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

Contributions to models of single neuron computation in striatum and cortex

A deeper understanding is required of how a single neuron utilizes its nonlinear subcellular devices to generate complex neuronal dynamics. Two compartmental models of cortex and striatum are accurately formulated and firmly grounded in the experimental reality of electrophysiology to address the questions: how striatal projection neurons implement location-dependent dendritic integration to carry out association-based computation and how cortical pyramidal neurons strategically exploit the type and location of synaptic contacts to enrich its computational capacities.Neuronale Zellen transformieren kontinuierliche Signale in diskrete Zeitserien von Aktionspotentialen und kodieren damit Perzeptionen und interne Zustände. Kompartiment-Modelle werden formuliert von Nervenzellen im Kortex und Striatum, die elektrophysiologisch fundiert sind, um spezifische Fragen zu adressieren: i) Inwiefern implementieren Projektionen vom Striatum ortsabhängige dendritische Integration, um Assoziationens-basierte Berechnungen zu realisieren? ii) Inwiefern nutzen kortikale Zellen den Typ und den Ort, um die durch sie realisierten Berechnungen zu optimieren

Simulations of information processing, control, and plasticity effects in the olfactory bulb

The olfactory system processes complex and varied information in its detection, recognition, and memory of odors. The exact functions that the olfactory bulb plays in this processing is still largely unknown. Studies were performed to help reveal bulb functionality in the olfactory system while contributing to the set of computer methods available for the study of neural systems.One interesting property of bulbar neurons is an increase in primary cell firing thresholds with depth. Since increased odor concentrations generally result in higher frequency inputs to the bulb and thus higher summation levels of primary cell membrane potentials, this threshold gradation transforms the frequency-encoded concentration data into a spatial representation in the number of primary cells responding in a single olfactory bulb glomerular region.Since this transformation relies on temporal summation of post-synaptic potentials (PSPs) to reflect concentration levels, direct physiological modeling of the transformation was possible while providing the added efficiency to permit the simulation of large numbers of cells and synaptic interactions. A novel physiological modeling methodology was developed for these tests that extends the extant physiological models to include time-constant and driving-force interactive effects between post-synaptic inputs. This novel method is derived using linear superposition of inputs to a lumped-circuit cell representation, resulting in a difference-of-exponentials PSP function that is more realistic and flexible than the common empirically-chosen alpha function.Also, the effects that interneuronal dendritic spines have on bulbar inhibitions were tested using biophysical computer simulations of primary-to-granule dendrodendritic reciprocal interactions. The graded strength properties of these synapses showed that reciprocal inhibitions to primary mitral cells are facilitated by the spine structures without the need of a high gain gradation while reducing lateral inhibition to other mitral cells. Furthermore, increases in the neck axial resistance of the synapsed spine further strengthen the reciprocal response and reduce the lateral inhibition; such resistance changes could therefore result in dendrodendritic synaptic plasticities and olfactory memory operations

Dendritic spine geometry and spine apparatus organization govern the spatiotemporal dynamics of calcium.

Dendritic spines are small subcompartments that protrude from the dendrites of neurons and are important for signaling activity and synaptic communication. These subcompartments have been characterized to have different shapes. While it is known that these shapes are associated with spine function, the specific nature of these shape-function relationships is not well understood. In this work, we systematically investigated the relationship between the shape and size of both the spine head and spine apparatus, a specialized endoplasmic reticulum compartment within the spine head, in modulating rapid calcium dynamics using mathematical modeling. We developed a spatial multicompartment reaction-diffusion model of calcium dynamics in three dimensions with various flux sources, including N-methyl-D-aspartate receptors (NMDARs), voltage-sensitive calcium channels (VSCCs), and different ion pumps on the plasma membrane. Using this model, we make several important predictions. First, the volume to surface area ratio of the spine regulates calcium dynamics. Second, membrane fluxes impact calcium dynamics temporally and spatially in a nonlinear fashion. Finally, the spine apparatus can act as a physical buffer for calcium by acting as a sink and rescaling the calcium concentration. These predictions set the stage for future experimental investigations of calcium dynamics in dendritic spines

Computational aspects of parvalbumin-positive interneuron function

The activity of neurons is dependent on the manner in which they process synaptic inputs from other cells. In the event of clustered synaptic input, neurons can respond in a nonlinear manner through synaptic and dendritic mechanisms. Such mechanisms are well established in principal excitatory neurons throughout the brain, where they increase neuronal computational ability and information storage capacity. In contrast for parvalbumin-positive (PV+) interneurons, the most common cortical class of in- hibitory interneuron, synaptic integration is thought to be either linear or sub-linear in nature, facilitating their role as mediators of precise and fast inhibition. This thesis addresses situations in which PV+ interneurons integrate synaptic inputs in a nonlinear manner, and explores the functions of this synaptic processing. First, I describe a form of cooperative supralinear synaptic integration by local excitatory inputs onto PV+ interneurons, and I extend these results to show how this augments the computational capability of PV+ cells within spiking neuron networks. I also explore the importance of polyamine-modulation of synaptic receptors in mediating sublinear synaptic integration, and discuss how this expands the array of mechanisms known to perform similar functions in PV+ cells. Finally, I present work manipulating PV+ cells experimentally during epilepsy. I consider these findings together with recent scientific advances and suggest how they account for a number of open questions and previously contradictory theories of PV+ interneuron function

Dendritic spikes control synaptic plasticity and somatic output in cerebellar Purkinje cells.

Neurons receive the vast majority of their input onto their dendrites. Dendrites express a plethora of voltage-gated channels. Regenerative, local events in dendrites and their role in the information transformation in single neurons are, however, poorly understood. This thesis investigates the basic properties and functional roles of dendritic spikes in cerebellar Purkinje cells using whole-cell patch clamp recordings from the dendrites and soma of rat Purkinje cells in brain slices. I show that parallel fibre (PF) evoked dendritic spikes are mediated by calcium channels, depend on membrane potential and stimulus intensity and are highly localized to the spiny branches receiving the synaptic input. A determining factor in the localization and spread of dendritic calcium spikes is the activation of large-conductance, calcium dependent potassium (BK) channels. I provide a strong link between dendritic spikes and the endocannabinoid dependent short-term synaptic plasticity, depolarization-induced suppression of excitation (DSE). Gating the dendritic spikes using stimulus intensity or membrane potential, I show that the threshold of DSE is identical to that of the dendritic spikes and the extent of DSE depends on the number of dendritic spikes. Blocking BK channels increases the spatial spread of dendritic spikes and enables current injection or climbing fibre (CF) evoked dendritic spikes to suppress PF inputs via DSE. By monitoring dendritic spikes during strong PF stimulation-induced long-term depression (LTD), I also provide a link between long-term synaptic plasticity and dendritic excitability. By showing that blocking CB1 cannabinoid receptors reduces the intensity requirement for LTD, I provide a connection between the short- and long-term changes in PF strength triggered by dendritic spikes I also investigate the effect dendritic spikes have on somatic action potential output. Contrary to pyramidal cells, where dendritic spikes boost the output of the neuron, the average Purkinje cell output becomes independent from the output strength for inputs triggering dendritic spikes. However, the temporal pattern of the output is strongly affected by dendritic spikes. I show that this phenomenon depends on BK channel activation resulting in a pause in somatic firing following dendritic spikes. In summary, I present a description of PF evoked local dendritic spikes and demonstrate their functional role in controlling the synaptic input and action potential output of cerebellar Purkinje cells

Storage of spatiotemporal input sequences in dendrites of pyramidal neurons

Plastic changes in neurons are widely considered to underpin the formation and maintenance of memory. The mechanisms of induction and expression of plasticity are, therefore, crucial to our understanding of the capacity of information storage that neurons possess. Using two-photon glutamate uncaging and whole-cell electrophysiological recordings, I demonstrate that dendrites of neurons are capable of preferentially storing specific spatiotemporal sequences, and describe the physiological properties of this new form of plasticity. Such plastic changes are dependent on Ca2+ influx through NMDA receptors, which is consistent with previous reports regarding induction of potentiation. Using two-photon Ca2+ imaging, I demonstrate that spatiotemporal plasticity is a result of a distinct homogeneous spatial increase in Ca2+ influx of different spatiotemporal sequences. Using the NEURON simulation environment, I used my experimental findings to perform simulations of synaptic plasticity rules. I found that homogeneous increases in synaptic strength across the dendrite can result in the spatiotemporal plasticity that I empirically observed. Moreover, I employed a genetic optimization algorithm and parallelized simulations to show that such changes are within physiological parameters observed in cortical neurons. My PhD therefore describes a novel form of plasticity, and proposes that dendrites are capable of more extensive information storage than was previously assumed