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Recordings were carried out in 4-8 week old C57/Bl6 mice. SERT-Cre::Rosa-TdTomato and SOM-Cre::Rosa-TdTomatotransgenic lines were used to fluorescently label DRN 5-HT and SOM GABA neurons, respectively. All experiments were carried out in accordance with procedures approved by the University of Ottawa Animal Care and Veterinary Services. Experiments were carried out at room temperature using a potassium-gluconate-based internal solution, except for synaptic physiology experiments for which a cesium-based solution was used. In all cases, the external solution consisted of standard artificial cerebrospinal fluid. Detailed information is available in our related publication. The data is laid out as shown below, with recordings from DRN 5-HT, DRN GABA, and L5 mPFC pyramidal neurons stored in the corresponding directories. . ├── 5HT │ ├── current_steps │ ├── GABA_synapses │ ├── gating │ ├── heated_gating │ ├── heated_pharmacology │ ├── long_curr_steps │ ├── membrane_parameters │ ├── OU_noise │ ├── OU_noise_heated │ ├── pharmacology │ └── spk_time ├── GABA │ ├── current_steps │ ├── DRN393_firing_vsteps │ ├── DRN398_firing_vsteps │ ├── long_curr_steps │ ├── matched_I_V_steps │ ├── membrane_parameters │ ├── OU_noise │ ├── spk_time │ └── unmatched_V_steps └── mPFC ├── current_steps ├── gating └── OU_noise The names of subdirectories mainly reflect the different types of experiments carried out in each cell type: current_steps: Short (~1s) steps of current applied in current clamp. long_curr_steps: 20-30s current steps. spk_time: A 1s hyperpolarizing current step of variable amplitude followed by a short depolarizing step to evoke spiking. This protocol has been used in the past to investigate an effect of inactivating potassium currents (eg IA) on spike timing. OU_noise: Frozen Ornstein-Uhlenbeck noise with various timescale and amplitude characteristics applied in current clamp. This protocol provides a rich dataset for training spiking neuron models (see Related works). Each experiment is divided into training and test portions which we recommend using for training and testing models, respectively. gating: Voltage clamp protocol designed to characterize the voltage-dependence of ionic currents that activate near spike threshold. Consists of a hyperpolarizing pulse followed by depolarizing steps of varying amplitude. These experiments were carried out in the presence of tetrodotoxin (TTX) to block voltage-gated sodium channels. In the GABA dataset, these experiments are split across the unmatched_V_steps, matched_V_steps, and DRN39X_firing_vsteps directories because in some cases we were able to carry out spk_time and gating experiments in the same cells. In the case of DRN39X_firing_vsteps, we carried out the spk_timing protocol, applied TTX, then carried out the gating protocol. In the case of matched_I_V_steps, both protocols were carried out in the presence of TTX. pharmacology: Voltage clamp protocol designed to activate voltage-dependent ionic currents. 18411010.abf was recorded under baseline conditions, 18411013.abf was recorded in the presence of TEA, and 18411015.abf was recorded in the presence of TEA + 4AP. All three recordings were carried out in the same cell. membrane_parameters: Passive membrane parameters (resistance and capacitance) of DRN neurons. Most of the data files included in this package are electrophysiological recordings stored in Axon binary format (ABF) which can be opened in Python using neo or ez-ephys (which itself uses neo internally). Recordings are named according to the following convention: <experimenter_prefix><YYMDD><id>.abf where <experimenter_prefix> is an optional prefix with the initials of the person who collected the data, <YYMDD> is the date the experiment was carried out (M is either a number representing a month between January and September, or one of the letters o, n, or d for the remaining months), and <id> is a three digit number. For example, JF19121013.abf was collected by Jean-François Boucher on January 21, 2019. Metadata is included in files named index.csv. These tables include a unique ID for each neuron recorded (this can be used to determine which recordings were carried out in the same neuron), the passive membrane resistance in MOhm (R), membrane capacitance in pF (C), and the holding current at -70 mV or -60 mV in pA (I_hold). checksums.txt includes SHA256 checksums that can be used to verify data integrity. This dataset contains whole-cell electrophysiological recordings (patch-clamp recordings) from three cell types in mice: serotonin (5-HT) neurons, somatostatin (SOM)-expressing GABA interneurons, and layer 5 pyramidal neurons. 5-HT and GABA neurons were recorded in the dorsal raphe nucleus (DRN), which is the main source of serotonergic input to the forebrain. Together, they make up the majority of the neurons found in the DRN. This dataset can be used to investigate the intrinsic electrophysiological properties of these two types of DRN neurons and contrast them with another abundant and well-studied cell type, the L5 pyramidal neuron. This data was used in our paper describing a spiking neural network model of the dorsal raphe nucleus: Emerson F. Harkin, Michael B. Lynn, Alexandre Payeur, Jean-François Boucher, Léa Caya-Bissonnette, Dominic Cyr, Chloe Stewart, André Longtin, Richard Naud, and Jean-Claude Béïque. Temporal derivative computation in the dorsal raphe network revealed by an experimentally-driven augmented integrate-and-fire modeling framework. eLife, 2023. doi: 10.7554/eLife.72951 See the included README.md for detailed information about the dataset.

Objective: To generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets. Methods: A validated algorithm was applied to private, military, and public AHC datasets to identify adult cases of MS between 2008 and 2010. In each dataset, we determined the 3-year cumulative prevalence overall and stratified by age, sex, and census region. We applied insurance-specific and stratum-specific estimates to the 2010 US Census data and pooled the findings to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. We also estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated our estimate to 2017. Results: The estimated 2010 prevalence of MS in the US adult population cumulated over 10 years was 309.2 per 100,000 (95% confidence interval [CI] 308.1–310.1), representing 727,344 cases. During the same time period, the MS prevalence was 450.1 per 100,000 (95% CI 448.1–451.6) for women and 159.7 (95% CI 158.7–160.6) for men (female:male ratio 2.8). The estimated 2010 prevalence of MS was highest in the 55- to 64-year age group. A US north-south decreasing prevalence gradient was identified. The estimated MS prevalence is also presented for 2017. Conclusion: The estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists. Our rigorous algorithm-based approach to estimating prevalence is efficient and has the potential to be used for other chronic neurologic conditions. Prev of MS in the US-E-Appendix-Feb-19-2018

Bien que les individus atteints de schizophrénie présentent un risque élevé de manifester des comportements agressifs par rapport à la population générale, peu d'efforts ont été consacrés à élucider les mécanismes neurocognitifs sous-jacents à cette augmentation. L'objectif de cette thèse était d'étudier les processus susceptibles d'être perturbés dans cette population spécifique de patients, notamment le traitement des émotions, le contrôle cognitif et le traitement de la récompense. À cette fin, nous avons eu recours à l'imagerie par résonance magnétique fonctionnelle basée sur des tâches, à de grands échantillons et à des groupes de contrôle appropriés de patients et de non-patients. Dans le premier échantillon de participants, nous avons évalué les altérations neurofonctionnelles chez des hommes souffrant de schizophrénie et ayant des antécédents de comportements agressifs en utilisant une tâche de traitement des émotions basée sur des images émotionnelles standardisées. Dans la première étude, les hommes violents atteints de schizophrénie ont montré une augmentation de la réponse du cortex cingulaire antérieur (ACC) aux images négatives, contrairement aux sujets sains et schizophrènes non-violents. La deuxième étude a approfondi ces résultats en identifiant une topologie perturbée de connectivité fonctionnelle basée sur la tâche au sein du réseau de la saillance émotionnelle pendant le traitement des émotions negatives. Ceci suggère une intégration inefficace des informations par l'ACC entre les régions frontales et limbiques. Ensemble, ces résultats soulignent l'importance de l'ACC dans la neurobiologie des comportements agressifs dans la schizophrénie. Dans le deuxième échantillon de participants, nous avons évalué le contrôle cognitif et le traitement de la récompense dans l'agression. Dans la troisième étude, nous avons examiné l'interaction entre le traitement des émotions négatives et le contrôle cognitif chez les hommes atteints de schizophrénie et ayant des antécédents de violence en emplyant une tâche Go-NoGo émotionnelle utilisant des stimuli de visages neutres et en colère. Nous avons constaté une activation réduite dans le cortex préfrontal dorsolatéral chez les hommes violents atteints de schizophrénie, en particulier lorsqu'ils inhibaient une réponse en regardant des visages en colère. Ces résultats indiquent une incapacité à recruter une région centrale du réseau de contrôle cognitif dans le contexte de la colère. Dans la quatrième étude, nous avons cherché à investiguer l'altération de la prise de décision liée à la récompense et son association avec l'agressivité dans la schizophrénie en utilisant le Balloon Analogue Risk Task. La tâche n'a pas fait ressortir de différences entre les hommes violents et non violents atteints de schizophrénie. Néanmoins, nous avons observé des activations plus élevées dans le striatum et l'insula en réponse à des événements de récompense, suggérant potentiellement que la surévaluation des stimuli de récompense peut être à la base des capacités de prise de décision altérées des individus atteints de schizophrénie. Cette thèse est la première à identifier des altérations de l'activité cérébrale fonctionnelle et de la connectivité pendant le traitement des émotions négatives chez des hommes agressifs atteints de schizophrénie. C'est également la première à observer des mécanismes neuronaux altérés impliqués dans l'interaction entre le contrôle cognitif et le traitement de la colère chez des hommes violents atteints de schizophrénie. Despite individuals with schizophrenia being at an elevated risk for aggressive behaviors compared to the general population, limited efforts have been devoted to understanding the neurocognitive mechanisms underlying the increase. The objective of this dissertation was to investigate processes thought to be disrupted in this specific patient population including emotion processing, cognitive control, and reward processing. To this end, we utilized task-based functional magnetic resonance imaging, large samples, and appropriate patient and non-patient control groups. In the first sample of participants, we assessed neurofunctional alterations in men with schizophrenia and a history of aggressive behaviors using an emotional processing task based on standardized affective photographs. In the first study, violent men with schizophrenia displayed increased anterior cingular cortex (ACC) response to negative images as opposed to non-violent healthy individuals and individuals with schizophrenia. The second study expanded on these results by identifying disrupted task-based functional connectivity topology within the emotional-salience network during negative emotion processing suggestive of inefficient information integration by the ACC between frontal and limbic regions. Together, these highlight the importance of the ACC in the neurobiology of aggressive behaviors in schizophrenia. In the second sample of participants, we assessed cognitive control and reward processing in aggression. In the third study, we investigated the interaction between negative emotion processing and inhibitory control among men with schizophrenia and a history of violence by employing an affective Go-NoGo task utilizing angry and neutral face stimuli. We found a reduced activation in the dorsolateral prefrontal cortex in violent men with schizophrenia specifically when inhibiting a response while viewing angry faces. These results are indicative of an inability to recruit a core region of the cognitive control network in the context of anger. In the fourth study, we aimed to investigate impaired reward-related decision-making and its association with aggression in schizophrenia using the Balloon Analogue Risk Task. The task did not elicit differences between violent and non-violent men with schizophrenia. Nevertheless, we observed increased activations in the striatum and insula in response to reward events potentially suggesting that overvaluation of outcome stimuli may underlie the impaired decision-making abilities of individuals with schizophrenia. This dissertation is the first to identify alterations in functional brain activity and connectivity during the processing of negative emotions among aggressive men with schizophrenia. This is also the first to observe impaired neural mechanisms involved in the interaction between cognitive control and anger processing among violent men with schizophrenia.

This article reviews possible ways that traumatic brain injury (TBI) can induce migraine-type post-traumatic headaches (PTHs) in children, adults, civilians, and military personnel. Several cerebral alterations resulting from TBI can foster the development of PTH, including neuroinflammation that can activate neural systems associated with migraine. TBI can also compromise the intrinsic pain modulation system and this would increase the level of perceived pain associated with PTH. Depression and anxiety disorders, especially post-traumatic stress disorder (PTSD), are associated with TBI and these psychological conditions can directly intensify PTH. Additionally, depression and PTSD alter sleep and this will increase headache severity and foster the genesis of PTH. This article also reviews the anatomic loci of injury associated with TBI and notes the overlap between areas of injury associated with TBI and PTSD.

L’objectif de cette thèse était la validation de l’existence ainsi que la découverte de nouveaux sous-types au sein de la maladie d’Alzheimer, première cause de démence au monde. Afin d’explorer son hétérogénéité, nous avons employé des méthodes d’apprentissage profond appliquées à une modalité de neuroimagerie, l’imagerie par résonance magnétique structurelle.Cependant, la découverte de biais méthodologiques importants dans de nombreuses études de notre domaine, ainsi que l’absence de consensus de la communauté sur la manière d’interpréter les résultats des méthodes d’apprentissage profond a fait en partie dévier la thèse de son objectif principal pour s’orienter d’avantage vers des problématiques de validation, de robustesse et d’interprétabilité de l’apprentissage profond. Ainsi, trois études expérimentales ont été menées pour s’assurer de la capacité des réseaux profonds de correctement détecter la maladie. La première est une étude expérimentale de méthodes d’apprentissage profond pour la classification de la maladie d’Alzheimer et a permis d’établir une juste comparaison des méthodes. La seconde étude a permis de constater un manque de robustesse de la classification avec l’apprentissage profond en termes de motifs d’atrophie découverts à l’aide de méthodes d’interprétabilité. Enfin, la dernière étude propose une méthode de découverte de sous-types aidée par l’augmentation de données. Bien que fonctionnant sur des données synthétiques, celle-ci ne généralise pas aux données réelles.Une contribution majeure de la thèse est la librairie ClinicaDL, grâce à laquelle les résultats expérimentaux de la thèse ont été produits de manière à être reproductibles. The goal of this PhD was the validation of the existence and the discovery of new subtypes of Alzheimer’s disease, the first cause of dementia worldwide. Indeed, despite its discovery more than a century ago, this disease is still not well defined and existing treatments are only weakly effective, possibly because several phenotypes exist within the disease. In order to explore its heterogeneity, we employed deep learning methods applied to a neuroimaging modality, structural magnetic resonance imaging.However, the discovery of important methodological biases in many studies in our field, as well as the lack of consensus regarding deep learning interpretability, partly changed the main objective of the PhD to focus more on issues of validation, robustness and interpretability of deep learning. Then, to correctly assess the ability of deep learning to detect Alzheimer’s disease, three experimental studies were conducted. The first one is a study of deep learning methods for Alzheimer’s classification and allowed a fair comparison of the methods. The second study found a lack of robustness of classification with deep learning in terms of atrophy patterns discovered using interpretability methods. Finally, the last study proposed a subtype discovery method aided by data augmentation. Although it works on synthetic data, it does not generalize to real data.Experimental results of this PhD were obtained thanks to ClinicaDL, one major contribution of this PhD. It is an open source Python library that was used to improve the reproducibility of deep learning experiments.

Multiple sclerosis (MS) is an immune-mediated demyelinating disorder of the central nervous system (CNS) that leads to neurodegeneration. Remyelination is an essential reparative process in MS. While remyelination occurs efficiently during the early stages of the disease, it significantly declines with disease progression. This is despite the presence of oligodendrocyte progenitor cells (OPCs) within the lesions with the ability to generate new myelinating oligodendrocytes (OLs). Understanding how OPC and OL are regulated in MS lesions is critical to promote remyelination in chronic MS lesions. Emerging studies indicate that a balanced activity of mTOR pathway is essential for normal differentiation and maturation of OLs. Other findings have suggested that the integrated stress response (ISR), which occurs upon phosphorylation of eIF2α, has a protective role in remyelination. In this study, we aimed to characterize the activity of mTOR and the ISR in OPCs and OLs during acute and chronic demyelination and remyelination by using a cuprizone mouse model of demyelination. We also used primary in vitro systems to assess the changes in OPC maturation under MS-like conditions. We found that mTOR and ISR activity is increased in OPCs and OLs during both acute and chronic demyelination in cuprizone mice, and this expression is sustained during the remyelination period. In vitro, we confirmed that rapamycin-inhibition of mTORC1 results in decreased OPC proliferation and differentiation and inhibit OL maturation and morphological complexity in vitro, while increasing their lysosomal activity. Treating OPCs with MS-relevant cytokines also decreases OPC proliferation acutely and reduces their differentiation while promoting lysosomal activity. This study provides initial data that suggest the involvement of mTOR and ISR in oligodendrocyte behavior in demyelinating lesions. Future studies are required to determine the role of these pathways in impaired remyelination during chronic MS.

Adenosine is a purine nucleoside which plays an important role in many biochemical processes. In addition, it controls many central nervous system (CNS) functions both under physiological and pathophysiological conditions. Adenosine acts through four adenosine receptors (AR), of which adenosine 1 receptors (A1R) and adenosine 2A receptors (A2AR) are of particular importance in CNS. This thesis aimed to investigate adenosine`s role in two major hypoxic conditions of early and late life of humans by changing its receptor functions using receptor antagonists. These two conditions were stroke, a problem in adults/elderly and apnea, a problem of early newborns. Four studies were conducted. In the first study, we used intracortical (IC) endothelin-1 (ET-1) injection in mice to induce a cortical stroke. Using magnetic resonance imaging (MRI), we found that stroke volume was increased in transgenic (Tg) mice with over-expression of the adenosine transport protein equilibrative nucleoside transporter 1 (ENT1). Caffeine, an AR antagonist neutralized this difference. In the second study, we used ET-1 to induce cortical stroke in mice and used the selective A1R antagonist 1,3-dipropyl-8-cyclopentylxanthine (DPCPX). Both MRI and histopathology were used to determine stroke volume. We found a greater stroke size in Tg mice treated with the A1R antagonist. In the third and fourth studies, the effect of antenatal caffeine on ontogeny of ARs and respiratory response to intermittent hypoxia was examined. Antenatal exposure to high dose caffeine caused a significant increase in A1Rs in the striatum on postnatal 1st day (P0). Also, high dose caffeine exposure caused a significant increase in gene expression of A1R and A2ARs in the brain stem (BS). These changes disappeared by postnatal 7th day (P6). There were several detrimental effects of high dose caffeine on pregnancy outcome but prenatal exposure to high dose caffeine did not change the hypoxic respiratory response of newborn rats on P6. We conclude that AR antagonists enhance ET-1 induced stroke injury in mice, however we did not observe a detrimental effect of antenatal caffeine on postnatal respiratory responses to transient hypoxia. Further research is needed to uncover the mechanisms by which AR antagonists affect responses to hypoxic conditions.

This thesis is an investigation of transcranial magnetic motor evoked potentials (TMMEP), somatosensory evoked potentials (SSEP), spinal evoked potentials (SEP) and brainstem auditory evoked responses (BAER) for the assessment of descending motor and ascending sensory pathways throughout the central nervous system of Cavalier King Charles Spaniel (CKCS) dogs with and without magnetic resonance imaging (MRI) confirmed syringomyelia. Fifty CKCS dogs were assigned into one of four groups, A (neurologic abnormalities and MRI-confirmed SM), B (neurologic abnormalities and no evidence of SM on MRI), C (no neurologic abnormalities and MRI-confirmed SM), and D (normal neurologic examination and no evidence of SM on MRI). Group D served as the control population for data analysis. Transcranial magnetic motor evoked potentials, SSEP, SEP, and BAER were performed on all dogs under sedation. Onset latencies were measured for TMMEP, SSEP, and SEP, and I-V interpeak latencies were measured for BAER. Dogs were anesthetized for brain and spinal cord MRI (cervical, thoracic, lumbar) including sagittal and transverse T2-weighted images. Transverse T2-weighted image sequences were acquired on all regions of the spinal cord affected with SM to measure syrinx size (mm2) at maximum diameter and area of the surrounding spinal cord in order to obtain an overall percentage of spinal cord affected by SM. There were no significant differences in mean latencies between groups A, B, C, and D for TMMEP, SSEP, SEP and BAER. There was, however, a significant linear association between severity of neurologic signs and syrinx size: the larger the syrinx, the more severe the neurologic signs. Additionally, dogs with SM affecting more than 28% of their spinal cord were more likely to exhibit neurologic signs. The results of this study suggest that TMMEP, SEP, SSEP and BAER tests do not detect functional abnormalities of the central nervous system in CKCS dogs with and without SM.

Les récentes avancées dans le domaine de l'intelligence artificielle ont ouvert la voie au développement de nouveaux modèles d'activité cérébrale. Les réseaux neuronaux artificiels (RNA) formés à des tâches complexes, telles que la reconnaissance d'images, peuvent être utilisés pour prédire la dynamique cérébrale en réponse à une série de stimuli avec une précision sans précédent, un processus appelé encodage cérébral. Les jeux vidéo ont fait l'objet d'études approfondies dans le domaine de l'intelligence artificielle, mais n'ont pratiquement pas été utilisés pour l'encodage cérébral. Les jeux vidéo offrent un cadre prometteur pour comprendre l'activité cérébrale dans un environnement riche, engageant et actif, contrairement aux tâches essentiellement passives qui dominent actuellement le domaine, telles que la visualisation d'images. Un défi majeur soulevé par les jeux vidéo complexes est que le comportement individuel est très variable d'un sujet à l'autre, et nous avons émis l'hypothèse que les RNAs doivent prendre en compte le comportement spécifique du sujet afin de capturer correctement les dynamiques cérébrales. Dans cette étude, nous avons cherché à utiliser des RNAs pour modéliser l'imagerie par résonance magnétique fonctionnelle (IRMf) et les données comportementales des participants, que nous avons collectées pendant que les sujets jouaient au jeu vidéo Shinobi III. En utilisant l'apprentissage par imitation, nous avons entraîné un RNA à jouer au jeu vidéo en reproduisant fidèlement le style de jeu unique de chaque participant. Nous avons constaté que les couches cachées de notre modèle d'apprentissage par imitation parvenaient à encoder des représentations neuronales pertinentes pour la tâche et à prédire la dynamique cérébrale individuelle avec une plus grande précision que divers modèles de contrôle, y compris des modèles entraînés sur les actions d'autres sujets. Les corrélations les plus fortes entre les activations des couches cachées et les signaux cérébraux ont été observées dans des zones cérébrales biologiquement plausibles, à savoir les réseaux somatosensoriels, attentionnels et visuels. Nos résultats soulignent le potentiel de la combinaison de l'apprentissage par imitation, de l'imagerie cérébrale et des jeux vidéo pour découvrir des relations spécifiques entre le cerveau et le comportement. Recent advances in the field of Artificial Intelligence have paved the way for the development of novel models of brain activity. Artificial Neural networks (ANN) trained on complex tasks, such as image recognition and language processing, can be used to predict brain dynamics in response to wide range of stimuli with unprecedented accuracy, a process called brain encoding. Videogames have been extensively studied in the AI field, but have hardly been used yet for brain encoding. Videogames provide a promising framework to understand brain activity in rich, engaging and active environments, in contrast to mostly passive tasks currently dominating the field, such as image viewing. A major challenge raised by complex videogames is that individual behavior is highly variable across subjects, and we hypothesized that ANNs need to account for subject-specific behavior in order to properly capture brain dynamics. In this study, we aimed to use ANNs to model functional magnetic resonance imaging (fMRI) and behavioral gameplay data, which we collected while subjects played the Shinobi III videogame. Using imitation learning, we trained an ANN to play the game closely replicating the unique gameplay style of individual participants. We found that hidden layers of our imitation learning model successfully encode task-relevant neural representations and predict individual brain dynamics with higher accuracy than various control models, including models trained on other subjects' actions. The highest correlations between layer activations and brain signals were observed in biologically plausible brain areas, i.e. somatosensory, attentional and visual networks. Our results highlight the potential of combining imitation learning, brain imaging, and videogames to uncover subject-specific relationships between brain and behavior.