Socially Mediated Shift in Neural Circuits Activation Regulated by Synergistic Neuromodulatory Signaling

Animals exhibit context-dependent behavioral decisions that are mediated by specific motor circuits. In social species these decisions are often influenced by social status. Although social status-dependent neural plasticity of motor circuits has been investigated in vertebrates, little is known of how cellular plasticity translates into differences in motor activity. Here, we used zebrafish (Danio rerio) as a model organism to examine how social dominance influences the activation of swimming and the Mauthner-mediated startle escape behaviors. We show that the status-dependent shift in behavior patterns whereby dominants increase swimming and reduce sensitivity of startle escape while subordinates reduce their swimming and increase startle sensitivity is regulated by the synergistic interactions of dopaminergic, glycinergic, and GABAergic inputs to shift the balance of activation of the underlying motor circuits. This shift is driven by socially induced differences in expression of dopaminergic receptor type 1b (Drd1b) on glycinergic neurons and dopamine (DA) reuptake transporter (DAT). Second, we show that GABAergic input onto glycinergic neurons is strengthened in subordinates compared with dominants. Complementary neurocomputational modeling of the empirical results show that drd1b functions as molecular regulator to facilitate the shift between excitatory and inhibitory pathways. The results illustrate how reconfiguration in network dynamics serves as an adaptive strategy to cope with changes in social environment and are likely conserved and applicable to other social species.

The Effects of Social Experience on Host Gut Microbiome in Male Zebrafish (Danio rerio)

AbstractAlthough the gut and the brain vastly differ in physiological function, they have been interlinked in a variety of different neurological and behavioral disorders. The bacteria that comprise the gut microbiome communicate and influence the function of various physiological processes within the body, including nervous system function. However, the effects of social experience in the context of dominance and social stress on gut microbiome remain poorly understood. Here, we examined whether social experience impacts the host zebrafish (Danio rerio) gut microbiome. We studied how social dominance during the first 2 weeks of social interactions changed the composition of zebrafish gut microbiome by comparing gut bacterial composition, diversity, and relative abundance between socially dominant, submissive, social isolates and control group-housed communal fish. Using amplicon sequencing of the 16S rRNA gene, we report that social dominance significantly affects host gut bacterial community composition but not bacterial diversity. At the genus level, Aeromonas and unclassified Enterobacteriaceae relative abundance decreased in dominant individuals while commensal bacteria (e.g., Exiguobacterium and Cetobacterium) increased in relative abundance. Conversely, the relative abundance of Psychrobacter and Acinetobacter was increased in subordinates, isolates, and communal fish compared to dominant fish. The shift in commensal and pathogenic bacteria highlights the impact of social experience and the accompanying stress on gut microbiome, with potentially similar effects in other social organisms.

Nuclear androgen and progestin receptors inversely affect aggression and social dominance in male zebrafish (Danio rerio)

Aggression is a fundamental behavior displayed universally among animal species, but hyper- or hypo-aggressiveness can be maladaptive with negative consequences for individuals and group members. While the social and ecological significance of aggression is well understood, the specific neurobiological and hormonal mechanisms responsible for mediating aggression have not been fully elucidated. Previous studies have shown a relationship between aggressive acts and circulating gonadal steroids, but whether classical nuclear steroid receptors regulate aggression in animals is still uncertain. We examined whether the nuclear androgen receptor (Ar) and nuclear progestin receptor (Pgr) were necessary for aggressive behaviors and maintenance of a dominance relationship in male zebrafish (Danio rerio). Dyadic social interactions of Ar knockout (ArKO), Pgr knockout (PgrKO) and wildtype (WT) controls were observed for two weeks (2-weeks). ArKO zebrafish were significantly less aggressive and had a less defined dominance relationship, whereas PgrKO dominant zebrafish were significantly and persistently more aggressive with a robust dominance relationship. Our results demonstrate the importance of nuclear steroid hormone receptors in regulating aggression of adult male zebrafish and provide new models for understanding of the mechanisms of aggression.

Compromised N-Glycosylation Processing of Kv3.1b Correlates with Perturbed Motor Neuron Structure and Locomotor Activity

Neurological difficulties commonly accompany individuals suffering from congenital disorders of glycosylation, resulting from defects in the N-glycosylation pathway. Vacant N-glycosylation sites (N220 and N229) of Kv3, voltage-gated K+ channels of high-firing neurons, deeply perturb channel activity in neuroblastoma (NB) cells. Here we examined neuron development, localization, and activity of Kv3 channels in wildtype AB zebrafish and CRISPR/Cas9 engineered NB cells, due to perturbations in N-glycosylation processing of Kv3.1b. We showed that caudal primary (CaP) motor neurons of zebrafish spinal cord transiently expressing fully glycosylated (WT) Kv3.1b have stereotypical morphology, while CaP neurons expressing partially glycosylated (N220Q) Kv3.1b showed severe maldevelopment with incomplete axonal branching and extension around the ventral musculature. Consequently, larvae expressing N220Q in CaP neurons had impaired swimming locomotor activity. We showed that replacement of complex N-glycans with oligomannose attached to Kv3.1b and at cell surface lessened Kv3.1b dispersal to outgrowths by altering the number, size, and density of Kv3.1b-containing particles in membranes of rat neuroblastoma cells. Opening and closing rates were slowed in Kv3 channels containing Kv3.1b with oligomannose, instead of complex N-glycans, which suggested a reduction in the intrinsic dynamics of the Kv3.1b α-subunit. Thus, N-glycosylation processing of Kv3.1b regulates neuronal development and excitability, thereby controlling motor activity.

Social Experience Regulates Endocannabinoids Modulation of Zebrafish Motor Behaviors

Social status-dependent modulation of neural circuits has been investigated extensively in vertebrate and invertebrate systems. However, the effects of social status on neuromodulatory systems that drive motor activity are poorly understood. Zebrafish form a stable social relationship that consists of socially dominant and subordinate animals. The locomotor behavior patterns differ according to their social ranks. The sensitivity of the Mauthner startle escape response in subordinates increases compared to dominants while dominants increase their swimming frequency compared to subordinates. Here, we investigated the role of the endocannabinoid system (ECS) in mediating these differences in motor activities. We show that brain gene expression of key ECS protein pathways are socially regulated. Diacylglycerol lipase (DAGL) expression significantly increased in dominants and significantly decreased in subordinates relative to controls. Moreover, brain gene expression of the cannabinoid 1 receptor (CB₁R) was significantly increased in subordinates relative to controls. Secondly, increasing ECS activity with JZL184 reversed swimming activity patterns in dominant and subordinate animals. JZL184 did not affect the sensitivity of the startle escape response in dominants while it was significantly reduced in subordinates. Thirdly, blockage of CB₁R function with AM-251 had no effect on dominants startle escape response sensitivity, but startle sensitivity was significantly reduced in subordinates. Additionally, AM-251 did not affect swimming activities in either social phenotypes. Fourthly, we demonstrate that the effects of ECS modulation of the startle escape circuit is mediated via the dopaminergic system specifically via the dopamine D1 receptor. Finally, our empirical results complemented with neurocomputational modeling suggest that social status influences the ECS to regulate the balance in synaptic strength between excitatory and inhibitory inputs to control the excitability of motor behaviors. Collectively, this study provides new insights of how social factors impact nervous system function to reconfigure the synergistic interactions of neuromodulatory pathways to optimize motor output.

Infant and adult SCA13 mutations differentially affect Purkinje cell excitability, maturation, and viability in vivo

Mutations in KCNC3, which encodes the Kv3.3 K⁺ channel, cause spinocerebellar ataxia 13 (SCA13). SCA13 exists in distinct forms with onset in infancy or adulthood. Using zebrafish, we tested the hypothesis that infant- and adult-onset mutations differentially affect the excitability and viability of Purkinje cells in vivo during cerebellar development. An infant-onset mutation dramatically and transiently increased Purkinje cell excitability, stunted process extension, impaired dendritic branching and synaptogenesis, and caused rapid cell death during cerebellar development. Reducing excitability increased early Purkinje cell survival. In contrast, an adult-onset mutation did not significantly alter basal tonic firing in Purkinje cells, but reduced excitability during evoked high frequency spiking. Purkinje cells expressing the adult-onset mutation matured normally and did not degenerate during cerebellar development. Our results suggest that differential changes in the excitability of cerebellar neurons contribute to the distinct ages of onset and timing of cerebellar degeneration in infant- and adult-onset SCA13.

Duality of 5-HT Effects on Crayfish Motoneurons

Serotonin (5-HT) is a major neuromodulator acting on the nervous system. Its various effects have been studied in vertebrates, as well as in arthropods, from the cellular and subcellular compartments up to the behavioral level, which includes the control of mood, aggression, locomotion, and anxiety. The diversity of responses of neurons to 5-HT has been related to its mode of application, the diversity of 5-HT-receptors, and the animals’ social status history. In the locomotor network of socially isolated crayfish, the duality of 5-HT-evoked responses (excitatory/inhibitory) on motoneurons (MNs), sensorimotor pathways, and their consequences on motor network activity has largely been studied. The aim of the present report is to examine if this duality of exogenous 5-HT-evoked responses in the crayfish locomotor network can be reproduced by direct activation of 5-HT neurons in the case of socially isolated animals. Our previous studies have focused on the mechanisms supporting these opposite effects on MNs, pointing out spatial segregation of 5-HT receptors responsible either for positive or negative responses. Here, we report new findings indicating that excitatory and inhibitory effects can be achieved simultaneously in different leg MNs by the activation of a single 5-HT cell in the first abdominal ganglion.

Social Status-Related Differences in Motor Activity Between Wild-Type and Mutant Zebrafish

Use of zebrafish as a model organism in biomedical research has led to the generation of many genetically modified mutant lines to investigate various aspects of developmental and cellular processes. However, the broader effects of the underlying mutations on social and motor behavior remain poorly examined. Here, we compared the dynamics of social interactions in the Tüpfel long-fin nacre mutant line, which lacks skin pigmentation, to wild-type zebrafish; and we determined whether status-dependent differences in escape and swimming behavior existed within each strain. We show that despite similarities in aggressive activity, Tüpfel long-fin nacre pairs exhibit unstable social relationships characterized by frequent reversals in social dominance compared to wild-type pairs. The lack of strong dominance relationships in Tüpfel long-fin nacre pairs correlates with weak territoriality and overlapping spatial distribution of dominants and subordinates. Conversely, wild-type dominants displayed strong territoriality that severely limited the movement of subordinates. Additionally, the sensitivity of the startle escape response was significantly higher in wild-type subordinates compared to dominants. However, status-related differences in sensitivity of escape response in Tüpfel long-fin nacre pairs were absent. Finally, we present evidence suggesting that these differences could be a consequence of a disruption of proper visual social signals. We show that in wild-type pairs dominants are more conspicuous, and that in wild-type and Tüpfel long-fin nacre pairings wild-type fish are more likely to dominate Tüpfel long-fin nacres. Our results serve as a cautionary note in research design when morphologically engineered zebrafish for color differences are utilized in the study of social behavior and central nervous system function.

Effects of Social Experience on the Habituation Rate of Zebrafish Startle Escape Response: Empirical and Computational Analyses

While the effects of social experience on nervous system function have been extensively investigated in both vertebrate and invertebrate systems, our understanding of how social status differentially affects learning remains limited. In the context of habituation, a well-characterized form of non-associative learning, we investigated how the learning processes differ between socially dominant and subordinate in zebrafish (Danio rerio). We found that social status and frequency of stimulus inputs influence the habituation rate of short latency C-start escape response that is initiated by the Mauthner neuron (M-cell). Socially dominant animals exhibited higher habituation rates compared to socially subordinate animals at a moderate stimulus frequency, but low stimulus frequency eliminated this difference of habituation rates between the two social phenotypes. Moreover, habituation rates of both dominants and subordinates were higher at a moderate stimulus frequency compared to those at a low stimulus frequency. We investigated a potential mechanism underlying these status-dependent differences by constructing a simplified neurocomputational model of the M-cell escape circuit. The computational study showed that the change in total net excitability of the model M-cell was able to replicate the experimental results. At moderate stimulus frequency, the model M-cell with lower total net excitability, that mimicked a dominant-like phenotype, exhibited higher habituation rates. On the other hand, the model with higher total net excitability, that mimicked the subordinate-like phenotype, exhibited lower habituation rates. The relationship between habituation rates and characteristics (frequency and amplitude) of the repeated stimulus were also investigated. We found that habituation rates are decreasing functions of amplitude and increasing functions of frequency while these rates depend on social status (higher for dominants and lower for subordinates). Our results show that social status affects habituative learning in zebrafish, which could be mediated by a summative neuromodulatory input to the M-cell escape circuit, which enables animals to readily learn to adapt to changes in their social environment.

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

Rapid development of Purkinje cell excitability, functional cerebellar circuit, and afferent sensory input to cerebellum in zebrafish

The zebrafish has significant advantages for studying the morphological development of the brain. However, little is known about the functional development of the zebrafish brain. We used patch clamp electrophysiology in live animals to investigate the emergence of excitability in cerebellar Purkinje cells, functional maturation of the cerebellar circuit, and establishment of sensory input to the cerebellum. Purkinje cells are born at 3 days post-fertilization (dpf). By 4 dpf, Purkinje cells spontaneously fired action potentials in an irregular pattern. By 5 dpf, the frequency and regularity of tonic firing had increased significantly and most cells fired complex spikes in response to climbing fiber activation. Our data suggest that, as in mammals, Purkinje cells are initially innervated by multiple climbing fibers that are winnowed to a single input. To probe the development of functional sensory input to the cerebellum, we investigated the response of Purkinje cells to a visual stimulus consisting of a rapid change in light intensity. At 4 dpf, sudden darkness increased the rate of tonic firing, suggesting that afferent pathways carrying visual information are already active by this stage. By 5 dpf, visual stimuli also activated climbing fibers, increasing the frequency of complex spiking. Our results indicate that the electrical properties of zebrafish and mammalian Purkinje cells are highly conserved and suggest that the same ion channels, Nav1.6 and Kv3.3, underlie spontaneous pacemaking activity. Interestingly, functional development of the cerebellum is temporally correlated with the emergence of complex, visually-guided behaviors such as prey capture. Because of the rapid formation of an electrically-active cerebellum, optical transparency, and ease of genetic manipulation, the zebrafish has great potential for functionally mapping cerebellar afferent and efferent pathways and for investigating cerebellar control of motor behavior.

Spatial segregation of excitatory and inhibitory effects of 5-HT on crayfish motoneurons

Altering neuronal membrane properties, including input resistance, is a key modulatory mechanism for changing neural activity patterns. The effect of membrane currents generated by either synaptic or voltage-dependent channels directly depends on neuron input resistance. We found that local application of serotonin to different regions of identified motoneurons (MNs) of the postural/walking network of isolated crayfish produced different changes in input resistance. Puff-applied 5-HT in the periphery of the initial segment produced exclusively inhibitory responses. In contrast, when 5-HT was puff-applied on the central arbor of the same depressor (Dep) MN, exclusively depolarizing responses were obtained. Both inhibitory and excitatory responses were direct because they persisted in low-calcium saline. We found numerous close appositions between 5-HT-immunoreactive processes and the initial segment of dextran-rhodamine-filled Dep MNs. In contrast, almost no close apposition sites were found in Dep MN arbor. It seems that the 5-HT controls the level of excitability of postural network MNs by two mechanisms acting at two different sites: inhibitory responses (consistent with an action involving opening of K(+) channels) occur in the initial segment region and may involve classic synaptic transmission, whereas depolarizing responses (consistent with an action involving closing of K(+) channels) occur on MN branches via apparent paracrine effects.

Spinocerebellar ataxia type 13 mutation that is associated with disease onset in infancy disrupts axonal pathfinding during neuronal development

Spinocerebellar ataxia type 13 (SCA13) is an autosomal dominant disease caused by mutations in the Kv3.3 voltage-gated potassium (K⁺) channel. SCA13 exists in two forms: infant onset is characterized by severe cerebellar atrophy, persistent motor deficits and intellectual disability, whereas adult onset is characterized by progressive ataxia and progressive cerebellar degeneration. To test the hypothesis that infant- and adult-onset mutations have differential effects on neuronal development that contribute to the age at which SCA13 emerges, we expressed wild-type Kv3.3 or infant- or adult-onset mutant proteins in motor neurons in the zebrafish spinal cord. We characterized the development of CaP (caudal primary) motor neurons at ∼36 and ∼48 hours post-fertilization using confocal microscopy and 3D digital reconstruction. Exogenous expression of wild-type Kv3.3 had no significant effect on CaP development. In contrast, CaP neurons expressing the infant-onset mutation made frequent pathfinding errors, sending long, abnormal axon collaterals into muscle territories that are normally innervated exclusively by RoP (rostral primary) or MiP (middle primary) motor neurons. This phenotype might be directly relevant to infant-onset SCA13 because interaction with inappropriate synaptic partners might trigger cell death during brain development. Importantly, pathfinding errors were not detected in CaP neurons expressing the adult-onset mutation. However, the adult-onset mutation tended to increase the complexity of the distal axonal arbor. From these results, we speculate that infant-onset SCA13 is associated with marked changes in the development of Kv3.3-expressing cerebellar neurons, reducing their health and viability early in life and resulting in the withered cerebellum seen in affected children.

Neural circuit activity in freely behaving zebrafish (Danio rerio)

Examining neuronal network activity in freely behaving animals is advantageous for probing the function of the vertebrate central nervous system. Here, we describe a simple, robust technique for monitoring the activity of neural circuits in unfettered, freely behaving zebrafish (Danio rerio). Zebrafish respond to unexpected tactile stimuli with short- or long-latency escape behaviors, which are mediated by distinct neural circuits. Using dipole electrodes immersed in the aquarium, we measured electric field potentials generated in muscle during short- and long-latency escapes. We found that activation of the underlying neural circuits produced unique field potential signatures that are easily recognized and can be repeatedly monitored. In conjunction with behavioral analysis, we used this technique to track changes in the pattern of circuit activation during the first week of development in animals whose trigeminal sensory neurons were unilaterally ablated. One day post-ablation, the frequency of short- and long-latency responses was significantly lower on the ablated side than on the intact side. Three days post-ablation, a significant fraction of escapes evoked by stimuli on the ablated side was improperly executed, with the animal turning towards rather than away from the stimulus. However, the overall response rate remained low. Seven days post-ablation, the frequency of escapes increased dramatically and the percentage of improperly executed escapes declined. Our results demonstrate that trigeminal ablation results in rapid reconfiguration of the escape circuitry, with reinnervation by new sensory neurons and adaptive changes in behavior. This technique is valuable for probing the activity, development, plasticity and regeneration of neural circuits under natural conditions.

Ritualized Submission and the Reduction of Aggression in an Invertebrate

Ritualized behaviors that signify acceptance of a dominance relationship and reduce aggression between rivals are a common feature of vertebrate social behavior. Although some invertebrates, including crayfish, lobsters, and ants, display dominance postures, more complex dominance rituals and their effects on fitness have not been reported. We found that crayfish display such a complex ritual, when two males engaged in pseudocopulatory behavior to signify their dominance relationship. This was followed by a reduction in aggression and an increased likelihood of the subordinate's survival. Pseudocopulation was initiated by the eventual dominant and could be accepted or refused by the eventual subordinate. The frequency of aggressive behavior declined significantly during the first hour in all pairs that pseudocopulated but remained high in pairs that did not. Whereas all the subordinate members of pairs that pseudocopulated survived the initial 24 hr of pairing, half of subordinates that did not pseudocopulate were killed during that time. This differential mortality indicates that the reduction of aggression induced by the pseudocopulatory ritual directly enhances the differential survival of male crayfish that engage in this behavior.

The neural basis of dominance hierarchy formation in crayfish

Fifty years of study of the nervous system and behavior of crayfish have revealed neural circuits for movements that are similar to those seen during formation of a dominance hierarchy. Given this background, it is of interest to ask what is understood about the neural substrates of dominance hierarchy formation. Here we will consider the social behavior that crayfish display in the wild and in the laboratory, and its relationship to movements released by activation of specific neural circuits. We will consider how these movements might be knit together to produce the behavior patterns that are characteristic of dominant and subordinate animals.

Patterns of neural circuit activation and behavior during dominance hierarchy formation in freely behaving crayfish

Creation of a dominance hierarchy within a population of animals typically involves a period of agonistic activity in which winning and losing decide relative positions in the hierarchy. Among crayfish, fighting between size-matched animals leads to an abrupt change of behavior as the new subordinate retreats and escapes from the attacks and approaches of the dominant (Issa et al., 1999). We used high-speed videography and electrical recordings of aquarium field potentials to monitor the release of aggressive and defensive behavior, including the activation of neural circuits for four different tail-flip behaviors. We found that the sequence of tail-flip circuit excitation traced the development of their dominance hierarchy. Offensive tail flipping, attacks, and approaches by both animals were followed by a sharp rise in the frequency of nongiant and medial giant escape tail flips and a fall in the frequency of offensive tail flips of the new subordinate. These changes suggest that sudden, coordinated changes in the excitability of a set of neural circuits in one animal produce the changes in behavior that mark its transition to subordinate status.

Dominance hierarchy formation in juvenile crayfish procambarus clarkii

The formation of social dominance hierarchies was studied in groups of five juvenile crayfish, 1.3-1.8 cm in length. Animals were grouped together in a small, featureless aquarium after having lived in isolation for more than a month. The occurrence of each of four behavior patterns (‘attack’, ‘approach’, ‘retreat’ and ‘escape’) was recorded for each animal, together with the frequency of encounters and the frequency of wins and losses. The frequencies of wins and losses were used to calculate the relative dominance value of each animal in the group. High levels of fighting developed immediately upon grouping the animals, and a positive feedback relationship between attacking and winning enabled one animal in each group to emerge quickly as the superdominant. If that animal was the largest, it remained as the superdominant; otherwise, it was replaced as superdominant within the first few days by the largest animal. This form of dominance hierarchy, with one superdominant and four subordinates, persisted throughout the duration of the grouping. Fighting declined over the first hour and by 24 h had dropped to low levels. After the first day, approaches were used together with attacks, and retreats replaced escapes. Attack and approach were the behavior patterns displayed most frequently by animals with high dominance values, whereas retreat and escape were performed by animals of low dominance. All these trends continued to develop over the next 2 weeks as the number of agonistic encounters declined to a low level.