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Letteratura scientifica selezionata sul tema "Functional integration in neuroscience"

Autore: Grafiati

Pubblicato: 14 dicembre 2024

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Articoli di riviste sul tema "Functional integration in neuroscience"

1

Shibkova, Dariya Zakharovna, and Pavel Azifovich Baiguzhin. "NEUROSCIENCE: INTERDISCIPLINARY INTEGRATION OR EXPANSION?" Психология. Психофизиология 13, no. 3 (2020): 111–21. http://dx.doi.org/10.14529/jpps200312.

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Aim. The paper aims to study the differentiation and integration of scientific disciplines in the natural sciences and humanities research areas of neuroscience based on a review of Russian scientific works and to propose a structural and functional model of neuroscience as an interdisciplinary system of knowledge about brain features that ensure human activity in various professional spheres. Methods. A theoretical analysis of scientific publications on the topic over the last ten years has been used along with such methods as comparison, generalization, and modelling. Results. The paper pres

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2

Ramsey, Richard. "Neural Integration in Body Perception." Journal of Cognitive Neuroscience 30, no. 10 (2018): 1442–51. http://dx.doi.org/10.1162/jocn_a_01299.

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The perception of other people is instrumental in guiding social interactions. For example, the appearance of the human body cues a wide range of inferences regarding sex, age, health, and personality, as well as emotional state and intentions, which influence social behavior. To date, most neuroscience research on body perception has aimed to characterize the functional contribution of segregated patches of cortex in the ventral visual stream. In light of the growing prominence of network architectures in neuroscience, the current article reviews neuroimaging studies that measure functional i

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3

Povich, Mark. "Model-based cognitive neuroscience: Multifield mechanistic integration in practice." Theory & Psychology 29, no. 5 (2019): 640–56. http://dx.doi.org/10.1177/0959354319863880.

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Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function. In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function. In this article, I show how Model-Based Cognitive Neuroscience (MBCN) epitomizes the integrative mechanistic perspective and concentrates the most revolutionary elements of t

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4

Wrobel, Andrzej. "The need of neuroinformatic approach in functional neurophysiology." Acta Neurobiologiae Experimentalis 65, no. 4 (2005): 421–23. http://dx.doi.org/10.55782/ane-2005-1570.

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Despite the enormous growth in the number of facts and regularities observed in neuroscience, the current state of the field does not allow their integration in coherent theoretical frameworks. Neuroinformatics is a new research field devoted to development of neuroscience data bases together with computational models and analytical tools for sharing, integration and analysis of experimental data and the advancement of theories of nervous system function. From 1996 the OECD countries promote fostering neuroinformatics by eliminating the barriers that prevent cooperation and by providing incent

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5

Castro, L. C. "Affective Neuroscience: A Crucial Role in Psychiatry." European Psychiatry 24, S1 (2009): 1. http://dx.doi.org/10.1016/s0924-9338(09)71130-7.

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Background:Neuroscience has been a growing revolutionary field of scientific knowledge. The increasing recognition of the importance of emotional processes and subjective experience in several aspects of human behaviour parallel the growing amount of research in the field of affective neuroscience. Affective neuroscience studies the brain mechanisms subjacent to emotional behaviour.Aim:To discuss the relevance of affective neuroscience research in social and biological sciences, namely within psychiatric and psychological researches.Methods:Review of the literature. MEDLINE and PubMed database

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6

Friston, Karl. "Functional integration and inference in the brain." Progress in Neurobiology 68, no. 2 (2002): 113–43. http://dx.doi.org/10.1016/s0301-0082(02)00076-x.

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7

Krebs, H. I., T. Brashers-Krug, S. L. Rauch, et al. "Integration of robotic technology with functional imaging." NeuroImage 3, no. 3 (1996): S394. http://dx.doi.org/10.1016/s1053-8119(96)80396-x.

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8

Arachchige, Arosh S. Perera Molligoda. "Transitioning from PET/MR to trimodal neuroimaging: why not cover the temporal dimension with EEG?" AIMS Neuroscience 10, no. 1 (2023): 1–4. http://dx.doi.org/10.3934/neuroscience.2023001.

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<abstract> <p>The possibility of multimodality imaging with PET/MR and the availability of ultra-high field MRI has allowed to investigate novel aspects of neuropsychiatric conditions. One of the major barriers in current studies is the lack of an instrument that allows to accurately cover the temporal aspect under the same physiological conditions. The aim of this commentary is to provide our perspective on how the integration of EEG-PET-MR could be a solution to the current challenge in molecular imaging and seems to hold great promise in future pharmacological challenging-based

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9

Parlatini, Valeria, Joaquim Radua, Flavio Dell’Acqua, et al. "Functional segregation and integration within fronto-parietal networks." NeuroImage 146 (February 2017): 367–75. http://dx.doi.org/10.1016/j.neuroimage.2016.08.031.

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10

Aydarkin, Evgeny K., and Marina A. Pavlovskaya. "Functional hemisphere asymmetry and sensorimotor integration." International Journal of Psychophysiology 77, no. 3 (2010): 327. http://dx.doi.org/10.1016/j.ijpsycho.2010.06.254.

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