Статті в журналах: "Quantitative Neuroscience"

1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Saravanapandian, Vidya, Erin M. Sparck, Karen Y. Cheng, Fei Yu, Courtney Yaeger, Terry Hu, Nanthia Suthana, et al. "Quantitative assessments reveal improved neuroscience engagement and learning through outreach." Journal of Neuroscience Research 97, no. 9 (April 15, 2019): 1153–62. http://dx.doi.org/10.1002/jnr.24429.

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12

Pierre, Kevin, Vanessa Molina, Shil Shukla, Anthony Avila, Nicholas Fong, Jessica Nguyen, and Brandon Lucke-Wold. "Chronic traumatic encephalopathy: Diagnostic updates and advances." AIMS Neuroscience 9, no. 4 (2022): 519–35. http://dx.doi.org/10.3934/neuroscience.2022030.

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<abstract> Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease that occurs secondary to repetitive mild traumatic brain injury. Current clinical diagnosis relies on symptomatology and structural imaging findings which often vary widely among those with the disease. The gold standard of diagnosis is post-mortem pathological examination. In this review article, we provide a brief introduction to CTE, current diagnostic workup and the promising research on imaging and fluid biomarker diagnostic techniques. For imaging, we discuss quantitative structural analyses, DTI, fMRI, MRS, SWI and PET CT. For fluid biomarkers, we discuss p-tau, TREM2, CCL11, NfL and GFAP. </abstract>

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13

Zanacchi, Francesca Cella. "Quantitative Super-resolution of Synaptic Proteins." iScience Notes 7, no. 7 (December 27, 2022): 1–2. http://dx.doi.org/10.22580/iscinotej7.7.1.

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Single molecule localization microscopy (SMLM) recently became more and more popular for studying the synaptic architecture, providing substantial advances in modern neuroscience. Recently developed methods based on DNA origami calibration transformed SML into an effective quantitative tool able to estimate the oligomeric states of macromolecular complexes. In this work, we apply a recently developed quantitative method based on stochastic optical reconstruction microscopy (qSTORM) to study the distribution of the synaptic proteins Homer in hippocampal neurons. Our experiments prove qSTORM as a suitable tool for novel quantitative insights into the nanoscale organization of excitatory synapses.

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14

Kas, Martien J., Alessandro Serretti, and Hugh Marston. "Quantitative neurosymptomatics: Linking quantitative biology to neuropsychiatry." Neuroscience & Biobehavioral Reviews 97 (February 2019): 1–2. http://dx.doi.org/10.1016/j.neubiorev.2018.11.013.

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15

Tabelow, Karsten, Evelyne Balteau, John Ashburner, Martina F. Callaghan, Bogdan Draganski, Gunther Helms, Ferath Kherif, et al. "hMRI – A toolbox for quantitative MRI in neuroscience and clinical research." NeuroImage 194 (July 2019): 191–210. http://dx.doi.org/10.1016/j.neuroimage.2019.01.029.

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16

Nephew, Benjamin C. "What we can learn from second animal neuroscience." Behavioral and Brain Sciences 36, no. 4 (July 25, 2013): 433–34. http://dx.doi.org/10.1017/s0140525x12002002.

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AbstractThere are several facets of second-person neuroscience which can benefit from comparisons with animal behavioral neuroscience studies. This commentary addresses the challenges involved in obtaining quantitative data from second-person techniques, the role of stress in inducing robust responses, the use of interactive functional magnetic resonance imaging (fMRI), and the value of applying interactive methods to studies of aggression and depression.

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17

Antoniades, Chrystalina A., and Roger H. S. Carpenter. "Making neurology quantitative." NeuroReport 23, no. 9 (June 2012): 572–75. http://dx.doi.org/10.1097/wnr.0b013e32835462f6.

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18

Farmakopoulou, Ignatia, Maria Theodoratou, and Evgenia Gkintoni. "Neuroscience as a Component in Educational Setting. An Interpretive Overview." Technium Education and Humanities 4 (January 6, 2023): 1–7. http://dx.doi.org/10.47577/teh.v4i.8236.

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In recent years, considerable advancements have been made in the field of educational neuroscience research. Researchers commend its existence and influence on educational procedures. This effort was intended to illustrate the educational applications of Neuroscience. In particular, research articles, quantitative and qualitative analyses, meta-analyses, and articles of critical inquiry on Neuroscience in Education were examined. In addition, a review of recent literature was attempted. From these studies, conclusions can be derived that can prove useful in the fields of research and teaching. Thus, best practices, methodologies, perspectives, attitudes, and perceptions that support the significance and value of Neuroscience in the field of education are offered.

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19

Kalogeras, Stavroula, Sami Mejri, and Faidonas Efthimiou. "The Neuroscience of Student Engagement." International Journal of Online Pedagogy and Course Design 12, no. 1 (January 1, 2022): 1–19. http://dx.doi.org/10.4018/ijopcd.311440.

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This paper discusses the findings of cognitive, metacognitive, and emotional implications of narrative instruction. The work guides readers in multiple-case design studies depicting storytelling as effective pedological practice. The collective case approach connects works from education, learning design, neuroscience, narratology, psychology, mathematics, science, and technology. Consideration is given to course design, instruction, student engagement, and aesthetic perspectives. The primary case study highlights storytelling episodes to mirror principles and best practices in course design and course facilitation using Blackboard as a learning platform. Through the frameworks of narrative instruction, students enrolled in online and face-to-face mathematics courses were tasked with completing a financial management project. Of the 160 students who received the survey questionnaire, 45 (28%) have responded. Qualitative and quantitative data analysis using Qualtrics and IBM's SPSS showed that students gained valuable skills in money management and financial literacy.

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20

Hoy, Ronald R. "Quantitative skills in undergraduate neuroscience education in the age of big data." Neuroscience Letters 759 (August 2021): 136074. http://dx.doi.org/10.1016/j.neulet.2021.136074.

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21

Ameer, Madiha, and Muhammad Tanvir Afzal. "Evaluation of h-index and its qualitative and quantitative variants in Neuroscience." Scientometrics 121, no. 2 (August 30, 2019): 653–73. http://dx.doi.org/10.1007/s11192-019-03209-6.

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22

Makarenko, O. M. "THE SUBSTANTIATION OF THE CONCEPT OF GLIOARCHITECTONICS FOR NEUROSCIENCE AND NEUROCYTOPATOLOGY." Актуальні проблеми сучасної медицини: Вісник Української медичної стоматологічної академії 22, no. 2 (September 27, 2022): 112–15. http://dx.doi.org/10.31718/2077-1096.22.2.112.

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The analysis of the structure and functional state of gliocytes enables to characterize the cytological parameters of various brain cell formations, normally, to objectively assess not only the impact on the formation of pathological factors (including their glial cell homeostasis), but also to assess the therapeutic effectiveness of different drugs in managing different CNS pathologies. The aim of this study is to promote the concept of glioarchitectonics for an in-depth and detailed study of the cerebral cortex (neocortex) in normal, experimental and clinical pathology of the central nervous system. This study is based on the analysis of the latest literary sources and the results of the authors' previous research. The system-cellular indicator of the evaluation of the glial formula (GF) characterizes the quantitative (percentage) content of individual cell types (astrocytes, oligodenrocytes, microgliocytes) in relation to the total number of gliocytes in a standard area of a histosection. The glial quantitative index characterizes the ratio of one type of gliocytes to another. In particular, index 1 represents the ratio of the sum of astrocytes to microgliocytes, index 2 represents the sum of oligodendrogliocytes to microgliocytes, and index 3 demonstrates the sum of astrocytes to the total number of oligodendrogliocytes. The use of quantitative methods of analysis in the study of the glial system of various cellular brain structures in health, in disease and after pharmacotherapy of experimental cerebrovascular pathology showed that these methods are sensitive and suitable for solving a number of theoretical and clinical tasks. This study has demonstrated that the analysis of the results of the glial formula and glial quantitative indices contributed to objective analysis of the structure of glia of various cellular brain formations in health in order to improve the parameters of evaluating the relevant histological characteristics. The obtained results can help to carry out not only qualitative, but also quantitative assessment of the impairment of glial homeostasis in various cellular formations of the brain (cerebrocortex, various nuclei of the hypothalamus) when modelling glial indices. The results of the study of glioarchitectonics and system indicators of the evaluation of the glial formula and glial indices of the quantitative glial system contributed to in-depth and detailed understanding of various cellular formations in the brain in health, in disease and after pharmacotherapy of experimental cerebrovascular pathology.

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23

Viding, Essi, Henrik Larsson, and Alice P. Jones. "Quantitative genetic studies of antisocial behaviour." Philosophical Transactions of the Royal Society B: Biological Sciences 363, no. 1503 (April 23, 2008): 2519–27. http://dx.doi.org/10.1098/rstb.2008.0037.

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This paper will broadly review the currently available twin and adoption data on antisocial behaviour (AB). It is argued that quantitative genetic research can make a significant contribution to further the understanding of how AB develops. Genetically informative study designs are particularly useful for investigating several important questions such as whether: the heritability estimates vary as a function of assessment method or gender; the relative importance of genetic and environmental influences varies for different types of AB; the environmental risk factors are truly environmental; and genetic vulnerability influences susceptibility to environmental risk. While the current data are not yet directly translatable for prevention and treatment programmes, quantitative genetic research has concrete translational potential. Quantitative genetic research can supplement neuroscience research in informing about different subtypes of AB, such as AB coupled with callous–unemotional traits. Quantitative genetic research is also important in advancing the understanding of the mechanisms by which environmental risk operates.

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24

Lent, Roberto, Frederico A. C. Azevedo, Carlos H. Andrade-Moraes, and Ana V. O. Pinto. "How many neurons do you have? Some dogmas of quantitative neuroscience under revision." European Journal of Neuroscience 35, no. 1 (December 13, 2011): 1–9. http://dx.doi.org/10.1111/j.1460-9568.2011.07923.x.

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25

Filiou, Michaela D., Daniel Martins-de-Souza, Paul C. Guest, Sabine Bahn, and Christoph W. Turck. "To label or not to label: Applications of quantitative proteomics in neuroscience research." PROTEOMICS 12, no. 4-5 (January 23, 2012): 736–47. http://dx.doi.org/10.1002/pmic.201100350.

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26

Wehner, Jeanne M., Richard A. Radcliffe, and Barbara J. Bowers. "Quantitative Genetics and Mouse Behavior." Annual Review of Neuroscience 24, no. 1 (March 2001): 845–67. http://dx.doi.org/10.1146/annurev.neuro.24.1.845.

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27

Vogel, Edgar H., Marı́a E. Castro, and Marı́a A. Saavedra. "Quantitative models of Pavlovian conditioning." Brain Research Bulletin 63, no. 3 (April 2004): 173–202. http://dx.doi.org/10.1016/j.brainresbull.2004.01.005.

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28

Krauth, J. "Quantitative analysis of recovery curves." Behavioural Brain Research 39, no. 2 (July 1990): 167–85. http://dx.doi.org/10.1016/0166-4328(90)90103-l.

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29

Gołyszny, Miłosz, Michał Zieliński, Monika Paul-Samojedny, Artur Pałasz, and Ewa Obuchowicz. "Chronic treatment with escitalopram and venlafaxine affects the neuropeptide S pathway differently in adult Wistar rats exposed to maternal separation." AIMS Neuroscience 9, no. 3 (2022): 395–422. http://dx.doi.org/10.3934/neuroscience.2022022.

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<abstract> Neuropeptide S (NPS), which is a peptide that is involved in the regulation of the stress response, seems to be relevant to the mechanism of action of antidepressants that have anxiolytic properties. However, to date, there have been no reports regarding the effect of long-term treatment with escitalopram or venlafaxine on the NPS system under stress conditions. This study aimed to investigate the effects of the above-mentioned antidepressants on the NPS system in adult male Wistar rats that were exposed to neonatal maternal separation (MS). Animals were exposed to MS for 360 min. on postnatal days (PNDs) 2–15. MS causes long-lasting behavioral, endocrine and neurochemical consequences that mimic anxiety- and depression-related features. MS and non-stressed rats were given escitalopram or venlafaxine (10mg/kg) IP from PND 69 to 89. The NPS system was analyzed in the brainstem, hypothalamus, amygdala and anterior olfactory nucleus using quantitative RT-PCR and immunohistochemical methods. The NPS system was vulnerable to MS in the brainstem and amygdala. In the brainstem, escitalopram down-regulated NPS and NPS mRNA in the MS rats and induced a tendency to reduce the number of NPS-positive cells in the peri-locus coeruleus. In the MS rats, venlafaxine insignificantly decreased the NPSR mRNA levels in the amygdala and a number of NPSR cells in the basolateral amygdala, and increased the NPS mRNA levels in the hypothalamus. Our data show that the studied antidepressants affect the NPS system differently and preliminarily suggest that the NPS system might partially mediate the pharmacological effects that are induced by these drugs. </abstract>

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30

Sharma, Alok K., James P. Morrison, Deepa B. Rao, Ingrid D. Pardo, Robert H. Garman, and Brad Bolon. "Toxicologic Pathology Analysis for Translational Neuroscience." International Journal of Toxicology 35, no. 4 (March 24, 2016): 410–19. http://dx.doi.org/10.1177/1091581816636372.

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A half-day American College of Toxicology continuing education course presented key issues often confronted by translational neuroscientists when predicting human risk from animal-derived toxicologic pathology data. Two talks correlated discrete structures with major functions in brains of rodents and nonrodents. The third lecture provided practical advice to obtain highly homologous rodent brain sections for quantitative morphometry in developmental neurotoxicity testing. The last presentation discussed demographic influences (eg, species, strain, sex, age), physiological attributes (eg, body composition, brain vascularity, pharmacokinetic/pharmacodynamic patterns, etc), and husbandry parameters (eg, group housing) recognized to impact the actions of neuroactive chemicals. Speakers described common cases of real-world challenges to animal data interpretation encountered when designing studies or extrapolating biological responses across species. The efficiency of translational neuroscience efforts will likely be enhanced as new methods (eg, high-resolution non-invasive imaging) improve our capability to cross-connect subtle anatomic and/or biochemical lesions with functional changes over time.

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31

Wu, Hongkun. "Reinforcement Learning Inspired by Psychology and Neuroscience." Journal of Education, Humanities and Social Sciences 8 (February 7, 2023): 2164–70. http://dx.doi.org/10.54097/ehss.v8i.4673.

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Decision-making is a crucial intelligence shared by animals and humans and it helps them to act in an intricate environment to seek rewards and avoid punishments. Psychologists first became interested in this ability and studied the conditional behavioral problems associated with it, then these studies have further led to the need for unified quantitative explanation models, among which Reinforcement learning is still the most convincing and data-backed model today. The model itself, in turn, facilitates research in neuroscience. In this paper, the researcher first introduces the original framework of reinforcement learning and the potential neural correlates to it. Then the paper reviews new developments in reinforcement learning algorithms that address the limitations of the original model as well as variants further inspired by neuroscience. Finally, the study highlights some new directions for future research. This study focuses on the evolution of reinforcement learning algorithms inspired by neuroscience, shows the relationship of mutual promotion and common development between reinforcement Learning and neuroscience, and clarifies some concerns for future exploration.

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Shen, Francis X. "The Law and Neuroscience Bibliography: Navigating the Emerging Field of Neurolaw†." International Journal of Legal Information 38, no. 3 (2010): 352–99. http://dx.doi.org/10.1017/s0731126500005916.

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In the past five years, we have witnessed extraordinary growth in the amount of legal scholarship, legal practice, and public policy at the intersection of law and neuroscience. For instance, in 2010 the first Daubert hearing was held on the admissibility of functional magnetic resonance imaging (fMRI) lie detection evidence; a Florida court was the first in the nation to admit quantitative encephalography (qEEG) evidence; and a Supreme Court decision on life imprisonment for minors cited brain development research. In France, the Prime Minister established the first Neuroscience and Public Policy program within the France Ministry for Social Affairs, and in the United States, multiple state legislators proposed bills related to neuroscience and law. Academics, too, have taken notice, with a number of symposia being offered around the country over the past few years.

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33

Charalambous, Nicholas, Adrian Goh, Ferenc Los, and Kanch Sharma. "DOES UNDERSTANDING BASIC NEUROSCIENCE CURE NEUROPHOBIA?" Journal of Neurology, Neurosurgery & Psychiatry 86, no. 11 (October 14, 2015): e4.140-e4. http://dx.doi.org/10.1136/jnnp-2015-312379.5.

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IntroductionNeurophobia – ‘a fear of the neural sciences and clinical neurology’1 is an established phenomenon amongst medical students and physicians.1–3 Conclusions from previous studies indicate a need for more neurology teaching,2 3 with basic neuroscience felt to be extremely useful.2 This study examines whether a concise, focused tutorial integrating basic neuroscience with clinical neurology helps overcome neurophobia.MethodsStudents from the University of Bristol (n=56) were surveyed using quantitative and qualitative questions pre/post/1 month after a 15 minute tutorial on neurological examination, integrating the relevant anatomy and physiology with clinical findings.ResultsAnalysis was performed using Wilcoxon signed ranks and Freidman testing. Comparing pre and post surveys there was a statistically significant improvement (p<0.05) in knowledge, confidence and understanding of clinical signs. Importantly this increased confidence persisted when students were re-surveyed 1 month later. Responses to difficulties faced when learning neurology include the following themes (1) complex/overwhelming subject, (2) lack of teaching, (3) inability to correlate neuroanatomy with clinical presentation.ConclusionWhen teaching students (or even clinicians) with “neurophobia”, always commence with a review of basic neuroscience as a foundation on which to build an understanding of neurological function in health and disease.

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34

Palacios, J. M. "Quantitative methods in neuroanatomy." Journal of Chemical Neuroanatomy 6, no. 3 (May 1993): 177. http://dx.doi.org/10.1016/0891-0618(93)90027-2.

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35

Kennedy, W. R., X. Navarro, T. Ferrer, and G. Crabb. "Diabetic neuropathy: Quantitative evaluation." Electroencephalography and Clinical Neurophysiology 87, no. 2 (August 1993): S7—S8. http://dx.doi.org/10.1016/0013-4694(93)90881-u.

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36

Valdes, P., J. L. Hernández, R. Biscay, R. Grave De Peralta, A. Gonzalez, and J. L. Valdes. "Nonlinear quantitative EEG analysis." Electroencephalography and Clinical Neurophysiology 87, no. 2 (August 1993): S135. http://dx.doi.org/10.1016/0013-4694(93)91497-o.

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37

Barnéoud, Pascal, Jocelyne Lolivier, David J. Sanger, Bernard Scatton, and Paul Moser. "Quantitative motor assessment in FALS mice." NeuroReport 8, no. 13 (September 1997): 2861–65. http://dx.doi.org/10.1097/00001756-199709080-00012.

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38

Spear, G. T., J. Caldwell, M. R. Lee, and M. E. Gurney. "Quantitative immunoassay of recombinant murine neuroleukin." Neuroscience 27, no. 1 (October 1988): 41–48. http://dx.doi.org/10.1016/0306-4522(88)90218-7.

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39

Geerts, Hugo, John Wikswo, Piet H. Graaf, Jane P. F. Bai, Chris Gaiteri, David Bennett, Susanne E. Swalley, et al. "Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges." CPT: Pharmacometrics & Systems Pharmacology 9, no. 1 (November 24, 2019): 5–20. http://dx.doi.org/10.1002/psp4.12478.

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40

Baker, John L., and Giorgio A. Ascoli. "Tracking the Source of Quantitative Knowledge in Neuroscience: A Neuroinformatics Role for Computational Models." Neuroinformatics 9, no. 1 (February 8, 2011): 1–2. http://dx.doi.org/10.1007/s12021-011-9100-7.

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Hyder, Fahmeed, and Douglas L. Rothman. "Quantitative fMRI and oxidative neuroenergetics." NeuroImage 62, no. 2 (August 2012): 985–94. http://dx.doi.org/10.1016/j.neuroimage.2012.04.027.

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42

Balla, Dávid Z., Rosa M. Sanchez-Panchuelo, Samuel J. Wharton, Gisela E. Hagberg, Klaus Scheffler, Susan T. Francis, and Richard Bowtell. "Functional quantitative susceptibility mapping (fQSM)." NeuroImage 100 (October 2014): 112–24. http://dx.doi.org/10.1016/j.neuroimage.2014.06.011.

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43

Yazulla, Stephen. "Quantitative Receptor Autoradiography." Neurochemistry International 10, no. 3 (January 1987): 399. http://dx.doi.org/10.1016/0197-0186(87)90116-1.

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44

Wang, Yinying. "Pulling at Your Heartstrings: Examining Four Leadership Approaches From the Neuroscience Perspective." Educational Administration Quarterly 55, no. 2 (September 18, 2018): 328–59. http://dx.doi.org/10.1177/0013161x18799471.

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Purpose: This review study aims to bridge neuroscience and educational leadership by exploring the neural mechanisms of the constructs relevant to educational leadership. Research Methods: The reviewed literature includes 69 neuroscience studies and 4 books on neuroscience. The brain activities and neurotransmitters associated with the constructs pertinent to educational leadership were coded to bridge the knowledge base of neuroscience and educational leadership. Findings: The neural mechanisms of the constructs related to educational leadership (e.g., vision, charisma, trust, and organizational justice) were organized by four different leadership approaches: charismatic, transformational, destructive, and culturally responsive school leadership. Emotions are the common thread weaving through all four leadership approaches. Implications: This study has salient theoretical, methodological, and practical implications for educational leadership. Theoretically, the findings not only accentuate the role of emotions in educational leadership, but also reveal the trade-off between emotions and analytical calculation in leaders’ decision making. Methodologically, the neuroscience methods (e.g., functional magnetic resonance imaging, quantitative electroencephalography, and hormonal analysis) add to the methodological repertoire of educational leadership research. Practically, the findings warrant the emotion training and present the potential of using neurological measurements in school leadership preparation and professional development.

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Zupanc, Günther K. H. "Understanding the Role of Diffusion in Synaptic Transmission through Inquiry-Based Learning & Quantitative Reasoning." American Biology Teacher 81, no. 6 (August 1, 2019): 435–41. http://dx.doi.org/10.1525/abt.2019.81.6.435.

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The elucidation of the principal features of chemical synaptic transmission has been one of the great achievements in the history of neuroscience, yet students have significant difficulties developing a deeper understanding of the underlying concept. This is particularly true for the role that diffusion of neurotransmitters across the synaptic cleft plays in this process. At least part of the learning problem is due to an erroneous view of diffusion as a slow process, and to an inability to apply the concepts of size and scale to the synapse and its structural components. To overcome these difficulties, a structured/guided inquiry activity, combined with quantitative reasoning tasks, is described for teaching chemical synaptic transmission as part of undergraduate biology or neuroscience courses. Through this activity, students familiarize themselves with the absolute and relative dimensions of the structural components of synapses; use data from morphometric and schematic models of synapses to estimate the time it takes a neurotransmitter to diffuse across the synaptic cleft; and evaluate how this process relates to synaptic delay and generation of a sufficiently high concentration of transmitter molecules for activation of postsynaptic receptors.

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46

Scalzo, Paula Luciana, Nilo Ikuta, Francisco Cardoso, Andrea Regner, and Antônio Lúcio Teixeira. "Quantitative plasma DNA analysis in Parkinson's disease." Neuroscience Letters 452, no. 1 (March 2009): 5–7. http://dx.doi.org/10.1016/j.neulet.2009.01.031.

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47

Pillay, Praneshri, and Paul R. Manger. "Order-specific quantitative patterns of cortical gyrification." European Journal of Neuroscience 25, no. 9 (April 25, 2007): 2705–12. http://dx.doi.org/10.1111/j.1460-9568.2007.05524.x.

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Ren, T., A. L. Nuttall, and A. A. Parthasarathi. "Quantitative measure of multicomponents of otoacoustic emissions." Journal of Neuroscience Methods 96, no. 2 (March 2000): 97–104. http://dx.doi.org/10.1016/s0165-0270(99)00187-9.

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Bakker, M., F. P. de Lange, J. A. Stevens, I. Toni, and B. R. Bloem. "Motor imagery of gait: a quantitative approach." Experimental Brain Research 179, no. 3 (January 9, 2007): 497–504. http://dx.doi.org/10.1007/s00221-006-0807-x.

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50

Hogan, Neville, and Tamar Flash. "Moving gracefully: quantitative theories of motor coordination." Trends in Neurosciences 10, no. 4 (April 1987): 170–74. http://dx.doi.org/10.1016/0166-2236(87)90043-9.

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