We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.

• MeSH
• Algorithms * MeSH
• Diagnosis, Computer-Assisted methods   MeSH
• Internet * MeSH
• Pattern Recognition, Automated methods   MeSH
• Software * MeSH
• Decision Support Systems, Clinical * MeSH
• Artificial Intelligence * MeSH
• User-Computer Interface * MeSH
• Publication type
• Journal Article MeSH

In the paper we show information theory tools for extracting relevant information for decision support systems from medical databases. Each proposed algorithm for selecting a set of relevant features has a specific score function defined by means of information-theoretical characteristics. Then algorithms are classified according to the primary criterion, that can lead to influence-preferring algorithms or weight-preferring algorithms. Other type of classification can be based on the way of selecting of features as forward, backward or combined algorithms. The software package called CORE (COnstitution and REduction) that supports the process of selection of features relevant for a decision making problem is described. Application on data about 1417 middle age men collected in the twenty years lasting interventional study of cardiovascular risk factors in middle aged men and for decision support in primary care are shown. However, the methodology presented is applicable for any decision making problem where extracting relevant information from data is required.

• MeSH
• Algorithms * MeSH
• Arteriosclerosis * MeSH
• Adult MeSH
• Information Theory MeSH
• Middle Aged MeSH
• Humans MeSH
• Risk Factors MeSH
• Decision Making, Computer-Assisted * MeSH
• Decision Support Systems, Clinical MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

In the paper we show results of two programs applied for data analysis and decision support in primary preventive study of atherosclerosis. First program E.T. (Epidemiology Tools) can be used for analysis of data from retrospective (case-control) studies, prospective (cohort) studies and for standardization. Second program called CORE (COnstitution and REduction) supports the process of selection of features that are relevant for given decision making task. Program CORE is using information theory approach. Both these programs were applied to analysis of data about 1417 middle age men collected in the longitudinal study on atherosclerosis in urban population. Apart from these two new programs we have analyzed data also by the STATISTICA software.

• MeSH
• Arteriosclerosis etiology   prevention & control   MeSH
• Adult MeSH
• Risk Assessment MeSH
• Data Interpretation, Statistical * MeSH
• Middle Aged MeSH
• Humans MeSH
• Longitudinal Studies MeSH
• Mathematical Computing MeSH
• Prospective Studies MeSH
• Retrospective Studies MeSH
• Software MeSH
• Stochastic Processes MeSH
• Decision Support Systems, Clinical * MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

The Environmental Impact Classification for Alien Taxa (EICAT) is an important tool for biological invasion policy and management and has been adopted as an International Union for Conservation of Nature (IUCN) standard to measure the severity of environmental impacts caused by organisms living outside their native ranges. EICAT has already been incorporated into some national and local decision-making procedures, making it a particularly relevant resource for addressing the impact of non-native species. Recently, some of the underlying conceptual principles of EICAT, particularly those related to the use of the precautionary approach, have been challenged. Although still relatively new, guidelines for the application and interpretation of EICAT will be periodically revisited by the IUCN community, based on scientific evidence, to improve the process. Some of the criticisms recently raised are based on subjectively selected assumptions that cannot be generalized and may harm global efforts to manage biological invasions. EICAT adopts a precautionary principle by considering a species' impact history elsewhere because some taxa have traits that can make them inherently more harmful. Furthermore, non-native species are often important drivers of biodiversity loss even in the presence of other pressures. Ignoring the precautionary principle when tackling the impacts of non-native species has led to devastating consequences for human well-being, biodiversity, and ecosystems, as well as poor management outcomes, and thus to significant economic costs. EICAT is a relevant tool because it supports prioritization and management of non-native species and meeting and monitoring progress toward the Kunming-Montreal Global Biodiversity Framework (GBF) Target 6.

Uso de la Clasificación de Impacto Ambiental de los Taxones Exóticos de la UICN para la toma de decisiones Resumen La Clasificación de Impacto Ambiental de los Taxones Exóticos (EICAT, en inglés) es una herramienta importante para las políticas y manejo de las invasiones biológicas y ha sido adoptada como un estándar de la Unión Internacional para la Conservación de la Naturaleza (UICN) para medir la seriedad del impacto ambiental causado por los organismos que viven fuera de su extensión nativa. La EICAT ya ha sido incorporada a algunos procedimientos locales y nacionales de toma de decisiones, lo que la vuelve un recurso particularmente relevante para abordar el impacto de las especies no nativas. Algunos principios conceptuales subyacentes de la EICAT han sido cuestionados recientemente, en particular aquellos relacionados con el uso del principio de precaución. Aunque todavía son relativamente nuevas, las directrices para la aplicación e interpretación de la EICAT tendrán una revisión periódica, basada en evidencia científica, por parte de la comunidad de la UICN para mejorar el proceso. Algunas de las críticas recientes están basadas en suposiciones seleccionadas subjetivamente que no pueden generalizarse y podrían perjudicar los esfuerzos globales para manejar las invasiones biológicas. La EICAT adopta un principio de precaución cuando considera el historial de impacto de una especie en cualquier otro lugar ya que algunos taxones tienen características que podrían volverlos más dañinos. Además, las especies no nativas suelen ser factores de pérdida de bidiversidad, incluso bajo otras presiones. Cuando ignoramos el principio de precaución al abordar el impacto de las especies no nativas, hay consecuencias devastadoras para el bienestar humano, la biodiversidad y los ecosistemas, así como resultados pobres de conservación, y por lo tanto con costos económicos importantes. La EICAT es una herramienta relevante porque respalda la priorización y el manejo de las especies no nativas y ayuda con el cumplimiento y monitoreo del progreso para llegar al objetivo 6 del Marco Mundial de Biodiversidad Kunming‐Montreal.

• Keywords
• biological invasions, evaluación de impacto, evidence synthesis, impact assessment, invasión biológica, managing invasive species, manejo de especies invasoras, precautionary principle, principio de precaución, síntesis de evidencias, 影响评估, 生物入侵, 管理入侵物种, 证据整合, 预防性原则,
• MeSH
• Biodiversity MeSH
• Ecosystem * MeSH
• Humans MeSH
• Conservation of Natural Resources MeSH
• Introduced Species * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Resilience is a complex system that represents dynamic behaviours through its complicated structure with various nodes, interrelations, and information flows. Like other international organizations NATO has also been dealing with the measurement of this complex phenomenon in order to have a comprehensive understanding of the civil environment and its impact on military operations. With this ultimate purpose, NATO had developed and executed a prototype model with the system dynamics modelling and simulation paradigm. NATO has created an aggregated resilience model as an upgrade of the prototype one, as discussed within this study. The structure of the model, aggregation mechanism and shock parametrization methodologies used in the development of the model comprise the scope of this study. Analytic Hierarchy Process (AHP), which is a multi-criteria decision-making technique is the methodology that is used for the development of the aggregation mechanism. The main idea of selecting the AHP methodology is its power and usefulness in mitigating bias in the decision-making process, its capability to increase the number of what-if scenarios to be created, and its contribution to the quality of causal explanations with the granularity it provides. The parametrized strategic shock input page, AHP-based weighted resilience and risk parameters input pages, one more country insertion to the model, and the decision support system page enhance the capacity of the prototype model. As part of the model, the decision support system page stands out as the strategic level cockpit where the colour codes give a clear idea at first about the overall situational picture and country-wise resilience and risk status. At the validation workshop, users not only validated the model but also discussed further development opportunities, such as adding more strategic shocks into the model and introduction of new parameters that will be determined by a big data analysis on relevant open source databases. The developed model has the potential to inspire high-level decision-makers dealing with resilience management in other international organizations, such as the United Nations.

• Keywords
• Analytic Hierarchy Process (AHP), NATO resilience, resilience aggregation, resilience measurement, system dynamics,
• Publication type
• Journal Article MeSH

Therapy of hypertension is still more or less empirical. Several classes of antihypertensive medications are known, the effect of which is based on different mechanisms. The efficacy of the treatment is not always a reliable indication of the appropriate selection as a good therapeutical response can sometimes be achieved at the expense of humoral simulation. This can lead to harmful increased synthesis of trophic hormones. The program for PC called HYPERTENZE supports decision making in therapy of arterial hypertension. It gives a sequence of decisions based on clinical experience using a series of parameters. The program is using the Microsoft Access language of the Access database system and due to the Access Developers Toolkit it does not require Access to be installed on the user's computer. The program HYPERTENZE offers the user essential information and explanation of the decisions in a graded form. The price list of equivalent medications can be updated by the user himself. It seems that this program might be very useful for Czech general practitioners.

• MeSH
• Antihypertensive Agents adverse effects   economics   therapeutic use   MeSH
• Databases as Topic MeSH
• Expert Systems MeSH
• Drug Combinations MeSH
• Hypertension drug therapy   MeSH
• Contraindications MeSH
• Blood Pressure MeSH
• Humans MeSH
• Drug Costs MeSH
• Drug Therapy, Computer-Assisted * MeSH
• Reproducibility of Results MeSH
• Risk Factors MeSH
• Family Practice MeSH
• Decision Support Systems, Management * MeSH
• Software MeSH
• Heart Rate MeSH
• Database Management Systems MeSH
• Therapeutic Equivalency MeSH
• Treatment Outcome MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic MeSH
• Names of Substances
• Antihypertensive Agents MeSH
• Drug Combinations MeSH

CONTEXT: The first European Association of Urology (EAU) guidelines on bladder cancer were published in 2002 [1]. Since then, the guidelines have been continuously updated. OBJECTIVE: To present the 2013 EAU guidelines on non-muscle-invasive bladder cancer (NMIBC). EVIDENCE ACQUISITION: Literature published between 2010 and 2012 on the diagnosis and treatment of NMIBC was systematically reviewed. Previous guidelines were updated, and the levels of evidence and grades of recommendation were assigned. EVIDENCE SYNTHESIS: Tumours staged as Ta, T1, or carcinoma in situ (CIS) are grouped as NMIBC. Diagnosis depends on cystoscopy and histologic evaluation of the tissue obtained by transurethral resection (TUR) in papillary tumours or by multiple bladder biopsies in CIS. In papillary lesions, a complete TUR is essential for the patient's prognosis. Where the initial resection is incomplete, where there is no muscle in the specimen, or where a high-grade or T1 tumour is detected, a second TUR should be performed within 2-6 wk. The risks of both recurrence and progression may be estimated for individual patients using the EORTC scoring system and risk tables. The stratification of patients into low-, intermediate-, and high-risk groups is pivotal to recommending adjuvant treatment. For patients with a low-risk tumour, one immediate instillation of chemotherapy is recommended. Patients with an intermediate-risk tumour should receive one immediate instillation of chemotherapy followed by 1 yr of full-dose bacillus Calmette-Guérin (BCG) intravesical immunotherapy or by further instillations of chemotherapy for a maximum of 1 yr. In patients with high-risk tumours, full-dose intravesical BCG for 1-3 yr is indicated. In patients at highest risk of tumour progression, immediate radical cystectomy should be considered. Cystectomy is recommended in BCG-refractory tumours. The long version of the guidelines is available from the EAU Web site: http://www.uroweb.org/guidelines/. CONCLUSIONS: These abridged EAU guidelines present updated information on the diagnosis and treatment of NMIBC for incorporation into clinical practice. PATIENT SUMMARY: The EAU Panel on Non-muscle Invasive Bladder Cancer released an updated version of their guidelines. Current clinical studies support patient selection into different risk groups; low, intermediate and high risk. These risk groups indicate the likelihood of the development of a new (recurrent) cancer after initial treatment (endoscopic resection) or progression to more aggressive (muscle-invasive) bladder cancer and are most important for the decision to provide chemo- or immunotherapy (bladder installations). Surgical removal of the bladder (radical cystectomy) should only be considered in patients who have failed chemo- or immunotherapy, or who are in the highest risk group for progression.

• Keywords
• Bacillus Calmette-Guerin (BCG), Bladder cancer, Cystectomy, Cystoscopy, Diagnosis, EAU Guidelines, Follow-up, Intravesical chemotherapy, Prognosis, Transurethral resection (TUR), Urothelial carcinoma,
• MeSH
• Chemotherapy, Adjuvant MeSH
• Administration, Intravesical MeSH
• BCG Vaccine administration & dosage   MeSH
• Biopsy standards   MeSH
• Cystectomy standards   MeSH
• Cystoscopy standards   MeSH
• Diagnostic Techniques, Urological standards   MeSH
• Neoplasm Invasiveness MeSH
• Carcinoma diagnosis   pathology   surgery   MeSH
• Humans MeSH
• Evidence-Based Medicine standards   MeSH
• Urinary Bladder Neoplasms diagnosis   pathology   surgery   MeSH
• Predictive Value of Tests MeSH
• Disease Progression MeSH
• Antineoplastic Agents administration & dosage   MeSH
• Societies, Medical standards   MeSH
• Neoplasm Staging MeSH
• Neoplasm Grading MeSH
• Urology standards   MeSH
• Urothelium pathology   MeSH
• Treatment Outcome MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Practice Guideline MeSH
• Geographicals
• Europe MeSH
• Names of Substances
• BCG Vaccine MeSH
• Antineoplastic Agents MeSH

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. 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