Whole-pelvic irradiation with boost to involved nodes and prostate in node-positive prostate cancer-long-term data from the prospective PLATIN-2 trial

PURPOSE

Node-positive prostate cancer is a potentially curable disease. Definitive radiotherapy to the prostate and lymphatic drainage is an effective treatment option but prospective long-term outcome data are scarce. Thus, the current study aimed to evaluate the toxicity and efficacy of definitive radiation therapy for men with prostate cancer and nodal metastases using modern irradiation techniques.

METHODS

A total of 40 treatment-naïve men with node-positive prostate cancer were allocated to the trial. All patients received definitive radiation therapy at two German university hospitals between 2009 and 2018. Radiation was delivered as intensity-modulated radiation therapy (IMRT) with 51 Gy to the lymphatic drainage with simultaneous integrated boost (SIB) up to 61.2 Gy to involved nodes and 76.5 Gy to the prostate in 34 fractions. Feasibility and safety, overall and progression-free survival, toxicity, and quality of life measurements were analyzed.

RESULTS

During a median follow-up of 79 months, median overall survival was 107 months and progression-free survival was 78 months. Based on imaging follow-up, no infield relapse was reported during the first 24 months of follow-up. There were 3 (8%) potentially treatment-related grade 3 toxicities. Common iliac node involvement was associated with a higher risk of progression (HR 15.8; 95% CI 2.1-119.8; p = 0.007).

CONCLUSION

Definitive radiation to the lymphatic drainage with SIB to the involved nodes and prostate is a safe and effective treatment approach for patients with treatment-naïve, node-positive prostate cancer with excellent infield tumor control rates and tolerable toxicity. Location rather than number of involved nodes is a major risk factor for progression.

Generalised exponential-Gaussian distribution: a method for neural reaction time analysis

Reaction times (RTs) are an essential metric used for understanding the link between brain and behaviour. As research is reaffirming the tight coupling between neuronal and behavioural RTs, thorough statistical modelling of RT data is thus essential to enrich current theories and motivate novel findings. A statistical distribution is proposed herein that is able to model the complete RT's distribution, including location, scale and shape: the generalised-exponential-Gaussian (GEG) distribution. The GEG distribution enables shifting the attention from traditional means and standard deviations to the entire RT distribution. The mathematical properties of the GEG distribution are presented and investigated via simulations. Additionally, the GEG distribution is featured via four real-life data sets. Finally, we discuss how the proposed distribution can be used for regression analyses via generalised additive models for location, scale and shape (GAMLSS).

Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding

The first measurement of lepton-jet momentum imbalance and azimuthal correlation in lepton-proton scattering at high momentum transfer is presented. These data, taken with the H1 detector at HERA, are corrected for detector effects using an unbinned machine learning algorithm (multifold), which considers eight observables simultaneously in this first application. The unfolded cross sections are compared with calculations performed within the context of collinear or transverse-momentum-dependent factorization in quantum chromodynamics as well as Monte Carlo event generators.

Dynamic divisive normalization circuits explain and predict change detection in monkey area MT

Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independently as possible from its current activation state. In motion-selective area MT, neurons respond to instantaneous speed changes with pronounced transients, often far exceeding the expected response as derived from their speed tuning profile. We here show that this complex, non-linear behavior emerges from the combined temporal dynamics of excitation and divisive inhibition, and provide a comprehensive mathematical analysis. A central prediction derived from this investigation is that attention increases the steepness of the transient response irrespective of the activation state prior to a stimulus change, and irrespective of the sign of the change (i.e. irrespective of whether the stimulus is accelerating or decelerating). Extracellular recordings of attention-dependent representation of both speed increments and decrements confirmed this prediction and suggest that improved change detection derives from basic computations in a canonical cortical circuitry.

Primary immunosuppressive TNI-based conditioning regimens in pediatric patients treated with haploidentical hematopoietic cell transplantation

PURPOSE

This retrospective analysis aims to address the toxicity and efficacy of a modified total nodal irradiation (TNI)-based conditioning regimen before haploidentical hematopoietic cell transplantation (HCT) in pediatric patients.

MATERIALS AND METHODS

Patient data including long-term follow-up were evaluated of 7 pediatric patients with malignant (n = 2) and non-malignant diseases (n = 5) who were treated by a primary TNI-based conditioning regimen. TNI was performed using anterior/posterior opposing fields. All patients received 7 Gy single-dose TNI combined with systemic agents followed by an infusion of peripheral blood stem cells (n = 7). All children had haploidentical family donors.

RESULTS

Engraftment was reached in 6/7 children after a median time of 9.5 days; 1 child had primary graft failure but was successfully reconditioned shortly thereafter. After an average follow-up time of 103.5 months (range 8.8-138.5 months), event-free (EFS) and overall survival (OS) rates were 71.4% and 85.7%, respectively. One child with a non-malignant disease died 8.8 months after transplantation due to a relapse and a multiple organ failure. Follow-up data was available for 5/6 long-term survivors with a median follow-up (FU) of 106.2 months (range 54.5-138.5 months). Hypothyroidism and deficiency of sexual hormones was present in 3/5 patients each. Mean forced expiratory volume in 1 s (FEV1) after TNI was 71%; mean vital capacity (VC) was 78%. Growth failure (< 10th percentile) occurred in 2/5 patients (height) and 1/5 patient (weight). No secondary malignancies were reported.

CONCLUSION

In this group of patients, a primary single-dose 7 Gy TNI-based conditioning regimen before HCT in pediatric patients allowed sustained engraftment combined with a tolerable toxicity profile leading to long-term OS/EFS. Late toxicity after a median FU of over 9 years includes growth failure, manageable hormonal deficiencies, and acceptable decrease in lung function.

68Ga-PSMA-PET/CT-directed IGRT/SBRT for oligometastases of recurrent prostate cancer after initial surgery

Background: We evaluated efficacy and toxicity of ⁶⁸Ga-PSMA-Positron Emission Tomography/Computed Tomography (PET/CT)-directed stereotactic body radiotherapy and image-guided radiotherapy (SBRT/IGRT) for oligometastases of prostate cancer recurrences after previous surgery.Methods: Nineteen patients were analyzed within a prospective PET-registry study (064/2013BO1) and retrospectively analyzed (807/2017BO2) fulfilling the following inclusion criteria: biochemical recurrence after radical prostatectomy, ≤five ⁶⁸Ga-PSMA-PET/CT positive lesions. Biochemical control was evaluated with EORTC (European Organization for Research and Treatment of Cancer)- and Phenix-definitions. Toxicity was scored according to CTCAE-criteria v. 4.03.Results: A total of 38 oligometastases (19 patients, 2 with re-treatment) were treated with SBRT/IGRT from October 2014 to July 2017. ⁶⁸Ga-PSMA-PET/CT-positive lesions were detected on average 39 months (5-139) after prostatectomy (pT2b-3b pN0-1 cM0). Mean PSA (Prostate-specific antigen)-level at time of imaging reached 2.2 ng/mL (range 0.2-10.1). PET/CT-positive lesions were treated with different fractionation schedules reaching biological equivalent doses (BED) of 116.7-230.0 Gy. Concomitant androgen deprivation therapy (ADT) was given in seven patients. After a median follow-up of 17 months (4-42) all patients were alive. Estimated 1-year PSA- control (n = 19) reached 80.8% (Phenix) and 67.5% (EORTC). A PSA-decline (≥50%) was detected in 16/19 patients after radiotherapy. Higher graded G3+-acute toxicity did not occur. Temporary late G3-proctitis was detected in one patient.Conclusions: Reaching of nadir ≤0.1 or 0.2 ng/mL was associated by improved DMFS (distant metastases free survival) and could serve as a surrogate endpoint for RT of oligometastases after initial prostatectomy. Short term effects of ⁶⁸Ga-PSMA-PET/CT-based ablative radiotherapy for oligometastases demonstrated an acceptable toxicity profile and favorable biochemical response.

Visual epidural field potentials possess high functional specificity in single trials

Recordings of epidural field potentials (EFPs) allow neuronal activity to be acquired over a large region of cortical tissue with minimal invasiveness. Because electrodes are placed on top of the dura and do not enter the neuronal tissue, EFPs offer intriguing options for both clinical and basic science research. On the other hand, EFPs represent the integrated activity of larger neuronal populations and possess a higher trial-by-trial variability and a reduced signal-to-noise ratio due the additional barrier of the dura. It is thus unclear whether and to what extent EFPs have sufficient spatial selectivity to allow for conclusions about the underlying functional cortical architecture, and whether single EFP trials provide enough information on the short timescales relevant for many clinical and basic neuroscience purposes. We used the high spatial resolution of primary visual cortex to address these issues and investigated the extent to which very short EFP traces allow reliable decoding of spatial information. We briefly presented different visual objects at one of nine closely adjacent locations and recorded neuronal activity with a high-density epidural multielectrode array in three macaque monkeys. With the use of receiver operating characteristics (ROC) to identify the most informative data, machine-learning algorithms provided close-to-perfect classification rates for all 27 stimulus conditions. A binary classifier applying a simple max function on ROC-selected data further showed that single trials might be classified with 100% performance even without advanced offline classifiers. Thus, although highly variable, EFPs constitute an extremely valuable source of information and offer new perspectives for minimally invasive recording of large-scale networks.NEW & NOTEWORTHY Epidural field potential (EFP) recordings provide a minimally invasive approach to investigate large-scale neural networks, but little is known about whether they possess the required specificity for basic and clinical neuroscience. By making use of the spatial selectivity of primary visual cortex, we show that single-trial information can be decoded with close-to-perfect performance, even without using advanced classifiers and based on very few data. This labels EFPs as a highly attractive and widely usable signal.

Optimizing the Yield of Multi-Unit Activity by Including the Entire Spiking Activity

Neurophysiological data acquisition using multi-electrode arrays and/or (semi-) chronic recordings frequently has to deal with low signal-to-noise ratio (SNR) of neuronal responses and potential failure of detecting evoked responses within random background fluctuations. Conventional methods to extract action potentials (spikes) from background noise often apply thresholds to the recorded signal, usually allowing reliable detection of spikes when data exhibit a good SNR, but often failing when SNR is poor. We here investigate a threshold-independent, fast, and automated procedure for analysis of low SNR data, based on fullwave-rectification and low-pass filtering the signal as a measure of the entire spiking activity (ESA). We investigate the sensitivity and reliability of the ESA-signal for detecting evoked responses by applying an automated receptive field (RF) mapping procedure to semi-chronically recorded data from primary visual cortex (V1) of five macaque monkeys. For recording sites with low SNR, the usage of ESA improved the detection rate of RFs by a factor of 2.5 in comparison to MUA-based detection. For recording sites with medium and high SNR, ESA delivered 30% more RFs than MUA. This significantly higher yield of ESA-based RF-detection still hold true when using an iterative procedure for determining the optimal spike threshold for each MUA individually. Moreover, selectivity measures for ESA-based RFs were quite compatible with MUA-based RFs. Regarding RF size, ESA delivered larger RFs than thresholded MUA, but size difference was consistent over all SNR fractions. Regarding orientation selectivity, ESA delivered more sites with significant orientation-dependent responses but with somewhat lower orientation indexes than MUA. However, preferred orientations were similar for both signal types. The results suggest that ESA is a powerful signal for applications requiring automated, fast, and reliable response detection, as e.g., brain-computer interfaces and neuroprosthetics, due to its high sensitivity and its independence from user-dependent intervention. Because the full information of the spiking activity is preserved, ESA also constitutes a valuable alternative for offline analysis of data with limited SNR.

Precision of T2 TSE MRI-CT-image fusions based on gold fiducials and repetitive T2 TSE MRI-MRI-fusions for adaptive IGRT of prostate cancer by using phantom and patient data

INTRODUCTION

To increase precision of radiation treatment (RT) delivery in prostate cancer, MRI-based RT as well as the use of fiducials like gold markers (GMs) have shown promising results. Their combined use is currently under investigation in clinical trials. Here, we aimed to evaluate a workflow of image registration based on GMs between CT and MRI as well as weekly MRI-MRI adaption based on T2 TSE sequence.

MATERIAL AND METHODS

A gel-phantom with two inserted GMs was scanned with CT and three different MR-scanners of 1.5 and 3 T (T2 TSE and T1 VIBE-Dixon, isotropic, voxel size 2 × 2 × 2 mm). After image fusion, deviations for fiducial and gel match were measured and artifacts were evaluated. Additionally, CT-MRI-match deviations and MRI-MRI-match deviations of 10 Patients from the M-basePro study using GMs were assessed.

RESULTS

GMs were visible in all imaging modalities. The outer gel contours were matched with <1 mm deviation, contour volumes varied between 0 and 1%. The deviations of the GMs were less than 2 mm in any direction of MRI/CT. Shifts of peripherally or centrally located GMs were randomly distributed. The average MRI-CT-match precision of 10 patients with GMs was 1.9 mm (range 1.1-3.1 mm).

CONCLUSIONS

Match inaccuracies for GMs between reference CT and voxel-isotropic T2-TSE sequences are small. Spatial deviations of CT- and MR-contoured fiducials were less than 2 mm, i.e., below SLT of the applied modalities. In patients, the average CT-MRI-match precision for GMs was 1.9 mm supporting their use in MR-guided high precision RT.

Emphasizing the "positive" in positive reinforcement: using nonbinary rewarding for training monkeys on cognitive tasks

Nonhuman primates constitute an indispensable model system for studying higher brain functions at the neurophysiological level. Studies involving these animals elucidated the neuronal mechanisms of various cognitive and executive functions, such as visual attention, working memory, and decision-making. Positive reinforcement training (PRT) constitutes the gold standard for training animals on the cognitive tasks employed in these studies. In the laboratory, PRT is usually based on application of a liquid reward as the reinforcer to strengthen the desired behavior and absence of the reward if the animal's response is wrong. By trial and error, the monkey may adapt its behavior and successfully reduce the number of error trials, and eventually learn even very sophisticated tasks. However, progress and success of the training strongly depend on reasonable error rates. If errors get too frequent, they may cause a drop in the animal's motivation to cooperate or its adaptation to high error rates and poor overall performance. We introduce in this report an alternative training regime to minimize errors and base the critical information for learning on graded rewarding. For every new task rule, the feedback to the animal is provided by different amounts of reward to distinguish the desired, optimal behavior from less optimal behavior. We applied this regime in different situations during training of visual attention tasks and analyzed behavioral performance and reaction times to evaluate its effectiveness. For both simple and complex behaviors, graded rewarding was found to constitute a powerful technique allowing for effective training without trade-off in accessible task difficulty or task performance. NEW & NOTEWORTHY Laboratory training of monkeys usually builds on providing a fixed amount of reward for the desired behavior, and no reward otherwise. We present a nonbinary, graded reward schedule to emphasize the positive, desired behavior and to keep errors on a moderate level. Using data from typical training situations, we demonstrate that graded rewards help to effectively guide the animal by success rather than errors and provide a powerful new tool for positive reinforcement training.

Determination of the strong coupling constant α s ( m Z ) in next-to-next-to-leading order QCD using H1 jet cross section measurements: H1 Collaboration

The strong coupling constant α s is determined from inclusive jet and dijet cross sections in neutral-current deep-inelastic ep scattering (DIS) measured at HERA by the H1 collaboration using next-to-next-to-leading order (NNLO) QCD predictions. The dependence of the NNLO predictions and of the resulting value ofα s ( m Z ) at the Z-boson mass m Z are studied as a function of the choice of the renormalisation and factorisation scales. Using inclusive jet and dijet data together, the strong coupling constant is determined to beα s ( m Z ) = 0.1157 ( 20 ) exp ( 29 ) th . Complementary,α s ( m Z ) is determined together with parton distribution functions of the proton (PDFs) from jet and inclusive DIS data measured by the H1 experiment. The valueα s ( m Z ) = 0.1142 ( 28 ) tot obtained is consistent with the determination from jet data alone. The impact of the jet data on the PDFs is studied. The running of the strong coupling is tested at different values of the renormalisation scale and the results are found to be in agreement with expectations.

Task-specific, dimension-based attentional shaping of motion processing in monkey area MT

Nonspatially selective attention is based on the notion that specific features or objects in the visual environment are effectively prioritized in cortical visual processing. Feature-based attention (FBA), in particular, is a well-studied process that dynamically and selectively addresses neurons preferentially processing the attended feature attribute (e.g., leftward motion). In everyday life, however, behavior may require high sensitivity for an entire feature dimension (e.g., motion), but experimental evidence for a feature dimension-specific attentional modulation on a cellular level is lacking. Therefore, we investigated neuronal activity in macaque motion-selective mediotemporal area (MT) in an experimental setting requiring the monkeys to detect either a motion change or a color change. We hypothesized that neural activity in MT is enhanced when the task requires perceptual sensitivity to motion. In line with this, we found that mean firing rates were higher in the motion task and that response variability and latency were lower compared with values in the color task, despite identical visual stimulation. This task-specific, dimension-based modulation of motion processing emerged already in the absence of visual input, was independent of the relation between the attended and stimulating motion direction, and was accompanied by a spatially global reduction of neuronal variability. The results provide single-cell support for the hypothesis of a feature dimension-specific top-down signal emphasizing the processing of an entire feature class.NEW & NOTEWORTHY Cortical processing serving visual perception prioritizes information according to current task requirements. We provide evidence in favor of a dimension-based attentional mechanism addressing all neurons that process visual information in the task-relevant feature domain. Behavioral tasks required monkeys to attend either color or motion, causing modulations of response strength, variability, latency, and baseline activity of motion-selective monkey area MT neurons irrespective of the attended motion direction but specific to the attended feature dimension.

25th Annual Computational Neuroscience Meeting: CNS-2016

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

Human feature-based attention consists of two distinct spatiotemporal processes

In human and nonhuman primates, goal-directed behavior requires the selection of relevant pieces of information from the multitude of simultaneous sensory inputs. Feature-based attention (FBA) plays a crucial role in this selection by improving the neuronal representation of an attended stimulus feature. Of particular interest for understanding the neuronal mechanisms behind FBA is the processing fate of spatially unattended stimuli, either sharing the attended feature attribute or belonging to the attended or to a nonattended feature dimension. Using a wide range of cue/stimulus combinations, we investigated event-related potentials from the human brain, recorded under conditions of different feature attention but constant visual stimulation. We found that neural processing of visual stimuli sharing the dimension or the attribute of the attended target is associated with two distinct spatiotemporal processes, particularly prominent during the selection negativity period. Dimension-based modulation of neural signals first emerged over frontal electrode sites, and temporally preceded and accompanied attribute-specific FBA effects at occipital, parieto-occipital, and parietal electrodes. The findings suggest a process of FBA that not only increases responses of those neurons particularly tuned to the attended attribute but also modulates activity in the cortical module that is selective for the feature dimension to which the attended attribute belongs.

Activism on rifapentine pricing: removing cost barriers to improve the uptake of tuberculosis research innovations

As recent advances have been made in developing tools to fight tuberculosis (TB), there is also a trend towards increasing advocacy by the civil society for TB research and access. One recent successful effort to increase access to treatment options for TB involved a collaborative effort to identify the need for and barriers to the use of rifapentine (RPT) use in the United States. Survey responses confirmed the under-utilization of RPT: 82% of survey respondents selected cost as a significant or potential barrier to use. Survey results provided data to support a year-long advocacy campaign urging the drug company Sanofi to lower the price of RPT. This campaign was based on a common evidence base built in part by the stakeholders themselves. After multiple engagements with communities and providers, Sanofi US announced on 12 December 2013 that they would drop the price of RPT to US$32 per blister pack of 32 tablets for US public health programs. While further work remains to secure access to RPT in the United States and worldwide, the lowering of the price of RPT reflects the positive impact that collaborative advocacy can accomplish, and sets an example for other drug companies to follow.

Transient activity in monkey area MT represents speed changes and is correlated with human behavioral performance

Neurons in the middle temporal area (MT) respond to motion onsets and speed changes with a transient-sustained firing pattern. The latency of the transient response has recently been shown to correlate with reaction time in a speed change detection task, but it is not known how the sign, the amplitude, and the latency of this response depend on the sign and the magnitude of a speed change, and whether these transients can be decoded to explain speed change detection behavior. To investigate this issue, we measured the neuronal representation of a wide range of positive and negative speed changes in area MT of fixating macaques and obtained three major findings. First, speed change transients not only reflect a neuron's absolute speed tuning but are shaped by an additional gain that scales the tuned response according to the magnitude of a relative speed change. Second, by means of a threshold model positive and negative population transients of a moderate number of MT neurons explain detection of both positive and negative speed changes, respectively, at a level comparable to human detection rates under identical visual stimulation. Third, like reaction times in a psychophysical model of velocity detection, speed change response latencies follow a power-law function of the absolute difference of a speed change. Both this neuronal representation and its close correlation with behavioral measures of speed change detection suggest that neuronal transients in area MT facilitate the detection of rapid changes in visual input.

Attentional spreading to task-irrelevant object features: experimental support and a 3-step model of attention for object-based selection and feature-based processing modulation

Directing attention to a specific feature of an object has been linked to different forms of attentional modulation. Object-based attention theory founds on the finding that even task-irrelevant features at the selected object are subject to attentional modulation, while feature-based attention theory proposes a global processing benefit for the selected feature even at other objects. Most studies investigated either the one or the other form of attention, leaving open the possibility that both object- and feature-specific attentional effects do occur at the same time and may just represent two sides of a single attention system. We here investigate this issue by testing attentional spreading within and across objects, using reaction time (RT) measurements to changes of attended and unattended features on both attended and unattended objects. We asked subjects to report color and speed changes occurring on one of two overlapping random dot patterns (RDPs), presented at the center of gaze. The key property of the stimulation was that only one of the features (e.g., motion direction) was unique for each object, whereas the other feature (e.g., color) was shared by both. The results of two experiments show that co-selection of unattended features even occurs when those features have no means for selecting the object. At the same time, they demonstrate that this processing benefit is not restricted to the selected object but spreads to the task-irrelevant one. We conceptualize these findings by a 3-step model of attention that assumes a task-dependent top-down gain, object-specific feature selection based on task- and binding characteristics, and a global feature-specific processing enhancement. The model allows for the unification of a vast amount of experimental results into a single model, and makes various experimentally testable predictions for the interaction of object- and feature-specific processes.

Monkey area MT latencies to speed changes depend on attention and correlate with behavioral reaction times

Selective visual attention is known to be associated with characteristic modulations of neuronal activity in early visual cortex, but there is only rare evidence showing that these neuronal modulations are directly related to attention-dependent behavioral improvements. Here, we describe a strong, transient increase in the response of neurons in the mediotemporal (MT) area to behaviorally relevant speed changes that is not only modulated by attention but also highly correlated with the animal's performance. In trials with fast reaction time (RT), this transient component occurs with short latency, whereas latency increases monotonically with slower RT. Importantly, RTs are related not to the firing rate modulation during sustained attentive tracking of the target prior to the speed change but to the variability of the neuronal response. Our findings suggest a direct link between attention-dependent response modulations in early visual cortex and improved behavioral performance.

p-Medicine: From data sharing and integration via VPH models to personalized medicine

The Worldwide innovative Networking in personalized cancer medicine (WIN) initiated by the Institute Gustave Roussy (France) and The University of Texas MD Anderson Cancer Center (USA) has dedicated its 3rd symposium (Paris, 6-8 July 2011) to discussion on gateways to increase the efficacy of cancer diagnostics and therapeutics (http://www.winconsortium.org/symposium.html).Speakers ranged from clinical oncologist to researchers, industrial partners, and tools developers; a famous patient was present: Janelle Hail, a 30-year breast cancer survivor, founder and CEO of the National Breast Cancer Foundation, Inc. (NBCF).The p-medicine consortium found this venue a perfect occasion to present a poster about its activities that are in accordance with the take home message of the symposium.In this communication, we summarize what we presented with particular attention to the interaction between the symposium's topic and content and our project.

A new type of recording chamber with an easy-to-exchange microdrive array for chronic recordings in macaque monkeys

In monkeys, long-term recordings with chronically implanted microelectrodes frequently suffer from a continuously decreasing probability to record single units or even small multiunit clusters. This problem is associated with two technical limitations of the available devices: first, restrictions for electrode movement, and second, absent possibility to exchange electrodes easily on a regular basis. Permitting to adjust the recording site and to use new recording tracks with proper electrodes may avoid these problems and make chronic more similar to acute recordings. Here, we describe a novel type of implant tackling this issue. It consists of a new type of recording chamber combined with an exchangeable multielectrode array that precisely fits into it. The multielectrode array is reversibly fixed to the chamber, and within a minute it can be exchanged against another array equipped with new electrodes at the awake animal. The array allows for bidirectional movement of six electrodes for a distance of up to 12 mm. The recording chamber enables hermetical isolation of the intracranial space, resulting in long-lasting aseptic conditions and reducing dural thickening to a minimum, as confirmed by microbiological and histopathological analysis. The device has a simple design and is both easy to produce and low in cost. Functionality has been tested in primary and secondary visual cortex of three macaque monkeys over a period of up to 15 mo. The results show that even after more than a year, single and multiunit responses can be obtained with high incidence.

[Connection between hyponatriemia and local herpes in an old lady?]

We report the case of a 84 year old patient who developed a syndrome of inappropriate antidiuretic hormone secretion (SIADH) with severe hyponatremia in the context of a localized herpes zoster L1/2. This is a rare but known complication of localized varizella zoster infection. Under water restriction and salt administration the hyponatremia was corrected slowly. One month after hospital discharge the patient showed a normal sodium value without diet.

Selective visual attention ensures constancy of sensory representations: Testing the influence of perceptual load and spatial competition

We report findings from several variants of a psychophysical experiment using an acceleration detection task in which we tested predictions derived from recent neurophysiological data obtained from monkey area MT. The task was designed as a Posner paradigm and required subjects to detect the speed-up of a moving bar, cued with 75% validity. Displays varied according to number of simultaneously presented objects, spatial distance, and difficulty of the task. All data obtained under different levels of competition with multiple objects were compared to a corresponding condition, in which only a single moving bar was presented in the absence of any interfering distracter object. For attended objects, subjects did not show any difference in their ability to detect accelerations, regardless of the strength of inter-object competition or spatial distance. This finding was consistent in all of the experiments, and was even obtained when the acceleration was made hardly detectable. In contrast, increasing competitive interactions either by enhancing number of objects or spatial proximity resulted in strong reduction of performance for non-attended objects. The findings support current noise reduction models and suggest that attention adjusts neuronal processing to ensure a constant sensory representation of the attended object as if this object was the only one in the scene.

Limits for the central production of Theta+ and Xi(--)pentaquarks in 920-GeV pA collisions

We have searched for Theta+(1540) and Xi(--)(1862) pentaquark candidates in proton-induced reactions on C, Ti, and W targets at midrapidity and square root of s = 41.6 GeV. In 2 x 10(8) inelastic events we find no evidence for narrow (sigma approximately 5 MeV) signals in the Theta+ --> pK0(S) and Xi(--) --> Xi- pi- channels; our 95% C.L. upper limits (UL) for the inclusive production cross section times branching fraction B dsigma/dy/(y approximately 0) are (4-16) mub/N for a Theta+ mass between 1521 and 1555 MeV, and 2.5 mub/N for the Xi(--). The UL of the yield ratio of Theta+/Lambda(1520) < (3-12)% is significantly lower than model predictions. Our UL of B Xi(--)/Xi(1530)0 < 4% is at variance with the results that have provided the first evidence for the Xi(--).

The influence of sustained selective attention on stimulus selectivity in macaque visual area MT

Remarkable alterations of perception during long-lasting attentional processes have been described in several recent studies. Although these findings have gained much interest, almost nothing is known about the modulation of neuronal responses during sustained attention. Therefore, we investigated the effect of prolonged selective attention on neuronal feature selectivity. Awake macaque monkeys were trained to perform a motion-tracking task that required attending one of two simultaneously presented moving bars for up to 15 sec. Extracellular recordings were obtained from neurons in macaque motion-sensitive middle temporal visual area (MT/V5). Under conditions of attention, we found high and constant direction selectivity over time. This was expressed by a strong and persistent response contrast between presentations of preferred and nonpreferred stimuli in successive motion cycles. With attention directed to another moving bar, neuronal responses to the behaviorally irrelevant stimulus became continuously less specific for the direction of motion. In particular, increasingly higher firing rates for motion in null direction caused a strong reduction of direction selectivity, which further increased with enhanced proximity between target and distracter bar. A passive condition experiment revealed that this reduction occurred only when motion remained the behaviorally relevant feature but disappeared when attention was withdrawn from this feature domain. Thus, sustained attention seems to stabilize direction selectivity of neurons in area MT against a time and competition-dependent degradation, whereas nonattended objects suffer from a reduced neuronal representation.

The influence of guiding equipment and stents on the beta dose distribution in the brachytherapy of in-stent restenosis

BACKGROUND

Intracoronary devices such as stents or guide wires may disturb the dose distribution of beta sources in cardiovascular brachytherapy. As clinical observations indicate that underdosage increases the risk of restenosis, accurate measurements are mandatory to investigate these effects.

METHODS AND RESULTS

Dose perturbation effects of different interventional equipment were systematically determined. Dose distributions of 90Sr-beta line sources were measured by means of a special set-up employing plastic scintillator dosimeters in a water phantom. Shielding effects were found to be 2-5% for single stents and 5-10% for graft stents, stent-in-stent geometries, and guiding catheters. Guide wires close to the source reduced the dose by 25-30%.

CONCLUSIONS

Beta dose perturbation effects of typical stent types are almost negligible and can be corrected by an increased source dwell time if necessary. Guide wires produce effects which are clinically much more important and should therefore be retracted from the irradiation area.

Directed evolution of a (beta alpha)8-barrel enzyme to catalyze related reactions in two different metabolic pathways

Enzymes participating in different metabolic pathways often have similar catalytic mechanisms and structures, suggesting their evolution from a common ancestral precursor enzyme. We sought to create a precursor-like enzyme for N'-[(5'-phosphoribosyl)formimino]-5-aminoimidazole-4-carboxamide ribonucleotide (ProFAR) isomerase (HisA; EC ) and phosphoribosylanthranilate (PRA) isomerase (TrpF; EC ), which catalyze similar reactions in the biosynthesis of the amino acids histidine and tryptophan and have a similar (betaalpha)(8)-barrel structure. Using random mutagenesis and selection, we generated several HisA variants that catalyze the TrpF reaction both in vivo and in vitro, and one of these variants retained significant HisA activity. A more detailed analysis revealed that a single amino acid exchange could establish TrpF activity on the HisA scaffold. These findings suggest that HisA and TrpF may have evolved from an ancestral enzyme of broader substrate specificity and underscore that (betaalpha)(8)-barrel enzymes are very suitable for the design of new catalytic activities.

A high-precision, high-resolution and fast dosimetry system for beta sources applied in cardiovascular brachytherapy

A fast dosimetry system based on plastic scintillator detectors has been developed which allows three-dimensional measurement of the radiation field in water of beta-sources appropriate for application in cardiovascular brachytherapy. This system fulfills the AAPM Task Group 60 recommendations for dosimetry of cardiovascular brachytherapy sources. To demonstrate the use of the system, measurements have been performed with an 90Y-wire source. The dose distribution was determined with a spatial resolution of better than 0.2 mm, with only a few minutes needed per scan. The scintillator dosemeter was absolutely calibrated in terms of absorbed dose to water with a precision of +/-7.5%. The relative precision achievable is +/-2.5%. The response of the system is linear within +/-2% for dose rates from 0.5 mGy s(-1) to 500 mGy s(-1).

Fluorescence 125I eye applicator

A new approach to optimize curative eye plaque brachytherapy is presented. The application of ophthalmic plaques is a common therapy modality for small and medium sized intraocular tumors. At Essen University Hospital eye applicators with photon emitting 125I seeds are used for the treatment of tumors with a thickness from 5 to 10 mm. Our clinical experiences indicate that the dose distributions of these applicators-used so far worldwide-are not optimal. A steeper dose falloff would meet the radiobiological requirements better, to provide the eradication of all tumor cells as well as sufficient occlusion of tumor supplying blood vessels. Our investigations for eye plaque optimization are based both on measurements and Monte Carlo simulation. For fast dosimetric measurements we have built a computer controlled device which allows reading out, directly and simultaneously, 16 1 mm3 scintillators. For the numerical simulations of the dose distribution of 125I eye plaques we have adapted a Monte Carlo program originally developed to calculate the synchrotron radiation in particle physics. We have investigated the influence of geometrical as well as physical eye plaque parameters on the dose distribution: Shielding of the primary radiation, penumbra modification, and energy conversion by exploiting fluorescence x-radiation have been considered. New types of fluorescence eye applicators have been designed which are more suitable for the prevention of radiopathic effects on structures at risk.

Characterization of two class II chitinase genes from peanut and expression studies in transgenic tobacco plants

Two different genes encoding class II chitinases from peanut (Arachis hypogaea L. cv. NC4), A.h.Chi2;1 and A.h.Chi2;2, have been cloned. In peanut cell suspension cultures, mRNA levels of A.h.Chi2;2 increased after ethylene or salicylate treatment and in the presence of conidia from Botrytis cinerea. The second gene, A.h.Chi2;1, was only expressed after treatment with the fungal spores. Transgenic tobacco plants containing the complete peanut A.h.Chi2;1 gene exhibited essentially the same expression pattern in leaves as observed in peanut cell cultures. Expression characteristics of transgenic tobacco carrying a promoter-GUS fusion of A.h.Chi2;1 are described.

Expression of a reporter gene is reduced by a ribozyme in transgenic plants

A chimeric gene encoding a ribozyme under the control of the cauliflower mosaic virus (CaMV) 35S promoter was introduced into transgenic tobacco plants. In vivo activity of this ribozyme, which was designed to cleave npt mRNA, was previously demonstrated by transient expression assays in plant protoplasts. The ribozyme gene was transferred into transgenic tobacco plants expressing an rbcS-npt chimeric gene as an indicator. Five double transformants out of sixteen exhibited a reduction in the amount of active NPT enzyme. To measure the amount of ribozyme produced, in the absence of its target, the ribozyme and target genes were separated by genetic segregation. The steady-state concentrations of ribozyme and target RNA were shown to be similar in the resulting single transformants. Direct evidence for a correlation between reduced npt gene expression and ribozyme expression was provided by crossing a plant containing only the ribozyme gene with a transgenic plant expressing the npt gene under control of the 35S promoter, i.e. the same promoter used to direct ribozyme expression. The expression of npt was reduced in all progeny containing both transgenes. Both steady-state levels of npt mRNA and amounts of active NPT enzyme are decreased. In addition, our data indicate that, at least in stable transformants, a large excess of ribozyme over target is not a prerequisite for achieving a significant reduction in target gene expression.

Identification of novel genes specifically expressed in Chlamydomonas reinhardtii zygotes

The maturation of zygotes formed by the fusion of two gametes is the essential part of the diploid phase of the Chlamydomonas reinhardtii sexual life cycle and results in mature zygotes competent to germinate. To understand the molecular mechanisms underlying zygote maturation and the attainment of competence for germination we isolated genomic clones representing three different genes that are specifically expressed in Chlamydomonas reinhardtii zygotes. Accumulation of the RNAs started more than 24 h after mating, setting these genes apart from genes expressed in young zygotes. Upon light-induced germination of zygotes, the mRNAs disappeared. The patterns of RNA accumulation and disappearance were gene-specific and suggested a function of these genes in maturation and/or in initial steps of germination.

Procedures for the Generation of Mature Chlamydomonas reinhardtii Zygotes for Molecular and Biochemical Analyses

Zygotes represent an important stage in the sexual cycle of the unicellular green alga Chlamydomonas reinhardtii. To study zygote germination at a molecular level, a protocol was elaborated for the generation of zygotes in large quantities and a method was developed for the extraction from zygotes of RNA that could be translated in vitro.