25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Neuromodulation of spinal autonomic regulation

The central nervous system is largely responsible for receiving sensory information from the environment and determining motor output. Yet, centrally-derived behavior and sensation depends on the optimal maintenance of the cells, tissues, and organs that feed and support these functions. Most of visceral regulation occurs without conscious oversight, making the spinal cord a key site for integration and control. How the spinal cord modulates output to our organs, or sensory information from them, is poorly understood. The overall aim of this dissertation was to better understand spinal processing of both visceral sensory information to and sympathetic output from the spinal cord. I first established and validated a HB9-GFP transgenic mouse model that unambiguously identified sympathetic preganglionic neurons (SPNs), the spinal output neurons for the sympathetic nervous system. Using this model, I investigated the electrophysiological similarities and diversity of SPNs, and compared their active and passive membrane properties to those in other animal models. My results indicate that while many of the same characteristics are shared, SPNs are a heterogeneous group that can be differentiated based on their electrophysiological properties. Since descending monoaminergic pathways have particularly dense projections to sympathetic regions of the spinal cord, I next examined the modulatory role that the monoamines have on spinal sympathetic output. While each neuromodulator tested had a unique signature of action, serotonin and norepinephrine appeared to increase the excitability of individual SPNs, while dopamine had more mixed actions. Since many autonomic reflexes are integrated by the spinal cord, I also questioned whether these reflexes would be similarly modulated. I therefore developed a novel in vitro spinal cord and sympathetic chain preparation, which allowed for the investigation of visceral afferent-mediated reflexes and their neuromodulation by monoamines. This preparation exposed a dichotomy of action, where sympathetic and somatic motor output is generally enhanced by the monoamines, but reflexes mediated by visceral input are depressed. Utilizing the spinal cord and sympathetic chain preparation, I also investigated how the spinal cord modulates visceral sensory information. One of the most powerful means of selectively inhibiting afferent information from reaching the spinal cord is presynaptic inhibition. I hypothesized that both spinal visceral afferents and descending monoaminergic systems would depress transmission of visceral afferents to the spinal cord. My results demonstrated that activity in spinal visceral afferents can lead to spinally generated presynaptic inhibition, and that in addition to depressing synaptic transmission to the spinal cord, the monoamines also depress the intrinsic circuitry that generates this activity-dependent presynaptic inhibition. Taken together, my results indicate that descending monoaminergic pathways act to limit the amount of visceral sensory information reaching the central nervous system and increase sympathetic output, resulting in an uncoupling of output from visceral sensory input and transitioning to a feed-forward, sympathetically dominant control strategy. This combination offers complex modulatory strategies for descending systems.PhDCommittee Chair: Hochman, Shawn; Committee Member: Nichols, Richard T; Committee Member: Schramm, Lawrence; Committee Member: Shinohara, Minoru; Committee Member: Tansey, Keit

29th Annual Computational Neuroscience Meeting: CNS*2020

Meeting abstracts This publication was funded by OCNS. The Supplement Editors declare that they have no competing interests. Virtual | 18-22 July 202

Influence of the dentritic morphology on electrophysiological responses of thalamocortical neurons

Les neurones thalamiques de relai ont un rôle exclusif dans la transformation et de transfert de presque toute l'information sensorielle dans le cortex. L'intégration synaptique et la réponse électrophysiologique des neurones thalamiques de relai sont déterminées non seulement par l’état du réseau impliqué, mais ils sont également contrôlés par leurs propriétés intrinsèques tels les divers canaux ioniques voltage-dépendants ainsi que l’arborisation dendritique élaboré. Par conséquent, investiguer sur le profil complexe de morphologie dendritique et sur les propriétés dendritiques actives révèle des renseignements importants sur la fonction d'entrée-sortie de neurones thalamiques de relai. Dans cette étude, nous avons reconstruit huit neurones thalamocorticaux (TC) du noyau VPL de chat adulte. En se basant sur ces données morphologiques complètes, nous avons développé plusieurs modèles multicompartimentaux afin de trouver un rôle potentiellement important des arbres dendritiques des neurones de TC dans l'intégration synaptique et l’intégration neuronale. L'analyse des caractéristiques morphologiques des neurones TC accordent des valeurs précises à des paramètres géométriques semblables ou différents de ceux publiés antérieurement. En outre, cette analyse fait ressortir de tous nouveaux renseignements concernant le patron de connectivité entre les sections dendritiques telles que l'index de l'asymétrie et la longueur de parcours moyen (c'est-à-dire, les paramètres topologiques). Nous avons confirmé l’étendue des valeurs rapportée antérieurement pour plusieurs paramètres géométriques tels que la zone somatique (2956.24±918.89 m2), la longueur dendritique totale (168017.49±4364.64 m) et le nombre de sous-arbres (8.3±1.5) pour huit neurones TC. Cependant, contrairement aux données rapportées antérieurement, le patron de ramification dendritique (avec des cas de bifurcation 98 %) ne suit pas la règle de puissance de Rall 3/2 pour le ratio géométrique (GR), et la valeur moyenne de GR pour un signal de propagation est 2,5 fois plus grande que pour un signal rétropropagé. Nous avons également démontré une variabilité significative dans l'index de symétrie entre les sous-arbres de neurones TC, mais la longueur du parcours moyen n'a pas montré une grande variation à travers les ramifications dendritiques des différents neurones. Nous avons examiné la conséquence d’une distribution non-uniforme des canaux T le long de l'arbre dendritique sur la réponse électrophysiologique émergeante, soit le potentiel Ca 2+ à seuil bas (low-threshold calcium spike, LTS) des neurones TC. En appliquant l'hypothèse du «coût minimal métabolique», nous avons constaté que le neurone modélisé nécessite un nombre minimal de canaux-T pour générer un LTS, lorsque les canaux-T sont situés dans les dendrites proximales. Dans la prochaine étude, notre modèle informatique a illustré l'étendue d'une rétropropagation du potentiel d'action et de l'efficacité de la propagation vers des PPSEs générés aux branches dendritiques distales. Nous avons démontré que la propagation dendritique des signaux électriques est fortement contrôlée par les paramètres morphologiques comme illustré par les différents paliers de polarisation obtenus par un neurone à équidistance de soma pendant la propagation et la rétropropagation des signaux électriques. Nos résultats ont révélé que les propriétés géométriques (c.-à-d. diamètre, GR) ont un impact plus fort sur la propagation du signal électrique que les propriétés topologiques. Nous concluons que (1) la diversité dans les propriétés morphologiques entre les sous-arbres d'un seul neurone TC donne une capacité spécifique pour l'intégration synaptique et l’intégration neuronale des différents dendrites, (2) le paramètre géométrique d'un arbre dendritique fournissent une influence plus élevée sur le contrôle de l'efficacité synaptique et l'étendue du potentiel d'action rétropropagé que les propriétés topologiques, (3) neurones TC suivent le principe d’optimisation pour la distribution de la conductance voltage-dépendant sur les arbres dendritiques.Thalamic relay neurons have an exclusive role in processing and transferring nearly all sensory information into the cortex. The synaptic integration and the electrophysiological response of thalamic relay neurons are determined not only by a state of the involved network, but they are also controlled by their intrinsic properties; such as diverse voltage-dependent ionic channels as well as by elaborated dendritic arborization. Therefore, investigating the complex pattern of dendritic morphology and dendritic active properties reveals important information on the input-output function of thalamic relay neurons. In this study, we reconstructed eight thalamocortical (TC) neurons from the VPL nucleus of adult cats. Based on these complete morphological data, we developed several multi-compartment models in order to find a potentially important role for dendritic trees of TC neurons in the synaptic integration and neuronal computation. The analysis of morphological features of TC neurons yield precise values of geometrical parameters either similar or different from those previously reported. In addition, this analysis extracted new information regarding the pattern of connectivity between dendritic sections such as asymmetry index and mean path length (i.e., topological parameters). We confirmed the same range of previously reported value for several geometric parameters such as the somatic area (2956.24±918.89 m2), the total dendritic length (168017.49±4364.64 m) and the number of subtrees (8.3±1.5) for eight TC neurons. However, contrary to previously reported data, the dendritic branching pattern (with 98% bifurcation cases) does not follow Rall’s 3/2 power rule for the geometrical ratio (GR), and the average GR value for a forward propagation signal was 2.5 times bigger than for a backward propagating signal. We also demonstrated a significant variability in the symmetry index between subtrees of TC neurons, but the mean path length did not show a large variation through the dendritic arborizations of different neurons. We examined the consequence of non-uniform distribution of T-channels along the dendritic tree on the prominent electrophysiological response, the low-threshold Ca2+ spike (LTS) of TC neurons. By applying the hypothesis of “minimizing metabolic cost”, we found that the modeled neuron needed a minimum number of T-channels to generate low-threshold Ca2+ spike (LTS), when T-channels were located in proximal dendrites. In the next study, our computational model illustrated the extent of an action potential back propagation and the efficacy of forward propagation of EPSPs arriving at the distal dendritic branches. We demonstrated that dendritic propagation of electrical signals is strongly controlled by morphological parameters as shown by different levels of polarization achieved by a neuron at equidistance from the soma during back and forward propagation of electrical signals. Our results revealed that geometrical properties (i.e. diameter, GR) have a stronger impact on the electrical signal propagation than topological properties. We conclude that (1) diversity in the morphological properties between subtrees of a single TC neuron lead to a specific ability for synaptic integration and neuronal computation of different dendrites, (2) geometrical parameter of a dendritic tree provide higher influence on the control of synaptic efficacy and the extent of the back propagating action potential than topological properties, (3) TC neurons follow the optimized principle for distribution of voltage-dependent conductance on dendritic trees