Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat

[EN] Connectomics data from animal models provide an invaluable opportunity to reveal the complex interplay between structure and function in the mammalian brain. In this work, we investigate the relationship between structural and functional connectivity in the rat brain cortex using a directed anatomical network generated from a carefully curated meta-analysis of published tracing data, along with resting-state functional MRI data obtained from a group of 14 anesthetized Wistar rats. We found a high correspondence between the strength of functional connections, measured as blood oxygen level dependent (BOLD) signal correlations between cortical regions, and the weight of the corresponding anatomical links in the connectome graph (maximum Spearman rank-order correlation rho = 0.48). At the network-level, regions belonging to the same functionally defined community tend to form more mutual weighted connections between each other compared to regions located in different communities. We further found that functional communities in resting-state networks are enriched in densely connected anatomical motifs. Importantly, these higher-order structural subgraphs cannot be explained by lower-order topological properties, suggesting that dense structural patterns support functional associations in the resting brain. Simulations of brain-wide resting-state activity based on neural mass models implemented on the empirical rat anatomical connectome demonstrated high correlation between the simulated and the measured functional connectivity (maximum Pearson correlation rho = 0: 53), further suggesting that the topology of structural connections plays an important role in shaping functional cortical networks.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-1-R (S.C) and BFU2015-64380-C2-2-R (D.M.) and EU Horizon 2020 Program 668863-SyBil-AA grant (S.C.). S.C. acknowledges financial support from the Spanish State Research Agency, through the "Severo Ochoa" Programme for Centres of Excellence in R&D (ref. SEV-2013-0317). A. D.-P., was supported by grant FPU13/01475 from the Spanish Ministerio de Educacion, Cultura y Deporte (MECD). O.S. acknowledges support by the J.S. McDonnell Foundation (#220020387) and the National Institutes of Health (NIH R01 AT009036-01). We are also grateful to Andrea Avena-Koenigsberger and Begona Fernandez for their technical support.Díaz-Parra, A.; Osborn, Z.; Canals Gamoneda, S.; Moratal, D.; Sporns, O. (2017). Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat. NeuroImage. 159:170-184. https://doi.org/10.1016/j.neuroimage.2017.07.046S17018415

RATT: RFID Assisted Tracking Tile. Preliminary results

© 2017 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Behavior is one of the most important aspects of animal life. This behavior depends on the link between animals, their nervous systems and their environment. In order to study the behavior of laboratory animals several tools are needed, but a tracking tool is essential to perform a thorough behavioral study. Currently, several visual tracking tools are available. However, they have some drawbacks. For instance, when an animal is inside a cave, or is close to other animals, the tracking cameras cannot always detect the location or movement of this animal. This paper presents RFID Assisted Tracking Tile (RATT), a tracking system based on passive Radio Frequency Identification (RFID) technology in high frequency band according to ISO/IEC 15693. The RATT system is composed of electronic tiles that have nine active RFID antennas attached; in addition, it contains several overlapping passive coils to improve the magnetic field characteristics. Using several tiles, a large surface can be built on which the animals can move, allowing identification and tracking of their movements. This system, that could also be combined with a visual tracking system, paves the way for complete behavioral studies.Research supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-2-R and BFU2015-64380-C2-1-R. Santiago Canals acknowledges financial support from the Spanish State Research Agency, through the "Severo Ochoa" Programme for Centres of Excellence in R&D (ref. SEV-2013-0317). Dario R. Quinones is supported by grant Ayudas para la formacion de personal investigador (FPI) from Universitat Politecnica de Valencia.Quiñones, DR.; Cuevas-López, A.; Cambra-Enguix J.; Canals-Gamoneda, S.; Moratal, D. (2017). RATT: RFID Assisted Tracking Tile. Preliminary results. Proceedings Intenational Anual Conference of IEEE Engineering in Medicine and Biology Society. 4114-4117. https://doi.org/10.1109/EMBC.2017.8037761S4114411

Automatic positioning device for cutting three-dimensional tissue in living or fixed samples. Proof of concept

"© 2017 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."[EN] The study and analysis of tissues has always been an important part of the subject in biology. For this reason, obtaining specimens of tissue has been vital to morphological and functionality research. Historically, the main tools used to obtain slices of tissue have been microtomes and vibratomes. However, they are largely unsatisfactory. This is because it is impossible to obtain a full, three-dimensional structure of a tissue sample with these devices. This paper presents an automatic positioning device for a three-dimensional cut in living or fixed tissue samples, which can be applied mainly in histology, anatomy, biochemistry and pharmacology. The system consists of a platform on which the tissue samples can be deposited, plus two containers. An electromechanical system with motors and gears gives the platform the ability to change the orientation of a sample. These orientation changes were tested with movement sensors to ensure that accurate changes were made. This device paves the way for researchers to make cuts in the sample tissue along different planes and in different directions by maximizing the surface of the tract that appears in a slice.Research supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-2-R and BFU2015-64380-C2-1-R. Santiago Canals acknowledges financial support from the Spanish State Research Agency, through the "Severo Ochoa" Programme for Centres of Excellence in R&D (ref. SEV- 2013-0317). Dario Quinones is supported by grant Ayudas para la formacion de personal investigador (FPI) from Universitat Politecnica de Valencia. We are grateful to Begoña Fernández (Neuroscience Institute, Consejo Superior de Investigaciones Científicas - CSIC, Alicante, Spain) for her excellent technical assistance.Quiñones, DR.; Pérez Feito, R.; García Manrique, JA.; Canals-Gamoneda, S.; Moratal, D. (2017). Automatic positioning device for cutting three-dimensional tissue in living or fixed samples. Proof of concept. Proceedings Intenational Anual Conference of IEEE Engineering in Medicine and Biology Society. 1372-1375. https://doi.org/10.1109/EMBC.2017.8037088S1372137

Dispositivo automático de posicionamiento para corte de tejido tridimensional en una muestra, vibrátomo que lo comprende y su uso

La presente invención se refiere a un dispositivo automático de posicionamiento para corte de tejido tridimensional, en una muestra de tejido viva o fijada caracterizado porque al menos comprende: - una plataforma (1) para depositar las muestras de tejido - un subsistema electromecánico que al menos comprende - un primer motor (2) y primeros medios mecánicos que imprimen un movimiento angular a la plataforma (1) - un segundo motor (3) y segundos medios mecánicos que imprimen un movimiento de inclinación de la plataforma (1) a un vibrátomo que comprende este dispositivo de posicionamiento, y a su uso en histología, anatomía, neurociencia, bioquímica o farmacología.Peer reviewedUniversitat Politécnica de Valencia, Consejo Superior de Investigaciones CientíficasA1 Solicitud de adición a la patent

A Tangible Educative 3D Printed Atlas of the Rat Brain

[EN] In biology and neuroscience courses, brain anatomy is usually explained using Magnetic Resonance (MR) images or histological sections of different orientations. These can show the most important macroscopic areas in an animals¿ brain. However, this method is neither dynamic nor intuitive. In this work, an anatomical 3D printed rat brain with educative purposes is presented. Hand manipulation of the structure, facilitated by the scale up of its dimensions, and the ability to dismantle the ¿brain¿ into some of its constituent parts, facilitates the understanding of the 3D organization of the nervous system. This is an alternative method for teaching students in general and biologists in particular the rat brain anatomy. The 3D printed rat brain has been developed with eight parts, which correspond to the most important divisions of the brain. Each part has been fitted with interconnections, facilitating assembling and disassembling as required. These solid parts were smoothed out, modified and manufactured through 3D printing techniques with poly(lactic acid) (PLA). This work presents a methodology that could be expanded to almost any field of clinical and pre-clinical research, and moreover it avoids the need for dissecting animals to teach brain anatomy.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-2-R (D.M.) and BFU2015-64380-C2-1-R and EU Horizon 2020 Program 668863-SyBil-AA grant (S.C.). S.C. acknowledges financial support from the Spanish State Research Agency, through the "Severo Ochoa" Programme for Centres of Excellence in R&D (ref. SEV-2013-0317). D.R.Q. was supported by grant "Ayudas para la formacion de personal investigador (FPI)" from the Vicerrectorado de Investigacion, Innovacion y Transferencia of the Universitat Politecnica de Valencia.Quiñones, DR.; Ferragud-Agulló, J.; Pérez Feito, R.; García Manrique, JA.; Canals-Gamoneda, S.; Moratal, D. (2018). A Tangible Educative 3D Printed Atlas of the Rat Brain. Materials. 11(9):1531-1542. https://doi.org/10.3390/ma11091531S15311542119Perrin, R. J., Fagan, A. M., & Holtzman, D. M. (2009). Multimodal techniques for diagnosis and prognosis of Alzheimer’s disease. Nature, 461(7266), 916-922. doi:10.1038/nature08538Linden, D. E. J. (2012). The Challenges and Promise of Neuroimaging in Psychiatry. Neuron, 73(1), 8-22. doi:10.1016/j.neuron.2011.12.014Teipel, S., Drzezga, A., Grothe, M. J., Barthel, H., Chételat, G., Schuff, N., … Fellgiebel, A. (2015). Multimodal imaging in Alzheimer’s disease: validity and usefulness for early detection. The Lancet Neurology, 14(10), 1037-1053. doi:10.1016/s1474-4422(15)00093-9Woo, C.-W., Chang, L. J., Lindquist, M. A., & Wager, T. D. (2017). Building better biomarkers: brain models in translational neuroimaging. Nature Neuroscience, 20(3), 365-377. doi:10.1038/nn.4478Ivanov, I. (2017). The Neuroimaging Gap - Where do we go from Here? Acta Psychopathologica, 03(03). doi:10.4172/2469-6676.100090Kastrup, O., Wanke, I., & Maschke, M. (2005). Neuroimaging of infections. NeuroRX, 2(2), 324-332. doi:10.1602/neurorx.2.2.324Preece, D., Williams, S. B., Lam, R., & Weller, R. (2013). «Let»s Get Physical’: Advantages of a physical model over 3D computer models and textbooks in learning imaging anatomy. Anatomical Sciences Education, 6(4), 216-224. doi:10.1002/ase.1345Zheng, Y., Yu, D., Zhao, J., Wu, Y., & Zheng, B. (2016). 3D Printout Models vs. 3D-Rendered Images: Which Is Better for Preoperative Planning? Journal of Surgical Education, 73(3), 518-523. doi:10.1016/j.jsurg.2016.01.003Li, Z., Li, Z., Xu, R., Li, M., Li, J., Liu, Y., … Chen, Z. (2015). Three-dimensional printing models improve understanding of spinal fracture—A randomized controlled study in China. Scientific Reports, 5(1). doi:10.1038/srep11570Kettenbach, J., Wong, T., Kacher, D., Hata, N., Schwartz, R. ., Black, P. M., … Jolesz, F. . (1999). Computer-based imaging and interventional MRI: applications for neurosurgery. Computerized Medical Imaging and Graphics, 23(5), 245-258. doi:10.1016/s0895-6111(99)00022-1Schwarz, A. J., Danckaert, A., Reese, T., Gozzi, A., Paxinos, G., Watson, C., … Bifone, A. (2006). A stereotaxic MRI template set for the rat brain with tissue class distribution maps and co-registered anatomical atlas: Application to pharmacological MRI. NeuroImage, 32(2), 538-550. doi:10.1016/j.neuroimage.2006.04.214Marro, A., Bandukwala, T., & Mak, W. (2016). Three-Dimensional Printing and Medical Imaging: A Review of the Methods and Applications. Current Problems in Diagnostic Radiology, 45(1), 2-9. doi:10.1067/j.cpradiol.2015.07.009Michalski, M. H., & Ross, J. S. (2014). The Shape of Things to Come. JAMA, 312(21), 2213. doi:10.1001/jama.2014.9542Ratto, M., & Ree, R. (2012). Materializing information: 3D printing and social change. First Monday, 17(7). doi:10.5210/fm.v17i7.3968Rengier, F., Mehndiratta, A., von Tengg-Kobligk, H., Zechmann, C. M., Unterhinninghofen, R., Kauczor, H.-U., & Giesel, F. L. (2010). 3D printing based on imaging data: review of medical applications. International Journal of Computer Assisted Radiology and Surgery, 5(4), 335-341. doi:10.1007/s11548-010-0476-xMannoor, M. S., Jiang, Z., James, T., Kong, Y. L., Malatesta, K. A., Soboyejo, W. O., … McAlpine, M. C. (2013). 3D Printed Bionic Ears. Nano Letters, 13(6), 2634-2639. doi:10.1021/nl4007744Guy, J. R., Sati, P., Leibovitch, E., Jacobson, S., Silva, A. C., & Reich, D. S. (2016). Custom fit 3D-printed brain holders for comparison of histology with MRI in marmosets. Journal of Neuroscience Methods, 257, 55-63. doi:10.1016/j.jneumeth.2015.09.002Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J.-P., Frith, C. D., & Frackowiak, R. S. J. (1994). Statistical parametric maps in functional imaging: A general linear approach. Human Brain Mapping, 2(4), 189-210. doi:10.1002/hbm.460020402Flandin, G., & Novak, M. J. U. (2013). fMRI Data Analysis Using SPM. fMRI, 51-76. doi:10.1007/978-3-642-34342-1_6Mueller, B. (2012). Additive Manufacturing Technologies – Rapid Prototyping to Direct Digital Manufacturing. Assembly Automation, 32(2). doi:10.1108/aa.2012.03332baa.010Gulanová, J., Kister, I., Káčer, N., & Gulan, L. (2018). A Comparative Study of various AM Technologies Based on Their Accuracy. Procedia CIRP, 67, 238-243. doi:10.1016/j.procir.2017.12.206D’Urso, P. S., Barker, T. M., Earwaker, W. J., Bruce, L. J., Atkinson, R. L., Lanigan, M. W., … Effeney, D. J. (1999). Stereolithographic biomodelling in cranio-maxillofacial surgery: a prospective trial. Journal of Cranio-Maxillofacial Surgery, 27(1), 30-37. doi:10.1016/s1010-5182(99)80007-9Müller, A., Krishnan, K. G., Uhl, E., & Mast, G. (2003). The Application of Rapid Prototyping Techniques in Cranial Reconstruction and Preoperative Planning in Neurosurgery. Journal of Craniofacial Surgery, 14(6), 899-914. doi:10.1097/00001665-200311000-00014Guarino, J., Tennyson, S., McCain, G., Bond, L., Shea, K., & King, H. (2007). Rapid Prototyping Technology for Surgeries of the Pediatric Spine and Pelvis. Journal of Pediatric Orthopaedics, 27(8), 955-960. doi:10.1097/bpo.0b013e3181594cedCanstein, C., Cachot, P., Faust, A., Stalder, A. F., Bock, J., Frydrychowicz, A., … Markl, M. (2008). 3D MR flow analysis in realistic rapid-prototyping model systems of the thoracic aorta: Comparison with in vivo data and computational fluid dynamics in identical vessel geometries. 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MRI texture-based radiomics analysis for the identification of altered functional networks in alcoholic patients and animal models

Alcohol use disorder (AUD) is a complex condition representing a leading risk factor for death, disease and disability. Its high prevalence and severe health consequences make necessary a better understanding of the brain network alterations to improve diagnosis and treatment. The purpose of this study was to evaluate the potential of resting-state fMRI 3D texture features as a novel source of biomarkers to identify AUD brain network alterations following a radiomics approach. A longitudinal study was conducted in Marchigian Sardinian alcohol-preferring msP rats (N = 36) who underwent resting-state functional and structural MRI before and after 30 days of alcohol or water consumption. A cross-sectional human study was also conducted among 33 healthy controls and 35 AUD patients. The preprocessed functional data corresponding to control and alcohol conditions were used to perform a probabilistic independent component analysis, identifying seven independent components as resting-state networks. Forty-three radiomic features extracted from each network were compared using a Wilcoxon signed-rank test with Holm correction to identify the network most affected by alcohol consumption. Features extracted from this network were then used in the machine learning process, evaluating two feature selection methods and six predictive models within a nested cross-validation structure. The classification was evaluated by computing the area under the ROC curve. Images were quantized using different numbers of gray-levels to test their influence on the results. The influence of ageing, data preprocessing, and brain iron accumulation were also analyzed. The methodology was validated using structural scans. The striatal network in alcohol-exposed msP rats presented the most significant number of altered features. The radiomics approach supported this result achieving good classification performance in animals (AUC = 0.915 ± 0.100, with 12 features) and humans (AUC = 0.724 ± 0.117, with 9 features) using a random forest model. Using the structural scans, high accuracy was achieved with a multilayer perceptron in both species (animals: AUC > 0.95 with 2 features, humans: AUC > 0.82 with 18 features). The best results were obtained using a feature selection method based on the p-value. The proposed radiomics approach is able to identify AUD patients and alcohol-exposed rats with good accuracy, employing a subset of 3D features extracted from fMRI. Furthermore, it can help identify relevant networks in drug addiction.This work was supported by the European Union’s Horizon 2020 research and innovation program (668863-SyBil-AA) and the ERA-NET NEURON program (FKZ 01EW1112-TRANSALC and PIM2010ERN-00679), as well as the Spanish State Research Agency through the Severo Ochoa Program for Centres of Excellence in R&D (SEV- 2017–0723). S.C. acknowledges financial support from the Ministerio de Economía y Competitividad (MINECO) under grant PGC2018–101055-B-I00. D.M. and S.C. acknowledge financial support from the Generalitat Valenciana through the Prometeo Program (PROMETEO/2019/015). Additional support was given to W.H.S by the Deutsche Forschungsgemeinschaft Center grant TRR 265 (Heinz et al., 2020) and the Bundesministerium für Bildung und Forschung (BMBF; FKZ: 031L0190A, 01ZX1909CA).Peer reviewe

Increased network centrality of the anterior insula in early abstinence from alcohol

Abnormal resting-state functional connectivity, as measured by functional magnetic resonance imaging (MRI), has been reported in alcohol use disorders (AUD), but findings are so far inconsistent. Here, we exploited recent developments in graph-theoretical analyses, enabling improved resolution and fine-grained representation of brain networks, to investigate functional connectivity in 35 recently detoxified alcohol dependent patients versus 34 healthy controls. Specifically, we focused on the modular organization, that is, the presence of tightly connected substructures within a network, and on the identification of brain regions responsible for network integration using an unbiased approach based on a large-scale network composed of more than 600 a priori defined nodes. We found significant reductions in global connectivity and region-specific disruption in the network topology in patients compared with controls. Specifically, the basal brain and the insular-supramarginal cortices, which form tightly coupled modules in healthy subjects, were fragmented in patients. Further, patients showed a strong increase in the centrality of the anterior insula, which exhibited stronger connectivity to distal cortical regions and weaker connectivity to the posterior insula. Anterior insula centrality, a measure of the integrative role of a region, was significantly associated with increased risk of relapse. Exploratory analysis suggests partial recovery of modular structure and insular connectivity in patients after 2 weeks. These findings support the hypothesis that, at least during the early stages of abstinence, the anterior insula may drive exaggerated integration of interoceptive states in AUD patients with possible consequences for decision making and emotional states and that functional connectivity is dynamically changing during treatment.This work was supported by the European Union's Horizon 2020 research and innovation programme (668863-SyBil-AA), the ERA-Net NEURON programme (FKZ 01EW1112-TRANSALC) and Deutsche Forschungsgemeinschaft (center grants SFB636 and TRR 265 subproject B0867). SC acknowledges the Spanish State Research Agency through the Severo Ochoa Programme for Centres of Excellence in R&D (SEV-2017-0723) and the Ministerio de Economía y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-1-R and BFU2015-64380-C2-2-R.Open Access Funding provided by Istituto Italiano di Tecnologia within the CRUI-CARE Agreement.Peer reviewe

White Paper 5: Brain, Mind & Behaviour

© CSICThe study of the brain will tell us what makes us humans and how our social behavior generates. Increasing our understanding of how the brain functions and interacts with the ecosystem to interpret the world will not only help to find effective means to treat and/or cure neurological and psychiatric disorders but will also change our vision on questions pertaining to philosophy and humanities and transform other fields such as economy and law. Neurosciences research at the CSIC is already valuable and should be intensified mainly focused on the eight major challenges described in this volume

Libro Blanco Volumen 5: Cerebro, mente y comportamiento

Llegar a entender cómo funciona el cerebro y cómo este interacciona con el ecosistema para interpretar el mundo que nos rodea sin duda facilitará el desarrollo de estrategias más eficaces para tratar o curar los trastornos neurológicos y psiquiátricos. Además, la comprensión de los principios fundamentales que controlan el funcionamiento del sistema nervioso transformará nuestra visión sobre muchas cuestiones que han sido tradicionalmente enmarcadas en el campo de la filosofía, repercutiendo en áreas como la economía o el derecho. Las neurociencias nos ayudarán, en definitiva, a entender qué nos hace humanos. Este es un campo en el que los investigadores del CSIC destacan internacionalmente y así debe seguir siendo en los próximos años. Para lograrlo, deberíamos potenciar y reforzar nuestras investigaciones en los ocho desafíos que describimos en este volumen.Peer reviewe

Implicaciones del óxido nítrico en la diferenciación y apoptosis de neuronas dopaminérgicas : papel de la glía

En este trabajo hemos estudiado el efecto del óxido nítrico (NO) sobre las neuronas dopaminérgicas en cultivo primario de rata y sobre neuronas dopaminérgicas de neuroblastoma humano NB69. El no mostró un efecto bifásico dependiente de su concentración, siendo neurotrófico a bajas dosis y neurotóxico a alta concentración. El efecto neurotrófico es selectivo para las neuronas dopaminérgicas y consiste en un aumento en la síntesis y captación de dopamina, un incremento en la ramificación neurítica y la expresión de novo de células con fenotipo dopaminérgico. El efecto tóxico consiste en un proceso de muerte celular programada y necrosis. El efecto tóxico es totalmente prevenido por factores solubles liberados por la glía y con antioxidante tiólicos. Además, hemos demostrado que la concentración intracelular de glutation (GSH) condiciona el efecto del NO. Una disminución en los niveles de GSH, transforma el efecto neurotrófico del NO en tóxico. En esta ocasión, la toxicidad es revertida con inhibidores de la guanilato ciclasa, de la proteína Kinasa G, así como de la lipoxigenasa 12 y las MAPKs ERK-1/2. Finalmente hemos demostrado que el NO activa selectivamente las ERK-1/2 en células de la glía y que esta activación inicia una cascada de señalización que mata a las neuronas dopaminérgica