The role of the lateral hypothalamic neural outputs in motivated behaviour

Comprendre comment le cerveau traite l’information est l’une des questions les plus intrigantes auxquelles les neurosciences modernes sont confrontées. L’étude actuelle vise à caractériser comment l’hypothalamus latéral (HL) traite l’information vers des cibles cérébrales en aval afin de guider des réponses comportementales appropriées. L’HL est une zone du cerveau qui régule des comportements vitaux tels que les fonctions autonomes et endocriniennes, l’équilibre homéostatique, la régulation du métabolisme et les cycles veille-sommeil. De plus, des études récentes soulignent son importance dans le traitement de l’aversion et de la récompense. L’HL envoie des projections neurales à de nombreux noyaux cérébraux connus pour traiter des signaux qui jouent un rôle important pour guider et orchestrer des réponses comportementales appropriées. Des expériences visant a déterminer les connections afferentes et efférentesde l’HL ont démontré que trois noyaux cérébraux importants reçoivent des projections importantes de l’HL. Il s’agit de l’habenula latéral (HbL), de l’aire tegmentale ventrale (ATV) et du noyau raphe dorsal (NRD). L’HbL est le principal centre de déception du cerveau : son activité augmente spécifiquement lorsqu’un animal est soumis à des stimuli aversifs ou en l’absence de récompenses attendues, jouant un rôle important dans la signalisation d’une erreur de prédiction de punition. L’ATV dopaminergique est le principal centre de récompense du cerveau. Il joue un rôle important dans l’encodage de la valeur des récompenses, l’apprentissage du renforcement et la motivation. Le NRD est le principal centre de sérotonine jouant un rôle important dans le traitement des émotions et les réponses adaptatives. Pour examiner spécifiquement la contribution des sorties neuronales de l’HL chez les souris en mouvement libre, nous avons utilisé une technique d’imagerie avancée du calcium – système de photométrie à fibres. La photométrie à fibres est une approche puissante qui combine des indicateurs de calcium codés génétiquement et des fibres optiques multimodes pour monitorer l’activité neuronale chez les animaux en mouvement libre, ce qui est essentiel pour comprendre comment des groupes spécifiques de neurones sont impliqués dans le contrôle ou la réponse à une action ou à un stimulus. Dans le premier chapitre, je présente un protocole qui a été développé pour une détection fiable des signaux de calcium à l’aide d’un système de photométrie multifibre. Le protocole détaille les composantes d’un système de photométrie multifibres, la méthode pour accéder aux structures profondes du cerveau pour délivrer et collecter la lumière, et une méthode pour prendre en compte les artefacts de mouvement avant et pendant les enregistrements. En outre,je présente un algorithme de traitement des signaux enregistrés qui tient compte des sources communes d’artefacts qui sont inévitables pendant les enregistrements. Dans le deuxième chapitre, je présente les résultats de l’étude du rôle fonctionnel de trois sorties neurales de l’HL vers le NRD, l’ATV et l’HbL. En utilisant le protocole décrit dans le premier chapitre, l’activité dans les voies HL→NRD, HL→ ATV et HL→HbL a été simultanément enregistrée lors de réponses comportamentales dans des contextes d’aversion et de récompense. Nous avons constaté que l’activité à ces trois sorties neurales de l’HL augmentait avec des stimuli et des signaux prédictifs de stimuli aversifs. L’activité neuronale augmente également lors des réponses comportementales motivées spontanées et diminue lors de l’immobilité comportementale. L’activation optogénétique indépendante des terminaisons axonales de l’HL au niveau de l’HbL, l’ATV ou le NRD était suffisante pour augmenter la mobilité, mais a eu des effets différents dans d’autres tests comportementaux. Dans l’ensemble, nous proposons que l’HL envoie des signaux complémentaires aux cibles en aval pour traiter les informations engagées pour promouvoir des comportements motivés. En annexe, je présente un ensemble d’analyse de données python qui a été développé pour traiter tous les enregistrements de photométrie à fibre optique présentés dans l’étude actuelle. Cet ensemble permet de combiner, de stocker et d’analyser les enregistrements de plusieurs souris, essais et différentes expériences avec diverses mesures, événements comportementaux et stimuli de manière standardisée.Understanding how brain processes information is the one of the most intriguing questions that modern neuroscience faces. The current study aims to characterize how the lateral hypothalamus (LH) processes information to downstream brain targets to guide proper behavioral responses. The LH is a brain area that regulates vital behaviors such as autonomic and endocrine functions, homeostatic balance, regulation of metabolism, and sleep-wake cycles. Moreover, recent studies point out its importance in aversive and appetitive processing. The LH sends neural projections to many brain nuclei known to process signals that play important roles to guide and orchestrate proper behavior responses. Tracing experiments demonstrated that three important brain nuclei receive significant inputs from the LH, the lateral habenula (LHb), the ventral tegmental area (VTA), and the dorsal raphe nucleus (DRN). The LHb is the main disappointment center of the brain: its activity specifically increases when an animalis presented an aversive stimuli or in the absence of expected rewards, playing an important role in signaling punishment prediction error. The dopaminergic VTA is the main brain reward center. It plays important roles in reward-value encoding, reinforcement learning and motivation. The DRN is the main serotonin center playing and important role in emotion processing and adaptive responses. To specifically examine the contribution of LH neural outputs in freely moving mice, we used an advanced calcium imaging technique – fiber photometry system. Fiber photometry is a powerful approach that combines genetically encoded calcium indicators and multimode optical fibers to monitor neuronal activity in freely moving animals, which is critical to understand how specific groups of neurons play in directing or responding to an action or a stimulus. In the first chapter, I present a protocol that was developed for reliable detection of calcium signal using a camera-based multi-fiber photometry system. The protocol details the components of a multi-fiber photometry system, a method to access deep brain structures to deliverand collect light, and a method to account for motion artifacts before and during recordings. Additionally, I present an algorithm for processing of recorded signals that accounts common sources of artefacts that are inevitable during recordings. In the second chapter, I present results of the investigation of the functional role of three LH outputs to the DRN, VTA, and LHb. Using the protocol described in the first chapter, activity in the LH→DRN, LH→ VTA and LH→LHb pathways were simultaneously recorded during motivated responses in aversive and appetitive contexts. We found that these three LH neural outputs increased activity with aversive stimuli and cues predicting them. The neural activity also increased at onsets of spontaneous motivated behavior responses and decreased duringbehavioral immobility. Independent optogenetic activation of axon terminals in LHb, VTA,or DRN was sufficient to increase mobility, but had different effects in other behavioural tests. Altogether, we propose that LH sends complementary signals to the downstream targets to process information engaged in motivated behaviors. In the annex, I present a data analysis python package that was developed to process all fiber photometry recordings presented in the current study. The package allow to combine, store, and analyze recordings from multiple mice, trials, and different experiments with various measurements, behavioural events, and stimuli in a standardized way

Phase variation mediates reductions in expression of surface proteins during persistent meningococcal carriage

Asymptomatic and persistent colonization of the upper respiratory tract by Neisseria meningitidis occurs despite elicitation of adaptive immune responses against surface antigens. A putative mechanism for facilitating host persistence of this bacterial commensal and pathogen is alterations in expression of surface antigens by simple sequence repeat (SSR)-mediated phase variation. We investigated how often phase variation occurs during persistent carriage by analyzing the SSRs of eight loci in multiple isolates from 21 carriers representative of 1 to 6 months carriage. Alterations in repeat number were detected by a GeneScan analysis and occurred at 0.06 mutations/gene/month of carriage. The expression states were determined by Western blotting and two genes, fetA and nadA, exhibited trends toward low expression states. A critical finding from our unique examination of combinatorial expression states, “phasotypes,” was for significant reductions in expression of multiple phase-variable surface proteins during persistent carriage of some strains. The immune responses in these carriers were examined by measuring variant-specific PorA IgG antibodies, capsular group Y IgG antibodies and serum bactericidal activity in concomitant serum samples. Persistent carriage was associated with high levels of specific IgG antibodies and serum bactericidal activity while recent strain acquisition correlated with a significant induction of antibodies. We conclude that phase-variable genes are driven into lower expression states during long-term persistent meningococcal carriage, in part due to continuous exposure to antibody-mediated selection, suggesting localized hypermutation has evolved to facilitate host persistence

New information on the Jurassic lepidosauromorph Marmoretta oxoniensis

The earliest known crown-group lepidosaurs are known from the Middle Triassic; however, their stem group is poorly sampled, with only a few representative fossils found. This is partly due to the small size and delicate bones of early stem-lepidosaurs (= non-lepidosaurian lepidosauromorphs), which make both preservation in the fossil record and subsequent discovery less likely. The Middle Jurassic lepidosauromorph Marmoretta oxoniensis is re-examined using high-resolution micro-computed tomography to reveal parts of the skull anatomy that were previously unknown. These include a squamosal, postorbital, more complete parietal, pterygoids, and an articulated posterior section of the mandible. Some differences between this and other Marmoretta specimens were identified as a result, such as the arrangement of palatal teeth and the shape of the parabasisphenoid. The status of Marmoretta as a stem-lepidosaur or stem-squamate has been debated. To evaluate this, we tested the phylogenetic position of Marmoretta by including our new data in an adapted phylogenetic character matrix. We recover Marmoretta as a stem-lepidosaur and sister to Fraxinisaura rozynekae. Our findings support the hypothesis that both taxa belonged to a clade of non-lepidosaurian lepidosauromorphs that co-existed with lepidosaurs into the Middle Jurassic

Constructing networks of quantum channels for state preparation

Entangled possibly mixed states are an essential resource for quantum computation, communication, metrology, and the simulation of many-body systems. It is important to develop and improve preparation protocols for such states. One possible way to prepare states of interest is to design an open system that evolves only towards the desired states. A Markovian evolution of a quantum system can be generally described by a Lindbladian. Tensor networks provide a framework to construct physically relevant entangled states. In particular, matrix product density operators (MPDOs) form an important variational class of states. MPDOs generalize matrix product states to mixed states, can represent thermal states of local one-dimensional Hamiltonians at sufficiently large temperatures, describe systems that satisfy the area law of entanglement, and form the basis of powerful numerical methods. In this work we develop an algorithm that determines for a given linear subspace of MPDOs whether this subspace can be the stable space of some frustration free k-local Lindbladian and, if so, outputs an appropriate Lindbladian. We proceed by using machine learning with networks of quantum channels, also known as quantum neural networks (QNNs), to train denoising post-processing devices for quantum sources. First, we show that QNNs can be trained on imperfect devices even when part of the training data is corrupted. Second, we show that QNNs can be trained to extrapolate quantum states to, e.g., lower temperatures. Third, we show how to denoise quantum states in an unsupervised manner. We develop a novel quantum autoencoder that successfully denoises Greenberger-Horne-Zeilinger, W, Dicke, and cluster states subject to spin-flip, dephasing errors, and random unitary noise. Finally, we develop recurrent QNNs (RQNNs) for denoising that requires memory, such as combating drifts. RQNNs can be thought of as matrix product quantum channels with a quantum algorithm for training and are closely related to MPDOs. The proposed preparation and denoising protocols can be beneficial for various emergent quantum technologies and are within reach of present-day experiments

Working Memory for Spatial Sequences: Developmental and Evolutionary Factors in Encoding Ordinal and Relational Structures

Sequence learning is a ubiquitous facet of human and animal cognition. Here, using a common sequence reproduction task, we investigated whether and how the ordinal and relational structures linking consecutive elements are acquired by human adults, children, and macaque monkeys. While children and monkeys exhibited significantly lower precision than adults for spatial location and temporal order information, only monkeys appeared to exceedingly focus on the first item. Most importantly, only humans, regardless of age, spontaneously extracted the spatial relations between consecutive items and used a chunking strategy to compress sequences in working memory. Monkeys did not detect such relational structures, even after extensive training. Monkey behavior was captured by a conjunctive coding model, whereas a chunk-based conjunctive model explained more variance in humans. These age- and species-related differences are indicative of developmental and evolutionary mechanisms of sequence encoding and may provide novel insights into the uniquely human cognitive capacities.Journal of Neuroscienc

Exploring the dynamic epigenome in pluripotent stem cells using quantitative methods

A totipotent stem cell has the potential to give rise to the trillions of cells in the human body, all carrying the very same genetic information. Through differentiation events, gene expression changes guided by epigenetic mechanisms resulting in specialized phenotypes. The more we understand of the highly dynamic epigenome, the better we will understand key phenomena such as human development, tissue regeneration and disease initiation and progression. In this thesis, focus lays on the role of key players in the field of molecular mechanisms of epigenetics using both mouse and human embryonic stem cells. In Paper I we investigated the non-catalytic function of ten-eleven translocation 1 (TET1) methylcytosine dioxygenase in mouse embryonic stem cells (ESCs). Upon knocking out TET1, endogenous retroviral expression increased, while neither cells expressing wild type TET1 or a non-catalytic mutant showed the same trend. Studying the epigenetic landscape, we found that TET1, independently of its catalytic activity, is important for establishment of the silencing histone marks H3K9me3 and H4K20me3 at endogenous retroviral elements. This suggests that TET1 serves as an interaction hub for chromatin modifying complexes to repress the interstitial heterochromatin that the ERVs reside in. In Paper II we investigated the role of Polycomb Repressive Complex 2 (PRC2) as an epigenetic regulator for cell type specification in human ESCs. By abolishing the function of PRC2 via drugs or knocking out its catalytic subunit we observed spurious differentiation of naïve pluripotent stem cells toward cells belonging to the mesoderm and trophectoderm lineages, indicating that PRC2 has a pivotal role in shielding naïve pluripotent stem cells from differentiating toward trophectoderm differentiation. In Paper III we used genetic code expansion in mouse ESCs to produce acute and defined fractions of labelled histone variant H3.3 to study its chromatin deposition kinetics and turnover rate using quantitative methods for immunocytochemistry, chromatin immunoprecipitation sequencing and protein quantification. We revealed that H3.3 accumulates rapidly in a subnuclear space together with DAXX, ATRX, Smarcad1 and HP1 prior to significant chromatin incorporation both at enhancers and interstitial heterochromatin Moreover, this technique allowed for studying novel interactors of H3.3 in a temporal manner directly after protein synthesis. Furthermore, we found that one of the interactors plays a key role as a chromatin remodeler allowing for H3.3 turnover in enhancers. Using the same methods, in Paper IV we expanded the study from Paper III to also focus on the kinetics of canonical histones H2A and H3 compared to the variants H2A.Z, macroH2A, H3.3 and CENP-A. Our results show that the histones are subjected differently to pre-assembly degradation, have defined individual genomic incorporation rates and distinctive half-life in chromatin. Using quantitative ChIP-seq allowed for studying the incorporation to repetitive elements, which is of essence when studying histone variants. Furthermore, we laid some ground work towards finding the enigmatic histone chaperone of macroH2A. Taken together, we show that TET1, PRC2 and histone variants play essential and unique roles in the maintenance of homeostasis in ESCs. Continuing to unravel their dynamics and roles will be instrumental for understanding epigenetically regulated diseases and lead to improved diagnostics and treatments

Population-level neural coding for higher cognition

Higher cognition encompasses advanced mental processes that enable complex thinking, decision-making, problem-solving, and abstract reasoning. These functions involve integrating information from multiple sensory modalities and organizing action plans based on the abstraction of past information. The neural activity underlying these functions is often complex, and the contribution of single neurons in supporting population-level representations of cognitive variables is not yet clear. In this thesis, I investigated the neural mechanisms underlying higher cognition in higher-order brain regions with single-neuron resolution in human and non-human primates performing working memory tasks. I aimed to understand how representations are arranged and how neurons contribute to the population code. In the first manuscript, I investigated the population-level neural coding for the maintenance of numbers in working memory within the parietal association cortex. By analyzing intra-operative intracranial micro-electrode array recording data, I uncovered distinct representations for numbers in both symbolic and nonsymbolic formats. In the second manuscript, I delved deeper into the neuronal organizing principles of population coding to address the ongoing debate surrounding memory maintenance mechanisms. I unveiled sparse structures in the neuronal implementation of representations and identified biologically meaningful components that can be directly communicated to downstream neurons. These components were linked to subpopulations of neurons with distinct physiological properties and temporal dynamics, enabling the active maintenance of working memory while resisting distraction. Lastly, using an artificial neural network model, I demonstrated that the sparse implementation of temporally modulated working memory representations is preferred in recurrently connected neural populations such as the prefrontal cortex. In summary, this thesis provides a comprehensive investigation of higher cognition in higher-order brain regions, focusing on working memory tasks involving numerical stimuli. By examining neural population coding and unveiling sparse structures in the neuronal implementation of representations, our findings contribute to a deeper understanding of the mechanisms underlying working memory and higher cognitive functions

Stability, resistance and change in mammalian microbiota and their associations with host health

What is the nature of a complex organism? Metagenomic research and its insights into biosystem function have fundamentally altered the answer to this question. High- throughput sequencing technology has revealed the multitude of microbes that live in and on human beings and other mammals. Metagenomics is beginning to uncover the relationships between microbiome and host that contribute to a complex organism’s biological processes. The vast quantities of data generated by sequencing have also created analytical challenges that require new methods to identify biologically meaningful results. The research described in this dissertation applies many of these techniques to elucidate the role of microbiota in human health. Chapter 1 presents results from our study of human choline metabolism that identified a relationship between the human gut microbiome and health. Primer design and qPCR experiments that confirm Chapter 1 results are explained in Chapter 2. Chapter 3 characterizes the microbial community from cystic fibrosis lung infection exposed to repeated courses of antibiotic therapy. An experiment designed to improve the resolution of ARISA, a metagenomic profiling technique, is described in Chapter 4. In Chapter 5, the relationship between gut microbial community composition and exercise in mice is investigated. In total, the work in this dissertation identifies several novel relationships between microbiota, host and environmental factors that may prove important in identifying underlying biological mechanisms that will improve human health