Retinogeniculate (RG) synapses connect retinal ganglion cells to the thalamic relay cells of the dorsal lateral geniculate nucleus (dLGN). They are critical for regulating the flow of visual information from retina to primary visual cortex (V1). RG synapses in dLGN are uniquely larger and stronger than their counterparts in other retinorecipient regions. Moreover, in dLGN, RG synapses can be classified into two groups: simple RG synapses, which contain glia-encapsulated single RTs synapsing onto relay cell dendrites, and complex RG synapses, which contain numerous RTs that converge onto the shared regions of relay cell dendrites. To identify target-derived molecules that direct the transformation of RTs into unique RG synapses in dLGN, I used RNAseq to obtain the whole transcriptome of dLGN and its adjacent retinorecipient nucleus, vLGN, at different time points during RG synapses development. Leucine-Rich Repeat Transmembrane Neuronal 1 (LRRTM1), a synaptogenic adhesion molecule, was the candidate I selected based on its expression pattern. Here, I discovered that LRRTM1 regulates the development of complex RG synapses. Mice lacking LRRTM1 (lrrtm1-/-) not only show a significant reduction in the number of complex RG synapses but they exhibit abnormal visual behaviors. This work reveals, for the first time, a high level of retinal convergence onto dLGN relay cells in thalamus and the functional significance of this convergence for vision. / Ph. D.

The aims of this thesis were (1) to learn about the identities of the molecules involved in the maintenance of long-term potentiation (LTP), and (2) to develop and test a behavioural paradigm capable of elucidating the interaction between these molecular processes and the persistence of long-term memories. By improving the stability of field recordings in in vitro electrophysiology, it was possible to investigate the molecular processes that determine the long-term changes in synaptic efficacy. In these experiments, the interactions between two convergent inputs onto the same neuronal population in the CA1 region of the hippocampus were monitored for over ten hours. Analytically powerful three-pathway protocols using sequential strong and weak tetanization in varying orders, and test stimulation over long periods of time after LTP-induction, enabled a pharmacological dissociation of potentially distinct roles of the calmodulin kinase (CaMK) pathways in LTP. This places constraints on the mechanisms by which synaptic potentiation, and possibly memories, become stabilized. The experiments show that tag setting is blocked by the CaMK inhibitor KN-93 that, at low concentration primarily blocks CaMKII, whereas a CaMKK inhibitor, STO-609, selectively limits the synthesis or the availability of plasticity related proteins (PRPs). To test whether memories can be subject to modulation by independent experiences, behavioural studies tested the possibility of lengthening the persistence of a relatively weak memory by pairing its induction with an event capable of inducing the synthesis of the required PRPs. Corticosterone-dependent stressful events like a cold swim proved to interfere and weaken spatial memories. On the other hand, the exploration of a novel environment succeeded in rescuing the decay of a weak memory. The effect of the exploration of the novel environment was dependent on NMDA and dopamine receptor activation, as well as protein synthesis. These results are discussed in relation to the synaptic tagging and capture hypothesis and a novel model of the neuronal mechanisms underlying synaptic plasticity is developed from them.

Coupling the small GTPase Rab3 to the Synaptic Vesicle Cycle

Posttraumatic epilepsy is a common consequence of brain trauma. However, little is known about how long-term changes in local excitatory and inhibitory synaptic networks contribute to epilepsy after closed-head brain injury. This study adapted a widely used model of experimental brain injury as a mouse model of posttraumatic epilepsy. Behavioral seizure activity and alterations in synaptic circuitry in the dentate gyrus were examined in mice after experimental cortical contusion brain injury. Spontaneous behavioral seizures were observed in 20% of mice after moderate injury and 36-40% of mice weeks after severe injury. In the dentate gyrus, most mice displayed regionally localized mossy fiber reorganization ipsilateral to the injury that was absent in control mice or sections contralateral to the injury. Extracellular field and whole-cell patch clamp recordings were performed in acute brain slice preparations of the dentate gyrus. Dentate granule cells displayed spontaneous and evoked activity that was consistent with network synchronization and the formation of recurrent excitatory network only in slices that had posttraumatic mossy fiber sprouting. The excitability of surviving hilar GABAergic interneurons, which provide important feedback inhibition to granule cells, was examined at similar time points. Cell-attached and whole-cell voltage-clamp recordings revealed increased spontaneous and glutamate photostimulation-evoked excitatory input to hilar GABA neurons ipsilateral to the injury, versus control and contralateral slices. Despite increased excitatory synaptic input to interneurons, whole-cell voltage-clamp recordings revealed a reduction in inhibitory synaptic input to granule cells. These findings suggest that there are alterations in excitatory and inhibitory circuits in mice with posttraumatic mossy fiber sprouting and seizures after cortical contusion head injury.

Proximale Spinale Muskel Atrophie (SMA) ist eine autosomal rezessive Krankheit, charakterisiert durch eine Degeneration des zweiten Motorneurons und einer progressiven Paralyse und Atrophie proximaler Muskeln. Nach Zystischer Fibrose, ist SMA die häufigste autosomal rezessive Erkrankung bei Menschen und der häufigste genetische Grund für Säuglingssterblichkeit. SMA, monogenetisch im Ursprung, ist verursacht durch eine Mutation in einem einzelnen Gen, dem Survival Motor Neuron 1 (SMN1) Gen, was zu einer reduzierten Menge an Survival Motor Neuron (SMN) protein führt. SMN ist ein ubiquitär expremiertes Protein mit house-keeping Funktion in snRNP Biogenese und pre-mRNA splicen. Dennoch, eine reduzierte Menge an SMN beeinträchtigt vor allem Motor Neurone und Muskeln aus bisher unverständlichen Gründen. Es wurde demonstriert, dass SMN mit ß-actin mRNA interagiert und an dessen Transport entlang des Axons beteiligt ist. Funktionelle Studien an der Neuromuskulären Synapse (NMJ) haben gezeigt, dass Evozierte Neurotransmitterfreisetzung um 55 % reduziert war in den meist betroffenen Muskelgruppen, dies indiziert, dass eine verringerte Menge an Vesikeln fusioniert, währenddessen asynchrone Transmitterfreisetzung um 300 % erhöht ist aufgrund von einer abnormalen Akkumulation von Calcium in der Nervenendigung in SMA Mäusen. Eine Mögliche Erklärung für diese Calcium Erhöhung ist eine herabgesetzte Calcium Aufnahme durch Mitochondrien während Serien von Aktions Potenzialen. Diese Studie präsentiert eine umfassende Analyse mit einem Fluoreszens Konfokal Mikroskop über die Organisation und Fülle Synaptischer Vesikel (SVs), Mitochonrien und Aktin in Nervenendigungen von SMA Mäusen ( Smn -/-; SMN2; SMNdelta7). Wir visualisierten Synaptische Vesikel mit einem Antikörper gegen den Acetylcholin ( VACht) und konnten zeigen, dass im Transversus Abdominis (TVA) Muskel SV Klusters während des Reifungsprozesse klein verbleiben mit einer Reduzierung von 50% der totalen Fläche die von SVs bedeckt ist. Diese schwere Reduktion von SVs wurde auch im der kaudalen Muskelstrang des Levator auris longus (LAL) Muskel gefunden, obwohl nur leichte Veränderungen in der Postsynapse dieses Muskels festzustellen sind. Diese Ergebniss von Präsynaptischer Pathologie, neben fast normalen postsynaptischen Status, verstärkt die Hypothese dass SMN-induzierte Veränderungen im Muskel nicht auschließlich eine reine Konsequenz von Motor Neuron Degeneration sein können. Als Nächstes, haben wir Mitochondria mit Mitotracker angefärbt und haben gefunden, dass die Fläche,die von Mitochondrien in Mutanten Mäusen bedeckt ist, etwa nur die Hälfte der Fläche im Wild typ beträgt. Überraschenderweise waren SVs und Mitochondrien stak kolokalisiert. In vielen Fällen war ein Kern von Mitochondrien deutlich umgeben von einem Ring aus SVs. Diese Verteilung war unbeeinträchtig in der Mutanten Maus und könnte eine mehr generelle Bedeutung in Nervenendigungen haben. Phalloidin gefärbtes Aktin zeigte das F-aktin ringförmige Strukturen um SV Klusters formt. Diese Strukturen und der Prozentuale Anteil der Nervenendigung der von Aktin bedeckt ist, war geringer in SMA Mutanten Mäusen. Aktin ist an multiblen Schritten des Vesikel Zyklus beteiligt. Kurz Strecken-Transport von Vesikeln und Organellen, wie Mitochondrien in Wachstunskegeln und Nervendigungen ist vor allem vom aktin-myosin-basierten Transport abhängig. Weitere Arbeit ist notwendig um zu klären ob die Charakteristiken des SMA Phänotyps wie abnormales SV Klustering, Reduktion von Mitochondrien, unabhängig auftreten oder eine gemeinsame Konsequenz von einer Dysfunktion des Aktin Zytoskeleton sind, was Aktin eine Schlüsselrolle in der SMA Pathogenese verleihen würde.

Biological neural systems (BNS) in general and the central nervous system (CNS) specifically exhibit a strikingly efficient computational power along with an extreme flexible and adaptive basis for acquiring and integrating new knowledge. Acquiring more insights into the actual mechanisms of information processing within the BNS and their computational capabilities is a core objective of modern computer science, computational sciences and neuroscience. Among the main reasons of this tendency to understand the brain is to help in improving the quality of life of people suffer from loss (either partial or complete) of brain or spinal cord functions. Brain-computer-interfaces (BCI), neural prostheses and other similar approaches are potential solutions either to help these patients through therapy or to push the progress in rehabilitation. There is however a significant lack of knowledge regarding the basic information processing within the CNS. Without a better understanding of the fundamental operations or sequences leading to cognitive abilities, applications like BCI or neural prostheses will keep struggling to find a proper and systematic way to help patients in this regard. In order to have more insights into these basic information processing methods, this thesis presents an approach that makes a formal distinction between the essence of being intelligent (as for the brain) and the classical class of artificial intelligence, e.g. with expert systems. This approach investigates the underlying mechanisms allowing the CNS to be capable of performing a massive amount of computational tasks with a sustainable efficiency and flexibility. This is the essence of being intelligent, i.e. being able to learn, adapt and to invent. The approach used in the thesis at hands is based on the hypothesis that the brain or specifically a biological neural circuitry in the CNS is a dynamic system (network) that features emergent capabilities. These capabilities can be imported into spiking neural networks (SNN) by emulating the dynamic neural system. Emulating the dynamic system requires simulating both the inner workings of the system and the framework of performing the information processing tasks. Thus, this work comprises two main parts. The first part is concerned with introducing a proper and a novel dynamic synaptic model as a vital constitute of the inner workings of the dynamic neural system. This model represents a balanced integration between the needed biophysical details and being computationally inexpensive. Being a biophysical model is important to allow for the abilities of the target dynamic system to be inherited, and being simple is needed to allow for further implementation in large scale simulations and for hardware implementation in the future. Besides, the energy related aspects of synaptic dynamics are studied and linked to the behaviour of the networks seeking for stable states of activities. The second part of the thesis is consequently concerned with importing the processing framework of the dynamic system into the environment of SNN. This part of the study investigates the well established concept of binding by synchrony to solve the information binding problem and to proposes the concept of synchrony states within SNN. The concepts of computing with states are extended to investigate a computational model that is based on the finite-state machines and reservoir computing. Biological plausible validations of the introduced model and frameworks are performed. Results and discussions of these validations indicate that this study presents a significant advance on the way of empowering the knowledge about the mechanisms underpinning the computational power of CNS. Furthermore it shows a roadmap on how to adopt the biological computational capabilities in computation science in general and in biologically-inspired spiking neural networks in specific. Large scale simulations and the development of neuromorphic hardware are work-in-progress and future work. Among the applications of the introduced work are neural prostheses and bionic automation systems.

Synaptic vesicle (SV) recycling in the presynapse is essential for the maintenance of neurotransmission. During mild stimulation clathrin-mediated endocytosis (CME) dominates, however during intense stimulation activity-dependent bulk endocytosis (ADBE) is the dominant form of membrane retrieval. The aim of this thesis was to determine how the signalling molecule GSK3 controlled ADBE, with the hypothesis that this enzyme was required at multiple stages of this endocytosis mode. I also hoped to identify a specific cargo for ADBE. I found that during intense action potential stimulation, a localised calcium increase is necessary for the activation of Akt, which inhibited GSK3. This activation was mediated via a phosphatidylinositol 3-kinase (PI3K)-dependent mechanism. Furthermore, I found that phosphatidylinositol 4-kinaseIIα (PI4KIIα), a molecule whose abundance is regulated by GSK3, had a key role in ADBE. Specifically, I found that the absence of PI4KIIα accelerated CME but inhibited ADBE and that PI4KIIα controls CME and ADBE via distinct mechanisms. The PI4KIIα study revealed potential cross-talk between CME and ADBE. To determine whether modulation of either endocytosis mode impacts on the other, the retrieval of genetically-encoded reporters of SV cargo was monitored during intense stimulation during inhibition of either CME or ADBE. The recovery of almost all SV cargo was unaffected by ADBE inhibition but was arrested by abolishing CME. In contrast, VAMP4-pHluorin retrieval was perturbed by inhibiting ADBE and not by blocking CME. Knockdown of VAMP4 also arrested ADBE, indicating that in addition to being the first identified ADBE cargo, it is also essential for this endocytosis mode to proceed.

No description available.

Contemporary cellular models of learning and memory are articulated around the idea that synapses undergo activity-dependent weight changes. However, conventional forms of Hebbian plasticity do not adequately address certain features inherent to behavioral learning. First, associative learning driven by delayed behavioral outcomes introduces a temporal credit assignment problem, whereby one must remember which action corresponds to which outcome. Yet, current models of associative synaptic plasticity, such as spike-timing-dependent plasticity, require near coincident activation of pre- and postsynaptic neurons (i.e., within ~ 10 ms), a time delay that is orders of magnitude smaller than that required for behavioral associations. For individual neurons to associate two cues, a biological mechanism capable of potentiating synaptic weights must be able to bind events that are separated in time. Theoretical work has suggested that a synaptic eligibility trace, a time-limited process that momentarily renders synapses eligible for weight updates via delayed instructive signals, can solve this problem. However, no material substrate of eligibility traces has been identified in the brain. Second, under certain conditions, neurons need to swiftly update their weights to reflect rapid learning. Current plasticity experiments require the repetition of multiple pairings to induce long-term synaptic plasticity. In this thesis, I addressed these problems using a combination of whole-cell recordings, two-photon uncaging, calcium imaging, and mechanistic modeling. I uncovered a form of synaptic plasticity known as behavioral timescale synaptic plasticity (BTSP) in layer 5 pyramidal neurons in the prefrontal cortex of mice. BTSP induced synaptic potentiation by pairing temporally separated pre- and postsynaptic events (0.5 s - 1 s), regardless of their order. The temporal window for BTSP induction offers a line of solution to the temporal credit assignment problem by highlighting the presence of a synaptic mechanism that expands the time for the induction of activity-dependent long-term synaptic plasticity, spanning hundreds of milliseconds. We further found that BTSP can be induced following a single pairing, enabling rapid weight updates required for one-shot learning. Using two-photon calcium imaging in apical oblique dendrites, I discovered a novel short-term and associative plasticity of calcium dynamics (STAPCD) that exhibited temporal characteristics mirroring the induction rules of BTSP. I identified a core set of molecular components crucial for both STAPCD and BTSP and developed a computational simulation that models the calcium dynamics as a latent memory trace of neural activity (i.e., eligibility traces). Together, we find that calcium handling by the endoplasmic reticulum enables synaptic weight updates upon receipt of delayed instructive signals, obeys rules of burst-dependent one-shot learning, and thus provides a mechanism that satisfies the requirements anticipated of eligibility traces. Collectively, these findings offer a neural mechanism for the binding of cellular events occurring in single shot and separated by behaviorally relevant temporal delays to induce potentiation at synapses, providing a cellular model of associative learning.

No description available.