fibers agreed with psychophysical data. These findings demonstrate that monaural preprocessing in the AVCN improves the temporal code in a way that is beneficial for binaural processing and may be crucial in achieving the exquisite sensitivity to ITDs observed in binaural pathways.
doi:10.1007/s10162-011-0268-1
PMCID: PMC3123442  PMID: 21567250
coincidence detection; interaural time difference; discrimination; binaural; sound localization
22.  Multiplicative Auditory Spatial Receptive Fields Created by a Hierarchy of Population Codes 
PLoS ONE  2009;4(11):e8015.
A multiplicative combination of tuning to interaural time difference (ITD) and interaural level difference (ILD) contributes to the generation of spatially selective auditory neurons in the owl's midbrain. Previous analyses of multiplicative responses in the owl have not taken into consideration the frequency-dependence of ITD and ILD cues that occur under natural listening conditions. Here, we present a model for the responses of ITD- and ILD-sensitive neurons in the barn owl's inferior colliculus which satisfies constraints raised by experimental data on frequency convergence, multiplicative interaction of ITD and ILD, and response properties of afferent neurons. We propose that multiplication between ITD- and ILD-dependent signals occurs only within frequency channels and that frequency integration occurs using a linear-threshold mechanism. The model reproduces the experimentally observed nonlinear responses to ITD and ILD in the inferior colliculus, with greater accuracy than previous models. We show that linear-threshold frequency integration allows the system to represent multiple sound sources with natural sound localization cues, whereas multiplicative frequency integration does not. Nonlinear responses in the owl's inferior colliculus can thus be generated using a combination of cellular and network mechanisms, showing that multiple elements of previous theories can be combined in a single system.
doi:10.1371/journal.pone.0008015
PMCID: PMC2776990  PMID: 19956693
23.  Neural Coding of Interaural Time Differences with Bilateral Cochlear Implants in Unanesthetized Rabbits 
The Journal of Neuroscience  2016;36(20):5520-5531.
Although bilateral cochlear implants (CIs) provide improvements in sound localization and speech perception in noise over unilateral CIs, bilateral CI users' sensitivity to interaural time differences (ITDs) is still poorer than normal. In particular, ITD sensitivity of most CI users degrades with increasing stimulation rate and is lacking at the high carrier pulse rates used in CI processors to deliver speech information. To gain a better understanding of the neural basis for this degradation, we characterized ITD tuning of single neurons in the inferior colliculus (IC) for pulse train stimuli in an unanesthetized rabbit model of bilateral CIs. Approximately 73% of IC neurons showed significant ITD sensitivity in their overall firing rates. On average, ITD sensitivity was best for pulse rates near 80–160 pulses per second (pps) and degraded for both lower and higher pulse rates. The degradation in ITD sensitivity at low pulse rates was caused by strong, unsynchronized background activity that masked stimulus-driven responses in many neurons. Selecting synchronized responses by temporal windowing revealed ITD sensitivity in these neurons. With temporal windowing, both the fraction of ITD-sensitive neurons and the degree of ITD sensitivity decreased monotonically with increasing pulse rate. To compare neural ITD sensitivity to human performance in ITD discrimination, neural just-noticeable differences (JNDs) in ITD were computed using signal detection theory. Using temporal windowing at lower pulse rates, and overall firing rate at higher pulse rates, neural ITD JNDs were within the range of perceptual JNDs in human CI users over a wide range of pulse rates.
SIGNIFICANCE STATEMENT Many profoundly deaf people wearing cochlear implants (CIs) still face challenges in everyday situations, such as understanding conversations in noise. Even with CIs in both ears, they have difficulty making full use of subtle differences in the sounds reaching the two ears [interaural time difference (ITD)] to identify where the sound is coming from. This problem is especially acute at the high stimulation rates used in clinical CI processors. This study provides a better understanding of ITD processing with bilateral CIs and shows a parallel between human performance in ITD discrimination and neural responses in the auditory midbrain. The present study is the first report on binaural properties of auditory neurons with CIs in unanesthetized animals.
doi:10.1523/JNEUROSCI.3795-15.2016
PMCID: PMC4871987  PMID: 27194332
binaural hearing; cochlear implant; inferior colliculus; interaural time difference; temporal coding
24.  The Interaural Time Difference Pathway: a Comparison of Spectral Bandwidth and Correlation Sensitivity at Three Anatomical Levels 
ABSTRACT
Temporal differences between the two ears are critical for spatial hearing. They can be described along axes of interaural time difference (ITD) and interaural correlation, and their processing starts in the brainstem with the convergence of monaural pathways which are tuned in frequency and which carry temporal information. In previous studies, we examined the bandwidth (BW) of frequency tuning at two stages: the auditory nerve (AN) and inferior colliculus (IC), and showed that BW depends on characteristic frequency (CF) but that there is no difference in the mean BW of these two structures when measured in a binaural, temporal framework. This suggested that there is little frequency convergence in the ITD pathway between AN and IC and that frequency selectivity determined by the cochlear filter is preserved up to the IC. Unexpectedly, we found that AN and IC neurons can be similar in CF and BW, yet responses to changes in interaural correlation in the IC were different than expected from coincidence patterns (“pseudo-binaural” responses) in the AN. To better understand this, we here examine the responses of bushy cells, which provide monaural inputs to binaural neurons. Using broadband noise, we measured BW and correlation sensitivity in the cat trapezoid body (TB), which contains the axons of bushy cells. This allowed us to compare these two metrics at three stages in the ITD pathway. We found that BWs in the TB are similar to those in the AN and IC. However, TB neurons were found to be more sensitive to changes in stimulus correlation than AN or IC neurons. This is consistent with findings that show that TB fibers are more temporally precise than AN fibers, but is surprising because it suggests that the temporal information available monaurally is not fully exploited binaurally.
doi:10.1007/s10162-013-0436-6
PMCID: PMC3946137  PMID: 24402167
binaural; temporal; bandwidth; interaural time difference; bushy cell; cochlear nucleus
25.  Comparison of Midbrain and Thalamic Space-Specific Neurons in Barn Owls 
Journal of neurophysiology  2006;95(2):783-790.
Spatial receptive fields of neurons in the auditory pathway of the barn owl result from the sensitivity to combinations of interaural time (ITD) and level differences across stimulus frequency. Both the forebrain and tectum of the owl contain such neurons. The neural pathways, which lead to the forebrain and tectal representations of auditory space, separate before the midbrain map of auditory space is synthesized. The first nuclei that belong exclusively to either the forebrain or the tectal pathways are the nucleus ovoidalis (Ov) and the external nucleus of the inferior colliculus (ICx), respectively. Both receive projections from the lateral shell subdivision of the inferior colliculus but are not interconnected. Previous studies indicate that the owl’s tectal representation of auditory space is different from those found in the owl’s forebrain and the mammalian brain. We addressed the question of whether the computation of spatial cues in both pathways is the same by comparing the ITD tuning of Ov and ICx neurons. Unlike in ICx, the relationship between frequency and ITD tuning had not been studied in single Ov units. In contrast to the conspicuous frequency independent ITD tuning of space-specific neurons of ICx, ITD selectivity varied with frequency in Ov. We also observed that the spatially tuned neurons of Ov respond to lower frequencies and are more broadly tuned to ITD than in ICx. Thus there are differences in the integration of frequency and ITD in the two sound-localization pathways. Thalamic neurons integrate spatial information not only within a broader frequency band but also across ITD channels.
doi:10.1152/jn.00833.2005
PMCID: PMC2532520  PMID: 16424454

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