Relevant bibliographies by topics / Human brain- Neuroimaging

Academic literature on the topic 'Human brain- Neuroimaging'

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Published: 6 September 2023

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Journal articles on the topic "Human brain- Neuroimaging"

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Posner, M. I., and M. E. Raichle. "The neuroimaging of human brain function." Proceedings of the National Academy of Sciences 95, no. 3 (February 3, 1998): 763–64. http://dx.doi.org/10.1073/pnas.95.3.763.

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Ho, Tiffany C., Stephan J. Sanders, Ian H. Gotlib, and Fumiko Hoeft. "Intergenerational Neuroimaging of Human Brain Circuitry." Trends in Neurosciences 39, no. 10 (October 2016): 644–48. http://dx.doi.org/10.1016/j.tins.2016.08.003.

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Hooker, Jacob M., and Richard E. Carson. "Human Positron Emission Tomography Neuroimaging." Annual Review of Biomedical Engineering 21, no. 1 (June 4, 2019): 551–81. http://dx.doi.org/10.1146/annurev-bioeng-062117-121056.

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Neuroimaging with positron emission tomography (PET) is the most powerful tool for understanding pharmacology, neurochemistry, and pathology in the living human brain. This technology combines high-resolution scanners to measure radioactivity throughout the human body with specific, targeted radioactive molecules, which allow measurements of a myriad of biological processes in vivo . While PET brain imaging has been active for almost 40 years, the pace of development for neuroimaging tools, known as radiotracers, and for quantitative analytical techniques has increased dramatically over the past decade. Accordingly, the fundamental questions that can be addressed with PET have expanded in basic neurobiology, psychiatry, neurology, and related therapeutic development. In this review, we introduce the field of human PET neuroimaging, some of its conceptual underpinnings, and motivating questions. We highlight some of the more recent advances in radiotracer development, quantitative modeling, and applications of PET to the study of the human brain.
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Swain, James E. "The human parental brain: In vivo neuroimaging." Progress in Neuro-Psychopharmacology and Biological Psychiatry 35, no. 5 (July 2011): 1242–54. http://dx.doi.org/10.1016/j.pnpbp.2010.10.017.

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Dhond, Rupali P., Norman Kettner, and Vitaly Napadow. "Neuroimaging Acupuncture Effects in the Human Brain." Journal of Alternative and Complementary Medicine 13, no. 6 (August 2007): 603–16. http://dx.doi.org/10.1089/acm.2007.7040.

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Fletcher, P. C. "Frontal lobes and human memory: Insights from functional neuroimaging." Brain 124, no. 5 (May 1, 2001): 849–81. http://dx.doi.org/10.1093/brain/124.5.849.

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Johns, Emily, and Irene Tracey. "Neuroimaging of Visceral Pain." Reviews in Pain 3, no. 2 (October 2009): 2–5. http://dx.doi.org/10.1177/204946370900300202.

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• Functional neuroimaging allows conscious reporting by human subjects to be related to changes in brain activation during painful stimulation. • Brain regions thought to be involved in the perception of pain include the primary and secondary somatosensory cortex, the anterior cingulate cortex, the prefrontal cortex, the insula and the thalamus. • There are major similarities in how visceral pain and somatic pain are processed by the brain. • No single brain region has been found to be responsible for visceral pain. • Patients with IBS often activate the same brain regions as healthy controls in response to pain, but with differing intensities. • Functional neuroimaging studies have failed to reach a consensus opinion on how the brain processes pain in Irritable Bowel Syndrome.
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O’Connor, Erin E., Edith V. Sullivan, Linda Chang, Dima A. Hammoud, Tony W. Wilson, Ann B. Ragin, Christina S. Meade, Jennifer Coughlin, and Beau M. Ances. "Imaging of Brain Structural and Functional Effects in People With Human Immunodeficiency Virus." Journal of Infectious Diseases 227, Supplement_1 (March 15, 2023): S16—S29. http://dx.doi.org/10.1093/infdis/jiac387.

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Abstract Before the introduction of antiretroviral therapy, human immunodeficiency virus (HIV) infection was often accompanied by central nervous system (CNS) opportunistic infections and HIV encephalopathy marked by profound structural and functional alterations detectable with neuroimaging. Treatment with antiretroviral therapy nearly eliminated CNS opportunistic infections, while neuropsychiatric impairment and peripheral nerve and organ damage have persisted among virally suppressed people with HIV (PWH), suggesting ongoing brain injury. Neuroimaging research must use methods sensitive for detecting subtle HIV-associated brain structural and functional abnormalities, while allowing for adjustments for potential confounders, such as age, sex, substance use, hepatitis C coinfection, cardiovascular risk, and others. Here, we review existing and emerging neuroimaging tools that demonstrated promise in detecting markers of HIV-associated brain pathology and explore strategies to study the impact of potential confounding factors on these brain measures. We emphasize neuroimaging approaches that may be used in parallel to gather complementary information, allowing efficient detection and interpretation of altered brain structure and function associated with suboptimal clinical outcomes among virally suppressed PWH. We examine the advantages of each imaging modality and systematic approaches in study design and analysis. We also consider advantages of combining experimental and statistical control techniques to improve sensitivity and specificity of biotype identification and explore the costs and benefits of aggregating data from multiple studies to achieve larger sample sizes, enabling use of emerging methods for combining and analyzing large, multifaceted data sets. Many of the topics addressed in this article were discussed at the National Institute of Mental Health meeting “Biotypes of CNS Complications in People Living with HIV,” held in October 2021, and are part of ongoing research initiatives to define the role of neuroimaging in emerging alternative approaches to identifying biotypes of CNS complications in PWH. An outcome of these considerations may be the development of a common neuroimaging protocol available for researchers to use in future studies examining neurological changes in the brains of PWH.
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Bethlehem, R. A. I., J. Seidlitz, S. R. White, J. W. Vogel, K. M. Anderson, C. Adamson, S. Adler, et al. "Brain charts for the human lifespan." Nature 604, no. 7906 (April 6, 2022): 525–33. http://dx.doi.org/10.1038/s41586-022-04554-y.

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AbstractOver the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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Roberts, Blaine R., Dominic J. Hare, Catriona A. McLean, Alison Conquest, Monica Lind, Qiao-Xin Li, Ashley I. Bush, Colin L. Masters, Maria-Christina Morganti-Kossmann, and Tony Frugier. "Traumatic brain injury induces elevation of Co in the human brain." Metallomics 7, no. 1 (2015): 66–70. http://dx.doi.org/10.1039/c4mt00258j.

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Following acute brain injury (<3 hours post-event), cobalt levels in the brain are significantly elevated. This elevation may have important implications for positron emission tomography neuroimaging for assessing brain injury severity.
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Dissertations / Theses on the topic "Human brain- Neuroimaging"

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Burgess, Richard Ely. "Magnetic resonance imaging at ultra high field implications for human neuroimaging /." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1089949841.

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Thesis (Ph. D.)--Ohio State University, 2004.
Title from first page of PDF file. Document formatted into pages; contains xiv, 222 p. : ill. (some col.). Advisor: Pierre-Marie Luc Robitaille, Dept. of Emergency Medicine. Includes bibliographical references.
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Krienen, Fenna Marie. "Large-Scale Networks in the Human Brain revealed by Functional Connectivity MRI." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:11081.

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The human brain is composed of distributed networks that connect a disproportionately large neocortex to the brainstem, cerebellum and other subcortical structures. New methods for analyzing non-invasive imaging data have begun to reveal new insights into human brain organization. These methods permit characterization of functional interactions within and across brain networks, and allow us to appreciate points of departure between the human brain and non-human primates.
Psychology
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Meyniel, Florent. "How the human brain allocates physical effort over time : evidence from behavior, neuroimaging and pharmacology." Paris 6, 2013. http://www.theses.fr/2013PA066366.

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Faire le bon choix, c’est trouver le bon compromis entre coût et bénéfice. Dans le cas de la gestion de l’effort physique, ce compromis prend une dimension temporelle. Pour comprendre comment la décision d’arrêter ou reprendre l’effort est prise, nous avons développé un paradigme expérimental chez le sujet humain sain et un modèle computationnel dans lequel le coût estimé augmente à l’effort car la fatigue affecte toute la commande motrice et diminue au repos quand nous récupérons. Le comportement reflète les variations de ce coût estimé et du compromis avec le bénéfice attendu. Grâce à la complémentarité de l’imagerie fonctionnelle par résonnance magnétique et de la magnétoencéphalographie (MEG), le coût estimé a été localisé dans les régions proprioceptives du cerveau : l’insula postérieure et le thalamus ventromédian. La MEG a également révélé que la désynchronisation du rythme beta moteur (13-30Hz) permet une reprise plus rapide de l’effort quand les enjeux sont importants. Cette gestion stratégique du repos est liée à l’utilité attendue qui peut être dissociée de l’utilité réelle. Nos résultats montrent que la gestion de l’effort est adaptée en ligne au coût estimé et modulée stratégiquement en fonction des coûts et bénéfices attendus. Les antalgiques (hypnose ou paracétamol) ont un effet limité sur ce processus, à l’inverse de la sérotonine (Escitalopram). Notre contribution, à l’interface entre médecine du sport, théorie de la décision et modèle d’accumulation utilisés en neurosciences, propose un mécanisme pour optimiser la gestion de l’effort physique en maximisant les gains et minimisant les dommages corporels
No pain, no gain: optimal decisions involve a tradeoff between cost and benefit. We propose that in physical effort allocation, this tradeoff is unfolded over time. We present a task to investigate this process in the laboratory with healthy humans and we suggest a computational model to account for decisions to stop and resume the effort. Costs increase during exertion, due to fatigue at all stages of the motor command and decrease during rest, due to recovery. We show that this dynamic may be captured by a cost-evidence variable and compared to the expected benefit. Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) complementarily showed that cost-evidence may be implemented in proprioceptive regions of the brain: posterior insula and ventro-medial thalamus. In addition, MEG showed that motor beta (13-30 Hz) desynchronization mediates the effect of incentives to hasten effort resumption. This strategic invigoration of rest is supported by a behavioral dissociation: the expected utility (not the actual utility) modulates rest durations. Together, our results support that the behavior is adapted on the fly to cost-evidence levels and that this mechanism is modulated strategically according to the expected cost and benefit. This behavior was not affected by pain killers (hypnosis or paracetamol), but by serotonin (Escitalopram). This work bridges a gap between sport medicine, value-based decision-making and accumulation models in neuroscience in showing that accumulation and dissipation of cost-evidence can guide the optimization of effort allocation: this mechanism implements the maximization of benefit while the body costs are minimized
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Manickam, Sameer. "Clustering-based approach for the localization of Human Brain Nuclei." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-284443.

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The study of brain nuclei in neuroimaging poses challenges owing to its small size. Many neuroimaging studies have been reported for effectively locating these nuclei and characterizing their functional connectivity with other regions of the brain. Hypothalamus, Locus Coeruleus, and Ventral Tegmental area are such nuclei found in the human brain, which are challenging to visualize owing to their size and lack of tissue contrast with surrounding regions. Resting-state functional magnetic resonance imaging (rsfMRI) analysis on these nuclei enabled researchers to characterize their connectivity with other regions of the brain. An automated method to successfully isolate voxels belonging to these nuclei is still a great challenge in the field of neuroimaging. Atlas-based segmentation is the most common method used to study the anatomy and the functional connectivity of these brain nuclei. However, atlas-based segmentation has shown inconsistency due to variation in brain atlases owing to different population studies. Therefore, in this study, we try to address the research problem of brain nuclei imaging using a clustering-based approach. Clustering-based methods separate of voxels utilizing their structural and functional homogeneity to each other. This type of method can help locate and cluster the voxels belonging to the nuclei. Elimination of erroneous voxels by the use of clustering methods would significantly improve the structural and functional analysis of the nuclei in the human brain. Since several clustering methods are available in neuroimaging studies, the goal of this study is to find a robust model that has less variability across different subjects. Non-parametrical statistical analysis was performed as functional magnetic resonance imaging (fMRI) based studies are corrupted with noise and artefact. Statistical investigation on the fMRI data helps to assess the significant experimental effects.
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Roeder, Luisa. "Cortical control of human gait." Thesis, Queensland University of Technology, 2016. https://eprints.qut.edu.au/101537/1/Luisa_Roeder_Thesis.pdf.

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This research has advanced our understanding of how the brain controls muscle activity during walking, in healthy adults of different ages and people with Parkinson's disease. It has shown that there is direct brain control of leg muscles during the double support phase of gait in these populations. Moreover, this brain control is reduced in people with Parkinson's compared to healthy individuals, and standard anti-Parkinsonian medication does not counteract this deficiency.
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Córdova, Palomera Aldo. "Early Neurodevelopment, adult human cognition and depressive psychopathology: analysis of neuroimaging brain correlates and epigenetic mediators." Doctoral thesis, Universitat de Barcelona, 2015. http://hdl.handle.net/10803/328712.

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In the behavioral sciences, the concept of phenotypic plasticity can be roughly categorized into two classes: developmental and activational plasticity. Developmental plasticity denotes the capacity of an individual carrying a specific genetic background to adopt different developmental trajectories under distinct settings. Complementarily, activational plasticity refers to the differential activation of adaptation mechanisms: an individual with high activational plasticity would be able to detect a wide range of environments, and to respond to it using a psychobiological phenotype from a relatively large catalogue. In this context, it is feasible postulating that several etiopathogenic mechanisms of depression-related phenotypes can be clarified by expanding on processes of biobehavioral plasticity in response to the experience. This expansion can be elaborated on the basis of both neurodevelopmental phenomena (developmental plasticity) and novel biological mechanisms detectable through neuroimaging and epigenetics approaches (activational plasticity). The present work expands on two specific hypotheses. First, depression-related psychopathological phenotypes are induced by factors altering the early neurodevelopment, and these long-lasting changes can be assessed in adulthood (depression and developmental plasticity). Secondly, the clinical manifestation of depression-related psychopathological phenotypes can be understood as activational plasticity deficits; these deficits can be assessed as neurobiological disease traits using novel epigenetic and neuroimaging techniques (depression and activational plasticity). The results of this work provide support to the neuroplasticity hypothesis of depression, from both developmental and activational perspectives. Developmentally, they suggest putative etiopathogenic pathways leading from an altered early neurodevelopment to an increased risk for depression-related phenotypes. By exploring and combining genetic, environmental and psychopathologic concepts, the feasibility of these results has been explained by combining the popular genetic pleiotropy hypothesis in psychiatry with a notion of disease-specificity liability driven by the environment. With regards to activational plasticity, this work has proposed novel genetic and epigenetic signatures potentially underlying the clinical manifestation of neuropsychiatric and neurocognitive features of depression (i.e., the genetics of DNMT3B and the epigenetics of DEPDC7); additionally, it has proposed new putative neurobiological mechanisms to explain depressive traits (i.e., a combination of differential and variable methylation, a genetically-mediated hippocampal communication deficit, and a new amygdalar synchrony failure driven by the genes).
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Kirk, Ulrich. "The modularity of aesthetic processing and perception in the human brain : functional neuroimaging studies of neuroaesthetics." Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1445135/.

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By taking advantage of the advent of functional Magnetic Resonance Imaging (fMRI) this thesis argues that aesthetics belongs in the domain of neurobiology by investigating the different brain processes that are implicated in aesthetic perception from two perspectives. The first experiment explores a specific artistic style that has stressed the problem in the relationship between objects and context. This study investigates the neural responses associated with changes in visual perception, as when objects are placed in their normal context versus when the object-context relationship is violated. Indeed, an aim of this study was to cast a new light on this specific artistic style from a neuroscientific perspective. In contrast to basic rewards, which relate to the reproduction of the species, the evolution of abstract, cognitive representations facilitates the use of a different class of rewards related to hedonics. The second part investigates the hedonic processes involved in aesthetic judgments in order to explore if such higher order cognitive rewards use the same neural reward mechanism as basic rewards. In the first of these experiments we modulate the extent to which the neural correlates of aesthetic preference vary as a function of expertise in architecture. In the second experiment we aim to measure the more general effects of labelling works of art with cognitive semantic information in order to explore the neural modulation of aesthetic preference relative to this information. The main finding of this thesis is that stimulus affective value is represented separately in OFC, with positive reward (increasing aesthetic judgments) being represented in medial OFC and negative reward value is being represented in lateral OFC. Furthermore ventral striatum encode reward expectancy and the predictive value of a stimulus. These findings suggest a dissociation of reward processing with separate neural substrates in reward expectancy and stimulus affective value.
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Putt, Shelby Stackhouse. "Human brain activity during stone tool production : tracing the evolution of cognition and language." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2133.

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This study aims to shed light on how and when mechanisms of the human brain evolved to support complex cognition and language. The field of evolutionary cognitive archaeology asserts that prehistoric technologies, as products of past cognition in action, are informative of the minimum cognitive and linguistic abilities that hominins needed to possess for their production. Previous researchers attempted to reconstruct the neural correlates of two Early Stone Age (ESA) tool industries, the 2.6 million-year-old Oldowan industry and the 0.7 million-year-old late Acheulian industry, by using positron emission tomography (PET) to observe the functional activation occurring in the brains of trained and expert stone knappers after making these different tool types. Because of evidence for overlap between the knapping and language circuits of the brain and increased anterior frontal activity during Acheulian tool production, these researchers argued that their results 1) indicate increased cognitive demands for late Acheulian tool production relative to Oldowan tool production and 2) support a technological origin for language, meaning that certain language functions co-opted the neural substrate and functions that were already established for toolmaking and tool use. Because of the motion limiting aspects of PET, however, these studies were unable to record the hemodynamic response of naturalistic stone knapping in real-time. They also were unable to observe the functional activation associated with the earliest stage of learning, which is likely to differ from late stage learning or expertise. Furthermore, any conclusion regarding a technological origin for language is problematic if it relies on data obtained from participants who learned to knap with verbal instruction. To test these two claims, this dissertation utilized a neuroimaging technique called functional near-infrared spectroscopy (fNIRS) to explore the neural correlates of real-time, naturalistic Oldowan and Acheulian stone knapping at three different points in learning. Participants in the study were separated into two groups to learn ESA knapping skills. Both groups watched the same video tutorials that depicted an expert’s hands as he made stone tools, but those in the verbal group heard spoken instructions, while those in the nonverbal group watched a version with the sound turned off. Functional brain images were reconstructed from the digitized landmarks of each participant’s head and from the optical data. An analysis of variance (ANOVA) revealed a clearer distinction between the neural processes of Oldowan and Acheulian tool manufacturing tasks than has previously been demonstrated. Only the Acheulian task recruited a frontotemporal working memory network. Selection for individuals with increased working memory capacities, which would have allowed them to make increasingly complex tools to gain access to novel dietary items, may have spurred the evolution of larger brain size in the genus Homo during the early Pleistocene. The results also demonstrated that the presence or absence of language during training dictated which higher-order cognitive areas of the brain become engaged and at what point in training. Thus, the results of previous neuroarchaeological studies reflect a very specific condition of stone knapping skill acquisition that involves linguistic instruction, which may not be analogous to how skills were transmitted during the ESA. Finally, evidence of overlap between left hemisphere language and stone knapping circuits among the participants in the nonverbal group lends additional support for the technological origin for language hypothesis.
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Cousijn, Helena. "Expression and neural correlates of schizophrenia risk gene ZNF804A." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:91c9b37f-5b7b-4400-b129-0c33e23ee6ed.

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Genome wide association studies have provided evidence for a significant association between ZNF804A (zinc finger protein 804A) - specifically the intronic single nucleotide polymorphism (SNP) rs1344706 - and schizophrenia, but little is known about the function of the gene or the effects of the SNP. By studying post-mortem human brain tissue, I characterised ZNF804A immunoreactivity in adult and foetal human brain and investigated effects of diagnosis and rs1344706 genotype on ZNF804A mRNA and protein expression. Secondly, I looked in a large sample of healthy volunteers (n=922) at the effects of rs1344706 on brain structure using volumetry and voxel based morphometry (VBM). Furthermore, I recruited healthy volunteers who were either homozygous for the risk allele or homozygous for the non-risk allele (n=50). They participated in magnetoencephalography (MEG) and magnetic resonance (MR) sessions in which brain activity was measured during a working memory task, a visual processing task, and rest. Using magnetic resonance spectroscopy, also neurotransmitter levels were assessed. The experiments conducted for this thesis showed for the first time that ZNF804A immunoreactivity can be detected in both foetal and adult human brain and that it is mainly localised to layer III pyramidal cells, with a granular subcellular distribution throughout the cytoplasm. No effect of rs1344706 on mRNA and protein expression was found. In our structural MRI study, rs1344706 did not affect macroscopic brain structure as measured by volumetry and VBM, and given the large sample size, this seems a convincing negative. However, we did find that rs1344706 alters prefrontal-hippocampal connectivity, with increased connectivity being observed in risk homozygotes. Additionally, using MEG, we found an effect of ZNF804A genotype on hippocampal connectivity in the theta band (4-8Hz), with non-risk homozygotes displaying more connectivity. This finding provides a first clue as to the mechanisms that might underlie the previously observed effects of rs1344706 on prefrontal-hippocampal connectivity. Future studies will need to elucidate the actual function of the ZNF804A protein, in order to bridge the gap between the molecular and neuroimaging findings described in this thesis.
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Uhrig, Lynn. "A study of the brain mechanisms of loss of consciousness during general anesthesia using non-human primate neuroimaging." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066339.

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Comment les agents anesthésiques induisent-ils une perte de conscience lors de l’anesthésie générale? La dissection des mécanismes neuronaux de l’anesthésie générale représente un défi important en neurosciences. L’émergence de l’IRM fonctionnelle (IRMf) chez le primate non-humain donne l’occasion d’étudier l’activité neuronale à l’état éveillé et sous anesthésie en s’affranchissant des contraintes cliniques. Le développement récent de paradigmes auditifs, tel que le paradigme ‘local-global’, qui explore spécifiquement les réseaux cérébraux impliqués dans l’état conscient, nous a permis d’émettre l’hypothèse que la combinaison de l’IRMf chez le primate, de paradigmes auditifs et de protocoles d’anesthésie contrôlés par l’électroencéphalogramme (EEG), pourraient aider à disséquer les mécanismes neuronaux de l’anesthésie générale.Dans une première étape, étant donnée l’utilisation extensive de l’IRM dans notre travail, il était important d’étudier systématiquement l’effet des agents anesthésiques sur l’oxygénation vasculaire cérébrale, paramètre critique pour le signal IRMf. Nous avons donc réalisé une expérience préliminaire, faisant appel à l’IRM à ultra-haut champ magnétique chez le rongeur, afin de détecter les éventuels modifications du signal T2* induits par chacun des agents anesthésiques. Nous avons pu démontrer que le propofol et la kétamine, deux agents anesthésiques utilisés en clinique, affectaient moins l’oxygénation sanguine cérébrale que les anesthésiques volatils.Dans une deuxième étape, nous avons développé une « boîte à outils » pour l’IRMf chez le primate éveillé et anesthésié, et avons validé notre dispositif expérimental avec un paradigme auditif basé sur des sons simples (basse et haute fréquence).Dans une troisième étape, nous avons testé le paradigme auditif ‘local-global’ chez le macaque éveillé et avons pu démontrer que le cerveau du macaque est capable d’un codage prédictif hiérarchique à travers un espace de travail global, composé d’un réseau fronto-pariéto-cingulaire, montrant une forte homologie avec celui de l’Homme.Dans une quatrième étape, nous avons testé le paradigme auditif ‘local-global’, chez le macaque anesthésié et avons pu démontrer une désorganisation progressive de l’espace de travail global neuronal sous anesthésie. Cette désorganisation a été proportionnelle au niveau de sédation sous propofol, et complète sous sédation profonde à la kétamine. Ces résultats sont compatibles avec l’hypothèse selon laquelle le mécanisme de la perte de conscience sous anesthésie, est lié à une désorganisation de l’organisation fonctionnelle hiérarchique de l’espace de travail neuronal. Le cortex pariétal apparaît comme une cible commune aux deux agents anesthésiques.Dans la dernière étape, nous avons étudié le réseau cérébral par défaut (« default mode network ») chez le macaque éveillé et anesthésié. Nous avons pu démontrer que sous anesthésie, le cerveau présentait encore des patrons de connectivité distincts et riches, mais que ces patrons étaient fortement liés à l’organisation anatomique sous-jacente, alors que, à l’état éveillé cette organisation se caractérisait par un haut degré de flexibilité temporelle ce qui permet une exploration non-stéréotypée d’une plus grande variété d’états cérébraux.En conclusion, les agents anesthésiques entraînent une désorganisation de l’espace de travail global neuronal, avec pour conséquence l’altération des dynamiques temporelles de l’activité cérébrale spontanée, induisant ainsi une suppression de la conscience
How can anesthetics induce a loss of consciousness during general anesthesia? A major challenge in neuroscience is to dissect the mechanisms of general anesthesia, which is quite difficult to achieve in the clinical conditions. The dawning of monkey functional MRI (fMRI) in neuroscience is an important opportunity to investigate neuronal activity in awake and anesthetized conditions. The recent development of auditory paradigms, such as the ‘local-global’ paradigm, that specifically explore brain networks thought to be specific of the conscious state led us to hypothesize that the combination of primate fMRI, auditory paradigms and single-drug anesthetic protocols with electroencephalography (EEG) control would help dissect the neuronal mechanisms of general anesthesia. In a first step, because we planned an extensive use of fMRI in our work, it was key to screen anesthetic agents for their effects on brain vascular oxygenation, a critical parameter for fMRI signal. Thus we did a preliminary experiment using ultra-high field MRI in rodents to assess subtle changes of the T2* signal under different anesthetic conditions and could demonstrate that propofol and ketamine, both clinical anesthetics, affects less brain blood oxygenation than volatile agents. In a second step, we developed a toolbox for awake and anesthetized monkey fMRI and validated the experimental set-up with a simple sound paradigm (low and high frequency sounds). In the third step, we tested the ‘local-global’ auditory paradigm in awake monkeys and could demonstrate that the macaque brain was capable of hierarchical predictive coding through a hypothetical macaque Global Neuronal Workspace made of frontal, parietal and cingulate cortices, in a striking homology with humans. In the fourth step, we tested the ‘local-global’ auditory paradigm in anesthetized monkeys and could demonstrate a progressive disorganization of the macaque GNW under anesthesia when increasing the levels of propofol sedation, and a complete suppression of the macaque GNW under deep ketamine sedation. These results are compatible with the hypothesis that the mechanism of loss of consciousness under anesthesia is related to the disorganization of a hierarchical GNW, with the parietal cortex as a common target among anesthetics. In the final step we studied the default network by acquiring resting state in awake and anesthetized monkeys and could demonstrate that under anesthesia, the brain still exhibits distinct and rich connectivity patterns, but these patterns become strongly related to the underlying white-matter structural map in a monotonic manner, while the awake state is characterized by a high degree of temporal flexibility which allows for a non-stereotyped exploration of a greater variety of brain states. In conclusion, by disorganizing the GNW, anesthetics alter the temporal dynamics of spontaneous brain activity, and specifically its departure from mere random fluctuations along established anatomical routes, leading to consciousness suppression
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Books on the topic "Human brain- Neuroimaging"

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Frank, Rösler, ed. Neuroimaging of human memory: Linking cognitive processes to neural systems. Oxford: Oxford University Press, 2009.

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Frank, Rösler, ed. Neuroimaging of human memory: Linking cognitive processes to neural systems. Oxford: Oxford University Press, 2009.

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Press, National Academy. Neuroimaging of Human Brain Function. National Academy Press, 1999.

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Proceedings of the National Academy of Sciences. (NAS Colloquium) Neuroimaging of Human Brain Function. National Academies Press, 1998.

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Proceedings of the National Academy of Sciences. (NAS Colloquium) Neuroimaging of Human Brain Function. National Academies Press, 1998.

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Bigler, Erin D. Neuroimaging I (Human Brain Function: Assessment and Rehabilitation). Springer, 1996.

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Bigler, Erin D. Neuroimaging II (Human Brain Function: Assessment and Rehabilitation). Springer, 1996.

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Annese, Jacopo. Neuroimaging Atlas of the Human Brain: MRI, DTI, and Histology. Elsevier Science & Technology Books, 2021.

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Papadelis, Christos, Patricia Ellen Grant, Yoshio Okada, and Hubert Preissl, eds. Magnetoencephalography: an emerging neuroimaging tool for studying normal and abnormal human brain development. Frontiers Media SA, 2015. http://dx.doi.org/10.3389/978-2-88919-658-6.

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Seeman, Philip, and Bertha Madras. Imaging of the Human Brain in Health and Disease. Elsevier Science & Technology Books, 2013.

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Book chapters on the topic "Human brain- Neuroimaging"

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Sowell, Elizabeth R., and Terry L. Jernigan. "Imaging the Developing Human Brain." In Neuroimaging I, 53–75. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4899-1701-0_3.

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Gevins, Alan. "Imaging the Neurocognitive Networks of the Human Brain." In Neuroimaging I, 133–59. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4899-1701-0_7.

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Tiede, U., M. Bomans, K. H. Höhne, A. Pommert, M. Riemer, Th Schiemann, R. Schubert, and W. Lierse. "A Computerized Three-Dimensional Atlas of the Human Skull and Brain." In Neuroimaging I, 185–97. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4899-1701-0_9.

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Shibasaki, Hiroshi. "Functional Neuroimaging of the Human Brain." In Contemporary Neuropsychiatry, 69–72. Tokyo: Springer Japan, 2001. http://dx.doi.org/10.1007/978-4-431-67897-7_9.

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Salimi, Ali, Aurore A. Perrault, Victoria Zhang, Soufiane Boucetta, and Thien Thanh Dang-Vu. "Neuroimaging of Brain Oscillations During Human Sleep." In Neuronal Oscillations of Wakefulness and Sleep, 171–97. New York, NY: Springer New York, 2020. http://dx.doi.org/10.1007/978-1-0716-0653-7_6.

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Trambaiolli, Lucas R., Claudinei E. Biazoli, and João R. Sato. "Brain Imaging Methods in Social and Affective Neuroscience: A Machine Learning Perspective." In Social and Affective Neuroscience of Everyday Human Interaction, 213–30. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08651-9_13.

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AbstractMachine learning (ML) is a subarea of artificial intelligence which uses the induction approach to learn based on previous experiences and make conclusions about new inputs (Mitchell, Machine learning. McGraw Hill, 1997). In the last decades, the use of ML approaches to analyze neuroimaging data has attracted widening attention (Pereira et al., Neuroimage 45(1):S199–S209, 2009; Lemm et al., Neuroimage 56(2):387–399, 2011). Particularly interesting recent applications to affective and social neuroscience include affective state decoding, exploring potential biomarkers of neurological and psychiatric disorders, predicting treatment response, and developing real-time neurofeedback and brain-computer interface protocols. In this chapter, we review the bases of the most common neuroimaging techniques, the basic concepts of ML, and how it can be applied to neuroimaging data. We also describe some recent examples of applications of ML-based analysis of neuroimaging data to social and affective neuroscience issues. Finally, we discuss the main ethical aspects and future perspectives for these emerging approaches.
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Ertekin, Ersen, Özüm Tunçyürek, Mehmet Turgut, and Yelda Özsunar. "Neuroimaging Techniques for Investigation of the Insula." In Island of Reil (Insula) in the Human Brain, 91–100. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75468-0_9.

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Takagi, Michael, George Youssef, and Valentina Lorenzetti. "Neuroimaging of the Human Brain in Adolescent Substance Users." In Drug Abuse in Adolescence, 69–99. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17795-3_6.

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Fazli, Siamac, Min-Ho Lee, Seul-Ki Yeom, John Williamson, Isabella Schlattner, Yiyu Chen, and Seong-Whan Lee. "Benefits and Limits of Multimodal Neuroimaging for Brain Computer Interfaces." In Trends in Augmentation of Human Performance, 35–48. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-7239-6_3.

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Dyson, Kenneth S., and Richard D. Hoge. "Neuroimaging as a Research Tool in Human Essential Hypertension." In Hypertension and the Brain as an End-Organ Target, 55–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25616-0_4.

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Conference papers on the topic "Human brain- Neuroimaging"

1

Wandell, Brian A., and Robert F. Dougherty. "Computational neuroimaging: maps and tracks in the human brain." In Electronic Imaging 2006, edited by Bernice E. Rogowitz, Thrasyvoulos N. Pappas, and Scott J. Daly. SPIE, 2006. http://dx.doi.org/10.1117/12.674141.

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Urgen, Burcu A., Selen Pehlivan, and Ayse P. Saygin. "Representational similarity of actions in the human brain." In 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI). IEEE, 2016. http://dx.doi.org/10.1109/prni.2016.7552341.

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Wang, Xixi, Carol A. Jew, Feng Lin, and Rajeev D. S. Raizada. "Manifolds of tool-graspability in the human brain." In 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI). IEEE, 2017. http://dx.doi.org/10.1109/prni.2017.7981507.

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Schoenmakers, Sanne, Tom Heskes, and Marcel van Gerven. "Hidden Markov Models for Reading Words from the Human Brain." In 2015 International Workshop on Pattern Recognition in NeuroImaging (PRNI). IEEE, 2015. http://dx.doi.org/10.1109/prni.2015.31.

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Lin, Chen-Hao P., Wiete Fehner, Inema E. Orukari, Lisa Kobayashi Frisk, Alvin Agato, Manish Verma, Anthony O'Sullivan, et al. "Fiber-Based Speckle Contrast Optical Tomography for Neuroimaging in Humans: Simulation of High-Density vs. Sparse Arrays and In Vivo Human Measurements." In Optics and the Brain. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/brain.2023.bth2b.2.

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We simulated speckle contrast optical tomography performance based on an anatomical head model comparing sparse and high-density arrays. We also demonstrated measurements of pulsatile flow on a human head using a multi-mode fiber-based speckle system.
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Franke, Katja, Robert Dahnke, Geoffrey Clarke, Anderson Kuo, Cun Li, Peter Nathanielsz, Matthias Schwab, and Christian Gaser. "MRI based biomarker for brain aging in rodents and non-human primates." In 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI). IEEE, 2016. http://dx.doi.org/10.1109/prni.2016.7552326.

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Salman, Adnan, Allen Malony, Sergei Turovets, Vasily Volkov, David Ozog, and Don Tucker. "Next-generation human brain neuroimaging and the role of high-performance computing." In 2013 International Conference on High Performance Computing & Simulation (HPCS). IEEE, 2013. http://dx.doi.org/10.1109/hpcsim.2013.6641421.

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Kim, Junsol. "Academic journal recommendation for human neuroimaging studies via brain activation-based filtering." In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2020. http://dx.doi.org/10.1109/bibm49941.2020.9313316.

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Gan, Jiangzhang, Xiaofeng Zhu, Rongyao Hu, Yonghua Zhu, Junbo Ma, Ziwen Peng, and Guorong Wu. "Multi-graph Fusion for Functional Neuroimaging Biomarker Detection." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/81.

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Brain functional connectivity analysis on fMRI data could improve the understanding of human brain function. However, due to the influence of the inter-subject variability and the heterogeneity across subjects, previous methods of functional connectivity analysis are often insufficient in capturing disease-related representation so that decreasing disease diagnosis performance. In this paper, we first propose a new multi-graph fusion framework to fine-tune the original representation derived from Pearson correlation analysis, and then employ L1-SVM on fine-tuned representations to conduct joint brain region selection and disease diagnosis for avoiding the issue of the curse of dimensionality on high-dimensional data. The multi-graph fusion framework automatically learns the connectivity number for every node (i.e., brain region) and integrates all subjects in a unified framework to output homogenous and discriminative representations of all subjects. Experimental results on two real data sets, i.e., fronto-temporal dementia (FTD) and obsessive-compulsive disorder (OCD), verified the effectiveness of our proposed framework, compared to state-of-the-art methods.
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Chen, Bin, John Moreland, and Jingyu Zhang. "Human Brain Functional MRI and DTI Visualization With Virtual Reality." In ASME 2011 World Conference on Innovative Virtual Reality. ASMEDC, 2011. http://dx.doi.org/10.1115/winvr2011-5565.

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Magnetic resonance diffusion tensor imaging (DTI) and functional MRI (fMRI) are two active research areas in neuroimaging. DTI is sensitive to the anisotropic diffusion of water exerted by its macromolecular environment and has been shown useful in characterizing structures of ordered tissues such as the brain white matter, myocardium, and cartilage. The diffusion tensor provides two new types of information of water diffusion: the magnitude and the spatial orientation of water diffusivity inside the tissue. This information has been used for white matter fiber tracking to review physical neuronal pathways inside the brain. Functional MRI measures brain activations using the hemodynamic response. The statistically derived activation map corresponds to human brain functional activities caused by neuronal activities. The combination of these two methods provides a new way to understand human brain from the anatomical neuronal fiber connectivity to functional activities between different brain regions. In this study, virtual reality (VR) based MR DTI and fMRI visualization with high resolution anatomical image segmentation and registration, ROI definition and neuronal white matter fiber tractography visualization and fMRI activation map integration is proposed. Rationale and methods for producing and distributing stereoscopic videos are also discussed.
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