Patterned Neurons in a Dish: In the Seek of Order

The brain is one of the most complex organs in the mammalian body. Electrical and chemical interaction of an incredible amount of cells gives rise to mind the way we perceive, remember, learn and act. With such huge complexity in mind, it comes to no surprise that we still are far from understanding the processes behind. In the past years though, different research fields started to cooperate to achieve one common goal. Thus, many new tools were developed which allowed gaining insights on the interactions of individual neurons and systems of nerve cells. In this work, I established and designed tools to manipulate and interact with neurons based on a bottom-up strategy. In contrast to work with the brain as one entity and investigate outputs of the system in terms of behavioral changes of the organism, the bottom-up approach represented in this thesis focuses on a small part of cells. Isolating small amounts of cells, extracted from the brain and cultured in a dish, helps to improve the reproducibility and target-selectivity of stimulations. In an ideal case, the behavior of each cell within this simplified network could be interfaced in a bidirectional way such that each individual cell could be measured and modified. Findings in such abstract systems can later serve as a basis to extrapolate the elementary functions of small circuits to a more complex structure within the brain. The primary aim of this work was to establish and test a platform, which can provide engineered, small and functional neuronal networks with defined topology and connectivity, together with the option of bidirectional interaction with the neuronal cells. In the first part of this thesis, an approach to reach patterns in the scale of single cells is presented. The developed system made it possible to adapt the surface pattern during the culture process. Therefore, it was possible to place the cells at a defined location, but furthermore also define the directionality of the connection between two cell clusters. This approach is based on the fluidic force microscope (FluidFM), which combines microfluidics with an atomic force microscope (AFM) system. Since the closed fluidic system allows the FluidFM to operate in liquid environment, modifications of the surface were also possible in presence of cultured cells. Starting from a non-adhesive background preventing attachment of cells, local modifications of the surface with the FluidFM allowed attachment of cells at specific sites. Since further modifications were possible after the cells already attached, delayed patterning of cell adhesive cues allowed inducing outgrowth of neurites in a predefined direction. In a first approach, we used the exchange of a non-fouling polymer (Poly(L-Lysine)-graft-Poly(Ethylene Glycol); PLL-g-PEG) by an adhesive polymer (Poly(L-Lysine); PLL) to induce such local adhesive sites on the surface. Since the polarity of neurons has shown to be highly influenced by different guidance cues, we further extended the system. Instead of a system based on the unspecific binding of molecules to the PLL layer, adaptation of a system based on the avidin/biotin interaction allowed attaching proteins specifically to a non-fouling surface. The flexibility of such a system could be demonstrated by sequentially patterning two different types of cells. To be able to test the activity of cultured neurons a calcium indicator and extracellular recordings were used in this work. Although the extracellular recordings have the advantage of a better time resolution, the disadvantage is the need of special culture dishes with embedded electrodes. Especially if random influences need to be excluded from the measured activity, a high amount of parallel cultures becomes important. Therefore, we tested the feasibility of cellulose as a culture substrate. Culturing cells on filter paper allowed for a higher amount of parallel cultures. Only during the measurement, the paper were sequentially transferred onto the electrode chip. Therefore, blockage of the electrode chips during the whole culture period could be avoided. In addition, the physical structure of the paper could be easily modified with a laser cutter, allowing macroscopic confined patterns of neuronal cells. The fiber structure of the filter paper furthermore allowed neurons to extend their processes in three dimensions. To allow also interacting with the neurons at the single cell level, the last part of this work focused on the local chemical stimulation of single neurons. In this case, the FluidFM could be utilized to locally deliver a neurotransmitter and therefore stimulate the cell below the cantilever. In combination with extracellular recordings, the system allowed to investigate changes within the whole network induced by such local chemical stimulation. Whereas local delivery of substances can also easily be achieved with glass pipettes, we could show that the stimulation efficiency is depending on the distance to the surface. The force control of the FluidFM in this case allowed for an exact calibration of the distance. Altogether, the presented toolset supports a highly flexible approach to achieve oriented neuronal networks with controlled connectivity. The FluidFM provides a method to extend a surface pattern even when the cells are already in place. This showed to be helpful for active guidance of the processes formed by the neurons, but also for a potential application of patterning of multiple cell types. Paper as a substrate for neuron cultures on the other hand allows for increased throughput instead, but with a limited resolution when it comes to single cell patterns compared to the approach with the FluidFM. In addition, the fiber structure of the filter paper provides the cells with a three dimensional environment to which the cells showed to respond. Laser cutting of the filter paper constitutes a fast solution to increase also the flexibility of this approach and to minimize the development time if a new design needs to be tested. Finally, the free movement of the FluidFM within the dish together with the force feedback ensured the flexibility to interact with the neuronal network at the single cell level, supporting the simulation of external inputs to the network at any time. Within this work, we show first applications of the different methods to present their potential in the field of neuroscience. Once we improve our experience with the patterning process of single cells, the tools developed in this thesis: the positioning of neurons, the directional connectivity, the writing of different chemical guidance cues in combination with the local chemical stimulation at the single cell level will help to tackle bigger questions

Simultaneous scanning ion conductance microscopy and atomic force microscopy with microchanneled cantilevers

We combined scanning ion conductance microscopy (SICM) and atomic force microscopy (AFM) into a single tool using AFM cantilevers with an embedded microchannel flowing into the nanosized aperture at the apex of the hollow pyramid. An electrode was positioned in the AFM fluidic circuit connected to a second electrode in the bath. We could thus simultaneously measure the ionic current and the cantilever bending (in optical beam deflection mode). First, we quantitatively compared the SICM and AFM contact points on the approach curves. Second, we estimated where the probe in SICM mode touches the sample during scanning on a calibration grid and applied the finding to image a network of neurites on a Petri dish. Finally, we assessed the feasibility of a double controller using both the ionic current and the deflection as input signals of the piezofeedback. The experimental data were rationalized in the framework of finite elements simulations

“Brains on a chip”: Towards engineered neural networks

The fundamental mechanisms of complex neural computation remain largely unknown, especially in respect to the characteristics of distinct neural circuits within the mammalian brain. The bottom-up approach of building well-defined neural networks with controlled topology has immense promise for improved reproducibility and increased target selectivity and response of drug action, along with hopes to unravel the relationships between functional connectivity and its imprinted physiological and pathological functions. In this review, we summarize the different approaches available for engineering neural networks treated analogously to a mathematical graph consisting of cell bodies and axons as nodes and edges, respectively. After discussing the advances and limitations of the current techniques in terms of cell placement to the nodes and guiding the growth of axons to connect them, the basic properties of patterned networks are analyzed in respect to cell survival and activity dynamics, and compared to that of in vivo and random in vitro cultures. Besides the fundamental scientific interest and relevance to drug and toxicology tests, we also visualize the possible applications of such engineered networks. The review concludes by comparing the possibilities and limitations of the different methods for realizing in vitro engineered neural networks in 2D

Paper-based patterned 3D neural cultures as a tool to study network activity on multielectrode arrays

Cells in vitro behave differently if cultured in a 2D or 3D environment. In spite of the continuous progress over the recent years, methods available for realizing 3D cultures of primary neurons are still fairly complex, limited in throughput and especially limited in compatibility with other techniques like multielectrode arrays (MEAs) for recording and stimulating the network activity with high temporal precision. In this manuscript, a paper-based approach is presented using cellulose filter paper as a mobile substrate for 3D cultures of primary rat hippocampal and cortical neurons. Acting as 3D scaffolds for network development, filter membranes with different surface treatments were prepared to control network homogeneity and laser cut to change the network topology through spatial confinement. The viability of the prepared cultures was comparable to that of reference 2D cultures for over 4 weeks, and the mechanical stability of the paper substrates made it possible to transfer the cultures to MEA chips in an on-demand manner. Once the cultures were successfully transduced with a gene-encoded calcium indicator and transferred to a MEA chip, the optical and electrical signals of neuronal activity were simultaneously recorded and combined to study the different activity patterns with high spatiotemporal resolution. The high-throughput nature of the presented approach makes it a valuable tool for investigating the intimate relationship between topology and function, by studying the intrinsic parameters influencing network synchronization and signal propagation through the different activity patterns of 3D neural cultures with arbitrary topology. The developed platform provides a robust and simple alternative to existing 3D culturing technologies for neurons.ISSN:2046-206

Controlled single-cell deposition and patterning by highly flexible hollow cantilevers

Single-cell patterning represents a key approach to decouple and better understand the role and mechanisms of individual cells of a given population. In particular, the bottom-up approach of engineering neuronal circuits with a controlled topology holds immense promises to perceive the relationships between connectivity and function. In order to accommodate these efforts, highly flexible SU-8 cantilevers with integrated microchannels have been fabricated for both additive and subtractive patterning. By directly squeezing out single cells onto adhesive surfaces, controlled deposition with a spatial accuracy of 5 μm could be achieved, while subtractive patterning has been realized by selective removal of targeted single cells. Complex cell patterns were created on substrates pre-patterned with cell-adhesive and repulsive areas, preserving the original pattern geometry for long-term studies. For example, a circular loop with a diameter of 530 μm has been realized using primary hippocampal neurons, which were fully connected to their respective neighbors along the loop. Using the same cantilevers, the versatility of the technique has also been demonstrated via in situ modification of already mature neuronal cultures by both detaching individual cells of the population and adding fresh ones, incorporating them into the culture

Modular microstructure design to build neuronal networks of defined functional connectivity

Theoretical and in vivo neuroscience research suggests that functional information transfer within neuronal networks is influenced by circuit architecture. Due to the dynamic complexities of the brain, it remains a challenge to test the correlation between structure and function of a defined network. Engineering controlled neuronal networks in vitro offers a way to test structural motifs; however, no method has achieved small, multi-node networks with stable, unidirectional connections. Here, we screened ten different microchannel architectures within polydimethylsiloxane (PDMS) devices to test their potential for axonal guidance. The most successful design had a 92% probability of achieving strictly unidirectional connections between nodes. Networks built from this design were cultured on multielectrode arrays and recorded on days in vitro 9, 12, 15 and 18 to investigate spontaneous and evoked bursting activity. Transfer entropy between subsequent nodes showed up to 100 times more directional flow of information compared to the control. Additionally, directed networks produced a greater amount of information flow, reinforcing the importance of directional connections in the brain being critical for reliable communication. By controlling the parameters of network formation, we minimized response variability and achieved functional, directional networks. The technique provides us with a tool to probe the spatio-temporal effects of different network motifs

Local Polymer Replacement for Neuron Patterning and <i>in Situ</i> Neurite Guidance

By locally dispensing poly-l-lysine (PLL) molecules with a FluidFM onto a protein and cell resistant poly-l-lysine-<i>graft</i>-polyethylene glycol (PLL-<i>g</i>-PEG) coated substrate, the antifouling layer can be replaced under the tip aperture by the cell adhesive PLL. We used this approach for guiding the adhesion and axonal outgrowth of embryonic hippocampal neurons <i>in situ</i>. Cultures of hippocampal neurons were chosen because they mostly contain pyramidal neurons. The hippocampus is known to be involved in memory formation, and the stages of network development are well characterized, which is an asset to fundamental research. After fabricating diffuse PLL spots with 10–250 μm diameter, seeded hippocampal cells stick preferentially onto the spots migrating toward the spot center along the PLL gradient. Cell clusters were formed depending on the lateral size of the PLL dots and the density of seeded cells. In a second step of this protocol, the FluidFM is used to connect <i>in situ</i> the obtained clusters. The outgrowth of neurites, which are known to grow preferentially on adhesive substrates, is tailored by writing PLL lines. Antibody staining confirms that the outgrowing neurites are mostly axons, while the activity of the neurons is assessed by a calcium indicator, proving cell viability. The calcium signal intensity of two actively interconnected clusters showed to be correlated, corroborating the formation of vectored and polarized interconnections

25th Annual Computational Neuroscience Meeting: CNS-2016

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, Padra