Spelling suggestions: "subject:"neuroscience.""
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Learning Structure in Time Series for Neuroscience and BeyondPfau, David Benjamin January 2015 (has links)
Advances in neuroscience are producing data at an astounding rate - data which are fiendishly complex both to process and to interpret. Biological neural networks are high-dimensional, nonlinear, noisy, heterogeneous, and in nearly every way defy the simplifying assumptions of standard statistical methods. In this dissertation we address a number of issues with understanding the structure of neural populations, from the abstract level of how to uncover structure in generic time series, to the practical matter of finding relevant biological structure in state-of-the-art experimental techniques. To learn the structure of generic time series, we develop a new statistical model, which we dub the probabilistic deterministic infinite automata (PDIA), which uses tools from nonparametric Bayesian inference to learn a very general class of sequence models. We show that the models learned by the PDIA often offer better predictive performance and faster inference than Hidden Markov Models, while being significantly more compact than models that simply memorize contexts. For large populations of neurons, models like the PDIA become unwieldy, and we instead investigate ways to robustly reduce the dimensionality of the data. In particular, we adapt the generalized linear model (GLM) framework for regres- sion to the case of matrix completion, which we call the low-dimensional GLM. We show that subspaces and dynamics of neural activity can be accurately recovered from model data, and with only minimal assumptions about the structure of the dynamics can still lead to good predictive performance on real data. Finally, to bridge the gap between recording technology and analysis, particularly as recordings from ever-larger populations of neurons becomes the norm, automated methods for extracting activity from raw recordings become a necessity. We present a number of methods for automatically segmenting biological units from optical imaging data, with applications to light sheet recording of genetically encoded calcium indicator fluorescence in the larval zebrafish, and optical electrophysiology using genetically encoded voltage indicators in culture. Together, these methods are a powerful set of tools for addressing the diverse challenges of modern neuroscience.
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Roles for Cytoplasmic Dynein and the Unconventional Kinesin, KIF1a, during Cortical DevelopmentHu, Daniel Jun-Kit January 2015 (has links)
Radial glial progenitor (RGP) cells are neural stem cells that give rise to the majority of neurons, glia, and adult stem cells during cortical development. These cells divide either symmetrically to form two daughter RGP cells or asymmetrically to form a daughter RGP cell or a daughter neuron/neuronal precursor. In between divisions, the nuclei of RGP cells oscillate in coordination with the cell cycle in a form of behavior known as interkinetic nuclear migration (INM). RGP nuclei migrate basally during G1, undergo S phase, and migrate apically during G2 to the apical, ventricular surface (VS). Mitosis only occurs when the nucleus reaches the VS. Two microtubule-associated motor proteins are required to drive nuclear movement: the unconventional kinesin, Kif1a, during G1-specific basal migration and cytoplasmic dynein during G2-specific apical migration. The strict coordination of motor activity, migratory direction, and cell cycle phase is highly regulated and we find that a G2 cell cycle-dependent protein kinase activates two distinct G2-specific mechanisms to recruit dynein to nuclear pores. The activities of these pathways initiate apical nuclear migration and maintain nuclear movement throughout G2.
Originally identified in HeLa cells, we find the two G2-specific recruitment pathways (“RanBP2-BicD2” and “Nup133-CENP-F”) are conserved in RGP cells. Disrupting either pathway arrests apical nuclear migration but does not affect G1-dependent basal migration. The “RanBP2-BicD2” pathway initiates early during G2 and is maintained throughout the cell cycle phase while the “Nup133-CENP-F” pathway is activated later in G2. Forced targeting of dynein to the nuclear envelope (NE) restores apical nuclear migration, with nuclei successfully reaching the VS. We also find that the G2/M-specific Cdk1 serves as a master regulator of apical nuclear migration in RGP cells. Pharmacological drug inhibitors of Cdk1 arrest apical migration without any effect on G1-dependent basal migration. Conversely, overactivating Cdk1 causes premature, accelerated apical nuclear migration. Specifically, Cdk1 drives apical nuclear migration through activation of both the “RanBP2-BicD2” and “Nup133-CENP-F” pathways. Cdk1 acts by phosphorylating RanBP2, priming it for BicD2 interaction. Forced targeting of BicD2-dynein to the NE in a RanBP2-independent manner rescues apical nuclear migration in the presence of Cdk1 drug inhibition. Additionally, Cdk1 seems to activate the “Nup133-CENP-F” at the CENP-F level, phosphorylating the protein to trigger nuclear export.
INM plays an important role in proper cell cycle progression and we find that arresting nuclei away from the VS prevents mitotic entry, demonstrating that apical nuclear migration to the VS is not just a correlated with cell cycle progression, but is required. When apical migration is restored by forced recruitment of dynein to the NE, mitotic entry is restored as well. In contrast, we find that arresting basal migration by Kif1a does not have a major influence on cell cycle progression. RGP cells still enter S-phase despite remaining close to the VS, revealing that, unlike mitotic entry, S-phase entry is not coupled with nuclear positioning. However, symmetric, proliferative divisions are favored over asymmetric, neurogenic divisions after inhibition of basal migration.
We further find that Kif1a and the proteins involved in the two recruitment pathways play additional role later in brain development. After a neurogenic division, the newly-born neuron migrates past the RPG nuclei and they undergo a multipolar morphology. After at least twenty-four hours, the immature neuron then transitions to a bipolar, migratory morphology where it continues migrating towards its final destination along RGP fibers to the cortical plate. We demonstrate that Kif1a and NE dynein recruitment proteins seem to be involved in the multipolar to bipolar transition and RNAi for these proteins prevent further migration by arresting the immature neurons in a multipolar morphology. Kif1a RNAi, in particular, also induced comparable arrest in surrounding control neurons. Further analysis reveal that the multipolar arrest in neurons is independent of the basal nuclear migration arrest in RGP cells. These results identify the control mechanism for NE dynein recruitment in RGP cells to drive apical nuclear migration, the relationship of cell cycle phase progression with nuclear positioning, and the sequential, independent roles of these proteins, particularly Kif1a, in neuronal maturation.
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Decoding the rhythms of avian auditory LFPSchachter, Mike J. 12 January 2017 (has links)
<p> We undertook a detailed analysis of population spike rate and LFP power in the Zebra finch auditory system. Utilizing the full range of Zebra finch vocalizations and dual-hemisphere multielectrode recordings from auditory neurons, we used encoder models to show how intuitive acoustic features such as amplitude, spectral shape and pitch drive the spike rate of individual neurons and LFP power on electrodes. Using ensemble decoding approaches, we show that these acoustic features can be successfully decoded from the population spike rate vector and the power spectra of the multielectrode LFP with comparable performance. In addition we found that adding pairwise spike synchrony to the spike rate decoder boosts performance above that of the population spike rate alone, or LFP power spectra. We also found that decoder performance grows quickly with the addition of more neurons, but there is notable redundancy in the population code. Finally, we demonstrate that LFP power on an electrode can be well predicted by population spike rate and spike synchrony. High frequency LFP power (80-190Hz) integrates neural activity spatially over a distance of up to 250 microns, while low frequency LFP power (0-30Hz) can integrate neural activity originating up to 800 microns away from the recording electrode. </p><p> To understand how an auditory system processes complex sounds, it is essential to understand how the temporal envelope of sounds, i.e. the time-varying amplitude, is encoded by neural activity. We studied the temporal envelope of Zebra finch vocalizations, and show that it exhibits modulations in the 0-30Hz range, similar to human speech. We then built linear filter models to predict 0-30Hz LFP activity from the temporal envelopes of vocalizations, achieving surprisingly high performance for electrodes near thalamorecipient areas of Zebra finch auditory cortex. We then show that there are two spatially-distinct subnetworks that resonate at different frequency bands, one subnetwork that resonates around 19Hz, and another subnetwork that resonates at 14Hz. These two subnetworks are present in every anatomical region. Finally we show that we can improve predictive performance with recurrent neural network models. </p>
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The Effects of Prostaglandin E<sub>2</sub> on the Neurons of the Ventromedial Preoptic Area of the Hypothalamus: A Mechanism of FeverRanels, Heather J. 01 January 2002 (has links)
No description available.
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Phenotypic properties and intrinsic currents of neurons involved in the neural generation of mammalian breathingHayes, John A. 01 January 2007 (has links)
Breathing is essential for mammalian life. Although there is an emerging consensus that the inspiratory respiratory rhythm is generated in a lower brainstem region known as the preBotzinger Complex (preBotC), the mechanism of rhythmogenesis is still unclear. Additionally, the modulation of intrinsic currents within preBotC neurons has yet to be fully elucidated. This dissertation addresses both of these issues and relies on imaging, electrophysiological, and modeling techniques. The first chapter examines the size and composition of the preBotC. The chapter also decribes the means by which substance P (SP) excites the vast majority of preBotC neurons by illustrating the characteristics of the SP-activated current (/SP) in these neurons. In the subsequent chapter, we characterize a voltage-dependent potassium current that is involved in maintaining stable rhythms during normal fictive breathing. The third chapter presents a mathematical model of heterogeneous and rhythmogenic neurons that initiate network bursts. We show how this behavior relies on feedback synaptic connections within the network that reinforces activity, i.e., recurrent-excitation. We also compare model results to experimental data and make testable predictions. The final chapter elaborates on the discussion of /SP from the first chapter and presents evidence suggesting that a cyclic adenosine monophosphate (cAMP)-modulated non-specific cation channel may account for the depolarizing response in preBotC neurons from several neuromodulators. Altogether, this dissertation advances the field's understanding on several fronts. We have distinguished possible functional roles of neurons from electrophysiological characteristics, estimated the number of neurons necessary for rhythmogenesis, characterized /SP , and clarified the distribution of SP-sensitive receptors among inspiratory neurons. We have identified and characterized a voltage-dependent potassium currrent important for inspiratory activity and analyzed its role. We have also described in detail how rhythmic bursts form from recurrent excitation and how this relates to experimental data. Finally, we have identified and begun characterizing a potentially important and novel mechanism for the modulation of membrane potentials in critical inspiratory neurons.
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Effects of moderate-level sound exposure on behavioral thresholds in chinchillasCarbajal, M. Sandra 03 October 2015 (has links)
<p>Normal audiometric thresholds following noise exposure have generally been considered as an indication of a recovered cochlea and intact peripheral auditory system, yet recent animal work has challenged this classic assumption. Moderately noise-exposed animals have been shown to have permanent loss of synapses on inner hair cells (IHCs) and permanent damage to auditory nerve fibers (ANFs), specifically the low-spontaneous rate fibers (low-SR), despite normal electrophysiological thresholds. Loss of cochlear synapses, known as cochlear synaptopathy, disrupts auditory-nerve signaling, which may result in perceptual speech deficits in noise despite normal audiometric thresholds. Perceptual deficit studies in humans have shown evidence consistent with the idea of cochlear synaptopathy. To date, there has been no direct evidence linking cochlear synaptopathy and perceptual deficits. Our research aims to develop a cochlear synaptopathy model in chinchilla, similar to previously established mouse and guinea pig models, to provide a model in which the effects of cochlear synaptopathy on behavioral and physiological measures of low-frequency temporal coding can be explored. </p><p> Positive-reinforcement operant-conditioning was used to train animals to perform auditory detection behavioral tasks for four frequencies: 0.5, 1, 2, and 4 kHz. Our goal was to evaluate the detection abilities of chinchillas for tone-in-noise and sinusoidal amplitude modulated (SAM) tone behavioral tasks, which are tasks thought to rely on low-SR ANFs for encoding. Testing was performed before and after exposure to an octave-band noise exposure centered at 1 kHz for 2 hours at 98.5 dB SPL. This noise exposure produced the synaptopathy phenotype in naïve chinchillas, based on auditory-brainstem responses (ABRs), otoacoustic emissions (OAEs) and histological analyses. Threshold shift and inferred synaptopathy was determined from ABR and OAE measures in our behavioral animals. </p><p> Overall, we have shown that chinchillas, similar to mice and guinea pigs, can display cochlear synaptopathy phenotype following moderate-level sound exposure. This finding was seen in naïve exposed chinchillas, but our results suggest the susceptibility to noise can vary between naïve and behavioral cohorts because minimal physiological evidence for synaptopathy was observed in the behavioral group. Hearing sensitivity determined by a tone-in-quiet behavioral task on normal hearing chinchillas followed trends reported previously, and supported the lack of permanent threshold shift following moderate noise exposure. As we expected, thresholds determined in a tone-in-noise behavioral task were higher than thresholds measured in quiet. Behavioral thresholds measured in noise after moderate noise exposure did not show threshold shifts relative to pre-exposure thresholds in noise. As expected, chinchillas were more sensitive at detecting fully modulated SAM-tone signals than less modulated, with individual modulation depth thresholds falling within previously reported mammalian ranges. </p><p> Although we have only been able to confirm cochlear synaptopathy in pilot assays with naïve animals so far (i.e., not in the pilot behavioral animals), this project has developed an awake protocol for moderate-level noise exposure, an extension to our lab’s previous experience with high-level permanent damage noise exposure under anesthesia. Also, we successfully established chinchilla behavioral training and testing protocols on several auditory tasks, a new methodology to our laboratory, which we hope will ultimately allow us to identify changes in auditory perception resulting from moderate-level noise exposure. </p>
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<italic>COMT</italic> Genotype and Self-Regulation Interactions: Pathways to Psychological VulnerabilityDavis, Elena Goetz January 2015 (has links)
<p>The present series of studies offers a perspective on how a particular functional genetic polymorphism, <italic>COMT</italic> Val<super>158</super>Met, interacts with individual differences in self-regulation to affect the <italic>mechanisms</italic> underlying successful versus unsuccessful goal pursuit. Individual differences in the mechanisms that underlie self-regulation can be understood as more or less beneficial for goal pursuit depending on the context. For example, relatively high levels of cognitive flexibility can facilitate self-regulation in certain situations (e.g., where a new strategy needs to be employed) but can be detrimental in others (e.g., where excessive flexibility results in distraction from continuing efforts needed to attain the goal). The functional role of the <italic>COMT</italic> Val<super>158</super>Met polymorphism can also be conceptualized as a trade-off where the adaptiveness of the Val- or Met-like dopaminergic signaling profiles is determined by features of the environment as well as by the individual's goals. By integrating across biological and behavioral levels of analysis, we can expand our understanding of individual differences in tendencies for successful versus unsuccessful self-regulation. In particular, <italic>COMT</italic> by self-regulation interactions constitute a particularly fruitful line of investigation to better understand goal pursuit, mood, and vulnerability.</p><p>Self-regulation is a theoretical construct that can be used to integrate behavioral findings with research on neurobiological processes and genetic variation, particularly <italic>COMT</italic>, in order to more fully examine behavior across multiple levels of analysis. Individual differences in self-regulation have been shown to have reliably identifiable neural correlates (e.g., Eddington, Dolcos, Cabeza, Krishnan, & Strauman, 2007), and many of the factors contributing to successful or dysfunctional goal pursuit have their basis in psychological processes directly affected by <italic>COMT</italic>. Some of these processes under investigation here include responding to rewards, utilizing feedback, and flexibly changing a pattern of responses under motivationally challenging conditions. There are also trait-like differences in neural network connectivity based on the interaction between <italic>COMT</italic> and self-regulatory variables. </p><p>The three studies that comprise this dissertation examined how <italic>COMT</italic> genotype can moderate the effect of previous regulatory experiences (i.e., success or failure at achieving one's personal goals) on behavior and brain function, using regulatory focus theory (Higgins, 1997) as a model of self-regulation. The first study (Goetz, Hariri, Pizzagalli, & Strauman, 2013) examined how one's experience of successful goal pursuit moderated the impact of <italic>COMT</italic> genotype on reward responsive behavior. This experiment utilized a probabilistic reward task to measure the participants' ability to alter their behavior in response to reinforcement, which serves as an index of their sensitivity to environmental feedback of success. This responsiveness was seen particularly for those individuals who have had previous experiences of success pursuing rewarded goals if they also had the <italic>COMT</italic> Val/Val genotype, which is associated with more flexible behavior.</p><p>The second study (Davis, Tharp, Hariri, & Strauman, in preparation) used priming to create a motivationally salient context of either promotion (related to ideal goals) or prevention (related to ought goals) in order to assess genotype group differences on a cognitive control task. The results showed that relatively flexible Val/Val individuals exhibited behavioral slowing when challenged by a motivational context that requires vigilance, i.e., after priming by a prevention failure. By contrast, relatively rigid Met/Met individuals exhibited behavioral slowing in response to a context that demands eagerness and openness to opportunities for positive feedback, i.e., after priming by a past promotion failure experience.</p><p>The third study explored how the interaction of <italic>COMT</italic> and regulatory focus variables may reveal insights into resting state neural network connectivity, ultimately leading to a deeper understanding of individual differences in goal pursuit behavior. Several nodes within the executive control and default mode networks show different patterns of connectivity based on previous goal pursuit success, <italic>COMT</italic> genotype, and their interaction. Because the neural networks that underlie successful goal pursuit are also moderated by <italic>COMT</italic> genotype, we can conclude that behaviors relevant to goal pursuit, such as the reward responsive and cognitive control behaviors explored in the previous studies, are likely supported by trait-like systems instantiated at the level of the brain. This provides further justification for exploring the interplay between <italic>COMT</italic> genotype and the promotion and prevention self-regulation systems, and points to several future directions of behavioral and fMRI investigation.</p> / Dissertation
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Prefrontal and midbrain contributions to fast executive control of behavior in the ratDuan, Chunyu A. 04 December 2015 (has links)
<p> Flexible control of behavior based on the relevant environmental context is a fundamental component of adaptive behavior. The capability to rapidly switch between different sensorimotor mappings to achieve the current goal is called executive control, and is predominantly studied in primates. To probe fast executive control using the tools available in rodents, we developed a novel rat behavior in which subjects are cued, on each trial, to apply a sensorimotor association to orient either toward a visual target (“Pro”) or away from it (“Anti”). Multiple behavioral asymmetries suggested that Anti behavior is cognitively demanding while Pro is easier to learn and perform. This is consistent with a prominent hypothesis in the primate literature that Anti required prefrontal cortex (PFC), whereas Pro could be mediated by the midbrain superior colliculus (SC). Pharmacological inactivation of rat medial PFC supported its expected role in Anti. Remarkably, bilateral SC inactivation substantially impaired Anti while leaving Pro essentially intact. Moreover, SC inactivation eliminated the performance cost of switching from Anti to Pro tasks. These results suggest a more diffuse network underlying response inhibition and task switching, including PFC and SC. Characterization of neural signatures underlying flexible sensorimotor transformation revealed dynamic task-relevant signals in the SC neurons during the delay period, similar to PFC neurons. We tested the causal requirement of this task set maintenance activity in the SC, and found a selective Anti impairment after optogenetic inactivation in bilateral SC during the delay. Together, our results establish a rodent model of rapid sensorimotor remapping and suggest a critical role for SC in maintaining a cognitively demanding task set to flexibly map sensory stimuli to correct motor outputs.</p>
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Anatomical connections of parietal cortex and visual acuity in Monodelphis domestica| Insights into the brain organization of the mammalian ancestorDooley, James Clinton 03 December 2015 (has links)
<p>The mammalian neocortex is highly dynamic, demonstrating incredible variability in size and complexity across species. This phenotypic diversity, however, evolved from an extinct common ancestor. By illuminating organization of this mammalian ancestor, we can better understand the common features and the constraints of the mammalian neocortex across all species. Brain organization is not preserved in fossilized tissue. Therefore, examinating the brain of extant species, such as the short-tailed opossum, and comparing it to the brains of other mammals, provides the best available data for understanding the brain organization of early mammals. We investigated both corticocortical and thalamocortical connections of parietal cortical areas as well as the visual acuity in the short-tailed opossum (Monodelphis domestica). This species was chosen because it is thought to share many features with early mammaliforms (including body morphology, ecological niche, and gross brain morphology). We also discuss the neocortical organization of the somatosensory and motor systems across small-brained mammals. This provides a more comprehensive understanding of similar features of organization, inherited from the common ancestor (homologous) as well as features of organization that are unique to this particular species. For studies of cortical connections of parietal cortex in Monodelphis domestica, injections of anatomical tracers were placed in four different cortical areas and both injection sites and retrogradely labeled cells were related to myeloarchitectonic boundaries of cortical fields. Using these techniques, we identified rostral and caudal somatosensory fields (SR and SC, respectively) on either side of primary somatosensory cortex (S1), as well as a multimodal region caudal to SC (termed MM). Together with the second somatosensory area (S2), these five areas compose an interconnected somatosensory/multisensory network in Monodelphis. Next, we investigated the thalamocortical connections of SR, S1, SC, and MM. In contrast with thalamocortical connections described in previous studies in the closely related Virginia opossum (Didelphis virginiana), Monodelphis domestica does not have strong projections from ventral lateral/ventral anterior nucleus to S1, suggesting a different pattern of motor organization in Monodelphis neocortex, and further complicating the hypothesized organization of the common mammalian ancestor. Finally, we provided the first behavioral measure of visual acuity in any American opossum. We discuss the significance of this finding, both in the context of future research on the visual system of Monodelphis as well as in the context of visual system organization across mammals.
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Molecular and Behavioral Mechanisms of Aversive Olfactory Learning in C. elegansZhang, Xiaodong January 2011 (has links)
The mechanisms of learning and memory are fundamental to our understanding of brain function. The aim of this thesis is to characterize the molecular, cellular and behavioral mechanisms underlying the aversive olfactory learning in the model organism C. elegans, to gain insight into animal learning in general. At the molecular level, I focused on the function of the transforming growth factor-\(\beta\) \((TGF-\beta)\) signaling pathway. The \(TGF-\beta\) pathway is conserved throughout the Metazoa and is critical for diverse physiological processes. It has also been implicated in neural plasticity, but the exact mechanisms remain elusive. Utilizing a behavioral assay that measures adult olfactory learning, I have found that DBL-1, a C. elegans \(TGF-\beta\) homolog, is required for learned olfactory avoidance of pathogenic bacteria. Mutations in DBL-1 signal transduction pathway, including those in the dbl-1 ligand, sma-6 and daf-4 receptors, and sma-3 SMAD, abolish the learning ability of adult animals. I have identified AVA neurons, a pair of command interneurons critical for olfactory sensorimotor response, as the essential release site of DBL-1 ligand in regulating learning. AVA neuronal activity is repressed by training, accompanied by an increase in the amount of DBL-1 secreted from AVA neurons after training. Remarkably, artificial inhibition of AVA activity in the absence of training is sufficient to increase AVA secretion of DBL-1, supporting a model in which experience dependent changes in neuronal activity lead to altered DBL-1 \(TGF-\beta\) signaling. Downstream of DBL-1 ligand, I found that the type I receptor SMA-6 primarily acts in the hypodermis to promote olfactory plasticity at the adult stage. At the behavioral level, I examined the taxis behavior of C. elegans toward different bacteria and the effect of training on its taxis strategy. Preliminary results suggest that C. elegans may be capable of modulating its olfactory preference by means of differentially adjusting its navigation strategy. In summary, this thesis uncovered the critical role of DBL-1 \(TGF-\beta\) signaling in C. elegans learning, and alterations in behavioral components underlying olfactory plasticity. These findings are expected to shed light on learning and memory in other animals as well.
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