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Статті в журналах з теми "Brain wiring"

Автор: Grafiati

Опубліковано: 11 березня 2023

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1

Goulas, A., R. F. Betzel, and C. C. Hilgetag. "Spatiotemporal ontogeny of brain wiring." Science Advances 5, no. 6 (June 2019): eaav9694. http://dx.doi.org/10.1126/sciadv.aav9694.

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Анотація:

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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2

Gluth, S., and L. Fontanesi. "Wiring the altruistic brain." Science 351, no. 6277 (March 3, 2016): 1028–29. http://dx.doi.org/10.1126/science.aaf4688.

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3

Umemori, Hisashi. "Wiring the functional brain." Neuroscience Research 68 (January 2010): e34. http://dx.doi.org/10.1016/j.neures.2010.07.394.

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4

Gordon, Neil. "Wiring of the brain." European Journal of Paediatric Neurology 12, no. 1 (January 2008): 1–3. http://dx.doi.org/10.1016/j.ejpn.2007.10.007.

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5

Peters, Michael A. "Wiring the Global Brain." Educational Philosophy and Theory 52, no. 4 (June 16, 2019): 327–31. http://dx.doi.org/10.1080/00131857.2019.1622413.

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6

Hilgetag, Claus C. "Principles of brain connectivity organization." Behavioral and Brain Sciences 29, no. 1 (February 2006): 18–19. http://dx.doi.org/10.1017/s0140525x06289015.

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Анотація:

Increases of absolute brain size during evolution reinforced stronger structuring of brain connectivity. One consequence is the hierarchical cluster structure of neural systems that combines predominantly short, but not strictly minimal, wiring with short processing pathways. Principles of “large equals well-connected” and “minimal wiring” do not completely account for observed patterns of brain connectivity. A structural model promises better predictions.

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7

Cheng, Shouqiang, Yeonwoo Park, Justyna D. Kurleto, Mili Jeon, Kai Zinn, Joseph W. Thornton, and Engin Özkan. "Family of neural wiring receptors in bilaterians defined by phylogenetic, biochemical, and structural evidence." Proceedings of the National Academy of Sciences 116, no. 20 (May 1, 2019): 9837–42. http://dx.doi.org/10.1073/pnas.1818631116.

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The evolution of complex nervous systems was accompanied by the expansion of numerous protein families, including cell-adhesion molecules, surface receptors, and their ligands. These proteins mediate axonal guidance, synapse targeting, and other neuronal wiring-related functions. Recently, 32 interacting cell surface proteins belonging to two newly defined families of the Ig superfamily (IgSF) in fruit flies were discovered to label different subsets of neurons in the brain and ventral nerve cord. They have been shown to be involved in synaptic targeting and morphogenesis, retrograde signaling, and neuronal survival. Here, we show that these proteins, Dprs and DIPs, are members of a widely distributed family of two- and three-Ig domain molecules with neuronal wiring functions, which we refer to as Wirins. Beginning from a single ancestral Wirin gene in the last common ancestor of Bilateria, numerous gene duplications produced the heterophilic Dprs and DIPs in protostomes, along with two other subfamilies that diversified independently across protostome phyla. In deuterostomes, the ancestral Wirin evolved into the IgLON subfamily of neuronal receptors. We show that IgLONs interact with each other and that their complexes can be broken by mutations designed using homology models based on Dpr and DIP structures. The nematode orthologs ZIG-8 and RIG-5 also form heterophilic and homophilic complexes, and crystal structures reveal numerous apparently ancestral features shared with Dpr-DIP complexes. The evolutionary, biochemical, and structural relationships we demonstrate here provide insights into neural development and the rise of the metazoan nervous system.

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8

Rubinov, Mikail, Rolf J. F. Ypma, Charles Watson, and Edward T. Bullmore. "Wiring cost and topological participation of the mouse brain connectome." Proceedings of the National Academy of Sciences 112, no. 32 (July 27, 2015): 10032–37. http://dx.doi.org/10.1073/pnas.1420315112.

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Brain connectomes are topologically complex systems, anatomically embedded in 3D space. Anatomical conservation of “wiring cost” explains many but not all aspects of these networks. Here, we examined the relationship between topology and wiring cost in the mouse connectome by using data from 461 systematically acquired anterograde-tracer injections into the right cortical and subcortical regions of the mouse brain. We estimated brain-wide weights, distances, and wiring costs of axonal projections and performed a multiscale topological and spatial analysis of the resulting weighted and directed mouse brain connectome. Our analysis showed that the mouse connectome has small-world properties, a hierarchical modular structure, and greater-than-minimal wiring costs. High-participation hubs of this connectome mediated communication between functionally specialized and anatomically localized modules, had especially high wiring costs, and closely corresponded to regions of the default mode network. Analyses of independently acquired histological and gene-expression data showed that nodal participation colocalized with low neuronal density and high expression of genes enriched for cognition, learning and memory, and behavior. The mouse connectome contains high-participation hubs, which are not explained by wiring-cost minimization but instead reflect competitive selection pressures for integrated network topology as a basis for higher cognitive and behavioral functions.

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9

Purnell, B. A. "Wiring the developing insect brain." Science 344, no. 6188 (June 5, 2014): 1128. http://dx.doi.org/10.1126/science.344.6188.1128-o.

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10

Richards, Linda J. "ISDN2012_0275: Wiring the developing brain." International Journal of Developmental Neuroscience 30, no. 8 (December 2012): 637. http://dx.doi.org/10.1016/j.ijdevneu.2012.10.097.

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11

Miyamichi, Kazunari, and Liqun Luo. "Brain Wiring by Presorting Axons." Science 325, no. 5940 (July 30, 2009): 544–45. http://dx.doi.org/10.1126/science.1178117.

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12

Hiesinger, P. Robin. "Brain wiring with composite instructions." BioEssays 43, no. 1 (November 4, 2020): 2000166. http://dx.doi.org/10.1002/bies.202000166.

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13

Song, Yuru, Douglas Zhou, and Songting Li. "Maximum Entropy Principle Underlies Wiring Length Distribution in Brain Networks." Cerebral Cortex 31, no. 10 (May 17, 2021): 4628–41. http://dx.doi.org/10.1093/cercor/bhab110.

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Abstract A brain network comprises a substantial amount of short-range connections with an admixture of long-range connections. The portion of long-range connections in brain networks is observed to be quantitatively dissimilar across species. It is hypothesized that the length of connections is constrained by the spatial embedding of brain networks, yet fundamental principles that underlie the wiring length distribution remain unclear. By quantifying the structural diversity of a brain network using Shannon’s entropy, here we show that the wiring length distribution across multiple species—including Drosophila, mouse, macaque, human, and C. elegans—follows the maximum entropy principle (MAP) under the constraints of limited wiring material and the spatial locations of brain areas or neurons. In addition, by considering stochastic axonal growth, we propose a network formation process capable of reproducing wiring length distributions of the 5 species, thereby implementing MAP in a biologically plausible manner. We further develop a generative model incorporating MAP, and show that, for the 5 species, the generated network exhibits high similarity to the real network. Our work indicates that the brain connectivity evolves to be structurally diversified by maximizing entropy to support efficient interareal communication, providing a potential organizational principle of brain networks.

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14

Mehta, Sharan Kaur, Christopher P. Scheitle, and Elaine Howard Ecklund. "Can Religiosity Be Explained by ‘Brain Wiring’? An Analysis of US Adults’ Opinions." Religions 10, no. 10 (October 19, 2019): 586. http://dx.doi.org/10.3390/rel10100586.

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Studies examining how religion shapes individuals’ attitudes about science have focused heavily on a narrow range of topics, such as evolution. This study expands this literature by looking at how religion influences individuals’ attitudes towards the claim that neuroscience, or “brain wiring,” can explain differences in religiosity. Our analysis of nationally representative survey data shows, perhaps unsurprisingly, that religiosity is negatively associated with thinking that brain wiring can explain religion. Net of religiosity, though, individuals reporting religious experiences are actually more likely to agree that brain wiring can explain religiosity, as are individuals belonging to diverse religious traditions when compared to the unaffiliated. We also find that belief in the general explanatory power of science is a significant predictor of thinking that religiosity can be explained by brain wiring, while women and the more highly educated are less likely to think this is true. Taken together, these findings have implications for our understanding of the relationship between religion and science, and the extent to which neuroscientific explanations of religiosity are embraced by the general US public.

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15

Barberis, Sergio Daniel. "Wiring optimization explanation in neuroscience: What is special about it?" THEORIA. An International Journal for Theory, History and Foundations of Science 34, no. 1 (April 11, 2019): 89. http://dx.doi.org/10.1387/theoria.18148.

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This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the target system.

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16

Sati, Aisha, Melanie Prescott, Christine Louise Jasoni, Elodie Desroziers, and Rebecca Elaine Campbell. "The Role of Microglia in the Polycystic Ovary Syndrome (PCOS)-Like Brain." Journal of the Endocrine Society 5, Supplement_1 (May 1, 2021): A556. http://dx.doi.org/10.1210/jendso/bvab048.1133.

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Abstract Polycystic ovary syndrome (PCOS) is the most common cause of anovulatory infertility, affecting roughly 1 in 8 women of reproductive age. Accumulating evidence from animal models suggests that the brain plays a key role in the development and maintenance of PCOS. In a well-characterised prenatally androgenised (PNA) mouse model of PCOS, aberrant neuronal wiring associated with PCOS deficits in adulthood are detected as early as postnatal day (P) 25, prior to disease onset. However, the mechanisms by which prenatal androgen exposure alters brain wiring remains unknown. Microglia, the immune cells of the brain, are active sculptors of neuronal wiring across development, mediating both the formation and removal of neuronal inputs. Therefore, microglia may play an important role in driving the abnormal neuronal wiring that leads to PCOS-like features in the PNA brain. Here, to assess whether microglia are altered in the brain of PNA mice, microglia number and morphology-associated activation states were quantified in two hypothalamic regions implicated in fertility regulation. Microglia were identified by immunolabelling for the microglia-specific marker, Iba-1, across developmental timepoints, including embryonic day 17.5, P0, P25, P40 and P60 (n = 7–14/group). At P0, PNA mice had significantly fewer “activated” amoeboid microglia compared to controls (P < 0.05). Later in development at P25, PNA mice exhibited significantly fewer “sculpting” microglia (P < 0.001), whereas at P60, PNA mice possessed a greater number of “activated” amoeboid microglia relative to controls (P < 0.01). This study demonstrates time-specific changes in the number and morphology of microglia in a mouse model of PCOS and suggests a role for microglia in driving the brain wiring abnormalities associated with PCOS. These findings support the need for future functional experiments to determine the relative importance of microglia function in shaping the PCOS-like brain and associated reproductive dysfunction.

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17

Chklovskii, Dmitri B. "Exact Solution for the Optimal Neuronal Layout Problem." Neural Computation 16, no. 10 (October 1, 2004): 2067–78. http://dx.doi.org/10.1162/0899766041732422.

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Evolution perfected brain design by maximizing its functionality while minimizing costs associated with building and maintaining it. Assumption that brain functionality is specified by neuronal connectivity, implemented by costly biological wiring, leads to the following optimal design problem. For a given neuronal connectivity, find a spatial layout of neurons that minimizes the wiring cost. Unfortunately, this problem is difficult to solve because the number of possible layouts is often astronomically large. We argue that the wiring cost may scale as wire length squared, reducing the optimal layout problem to a constrained minimization of a quadratic form. For biologically plausible constraints, this problem has exact analytical solutions, which give reasonable approximations to actual layouts in the brain. These solutions make the inverse problem of inferring neuronal connectivity from neuronal layout more tractable.

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18

Linneweber, Gerit Arne, Maheva Andriatsilavo, Suchetana Bias Dutta, Mercedes Bengochea, Liz Hellbruegge, Guangda Liu, Radoslaw K. Ejsmont, et al. "A neurodevelopmental origin of behavioral individuality in the Drosophila visual system." Science 367, no. 6482 (March 5, 2020): 1112–19. http://dx.doi.org/10.1126/science.aaw7182.

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The genome versus experience dichotomy has dominated understanding of behavioral individuality. By contrast, the role of nonheritable noise during brain development in behavioral variation is understudied. Using Drosophila melanogaster, we demonstrate a link between stochastic variation in brain wiring and behavioral individuality. A visual system circuit called the dorsal cluster neurons (DCN) shows nonheritable, interindividual variation in right/left wiring asymmetry and controls object orientation in freely walking flies. We show that DCN wiring asymmetry instructs an individual’s object responses: The greater the asymmetry, the better the individual orients toward a visual object. Silencing DCNs abolishes correlations between anatomy and behavior, whereas inducing DCN asymmetry suffices to improve object responses.

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19

Travis, John. "Brain Wiring Depends on Multifaceted Gene." Science News 157, no. 26 (June 24, 2000): 406. http://dx.doi.org/10.2307/4012540.

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20

Zilles, K., and K. Amunts. "Segregation and Wiring in the Brain." Science 335, no. 6076 (March 29, 2012): 1582–84. http://dx.doi.org/10.1126/science.1221366.

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21

Penn, A. A. "Early Brain Wiring: Activity-Dependent Processes." Schizophrenia Bulletin 27, no. 3 (January 1, 2001): 337–47. http://dx.doi.org/10.1093/oxfordjournals.schbul.a006880.

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22

Archer, Ruth. "Brain wiring explains sex differences inDrosophilabehaviour." Journal of Experimental Biology 219, no. 23 (November 30, 2016): 3675. http://dx.doi.org/10.1242/jeb.130369.

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23

Dickson, B. J. "DEVELOPMENT: Wiring the Brain with Insulin." Science 300, no. 5618 (April 18, 2003): 440–41. http://dx.doi.org/10.1126/science.1084513.

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24

Meckel, Katherine R., and Drew D. Kiraly. "Maternal microbes support fetal brain wiring." Nature 586, no. 7828 (September 23, 2020): 203–5. http://dx.doi.org/10.1038/d41586-020-02657-y.

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25

Buzsáki, György. "Electrical Wiring of the Oscillating Brain." Neuron 31, no. 3 (August 2001): 342–44. http://dx.doi.org/10.1016/s0896-6273(01)00378-6.

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26

Hirano, Shinji, and Masatoshi Takeichi. "Cadherins in Brain Morphogenesis and Wiring." Physiological Reviews 92, no. 2 (April 2012): 597–634. http://dx.doi.org/10.1152/physrev.00014.2011.

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Cadherins are Ca2+-dependent cell-cell adhesion molecules that play critical roles in animal morphogenesis. Various cadherin-related molecules have also been identified, which show diverse functions, not only for the regulation of cell adhesion but also for that of cell proliferation and planar cell polarity. During the past decade, understanding of the roles of these molecules in the nervous system has significantly progressed. They are important not only for the development of the nervous system but also for its functions and, in turn, for neural disorders. In this review, we discuss the roles of cadherins and related molecules in neural development and function in the vertebrate brain.

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27

Wernet, Mathias F., and Claude Desplan. "Brain Wiring in the Fourth Dimension." Cell 162, no. 1 (July 2015): 20–22. http://dx.doi.org/10.1016/j.cell.2015.06.040.

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28

Murcia-Belmonte, Verónica, and Lynda Erskine. "Wiring the Binocular Visual Pathways." International Journal of Molecular Sciences 20, no. 13 (July 4, 2019): 3282. http://dx.doi.org/10.3390/ijms20133282.

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Retinal ganglion cells (RGCs) extend axons out of the retina to transmit visual information to the brain. These connections are established during development through the navigation of RGC axons along a relatively long, stereotypical pathway. RGC axons exit the eye at the optic disc and extend along the optic nerves to the ventral midline of the brain, where the two nerves meet to form the optic chiasm. In animals with binocular vision, the axons face a choice at the optic chiasm—to cross the midline and project to targets on the contralateral side of the brain, or avoid crossing the midline and project to ipsilateral brain targets. Ipsilaterally and contralaterally projecting RGCs originate in disparate regions of the retina that relate to the extent of binocular overlap in the visual field. In humans virtually all RGC axons originating in temporal retina project ipsilaterally, whereas in mice, ipsilaterally projecting RGCs are confined to the peripheral ventrotemporal retina. This review will discuss recent advances in our understanding of the mechanisms regulating specification of ipsilateral versus contralateral RGCs, and the differential guidance of their axons at the optic chiasm. Recent insights into the establishment of congruent topographic maps in both brain hemispheres also will be discussed.

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29

Paolicelli, Rosa C., and Cornelius T. Gross. "Microglia in development: linking brain wiring to brain environment." Neuron Glia Biology 7, no. 1 (February 2011): 77–83. http://dx.doi.org/10.1017/s1740925x12000105.

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Microglia are enigmatic non-neuronal cells that infiltrate and take up residence in the brain during development and are thought to perform a surveillance function. An established literature has documented how microglia are activated by pathogenic stimuli and how they contribute to and resolve injuries to the brain. However, much less work has been aimed at understanding their function in the uninjured brain. A series of recent in vivo imaging studies shows that microglia in their resting state are highly motile and actively survey their neuronal surroundings. Furthermore, new data suggest that microglia in their resting state are able to phagocytose unwanted synapses and in this way contribute to synaptic pruning and maturation during development. Coupled with their exquisite sensitivity to pathogenic stimuli, these data suggest that microglia form a link that couples changes in brain environment to changes in brain wiring. Here we discuss this hypothesis and propose a model for the role of microglia during development in sculpting brain connectivity.

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30

Chen, Yuhan, Qixiang Lin, Xuhong Liao, Changsong Zhou, and Yong He. "Association of aerobic glycolysis with the structural connectome reveals a benefit–risk balancing mechanism in the human brain." Proceedings of the National Academy of Sciences 118, no. 1 (December 21, 2020): e2013232118. http://dx.doi.org/10.1073/pnas.2013232118.

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Aerobic glycolysis (AG), that is, the nonoxidative metabolism of glucose, contributes significantly to anabolic pathways, rapid energy generation, task-induced activity, and neuroprotection; yet high AG is also associated with pathological hallmarks such as amyloid-β deposition. An important yet unresolved question is whether and how the metabolic benefits and risks of brain AG is structurally shaped by connectome wiring. Using positron emission tomography and magnetic resonance imaging techniques as well as computational models, we investigate the relationship between brain AG and the macroscopic connectome. Specifically, we propose a weighted regional distance-dependent model to estimate the total axonal projection length of a brain node. This model has been validated in a macaque connectome derived from tract-tracing data and shows a high correspondence between experimental and estimated axonal lengths. When applying this model to the human connectome, we find significant associations between the estimated total axonal projection length and AG across brain nodes, with higher levels primarily located in the default-mode and prefrontal regions. Moreover, brain AG significantly mediates the relationship between the structural and functional connectomes. Using a wiring optimization model, we find that the estimated total axonal projection length in these high-AG regions exhibits a high extent of wiring optimization. If these high-AG regions are randomly rewired, their total axonal length and vulnerability risk would substantially increase. Together, our results suggest that high-AG regions have expensive but still optimized wiring cost to fulfill metabolic requirements and simultaneously reduce vulnerability risk, thus revealing a benefit–risk balancing mechanism in the human brain.

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31

Simon-Martinez, Cristina, Ellen Jaspers, Lisa Mailleux, Els Ortibus, Katrijn Klingels, Nicole Wenderoth, and Hilde Feys. "Corticospinal Tract Wiring and Brain Lesion Characteristics in Unilateral Cerebral Palsy: Determinants of Upper Limb Motor and Sensory Function." Neural Plasticity 2018 (September 13, 2018): 1–13. http://dx.doi.org/10.1155/2018/2671613.

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Brain lesion characteristics (timing, location, and extent) and the type of corticospinal tract (CST) wiring have been proposed as determinants of upper limb (UL) motor function in unilateral cerebral palsy (uCP), yet an investigation of the relative combined impact of these factors on both motor and sensory functions is still lacking. Here, we first investigated whether structural brain lesion characteristics could predict the underlying CST wiring and we explored the role of CST wiring and brain lesion characteristics to predict UL motor and sensory functions in uCP. Fifty-two participants with uCP (mean age (SD): 11 y and 3 m (3 y and 10 m)) underwent a single-pulse Transcranial Magnetic Stimulation session to determine CST wiring between the motor cortex and the more affected hand (n=17 contralateral, n=19 ipsilateral, and n=16 bilateral) and an MRI to determine lesion timing (n=34 periventricular (PV) lesion, n=18 corticosubcortical (CSC) lesion), location, and extent. Lesion location and extent were evaluated with a semiquantitative scale. A standardized protocol included UL motor (grip strength, unimanual capacity, and bimanual performance) and sensory measures. A combination of lesion locations (damage to the PLIC and frontal lobe) significantly contributed to differentiate between the CST wiring groups, reclassifying the participants in their original group with 57% of accuracy. Motor and sensory functions were influenced by each of the investigated neurological factors. However, multiple regression analyses showed that motor function was predicted by the CST wiring (more preserved in individuals with contralateral CST (p<0.01)), lesion extent, and damage to the basal ganglia and thalamus. Sensory function was predicted by the combination of a large and later lesion and an ipsilateral or bilateral CST wiring, which led to increased sensory deficits (p<0.05). These novel insights contribute to a better understanding of the underlying pathophysiology of UL function and may be useful to delineate individualized treatment strategies.

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32

Paquola, Casey, Jakob Seidlitz, Oualid Benkarim, Jessica Royer, Petr Klimes, Richard A. I. Bethlehem, Sara Larivière, et al. "A multi-scale cortical wiring space links cellular architecture and functional dynamics in the human brain." PLOS Biology 18, no. 11 (November 30, 2020): e3000979. http://dx.doi.org/10.1371/journal.pbio.3000979.

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Анотація:

The vast net of fibres within and underneath the cortex is optimised to support the convergence of different levels of brain organisation. Here, we propose a novel coordinate system of the human cortex based on an advanced model of its connectivity. Our approach is inspired by seminal, but so far largely neglected models of cortico–cortical wiring established by postmortem anatomical studies and capitalises on cutting-edge in vivo neuroimaging and machine learning. The new model expands the currently prevailing diffusion magnetic resonance imaging (MRI) tractography approach by incorporation of additional features of cortical microstructure and cortico–cortical proximity. Studying several datasets and different parcellation schemes, we could show that our coordinate system robustly recapitulates established sensory-limbic and anterior–posterior dimensions of brain organisation. A series of validation experiments showed that the new wiring space reflects cortical microcircuit features (including pyramidal neuron depth and glial expression) and allowed for competitive simulations of functional connectivity and dynamics based on resting-state functional magnetic resonance imaging (rs-fMRI) and human intracranial electroencephalography (EEG) coherence. Our results advance our understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human brain organisation. Our evaluations demonstrate the cortical wiring space bridges across scales of neural organisation and can be easily translated to single individuals.

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33

Grange, Pascal. "Topology of the mesoscale connectome of the mouse brain." Computational and Mathematical Biophysics 8, no. 1 (October 27, 2020): 126–40. http://dx.doi.org/10.1515/cmb-2020-0106.

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AbstractThe wiring diagram of the mouse brain has recently been mapped at a mesoscopic scale in the Allen Mouse Brain Connectivity Atlas. Axonal projections from brain regions were traced using green fluoresent proteins. The resulting data were registered to a common three-dimensional reference space. They yielded a matrix of connection strengths between 213 brain regions. Global features such as closed loops formed by connections of similar intensity can be inferred using tools from persistent homology. We map the wiring diagram of the mouse brain to a simplicial complex (filtered by connection strengths). We work out generators of the first homology group. Some regions, including nucleus accumbens, are connected to the entire brain by loops, whereas no region has non-zero connection strength to all brain regions. Thousands of loops go through the isocortex, the striatum and the thalamus. On the other hand, medulla is the only major brain compartment that contains more than 100 loops.

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34

Drew, Liam. "Wiring up the brain to beat depression." Nature 608, no. 7924 (August 24, 2022): S46—S47. http://dx.doi.org/10.1038/d41586-022-02209-6.

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35

Strickland, Eliza. "A wiring diagram of the brain [News]." IEEE Spectrum 50, no. 5 (May 2013): 12–14. http://dx.doi.org/10.1109/mspec.2013.6511089.

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36

Hamann, Stephan. "Blue genes: wiring the brain for depression." Nature Neuroscience 8, no. 6 (June 2005): 701–3. http://dx.doi.org/10.1038/nn0605-701.

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37

Barinaga, M. "Neurobiology: New Clue to Brain Wiring Mystery." Science 270, no. 5236 (October 27, 1995): 581. http://dx.doi.org/10.1126/science.270.5236.581.

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38

Bendriem, Raphael M., and M. Elizabeth Ross. "Wiring the Human Brain: A User’s Handbook." Neuron 95, no. 3 (August 2017): 482–85. http://dx.doi.org/10.1016/j.neuron.2017.07.008.

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39

Laino, Charlene. "FAULTY WIRING IN BRAIN MAY CAUSE STUTTERING." Neurology Today 3, no. 6 (June 2003): 24–27. http://dx.doi.org/10.1097/00132985-200306000-00013.

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40

Rubenstein, John L. R. "Major progress towards elucidating brain wiring diagrams." Journal of Comparative Neurology 522, no. 9 (April 19, 2014): 1987–88. http://dx.doi.org/10.1002/cne.23586.

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41

Chiêm, Benjamin, Frédéric Crevecoeur, and Jean-Charles Delvenne. "Structure-informed functional connectivity driven by identifiable and state-specific control regions." Network Neuroscience 5, no. 2 (2021): 591–613. http://dx.doi.org/10.1162/netn_a_00192.

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Анотація:

Abstract Describing how the brain anatomical wiring contributes to the emergence of coordinated neural activity underlying complex behavior remains challenging. Indeed, patterns of remote coactivations that adjust with the ongoing task-demand do not systematically match direct, static anatomical links. Here, we propose that observed coactivation patterns, known as functional connectivity (FC), can be explained by a controllable linear diffusion dynamics defined on the brain architecture. Our model, termed structure-informed FC, is based on the hypothesis that different sets of brain regions controlling the information flow on the anatomical wiring produce state-specific functional patterns. We thus introduce a principled framework for the identification of potential control centers in the brain. We find that well-defined, sparse, and robust sets of control regions, partially overlapping across several tasks and resting state, produce FC patterns comparable to empirical ones. Our findings suggest that controllability is a fundamental feature allowing the brain to reach different states.

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42

Coletta, Ludovico, Marco Pagani, Jennifer D. Whitesell, Julie A. Harris, Boris Bernhardt, and Alessandro Gozzi. "Network structure of the mouse brain connectome with voxel resolution." Science Advances 6, no. 51 (December 2020): eabb7187. http://dx.doi.org/10.1126/sciadv.abb7187.

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Fine-grained descriptions of brain connectivity are required to understand how neural information is processed and relayed across spatial scales. Previous investigations of the mouse brain connectome have used discrete anatomical parcellations, limiting spatial resolution and potentially concealing network attributes critical to connectome organization. Here, we provide a voxel-level description of the network and hierarchical structure of the directed mouse connectome, unconstrained by regional partitioning. We report a number of previously unappreciated organizational principles in the mammalian brain, including a directional segregation of hub regions into neural sink and sources, and a strategic wiring of neuromodulatory nuclei as connector hubs and critical orchestrators of network communication. We also find that the mouse cortical connectome is hierarchically organized along two superimposed cortical gradients reflecting unimodal-transmodal functional processing and a modality-specific sensorimotor axis, recapitulating a phylogenetically conserved feature of higher mammals. These findings advance our understanding of the foundational wiring principles of the mammalian connectome.

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Shah, Apurva, Abhishek Lenka, Jitender Saini, Shivali Wagle, Rajini M. Naduthota, Ravi Yadav, Pramod Kumar Pal, and Madhura Ingalhalikar. "Altered Brain Wiring in Parkinson's Disease: A Structural Connectome-Based Analysis." Brain Connectivity 7, no. 6 (August 2017): 347–56. http://dx.doi.org/10.1089/brain.2017.0506.

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44

Xie, Yajun, and Corey Harwell. "Attraction and repulsion cooperate during brain-circuit wiring." Nature 594, no. 7863 (June 4, 2021): 341–43. http://dx.doi.org/10.1038/d41586-021-01502-0.

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45

Chedotal, A., and L. J. Richards. "Wiring the Brain: The Biology of Neuronal Guidance." Cold Spring Harbor Perspectives in Biology 2, no. 6 (May 12, 2010): a001917. http://dx.doi.org/10.1101/cshperspect.a001917.

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46

Zipursky, S. Lawrence, Woj M. Wojtowicz, and Daisuke Hattori. "Got diversity? Wiring the fly brain with Dscam." Trends in Biochemical Sciences 31, no. 10 (October 2006): 581–88. http://dx.doi.org/10.1016/j.tibs.2006.08.003.

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47

Song, Qiong, and Joseph G. Gleeson. "Primary Cilia and Brain Wiring, Connecting the Dots." Developmental Cell 51, no. 6 (December 2019): 661–63. http://dx.doi.org/10.1016/j.devcel.2019.11.017.

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48

Bi, Yanchao, and Yong He. "Connectomics Reveals Faulty Wiring Patterns for Depressed Brain." Biological Psychiatry 76, no. 7 (October 2014): 515–16. http://dx.doi.org/10.1016/j.biopsych.2014.07.002.

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49

Melozzi, Francesca, Eyal Bergmann, Julie A. Harris, Itamar Kahn, Viktor Jirsa, and Christophe Bernard. "Individual structural features constrain the mouse functional connectome." Proceedings of the National Academy of Sciences 116, no. 52 (December 11, 2019): 26961–69. http://dx.doi.org/10.1073/pnas.1906694116.

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Анотація:

Whole brain dynamics intuitively depend upon the internal wiring of the brain; but to which extent the individual structural connectome constrains the corresponding functional connectome is unknown, even though its importance is uncontested. After acquiring structural data from individual mice, we virtualized their brain networks and simulated in silico functional MRI data. Theoretical results were validated against empirical awake functional MRI data obtained from the same mice. We demonstrate that individual structural connectomes predict the functional organization of individual brains. Using a virtual mouse brain derived from the Allen Mouse Brain Connectivity Atlas, we further show that the dominant predictors of individual structure–function relations are the asymmetry and the weights of the structural links. Model predictions were validated experimentally using tracer injections, identifying which missing connections (not measurable with diffusion MRI) are important for whole brain dynamics in the mouse. Individual variations thus define a specific structural fingerprint with direct impact upon the functional organization of individual brains, a key feature for personalized medicine.

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50

Levitt, James J., Paul G. Nestor, Marek Kubicki, Amanda E. Lyall, Fan Zhang, Tammy Riklin-Raviv, Lauren J. O′Donnell, Robert W. McCarley, Martha E. Shenton, and Yogesh Rathi. "Miswiring of Frontostriatal Projections in Schizophrenia." Schizophrenia Bulletin 46, no. 4 (January 28, 2020): 990–98. http://dx.doi.org/10.1093/schbul/sbz129.

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Abstract We investigated brain wiring in chronic schizophrenia and healthy controls in frontostriatal circuits using diffusion magnetic resonance imaging tractography in a novel way. We extracted diffusion streamlines in 27 chronic schizophrenia and 26 healthy controls connecting 4 frontal subregions to the striatum. We labeled the projection zone striatal surface voxels into 2 subtypes: dominant-input from a single cortical subregion, and, functionally integrative, with mixed-input from diverse cortical subregions. We showed: 1) a group difference for total striatal surface voxel number (P = .045) driven by fewer mixed-input voxels in the left (P = .007), but not right, hemisphere; 2) a group by hemisphere interaction for the ratio quotient between voxel subtypes (P = .04) with a left (P = .006), but not right, hemisphere increase in schizophrenia, also reflecting fewer mixed-input voxels; and 3) fewer mixed-input voxel counts in schizophrenia (P = .045) driven by differences in left hemisphere limbic (P = .007) and associative (P = .01), but not sensorimotor, striatum. These results demonstrate a less integrative pattern of frontostriatal structural connectivity in chronic schizophrenia. A diminished integrative pattern yields a less complex input pattern to the striatum from the cortex with less circuit integration at the level of the striatum. Further, as brain wiring occurs during early development, aberrant brain wiring could serve as a developmental biomarker for schizophrenia.

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