Neuronal computation on complex dendritic morphologies

When we think about neural cells, we immediately recall the wealth of electrical behaviour which, eventually, brings about consciousness. Hidden deep in the frequencies and timings of action potentials, in subthreshold oscillations, and in the cooperation of tens of billions of neurons, are synchronicities and emergent behaviours that result in high-level, system-wide properties such as thought and cognition. However, neurons are even more remarkable for their elaborate morphologies, unique among biological cells. The principal, and most striking, component of neuronal morphologies is the dendritic tree. Despite comprising the vast majority of the surface area and volume of a neuron, dendrites are often neglected in many neuron models, due to their sheer complexity. The vast array of dendritic geometries, combined with heterogeneous properties of the cell membrane, continue to challenge scientists in predicting neuronal input-output relationships, even in the case of subthreshold dendritic currents. In this thesis, we will explore the properties of neuronal dendritic trees, and how they alter and integrate the electrical signals that diffuse along them. After an introduction to neural cell biology and membrane biophysics, we will review Abbott's dendritic path integral in detail, and derive the theoretical convergence of its infinite sum solution. On certain symmetric structures, closed-form solutions will be found; for arbitrary geometries, we will propose algorithms using various heuristics for constructing the solution, and assess their computational convergences on real neuronal morphologies. We will demonstrate how generating terms for the path integral solution in an order that optimises convergence is non-trivial, and how a computationally-significant number of terms is required for reasonable accuracy. We will, however, derive a highly-efficient and accurate algorithm for application to discretised dendritic trees. Finally, a modular method for constructing a solution in the Laplace domain will be developed

Model and Appearance Based Analysis of Neuronal Morphology from Different Microscopy Imaging Modalities

The neuronal morphology analysis is key for understanding how a brain works. This process requires the neuron imaging system with single-cell resolution; however, there is no feasible system for the human brain. Fortunately, the knowledge can be inferred from the model organism, Drosophila melanogaster, to the human system. This dissertation explores the morphology analysis of Drosophila larvae at single-cell resolution in static images and image sequences, as well as multiple microscopy imaging modalities. Our contributions are on both computational methods for morphology quantification and analysis of the influence of the anatomical aspect. We develop novel model-and-appearance-based methods for morphology quantification and illustrate their significance in three neuroscience studies. Modeling of the structure and dynamics of neuronal circuits creates understanding about how connectivity patterns are formed within a motor circuit and determining whether the connectivity map of neurons can be deduced by estimations of neuronal morphology. To address this problem, we study both boundary-based and centerline-based approaches for neuron reconstruction in static volumes. Neuronal mechanisms are related to the morphology dynamics; so the patterns of neuronal morphology changes are analyzed along with other aspects. In this case, the relationship between neuronal activity and morphology dynamics is explored to analyze locomotion procedures. Our tracking method models the morphology dynamics in the calcium image sequence designed for detecting neuronal activity. It follows the local-to-global design to handle calcium imaging issues and neuronal movement characteristics. Lastly, modeling the link between structural and functional development depicts the correlation between neuron growth and protein interactions. This requires the morphology analysis of different imaging modalities. It can be solved using the part-wise volume segmentation with artificial templates, the standardized representation of neurons. Our method follows the global-to-local approach to solve both part-wise segmentation and registration across modalities. Our methods address common issues in automated morphology analysis from extracting morphological features to tracking neurons, as well as mapping neurons across imaging modalities. The quantitative analysis delivered by our techniques enables a number of new applications and visualizations for advancing the investigation of phenomena in the nervous system

Optical analysis of synaptic plasticity in rat hippocampus

Long-term potentiation (LTP) in the CA1 region of the hippocampus is dependent on NMDA receptor activation. Downstream of NMDA receptor signaling, the activation of α-calcium/calmodulin-dependent protein kinase II (αCaMKII) is both necessary and sufficient for the induction of this form of LTP. It has been shown that αCaMKII accumulates in spines after glutamate application or ‘chemical LTP’. This postsynaptic accumulation of αCaMKII could be a key step for the induction of LTP, because it localizes the activated kinase close to the substrates of synaptic potentiation. It is not clear, however, what the threshold, time course of αCaMKII translocation are, and whether it is specific to the stimulated synapses only. To address these three questions, I combined optical stimulation techniques (Channelrhodopsin-2 stimulation and two-photon glutamate uncaging) with optical measurements of calcium transients and αCaMKII concentration. This ‘all-optical’ approach made it possible to investigate synapse-specific changes during the induction of LTP. I could show that coincident activity of pre- and postsynaptic cells was needed to trigger the translocation of αCaMKII. Functional potentiation could be measured immediately after stimulation, whereas αCaMKII accumulation reached its peak ~10 min later. This points to an additional structural role of αCaMKII at the postsynaptic density. Both αCaMKII fractions, the cytoplasmic fraction and postsynaptic bound αCaMKII, increased after optical LTP induction. These changes were restricted to stimulated spines. In spines that showed a persistent volume increase, the amount of bound αCaMKII was increased by a factor of two after 30-40 minutes. A second very interesting finding was the close correlation between spine volume changes and LTP, in terms of the time course, induction threshold and specificity. The optical LTP protocol led to a lasting volume increase only in the stimulated spines, but not in directly neighboring spines on the same dendrite. Spine volume reached its maximum immediately after stimulation. Since my all-optical approach relied heavily on the use of a newly identified light-gated cation channel (Channelrhodopsin-2, ChR2), I finally also characterized light activation of ChR2 in hippocampal pyramidal cells in detail. Neuronal activity could be controlled by blue light with millisecond precision. No direct activation of ChR2 was observed by two-photon imaging lasers, making it possible to combine the ChR2 stimulation technique with two-photon imaging. This led to a third important finding: the release probability of ChR2-expressing axonal terminals was increased if the action potential was induced by light. As a result, pairing of light stimulation with postsynaptic depolarization induced reliable long-term potentiation at CA1 synapses. In summary, the new all-optical approach that combines ChR2 stimulation, two-photon glutamate uncaging, and optical measurements of calcium transients and protein concentration, provides a new avenue for investigating plasticity at the level of single synapses. The induction of LTP in single synapses revealed that accumulation of αCaMKII is input specific thus validating Hebb’s postulate on a micrometer scale

Distribution and regulation of ion channels in neurons: Quantitative studies of global ion channel transport and homeostatic synaptic scaling

A healthy neuron must continually produce millions of proteins and distribute them to function-specific regions of the cell. Among these proteins are ion channels that modulate neuronal excitability, allowing neurons to fulfill their primary role of information transfer. Neurons are unique among cells in their morphology, with projections that extend hundreds to thousands of microns. Neuron size and asymmetry pose a challenge for autoregulation of properties that require cargo transport across the cell. Homeostasis of ion channel localization has strong implications for neural excitability. This thesis concerns the intracellular distribution of ion channels in the context of longitudinal transport and global neuron regulation. The principal contributions are experimental measurements, data analysis, and modeling in the study of longitudinal neurite transport. Empirical investigations focus on the distribution and trafficking kinetics of ion channel Kv4.2, including quantitative measurements of both passive diffusion and active microtubule-based transport in both axons and dendrites (Chapters 3 and 5). Mass action models reveal that measured transport profiles corroborate discrepancies in Kv4.2 localization both between neurite types and along the somatodendritic axis (Chapter 4). Exchange between mobile and immobile fractions, inferred from analysis of repeated photobleaching, shapes intracellular distribution of Kv4.2 (Chapter 5). Further, the ensuing theoretical study surveys global regulation of ion channels, specifically for synaptic scaling, which requires cell-wide modulation of AMPA receptors for normalization of neural excitability. A unified model of synaptic potentiation, transport, and feedback reveals limitations imposed on synaptic scaling by neuron morphology. A neuron balances the stability, accuracy, and efficiency of synaptic scaling (Chapter 6).National Institutes of Health Oxford-Cambridge Scholars Gates Cambridge University of North Carolina Medical Scientist Training Progra

Molecular dissection of ephrinB reverse signaling

Synapses form when highly motile dendritic filopodia establish axonal contacts. When a synaptic contact is stabilized, it gives rise to the formation of a dendritic spine, which has recently been shown to involve a number of molecules that mostly regulate the actin cytoskeleton. Thus, it is not surprising that Eph receptor tyrosine kinases, as known regulators of signaling pathways involved in actin cytoskeleton remodeling, have been shown to be required for spine development and maintenance. The main characteristic of interactions of the Eph receptor with its membrane associated ephrin ligand is that they can propagate bidirectional signals. Both forward (downstream of Eph receptor) and reverse (downstream of ephrin ligand) signaling have been shown to play a role in mature synapses, where spine morphology changes are associated with synaptic plasticity. Thus, ephrinB reverse signaling might be as important for dendritic spine development as signaling pathways downstream of Eph receptors. Intrigued by this idea, we hypothesized that some of the spine morphology changes during plasticity might be regulated exclusively by ephrin reverse signaling pathways. Analyzing spine formation in cultures of dissociated hippocampal neurons, we demonstrated that stimulation of hippocampal neurons with EphB receptor bodies leads to increased spine maturation. Expression of a truncated form of ephrinB ligand, which is still able to activate EphB receptor but is unable to transduce intracellular signals, impairs spine morphology. To find new players of reverse signaling that are important in directing ephrin-mediated spine morphology, we performed a proteomic analysis of the phosphotyrosine dependent ephrin interactor Grb4 (Nck-2, Nck beta). We identified the signaling adaptor G protein-coupled receptor kinase-interacting protein (GIT)1 (Cat1) as well as the exchange factor for Rac βPIX (β-p21-activated protein kinase (PAK)-interacting exchange factor), also called RhoGEF7 or Cool-1, as novel Grb4 binding partners, which have both previously been shown to be required for spine formation. We show that Grb4 binds and recruits GIT1 to synapses downstream of activated ephrinB ligand. Interactions of Grb4 with ephrin or GIT1 are necessary for proper spine morphogenesis and synapse formation. We therefore provide evidence for an important role of ephrinB reverse signaling in spine formation and describe the ephrinB reverse signaling pathway involved in this process