Artículos de revistas: "Brain"

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Scull, A. "Left brain, right brain: One brain, two brains". Brain 133, n.º 10 (25 de septiembre de 2010): 3153–56. http://dx.doi.org/10.1093/brain/awq255.

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Vadza, Kejal Chintan. "Brain Gate & Brain Computer Interface". International Journal of Scientific Research 2, n.º 5 (1 de junio de 2012): 45–49. http://dx.doi.org/10.15373/22778179/may2013/19.

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Gowda, Ashmitha. "Brain Fingerprinting". International Journal of Research Publication and Reviews 4, n.º 5 (4 de mayo de 2023): 1707–10. http://dx.doi.org/10.55248/gengpi.234.5.40436.

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4

Goodman, G., R. R. Poznanski, L. Cacha y D. Bercovich. "The Two-Brains Hypothesis: Towards a guide for brain–brain and brain–machine interfaces". Journal of Integrative Neuroscience 14, n.º 03 (septiembre de 2015): 281–93. http://dx.doi.org/10.1142/s0219635215500235.

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5

Tsibu, George. "The Child Brain". Clinical Medical Reviews and Reports 2, n.º 02 (24 de febrero de 2020): 01. http://dx.doi.org/10.31579/2690-8794/011.

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The brain is an organ is a part of the central nervous system created for responses and impulse of the movement of charges and information across the whole body.It is the major organ because it is the first portion to start growing immediately the zygote is form after fertilization .The weight of the brain is fully grown when the child reaches 15years.Boy did you fight your way through, that is unheard of,The embryo of male generative fluid is responsible for the characteristic of the kind of brain a child will have,The growing brain is having a shock recognisable in it shell,vast growth occurs in the next Seven month.

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Pinheiro, Renato Serquiz E., Yanny Cinara T. Ernesto y Irami Araújo-Filho. "Bleeding Brain Intraparenchymal". International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (30 de abril de 2019): 1719–24. http://dx.doi.org/10.31142/ijtsrd23500.

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7

R. Suryawanshi, Chandani y Vinod Nayyar. "BLUE BRAIN". INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 7, n.º 2 (30 de noviembre de 2013): 1009–17. http://dx.doi.org/10.24297/ijmit.v7i2.3294.

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Today scientists are in research to create an artificial brain that can think, respond, take decision, and keep anything in memory. The main aim is to upload human brain into machine. So that man can think, take decision without any effort. After the death of the body, the virtual brain will act as the man. So, even after the death of a person we will not loose the knowledge, intelligence, personalities, feelings and memories of that man, that can be used for the development of the human society. Technology is growing faster than every thing. IBM is now in research to create a virtual brain, called Blue brain. If possible, this would be the first virtual brain of the world. IBM, in partnership with scientists at Switzerlands Ecole Polytech- nique Federale de Lausannes (EPFL) Brain and Mind Institute will begin simulating the brains biological systems and output the data as a working 3-dimensional model that will recreate the high-speed electrochemical interactions that take place within the brains interior. These include cognitive functions such as language, learning, perception and memory in addition to brain malfunction such as psychiatric disorders like depression and autism. From there, the modeling will expand to other regions of the brain and, if successful, shed light on the relationships between genetic, molecular and cognitive functions of the brain.

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8

R, Divya. "Instagramification of the Brain". Neurology & Neurotherapy Open Access Journal 4, n.º 1 (2019): 1–2. http://dx.doi.org/10.23880/nnoaj-16000133.

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Internet usage is the most widespread technological advancement in the history of humanity. It plays a major role in search for information, entertainment area, and management of social networks and relationships in day - to - day life. In a recent research conducted by a team of international researchers from various universities across th e globe found that the Internet usage resulted in acute and sustained modifications in cognition, attention span, memory and social interactions in users

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9

Markou, Athina, Theodora Duka y Gordana Prelevic. "Estrogens and brain function". HORMONES 4, n.º 1 (15 de enero de 2005): 9–17. http://dx.doi.org/10.14310/horm.2002.11138.

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10

Salami, A., M. Ajani, I. Orhorho, G. Ogun, A. Adeoye, C. Okolo, A. Oluwasola y J. Ogunbiyi. "Brain weights in adult africans". Journal of Morphological Sciences 34, n.º 04 (octubre de 2017): 223–25. http://dx.doi.org/10.4322/jms.106316.

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Abstract Introduction: The average brain weight of adult humans, using Caucasian figures, is said to be between 1300g to 1400g. Few studies have however been done to make actual evaluations of brain weights in adult Africans. This study seeks to examine the weight of brains from people of African descent with respect to variations in sex and age in decades using autopsy specimens. Materials and Methods: Analysis of the weight of brains removed from both male and female adult patients during fresh autopsy of their bodies in our center over a ten year period was done. The study criteria required non-involvement of the central nervous system in the cause of death. The brains were grouped based on age in decades and further grouped into early, middle and late age groups. Descriptive statistical analysis was done using SPSS 20 statistics software. Results: A total of one hundred and sixteen brains were included in the study and the mean brain weight was 1280g with a range between 1015g to 1590g. There was no statistically significant difference in the mean brain weight of the different age groups. The average male brain was heavier than those of females and the difference was statistically signiicant. Conclusion: The brain weight of adult Africans in our study is similar to that seen in Caucasians. There is no statistically significant difference in the brain weight of adults from early adulthood to the elderly adults. Male adults have statistically heavier brains than the females.

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11

Striedter, Georg F. "Précis of Principles of Brain Evolution". Behavioral and Brain Sciences 29, n.º 1 (febrero de 2006): 1–12. http://dx.doi.org/10.1017/s0140525x06009010.

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Brain evolution is a complex weave of species similarities and differences, bound by diverse rules and principles. This book is a detailed examination of these principles, using data from a wide array of vertebrates but minimizing technical details and terminology. It is written for advanced undergraduates, graduate students, and more senior scientists who already know something about “the brain,” but want a deeper understanding of how diverse brains evolved. The book's central theme is that evolutionary changes in absolute brain size tend to correlate with many other aspects of brain structure and function, including the proportional size of individual brain regions, their complexity, and their neuronal connections. To explain these correlations, the book delves into rules of brain development and asks how changes in brain structure impact function and behavior. Two chapters focus specifically on how mammal brains diverged from other brains and how Homo sapiens evolved a very large and “special” brain.

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12

Millar, Brian. "Brain dead, brain absent, brain donors". Intensive and Critical Care Nursing 9, n.º 3 (septiembre de 1993): 209–10. http://dx.doi.org/10.1016/0964-3397(93)90031-r.

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13

Berg, Thomas. "Human Brain Cells in Animal Brains". National Catholic Bioethics Quarterly 6, n.º 1 (2006): 89–107. http://dx.doi.org/10.5840/ncbq20066169.

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14

Swain, James E. "Brain design: The evolution of brains". Behavioral and Brain Sciences 29, n.º 1 (febrero de 2006): 24–25. http://dx.doi.org/10.1017/s0140525x06349011.

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After reviewing historical aspects of brain evolution, this accessible book provides an enjoyable overview of several general principles of brain evolution, culminating in discussions of mammalian and human brains and a framework for future research.

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15

Endevelt-Shapira, Yaara y Ruth Feldman. "Mother–Infant Brain-to-Brain Synchrony Patterns Reflect Caregiving Profiles". Biology 12, n.º 2 (10 de febrero de 2023): 284. http://dx.doi.org/10.3390/biology12020284.

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Biobehavioral synchrony, the coordination of physiological and behavioral signals between mother and infant during social contact, tunes the child’s brain to the social world. Probing this mechanism from a two-brain perspective, we examine the associations between patterns of mother–infant inter-brain synchrony and the two well-studied maternal behavioral orientations—sensitivity and intrusiveness—which have repeatedly been shown to predict positive and negative socio-emotional outcomes, respectively. Using dual-electroencephalogram (EEG) recordings, we measure inter-brain connectivity between 60 mothers and their 5- to 12-month-old infants during face-to-face interaction. Thirty inter-brain connections show significantly higher correlations during the real mother–infant face-to-face interaction compared to surrogate data. Brain–behavior correlations indicate that higher maternal sensitivity linked with greater mother–infant neural synchrony, whereas higher maternal intrusiveness is associated with lower inter-brain coordination. Post hoc analysis reveals that the mother-right-frontal–infant-left-temporal connection is particularly sensitive to the mother’s sensitive style, while the mother-left-frontal–infant-right-temporal connection indexes the intrusive style. Our results support the perspective that inter-brain synchrony is a mechanism by which mature brains externally regulate immature brains to social living and suggest that one pathway by which sensitivity and intrusiveness exert their long-term effect may relate to the provision of coordinated inputs to the social brain during its sensitive period of maturation.

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16

Tsutsui, Yoshihiro, Hideya Kawasaki y Isao Kosugi. "Reactivation of Latent Cytomegalovirus Infection in Mouse Brain Cells Detected after Transfer to Brain Slice Cultures". Journal of Virology 76, n.º 14 (15 de julio de 2002): 7247–54. http://dx.doi.org/10.1128/jvi.76.14.7247-7254.2002.

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ABSTRACT Cytomegalovirus (CMV) is the most significant infectious cause of brain disorders in humans involving the developing brain. It is hypothesized that the brain disorders occur after recurrent reactivation of the latent infection in some kinds of cells in the brains. In order to test this hypothesis, we examined the reactivation of latent murine CMV (MCMV) infection in the mouse brain by transfer to brain slice culture. We infected neonatal and young adult mice intracerebrally with recombinant MCMV in which the lacZ gene was inserted into a late gene. The brains were removed 6 months after infection and used to prepare brain slices that were then cultured for up to 4 weeks. Reactivation of latent infection in the brains was detected by β-galactosidase (β-Gal) staining to assess β-galactosidase expression. Viral replication was also confirmed by the plaque assay. Reactivation was observed in about 75% of the mice infected during the neonatal period 6 months after infection. Unexpectedly, reactivation was also observed in 75% of mice infected as young adults, although the infection ratio in the brain slices was significantly lower than that in neonatally infected mice. β-Gal-positive cells were observed in marginal regions of the brains or immature neural cells in the ventricular walls. Immunohistochemical staining showed that the β-Gal-positive reactivated cells were neural stem or progenitor cells. These results suggest that brain disorders may occur long after infection by reactivation of latent infection in the immature neural cells in the brain.

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17

Witte, Otto W. y Malgorzata Kossut. "Impairment of Brain Plasticity by Brain Inflammation". Zeitschrift für Psychologie 224, n.º 2 (abril de 2016): 133–38. http://dx.doi.org/10.1027/2151-2604/a000247.

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Abstract. The ability to learn and the ability to reshape brain circuits are regarded as some of the most remarkable and important features of the brain. This ability declines with age due to largely unknown reasons, and it also is altered following stroke. Brain aging is associated with a progressive increase of the levels of inflammatory cytokine in the brain. Likewise, stroke causes pronounced increases of inflammatory cytokines in the brain. Following stroke, plasticity of the cortical representation following sensory deprivation and visualized with [14C]-2-deoxyglucose autoradiography is impaired for several weeks. Likewise, plasticity of visual acuity induced by occlusion of the ipsilateral eye is impaired. Both forms of plasticity may be rescued by treatment with anti-inflammatory drugs. In contrast to this, ocular dominance plasticity which is also induced by visual occlusion is not rescued by this intervention, neither following stroke nor in aged brains. Antiinflammatory interventions may therefore be a useful tool to enhance brain plasticity following stroke, but need to be supplemented by additional strategies to enhance brain plasticity.

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18

Farajirad, Mohammad. "The Gut-Brain Axis: How the Microbiome may Influence Brain Tumors, A Narrative Review". International Journal of Surgery & Surgical Techniques 7, n.º 2 (2023): 1–6. http://dx.doi.org/10.23880/ijsst-16000192.

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Aim: To review the current literature and demonstrate the potential relationship between gut microbiome and brain tumor. Methods: A comprehensive search of the available literature was conducted using the PubMed, Google Scholar, OVID, Embase and other database to identify studies investigating the relationship between the gut microbiome and brain cancer. The search was limited to articles published in English between 2010 and 2022. Conclusion: While the research on the relationship between the gut microbiome and brain cancer is limited, the studies that have been conducted suggest that there may be a connection. The gut microbiome has been shown to play roles in a number of diseases, and some evidence suggests that it may also be involved in the development and progression of brain cancer. The gut microbiome may suggest a new method for the prevention, diagnosis, and treatment of brain cancer and further research in this area has the potential to lead to new and innovative strategies for managing this disease.

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19

Goulas, A., R. F. Betzel y C. C. Hilgetag. "Spatiotemporal ontogeny of brain wiring". Science Advances 5, n.º 6 (junio de 2019): eaav9694. http://dx.doi.org/10.1126/sciadv.aav9694.

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The wiring of vertebrate and invertebrate brains provides the anatomical skeleton for cognition and behavior. Connections among brain regions are characterized by heterogeneous strength that is parsimoniously described by the wiring cost and homophily principles. Moreover, brains exhibit a characteristic global network topology, including modules and hubs. However, the mechanisms resulting in the observed interregional wiring principles and network topology of brains are unknown. Here, with the aid of computational modeling, we demonstrate that a mechanism based on heterochronous and spatially ordered neurodevelopmental gradients, without the involvement of activity-dependent plasticity or axonal guidance cues, can reconstruct a large part of the wiring principles (on average, 83%) and global network topology (on average, 80%) of diverse adult brain connectomes, including fly and human connectomes. In sum, space and time are key components of a parsimonious, plausible neurodevelopmental mechanism of brain wiring with a potential universal scope, encompassing vertebrate and invertebrate brains.

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20

van den Pol, Anthony N. "Brain Trauma Enhances Transient Cytomegalovirus Invasion of the Brain Only in Mice That Are Immunodeficient". Journal of Virology 83, n.º 1 (22 de octubre de 2008): 420–27. http://dx.doi.org/10.1128/jvi.01728-08.

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ABSTRACT Cytomegalovirus (CMV) is one of the most common viral pathogens leading to neurological dysfunction in individuals with depressed immune systems. How CMV enters the brain remains an open question. The hypothesis that brain injury may enhance the entrance of CMV into the brain was tested. Insertion of a sterile needle into the brain caused a dramatic increase in mouse CMV in the brains of immunodeficient SCID mice inoculated peripherally within an hour of injury and examined 1 week later; peripheral inoculation 48 h after injury and a 1-week survival resulted in only a modest infection at the site of injury. In contrast, uninjured SCID mice, as well as injured immunocompetent control mice, showed little sign of viral infection at the same time intervals. Direct inoculation of the brain resulted in widespread dispersal and enhanced replication of mCMV in SCID brains tested 1 week later but not in parallel control brains. Differential viremia was unlikely to account for the greater viral load in the SCID brain, since increased mCMV in the blood of SCID compared to controls was not detected until a longer interval. These data suggest that brain injury enhances CMV invasion of the brain, but only when the adaptive immune system is compromised, and that the brain's ability to resist viral infection recovers rapidly after injury.

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21

Tominaga, Kaoru, Eiji Sakashita, Katsumi Kasashima, Kenji Kuroiwa, Yasumitsu Nagao, Naoki Iwamori y Hitoshi Endo. "Tip60/KAT5 Histone Acetyltransferase Is Required for Maintenance and Neurogenesis of Embryonic Neural Stem Cells". International Journal of Molecular Sciences 24, n.º 3 (20 de enero de 2023): 2113. http://dx.doi.org/10.3390/ijms24032113.

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Epigenetic regulation via epigenetic factors in collaboration with tissue-specific transcription factors is curtail for establishing functional organ systems during development. Brain development is tightly regulated by epigenetic factors, which are coordinately activated or inactivated during processes, and their dysregulation is linked to brain abnormalities and intellectual disability. However, the precise mechanism of epigenetic regulation in brain development and neurogenesis remains largely unknown. Here, we show that Tip60/KAT5 deletion in neural stem/progenitor cells (NSCs) in mice results in multiple abnormalities of brain development. Tip60-deficient embryonic brain led to microcephaly, and proliferating cells in the developing brain were reduced by Tip60 deficiency. In addition, neural differentiation and neuronal migration were severely affected in Tip60-deficient brains. Following neurogenesis in developing brains, gliogenesis started from the earlier stage of development in Tip60-deficient brains, indicating that Tip60 is involved in switching from neurogenesis to gliogenesis during brain development. It was also confirmed in vitro that poor neurosphere formation, proliferation defects, neural differentiation defects, and accelerated astrocytic differentiation in mutant NSCs are derived from Tip60-deficient embryonic brains. This study uncovers the critical role of Tip60 in brain development and NSC maintenance and function in vivo and in vitro.

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22

Yoo, Seung-Schik, Hyungmin Kim, Emmanuel Filandrianos, Seyed Javid Taghados y Shinsuk Park. "Non-Invasive Brain-to-Brain Interface (BBI): Establishing Functional Links between Two Brains". PLoS ONE 8, n.º 4 (3 de abril de 2013): e60410. http://dx.doi.org/10.1371/journal.pone.0060410.

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23

Robertson, Susan L. "Brain drain, brain gain and brain circulation". Globalisation, Societies and Education 4, n.º 1 (marzo de 2006): 1–5. http://dx.doi.org/10.1080/14767720600554908.

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24

Hunter, Philip. "Brain drain, brain gain or brain sharing?" EMBO reports 14, n.º 4 (15 de marzo de 2013): 315–18. http://dx.doi.org/10.1038/embor.2013.33.

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25

Peters, Michael A. "Human Brain Project; Blue Brain; Virtual Brain". Educational Philosophy and Theory 45, n.º 8 (5 de abril de 2013): 817–20. http://dx.doi.org/10.1080/00131857.2013.781295.

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26

Bach-y-Rita, Paul y Gaetano L. Aiello. "Brain energetics and evolution". Behavioral and Brain Sciences 24, n.º 2 (abril de 2001): 280–81. http://dx.doi.org/10.1017/s0140525x01243957.

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The human brain does not use more energy than the smaller brains of animals of comparable corporal weight. Uniquely, human functions localized largely in parts of the human brain that show greatest size increase over other animals may be mediated primarily by nonsynaptic neurotransmission, with reduced energy cost per kilogram of brain. This may affect the energetic constraints on evolution.

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27

Link, Christopher D. "Is There a Brain Microbiome?" Neuroscience Insights 16 (enero de 2021): 263310552110187. http://dx.doi.org/10.1177/26331055211018709.

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Numerous studies have identified microbial sequences or epitopes in pathological and non-pathological human brain samples. It has not been resolved if these observations are artifactual, or truly represent population of the brain by microbes. Given the tempting speculation that resident microbes could play a role in the many neuropsychiatric and neurodegenerative diseases that currently lack clear etiologies, there is a strong motivation to determine the “ground truth” of microbial existence in living brains. Here I argue that the evidence for the presence of microbes in diseased brains is quite strong, but a compelling demonstration of resident microbes in the healthy human brain remains to be done. Dedicated animal models studies may be required to determine if there is indeed a “brain microbiome.”

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28

Kupade, Kandgonda A. "Brain Signal Sort out Methods". Journal of Advanced Research in Dynamical and Control Systems 12, n.º 3 (20 de marzo de 2020): 12–20. http://dx.doi.org/10.5373/jardcs/v12i3/20201162.

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29

Murphy, Alexandra. "Vom Boom zum Brain Drain". osteuropa 70, n.º 10-11 (2020): 321. http://dx.doi.org/10.35998/oe-2020-0083.

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30

Deepa, R. y P. Narendran. "Brain Tumor Detection Segmentation Techniques". International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (30 de abril de 2018): 207–12. http://dx.doi.org/10.31142/ijtsrd9634.

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31

Klyuchko, O. M. "TECHNOLOGIES OF BRAIN IMAGES PROCESSING". Biotechnologia Acta 10, n.º 6 (diciembre de 2017): 5–17. http://dx.doi.org/10.15407/biotech10.06.005.

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32

Pulaparthi, Naga MahaLakshmi, Madhulika Dabbiru, Charishma Penkey y Dr Nrusimhadri Naveen. "Brain Stroke Detection Using DeepLearning". International Journal of Research Publication and Reviews 4, n.º 4 (abril de 2023): 2468–73. http://dx.doi.org/10.55248/gengpi.4.423.35996.

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33

C, Machado. "More about the Respirator Brain". Anaesthesia & Critical Care Medicine Journal 9, n.º 1 (5 de enero de 2024): 1–2. http://dx.doi.org/10.23880/accmj-16000235.

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34

Smulders, Tom V. "The relevance of brain evolution for the biomedical sciences". Biology Letters 5, n.º 1 (21 de octubre de 2008): 138–40. http://dx.doi.org/10.1098/rsbl.2008.0521.

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Most biomedical neuroscientists realize the importance of the study of brain evolution to help them understand the differences and similarities between their animal model of choice and the human brains in which they are ultimately interested. Many think of evolution as a linear process, going from simpler brains, as those of rats, to more complex ones, as those of humans. However, in reality, every extant species' brain has undergone as long a period of evolution as has the human brain, and each brain has its own species-specific adaptations. By understanding the variety of existing brain types, we can more accurately reconstruct the brains of common ancestors, and understand which brain traits (of humans as well as other species) are derived and which are ancestral. This understanding also allows us to identify convergently evolved traits, which are crucial in formulating hypotheses about structure–function relationships in the brain. A thorough understanding of the processes and patterns of brain evolution is essential to generalizing findings from ‘model species’ to humans, which is the backbone of modern biomedical science.

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35

Reardon, P. K., Jakob Seidlitz, Simon Vandekar, Siyuan Liu, Raihaan Patel, Min Tae M. Park, Aaron Alexander-Bloch et al. "Normative brain size variation and brain shape diversity in humans". Science 360, n.º 6394 (31 de mayo de 2018): 1222–27. http://dx.doi.org/10.1126/science.aar2578.

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Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology.

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Sayol, Ferran, Louis Lefebvre y Daniel Sol. "Relative Brain Size and Its Relation with the Associative Pallium in Birds". Brain, Behavior and Evolution 87, n.º 2 (2016): 69–77. http://dx.doi.org/10.1159/000444670.

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Despite growing interest in the evolution of enlarged brains, the biological significance of brain size variation remains controversial. Much of the controversy is over the extent to which brain structures have evolved independently of each other (mosaic evolution) or in a coordinated way (concerted evolution). If larger brains have evolved by the increase of different brain regions in different species, it follows that comparisons of the whole brain might be biologically meaningless. Such an argument has been used to criticize comparative attempts to explain the existing variation in whole-brain size among species. Here, we show that pallium areas associated with domain-general cognition represent a large fraction of the entire brain, are disproportionally larger in large-brained birds and accurately predict variation in the whole brain when allometric effects are appropriately accounted for. While this does not question the importance of mosaic evolution, it suggests that examining specialized, small areas of the brain is not very helpful for understanding why some birds have evolved such large brains. Instead, the size of the whole brain reflects consistent variation in associative pallium areas and hence is functionally meaningful for comparative analyses.

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Joel, Daphna, Zohar Berman, Ido Tavor, Nadav Wexler, Olga Gaber, Yaniv Stein, Nisan Shefi et al. "Sex beyond the genitalia: The human brain mosaic". Proceedings of the National Academy of Sciences 112, n.º 50 (30 de noviembre de 2015): 15468–73. http://dx.doi.org/10.1073/pnas.1509654112.

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Whereas a categorical difference in the genitals has always been acknowledged, the question of how far these categories extend into human biology is still not resolved. Documented sex/gender differences in the brain are often taken as support of a sexually dimorphic view of human brains (“female brain” or “male brain”). However, such a distinction would be possible only if sex/gender differences in brain features were highly dimorphic (i.e., little overlap between the forms of these features in males and females) and internally consistent (i.e., a brain has only “male” or only “female” features). Here, analysis of MRIs of more than 1,400 human brains from four datasets reveals extensive overlap between the distributions of females and males for all gray matter, white matter, and connections assessed. Moreover, analyses of internal consistency reveal that brains with features that are consistently at one end of the “maleness-femaleness” continuum are rare. Rather, most brains are comprised of unique “mosaics” of features, some more common in females compared with males, some more common in males compared with females, and some common in both females and males. Our findings are robust across sample, age, type of MRI, and method of analysis. These findings are corroborated by a similar analysis of personality traits, attitudes, interests, and behaviors of more than 5,500 individuals, which reveals that internal consistency is extremely rare. Our study demonstrates that, although there are sex/gender differences in the brain, human brains do not belong to one of two distinct categories: male brain/female brain.

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Adelson, P. David. "Pediatric Traumatic Brain Injury : Present and Future Considerations in Management(Traumatic Brain Injury: Recent Advances)". Japanese Journal of Neurosurgery 19, n.º 3 (2010): 196–201. http://dx.doi.org/10.7887/jcns.19.196.

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Luquero, Aureli, Noelia Pimentel, Gemma Vilahur, Lina Badimon y Maria Borrell-Pages. "Unique Splicing of Lrp5 in the Brain: A New Player in Neurodevelopment and Brain Maturation". International Journal of Molecular Sciences 25, n.º 12 (20 de junio de 2024): 6763. http://dx.doi.org/10.3390/ijms25126763.

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Low-density lipoprotein receptor-related protein 5 (LRP5) is a constitutively expressed receptor with observed roles in bone homeostasis, retinal development, and cardiac metabolism. However, the function of LRP5 in the brain remains unexplored. This study investigates LRP5’s role in the central nervous system by conducting an extensive analysis using RNA-seq tools and in silico assessments. Two protein-coding Lrp5 transcripts are expressed in mice: full-length Lrp5-201 and a truncated form encoded by Lrp5-202. Wt mice express Lrp5-201 in the liver and brain and do not express the truncated form. Lrp5−/− mice express Lrp5-202 in the liver and brain and do not express Lrp5-201 in the liver. Interestingly, Lrp5−/− mouse brains show full-length Lrp5-201 expression, suggesting that LRP5 has a role in preserving brain function during development. Functional gene enrichment analysis on RNA-seq unveils dysregulated expression of genes associated with neuronal differentiation and synapse formation in the brains of Lrp5−/− mice compared to Wt mice. Furthermore, Gene Set Enrichment Analysis highlights downregulated expression of genes involved in retinol and linoleic acid metabolism in Lrp5−/− mouse brains. Tissue-specific alternative splicing of Lrp5 in Lrp5−/− mice supports that the expression of LRP5 in the brain is needed for the correct synthesis of vitamins and fatty acids, and it is indispensable for correct brain development.

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40

Joel, Daphna y Anne Fausto-Sterling. "Beyond sex differences: new approaches for thinking about variation in brain structure and function". Philosophical Transactions of the Royal Society B: Biological Sciences 371, n.º 1688 (19 de febrero de 2016): 20150451. http://dx.doi.org/10.1098/rstb.2015.0451.

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In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being.

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41

Groothuis, Jitte y Hans M. Smid. "Nasonia Parasitic Wasps Escape from Haller's Rule by Diphasic, Partially Isometric Brain-Body Size Scaling and Selective Neuropil Adaptations". Brain, Behavior and Evolution 90, n.º 3 (2017): 243–54. http://dx.doi.org/10.1159/000480421.

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Haller's rule states that brains scale allometrically with body size in all animals, meaning that relative brain size increases with decreasing body size. This rule applies both on inter- and intraspecific comparisons. Only 1 species, the extremely small parasitic wasp Trichogramma evanescens, is known as an exception and shows an isometric brain-body size relation in an intraspecific comparison between differently sized individuals. Here, we investigated if such an isometric brain-body size relationship also occurs in an intraspecific comparison with a slightly larger parasitic wasp, Nasonia vitripennis, a species that may vary 10-fold in body weight upon differences in levels of scramble competition during larval development. We show that Nasonia exhibits diphasic brain-body size scaling: larger wasps scale allometrically, following Haller's rule, whereas the smallest wasps show isometric scaling. Brains of smaller wasps are, therefore, smaller than expected and we hypothesized that this may lead to adaptations in brain architecture. Volumetric analysis of neuropil composition revealed that wasps of different sizes differed in relative volume of multiple neuropils. The optic lobes and mushroom bodies in particular were smaller in the smallest wasps. Furthermore, smaller brains had a relatively smaller total neuropil volume and larger cellular rind than large brains. These changes in relative brain size and brain architecture suggest that the energetic constraints on brain tissue outweigh specific cognitive requirements in small Nasonia wasps.

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42

Jiang, Ying, Jia Yu Wang, Xiao Fu Huang, Chun Lan Mai y Wen Bo Liao. "Brain size evolution in small mammals: test of the expensive tissue hypothesis". Mammalia 85, n.º 5 (20 de mayo de 2021): 455–61. http://dx.doi.org/10.1515/mammalia-2019-0134.

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Abstract Brain size exhibits significant changes within and between species. Evolution of large brains can be explained by the need to improve cognitive ability for processing more information in changing environments. However, brains are among the most energetically expensive organs. Enlarged brains can impose energetic demands that limit brain size evolution. The expensive tissue hypothesis (ETH) states that a decrease in the size of another expensive tissue, such as the gut, should compensate for the cost of a large brain. We studied the interplay between energetic limitations and brain size evolution in small mammals using phylogenetically generalized least squares (PGLS) regression analysis. Brain mass was not correlated with the length of the digestive tract in 37 species of small mammals after correcting for phylogenetic relationships and body size effects. We further found that the evolution of a large brain was not accompanied by a decrease in male reproductive investments into testes mass and in female reproductive investment into offspring number. The evolution of brain size in small mammals is inconsistent with the prediction of the ETH.

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43

Greene, J. "Left Brain Right Brain". Journal of Neurology, Neurosurgery & Psychiatry 57, n.º 10 (1 de octubre de 1994): 1300. http://dx.doi.org/10.1136/jnnp.57.10.1300-a.

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44

Cahill, Larry. "His Brain, Her Brain". Scientific American 292, n.º 5 (mayo de 2005): 40–47. http://dx.doi.org/10.1038/scientificamerican0505-40.

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45

Cahill, Larry. "His Brain, Her Brain". Scientific American 21, n.º 2s (23 de octubre de 2012): 4–11. http://dx.doi.org/10.1038/scientificamericanbrain0512-4.

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46

Cahill, Larry. "His Brain, Her Brain". Scientific American Mind 20, n.º 3 (mayo de 2009): 40–47. http://dx.doi.org/10.1038/scientificamericanmind0509-40.

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47

Kamal, Arif H. "Left Brain, Right Brain". Journal of Palliative Medicine 15, n.º 8 (agosto de 2012): 951. http://dx.doi.org/10.1089/jpm.2012.0065.

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48

Suilleabháin, Séamus V. Ó. "Left Brain, Right Brain". Irish Educational Studies 5, n.º 2 (enero de 1985): 1–24. http://dx.doi.org/10.1080/0332331850050203.

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49

Larsson, L. "BRAIN DAMAGE, BRAIN REPAIR". Brain 125, n.º 12 (1 de diciembre de 2002): 2785–86. http://dx.doi.org/10.1093/brain/awf266.

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50

Davies, Stephen. "Left brain, right brain". Behaviour Research and Therapy 34, n.º 3 (marzo de 1996): 291. http://dx.doi.org/10.1016/s0005-7967(96)90037-6.

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