Academic literature on the topic 'Quantitative Neuroscience'

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Journal articles on the topic "Quantitative Neuroscience"

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Höller, Yvonne. "Quantitative EEG in Cognitive Neuroscience." Brain Sciences 11, no. 4 (April 19, 2021): 517. http://dx.doi.org/10.3390/brainsci11040517.

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Hu, Chenfei, and Gabriel Popescu. "Quantitative Phase Imaging (QPI) in Neuroscience." IEEE Journal of Selected Topics in Quantum Electronics 25, no. 1 (January 2019): 1–9. http://dx.doi.org/10.1109/jstqe.2018.2869613.

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Milton, John G. "Quantitative Neuroscience: From Chalk Board to Bedside." Mathematical Modelling of Natural Phenomena 5, no. 2 (2010): 1–4. http://dx.doi.org/10.1051/mmnp/20105299.

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Webster, Gregory D. "Evolutionary Theory in Cognitive Neuroscience: A 20-Year Quantitative Review of Publication Trends." Evolutionary Psychology 5, no. 3 (July 1, 2007): 147470490700500. http://dx.doi.org/10.1177/147470490700500304.

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Evolutionary cognitive neuroscience is an emerging and promising new scientific field that combines the meta-theoretical strengths of an evolutionary perspective with the methodological rigor of neuroscience. The purpose of the present research was to quantify and test evolution's influence in neuroscience and cognitive neuroscience journals over time (1987–2006). In Study 1, analyses from a convenience sample of 10 neuroscience journals revealed that the proportion of neuroscience articles mentioning evolution grew significantly over the last 20 years. Moreover, beginning as early as 1990, the average proportion of neuroscience articles mentioning evolution was significantly different from zero. These effects were not moderated by between-journals differences in impact factor (a citation rate index), suggesting that the observed growth was fairly consistent across journals. In Study 2, analyses from a convenience sample of 4 cognitive neuroscience journals revealed that the proportion of cognitive neuroscience articles mentioning evolution neither differed from zero nor grew significantly over time (1987–2006); however, the change-over-time effect size was large. Compared to other research areas, evolution's penetration into cognitive neuroscience articles grew faster than anthropology, economics, and sociology, but not psychology. The implications of evolutionary psychology's increasing role in science in general, and in cognitive neuroscience in particular, are discussed.
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Duffus, Dwight, and Andrei Olifer. "Introductory Life Science Mathematics and Quantitative Neuroscience Courses." CBE—Life Sciences Education 9, no. 3 (September 2010): 370–77. http://dx.doi.org/10.1187/cbe.10-03-0026.

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We describe two sets of courses designed to enhance the mathematical, statistical, and computational training of life science undergraduates at Emory College. The first course is an introductory sequence in differential and integral calculus, modeling with differential equations, probability, and inferential statistics. The second is an upper-division course in computational neuroscience. We provide a description of each course, detailed syllabi, examples of content, and a brief discussion of the main issues encountered in developing and offering the courses.
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Field, Thomas A., Eric T. Beeson, Chad Luke, Michelle Ghoston, and Nedeljko Golubovic. "Counselors' Neuroscience Conceptualizations of Depression." Journal of Mental Health Counseling 41, no. 3 (July 1, 2019): 260–79. http://dx.doi.org/10.17744/mehc.41.3.05.

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The authors conducted the first-ever study into counselor conceptualization of client problems using neuroscience theories. The authors selected an embedded mixed-methods design. Participants (N = 334) provided quantitative demographic information and responded to an open-ended qualitative question regarding a hypothetical situation of a client asking the counselor to explain depression from a neuroscience perspective. The authors coded, tallied, and transformed qualitative responses to quantitative data via frequency counts. Kappa coefficients for the coding team exceeded the threshold for acceptable reliability. Approximately half of the counselors applied neuroscience theories to explain client experiences of depression (57.7%, n = 194), and some counselors integrated multiple neuroscience theories in their response (23.2%, n = 45). The monoamine and neuroplasticity theories were the two most common neuroscience theories for depression. Implications for research and training are discussed.
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Bloomingdale, Peter, Tatiana Karelina, Murat Cirit, Sarah F. Muldoon, Justin Baker, William J. McCarty, Hugo Geerts, and Sreeraj Macha. "Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies." CPT: Pharmacometrics & Systems Pharmacology 10, no. 5 (March 29, 2021): 412–19. http://dx.doi.org/10.1002/psp4.12607.

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Zinchuk, Vadim, and Olga Grossenbacher-Zinchuk. "Recent advances in quantitative colocalization analysis: Focus on neuroscience." Progress in Histochemistry and Cytochemistry 44, no. 3 (October 2009): 125–72. http://dx.doi.org/10.1016/j.proghi.2009.03.001.

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Cofré, Rodrigo, Cesar Maldonado, and Bruno Cessac. "Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics." Entropy 22, no. 11 (November 23, 2020): 1330. http://dx.doi.org/10.3390/e22111330.

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The Thermodynamic Formalism provides a rigorous mathematical framework for studying quantitative and qualitative aspects of dynamical systems. At its core, there is a variational principle that corresponds, in its simplest form, to the Maximum Entropy principle. It is used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of science. In particular, it has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, in order to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.
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Cherniak, Christopher. "The Bounded Brain: Toward Quantitative Neuroanatomy." Journal of Cognitive Neuroscience 2, no. 1 (January 1990): 58–68. http://dx.doi.org/10.1162/jocn.1990.2.1.58.

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An idea that human cognitive resources are virtually without limit turns up at all levels of mind/brain science. This tacit unbounded-resource assumption has paradoxical consequences in neuroscience, particularly involving the quantitative incoherence of some key anatomical studies of cortical connectivity resources: cortical sheet area, synaptic density there, and giant axonic arborizations in visual cortex. This inattention to quantitative consistency checking in neuroanatomy appears to stem from, as a notable instance, something of the nonspatial character of the Cartesian concept of mind being extended to the brain as physical structure.
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Dissertations / Theses on the topic "Quantitative Neuroscience"

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Ganau, Mario. "Nanotechnology Applications in Quantitative Neuroscience: Proteomic Analysis of Malignant Gliomas." Doctoral thesis, Università degli studi di Trieste, 2013. http://hdl.handle.net/10077/8575.

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2011/2012
Abstract (English) The current limit of knowledge advancement in proteomic analysis of gliomas, the most common primary malignant brain tumors, is related to the high sensitivity required to detect specific biomarkers within few cells volumes. To address this problem we developed a quantitative approach to eventually enable precise, high throughput and low cost analysis of glial cells with potential capability of real-time pathological screening and subtyping of brain tumors. A device consisting in micro-fabricated wells capable to isolate and host living astrocytes was designed and functionalized. Then for the fabrication of a nanobiosensor, able to detect in small volumes the presence of specific biomarkers, ideally for multiplexing assays and meant to fit within the small dimensions of this microdevice, an approach consisting in DNA-directed-immobilization (DDI) of biotinylated antibodies (Abs) on a single stranded DNA (ssDNA) nanoarray, produced by Atomic Force Microscopy (AFM) nanografting, was carefully optimized. The proof of concept was realized with Abs specific for Glial Fibrillary Acidic Protein (GFAP), a biomarker which belongs to the family of intermediate filaments and is crucial in cell’s differentiation, within a platform ready for parallelization. Nanosized patches of thiol modified ssDNA were prepared by AFM-based nanografting inside a matrix of self assembled monolayers (SAM) of alkanethiol-modified gold surfaces. Subsequently a complementary DNA strand (cDNA) conjugated to streptavidin (STV) was allowed to covalently bind to the patch by sequence specific DNA hybridization. Finally the biotin binding sites of STV were exploited to immobilize biotinylated monoclonal GFAP Abs (already in use for ELISA assays) on the top of those nanopatches. The efficiency of those nano-immuno arrays was tested by successfully obtaining the immobilization of purified recombinant GFAP protein, down to a concentration of 4 nM, firstly in standard PBS then in multicells’ lysate obtained from U87 glial cultures. The immobilization was detected by means of AFM measuring step by step the increases in the height of the patches and excluding modification of the roughness of both the SAM and the nanopatches after incubation with the cells’ lysate through a signal to noise ratio analysis. Titration curves for a comparison of sensitivity between this technique and the conventional ELISA assays are provided, they indeed confirm that the sensitivity of our nanosensors is at least that of ELISA, with the advantage of the scalability of the device.
Abstract (Italiano) L’attuale limite di avanzamento dello stato dell’arte dell’analisi proteomica dei gliomi cerebrali, la classe istologica di tumori cerebrali più frequente ed aggressiva, è legato alla difficoltà di individuare specifici biomarkers in piccoli volumi cellulari. Per superare questo limite si è deciso di sviluppare un approccio nanoquantitativo che consenta un’analisi proteomica precisa, ad alta sensibilità e basso costo, degli astrociti tumorali, con potenzialità di screening in tempo reale e sottotipizzazione di tumori cerebrali. Previa fabbricazione e funzionalizzazione di micro pozzetti idonei ad ospitare cellule astrocitarie, ci si è dedicati alla realizzazione di biosensori in grado di riconoscere specifici biomarkers e di essere accoppiati ai micro pozzetti. Al fine di immobilizzare anticorpi specifici per proteine di interesse in ambito neuroncologico, è stato scelto un approccio basato sul nanografting con Microscopio a Forza Atomica (AFM) e sull’immobilizzazione diretta sul DNA di anticorpi (DDI). In particolare la prova concettuale è stata condotta con anticorpi specifici per la Glial Fibrillary Acidic Protein (GFAP), un marcatore della differenziazione astrocitaria appartenente alla famiglia dei filamenti intermedi intracellulari, su una piattaforma atta ad una successiva parallelizzazione. I nanocostrutti responsabili del riconoscimento della proteina d’interesse, sono stati realizzati partendo da molecole di DNA a singola elica (ssDNA) graftate in una matrice di monostrati autoassemblati (SAM) di superfici d’oro alchiltiolo modificato. Al fine di sfruttare la capacità della streptavidina (STV) di legarsi ad anticorpi biotinilati è stata successivamente indotta l’ibridazione di un filamento di DNA complementare (cDNA) a quello precedentemente immobilizzato sulla superficie nanoassemblata che presentasse anche una coda di STV. I siti di legame per la biotina intrinseci al tetramero di STV sono quindi stati sfruttati per immobilizzare sulla superficie dei nanocostrutti degli anticorpi monoclonali biotinilati specifici per GFAP (già in uso per i protocolli ELISA). L’efficienza dei nano-immuno costrutti così ottenuti è stata testata ottenendo l’immobilizzazione di GFAP ricombinante anche a basse concentrazioni (fino a 4nM), sia in presenza di standard PBS, sia in presenza di un lisato multicellulare ottenuto da colture gliali di cellule U87. L’immobilizzazione di GFAP è stata confermata dall’incremento in altezza dei nanocostrutti misurato all’AFM escludendo modificazioni del rapporto segnale/rumore sia del SAM che dei nanocostrutti prima e dopo aggiunta di lisato multicellulare. Il limite di sensibilità del prototipo così ottenuto è stato confrontato con quello raggiungibile con protocolli standard ELISA, mostrando una sensibilità almeno comparabile all’ELISA a fronte di un maggiore potenziale diagnostico legato alla sua scalabilità.
XXV Ciclo
1979
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Yan, Haiyan. "Quantitative EEG changes in excessive daytime sleepiness." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0017/MQ57169.pdf.

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Coletta, Annette Lisa. "A Quantitative Assessment of Empathy After an Art Prime with Counseling Students." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6717.

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Empathy skills are necessary to form therapeutic relationships. Previous research showed that participating in the arts engaged similar neuropathways as those needed to produce empathy. The theoretical framework for this study was art therapy relational neuroscience. The purpose of this pretest, posttest quantitative research study, using the Toronto Empathy Questionnaire, was to examine if a single art session could effectively prime for empathy. Using nonprobability, convenience sampling method, 74 graduate counseling students completed online surveys. Four findings are of note: (a) a t-test showed a significant difference between mean values of pre-post test scores, (b) an independent groups t-test indicated no difference in empathy gain scores as related to gender, (c) a Pearson's correlation indicated that age and art experience were positively correlated to empathy gain scores, (d) a multiple regression indicated that none of the variables examined moderated each other or empathy. Age, and art experience, independently, were found to be positively correlated with empathy scores. The results suggest that the self-conducted art session could enhance empathy. This research is an important contribution to the existing literature and enhances social change by studying a previously underrepresented population and investigating the possible effectiveness of a single art session prime for empathy. Using art to enhance empathy in graduate counseling students may aid with securing graduation, licensure, and therapeutic alliances with future clients.
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Munoz, Maniega Susana. "Diffusion tensor MRI of human ischaemic stroke : quantitative measurements, acquisition and registration issues." Thesis, University of Edinburgh, 2007. http://hdl.handle.net/1842/1955.

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The value of diffusion-weighted magnetic resonance imaging (DW-MRI) for early diagnosis of human ischaemic stroke has triggered the rapid development of this imaging technique. The introduction of the diffusion tensor (DT) model provides a range of tools that permit the quantitative assessment of this and many other neurological disorders. This thesis addresses some of the methodological issues encountered when using DT-MRI to image acute stroke patients.
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Segerdahl, Andrew Reilly. "Investigation of the neural correlates of ongoing pain states using quantitative perfusion arterial spin labelling." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:e55cc4a1-cbd3-477d-a7c2-0935349914f1.

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At present, there are few clinically effective pain therapies available to treat chronic pain. One reason is due to a lack of understanding about how pain emerges in the brain. Excitingly, an emerging body of work suggests that the perfusion imaging technique, arterial spin labelling (ASL), is particularly well-suited to investigate this issue. The primary aim of this thesis is to develop and optimise a quantitative perfusion imaging approach to investigate the neural correlates of both experimental and pathological tonic pain. In Chapter 2, we explore different methods of inducing ongoing pain in healthy subjects. Results from this study show that mechanically induced pain is well suited for use in ASL FMRI experiments. In Chapter 3, we compare currently available ASL FMRI approaches for investigating tonic states, using a range of sensory paradigms. Results from these experiments support the use of an optimised version of Continuous ASL (CASL) FMRI to obtain whole-brain perfusion. Additionally, we discuss our decision to proceed with the newly acquired pseudo-continuous ASL (pCASL); a novel ASL technique that benefits from maximal signal-to-noise (SNR) across a whole-brain volume. In Chapter 4 we implement the pCASL FMRI approach to image the neural correlates of ongoing experimental pain. Results from the investigation of parametrically modulated ongoing mechanical pain show robust pain-related activation of key pain related regions that are monotonically active with an increase in stimulus intensity. Additionally, data from this experiment shows the presence of complex perfusion dynamics relative to pain worthy of further study. In Chapter 5, we optimised the pCASL sequence to obtain absolute perfusion changes across the whole-brain volume, using multi-inversion times, so that we could investigate the perfusion dynamics observed in Chapter 4. Results show that absolute perfusion changes during tonic pain are considerably less than for regions recruited during a non- pain task. Additionally, dynamic perfusion changes show complex stimulus responses across all active regions regardless of stimulus type. We conclude that while the technique is well suited to quantify absolute perfusion, the mechanisms underlying the dynamic changes in CBF (neuronal signal, neurovascular coupling) need further study. Finally, in Chapter 6, we implement the absolute perfusion approach developed in Chaper 5 to interrogate the neural correlates of the genetic pain disease, Erythromelalgia, and pleasurable relief. The results of this study show pain-related activation (and relief-induced reduction) of key pain-related regions. We conclude from these results that the ASL technique developed over the course of this thesis can be used to study a range of pain pathologies. Taken together, the results of this thesis document the development of a powerful perfusion imaging technique capable of quantifying absolute perfusion changes across a whole-brain volume. The data presented here from investigations of both experimental and pathological pain states supports the use of this technique in future tonic pain studies, as well as other neuroscience applications. We are confident that implementation of this imaging approach will provide integral insight into the mechanisms of ongoing pain states; and further the development of novel efficacious pain treatment options.
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Lancione, Marta. "Structural and functional neuroimaging using quantitative susceptibility mapping and ultra-high field magnetic resonance imaging." Thesis, IMT Alti Studi Lucca, 2021. http://e-theses.imtlucca.it/339/1/Lancione_phdthesis.pdf.

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In the last decade, Quantitative Susceptibility Mapping (QSM) has been proven a promising Magnetic Resonance Imaging (MRI) tool for the non-invasive quantification of clinically relevant biomarkers, such as iron stores and myelination. The relative simplicity of QSM implementation, which does not require dedicated hardware or acquisition sequence, and its validation with histological evidence favored the diffusion of this technique in the clinical practice, particularly in the diagnosis and follow-up of neurodegenerative diseases. In this thesis, we discussed a critical issue affecting quantification, namely the dependence on acquisition parameters, and its implications for clinical and fundamental research. Specifically, we investigated QSM potential in the study of synucleinopathies, that is a group of neurodegenerative disorders including Multiple System Atrophy (MSA) and Parkinson’s disease (PD), and its capability of detecting brain function via functional QSM (fQSM). As a first step, we assessed how TE-dependence affects QSM intra- and inter-scanner reproducibility by performing repeated measurements on the same participants acquired with both a 3T and a 7T scanner. Then, we explored the impact of TE on the diagnostic accuracy of this technique by acquiring multi-echo data at 7T on MSA patients with Parkinsonian and cerebellar phenotypes and a group of Healthy Controls (HC). In this study, we also assessed the potential of histogram analysis in enhancing QSM diagnostic power. In a third work, we aimed to identify a presymptomatic biomarker in patients at risk for synucleinopathies using 7T QSM. Specifically, we measured and compared iron deposition in nigrosome 1 (a small ovoid-shaped structure located within the dorsolateral portion of the Substantia Nigra pars compacta (SNc)) of PD, idiopathic Rapid Eye Movement (REM) sleep Behavior Disorder (iRBD) patients and HC. Finally, we implemented fQSM and explored its potential compared to fMRI using xii 7T MRI, a stimulation paradigm for tonotopic mapping, and univariate and multivariate analysis approaches. Overall, these studies emphasize the importance of QSM in both structural and functional studies and prove that QSM is a versatile and powerful tool for a wide range of neuroimaging applications.
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Masri, Rania. "Neurons of the primate retina: A qualitative and quantitative analysis." Thesis, The University of Sydney, 2019. http://hdl.handle.net/2123/21165.

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Parallel processing begins in the retina, where input from photoreceptors is transmitted to 12 types of bipolar cell. Bipolar cells are interneurons that propagate visual signals to over 17 types of ganglion cell, which are output neurons of the retina. In this way various vertical pathways are formed that deliver different sensory signals to the brain. This thesis comprises a detailed map of the cell types that contribute to parallel processing in primate retina. Chapter 1 introduces the structure of the primate retina and describes the morphology of retinal cells and their contribution to visual processing. Chapter 2 provides a survey of ganglion cell types in marmoset retina. Ganglion cells were transfected with a plasmid for the expression of a synaptic marker conjugated to green fluorescent protein. At least 17 morphological types of ganglion cell were identified. The contribution of widefield ganglion cells is greater to peripheral than to foveal vision, whereas the fovea is dominated by midget and parasol cells. Outside the fovea ganglion cell diversity in marmoset retina is likely as great as that reported for non-primates. In Chapter 3 particle-mediated gene transfection was applied to post mortem human retina. Human retinas maintained their morphology and immunohistochemical properties for at least 3 days in culture. This study showed that gene transfection can be used to target cells in the human retina, with the potential to study their connectivity and structural changes in diseases. Chapter 4 provides a quantitative analysis of the major cell populations in the inner nuclear layer (INL) of normal human retina. Immunohistochemical markers were applied to vertical sections to label and quantify horizontal, bipolar, amacrine and Müller cells across the retina. Cone photoreceptors and ganglion cells were also counted. With the exception of the fovea, the proportion of different cell populations in the INL is comparable across all eccentricities and comparable to non-human primates and other mammals. The cone to cone bipolar cell ratio was constant across the retina suggesting that convergence and divergence do not change with eccentricity. The data provided in this thesis will serve as a reference for the interpretation of abnormalities in disease, and the informed targeting of treatments in human retinas.
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Tziortzi, Andri. "Quantitative dopamine imaging in humans using magnetic resonance and positron emission tomography." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:26b8b4c2-0237-4c40-8c84-9ae818a0dabf.

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Dopamine is an important neurotransmitter that is involved in several human functions such as reward, cognition, emotions and movement. Abnormalities of the neurotransmitter itself, or the dopamine receptors through which it exerts its actions, contribute to a wide range of psychiatric and neurological disorders such as Parkinson’s disease and schizophrenia. Thus far, despite the great interest and extensive research, the exact role of dopamine and the causalities of dopamine related disorders are not fully understood. Here we have developed multimodal imaging methods, to investigate the release of dopamine and the distribution of the dopamine D2-like receptor family in-vivo in healthy humans. We use the [11C]PHNO PET ligand, which enables exploration of dopamine-related parameters in striatal regions, and for the first time in extrastriatal regions, that are known to be associated with distinctive functions and disorders. Our methods involve robust approaches for the manual and automated delineation of these brain regions, in terms of structural and functional organisation, using information from structural and diffusion MRI images. These data have been combined with [11C]PHNO PET data for quantitative dopamine imaging. Our investigation has revealed the distribution and the relative density of the D3R and D2R sites of the dopamine D2-like receptor family, in healthy humans. In addition, we have demonstrated that the release of dopamine has a functional rather than a structural specificity and that the relative densities of the D3R and D2R sites do not drive this specificity. We have also shown that the dopamine D3R receptor is primarily distributed in regions that have a central role in reward and addiction. A finding that supports theories that assigns a primarily limbic role to the D3R.
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Hengenius, James B. "Quantitative modeling of spatiotemporal systems| Simulation of biological systems and analysis of error metric effects on model fitting." Thesis, Purdue University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3687049.

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Understanding the biophysical processes underlying biological and biotechnological processes is a prerequisite for therapeutic treatments and technological innovation. With the exponential growth of computational processing speed, experimental findings in these fields have been complemented by dynamic simulations of developmental signaling and genetic interactions. Models provide means to evaluate "emergent" properties of systems sometimes inaccessible by reductionist approaches, making them test beds for biological inference and technological refinement.

The complexity and interconnectedness of biological processes pose special challenges to modelers; biological models typically possess a large number of unknown parameters relative to their counterparts in other physical sciences. Estimating these parameter values requires iterative testing of parameter values to find values that produce low error between model and data. This is a task whose length grows exponentially with the number of unknown parameters. Many biological systems require spatial representation (i.e., they are not well-mixed systems and change over space and time). Adding spatial dimensions complicates parameter estimation by increasing computational time for each model evaluation. Defining error for model-data comparison is also complicated on spatial domains. Different metrics compare different features of data and simulation, and the desired features are dependent on the underlying research question.

This dissertation documents the modeling, parameter estimation, and simulation of two spatiotemporal modeling studies. Each study addresses an unanswered research question in the respective experimental system. The former is a 3D model of a nanoscale amperometric glucose biosensor; the model was used to optimize the sensor's design for improved sensitivity to glucose. The latter is a 3D model of the developmental gap gene system that helps establish the bodyplan of Drosophila melanogaster; I wished to determine if the embryo's geometry alone was capable of accounting for observed spatial distributions of gap gene products and to infer feasible genetic regulatory networks (GRNs) via parameter estimation of the GRN interaction terms. Simulation of the biosensor successfully predicted an optimal electrode density on the biosensor surface, allowing us to fabricate improved biosensors. Simulation of the gap gene system on 1D and 3D embryonic demonstrated that geometric effects were insufficient to produce observed distributions when simulated with previously reported GRNs. Noting the effects of the error definition on the outcome of parameter estimation, I conclude with a characterization of assorted error definitions (objective functions), describe data characteristics to which they are sensitive, and end with a suggested procedure for objective function selection. Choice of objective function is important in parameter estimation of spatiotemporal system models in varied biological and biotechnological disciplines.

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Mumuni, Abdul Nashirudeen. "Investigation of brain tissue water NMR response by optimised quantitative single-voxel proton magnetic resonance spectroscopy." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4717/.

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Nuclear Magnetic Resonance (NMR) is a phenomenon in which certain nuclei in the presence of a magnetic field and radiofrequency (RF) radiation emit a certain amount of signal at a frequency equal to that of the RF radiation. Proton Magnetic Resonance Spectroscopy (1H-MRS) is an NMR technique capable of measuring the chemical composition, often referred to as metabolites, of the human body non-invasively and in vivo. It is commonly used as a research tool in the investigation of neurological disorders such as multiple sclerosis, brain tumors, stroke, clinical depression, and schizophrenia. Accurate quantification of the metabolites of interest requires a reference standard of known and fixed concentration. Brain tissue water has been previously reported to have a fairly constant and known concentration, and so has been suggested to be a suitable reference concentration in absolute quantitative 1H-MRS of the human brain. In practice, however, it is challenging to measure the actual tissue water concentration; hence, some studies choose to use estimates of tissue water concentration from the literature. These literature values are usually averages from a healthy study group. There are however indications that brain tissue water content could vary widely in certain disease conditions such as in brain tumors and inflammation. In such situations, absolute metabolite quantification using the literature estimates of tissue water content will be inaccurate while the measurement of cerebral water content using the available techniques will be impractical for the patients due to scanning time considerations. It is therefore necessary to develop a technique that can be used to quantify both the reference water and metabolite concentrations, simultaneously without subject tolerance issues. The main objective of this thesis was to investigate the response of water NMR signal from human brain tissue under various measurement conditions using the single-voxel 1H-MRS technique. As part of the investigation, the thesis also focused on the development of methods for the absolute quantification of cerebral water and metabolite concentrations. A standard 1H-MRS water-suppressed acquisition on the General Electric (GE) MR scanner acquires some unsuppressed-water spectra at the beginning of the PRESS pulse sequence. Using the Spectroscopy Analysis by GE (SAGE) software package (version 7), this thesis developed methods to optimise the unsuppressed-water and suppressed-water signals from which, respectively, cerebral water and metabolite concentrations were estimated. The unsuppressed-water signal response characteristics were investigated in experiments at 3 T that involved: 1) variation of the MRS voxel position over a three-dimensional RF field within an eight-channel head coil; 2) measurement of the relaxation times of brain tissue water using standard saturation recovery and multi spin-echo MRS techniques; 3) measurement of brain tissue water content in peripheral inflammation; and 4) estimation of the BOLD effect on the water spectral peak. The stability of the MR scanner used for all the investigations was assessed. Over the project period, the worst precision measurements of the scanner (for both water and metabolite signals) were observed to be about 12 % and 26 % in serial phantom and human studies, respectively. The MRI/MRS scanner was therefore found to measure water and metabolite signals with good precision, both in vivo and in vitro. By recording the water NMR signal responses at various locations within the phased-array head coil, RF sensitivity profile (voxel position-dependent) equations of the head coil were obtained. The coordinates of any in vivo voxel could be substituted into an appropriate profile equation to estimate an unsuppressed-water signal area that could be used as a reference signal to quantify brain tissue water content. This novel technique of quantifying cerebral water content is superior to the previous techniques of performing multi-echo unsuppressed-water signal acquisitions. The method does not require extra unsuppressed-water acquisitions, or corrections for variations in the sensitivity of the eight-channel head coil as both the in vivo and reference signals are acquired from the same voxel position. Brain tissue water content was subsequently quantified accurately using the newly developed method of referencing. In frontal brain voxels, the average water content, WC of grey matter, GM was found to be higher than that of white matter, WM (GM/WM WC ± SE = 46.37 ± 2.58/42.86 ± 2.46 mol/kg; p = 0.02); parietal voxels also showed a similar comparison (GM/WM WC ± SE = 37.23 ± 1.70/34.14 ± 2.02 mol/kg; p = 0.03). These findings were consistent with previous reports of cerebral water content. For regions of mixed proportions of grey and white matter tissues, the average water contents of each tissue type considered separately (by voxel segmentation) and together were found to compare with literature estimates. Using data from five voxel positions, average brain tissue water content was observed to be uniformly distributed across the human brain by one-way ANOVA (p = 0.60), and did not vary significantly with gender (p > 0.05) and age (p > 0.05). For the first time, cerebral water content was observed in this thesis to remain fairly constant in psoriatic arthritis, a peripheral inflammatory condition (one-way ANOVA, p = 0.63). Among five brain metabolites quantified in the psoriasis patients, only the mean concentration of creatine, Cr was found to be significantly lower in the frontal grey matter voxels of the patients, PsA compared to healthy controls, HC at baseline (PsA/HC ± SE = 6.34 ± 0.38/7.78 ± 0.38 mM/kg; p = 0.01) and post-TNF-alpha blockade medication (PsA/HC ± SE = 6.69 ± 0.25/7.78 ± 0.38 mM/kg; p = 0.03). None of the metabolite concentrations, including Cr (p = 0.27), changed significantly with medication. The condition of PsA was not observed to affect the mood of the patients, as indicated by their BDI scores. The significant finding of Cr concentration alteration in psoriatic arthritis thus suggests that Cr may not be a reliable denominator in studies of psoriasis that express the metabolite levels as ratios. The T1 and T2 relaxation times of water and the metabolites were measured in the prefrontal grey matter (T1/T2 ± SE = 1574 ± 61/147 ± 6 ms) and bilateral Hippocampi (T1/T2 ± SE; left = 1475 ± 68/178 ± 83 ms, right = 1389 ± 58/273 ± 98 ms). The relaxation time estimates for the metabolites were in agreement with literature values; relaxation times for water however were measured for the first time in those regions and at 3 T. The measured relaxation times were used to correct the water and metabolite signals for relaxation effects during their absolute quantification, and could as well serve the same purpose in future studies. There is increasing interest in the BOLD response of cerebral metabolites and water during tasks. This thesis thus also assessed changes in brain tissue metabolite and water contents while a subject experienced a visual stimulus. In the presence of the visual stimulus, the BOLD effects on the metabolite and water spectral peaks were found to be comparable, as has been observed in previous studies. For the first time, this thesis further investigated the impact of temporal resolution (determined by NEX) on the amount of the BOLD signal acquired from cerebral water and metabolites. In a single visual activation paradigm, the BOLD effect resulted in increased water peak area which differed significantly between NEX values of 2 and 8 (p < 0.01); this observation also was true for NAA and Glu. The findings thus suggest that temporal resolution of the MRS data could result in significant differences in the results of functional MRS studies.
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Books on the topic "Quantitative Neuroscience"

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Pardalos, P. M., J. C. Sackellares, P. R. Carney, and L. D. Iasemidis, eds. Quantitative Neuroscience. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4613-0225-4.

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Ellis, Carson Richard, Daube-Witherspoon Margaret E, and Herscovitch Peter, eds. Quantitative functional brain imaging with positron emission tomography. San Diego, Calif: Academic Press, 1998.

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Tranquillo, Joseph Vincent. Quantitative neurophysiology. San Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2008.

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Plonsey, Robert. Bioelectricity: A Quantitative Approach. Boston, MA: Springer US, 2000.

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Habib, Zaidi, ed. Quantitative analysis of nuclear medicine images. New York: Springer, 2005.

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Evans, Stephen M., Ann Marie Janson, and Jens Randel Nyengaard. Quantitative Methods in Neuroscience: A Neuroanatomical Approach. Oxford University Press, 2004.

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(Editor), Stephen M. Evans, Ann Marie Janson (Editor), and Jens Randel Nyengaard (Editor), eds. Quantitative Methods in Neuroscience: A Neuroanatomical Approach. Oxford University Press, USA, 2004.

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Quantitative neuroscience: Models, algorithms, diagnostics, and therapeutic applications. Boston: Kluwer Academic, 2004.

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Pardalos, P. M. Quantitative Neuroscience: Models, Algorithms, Diagnostics, and Therapeutic Applications. Springer, 2011.

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Pardalos, P. M. Quantitative Neuroscience: Models, Algorithms, Diagnostics, and Therapeutic Applications. Springer London, Limited, 2013.

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Book chapters on the topic "Quantitative Neuroscience"

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Thomassen, Arnold J. W. M., and Hein J. C. M. Tibosch. "A Quantitative Model of Graphic Production." In Tutorials in Motor Neuroscience, 269–81. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3626-6_22.

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Zornoza, Teodoro, María José Cano-Cebrián, Ana Polache, and Luis Granero. "Quantitative In Vivo Microdialysis in Pharmacokinetic Studies." In Microdialysis Techniques in Neuroscience, 103–20. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-62703-173-8_6.

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Mizusawa, Hidehiro. "Prism Adaptation Test (PAT): A Practical and Quantitative Method to Evaluate Cerebellar Function." In Contemporary Clinical Neuroscience, 445–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75817-2_22.

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Asherson, Philip, and Hugh Gurling. "Quantitative and Molecular Genetics of ADHD." In Behavioral Neuroscience of Attention Deficit Hyperactivity Disorder and Its Treatment, 239–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/7854_2011_155.

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Milošević, Nebojša. "The Morphology of the Brain Neurons: Box-Counting Method in Quantitative Analysis of 2D Image." In Springer Series in Computational Neuroscience, 109–26. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3995-4_7.

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Haralanov, Svetlozar, Evelina Haralanova, Emil Milushev, and Diana Shkodrova. "Locomotor Movement-Pattern Analysis as an Individualized Objective and Quantitative Approach in Psychiatry and Psychopharmacology: Clinical and Theoretical Implications." In Psychiatry and Neuroscience Update, 387–416. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95360-1_32.

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Wang, Yue-Ting, Sujeewa C. Piyankarage, and Gregory R. J. Thatcher. "Quantitative Profiling of Reversible Cysteome Modification Under Nitrosative Stress." In Analysis of Post-Translational Modifications and Proteolysis in Neuroscience, 55–72. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/7657_2015_88.

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Biercewicz, Konrad, and Mariusz Borawski. "Examining the Degree of Engagement of a Participant in Economic Games Using Cognitive Neuroscience Techniques." In Experimental and Quantitative Methods in Contemporary Economics, 201–16. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30251-1_15.

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Cottrell, Marie, and Patrick Rousset. "The Kohonen algorithm: A powerful tool for analysing and representing multidimensional quantitative and qualitative data." In Biological and Artificial Computation: From Neuroscience to Technology, 861–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0032546.

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Kager, Klara. "Language Aptitude in Relation to Handedness, Hemispheric Dominance, Cognitive Learning Strategies and Non-verbal IQ: A Combined Quantitative and Qualitative Study." In Exploring Language Aptitude: Views from Psychology, the Language Sciences, and Cognitive Neuroscience, 167–93. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91917-1_9.

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Conference papers on the topic "Quantitative Neuroscience"

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Saha Roy, Tiasha, Jesse Breedlove, Ghislain St-Yves, Kendrick Kay, and Thomas Naselaris. "Quantitative comparison of imagery and perception." In 2022 Conference on Cognitive Computational Neuroscience. San Francisco, California, USA: Cognitive Computational Neuroscience, 2022. http://dx.doi.org/10.32470/ccn.2022.1310-0.

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Thorburn, Craig, Naomi Feldman, and Thomas Schatz. "A quantitative model of the language familiarity effect in infancy." In 2019 Conference on Cognitive Computational Neuroscience. Brentwood, Tennessee, USA: Cognitive Computational Neuroscience, 2019. http://dx.doi.org/10.32470/ccn.2019.1353-0.

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Rajalingham, Rishi, Hyodong Lee, and James J. DiCarlo. "Selective behavioral deficits from focal inactivation of primate inferior temporal (IT) cortex: a new quantitative constraint for models of core object recognition." In 2018 Conference on Cognitive Computational Neuroscience. Brentwood, Tennessee, USA: Cognitive Computational Neuroscience, 2018. http://dx.doi.org/10.32470/ccn.2018.1056-0.

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Klimenkov, Igor, Nikolai Sudakov, Mikhail Pastukhov, Mikhail Svinov, and Nikolai Kositsyn. "QUANTITATIVE INDICATORS OF STIMULUSDEPENDENT APOPTOSIS AND PROLIFERATION OF CELLS IN THE OLFACTORY EPITHELIUM IN FISH." In XIV International interdisciplinary congress "Neuroscience for Medicine and Psychology". LLC MAKS Press, 2018. http://dx.doi.org/10.29003/m186.sudak.ns2018-14/249-250.

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Harahap, Iskandar Azmy, Abdullah Rasyid,, and Masteria Yunovilsa Putra. "Estimation of quantitative risk assessment of dietary exposure to lead (Pb) from sea cucumbers in Indonesia." In THE FIRST INTERNATIONAL CONFERENCE ON NEUROSCIENCE AND LEARNING TECHNOLOGY (ICONSATIN 2021). AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0118424.

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Vasilyeva, Valentina, and Nina Shumeyko. "QUANTITATIVE CHANGES IN THE FIBROUS STRUCTURES OF THE VISUAL AND MOTOR AREAS OF THE CEREBRAL CORTEX OF CHILDREN FROM BIRTH TO 7 YEARS." In XVIII INTERNATIONAL INTERDISCIPLINARY CONGRESS NEUROSCIENCE FOR MEDICINE AND PSYCHOLOGY. LCC MAKS Press, 2022. http://dx.doi.org/10.29003/m2705.sudak.ns2022-18/87-88.

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M. Bahgat, Mohamed, Ashraf Elsafty, and Ashraf Shaarawy. "Validating the Impact of FIRST as a New Learner Experience Framework for Teachers Professional Development." In International Conference on Education. The International Institute of Knowledge Management, 2020. http://dx.doi.org/10.17501/24246700.2020.6204.

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Teachers’ Professional Development ‘TPD’ has always been an area of growing interest in educational research. Several researchers have thoroughly explored the TPD domain aiming to develop and train teachers on how to understand, experience, practice and have a sustainable impact on learners. FIRST (Bahgat et al. 2018) is a new learner experience framework, which consists of five domains; focusing on learner ‘ F’, interacting within group dynamics ‘ I’, reviewing actively ‘R’, structuring and sequencing ‘S’, and transforming learning into performance ‘T’. It is designed based on educational psychology, neuroscience, and cognitive psychology, to create a framework that promotes active deep learning and inspires a positive transformation in mindset and behaviours. FIRST was applied on a TPD program named Roadmap of Outstanding Educators ‘ROOTS’. The participants were one hundred and seven teachers. This paper attempts to explore the impact of FIRST Framework on TPD, teachers experience as learners and teachers motivation to transfer their learning into performance in the classrooms. The study employed exploratory sequential mixed methods design using case study methodology. Qualitative data was analysed and interpreted into codes and themes. Quantitative data was analysed using SPSS. Major findings: (1) Teachers reported that FIRST is comprehensive and compiles various educational theories, models and strategies, they were able to apply the principles and strategies in their classrooms immediately after the professional program days were over, (2) Student’s feedback and overall experience were enhanced, (3) Some schools has adopted FIRST as a learner experience. These findings recommended that teachers should live the TPD experience as learners. The TPD programs should include follow up phase to enhance teachers’ experience and encourage the transfer of learning into performance. Keywords: Active Learning; Deep Learning; Student Experience; Teachers Professional Developmen
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Daube, Christoph, Bruno Giordano, Phillippe Schyns, and Robin Ince. "Quantitatively comparing predictive models with the Partial Information Decomposition." In 2019 Conference on Cognitive Computational Neuroscience. Brentwood, Tennessee, USA: Cognitive Computational Neuroscience, 2019. http://dx.doi.org/10.32470/ccn.2019.1142-0.

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Reports on the topic "Quantitative Neuroscience"

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Semerikov, Serhiy O., Illia O. Teplytskyi, Yuliia V. Yechkalo, and Arnold E. Kiv. Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot. [б. в.], November 2018. http://dx.doi.org/10.31812/123456789/2648.

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The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins and macros. After analyzing a collection of writings of 1890-1950, the research determines the role of the scientific journal “Bulletin of Mathematical Biophysics”, its founder Nicolas Rashevsky and the scientific community around the journal in creating and developing models and methods of computational neuroscience. There are identified psychophysical basics of creating neural networks, mathematical foundations of neural computing and methods of neuroengineering (image recognition, in particular). The role of Walter Pitts in combining the descriptive and quantitative theories of training is discussed. It is shown that to acquire neural simulation competences in the spreadsheet environment, one should master the models based on the historical and genetic approach. It is indicated that there are three groups of models, which are promising in terms of developing corresponding methods – the continuous two-factor model of Rashevsky, the discrete model of McCulloch and Pitts, and the discrete-continuous models of Householder and Landahl.
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Burnett, Cathy. Scoping the field of literacy research: how might a range of research be valuable to primary teachers? Sheffield Hallam University, 2022. http://dx.doi.org/10.7190/shu-working-papers/2201.

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Literacy research has an important role to play in helping to shape educational policy and practice. The field of literacy research however is difficult to navigate as literacy has been understood and researched in many different ways. It encompasses work from psychology, sociology, philosophy and neuroscience, literary theory, media and literacy studies, and methodologies include a range of qualitative, quantitative and mixed methods approaches. In mapping this complex field, I draw on a systematic ‘scoping survey’ of a sample of peerreviewed articles featuring literacy research relevant to literacy education for children aged 5-11. Studies were deemed relevant if they: addressed literacy pedagogies and interventions; and/or provided pertinent insights (e.g. into children’s experiences of literacy); and/or offered implications for the range and scope of literacy education. The results of this survey are important in two ways. Firstly they help to articulate the range of literacy research and the varied ways that such research might speak to literacy education. Secondly they challenge easy distinctions between paradigms in literacy research. Recognising this complexity and heterogeneity matters given the history of relationships between literacy policy and practice in countries such as England, where polarised debate has often erased the subtle differences of perspective and confluence of interest that this survey illuminates. Based on the results of this survey I argue that an inclusive approach to literacy research is needed in educational contexts. Otherwise alternative and/or complementary ways of supporting children’s literacy learning may be missed, as will important possibilities for literacy education and children’s current and future lives.
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