Дисертації з теми "Computational neuroimaging, cognitive neuroscience"
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Salimi-Khorshidi, Gholamreza. "Statistical models for neuroimaging meta-analytic inference." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:40a10327-7f36-42e7-8120-ae04bd8be1d4.
Повний текст джерелаCooke, Megan E. "Integrating Genetics and Neuroimaging to study Subtypes of Binge Drinkers." VCU Scholars Compass, 2017. https://scholarscompass.vcu.edu/etd/5167.
Повний текст джерелаCronin, Beau D. "Quantifying uncertainty in computational neuroscience with Bayesian statistical inference." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45336.
Повний текст джерелаIncludes bibliographical references (p. 101-106).
Two key fields of computational neuroscience involve, respectively, the analysis of experimental recordings to understand the functional properties of neurons, and modeling how neurons and networks process sensory information in order to represent the environment. In both of these endeavors, it is crucial to understand and quantify uncertainty - when describing how the brain itself draws conclusions about the physical world, and when the experimenter interprets neuronal data. Bayesian modeling and inference methods provide many advantages for doing so. Three projects are presented that illustrate the advantages of the Bayesian approach. In the first, Markov chain Monte Carlo (MCMC) sampling methods were used to answer a range of scientific questions that arise in the analysis of physiological data from tuning curve experiments; in addition, a software toolbox is described that makes these methods widely accessible. In the second project, the model developed in the first project was extended to describe the detailed dynamics of orientation tuning in neurons in cat primary visual cortex. Using more sophisticated sampling-based inference methods, this model was applied to answer specific scientific questions about the tuning properties of a recorded population. The final project uses a Bayesian model to provide a normative explanation of sensory adaptation phenomena. The model was able to explain a range of detailed physiological adaptation phenomena.
by Beau D. Cronin.
Ph.D.
Lundh, Dan. "A computational neuroscientific model for short-term memory." Thesis, University of Exeter, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324742.
Повний текст джерелаVellmer, Sebastian. "Applications of the Fokker-Planck Equation in Computational and Cognitive Neuroscience." Doctoral thesis, Humboldt-Universität zu Berlin, 2020. http://dx.doi.org/10.18452/21597.
Повний текст джерелаThis thesis is concerned with the calculation of statistics, in particular the power spectra, of point processes generated by stochastic multidimensional integrate-and-fire (IF) neurons, networks of IF neurons and decision-making models from the corresponding Fokker-Planck equations. In the brain, information is encoded by sequences of action potentials. In studies that focus on spike timing, IF neurons that drastically simplify the spike generation have become the standard model. One-dimensional IF neurons do not suffice to accurately model neural dynamics, however, the extension towards multiple dimensions yields realistic behavior at the price of growing complexity. The first part of this work develops a theory of spike-train power spectra for stochastic, multidimensional IF neurons. From the Fokker-Planck equation, a set of partial differential equations is derived that describes the stationary probability density, the firing rate and the spike-train power spectrum. In the second part of this work, a mean-field theory of large and sparsely connected homogeneous networks of spiking neurons is developed that takes into account the self-consistent temporal correlations of spike trains. Neural input is approximated by colored Gaussian noise generated by a multidimensional Ornstein-Uhlenbeck process of which the coefficients are initially unknown but determined by the self-consistency condition and define the solution of the theory. To explore heterogeneous networks, an iterative scheme is extended to determine the distribution of spectra. In the third part, the Fokker-Planck equation is applied to calculate the statistics of sequences of binary decisions from diffusion-decision models (DDM). For the analytically tractable DDM, the statistics are calculated from the corresponding Fokker-Planck equation. To determine the statistics for nonlinear models, the threshold-integration method is generalized.
Cattinelli, I. "INVESTIGATIONS ON COGNITIVE COMPUTATION AND COMPUTATIONAL COGNITION." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/155482.
Повний текст джерелаPetitet, Pierre. "Sensorimotor adaptation : mechanisms, modulation and rehabilitation potential." Thesis, University of Oxford, 2018. http://ora.ox.ac.uk/objects/uuid:5935d96d-625a-4778-b42d-bb56c96d96cc.
Повний текст джерелаWright, Sean Patrick. "Cognitive neuroscience of episodic memory: behavioral, genetic, electrophysiological, and computational approaches to sequence memory." Thesis, Boston University, 2003. https://hdl.handle.net/2144/27805.
Повний текст джерелаPLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.
2031-01-02
Vellmer, Sebastian [Verfasser]. "Applications of the Fokker-Planck Equation in Computational and Cognitive Neuroscience / Sebastian Vellmer." Berlin : Humboldt-Universität zu Berlin, 2020. http://d-nb.info/1214240682/34.
Повний текст джерелаGing-Jehli, Nadja Rita. "On the implementation of Computational Psychiatry within the framework of Cognitive Psychology and Neuroscience." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555338342285251.
Повний текст джерелаAsher, Derrik E. "Action Selection and Execution with Computational Neural Networks of Neuromodulation and Sensory Integration." Thesis, University of California, Irvine, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3626926.
Повний текст джерелаNeuromodulation is a neurophysiological process by which a single neuron can regulate the neural activity of a diverse population of neurons. Sensory integration is a neurobiological process by which the brain combines multiple sensory modality inputs (i.e., vision, proprioception, audition, tactile, olfactory, vestibular, interoception, and taste) into usable functional outputs. In biological systems, neuromodulation and sensory integration have been shown to have a strong influence over action selection (decision-making) and action execution (motor output) respectively. The experiments portrayed in Chapters 1-4 provide empirical and theoretical evidence for neuromodulatory influence over selected actions through predictions of expected costs and rewards. The simulation experiments described in Chapters 5-6 illustrate how sensory integration influences action execution across different neural architectures in visually and memory guided sensorimotor transformation tasks. The implications of these results and future endeavors are discussed in Chapter 7, along with a proposed computational model of both action selection and sensory integration to investigate the dynamics of decision-making influenced by the integration of multiple sensory inputs in order to execute an action.
De, Pisapia Nicola. "A framework for implicit planning : towards a cognitive/computational neuroscience theory of prefrontal cortex function." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/24519.
Повний текст джерелаMilano, Isabel. "The Characterization of Alzheimer’s Disease and the Development of Early Detection Paradigms: Insights from Nosology, Biomarkers and Machine Learning." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2192.
Повний текст джерелаJessup, Ryan K. "Neural correlates of the behavioral differences between descriptive and experiential choice an examination combining computational modeling with fMRI /." [Bloomington, Ind.] : Indiana University, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3337258.
Повний текст джерелаTitle from PDF t.p. (viewed on Feb. 17, 2010). Source: Dissertation Abstracts International, Volume: 69-12, Section: B, page: 7830. Advisers: Jerome R. Busemeyer; Peter M. Todd.
Lin, Chia-Shu. "Decision-making in the context of pain." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:3ba80922-3629-4958-a62b-7ebf75871bbf.
Повний текст джерелаSchmidt, Kristin. "Manipulating the hypothalamic-pituitary-adrenal axis : effects on cognitive and emotional information processing and neural connectivity." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:c0475a98-e070-4446-9179-eb87047cb854.
Повний текст джерелаZaldivar, Andrew. "Investigating the Interactions of Neuromodulators| A Computational Modeling, Game Theoretic, Pharmacological, Embodiment, and Neuroinformatics Perspective." Thesis, University of California, Irvine, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3631146.
Повний текст джерелаNeuromodulatory systems originate in nuclei localized in the subcortical region of the brain and control fundamental behaviors by interacting with many areas of the central nervous system. Much is known about neuromodulators, but their structural and functional implications in fundamental behavior remain unclear. This dissertation set out to investigate the interaction of neuromodulators and their role in modulating behaviors by combining methodologies in computational modeling, game theory, embodiment, pharmacological manipulations, and neuroinformatics. The first study introduces a novel computational model that predicts how dopamine and serotonin shape competitive and cooperative behavior in a game theoretic environment. The second study adopted the model from the first study to gauge how humans react to adaptive agents, as well as measuring the influence of embodied agents on game play. The third study investigates functional activity of these neuromodulatory circuits by exploring the expression energy of neuromodulatory receptors using the Allen Brain Atlas. The fourth study features a web application known as the Allen Brain Atlas-Drive Visualization, which provides users with a quick and intuitive way to survey large amounts of expression energy data across multiple brain regions of interest. Finally, the last study continues exploring the interaction of dopamine and serotonin by focusing specifically on the reward circuit using the Allen Brain Atlas. The first two studies provide a more behavioral understanding of how dopamine and serotonin interacts, what that interaction might look like in the brain, and how those interactions transpire in complex situations. The remaining three studies uses a neuroinformatics approach to reveal the underlying empirical structure and function behind the interactions of dopamine, serotonin, acetylcholine and norepinephrine in brain regions responsible for the behaviors discussed in the first two studies. When combined, each study provides an additional level of understanding about neuromodulators. This is of great importance because neuroscience simply cannot be explained through one methodology. It is going to take a multifaceted effort, like the one presented in this dissertation, to obtain a deeper understanding of the complexity behind neuromodulators and their structural and functional relationship with each other.
Jennette, Kyle Joseph. "The Association of Cognitive Endophenotypes and Risky Single Nucleotide Polymorphisms of Alzheimer's Disease within the Alzheimer's Disease Neuroimaging Initiative (ADNI) Database." Scholar Commons, 2015. https://scholarcommons.usf.edu/etd/5510.
Повний текст джерелаCogliati, Dezza Irene. "“Vanilla, Vanilla .but what about Pistachio?” A Computational Cognitive Clinical Neuroscience Approach to the Exploration-Exploitation Dilemma." Doctoral thesis, Universite Libre de Bruxelles, 2018. https://dipot.ulb.ac.be/dspace/bitstream/2013/278730/3/Document1.pdf.
Повний текст джерелаDoctorat en Sciences psychologiques et de l'éducation
info:eu-repo/semantics/nonPublished
Thomas, Adam G. "Brain plasticity and aerobic fitness." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:c941d5b2-4b37-420a-be3f-d71e753fc8d6.
Повний текст джерелаHaarsma, Joost. "Towards a mechanistic understanding of the neurobiological mechanisms underlying psychosis." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/283000.
Повний текст джерелаClark, Ian Alexander. "A clinical neuroscience investigation into flashbacks and involuntary autobiographical memories." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:04f72e37-73fe-4347-8af1-8d8852c05f1b.
Повний текст джерелаIyer, Laxmi R. "CANDID - A Neurodynamical Model of Idea Generation." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1326828617.
Повний текст джерелаBolenz, Florian, Andrea M. F. Reiter, and Ben Eppinger. "Developmental Changes in Learning: Computational Mechanisms and Social Influences." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-232296.
Повний текст джерелаHunt, Laurence T. "Modelling human decision under risk and uncertainty." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:244ce799-7397-4698-8dac-c8ca5d0b3e28.
Повний текст джерелаMichael, Elizabeth. "Dissociable sources of uncertainty in perceptual decision making." Thesis, University of Oxford, 2016. http://ora.ox.ac.uk/objects/uuid:581e8fc9-1e12-4877-a89a-44cdc67c45e2.
Повний текст джерелаBolenz, Florian, Andrea M. F. Reiter, and Ben Eppinger. "Developmental Changes in Learning: Computational Mechanisms and Social Influences." Frontiers Research Foundation, 2017. https://tud.qucosa.de/id/qucosa%3A30736.
Повний текст джерелаHoward, Newton. "Approach to study the brain : towards the early detection of neurodegenerative disease." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:2f81e9d4-ac91-444f-b966-ce1fc665b065.
Повний текст джерелаVetter, Nora. "Theory of Mind Development in Adolescence and its (Neuro)cognitive Mechanisms." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-110202.
Повний текст джерелаFoubert, Luc. "Spatio-temporal characteristics of the visual interhemispheric integration via the corpus callosum : computational modeling & optical imaging approaches." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2007. http://tel.archives-ouvertes.fr/tel-00811495.
Повний текст джерелаLabache, Loïc. "Création d'Atlas des Réseaux Cérébraux Sous-tendant les Fonctions Cognitives Latéralisées : Application à l'Étude de la Variabilité Inter-individuelle du Langage." Thesis, Bordeaux, 2020. http://www.theses.fr/2020BORD0155.
Повний текст джерелаMy thesis work is part of a multi-modal and multi-scale integration approach which has led to the emergence of cognitive and population neuroimaging. More specifically, fMRI provides two types of three-dimensional functional brain maps: activation maps allowing for visualizing brain regions directly involved in a cognitive process, and intrinsic connectivity maps measuring the synchronization between spatially distant but functionally connected regions. I have applied new statistical methodologies to these two types of maps, allowing me to deal with both the individual and the spatial dimensions. In the first part, I designed atlases of brain regions dedicated to specific cognitive functions, based on their hemispheric lateralization and targeting a population selected for its low variability. I present here the first two language atlases. Indeed, although there are many approaches to map language areas in patients, there was no atlas of networks supporting language functions in healthy individuals so far. I first identified left activated and left asymmetrical regions, both during sentence production, listening and reading, in 137 healthy right-handed individuals. Analysis of the intrinsic connectivity between the 32 identified regions reveals that they are part of 3 distinct functional networks, which constitute the SENSAAS (SENtence Supramodal Areas AtlaS) brain atlas. Among these networks, one with 18 regions contains the essential language areas (SENT_CORE), i.e. the brain areas whose lesion leads to an impairment in the integration of the meaning of speech. Specifically, SENT_CORE contains 3 hubs supporting the information integration and dissemination, localized in the Broca and Wernicke area. I then applied this methodology to the elaboration of an atlas of word processing networks. I identified 21 brain regions organized into 2 distinct networks, one of which is a phonological network including the audio-motor loop. For the first time, a strong intrinsic connectivity between the left audio-motor loop and the prosodic processing, located in the upper temporal sulcus of the right hemisphere, is evidenced. Finally, I developed a new method for studying the variability of three-dimensional data. This new method includes two different mathematical tools based on hierarchical agglomerative clustering algorithms. The first one makes it possible to identify variables leading to partition instability, the second one allows for extracting stable sub-populations from a starting population. The applications of all of this work are numerous: for example, I used the SENT_CORE network to study the inter-individual variability of hemispheric lateralization of the sentence supramodal areas. I have thus identified two groups of typical asymmetric left language individuals, with high left intra-hemispheric intrinsic connectivity and low inter-hemispheric connectivity, and a group of atypical individuals: rightward asymmetrical for language, with high intrinsic connectivity of language networks in both hemispheres and high inter-hemispheric connectivity. SENSAAS has also been used to study the genetic support of language atypicality, as well as for the topological characterization of the memory and language networks of individuals with mesial temporal lobe epilepsy. The new method for assessing inter-individual variability was used to evaluate the stability of the intrinsic networks of a new functional atlas adapted for late adulthood
Pallarés, Picazo Vicente. "Individual traits versus invariances of cognitive functions: a model-based study of brain connectivity." Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/666806.
Повний текст джерелаÉs conegut en la literatura de neuroimatge que les xarxes cerebrals funcionals reflecteixen trets personals. Aquestes característiques individuals podrien interferir en caracteritzar la cognició entesa com la manera en què les xarxes es coordinen per realitzar una tasca, com mantenir l'atenció, recordar o processar informació visual. Cóm aquests aspectes individuals coexisteixen amb mecanismes generals, és, per tant, una pregunta clau en recerca sobre connectivitat cerebral. Aquest treball estudia la relació entre marcadors de connectivitat específics tant de subjectes, com de tasques. Se centra en dues escales temporals: la variabilitat entre sessions, i les fluctuacions ràpides produïdes durant una sessió d'adquisició. Utilitzem tècniques de machine learning per separar quantitativament les contribucions d'informació del subjecte i de l'estat cognitiu a la connectivitat. La metodologia presentada ens permet extreure aquelles xarxes representatives d'ambdues dimensions, així com aprofundir en la seva evolució, suggerint les escales temporals rellevants en la cognició.
There is consistent evidence in the neuroimaging literature that functional brain networks reflect personal traits. Individual specificity may interfere with the characterization of cognition, in terms of coordination of brain networks to perform a task, such as sustained attention, memory retrieval or visual information processing. How individual traits coexist with invariant mechanisms is, therefore, a key question in brain connectivity research. This work aims to examine the relationship between subject- and task-specific connectivity signatures. It focuses on two different timescales: day-to-day variability and faster fluctuations exhibited within a scanning session. We adopt a machine learning approach to quantitatively disentangle the contribution of subject information and cognitive state to the connectivity patterns. The proposed methodology allows us to extract the specific brain networks that support each of the two dimensions, as well as to delve into their changes over time, suggesting the relevant timescales for cognition.
Bartley, Jessica E. "Exploring the Neural Mechanisms of Physics Learning." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3889.
Повний текст джерелаInsabato, Andrea. "Neurodynamical theory of decision confidence." Doctoral thesis, Universitat Pompeu Fabra, 2014. http://hdl.handle.net/10803/129463.
Повний текст джерелаEl estudio de la confianza en la decisión ofrece una perspectiva ventajosa sobre los procesos de introspección y sobre los procesos de evaluación de la toma de decisiones. No obstante todav'ia no tenemos un conocimiento exhaustivo del sustrato neurofisiológico y computacional de la confianza en la decisión. Existen principalmente dos paradigmas experimentales para medir la confianza en la decisión en los sujetos no humanos: apuesta post-decisional (post-decision wagering) y opción insegura (uncertain option). En esta tesis tratamos de aclarar los mecanísmos computacionales que subyacen a los procesos de toma de decisiones y juicios de confianza en ambos paradigmas experimentales. El modelo que proponemos para explicar los experimentos de apuesta post-decisional es una red neuronal de atractores de dos capas. En este modelo la primera capa se encarga de la toma de decisiones, mientras la segunda capa vigila la actividad de la primera capa y toma un juicio sobre la confianza en la decisión. Sucesivamente testeamos la predicción de este modelo analizando la actividad de neuronas registrada en el cerebro de dos monos, mientras estos desempeñaban una tarea de toma de decisiones. Con este análisis mostramos la existencia de neuronas en la corteza premotora ventral que codifican la confianza en la decisión. Nuestros resultados muestran también que en el cerebro de los primates existen tanto neuronas que codifican confianza como neuronas que la codifican de forma continua. Más en específico mostramos que existen tres mecanismos de codificación: 1. codificación por tiempo de cambio, 2. codificación por tasa de disparo, 3. codificación binaria. En relación a las tareas de opción insegura proponemos un modelo de red de atractores para opciones multiplas. En este modelo la confianza emerge de la dinámica estocástica de las neuronas de decisión, volviéndose así innecesaria la supervisión del proceso de toma de decisiones por parte de otra red (como en el modelo de la tarea de apuesta post-decisional). El modelo explica los datos de comportamiento de los monos y los registros de la actividad de neuronas del área lateral intraparietal como efectos de la dinámica multiestable de la red de atractores. Además el modelo produce interesantes y novedosas predicciones que se podrán testear en experimentos futuros. La compleja representación neurofisiológica y los distintos mecanísmos computacionales que emergen de este trabajo sugieren distintos aspectos funcionales de la confianza en la toma de decisiones.
Sreenivasan, Varsha. "Structural connectivity correlates of human cognition explored with diffusion MRI and tractography." Thesis, 2021. https://etd.iisc.ac.in/handle/2005/5228.
Повний текст джерелаBerteau, Stefan André. "Modeling biophysical and neural circuit bases for core cognitive abilities evident in neuroimaging patterns: hippocampal mismatch, mismatch negativity, repetition positivity, and alpha suppression of distractors." Thesis, 2018. https://hdl.handle.net/2144/27671.
Повний текст джерелаKriete, Trenton E. "Impaired cognitive flexibility and intact cognitive control in autism a computational cognitive neuroscience approach /." Diss., 2005. http://etd.library.vanderbilt.edu/ETD-db/available/etd-04012005-125030/.
Повний текст джерелаMurugan, Rohini. "Computational mechanisms underlying eye-head coordination." Thesis, 2021. https://etd.iisc.ac.in/handle/2005/5536.
Повний текст джерелаGUAZZINI, ANDREA. "Computational models of cognitive activity: from neural to social dynamics." Doctoral thesis, 2009. http://hdl.handle.net/2158/822745.
Повний текст джерелаLin, Yao. "FMRI of a Visual Patterns N-back Task in Typical Development." Thesis, 2012. http://hdl.handle.net/1807/33290.
Повний текст джерелаHassall, Cameron Dale. "Learning in Non-Stationary Environments." 2013. http://hdl.handle.net/10222/36240.
Повний текст джерелаPrince, Steven Eric. "Functional Neuroimaging Investigations of Human Memory Comparisons of Successful Encoding and Retrieval for Relational and Item Information." Diss., 2007. http://hdl.handle.net/10161/201.
Повний текст джерелаConroy, Susan Kim. "Chemotherapy, estrogen, and cognition : neuroimaging and genetic variation." Thesis, 2014. http://hdl.handle.net/1805/4027.
Повний текст джерелаThe time course and biological mechanisms by which breast cancer (BC) and/or alterations in estrogen status lead to cognitive and brain changes remain unclear. The studies presented here use neuroimaging, cognitive testing, genetics, and biomarkers to investigate how post-chemotherapy interval (PCI), chemotherapy-induced amenorrhea (CIA), and genetic variation in the estrogen pathway affect the brain. Chapter 1 examines the association of post-chemotherapy interval (PCI) with gray matter density (GMD) and working memory-related brain activation in BC survivors (mean PCI 6.4, range 3-10 years). PCI was positively associated with GMD and activation in the right frontal lobe, and GMD in this region was correlated with global neuropsychological function. In regions where BC survivors showed decreased GMD compared to controls, this was inversely related to oxidative DNA damage and learning and memory scores. This is the first study to show neural effects of PCI and relate DNA damage to brain alterations in BC survivors. Chapter 2 demonstrates prospectively, in an independent cohort, decreased combined magnitudes of brain activation and deactivation from pre-to post-chemotherapy in patients undergoing CIA compared to both postmenopausal BC patients undergoing chemotherapy and healthy controls. CIA’s change in activity magnitude was strongly correlated with change in processing speed, suggesting this activity increase reflects effective cognitive compensation. These results demonstrate that the pattern of change in brain activity from pre- to post-chemotherapy varies according to pre-treatment menopausal status. Chapter 3 presents the effects of variation in ESR1, the gene that codes for estrogen receptor-α, on brain structure in healthy older adults. ESR1 variation was associated with hippocampus and amygdala volumes, particularly in females. Single nucleotide polymorphism (SNP) rs9340799 influenced cortical GMD and thickness differentially by gender. Apolipoprotein E (APOE)-ε4 carrier status modulated the effect of SNP rs2234693 on amygdala volumes in women. This study showed that genetic variation in estrogen relates to brain morphology in ways that differ by sex, brain region and APOE-ε4 carrier status. The three studies presented here explore the interplay of BC, estrogen, and cognition, showing that PCI, CIA, and ESR1 genotype influence brain phenotypes. Cognitive correlates of neuroimaging findings indicate potential clinical significance of these results.
(9790292), Michael Cvirn. "The effects of temperature, sleep restriction, and physical activity on the sleep architecture and cognitive performance of volunteer firefighters during various simulation wildland fireground tours." Thesis, 2018. https://figshare.com/articles/thesis/The_effects_of_temperature_sleep_restriction_and_physical_activity_on_the_sleep_architecture_and_cognitive_performance_of_volunteer_firefighters_during_various_simulation_wildland_fireground_tours/13447676.
Повний текст джерелаThompson, Jessica A. F. "Characterizing and comparing acoustic representations in convolutional neural networks and the human auditory system." Thesis, 2020. http://hdl.handle.net/1866/24665.
Повний текст джерелаAuditory processing in the human brain and in contemporary machine hearing systems consists of a cascade of representational transformations that extract and reorganize relevant information to enable task performance. This thesis is concerned with the nature of acoustic representations and the network design and learning principles that support their development. The primary scientific goals are to characterize and compare auditory representations in deep convolutional neural networks (CNNs) and the human auditory pathway. This work prompts several meta-scientific questions about the nature of scientific progress, which are also considered. The introduction reviews what is currently known about the mammalian auditory pathway and introduces the relevant concepts in deep learning.The first article argues that the most pressing philosophical questions at the intersection of artificial and biological intelligence are ultimately concerned with defining the phenomena to be explained and with what constitute valid explanations of such phenomena. I highlight relevant theories of scientific explanation which we hope will provide scaffolding for future discussion. Article 2 tests a popular model of auditory cortex based on frequency-specific spectrotemporal modulations. We find that a linear model trained only on BOLD responses to simple dynamic ripples (containing only one fundamental frequency, temporal modulation rate, and spectral scale) can generalize to predict responses to mixtures of two dynamic ripples. Both the third and fourth article investigate how CNN representations are affected by various aspects of training. The third article characterizes the language specificity of CNN layers and explores the effect of freeze training and random weights. We observed three distinct regions of transferability: (1) the first two layers were entirely transferable between languages, (2) layers 2--8 were also highly transferable but we found some evidence of language specificity, (3) the subsequent fully connected layers were more language specific but could be successfully finetuned to the target language. In Article 4, we use similarity analysis to find that the superior performance of freeze training achieved in Article 3 can be largely attributed to representational differences in the penultimate layer: the second fully connected layer. We also analyze the random networks from Article 3, from which we conclude that representational form is doubly constrained by architecture and the form of the input and target. To test whether acoustic CNNs learn a similar representational hierarchy as that of the human auditory system, the fifth article presents a similarity analysis to compare the activity of the freeze trained networks from Article 3 to 7T fMRI activity throughout the human auditory system. We find no evidence of a shared representational hierarchy and instead find that all of our auditory regions were most similar to the first fully connected layer. Finally, the discussion chapter reviews the merits and limitations of a deep learning approach to neuroscience in a model comparison framework. Together, these works contribute to the nascent enterprise of modeling the auditory system with neural networks and constitute a small step towards a unified science of intelligence that studies the phenomena that are exhibited in both biological and artificial intelligence.
(10514360), Uttara Vinay Tipnis. "Data Science Approaches on Brain Connectivity: Communication Dynamics and Fingerprint Gradients." Thesis, 2021.
Знайти повний текст джерелаVetter, Nora. "Theory of Mind Development in Adolescence and its (Neuro)cognitive Mechanisms." Doctoral thesis, 2012. https://tud.qucosa.de/id/qucosa%3A26820.
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