Dissertations / Theses on the topic 'Cortical layers'

The neocortex covers 90% of the human cerebral cortex [41] and is responsible for higher cognitive function and socio-cognitive skills in all mammals. It is known to be structured in layers and in some species or cortical areas, in columns. A balanced network model was built, which incorporated these structural organizations and in particular, the layers, minicolumns and hypercolumns. The dynamics of eight different network models were studied, based on combinations of structural organizations that they have. The eigenvalue spectra of their matrices was calculated showing that layered networks have eigenvalues outside their bulk distribution in contrast to networks with columns and no layers. It was demonstrated, through simulations, that networks with layers are unstable and have a lower threshold to synchronization, thus, making them more susceptible to switch to synchronous and regular activity regimes [10]. Moreover, introduction of minicolumns to these networks was observed to partially counterbalance synchrony and regularity, in the network and neuron activity, respectively. Layered networks, principally the ones without minicolumns, also have higher degree correlations and a reduced size of potential pre- and post- connections, which induces correlations in the neuronal activity and oscillations.

Visual attention improves sensory processing, as well as perceptual readout and behavior. Over the last decades, many proposals have been put forth to explain how attention affects visual neural processing. These include the modulation of neural firing rates and synchrony, neural tuning properties, and rhythmic, subthreshold activity. Despite the wealth of knowledge provided by previous studies, the way attention shapes interactions between cortical layers within and between visual sensory areas is only just emerging. To investigate this, we studied neural signals from macaque V1 and V4 visual areas, while monkeys performed a covert, feature-based spatial attention task. The data were simultaneously recorded from laminar electrodes disposed normal to cortical surface in both areas (16 contacts, 150 μm inter-contact spacing). Stimuli presentation was based on the overlap of the receptive fields (RFs) of V1 and V4. Channel depths alignment was referenced to laminar layer IV, based on spatial current source density and temporal latency analyses. Our analyses mainly focused on the study of Local Field Potential (LFP) signals, for which we applied local (bipolar) re-referencing offline. We investigated the effects of attention on LFP spectral power and laminar interactions between LFP signals at different depths, both at the local level within V1 and V4, and at the inter-areal level across V1 and V4. Inspired by current progress from literature, we were interested in the characterization of frequency-specific laminar interactions, which we investigated both in terms of rhythmic synchronization by computing spectral coherence, and in terms of directed causal influence, by computing Granger causalities (GCs). The spectral power of LFPs in different frequency bands showed relatively small differences along cortical depths both in V1 and in V4. However, we found attentional effects on LFP spectral power consistent with previous literature. For V1 LFPs, attention to stimuli in RF location mainly resulted in a shift of the low-gamma (∼30-50 Hz) spectral power peak towards (∼3-4 Hz) higher frequencies and increases in power for frequency bands above low-gamma peak frequencies, as well as decreases in power below these frequencies. For V4 LFPs, attention towards stimuli in RF locations caused a decrease in power for frequencies < 20 Hz and a broad band increase for frequencies > 20 Hz. Attention affected spectral coherence within V1 and within V4 layers in similar way as the spectral power modulation described above. Spectral coherence between V1 and V4 channel pairs was increased by attention mainly in the beta band (∼ 15-30 Hz) and the low-gamma range (∼ 30-50 Hz). Attention affected GC interactions in a layer and frequency dependent manner in complex ways, not always compliant with predictions made by the canonical models of laminar feed-forward and feed-back interactions. Within V1, attention increased feed-forward efficacy across almost all low-frequency bands (∼ 2-50 Hz). Within V4, attention mostly increased GCs in the low and high gamma frequency in a 'downwards' direction within the column, i.e. from supragranular to granular and to infragranular layers. Increases were also evident in an ‘upwards’ direction from granular to supragranular layers. For inter-areal GCs, the dominant changes were an increase in the gamma frequency range from V1 granular and infragranular layers to V4 supragranular and granular layers, as well as an increase from V4 supragranular layers to all V1 layers.

The subplate layer of the cerebral cortex is comprised of a heterogeneous population of cells and contains some of the earliest-generated neurons. Subplate plays a fundamental role in cortical development. In the embryonic brain, subplate cells contribute to the guidance and areal targeting of corticofugal and thalamic axons. At later stages, these cells are involved in the maturation and plasticity of the cortical circuitry and the establishment of functional modules. In my thesis, I aimed to further characterize the embryonic murine subplate by establishing a gene expression profile of this population at embryonic day 15.5 (E15.5) using laser capture microdissection combined with microarrays. I found over 250 transcripts with presumed higher expression in the subplate at E15.5. Using quantitative RT-PCR, in situ hybridization and immunohistochemistry, I have confirmed specific expression in the E15.5 subplate for 13 selected genes which have not been previously associated with this compartment. In the reeler mutant, the expression pattern of a majority of these genes was shifted in accordance with the altered position of subplate cells. These genes belong to several functional groups and likely contribute to the maturation and electrophysiological properties of subplate cells and to axonal growth and guidance. The roles of two selected genes - cadherin 10 (Cdh10) and Unc5 homologue c (Unc5c) - were explored in more detail. Preliminary results suggest an involvement of Cdh10 in subplate layer organization while Unc5c could mediate the waiting period of subplate corticothalamic axons in the internal capsule. Finally, I compared the expression of a selection of subplate-specific genes (subplate markers) between mouse and rat and found some surprising species differences. Confirmed subplate markers were used to monitor subplate injury in a rat model of preterm hypoxiaischemia and it appeared that deep cortical layers including subplate showed an increased vulnerability over upper layers. Further characterization of subplate-specific genes will allow us to broaden our understanding of molecular mechanisms underlying subplate properties and functions in normal and pathological development.

Le principe de codage efficace suggère que le traitement des informations dans le système visuel primaire est optimisé et adapté aux statistiques de l’environnement. Une étude intracellulaire menée dans le cortex visuel primaire (V1) du chat anesthésié et paralysé a démontré que la reproductibilité des réponses neuronales est optimisée lorsque des statistiques naturelles sont présentées. En utilisant les mêmes stimuli artificiels et naturels, nous avons enregistré, à l’aide d’électrodes laminaires denses, l’activité neuronale (activité unitaire, multi-unitaire et potentiel de champ local) dans le cortex visuel primaire du chat. Dans un 1er temps, nous avons étudié la reproductibilité de l’activité neuronale et sa dépendance laminaire. Nos résultats démontrent que les images naturelles induisent toujours la réponse la plus reproductible, suggérant une optimisation de V1 dans le traitement des statistiques naturelles. De plus, nous avons montré que les couches 4 et 5/6 présentent des réponses plus reproductibles que la couche 2/3. Cela suggère qu’un « filtrage fonctionnel » des informations pertinentes se produit entre ces différents compartiments laminaires. Dans un 2nd temps nous avons étudié la corrélation de la réponse ou de la variabilité de la réponse de neurones situés dans une même couche ou dans des couches différentes. Les niveaux de corrélation sont les plus élevées lorsque les images naturelles sont présentées. De plus, les corrélations sont plus fortes au sein d’une même couche qu’entre deux couches. Cela suggère qu’un regroupement fonctionnel des neurones se produit afin d’optimiser l’encodage de l’information visuelle
The principle of efficient coding suggests that processing in the early visual system should be optimized and adapted to the environmental statistics. An intracellular study of the primary visual cortex (V1) in the anesthetized and paralyzed cat showed that the reliability of the neural response is optimized for natural statistics. Using the same natural and artificial stimuli, we recorded the neuronal population activity (single unit, multi-unit and local field potentials) in cat’s V1 with high-density linear silicon probes. We first investigated the reliability and of the mesoscopic signal with the intracellular signal and explored its laminar dependency. Our results showed that natural images evoke, at all scales, the most reliable response, suggesting that V1 is better suited to efficiently encode natural statistics. In addition, granular and infragranular layers displayed higher reliability levels than the supragranular one. This argues for a functional filtering of the pertinent information between these layers. We also explored which statistics of the natural images produce this reliable response. Finally, we specifically addressed the role of the correlations between neurons (within and between layers) by measuring the amount of shared variability and signal of the neuronal population in response to our stimulus set. We observed that natural images always evoked higher correlations. We did not observe a strong decorrelation at the single cell level but instead at the scale of groups of neurons, with those that are close together being more correlated and farther apart less correlated, arguing for a functional clustering of the neurons into coherent “neural mass”

Mitochondrial metabolism of reactive oxygen species (ROS) is tightly regulated during brain development. Imbalance has been correlated to neuropsychiatric disorders. Nevertheless, the contribution of ROS accumulation to aberrant cortical circuit organization and function remains unknown. Individuals with 22q11 deletion syndrome (22q11DS) are highly susceptible to psychiatric disorders; therefore, 22q11DS has been suggested as a model for studying the neurodevelopmental origins of these disorders. Six genes –Mrpl40, Tango2, Prodh, Zdhhc8, Txnrd2 and Scl25a1– located in the 22q11DS commonly deleted region encode proteins that localize to mitochondria. This project aimed to characterize the effects of altered mitochondrial function, due to diminished dosage of these genes, on cortical projection neuron development, using the LgDel mouse model of 22q11DS. I found growth deficits in LgDel neurons that are due to increased mitochondrial ROS and are Txnrd2-dependent. Antioxidant treatment, by n-acetyl cysteine (NAC), rescues neuronal morphogenesis in LgDel and Txnrd2-depleted neurons in vitro and in vivo. Electroporation of Txnrd2 restores ROS levels and normal dendritic and axonal growth. Txnrd2-dependent redox regulation underlies a key aspect of cortical circuit differentiation in a mouse model of 22q11DS. These studies define the effects of mitochondrial accumulation of ROS on neuronal integrity, and establish the role of altered pyramidal neuron differentiation in the formation of circuits in 22q11DS. These data provide novel insight into the role of redox imbalance in aberrant development of cortical circuits.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, February 2017.
Cataloged from PDF version of thesis. "September 2016."
Includes bibliographical references.
Neocortex learns predictive models of sensory input, allowing mammals to anticipate future events. A fundamental component of this process is the comparison between expected and actual sensory input, and the layered architecture of neocortex is presumably central to this computation. In this thesis, I examine the role of laminar differences, and specifically the role of layer 6 (L6) in the encoding and perception of stimuli that deviate from previous patterns. In awake mice, layer 4 neurons encode current stimulus deviations with a predominantly monotonic, faithful encoding, while neurons in layer 2/3 encode history dependent change signals with heterogeneous receptive fields. Corticothalamic (CT) cells in Layer 6 respond sparsely, but faithfully encode stimulus identity. Weak optogenetic drive of L6 CT cells disrupted this encoding in layer 6 without affecting overall firing rates. This manipulation also caused layer 2/3 to represent only current stimuli. In a head-fixed stimulus detection task, small stimulus deviations typically make stimuli more detectable, and the L6 manipulation removed this effect, without affecting detection of non-changing stimuli. Analogously, in free sensory decision making behavior, the manipulation selectively impaired perception of deviant stimuli, without affecting basic performance. In contrast, stronger L6 drive reduced sensory gain and impaired tactile sensitivity. These results show an explicit laminar encoding of stimulus changes, and that L6 can play a role in the perception of sensory changes by modulating responses depending on previous, or expected input. This finding provides a new perspective on how the layered cortical architecture can implement computations on hierarchical models of the world.
by Jakob Voigts.
Ph. D.

To fully understand how the brain works, it is necessary to relate the brain’s function to its anatomy. Cortical anatomy is subject-specific. It is character- ized by the thickness and number of intracortical layers, which differ from one cortical area to the next. Each cortical area fulfills a certain function. With magnetic res- onance imaging (MRI) it is possible to study structure and function in-vivo within the same subject. The resolution of ultra-high field MRI at 7T allows to resolve intracortical anatomy. This opens the possibility to relate cortical function of a sub- ject to its corresponding individual structural area, which is one of the main goals of neuroimaging. To parcellate the cortex based on its intracortical structure in-vivo, firstly, im- ages have to be quantitative and homogeneous so that they can be processed fully- automatically. Moreover, the resolution has to be high enough to resolve intracortical layers. Therefore, the in-vivo MR images acquired for this work are quantitative T1 maps at 0.5 mm isotropic resolution. Secondly, computational tools are needed to analyze the cortex observer-independ- ently. The most recent tools designed for this task are presented in this thesis. They comprise the segmentation of the cortex, and the construction of a novel equi-volume coordinate system of cortical depth. The equi-volume model is not restricted to in- vivo data, but is used on ultra-high resolution post-mortem data from MRI as well. It could also be used on 3D volumes reconstructed from 2D histological stains. An equi-volume coordinate system yields firstly intracortical surfaces that follow anatomical layers all along the cortex, even within areas that are severely folded where previous models fail. MR intensities can be mapped onto these equi-volume surfaces to identify the location and size of some structural areas. Surfaces com- puted with previous coordinate systems are shown to cross into different anatomical layers, and therefore also show artefactual patterns. Secondly, with the coordinate system one can compute cortical traverses perpendicularly to the intracortical sur- faces. Sampling intensities along equi-volume traverses results in cortical profiles that reflect an anatomical layer pattern, which is specific to every structural area. It is shown that profiles constructed with previous coordinate systems of cortical depth disguise the anatomical layer pattern or even show a wrong pattern. In contrast to equi-volume profiles these profiles from previous models are not suited to analyze the cortex observer-independently, and hence can not be used for automatic delineations of cortical areas. Equi-volume profiles from four different structural areas are presented. These pro- files show area-specific shapes that are to a certain degree preserved across subjects. Finally, the profiles are used to classify primary areas observer-independently.

Pyramidal cells are the principal excitatory neurons in the cerebral cortex and those in layer 5 (L5) form its primary output. Tufted L5 pyramidal cells present a complex morphology, with non-uniform distributions of active membrane conductances. Their dendritic tree receives thousands of synaptic inputs from local circuits as well as long range inputs from other cortical regions and thalamic nuclei. Hence, the timing of their synaptic inputs are likely to span a wide range of temporal scales, raising the question of how an individual L5 pyramidal cell combines and transforms such temporally and spatially diverse signals. The integrative properties of pyramidal neurons have been extensively studied in vitro and several models have been suggested for the computations performed by these cells. However, cortical pyramidal cells in vivo are constantly bombarded by asynchronous synaptic input, re ecting the activity of the network in which they are embedded. Little is known about how the resulting background activity interacts with nonlinear dendritic properties. I have used experimentally-constrained models of L5 pyramidal neurons to explore synaptic integration under a range of di erent conditions including those measured in vivo. The major result from this study is that background synaptic activity can profoundly alter the integrative properties of pyramidal cells, by activating a distributed NMDA receptor conductance. This distributed nonlinear conductance lowers the threshold for dendritic spikes generation, extends the spikes duration and increases the probability of additional regenerative events occurring in neighbouring branches. Simulations with mixed excitatory/inhibitory background also suggest that dendritic inhibition may be speci cally tuned to regulate this powerful re-generative mechanism. My results suggest a new role for NMDA receptors. During the network activity experienced by pyramidal neurons in vivo, the distributed NMDA conductance may enable pyramidal cells to integrate synaptic input over extended spatio-temporal scales.

Cette thèse présente le développement d’une méthodologie qui permet d’analyser la structure en couches du cortex cérébral, en utilisant l’imagerie par résonance magnétique en champ intense (IRM à 7 teslas). Alors que l’architecture corticale est traditionnellement étudiée par imagerie microscopique de coupes de tissu post-mortem, l’utilisation d’une technique non invasive telle que l’IRM permet d’envisager d’étudier la lamination corticale in vivo, et ainsi de dépasser les atlas architecturaux classiques comme celui de Brodmann.Deux approches ont été utilisées pour l’acquisition d’images à haute résolution. La première, développée pour l’imagerie in vivo, utilise une reconstruction super-résolue à partir de coupes épaisses acquises dans différentes géométries. La seconde, basée sur une séquence tridimensionnelle optimisée pour l’imagerie post-mortem, a permis l’acquisition d’images de pièces anatomiques.La contribution principale de cette thèse réside dans le développement d’un couple de méthodes permettant d’extraire automatiquement, en chaque point du cortex, un profil caractérisant son architecture en couches. Pour permettre l’extraction robuste de ces profils, un modèle original de l’influence de la courbure corticale a été développé et implémenté.Ces méthodes ont été testées et validées sur plusieurs pièces anatomiques. Ce travail permet d’envisager la caractérisation de l’architecture des aires corticales, voire leur délimitation automatique, en utilisant l’IRM en champ intense
This thesis presents the development of a methodology for the analysis of the layered structure of the cerebral cortex, using high-field magnetic resonance imaging (7-tesla MRI). While cortical layers are traditionally studied using microscopic imaging of post-mortem tissue slices, the use a non-invasive technique such as MRI will enable in vivo studies, and thus allow new approaches beyond the use of classical architectural atlases such as Brodmann's.Two imaging methodologies have been used to acquire high-resolution images. First, a method based on super-resolution reconstruction from thick slices acquired in different geometries was developed for in vivo imaging. Second, a three-dimensional imaging sequence optimized for post-mortem tissue allowed imaging excised brain specimen.The main contribution of this thesis consists of a pair of methods that perform an automatic extraction of cortical profiles, which characterize the laminar architecture at any cortical location. In order to allow robust extraction of these profiles, an original model of the influence of cortical curvature was developed and implemented.These methods were tested and validated on multiple brain specimen. This work allows envisaging an automatic microarchitectural characterization of cortical areas, and even architectural parcellation, using high-field MRI

Following traumatic brain injury (TBI), the hippocampus is particularly vulnerable to damage, and BDNF, an endogenous neurotrophin that activates the TrkB receptor, has been shown to play a key role in the brain’s neuroprotective response. Activation of the TrkB signaling pathway by BDNF in the CNS promotes cell survival and aids in cell growth. However, due to its inability to cross the blood brain barrier (BBB), the therapeutic advantages of BDNF treatment following TBI are limited. 7,8-Dihydroxyflavone (7,8-DHF) is a flavonoid that mimics the effects of BDNF, is a potent TrkB receptor agonist, and can successfully cross the BBB. Our lab has previously demonstrated that administration of 7,8-DHF post-TBI results in improved cognitive functional recovery, increased neuronal survival, and reduced lesion volume. The current study examined the effects of 7,8-DHF on neurogenesis and neuronal migration in the dentate gyrus following TBI. In this study, adult male Sprague-Dawley rats were subjected to moderate controlled cortical impact injury (CCI) or sham surgery. Injured animals received 5 daily single doses of 7,8-DHF treatment (i.p) or vehicle starting either 60 mins after injury or 2 days after injury. BrdU was administered in 3 doses at 2 days post-injury for animals sacrificed at day 15, and single daily doses at days 1-7 post-injury for animals sacrificed at day 28 to label cell proliferation. Animals were sacrificed at 15 days or 28 days post-injury to examine cell proliferation, generation of new neurons, and differentiation of newly generated cells using proliferation marker Ki67, immature neuronal marker DCX, and BrdU double-labeling with markers for mature neurons (NeuN), astrocytes (GFAP) and microglia (Iba1). We found that administration of 5 doses (5mg/kg) of 7,8-DHF beginning two days post-injury had the strongest effect on neurogenesis and migration, but did not have a significant prolonged effect on cell proliferation at 15 days post-injury. We also found that 7,8-DHF treatment given early or 2 days post-TBI did not affect the neuronal differentiation in the granule cell layer. However, a higher percentage of BrdU/GFAP+ and BrdU/IBa1+ cells were found in the hilus regions in 7,8-DHF treated animals, suggesting newly generated cells in this region are mostly glial cell types. Our results suggest that 7,8-DHF has neurotrophic-like therapeutic effects following injury, and due to increased neurogenesis (compared to injured animals treated with vehicle), may effectively contribute to greater cell survival long-term. Additionally, potential long-term survival coupled with increased outward migration from the subgranular zone may result in increased integration of newly formed neurons into existing hippocampal circuitry, further contributing to cognitive recovery.

Le cortex cérébral contrôle des fonctions complexes comme la perception sensorielle, le comportement moteur ou la cognition par le biais de circuits très organisés. Ces circuits se développent dans l'embryon et les mauvais câblages sont liés à l'étiologie de troubles neurodéveloppementaux comme l‘Autisme ou la Schizophrénie. La couche la plus superficielle du cortex, la couche 1 (L1), joue un rôle central dans le fonctionnement du cerveau. Elle permet l'intégration des informations de la périphérie par des stimuli internes, ce qui façonnent notre perception. Bien qu'il soit de plus en plus évident que la L1 joue un rôle important dans l'intégration sensorielle, les connaissances sur sa formation sont limitées. Le câblage de L1 est modelé par la densité des cellules de Cajal-Retzius (CRc), une population transitoire de neurones corticaux, qui façonnent les circuits corticaux sous-jacents. Cependant, il reste à déchiffrer comment la densité et l'élimination des CRc sont régulées et si les CRc sont essentielles au câblage cortical. Ici, nous avons démontré que i) la densité des CRc est étroitement maintenue pendant le développement et n'est pas affectée par l'activité sensorielle précoce, ii) l'élimination de sous-populations de CRc est activité-dépendente et iii) les perturbations de la densité et la mort des CRc ont des conséquences à long-terme sur le câblage des circuits sous-jacents. Ces travaux permettent de mieux comprendre les rôles d'une population neuronale transitoire dans la régulation du câblage d'une couche essentielle mais encore peu étudiée du néocortex. Cela permet aussi de comprendre comment les CRc soutiennent la construction du néocortex dans des conditions physiologiques, et comment elles pourraient contribuer aux mauvais câblages menant à différents troubles neurodéveloppementaux
The cerebral cortex controls complex functions like sensory perception, motor behavior or cognition via highly organized circuits. These circuits develop in the embryo and miswirings are linked to the etiology of neurodevelopmental disorders like Autism Spectrum Disorder or Schizophrenia. The most superficial layer of the cortex, layer 1 (L1), is playing a central role in brain function. It enables the integration of inputs from the periphery with internal stimuli, shaping our perception. Although there is increasing evidence that L1 plays important roles in sensory integration, there is limited knowledge about its formation. L1 wiring is regulated by the density of transient inhabitants, the Cajal-Retzius cells, a population of cortical neurons, which shape underlying cortical circuits. However, how CRc density and elimination are regulated and whether CRc are key for cortical wiring remained to be deciphered. Here, we have shown show that i) the density of CRc is tightly maintained during development and is not impacted by early sensory activity, ii) the elimination of subsets of CRc is activity dependent and iii) impairments in both density and death of CRc have long lasting consequences on the wiring of the underlying circuits. This work provides a better understanding of the roles of a transient neuronal population in regulating the wiring of an essential but understudied layer of the neocortex. This is instrumental in understanding how CRc sustain neocortex construction in physiological conditions, and how they could contribute to miswirings leading to different neurodevelopmental disorders

Les objets perceptuels sont les unités élémentaires utilisées par le cerveau pour construire une représentation interne du monde a partir de signaux physiques, comme la lumière ou les ondes sonores. Alors que ces signaux sont d'abord traduit, par les récepteurs dans les organes périphériques, en signaux neuronaux, l'émergence d'objets perceptuels nécessite un traitement intensif dans le système nerveux central qui n'est pas encore entièrement connu. Il est intéressant de noter que les progrès récents de deep learning montrent qu'une séries d'opérations non linéaires et linéaires est très efficace pour catégoriser les objets perceptuels visuels et auditifs de la même manière que les humains. En revanche, la plupart des connaissances actuelles sur le système auditif se concentrent sur les transformations linéaires. Afin de comprendre la contribution des non-linéarités du système auditif à la perception, nous avons étudié l'encodage des sons avec une intensité croissante et une intensité décroissante dans le cortex auditif de la souris. Ces deux sons sont perçus avec une importance inégale malgré le fait qu'ils ont la même énergie physique et le même contenu spectral, un phénomène incompatible avec le traitement linéaire. En enregistrant l'activité de grandes populations corticales pour les sons montants et descendants, nous avons constaté que le cortex les encode avec des populations distinctes qui détectent des caractéristiques non linéaires, ce qui explique l'asymétrie perceptuelle. Nous avons également montré que, dans les modèles de reinforcement learning, la quantité d'activité neuronale déclenchée par un son impacte la vitesse et la stratégie d'apprentissage. Des effets très similaires ont été observés dans plusieurs taches de discrimination ou les sons provoquaient des réponses neuronales de différentes intensités. Ceci établit que les non-linéarités du système auditif ont un impact sur la perception et le comportement. Pour mieux identifier les non-linéarités qui influencent le codage des sons, nous avons ensuite enregistré l'activité d'environ 60 000 neurones échantillonnant toute la superficie du cortex auditif. Au-delà de l'organisation tonotopique à fine échelle découverte avec cet ensemble de données, nous avons identifié et quantifié 7 non-linéarités. Il est aussi intéressant de constater que différentes non-linéarités peuvent interagir entre elles d'une manière non triviale. La connaissance de ces interactions est importante pour affiner le modèle de traitement auditif. Enfin, nous nous sommes demandé si les processus non linéaires sont également importants pour l'intégration multisensorielle. Nous avons mesuré, par imagerie calcique, comment les images et les sons se combinent dans le cortex visuel et auditif. Nous n'avons trouvé aucune modulation du cortex auditif (L2/3) en réponse à des stimuli visuels. Nous avons observé que les entrées du cortex auditif dans le cortex visuel affectent les réponses visuelles concomitantes à un son. Nous avons constaté que les projections du cortex auditif au cortex visuel encode de préférence une caractéristique non linéaire particulière : l'apparition soudaine de sons fort. Par conséquent, l'activité du cortex visuel pour une image et un son fort est plus élevée que pour l'image seule ou combinée à un son faible. Ce résultat suggère que les sons forts sont pertinents du point de vue de comportement multisensoriel, peut-être pour indiquer la présence de nouveaux objets dans le champ visuel, ce qui pourrait représenter des menaces potentielles. En conclusion, nos résultats montrent que les non-linéarités sont omniprésentes dans le traitement du son par le cerveau et jouent également un rôle dans l'intégration de l'information auditive avec l'information visuelle. Il est non seulement crucial de tenir compte de ces non-linéarités pour comprendre comment se forment les représentations perceptuelles, mais aussi pour prédire l'impact de ces représentations sur le comportement
Perceptual objects are the elementary units used by the brain to construct an inner world representation of the environment from multiple physical sources, like light or sound waves. While the physical signals are first encoded by receptors in peripheral organs into neuroelectric signals, the emergence of perceptual object require extensive processing in the central nervous system which is not yet fully characterized. Interestingly, recent advances in deep learning shows that implementing series of nonlinear and linear operations is a very efficient way to create models that categorize visual and auditory perceptual objects similarly to humans. In contrast, most of the current knowledge about the auditory system concentrates on linear transformations. In order to establish a clear example of the contribution of auditory system nonlinearities to perception, we studied the encoding of sounds with an increasing intensity (up ramps) and a decreasing intensity (down ramps) in the mouse auditory cortex. Two behavioral tasks showed evidence that these two sounds are perceived with unequal salience despite carrying the same physical energy and spectral content, a phenomenon incompatible with linear processing. Recording the activity of large cortical populations for up- and down-ramping sounds, we found that cortex encodes them into distinct sets of non-linear features, and that asymmetric feature selection explained the perceptual asymmetry. To complement these results, we also showed that, in reinforcement learning models, the amount of neural activity triggered by a stimulus (e.g. a sound) impacts learning speed and strategy. Interestingly very similar effects were observed in sound discrimination behavior and could be explain by the amount of cortical activity triggered by the discriminated sounds. This altogether establishes that auditory system nonlinearities have an impact on perception and behavior. To more extensively identify the nonlinearities that influence sounds encoding, we then recorded the activity of around 60,000 neurons sampling the entire horizontal extent of auditory cortex. Beyond the fine scale tonotopic organization uncovered with this dataset, we identified and quantified 7 nonlinearities. We found interestingly that different nonlinearities can interact with each other in a non-trivial manner. The knowledge of these interactions carry good promises to refine auditory processing model. Finally, we wondered if the nonlinear processes are also important for multisensory integration. We measured how visual inputs and sounds combine in the visual and auditory cortex using calcium imaging in mice. We found no modulation of supragranular auditory cortex in response to visual stimuli, as observed in previous others studies. We observed that auditory cortex inputs to visual cortex affect visual responses concomitant to a sound. Interestingly, we found that auditory cortex projections to visual cortex preferentially channel activity from neurons encoding a particular non-linear feature: the loud onset of sudden sounds. As a result, visual cortex activity for an image combined with a loud sound is higher than for the image alone or combine with a quiet sound. Moreover, this boosting effect is highly nonlinear. This result suggests that loud sound onsets are behaviorally relevant in the visual system, possibly to indicate the presence of a new perceptual objects in the visual field, which could represent potential threats. As a conclusion, our results show that nonlinearities are ubiquitous in sound processing by the brain and also play a role in the integration of auditory information with visual information. In addition, it is not only crucial to account for these nonlinearities to understand how perceptual representations are formed but also to predict how these representations impact behavior

碩士
國立臺灣大學
心理學研究所
107
The discrete architecture modules of the rat barrel cortex are an important animal model in studying cortical coding of sensory information and its circuitry. Neurons within the same barrel tend to respond mainly to the deflection of a single whisker (called ‘principal whisker’, PW). However, their responses also modulated when surrounding whiskers (SWs) are deflected alone with the PW. When studying the surround modulation effect, most previous studies deflect only the PW and a single SW, a scheme differs significantly from the synchronous movement of multi-whiskers when rats are exploring the environment. In this study, we aimed on the effect of surround modulation by deflecting multi-whiskers simultaneously with different stimulus patterns: a single whisker (single condition), multi-whiskers (n = 5, chosen randomly) moving in the same direction (correlated condition), multi-whiskers (n = 5, chosen randomly) moving in different directions (uncorrelated condition). We tried to address three questions. First, how firing rate and directional tuning were affected by surround modulation in different stimulus patterns (the contextual effect). Second, were the effect of surround modulation different across different cortical layers. Third, in what degree the response in barrel cortex could be characterized by the linear-nonlinear model. Half of the recorded neurons showed significant surround modulation effect. Comparing to the single-whisker condition, neurons in the multi-whisker conditions tended to have lower firing rates and higher directional selectivity indices. Neurons with significant surround suppression were three times as many as those with significant surround facilitation, indicating that surround suppression was dominant in barrel field cortex. The contextual effect in multi-whisker conditions was found only in the supragranular layer – the reduction in firing rate was larger in the correlated condition than in the uncorrelated condition, maybe due to abandon lateral connections among neurons with similar properties. In contrast, the contextual effect was not evident in other two layers. Moreover, cortical responses in barrel field under multi-whisker conditions were less characterized by the LN model than those under single whisker condition. Overall, these results indicated that surround suppression was dominant especially for neurons in the supragranular layer of the barrel field cortex, which might serve an important role in integrating inputs from the granular layer. In contrast, neurons in the granular layer were less affected by surround stimulation and might serve as critical feature detectors (Brecht, 2007).

abstract: Following a traumatic brain injury (TBI) 5-50% of patients will develop post traumatic epilepsy (PTE). Pediatric patients are most susceptible with the highest incidence of PTE. Currently, we cannot prevent the development of PTE and knowledge of basic mechanisms are unknown. This has led to several shortcomings to the treatment of PTE, one of which is the use of anticonvulsant medication to the population of TBI patients that are not likely to develop PTE. The complication of identifying the two populations has been hindered by the ability to find a marker to the pathogenesis of PTE. The central hypothesis of this dissertation is that following TBI, the cortex undergoes distinct cellular and synaptic reorganization that facilitates cortical excitability and promotes seizure development. Chapter 2 of this dissertation details excitatory and inhibitory changes in the rat cortex after severe TBI. This dissertation aims to identify cortical changes to a single cell level after severe TBI using whole cell patch clamp and electroencephalogram electrophysiology. The work of this dissertation concluded that excitatory and inhibitory synaptic activity in cortical controlled impact (CCI) animals showed the development of distinct burst discharges that were not present in control animals. The results suggest that CCI induces early "silent" seizures that are detectable on EEG and correlate with changes to the synaptic excitability in the cortex. The synaptic changes and development of burst discharges may play an important role in synchronizing the network and promoting the development of PTE.
Dissertation/Thesis
Masters Thesis Biology 2014

博士
慈濟大學
醫學科學研究所
106
Numerous neurological disorders such as epidural hematoma can cause compression of cerebral cortex. In the present study we designed to investigate whether and how sustained compression of primary somatosensory cortex affects stellate neurons and thalamocortical afferent (TCA) fibers. The rat primary somatosensory cortex was subjected to bead epidural compression. Immunohistochemical results showed increases of oxidative markers 3-nitrotyrosine and 4-hydroxynonenal expressions in barrel cortices after compression. Conversely, application of antioxidant ascorbic acid or apocynin significantly ameliorated the increase of oxidative stress. Furthermore, anterograde tracing analyses demonstrated a progressive decrease of TCA fiber density in barrel field for 6 months after compression. Because we observed an abrupt decrease of TCA fiber density at 3 days after compression, we further inspected the ultrastructure of TCA fibers under electron microscope at this time point. Some TCA fiber terminals were distorted and broken, containing dissolved or darkened mitochondria and fewer synaptic vesicles. In addition, there were disrupted mitochondria and myelin sheath in some myelinated TCA fibers. Using Golgi-Cox staining, we observed the reduction of dendritic arbors and the stripping of dendritic spines of stellate neurons for at least 3 months after compression. Treatment of antioxidant ascorbic acid or apocynin was able to reverse the decrease of TCA fiber density but not the shrinkage of dendrites and the stripping of dendritic spines of stellate neurons after compression. Collectively, these findings demonstrate that sustained epidural compression of primary somatosensory cortex causes a long-term reduction of the TCA fibers and the dendrites of stellate neurons. Oxidative stress participates in the reduction of TCA fiber density in layer IV of barrel cortices but not the shrinkage of dendrites and the stripping of dendritic spines of stellate neurons.

Nicotinic acetylcholine receptors (nAChRs) are a major class of ligand-gated ion channels in the brain, with the α7 subtype of nAChRs playing an important role in attention, working memory and synaptic plasticity. Alterations in expression of α7 nAChRs are observed in neurological disorders including schizophrenia and Alzheimer’s disease. Therefore, understanding the fundamentals of how α7 nAChRs are regulated will increase our comprehension of how α7 nAChRs influence neuronal excitability, cognition and the pathophysiology of various neurological disorders. The purpose of this thesis was to investigate how protein kinases modulate the function and trafficking of α7 nAChRs in CNS neurons. In chapter 2, I describe a novel fast agonist applicator that I developed to reliably elicit α7 nAChR currents in both brain slices and cultured cells. In chapter 3, I examined whether an immune protein in the brain, the T-cell receptor (TCR), can modulate α7 nAChR activity. Activation of TCRs decreased α7 nAChR whole-cell recorded currents from layer 1 prefrontal cortical (PFC) neurons. TCR attenuated α7 nAChR currents through the activation of Fyn and Lck tyrosine kinases, which targeted tyrosine 442 in the M3-M4 cytoplasmic loop of α7. The mechanisms of the attenuated α7 current were contributed by a TCR mediated decrease in surface receptor expression and an attenuation of the α7 single-channel conductance. TCR stimulation also resulted in a decrease in neuronal excitability by negatively modulating α7 activity. In chapter 4, I tested whether PKA can modulate α7 nAChR function in CNS neurons. The pharmacological agents PKA agonist 8-Br-cAMP and PKA inhibitor KT-5720, as well as over-expressing dominant negative PKA and the catalytic subunit of PKA, demonstrated that activation of PKA leads to a reduction of α7 nAChR currents in HEK 293T cells and layer 1 cortical interneurons. Serine 365 of the M3-M4 cytoplasmic domain of α7 was necessary for the PKA modulation of α7. The mechanism of down-regulation in α7 receptor function was due to decreased surface receptor expression but not alterations in single-channel conductance nor gating kinetics. The results of this thesis demonstrate that α7 nAChRs constitute a major substrate for modulation via TCR activated tyrosine kinases and the cyclic AMP/PKA pathway.
Graduate
kpragya2000504@gmail.com

To fully understand how the brain works, it is necessary to relate the brain’s function to its anatomy. Cortical anatomy is subject-specific. It is character- ized by the thickness and number of intracortical layers, which differ from one cortical area to the next. Each cortical area fulfills a certain function. With magnetic res- onance imaging (MRI) it is possible to study structure and function in-vivo within the same subject. The resolution of ultra-high field MRI at 7T allows to resolve intracortical anatomy. This opens the possibility to relate cortical function of a sub- ject to its corresponding individual structural area, which is one of the main goals of neuroimaging. To parcellate the cortex based on its intracortical structure in-vivo, firstly, im- ages have to be quantitative and homogeneous so that they can be processed fully- automatically. Moreover, the resolution has to be high enough to resolve intracortical layers. Therefore, the in-vivo MR images acquired for this work are quantitative T1 maps at 0.5 mm isotropic resolution. Secondly, computational tools are needed to analyze the cortex observer-independ- ently. The most recent tools designed for this task are presented in this thesis. They comprise the segmentation of the cortex, and the construction of a novel equi-volume coordinate system of cortical depth. The equi-volume model is not restricted to in- vivo data, but is used on ultra-high resolution post-mortem data from MRI as well. It could also be used on 3D volumes reconstructed from 2D histological stains. An equi-volume coordinate system yields firstly intracortical surfaces that follow anatomical layers all along the cortex, even within areas that are severely folded where previous models fail. MR intensities can be mapped onto these equi-volume surfaces to identify the location and size of some structural areas. Surfaces com- puted with previous coordinate systems are shown to cross into different anatomical layers, and therefore also show artefactual patterns. Secondly, with the coordinate system one can compute cortical traverses perpendicularly to the intracortical sur- faces. Sampling intensities along equi-volume traverses results in cortical profiles that reflect an anatomical layer pattern, which is specific to every structural area. It is shown that profiles constructed with previous coordinate systems of cortical depth disguise the anatomical layer pattern or even show a wrong pattern. In contrast to equi-volume profiles these profiles from previous models are not suited to analyze the cortex observer-independently, and hence can not be used for automatic delineations of cortical areas. Equi-volume profiles from four different structural areas are presented. These pro- files show area-specific shapes that are to a certain degree preserved across subjects. Finally, the profiles are used to classify primary areas observer-independently.:1 Introduction p. 1 2 Theoretical Background p. 5 2.1 Neuroanatomy of the human cerebral cortex . . . .p. 5 2.1.1 Macroscopical structure . . . . . . . . . . . .p. 5 2.1.2 Neurons: cell bodies and fibers . . . . . . . .p. 5 2.1.3 Cortical layers in cyto- and myeloarchitecture . . .p. 7 2.1.4 Microscopical structure: cortical areas and maps . .p. 11 2.2 Nuclear Magnetic Resonance . . . . . . . . . . . . . .p. 13 2.2.1 Proton spins in a static magnetic field B0 . . . . .p. 13 2.2.2 Excitation with B1 . . . . . . . . . . . . . . . . .p. 15 2.2.3 Relaxation times T1, T2 and T∗ 2 . . . . . . . . . .p. 16 2.2.4 The Bloch equations . . . . . . . . . . . . . . . . p. 17 2.3 Magnetic Resonance Imaging . . . . . . . . . . . . . .p. 20 2.3.1 Encoding of spatial location and k-space . . . . . .p. 20 2.3.2 Sequences and contrasts . . . . . . . . . . . . . . p. 22 2.3.3 Ultra-high resolution MRI . . . . . . . . . . . . . p. 24 2.3.4 Intracortical MRI: different contrasts and their sources p. 25 3 Image analysis with computed cortical laminae p. 29 3.1 Segmentation challenges of ultra-high resolution images p. 30 3.2 Reconstruction of cortical surfaces with the level set method p. 31 3.3 Myeloarchitectonic patterns on inflated hemispheres . . . . p. 33 3.4 Profiles revealing myeloarchitectonic laminar patterns . . .p. 36 3.5 Standard computational cortical layering models . . . . . . p. 38 3.6 Curvature bias of computed laminae and profiles . . . . . . p. 39 4 Materials and methods p. 41 4.1 Histology . . . . . p. 41 4.2 MR scanning . . . . p. 44 4.2.1 Ultra-high resolution post-mortem data p. 44 4.2.2 The MP2RAGE sequence . . . . . . . . p. 45 4.2.3 High-resolution in-vivo T1 maps . . . .p. 46 4.2.4 High-resolution in-vivo T∗ 2-weighted images p. 47 4.3 Image preprocessing and experiments . . . . . .p. 48 4.3.1 Fully-automatic tissue segmentation . . . . p. 48 4.3.2 Curvature Estimation . . . . . . . . . . . . p. 49 4.3.3 Preprocessing of post-mortem data . . . . . .p. 50 4.3.4 Experiments with occipital pole post-mortem data .p. 51 4.3.5 Preprocessing of in-vivo data . . . . . . . . . . p. 52 4.3.6 Evaluation experiments on in-vivo data . . . . . .p. 56 4.3.7 Application experiments on in-vivo data . . . . . p. 56 4.3.8 Software . . . . . . . . . . . . . . . . . . . . .p. 58 5 Computational cortical layering models p. 59 5.1 Implementation of standard models . .p. 60 5.1.1 The Laplace model . . . . . . . . .p. 60 5.1.2 The level set method . . . . . . . p. 61 5.1.3 The equidistant model . . . . . . .p. 62 5.2 The novel anatomically motivated equi-volume model p. 63 5.2.1 Bok’s equi-volume principle . . . . . .p. 63 5.2.2 Computational equi-volume layering . . p. 66 6 Validation of the novel equi-volume model p. 73 6.1 The equi-volume model versus previous models on post-mortem samples p. 73 6.1.1 Comparing computed surfaces and anatomical layers . . . . . . . . p. 73 6.1.2 Cortical profiles reflecting an anatomical layer . . . . . . . . .p. 79 6.2 The equi-volume model versus previous models on in-vivo data . . . .p. 82 6.2.1 Comparing computed surfaces and anatomical layers . . . . . . . . p. 82 6.2.2 Cortical profiles reflecting an anatomical layer . . . . . . . . .p. 85 6.3 Dependence of computed surfaces on cortical curvature . . . . .p. 87 6.3.1 Within a structural area . . . . . . . . . . . . . . . . . . p. 87 6.3.2 Artifactual patterns on inflated surfaces . . . . . . . . . .p. 87 7 Applying the equi-volume model: Analyzing cortical architecture in-vivo in different structural areas p. 91 7.1 Impact of resolution on cortical profiles . . . . . . . . . . . . . p. 91 7.2 Intersubject variability of cortical profiles . . . . . . . . . . . p. 94 7.3 Myeloarchitectonic patterns on inflated hemispheres . . . . . . .p. 95 7.3.1 Comparison of patterns with inflated labels . . . . . . . . . .p. 97 7.3.2 Patterns at different cortical depths . . . . . . . . . . . . .p. 97 7.4 Fully-automatic primary-area classification using cortical profiles p. 99 8 Discussion p. 105 8.1 The novel equi-volume model . . . . . . . . . . . . . . . . . . . . .p. 105 8.2 Analyzing cortical myeloarchitecture in-vivo with T1 maps . . . . . .p. 109 9 Conclusion and outlook p. 113 Bibliography p. 117 List of Figures p. 127

Η δημιουργία του εγκεφαλικού φλοιού στηρίζεται στη διαδοχική εμφάνιση πληθυσμών προγονικών νευρώνων, οι οποίοι δίνουν γένεση σε νευρικά και γλοιακά κύτταρα. Κατά την νευρογένεση όλοι οι νευρώνες του εγκεφαλικού φλοιού προέρχονται από το νευροεπιθήλιο που βρίσκεται δίπλα από τις πλευρικές κοιλίες. Τα νευροεπιθηλιακά κύτταρα αρχικά διαιρούνται με σκοπό την δημιουργία ικανού αριθμού πρόδρομων κυττάρων που θα δώσουν γένεση στον αναπτυσσόμενο φλοιό. Αργότερα, τα κύτταρα αυτά, διαφοροποιούνται προς τις άλλες κατηγορίες πρόδρομων κυττάρων και προς τους διαφοροποιημένους νευρώνες. Η πρωτεΐνη Geminin έχει προταθεί ως ένα μόριο που ρυθμίζει τόσο τον κυτταρικό πολλαπλασιασμό όσο και την κυτταρική διαφοροποίηση. Προκειμένου να διερευνηθεί ο ρόλος της πρωτεΐνης Geminin in vivo στη δημιουργία νευρώνων, πραγματοποιήθηκαν πειράματα υπερέκφρασης της Geminin στον αναπτυσσόμενο εγκεφαλικό φλοιό του μυός κατά την Ε14.5 dpc. Τα αποτελέσματα της παρούσας εργασίας δείχνουν ότι η υπερέκφραση της Geminin οδηγεί στην αύξηση του αριθμού των κυττάρων της ανώτερης στοιβάδας και μείωση του αριθμού των κυττάρων της κατώτερης στοιβάδας. Συνοψίζοντας, τα αποτελέσματά μας προτείνουν ότι η Geminin συμμετέχει στη ρύθμιση του πληθυσμού των φλοιϊκών νευρώνων.
Cortical development is a highly ordered process, involving the timely orchestration of the appearance of different neural progenitor lineages, which succeed one another in order to generate the neurons and glia comprising the cortex.During neurogenesis, the cortical neurons are originated from the neuroepithelium that lies next to the lateral vesicles. At the beginning, neuroepithelial cells divide in order to expand their population and to create the number of progenitor cells that would give rise to the neurons and glia that comprise the cortex. Geminin has been shown to regulate cell proliferation, fate determination and organogenesis, representing a potential link between these processes. In order to investigate the in vivo role of Geminin in the creation of the cortical neurons, we performed overexpression experiments with of Geminin in the developing mouse cortex. Our results indicate that overexpression of Geminin in the developing cerebral cortex increases the number of the upper layer cells and reduces the number of the deep layer cells at E14.5 dpc. Our work suggests that Geminin is a molecule that participates in the regulation of the correct number of cortical progenitors and neurons in the cerebral cortex.