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Journal articles on the topic 'Functional integration in neuroscience'

Author: Grafiati

Published: 14 December 2024

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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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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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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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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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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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11

Rohr, Christiane S., Anish Arora, Ivy Y. K. Cho, et al. "Functional network integration and attention skills in young children." Developmental Cognitive Neuroscience 30 (April 2018): 200–211. http://dx.doi.org/10.1016/j.dcn.2018.03.007.

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12

Laxane, Rahul. "Neuro-Robotics: Bridging Neuroscience and Robotics." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30166.

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The field of neurorobotics represents the combination of neuroscience and robotics, aiming to elucidate neural functional principles and use them to create intelligent robots. This article considers the symbiotic relationship between the two fields and explores how insights from neuroscience can inform the design and control of robots; Robotic platforms offer a unique opportunity to learn and validate insights from neuroscience. For example, this article focuses on the core concepts of neuroscience and robotics and highlights key advances that support the integration of these fields, including

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13

Vilcaes, A. Alejandro, Natali L. Chanaday, and Ege T. Kavalali. "Interneuronal exchange and functional integration of synaptobrevin via extracellular vesicles." Neuron 109, no. 6 (2021): 971–83. http://dx.doi.org/10.1016/j.neuron.2021.01.007.

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14

Jakubs, K., S. Bonde, R. E. Iosif, et al. "Inflammation Regulates Functional Integration of Neurons Born in Adult Brain." Journal of Neuroscience 28, no. 47 (2008): 12477–88. http://dx.doi.org/10.1523/jneurosci.3240-08.2008.

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15

Kundu, Prantik, Brenda E. Benson, Dana Rosen, et al. "The Integration of Functional Brain Activity from Adolescence to Adulthood." Journal of Neuroscience 38, no. 14 (2018): 3559–70. http://dx.doi.org/10.1523/jneurosci.1864-17.2018.

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16

Sepulcre, Jorge. "Functional Streams and Cortical Integration in the Human Brain." Neuroscientist 20, no. 5 (2014): 499–508. http://dx.doi.org/10.1177/1073858414531657.

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17

Garrett, Douglas D., Samira M. Epp, Alistair Perry, and Ulman Lindenberger. "Local temporal variability reflects functional integration in the human brain." NeuroImage 183 (December 2018): 776–87. http://dx.doi.org/10.1016/j.neuroimage.2018.08.019.

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18

Lavigne, Katie M., Paul D. Metzak, and Todd S. Woodward. "Functional brain networks underlying detection and integration of disconfirmatory evidence." NeuroImage 112 (May 2015): 138–51. http://dx.doi.org/10.1016/j.neuroimage.2015.02.043.

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19

Piccinini, Gualtiero, and Carl Craver. "Integrating psychology and neuroscience: functional analyses as mechanism sketches." Synthese 183, no. 3 (2011): 283–311. http://dx.doi.org/10.1007/s11229-011-9898-4.

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20

Macé, Émilie, Gabriel Montaldo, Stuart Trenholm, et al. "Whole-Brain Functional Ultrasound Imaging Reveals Brain Modules for Visuomotor Integration." Neuron 100, no. 5 (2018): 1241–51. http://dx.doi.org/10.1016/j.neuron.2018.11.031.

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21

Triarhou, Lazaros C. "The cerebellar model of neural grafting: Structural integration and functional recovery." Brain Research Bulletin 39, no. 3 (1996): 127–38. http://dx.doi.org/10.1016/0361-9230(95)02090-x.

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22

Song, H. "New Neurons in the Adult Mammalian Brain: Synaptogenesis and Functional Integration." Journal of Neuroscience 25, no. 45 (2005): 10366–68. http://dx.doi.org/10.1523/jneurosci.3452-05.2005.

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23

van den Heuvel, M. P., and O. Sporns. "An Anatomical Substrate for Integration among Functional Networks in Human Cortex." Journal of Neuroscience 33, no. 36 (2013): 14489–500. http://dx.doi.org/10.1523/jneurosci.2128-13.2013.

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24

Fan, J., P. R. Hof, K. G. Guise, J. A. Fossella, and M. I. Posner. "The Functional Integration of the Anterior Cingulate Cortex during Conflict Processing." Cerebral Cortex 18, no. 4 (2007): 796–805. http://dx.doi.org/10.1093/cercor/bhm125.

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25

Benedetti, Bruno, Dominik Dannehl, Richard König, et al. "Functional Integration of Neuronal Precursors in the Adult Murine Piriform Cortex." Cerebral Cortex 30, no. 3 (2019): 1499–515. http://dx.doi.org/10.1093/cercor/bhz181.

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Abstract The extent of functional maturation and integration of nonproliferative neuronal precursors, becoming neurons in the adult murine piriform cortex, is largely unexplored. We thus questioned whether precursors eventually become equivalent to neighboring principal neurons or whether they represent a novel functional network element. Adult brain neuronal precursors and immature neurons (complex cells) were labeled in transgenic mice (DCX-DsRed and DCX-CreERT2 /flox-EGFP), and their cell fate was characterized with patch clamp experiments and morphometric analysis of axon initial segments.

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26

Zhang, Wei, and Qian Hong. "Modeling Brain Functional Networks Using Graph Neural Networks: A Review and Clinical Application." IECE Transactions on Intelligent Systematics 1, no. 2 (2024): 58–68. http://dx.doi.org/10.62762/tis.2024.680959.

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The integration of graph neural networks (GNNs) with brain functional network analysis is an emerging field that combines neuroscience and machine learning to enhance our understanding of complex brain dynamics. We first briefly introduce the fundamentals of brain functional networks, followed by an overview of Graph Neural Network principles and architectures. The review then focuses on the applications of these networks and address current challenges in the field, such as the need for interpretable models and effective integration of multi-modal neuroimaging data. We also highlight the poten

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27

Fauzi, Muhammad Ilfan. "Pemanfaan Neurosains dalam Desain Pengembangan Kurikulum Bahasa Arab." Arabiyatuna : Jurnal Bahasa Arab 4, no. 1 (2020): 1. http://dx.doi.org/10.29240/jba.v4i1.1095.

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This paper discusses the contribution of neuroscience in the development of the Arabic language curriculum of the modern era with the development of a very strategic and practical reconstruction. One of them is the emergence of integration between nation, brain based learning, and character building using a neuroscience approach. The basic point of this study is the right brain functional statement as the basic for developing the Arabic language curriculum. The purpose of this paper is to provide an understanding that the learning process of Arabic can be integrated with the neuroscience appro

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28

Bédard, Mélanie, Line Laplante, and Julien Mercier. "Development of Reading Remediation for Dyslexic Individuals." Zeitschrift für Psychologie 224, no. 4 (2016): 240–46. http://dx.doi.org/10.1027/2151-2604/a000259.

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Abstract. Dyslexia is a phenomenon for which the brain correlates have been studied since the beginning of the 20th century. Simultaneously, the field of education has also been studying dyslexia and its remediation, mainly through behavioral data. The last two decades have seen a growing interest in integrating neuroscience and education. This article provides a quick overview of pertinent scientific literature involving neurophysiological data on functional brain differences in dyslexia and discusses their very limited influence on the development of reading remediation for dyslexic individu

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29

Ray, Dipanjan, Nilambari Hajare, Dipanjan Roy, and Arpan Banerjee. "Large-scale Functional Integration, Rather than Functional Dissociation along Dorsal and Ventral Streams, Underlies Visual Perception and Action." Journal of Cognitive Neuroscience 32, no. 5 (2020): 847–61. http://dx.doi.org/10.1162/jocn_a_01527.

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Visual dual-stream theory posits that two distinct neural pathways of specific functional significance originate from primary visual areas and reach the inferior temporal (ventral) and posterior parietal areas (dorsal). However, there are several unresolved questions concerning the fundamental aspects of this theory. For example, is the functional dissociation between ventral and dorsal stream driven by features in input stimuli or is it driven by categorical differences between visuoperceptual and visuomotor functions? Is the dual stream rigid or flexible? What is the nature of the interactio

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30

Hogan, Patrick Colm. "Continuity and change in narrative study." Narrative Inquiry 16, no. 1 (2006): 66–74. http://dx.doi.org/10.1075/ni.16.1.10hog.

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Since its ancient origins, narrative theory has involved two broad types of analysis — componential and functional. Componential analysis seeks to isolate the elements and operations that make up narrative. Functional analysis explores the purposes of narrative. Commonly, writers isolate two functions — one emotive, the other ethical and/or political. The broad framework of narrative theory has remained largely the same since its inception. Changes have primarily been a matter of expanding the scope or detail of componential or functional analyses. In the twentieth century, there was a particu

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31

Cooper, C. Garret, and Benjamin M. Ramsden. "Clustered cortical organization and the enhanced probability of intra-areal functional integration." Network: Computation in Neural Systems 21, no. 1-2 (2010): 1–34. http://dx.doi.org/10.3109/0954898x.2010.484475.

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32

Gohel, Suril R., and Bharat B. Biswal. "Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands." Brain Connectivity 5, no. 1 (2015): 23–34. http://dx.doi.org/10.1089/brain.2013.0210.

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33

Macaluso, Emiliano, and Jon Driver. "Multisensory spatial interactions: a window onto functional integration in the human brain." Trends in Neurosciences 28, no. 5 (2005): 264–71. http://dx.doi.org/10.1016/j.tins.2005.03.008.

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34

Syed, N. I., R. L. Ridgway, K. Lukowiak, and A. G. M. Bulloch. "Transplantation and functional integration of an identified respiratory interneuron in lymnaea stagnalis." Neuron 8, no. 4 (1992): 767–74. http://dx.doi.org/10.1016/0896-6273(92)90097-w.

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35

Spencer, G. E., N. I. Syed, E. van Kesteren, K. Lukowiak, W. P. M. Geraerts, and J. van Minnen. "Synthesis and functional integration of a neurotransmitter receptor in isolated invertebrate axons." Journal of Neurobiology 44, no. 1 (2000): 72–81. http://dx.doi.org/10.1002/1097-4695(200007)44:1<72::aid-neu7>3.0.co;2-#.

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36

Feklicheva, Inna, Ilya Zakharov, Nadezda Chipeeva, et al. "Assessing the Relationship between Verbal and Nonverbal Cognitive Abilities Using Resting-State EEG Functional Connectivity." Brain Sciences 11, no. 1 (2021): 94. http://dx.doi.org/10.3390/brainsci11010094.

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The present study investigates the relationship between individual differences in verbal and non-verbal cognitive abilities and resting-state EEG network characteristics. We used a network neuroscience approach to analyze both large-scale topological characteristics of the whole brain as well as local brain network characteristics. The characteristic path length, modularity, and cluster coefficient for different EEG frequency bands (alpha, high and low; beta1 and beta2, and theta) were calculated to estimate large-scale topological integration and segregation properties of the brain networks.

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37

De Pascalis, Vilfredo. "Brain Functional Correlates of Resting Hypnosis and Hypnotizability: A Review." Brain Sciences 14, no. 2 (2024): 115. http://dx.doi.org/10.3390/brainsci14020115.

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This comprehensive review delves into the cognitive neuroscience of hypnosis and variations in hypnotizability by examining research employing functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and electroencephalography (EEG) methods. Key focus areas include functional brain imaging correlations in hypnosis, EEG band oscillations as indicators of hypnotic states, alterations in EEG functional connectivity during hypnosis and wakefulness, drawing critical conclusions, and suggesting future research directions. The reviewed functional connectivity findings support

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38

Schlösser, R., K. Koch, G. Wagner, et al. "Intensive practice of a cognitive task is associated with enhanced functional integration in schizophrenia." Psychological Medicine 39, no. 11 (2009): 1809–19. http://dx.doi.org/10.1017/s0033291709005820.

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BackgroundThere is increasing evidence that the frequently reported working memory impairments in schizophrenia might be partly due to an alteration in the functional connectivity between task-relevant areas. However, little is known about the functional connectivity patterns in schizophrenia patients during learning processes. In a previous study, Koch et al. [Neuroscience (2007) 146, 1474–1483] have demonstrated stronger exponential activation decreases in schizophrenia patients during overlearning of short-term memory material. The question arises whether these differential temporal pattern

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39

Montemayor, Carlos, and Marc Wittmann. "The Varieties of Presence: Hierarchical Levels of Temporal Integration." Timing & Time Perception 2, no. 3 (2014): 325–38. http://dx.doi.org/10.1163/22134468-00002030.

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We propose a hierarchical, three-level analysis of the present, in terms of simultaneity of events, experienced presence, and an extended mental presence containing the narrative self. The literature on the philosophy, psychology and neuroscience of time consciousness does not precisely distinguish these varieties of presence: first, a functional moment of perception in the range of milliseconds defines what is simultaneous and successive. Below a certain threshold events are processed as co-temporal. Secondly, the experienced moment of two to three seconds is related to a temporal-processing

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40

Hu, Yi, and Dihao Wang. "Integrative approaches in cognitive neuroscience: Computational tools for analyzing EEG and fMRI data." Applied and Computational Engineering 82, no. 1 (2024): 148–53. http://dx.doi.org/10.54254/2755-2721/82/20240963.

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Abstract. This paper explores the integrative approaches in cognitive neuroscience that utilize computational tools to analyze electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data. These methodologies provide comprehensive insights into the complex mechanisms underlying cognitive functions. By leveraging advanced computational models, researchers can decode brain activity patterns and understand the neural correlates of cognitive processes. This paper discusses technological advancements, such as machine learning algorithms, statistical models, and signal processing

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41

Karakas, H. M. "Epilogue: Integration structural and functional MRI data with EEG." International Journal of Psychophysiology 69, no. 3 (2008): 161. http://dx.doi.org/10.1016/j.ijpsycho.2008.05.411.

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42

Babiloni, Fabio, Filippo Carducci, Cosimo Del Gratta, et al. "On the integration of high resolution EEG and event-related functional MR." NeuroImage 11, no. 5 (2000): S631. http://dx.doi.org/10.1016/s1053-8119(00)91561-1.

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43

Wei, Jing, Xiaoyue Wang, Xiaohong Cui, et al. "Functional Integration and Segregation in a Multilayer Network Model of Patients with Schizophrenia." Brain Sciences 12, no. 3 (2022): 368. http://dx.doi.org/10.3390/brainsci12030368.

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Research has shown that abnormal brain networks in patients with schizophrenia appear at different frequencies, but the relationship between these different frequencies is unclear. Therefore, it is necessary to use a multilayer network model to evaluate the integration of information from different frequency bands. To explore the mechanism of integration and separation in the multilayer network of schizophrenia, we constructed multilayer frequency brain network models in 50 patients with schizophrenia and 69 healthy subjects, and the entropy of the multiplex degree (EMD) and multilayer cluster

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44

Làdavas, Elisabetta, and Francesco Pavani. "Neuropsychological evidence of the functional integration of visual, auditory and proprioceptive spatial maps." NeuroReport 9, no. 6 (1998): 1195–200. http://dx.doi.org/10.1097/00001756-199804200-00043.

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45

Sørensen, Andreas Toft, Lachlan Thompson, Deniz Kirik, Anders Björklund, Olle Lindvall, and Merab Kokaia. "Functional properties and synaptic integration of genetically labelled dopaminergic neurons in intrastriatal grafts." European Journal of Neuroscience 21, no. 10 (2005): 2793–99. http://dx.doi.org/10.1111/j.1460-9568.2005.04116.x.

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46

Pardillo-Díaz, Ricardo, Patricia Perez-Garcia, Livia Carrascal, et al. "NEWLY GENERATED NEURONS IN MECHANICAL CORTICAL BRAIN INJURIES: A STUDY OF FUNCTIONAL INTEGRATION." IBRO Neuroscience Reports 15 (October 2023): S194—S195. http://dx.doi.org/10.1016/j.ibneur.2023.08.299.

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47

Fulcher, Ben D. "Discovering Conserved Properties of Brain Organization Through Multimodal Integration and Interspecies Comparison." Journal of Experimental Neuroscience 13 (January 2019): 117906951986204. http://dx.doi.org/10.1177/1179069519862047.

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The primate cerebral cortex is broadly organized along hierarchical processing streams underpinned by corresponding variation in the brain’s microstructure and interareal connectivity patterns. Fulcher et al. recently demonstrated that a similar organization exists in the mouse cortex by combining independent datasets of cytoarchitecture, gene expression, cell densities, and long-range axonal connectivity. Using the T1w:T2w magnetic resonance imaging map as a common spatial reference for data-driven comparison of cortical gradients between mouse and human, we highlighted a common hierarchical

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48

Fein, Deborah. "Thoughtful People Thinking About People Thinking About Thinking People." Journal of the International Neuropsychological Society 12, no. 5 (2006): 759–60. http://dx.doi.org/10.1017/s1355617706220939.

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Social Neuroscience: People Thinking About Thinking People. John T. Cacioppo, Penny S. Visser, and Cynthia L. Pickett (Eds.). 2006. Cambridge, MA: The MIT Press, 328 pp., $45.00 (HB)Perhaps not since the flowering of clinical neuropsychology thirty years ago have we seen this sense of exhilaration about the emergence of a new field through the integration of existing disciplines. Clearly, these authors and thinkers feel the same excitement that could be felt when new collaborations were being forged among neurologists, psychiatrists, psychologists, and communication specialists in earlier deca

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49

Cinciute, Sigita. "Translating the hemodynamic response: why focused interdisciplinary integration should matter for the future of functional neuroimaging." PeerJ 7 (March 25, 2019): e6621. http://dx.doi.org/10.7717/peerj.6621.

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The amount of information acquired with functional neuroimaging techniques, particularly fNIRS and fMRI, is rapidly growing and has enormous potential for studying human brain functioning. Therefore, many scientists focus on solving computational neuroimaging and Big Data issues to advance the discipline. However, the main obstacle—the accurate translation of the hemodynamic response (HR) by the investigation of a physiological phenomenon called neurovascular coupling—is still not fully overcome and, more importantly, often overlooked in this context. This article provides a brief and critical

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50

Calabro, Finnegan J., Vishnu P. Murty, Maria Jalbrzikowski, Brenden Tervo-Clemmens, and Beatriz Luna. "Development of Hippocampal–Prefrontal Cortex Interactions through Adolescence." Cerebral Cortex 30, no. 3 (2019): 1548–58. http://dx.doi.org/10.1093/cercor/bhz186.

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Abstract Significant improvements in cognitive control occur from childhood through adolescence, supported by the maturation of prefrontal systems. However, less is known about the neural basis of refinements in cognitive control proceeding from adolescence to adulthood. Accumulating evidence indicates that integration between hippocampus (HPC) and prefrontal cortex (PFC) supports flexible cognition and has a protracted neural maturation. Using a longitudinal design (487 scans), we characterized developmental changes from 8 to 32 years of age in HPC-PFC functional connectivity at rest and its

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