Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

It is well known that attentional selection of relevant information relies on local synchronization of alpha band neuronal oscillations in visual cortices for inhibition of distracting inputs. Additionally, evidence for long-range coupling of neuronal oscillations between visual cortices and regions engaged in the anticipation of upcoming stimuli has been more recently provided. Nevertheless, on the one hand the relation between long-range functional coupling and anatomical connections is still to be assessed, and, on the other hand, the specific role of the alpha and beta frequency bands in the different processes underlying visuo-spatial attention still needs further clarification. We address these questions using measures of linear (frequency-specific) and nonlinear (cross-frequency) phase-synchronization in a cohort of 28 healthy subjects using magnetoencephalography. We show that alpha band phase-synchronization is modulated by the orienting of attention according to a parieto-occipital top-down mechanism reflecting behavior, and its hemispheric asymmetry is predicted by volume's asymmetry of specific tracts of the Superior-Longitudinal-Fasciculus. We also show that a network comprising parietal regions and the right putative Frontal-Eye-Field, but not the left, is recruited in the deployment of spatial attention through an alpha-beta cross-frequency coupling. Overall, we demonstrate that the visuospatial attention network features subsystems indexed by characteristic spectral fingerprints, playing different functional roles in the anticipation of upcoming stimuli and with diverse relation to fiber tracts.

Motivation exerts control over behavior by eliciting Pavlovian responses, which can either match or conflict with instrumental action. We can overcome maladaptive motivational influences putatively through frontal cognitive control. However, the neurocomputational mechanisms subserving this control are unclear; does control entail up-regulating instrumental systems, down-regulating Pavlovian systems, or both? We combined electroencephalography (EEG) recordings with a motivational Go/NoGo learning task (N = 34), in which multiple Go options enabled us to disentangle selective action learning from nonselective Pavlovian responses. Midfrontal theta-band (4 Hz-8 Hz) activity covaried with the level of Pavlovian conflict and was associated with reduced Pavlovian biases rather than reduced instrumental learning biases. Motor and lateral prefrontal regions synchronized to the midfrontal cortex, and these network dynamics predicted the reduction of Pavlovian biases over and above local, midfrontal theta activity. This work links midfrontal processing to detecting Pavlovian conflict and highlights the importance of network processing in reducing the impact of maladaptive, Pavlovian biases.

Low-frequency neural entrainment to rhythmic input has been hypothesized as a canonical mechanism that shapes sensory perception in time. Neural entrainment is deemed particularly relevant for speech analysis, as it would contribute to the extraction of discrete linguistic elements from continuous acoustic signals. However, its causal influence in speech perception has been difficult to establish. Here, we provide evidence that oscillations build temporal predictions about the duration of speech tokens that affect perception. Using magnetoencephalography (MEG), we studied neural dynamics during listening to sentences that changed in speech rate. We observed neural entrainment to preceding speech rhythms persisting for several cycles after the change in rate. The sustained entrainment was associated with changes in the perceived duration of the last word's vowel, resulting in the perception of words with different meanings. These findings support oscillatory models of speech processing, suggesting that neural oscillations actively shape speech perception.

Oscillatory activity in the alpha and gamma bands is considered key in shaping functional brain architecture. Power increases in the high-frequency gamma band are typically reported in parallel to decreases in the low-frequency alpha band. However, their functional significance and in particular their interactions are not well understood. The present study shows that, in the context of an N-back working memory task, alpha power decreases in the dorsal visual stream are related to gamma power increases in early visual areas. Granger causality analysis revealed directed interregional interactions from dorsal to ventral stream areas, in accordance with task demands. Present results reveal a robust, behaviorally relevant, and architectonically decisive power-to-power relationship between alpha and gamma activity. This relationship suggests that anatomically distant power fluctuations in oscillatory activity can link cerebral network dynamics on trial-by-trial basis during cognitive operations such as working memory.

Although the mammalian neocortex has a clear laminar organization, layer-specific neuronal computations remain to be uncovered. Several studies suggest that gamma band activity in primary visual cortex (V1) is produced in granular and superficial layers and is associated with the processing of visual input. Oscillatory alpha band activity in deeper layers has been proposed to modulate neuronal excitability associated with changes in arousal and cognitive factors. To investigate the layer-specific interplay between these two phenomena, we characterized the coupling between alpha and gamma band activity of the local field potential in V1 of the awake macaque. Using multicontact laminar electrodes to measure spontaneous signals simultaneously from all layers of V1, we found a robust coupling between alpha phase in the deeper layers and gamma amplitude in granular and superficial layers. Moreover, the power in the two frequency bands was anticorrelated. Taken together, these findings demonstrate robust interlaminar cross-frequency coupling in the visual cortex, supporting the view that neuronal activity in the alpha frequency range phasically modulates processing in the cortical microcircuit in a top-down manner.

Spatial attention provides a mechanism for, respectively, enhancing relevant and suppressing irrelevant information. While it is well established that attention modulates oscillations in the alpha band, it remains unclear if alpha oscillations are involved in directly modulating the neuronal excitability associated with the allocation of spatial attention. In this study, in humans, we utilized a novel broadband frequency (60-70 Hz) tagging paradigm to quantify neuronal excitability in relation to alpha oscillations in a spatial attention paradigm. We used magnetoencephalography to characterize ongoing brain activity as it allows for localizing the sources of both the alpha and frequency tagging responses. We found that attentional modulation of alpha power and the frequency tagging response are uncorrelated over trials. Importantly, the neuronal sources of the tagging response were localized in early visual cortex (V1) whereas the sources of the alpha activity were identified around parieto-occipital sulcus. Moreover, we found that attention did not modulate the latency of the frequency tagged responses. Our findings point to alpha band oscillations serving a downstream gating role rather than implementing gain control of excitability in early visual regions.

Food deprivation is known to trigger hunger sensation and motivation to eat for energy replenishing. However, brain mechanisms associated with hunger and neural circuitries that mediate hunger driven responses remained to be investigated. To understand neural signaling of hunger, local field potentials (LFPs) in the lateral hypothalamus (LHa), nucleus accumbens (NAc), dorsal hippocampus (HP) and olfactory bulb (OB) and their interconnectivities were studied in freely moving adult male Albino mice during 18-20 h food deprivation and fed periods. Raw LFP signals were recorded and analyzed for mean values of spectral frequency power and coherence values. One-way repeated measures ANOVA revealed significant increases in spectral powers of beta and gamma frequency ranges induced by food deprivation in the LHa, HP, NAc but not OB. No change of spectral power in these brain regions was induced by food feeding. The analyses of coherent activity between brain regions also deliniated some distributed neural network activities correlated with hunger. In particular, coherent function indicated the increased beta and gamma phase synchrony between the pairs of LHa-HP and NAc-OB regions, and decreased gamma synchrony between the pairs of LHa-NAc and NAc-HP induced by food deprivation. It was found that plasma glucose level, locomotor count, travelled distance and time spent on moving were not altered by food deprivation. These results suggest that changes in LFP hallmarks in these brain regions were associated with hunger driven by negative energy balance.

The human organic cation transporter 1 (OCT1) is expressed in the liver and mediates hepatocellular uptake of organic cations. However, some studies have indicated that OCT1 could transport neutral or even anionic substrates. This capability is interesting concerning protein-substrate interactions and the clinical relevance of OCT1. To better understand the transport of neutral, anionic, or zwitterionic substrates, we used HEK293 cells overexpressing wild-type OCT1 and a variant in which we changed the putative substrate binding site (aspartate474) to a neutral amino acid. The uncharged drugs trimethoprim, lamivudine, and emtricitabine were good substrates of hOCT1. However, the uncharged drugs zalcitabine and lamotrigine, and the anionic levofloxacin, and prostaglandins E2 and F2α, were transported with lower activity. Finally, we could detect only extremely weak transport rates of acyclovir, ganciclovir, and stachydrine. Deleting aspartate474 had a similar transport-lowering effect on anionic substrates as on cationic substrates, indicating that aspartate474 might be relevant for intra-protein, rather than substrate-protein, interactions. Cellular uptake of the atypical substrates by the naturally occurring frequent variants OCT1*2 (methionine420del) and OCT1*3 (arginine61cysteine) was similarly reduced, as it is known for typical organic cations. Thus, to comprehensively understand the substrate spectrum and transport mechanisms of OCT1, one should also look at organic anions.

Brain-computer interfaces (BCI) based on steady-state visual evoked potentials (SSVEPs/SSVEFs) are among the most commonly used BCI systems. They require participants to covertly attend to visual objects flickering at specified frequencies. The attended location is decoded online by analysing the power of neuronal responses at the flicker frequency.

Sustained attention has long been thought to benefit perception in a continuous fashion, but recent evidence suggests that it affects perception in a discrete, rhythmic way. Periodic fluctuations in behavioral performance over time, and modulations of behavioral performance by the phase of spontaneous oscillatory brain activity point to an attentional sampling rate in the theta or alpha frequency range. We investigated whether such discrete sampling by attention is reflected in periodic fluctuations in the decodability of visual stimulus orientation from magnetoencephalographic (MEG) brain signals. In this exploratory study, human subjects attended one of the two grating stimuli, while MEG was being recorded. We assessed the strength of the visual representation of the attended stimulus using a support vector machine (SVM) to decode the orientation of the grating (clockwise vs. counterclockwise) from the MEG signal. We tested whether decoder performance depended on the theta/alpha phase of local brain activity. While the phase of ongoing activity in the visual cortex did not modulate decoding performance, theta/alpha phase of activity in the frontal eye fields and parietal cortex, contralateral to the attended stimulus did modulate decoding performance. These findings suggest that phasic modulations of visual stimulus representations in the brain are caused by frequency-specific top-down activity in the frontoparietal attention network, though the behavioral relevance of these effects could not be established.

Psychostimulants are used therapeutically and for illegal recreational purposes. Many of these are inhibitors of the presynaptic noradrenaline, dopamine, and serotonin transporters (NET, DAT, and SERT). According to their physicochemical properties, some might also be substrates of polyspecific organic cation transporters (OCTs) that mediate uptake in liver and kidneys for metabolism and excretion. OCT1 is genetically highly polymorphic, with strong effects on transporter activity and expression. To study potential interindividual differences in their pharmacokinetics, 18 psychostimulants and hallucinogens were assessed in vitro for transport by different OCTs as well as by the high-affinity monoamine transporters NET, DAT, and SERT. The hallucinogenic natural compound mescaline was found to be strongly transported by wild-type OCT1 with a K m of 24.3 µM and a v max of 642 pmol × mg protein-1 × min-1. Transport was modestly reduced in variants *2 and *7, more strongly reduced in *3 and *4, and lowest in *5 and *6, while *8 showed a moderately increased transport capacity. The other phenylethylamine derivatives methamphetamine, para-methoxymethamphetamine, (-)-ephedrine, and cathine ((+)-norpseudoephedrine), as well as dimethyltryptamine, were substrates of OCT2 with K m values in the range of 7.9-46.0 µM and v max values between 70.7 and 570 pmol × mg protein-1 × min-1. Affinities were similar or modestly reduced and the transport capacities were reduced down to half in the naturally occurring variant A270S. Cathine was found to be a substrate for NET and DAT, with the Km being 21-fold and the v max 10-fold higher for DAT but still significantly lower compared to OCT2. This study has shown that several psychostimulants and hallucinogens are substrates for OCTs. Given the extensive cellular uptake of mescaline by the genetically highly polymorphic OCT1, strong interindividual variation in the pharmacokinetics of mescaline might be possible, which could be a reason for highly variable adverse reactions. The involvement of the polymorphic OCT2 in the renal excretion of several psychostimulants could be one reason for individual differences in toxicity.

Laminar functional magnetic resonance imaging (fMRI) holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded electroencephalography (EEG) and high-resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions in visual cortex. Our results indicate that our task-induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent, alpha band oscillations relate to laminar-specific fMRI connectivity. The differential effects for alpha and beta bands indicate that they relate to different feedback-related neural processes that are differentially expressed in intra-region laminar fMRI-based connectivity.

Human monoamine transporters (MATs) are cation transporters critically involved in neuronal signal transmission. While inhibitors of MATs have been intensively studied, their substrate spectra have received far less attention. Polyspecific organic cation transporters (OCTs), predominantly known for their role in hepatic and renal drug elimination, are also expressed in the central nervous system and might modulate monoaminergic signaling. Using HEK293 cells overexpressing MATs or OCTs, we compared uptake of 48 compounds, mainly phenethylamine and tryptamine derivatives including matched molecular pairs, across noradrenaline, dopamine and serotonin transporters and OCTs (1, 2, and 3). Generally, MATs showed surprisingly high transport activities for numerous analogs of neurotransmitters, but their substrate spectra were limited by molar mass. Human OCT2 showed the broadest substrate spectrum, and also the highest overlap with MATs substrates. Comparative kinetic analyses revealed that the radiotracer meta-iodobenzylguanidine had the most balanced uptake across all six transporters. Matched molecular pair analyses comparing MAT and OCT uptake using the same methodology could provide a better understanding of structural determinants for high cell uptake by MATs or OCTs. The data may result in a better understanding of pharmacokinetics and toxicokinetics of small molecular organic cations and, possibly, in the development of more specific radiotracers for MATs.

It has been demonstrated that alpha activity is lateralized when attention is directed to the left or right visual hemifield. We investigated whether real-time neurofeedback training of the alpha lateralization enhances participants' ability to modulate posterior alpha lateralization and causes subsequent short-term changes in visual detection performance. The experiment consisted of three phases: (i) pre-training assessment, (ii) neurofeedback phase and (iii) post-training assessment. In the pre- and post-training phases we measured the threshold to covertly detect a cued faint Gabor stimulus presented in the left or right hemifield. During magnetoencephalography (MEG) neurofeedback, two face stimuli superimposed with noise were presented bilaterally. Participants were cued to attend to one of the hemifields. The transparency of the superimposed noise and thus the visibility of the stimuli were varied according to the momentary degree of hemispheric alpha lateralization. In a double-blind procedure half of the participants were provided with sham feedback. We found that hemispheric alpha lateralization increased with the neurofeedback training; this was mainly driven by an ipsilateral alpha increase. Surprisingly, comparing pre- to post-training, detection performance decreased for a Gabor stimulus presented in the hemifield that was un-attended during neurofeedback. This effect was not observed in the sham group. Thus, neurofeedback training alters alpha lateralization, which in turn decreases performances in the untrained hemifield. Our findings suggest that alpha oscillations play a causal role for the allocation of attention. Furthermore, our neurofeedback protocol serves to reduce the detection of unattended visual information and could therefore be of potential use for training to reduce distractibility in attention deficit patients, but also highlights that neurofeedback paradigms can have negative impact on behavioral performance and should be applied with caution.

Neuronal synchronization reflected by oscillatory brain activity has been strongly implicated in the mechanisms supporting selective gating. We here aimed at identifying the anatomical pathways in humans supporting the top-down control of neuronal synchronization. We first collected diffusion imaging data using magnetic resonance imaging to identify the medial branch of the superior longitudinal fasciculus (SLF), a white-matter tract connecting frontal control areas to parietal regions. We then quantified the modulations in oscillatory activity using magnetoencephalography in the same subjects performing a spatial attention task. We found that subjects with a stronger SLF volume in the right compared to the left hemisphere (or vice versa) also were the subjects who had a better ability to modulate right compared to left hemisphere alpha and gamma band synchronization, with the latter also predicting biases in reaction time. Our findings implicate the medial branch of the SLF in mediating top-down control of neuronal synchronization in sensory regions that support selective attention.

There have been a number of studies suggesting that oscillatory alpha activity (~10 Hz) plays a pivotal role in attention by gating information flow to relevant sensory regions. The vast majority of these studies have looked at shifts of attention in the spatial domain and only in a single modality (often visual or sensorimotor). In the current magnetoencephalography (MEG) study, we investigated the role of alpha activity in the suppression of a distracting modality stream. We used a cross-modal attention task where visual cues indicated whether participants had to judge a visual orientation or discriminate the auditory pitch of an upcoming target. The visual and auditory targets were presented either simultaneously or alone, allowing us to behaviorally gauge the "cost" of having a distractor present in each modality. We found that the preparation for visual discrimination (relative to pitch discrimination) resulted in a decrease of alpha power (9-11 Hz) in the early visual cortex, with a concomitant increase in alpha/beta power (14-16 Hz) in the supramarginal gyrus, a region suggested to play a vital role in short-term storage of pitch information (Gaab et al., 2003). On a trial-by-trial basis, alpha power over the visual areas was significantly correlated with increased visual discrimination times, whereas alpha power over the precuneus and right superior temporal gyrus was correlated with increased auditory discrimination times. However, these correlations were only significant when the targets were paired with distractors. Our work adds to increasing evidence that the top-down (i.e. attentional) modulation of alpha activity is a mechanism by which stimulus processing can be gated within the cortex. Here, we find that this phenomenon is not restricted to the domain of spatial attention and can be generalized to other sensory modalities than vision.

Recent research has demonstrated that cortical motor areas are engaged when observing motor actions of others. However, little is known about the possible contribution of the motor system for evaluating the correctness of others' actions. To address this question we designed an MEG experiment in which subjects were executing and observing motor actions with and without errors. In the execution task subjects were asked to make speeded button presses according to instruction cues. During the observation task, they viewed pictures of an actor's hand making button presses which were correct or incorrect according to the cues. Time-frequency representations of the MEG data demonstrated a depression in oscillatory activity in the beta band activity (15-35 Hz) during execution followed by a beta rebound that was stronger for incorrect compared to correct executions. During the observation task, a similar time-course of the beta activity was identified and importantly the modulations were stronger for the observation of incorrect than correct actions. Sources accounting for the difference in beta activity between correct and incorrect actions were localized using a beamforming technique. Both for the execution and observation conditions sources were identified to the dorsal motor areas comprising both primary and pre-motor cortex. Our findings demonstrate that not only is cortical motor activity modulated by action observation, but the modulation increases when the observed action is erroneous. This suggests that the motor system is engaged in evaluating the correctness of the actions of others.

Cytotoxic T lymphocyte-associated protein 4 (CTLA-4) is a coinhibitory checkpoint protein expressed on the surface of T cells. A recent study by our working group revealed that the rs231775 single nucleotide polymorphism (SNP) in the CTLA-4 gene was associated with the survival of patients with sepsis and served as an independent prognostic variable. To further investigate the impact of CTLA-4 genetic variants on sepsis survival, we examined the effect of two functional SNPs, CTLA-4 rs733618 and CTLA-4 rs3087243, and inferred haplotypes, on the survival of 644 prospectively enrolled septic patients. Kaplan⁻Meier survival analysis revealed significantly lower 90-day mortality for rs3087243 G allele carriers (n = 502) than for AA-homozygous (n = 142) patients (27.3% vs. 40.8%, p = 0.0024). Likewise, lower 90-day mortality was observed for TAA haplotype-negative patients (n = 197; compound rs733618 T/rs231775 A/rs3087243 A) than for patients carrying the TAA haplotype (n = 447; 24.4% vs. 32.9%, p = 0.0265). Carrying the rs3087243 G allele hazard ratio (HR): 0.667; 95% confidence interval (CI): 0.489⁻0.909; p = 0.0103) or not carrying the TAA haplotype (HR: 0.685; 95% CI: 0.491⁻0.956; p = 0.0262) remained significant covariates for 90-day survival in the multivariate Cox regression analysis and thus served as independent prognostic variables. In conclusion, our findings underscore the significance of CTLA-4 genetic variants as predictors of survival of patients with sepsis.

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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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. 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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. 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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. 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