Motivation

One of the main goals of neuroscience is to understand the biological mechanisms responsible for human mental activity. In particular, the study of the cerebral cortex is and without any doubt will be the greatest challenge for science in the next centuries, since it represents the foundation of our humanity. In other words, the cerebral cortex is the structure whose activity is related to the capabilities that distinguish humans from other mammals. Thanks to the development and evolution of the cerebral cortex we are able to perform highly complex and specifically human tasks, such as writing a book, composing a symphony or developing technologies.

For these reasons the Blue Brain project emerged in 2005, when the L’Ecole Polytechnique Fédérale de Lausanne (Switzerland) and IBM jointly launched an ambitious project to create a functional brain model by means of reverse engineering of the mammalian brain, using the Blue Gene supercomputer from IBM. The aim was to understand the functioning and dysfunction of the brain through detailed simulations. By late 2006, the Blue Brain project had created a model of the basic functional unit of the brain, the neocortical column. However, the goals set by the project, which covered a period of 10 years, imposed its conversion into an international initiative (The Blue Brain Project, Nat Rev Neurosci. 7, 153-160, 2006). In this context, the Cajal Blue Brain project, the Spanish contribution to this international project, started in January 2009 led by the Universidad Politécnica de Madrid (UPM) and the Consejo Superior de Investigaciones Científicas (CSIC) .

Responsive image

Neuronal Forest simulation

Art and Technical Direction: Luis Pastor, Ángel Rodríguez, Susana Mata and Sofía Bayona - Art and Technical - Production and Development: Juan Pedro Brito and Luis Miguel Serrano - Technical Advice: José Miguel Espadero - Art Advice: Eva Cortés - Scientific Advice: Javier DeFelipe y Ruth Benavides-Piccione

"The garden of neurology offers the investigator captivating spectacles and incomparable artistic emotions. In it, my aesthetic instincts were at last full satisfied. Like the entomologist hunting for brightly colored butterflies, my attention was drawn to the flower garden of the gray matter that contained cells with delicate and elegant forms, the mysterious butterflies of the soul, the beating of whose wings may some day (who knows?) clarify the secret of mental life. […] Even from the aesthetic point of view, the nervous tissue contains the most charming attractions. In our parks is there any tree more elegant and luxurious than the Purkinje cell from the cerebellum or the psychic cell, that is the famous cerebral pyramid?"

Santiago Ramón y Cajal, 1894

Overall, the Blue Brain Project is based on the hypothesis of some scientists that detailed maps of the synaptic connections will be needed in order to understand how the brain functions. Such large-scale circuit reconstructions, “connectome and synaptome”, will soon be possible thanks to recent technological advances in the acquisition and processing of experimental data. Although the scientific community is divided on the feasibility and value of this working hypothesis, it is important to note that similar objections were voiced when the Human Genome Project was first proposed, now widely considered as a great scientific success.

One of the strengths of the Cajal Blue Brain project is that all the participating laboratories and research groups will be coordinated, so that all the effort will be channelled towards a specific objective, using strictly common methodological criteria. Thus, the data generated in a laboratory can be effectively used by other research groups. Definitively, the Cajal Blue Brain project is structured in such a way that it will work as a single, large multidisciplinary laboratory. In this way, the project will generate significant advances in our understanding of the structure and function of the normal brain.

Responsive image
CeSViMa Supercomputer

The Project


Responsive image

The project is markedly interdisciplinary in nature, requiring the collaboration of scientists from different fields. The long-term objectives of the Cajal Blue Brain can be summarized as follows:

Key Objectives:

  • To decode the synaptome or detailed map of the synaptic connections of the cortical column and, as a result, reconstruct all its components.
  • To give a strong boost to research on the cortical column, exploring in depth current hypotheses about its normal function and dysfunctions (especially Alzheimer’s disease)
  • To devise new methods to process and analyze the experimental data obtained in the aforementioned research studies.
  • To develop computer technology to study neuronal functions using graphics tools and visualization methods

Other Objectives:

  • To understand the implication of glial cells and blood vessels in the organization of the cortical column.
  • To study the modulation of the functional organization of the cerebral cortex by cortical and subcortical afferent connections.
  • To decipher the functional organization of cortical circuits in vitro.
  • To simulate in silico the activity of the cortical column by means of a supercomputer.

As the Universidad Politécnica did not have a Neuroscience laboratory equipped with the tools and personnel required to become a world leader in the research proposed through this ambitious project and other related projects, the joint UPM-CSIC "Laboratorio Cajal de Circuitos Corticales or LCCC (Cajal Cortical Circuit Laboratory)" was created, which is part of the Centro de Tecnología Biomédica or CTB (Biomedical Technology) of the UPM Montegancedo Campus. The work carried out at the LCCC, the maintenance of this laboratory and the progressive acquisition of the most advanced tools and technologies is essential in order to obtain the neurobiological data required to meet the project’s objectives. The maintenance of the LCCC is therefore a priority in the Cajal Blue Brain project as it generates the knowledge which is the basis for the subsequent development of computer tools and data analysis methods the project requires.

Project Organization

Responsive image

BBP Structure

Project Management

  • Project Director: Prof. Javier DeFelipe (LCCC, UPM-CSIC)
  • Project Manager: Dr. Pilar Flores-Romero (LCCC, UPM-CSIC)

Coordinators of the Scientific Modules

  • Neuroscience: Prof. Javier DeFelipe (CCCL, UPM-CSIC)
  • Image Processing: Dr. Luis Baumela (UPM)
  • Data Mining: Dr. Pedro Larrañaga (UPM)
  • Visualization: Dr. Angel Rodríguez (UPM)
  • Informatics Tools: Dr. Jose María Peña (UPM)

External Collaborators

  • Prof. Luis Pastor (GMRV, URJC)
  • Prof. Alfonso Araque (IC, CSIC)
  • Prof. Rafael Luján (UCLM)

Research

Espina

Responsive image

Since synapses are key elements in the structure of nervous circuits, understanding their location, size and proportion between the two different types is extraordinarily important in terms of function.

In this way, Espina tool automatically performs segmentation and 3D volume reconstruction of synapses in the cerebral cortex, helping the user to examine large tissue volumes and interactively validate the results provided by the software.

Morales J, Alonso-Nanclares L, Rodríguez J-R, DeFelipe J, Rodríguez Á and Merchán-Pérez Á (2011) ESPINA: a tool for the automated segmentation and counting of synapses in large stacks of electron microscopy images. Front. Neuroanat. 5:18. doi: 10.3389/fnana.2011.00018

ESPINA can display multiple spatially or temporally related images. These image sets are called stacks. The images that make up a stack are called sections. All the sections in a stack must be the same size and bit depth. ESPINA supports 8-bit images.

ESPINA is a memory intensive application. In a Linux x64 machine the maximum image stack size is only limited by the amount of RAM installed in the system (a machine with 4GB of RAM can process stacks up to 200MB in size). The Win32 version of ESPINA can only manage 2 GB of RAM and a maximum stack size of about 40MB. A Win64 version is currently under development.


Responsive image

Dispine

Responsive image

Current understanding of the synaptic organization of the cerebral cortex depends to a large extent on knowledge of the synaptic inputs to the pyramidal cells. Indeed, their dendritic surfaces are covered by thin protrusions named dendritic spines, which represent the sites of most excitatory synapses in the cerebral cortex, and therefore, are critical in learning, memory and cognition.

This tool facilitates the analysis of the 3D structure of spine insertions in dendrites, providing insight on spine distribution patterns.

Juan Morales, Ruth Benavides-Piccione, Angel Rodríguez, Luis Pastor, Rafael Yuste, Javier De Felipe (2012). Three-Dimensional Analysis of Spiny Dendrites Using Straightening and Unrolling Transforms. Neuroinformatics October 2012 Volume 10, Issue 4, pp 391-407.

Windows Installation

Dispine depends on python 2.6, PyQt4, numpy, python wrappers of VTK and pygame.

In windows the easiest way to install all the dependencies is running the Python xy installer and mark the numpy and VTK packages to install. Then install pygame following the withard instructions.

Test set

If you want to test the tool, we provide a test set you can use. Unzip it and load the file "api m16 1 5-1.spiral" from the Dispine dialogue "File->Open spines...".

Responsive image

Audispine

We present a new method with musical feedback for exploring dendritic spine morphology and distribution patterns in pyramidal neurons. We demonstrate that audio analysis of spiny dendrites with apparently similar morphology may “sound” quite different, revealing anatomical substrates that are not apparent from simple visual inspection.

Pablo Toharia, Juan Morales, Octavio de Juan, Isabel Fernaud, Angel Rodríguez, Javier DeFelipe. Neuroinformatics, January 2014. Musical representation of dendritic spine distribution: a new exploratory tool

Responsive image

Neuronize

This tool presents a new technique for the generation of three-dimensional models for neuronal cells from the morphological information extracted through computed-aided tracing applications. The 3D polygonal meshes that approximate the cell membrane can be generated at different resolution levels, allowing balance to be reached between the complexity and the quality of the final model.

Neuronize implements a novel approach to generate a realistic 3D shape of the soma from the incomplete information stored in the digitally traced neuron using a physical deformation technique.

The addition of a set of spines along the dendrites completes the model, generating a final 3D neuronal cell suitable for its visualization in a wide range of 3D environments.

Brito JP, Mata S, Bayona S, Pastor L, Defelipe J, Benavides-Piccione R (2013). A tool for building realistic neuronal cell morphologies. Front Neuroanat. 2013 Jun 3;7:15. doi: 10.3389/fnana.2013.00015. eCollection 2013.

Responsive image

Neuronize requires Matlab Compiler Runtime 2012b (you can download freely, clicking on here)to be installed on your computer. Versions for Windows 32 and 64 bits platforms are available. Versions for Linux and Mac are under development.

The video may also help you see how to work with NEURONIZE. It shows a common working session:

Please register for release announcements and then proceed directly to download the NEURONIZE software.

The personal data you enter here will be stored and used for no other reason than to send you messages regarding NEURONIZE updates, bug fixes, and Cajal Blue Brain workshop announcements. Your data will only be disclosed to the entities directly involved with the development and release of NEURONIZE software.


SAS

Responsive image

Synaptic Apposition Surface (SAS)

We have developed an efficient computational technique to automatically extract the surface from synaptic junctions that have previously been three- dimensionally reconstructed from actual tissue samples imaged by automated FIB/SEM.

Juan Morales, Angel Rodríguez, José-Rodrigo Rodríguez, Javier DeFelipe and Angel Merchán-Pérez (2013). Characterization and extraction of the synaptic apposition surface for synaptic geometry analysis Front. Neuroanat., 04 July 2013 | doi: 10.3389/fnana.2013.00020

Publications

2009 CBBP Scientific Publications

  • Merchán-Pérez A, Rodriguez JR, Ribak CE, DeFelipe J (2009) Proximity of excitatory and inhibitory axon terminals adjacent to pyramidal cell bodies provides a putative basis for nonsynaptic interactions. Proc Natl Acad Sci USA. 106(24):9878-83.
  • Merchan-Pérez A, Rodriguez J, Alonso-Nanclares L, Schertel A and DeFelipe J (2009) Counting synapses using FIB/SEM microscopy: a true revolution for ultrastructural volume reconstruction. Front. Neuroanat. 3:18. doi:10.3389/neuro.05.018.2009.
  • Inda MC, DeFelipe J, Munoz A. (2009) Morphology and Distribution of Chandelier Cell Axon Terminals in the Mouse Cerebral Cortex and Claustroamygdaloid Complex. Cereb Cortex. 19(1):41-54.
  • Knafo S, Alonso-Nanclares L, J. Gonzalez-Soriano J, Merino-Serrais P, I. Fernaud-Espinosa1 I, Ferrer I, DeFelipe J (2009) Widespread changes in dendritic spines in a model of Alzheimer’s disease. Cereb Cortex 19(3):586-92.
  • Knafo S, Venero C, Merino-Serrais P, Fernaud-Espinosa I, Gonzalez-Soriano J, Ferrer I, Santpere G and DeFelipe J (2009) Morphological alterations to neurons of the amygdala and impaired fear conditioning in a transgenic mouse model of Alzheimer’s disease. J. Pathol. 219:41-51.
  • Kastanauskaite A, Alonso-Nanclares L, Blazquez-Llorca L, Pastor J, Sola RG, DeFelipe J (2009) Alterations of the microvascular network in sclerotic hippocampi from patients with epilepsy. J Neuropathol Exp Neurol. 68:939-950.
  • Yague JG, Azcoitia I, DeFelipe J, Garcia-Segura LM, Muñoz A (2009) Aromatase expression in the normal and epileptic human hippocampus. Brain Res. 2009 Oct 6. [Epub ahead of print].
  • Garcia-Marin V, Blazquez-Llorca L, Rodriguez JR, Boluda S, Muntane G, Ferrer I, DeFelipe J (2009) Diminished perisomatic GABAergic terminals on cortical neurons adjacent to amyloid plaques. Front Neuroanat. 3:28. Epub 2009 Nov 20.
  • Perea G, Araque A (2009) Glia modulates synaptic transmission. Brain Research Reviews (in press).
  • Araque A, Navarrete M (2009) Glial cells in neuronal network function. Philosophical Transactions of the Royal Society B (in press).
  • Perea G, Navarrete M, Araque A (2009) Tripartite synapses: astrocytes process and control synaptic information. Trends in Neurosciences 32: 421-431.
  • A. LaTorre, JM Peña, S. Muelas, AA. Freitas. Learning Hybridization Strategies in Evolutionary Algorithms. Intelligent Data Analysis 14 (3), 2010
  • S. Muelas, JM Peña, A. LaTorre. A New Initialization Procedure for the Estimation of Distribution Algorithms. Softcomputing (Accepted for publication)
  • G. Beslon, D. Parsons, JM Peña, C Rigotti, Y. Sanchez-Dehesa. From Digital Genetics to Knowledge Discovery: Perspectives in Genetic Network Understanding Intelligent Data Analysis (Accepted for Publication)
  • MS. Pérez, A. Sánchez, JH. Abawajy, V. Robles JM. Peña An agent architecture for managing data resources in a grid environment Future Generation Computer Systems 25, (7), 2009, 747-755
  • Y. Sanchez-Dehesa, D. Parsons, JM. Peña, G. Beslon. Modelling Evolution of Regulatory Networks in Artificial Bacteria. Mathematical Modelling of Natural Phenomena 3(2), 2008 :27-66
  • S. Gonzalez, L. Guerra, V. Robles, JM. Peña, F. Famili. CliDaPa: A New Approach to Combining Clinical Data with DNA Microarrays Intelligent Data Analysis (Accepted for Publication)
  • G. Beslon, D. Parsons, Y. Sanchez-Dehesa, JM Peña, C. Knibbe. Scaling Laws in Bacterial Genomes : A Side-Effect of Selection of Mutational Robustness?. Biosystems (Accepted for Publication).
  • M-L. Zhang, JM Peña, V Robles. Feature selection for multi-label naive Bayes classification. Information Science 179 (19), 2009: 3218-3229
  • R. Santana, C. Bielza, P. Larrañaga, J. A. Lozano, C. Echegoyen, A. Mendiburu, R. Armañanzas, S. Shakya. MATEDA: A Matlab package for the implementation and analysis of estimation of distribution algorithms. Journal of Statistical Software. Accepted for publication.
  • D. Otaegui, S. Baranzini, R. Armañanzas, B. Calvo, M. Muñoz-Culla, P. Khankhanian, I. Inza, J. A. Lozano, A. Asensio, T. Castillo-Triviño, J. Olsacoaga, A. López de Munain. Differential micro RNA expression in PBMC from multiple sclerosis patients. PLoS ONE, vol 4(7), e6309.
  • Inza, B. Calvo, R. Armañanzas, E. Bengoetxea, P. Larrañaga, J. A. Lozano. Machine learning: An indispensable tool in bioinformatics. In R. Matthiesen, editor, Bioinformatics Methods in Clinical Research. Humana Press
Other CBBP Publications
  • DeFelipe J, Jones EG. (2009) Neocortical Microcircuits. Handbook of Brain Microcircuits. (ed. Gordon Shepherd and Sten Grillner), Oxford University Press, New York (en prensa).
  • DeFelipe J (2009) Cajal y las mariposas del alma: plasticidad cerebral y procesos mentales. Ateneo (Madrid).
  • LaTorre, JM. Peña, V. Robles, S. Muelas, P. deMiguel. Supercomputer Scheduling with Combined Evolutionary Techniques. In the book Meta-heuristics for Scheduling: Distributed Computing Environments. Springer-Verlag ISBN 978-3-540-69260-7

2010 Scientific Publications

  • From the Connectome to the Synaptome: An Epic Love Story. DeFelipe J. Science 26 November 2010: Vol. 330 no. 6008 pp. 1198-1201 DOI: 10.1126/science.1193378
  • GABAergic complex basket formations in the human neocortex. Blazquez-Llorca L, García-Marín V, DeFelipe J. J Comp Neurol. 2010 Dec 15;518 (24):4917-37.PMID: 21031559 [PubMed - in process] Related citations
  • Differential distribution of neurons in the gyral white matter of the human cerebral cortex. García-Marín V, Blazquez-Llorca L, Rodriguez JR, Gonzalez-Soriano J, DeFelipe J. J Comp Neurol. 2010 Dec 1;518(23):4740-59.PMID: 20963826 [PubMed - in process] Related citations
  • Layer-specific alterations to CA1 dendritic spines in a mouse model of Alzheimer's disease. Merino-Serrais P, Knafo S, Alonso-Nanclares L, Fernaud-Espinosa I, Defelipe J. Hippocampus. 2010 Sep 16. [Epub ahead of print]PMID: 20848609 [PubMed - as supplied by publisher]Related citations
  • Pericellular innervation of neurons expressing abnormally hyperphosphorylated tau in the hippocampal formation of Alzheimer's disease patients. Blazquez-Llorca L, Garcia-Marin V, Defelipe J. Front Neuroanat. 2010 Jun 24;4:20. PMID: 20631843 [PubMed - in process]Free PMC Article Free textRelated citations
  • Alterations of cortical pyramidal neurons in mice lacking high-affinity nicotinic receptors. Ballesteros-Yáñez I, Benavides-Piccione R, Bourgeois JP, Changeux JP, DeFelipe J. Proc Natl Acad Sci U S A. 2010 Jun 22;107(25):11567-72. Epub 2010 Jun 7.PMID: 20534523 [PubMed - indexed for MEDLINE] Related citations
  • Cortical white matter: beyond the pale remarks, main conclusions and discussion. Defelipe J, Fields RD, Hof PR, Höistad M, Kostovic I, Meyer G, Rockland KS.Front Neuroanat. 2010 Mar 24;4:4. No abstract available. PMID: 20428509 [PubMed - in process] Free PMC ArticleFree textRelated citations
  • Cortical GABAergic Neurons: Stretching it Remarks, Main Conclusions and Discussion. Clancy B, Defelipe J, Espinosa A, Fairén A, Jinno S, Kanold P, Luhmann HJ, Rockland KS, Tamamaki N, Yan XX. Front Neuroanat. 2010 Mar 2; 4:7. No abstract available. PMID: 20224807 [PubMed - in process]Free PMC ArticleFree textRelated citations
  • Aromatase expression in the normal and epileptic human hippocampus. Yague JG, Azcoitia I, DeFelipe J, Garcia-Segura LM, Muñoz A. Brain Res. 2010 Feb 22; 1315:41-52. Epub 2009 Oct 6.PMID: 19815003 [PubMed - indexed for MEDLINE] Related citations
  • Dyrk1A is a major player in the dendritic abnormalities of Down syndrome patients. Martinez de Lagrán M., Benavides-Piccione R, Ballesteros-Yañez I, Calvo M, Morales M, Fillat C, DeFelipe J, Ramakers G, and Dierssen M (2010) Journal of Neuroscience (submitted).
  • Pyramidal cells in prefrontal cortex of primates: marked specializations differences in neuronal structure among species Elston GN, Benavides-Piccione R, Elston A, Manger PR, DeFelipe J (2010) Frontier in Neuroscience (submitted).
  • Casein kinase 2 and microtubules control axon initial segment formation. Sánchez-Ponce D, Muñoz A and Garrido JJ. Moll and Cell Neurosci 2010 (In press).
  • Navarrete M, Araque A. Endocannabinoids potentiate synaptic transmission through stimulation of astrocytes. Neuron (2010) 68, 113-26.
  • Araque A, Navarrete M. Glial cells in neuronal network function. Philos Trans R Soc Lond B Biol Sci. (2010) 365, 2375-81.
  • Perea G, Araque A. GLIA modulates synaptic transmission. Brain Res Rev. (2010) 63, 93-102.
  • Guillaume Beslon, David P. Parsons, Jose M. Peña, Christophe Rigotti, Yolanda Sanchez-Dehesa: From digital genetics to knowledge discovery: Perspectives in genetic network understanding. Intell. Data Anal. 14(2): 173-191 (2010)
  • S. Lasserre, J. Hernando, S. Hill, F. Schürmann, P. de Miguel, G. Abou-Jaoudé, H. Markram, "A Neuron Membrane Mesh Representation for Visualization of Electrophysiological Simulations", IEEE Transactions on Visualization and Computer Graphics, accepted on December 13th 2010
  • L Guerra, LM McGarry, V Robles, C Bielza, P Larrañaga, R Yuste, “Comparison between supervised and unsupervised classifications of neuronal cell types: a case study”, Developmental Neurobiology, vol 71 (1), pp 71-82, 2011
  • Santana, R., Bielza, C., Larrañaga, P. (2010) Optimizing Brain Networks Topologies Using Multi-objective Evolutionary Computation, Neurinformatics, in press, DOI 10.1007/s12021-010-9085-7
  • López-Cruz, P., Bielza, C., Larrañaga, P., Benavides-Piccione, R., DeFelipe, J. (2010) Models and Simulation of 3D Neuronal Dendritic Trees Using Bayesian Networks, Neuroinformatics, in press.

Other CBBP Publications

  • “El cerebro, la gran cepa azul”. Arte y neurociencia. Coordinador: Javier de Felipe. Noviembre 2010
  • DeFelipe J, Jones EG. (2010) Neocortical Microcircuits. Handbook of Brain Microcircuits. (ed. Gordon Shepherd and Sten Grillner), Oxford University Press, New York.
  • DeFelipe J, (2010) The birth of modern neuroscience. In: Portraits of the Mind: Visualizing the Brain from Antiquity to the 21st Century. Schoonover CE (ed). Abrams, New York.
  • DeFelipe J (2010) Reflexiones sobre lo bello, el arte y la evolución del cerebro. En Neuroestética. Martín Araguz A (ed) Madrid. Saned, pp 51-76.
  • DeFelipe J (2010) Sobre lo bello, el arte y la ciencia: Paisajes neuonales.Coordinadores Javier de Felipe y Franck González. En: El cerebro, la gran cepa azul. Arte y Neurociencia. Museo Elder. Las Palmas de Gran Canaria, pp 33-72.
  • Morales, D.A. Matemáticas aplicadas en la predicción en medicina. Un paseo por la Geometría. D. Morales. Departamento de Matemáticas de la Facultad de Ciencia y Tecnología. Universidad del País Vasco. 2010. Pp 149-167

Other Publications

  • Higuera-Matas, A., Montoya, G.L., Coria, S.M., Miguéns, M., García-Lecumberri, C., and Ambrosio, E (2010). Differential gene expression in the nucleus accumbens and frontal cortex of Lewis and Fischer 344 rats relevant to drug addiction. Current Neuropharmacolgy (En prensa).
  • Higuera-Matas A, Soto-Montenegro ML, Montoya GL, García-Vázquez V, Pascau J, Miguens M, Del Olmo N, Vaquero JJ, García-Lecumberri C, Desco M, Ambrosio E (2010). Chronic Cannabinoid Administration to Periadolescent Rats Modulates the Metabolic Response to Acute Cocaine in the Adult Brain. Mol Imaging Biol (Epub ahead of print).
  • Higuera-Matas A, Botreau F, Del Olmo N, Miguéns M, Olías O, Montoya GL, García-Lecumberri C, Ambrosio E (2010). Periadolescent exposure to cannabinoids alters the striatal and hippocampal dopaminergic system in the adult rat brain. Eur Neuropsychopharmacol. Dec; 20(12):895-906.
  • García-Lecumberri, C., Torres, I., Martín, S., Crespo, J.A., Miguéns, M., Higuera-Matas, A., Nicanor, C. Ambrosio, E (2010). Strain differences in the dose-response relationship for morphine self-administration and impulsive choice between lewis and fischer 344 rats. J. Psychopharmacology (Epub ahead of print).
  • Guillaume Beslon, David P. Parsons, Yolanda Sanchez-Dehesa, José M. Peña, Carole Knibbe: Scaling laws in bacterial genomes: A side-effect of selection of mutational robustness? Biosystems 102(1): 32-40 (2010)
  • Santiago González, Luis Guerra, Víctor Robles, José M. Peña, Fazel Famili: CliDaPa: A new approach to combining clinical data with DNA microarrays. Intell. Data Anal. 14(2): 207-223 (2010)
  • Antonio LaTorre, José María Peña, Santiago Muelas, Alex A. Freitas: Learning hybridization strategies in evolutionary algorithms. Intell. Data Anal. 14(3): 333-354 (2010)
  • S. Muelas, J.M. Peña, A. LaTorre, and V. Robles, “A new initialization procedure for the distributed estimation of distribution algorithms” Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2010.
  • S. Muelas, A. LaTorre, and J.M. Peña, “A New Methodology for the Automatic Creation of Adaptive Hybrid Algorithms” Intelligent Data Analysis Journal (accepted, to be published in 2011)
  • LaTorre, A.; Muelas, S. & Peña, J.M. A MOS-based Dynamic Memetic Differential Evolution Algorithm for Continuous Optimization: A Scalability Test (accessible on-line: DOI: 10.1007/s00500-010-0646-3) Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2010, 1-13
  • Vidaurre, D., Bielza, C., Larrañaga, P. (2010) Learning an L1-regularized Gaussian Bayesian Network in the Equivalence Class Space, IEEE Transactions on Systems, Man and Cybernetics, Part B, 40, 5, 1231–1242
  • Jorge Muruzábal · Diego Vidaurre · Julián Sánchez “SOMwise Regression: a new clusterwise regression method”, Neural Computing and Applications, (Submmitted in September 2010), 2011. In press.
  • Santana, R., Bielza, C., Larrañaga, P., Lozano, J.A., Echegoyen, C., Mendiburu, A., Armañanzas, A., Shakya, S. (2010) Mateda-2.0: Estimation of Distribution Algorithms in MATLAB, Journal of Statistical Software, 35, 7, 1-30
  • Cuesta, I., Bielza, C., Cuenca-Estrella, M., Larrañaga, P., Rodríguez-Tudela, J.L. (2010) Evaluation by data mining techniques of fluconazole breakpoints established by the clinical and laboratory standards institute (CLSI) and comparison with those of the European committee on antimicrobial susceptibility testing (EUCAST). Antimicrobial Agents and Chemotherapy, 54, 4, 1541-1546
  • Bielza, C., Gómez, M., Shenoy, P.P. (2010) Modelling Challenges with Influence Diagrams: Constructing Probability and Utility Models, Decision Support Systems, 49, 354–364
  • Bielza, C., Gómez, M., Shenoy, P.P. (2010) A Review of Representation Issues and Modelling Challenges with Influence Diagrams, Omega, 39, 227–241
  • C. Bielza, J. A. Fernández del Pozo, P. Larrañaga, E. Bengoetxea (2010) Multidimensional statistical analysis of the parameterization of a genetic algorithm for the optimal ordering of tables. Expert Systems with Applications (37), 804-815
  • R. Santana, P. Larrañaga, J. A. Lozano (2010) Learning factorizations in estimation of distribution algorithms using afinity propagation. Evolutionary Computation 18, 4, 515-546
  • Armañanzas, R., Saeys, Y., Inza, I., García-Torres, M., Bielza, C., van de Peer, Y., Larrañaga, P. (2011) Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms, IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press, http://doi.ieeecomputersociety.org/10.1109/TCBB.2010.18 Borchani, H., Larrañaga, P., Bielza, C. (2010) Classifying Evolving Data Streams with Partially Labelled Data, Intelligent Data Analysis, in press
  • P. Larrañaga, S. Moral (2011) Probabilistic graphical models in artificial intelligence. Applied Soft Computing (in press)
  • Bielza, C., Li, G., Larrañaga, P. (2011). Multi-Dimensional Classfication with Bayesian Networks. International Journal of Approximate Reasoning (in press)
  • Bielza, C., Robles, V., Larrañaga, P. (2010) Regularized Logistic Regression without a Penalty Term: An Application to Cancer Classification with Microarray Data, Expert Systems with Applications, in press (doi: 10.1016/j.eswa.2010.09.140)
  • Fernández del Pozo, J.A., Bielza, C. (2011) Dealing with Complex Queries in Decision Support Systems, Data & Knowledge Engineering, 70, 167-181
  • D.A. Morales, E. Bengoetxea, P. Larranaga. Automatic characterization of human embryos for improved selection on in-vitro fertilization using Bayesian classifiers. Artificial Intelligence in Medicine. Submitted response for reviewers.R. Santana, A. Mendiburu, N. Zaitlen, E. Eskin and J. A. Lozano (2010). Multi-marker tagging SNP selection using estimation of distribution algorithms. Artificial Intelligence in Medicine. Vol. 50 No. 3. Pp. 193:201.
  • M. García-Torres, R. Armañanzas, C. Bielza, P. Larrañaga (2010). Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Information Sciences, accepted for publication.
  • A high performance suite of data services for grids. Alberto Sánchez, María S. Pérez, Jesús Montes, Toni Cortés. Future Generation Computer Systems, Elsevier Science Publishers ISSN:0167-739X , Volume 26, Number 4, page 622--632 – 2010
  • Finding order in chaos: a behavior model of the whole grid. Jesús Montes, Alberto Sánchez, Julio J. Valdés, María S. Pérez, Pilar Herrero. Concurrency and Computation: Practice and Experience. John Wiley & Sons, Volume 22, page 1386--1415 – 2010.
  • GCViR: Grid Content-Based Video Retrieval with Work Allocation Brokering. Pablo Toharia, Alberto Sánchez, José L. Bosque, Óscar D. Robles. Concurrency and Computation, Practice and Experience. John Wiley & Sons, Volume 22, page 1450--1475 – 2010
  • Toharia Pablo, Sánchez Campos Alberto, Bosque José L., Robles Sánchez Óscar D. “GCViR: Grid Content-Based Video Retrieval with Work Allocation Brokering”. Concurrency and Computation, Practice and Experience. John Wiley & Sons, Volume 22, page 1450--1475 – 2010
  • García Lorenzo Marcos, Otaduy Miguel Ángel, O ‘Sullivan  Carol.  Perceptually validated global/local deformations.   Computer Animation and Virtual Worlds.  Volume 21, Issue 3-4, pages 245–254, May 2010.
  • C. Pedraza, E. Castillo, J. Castillo, J. L. Bosque, J. I. Martínez, O. D. Robles, J. Cano, P. Huerta. Content-based image retrieval algorithm acceleration in a low-cost reconfigurable FPGA cluster. Vol: 56 (1), pp: 633-640, 2010, ISSN:1383-7621 DOI: 10.1016/j.sysarc.2010.07.017, Elsevier - Academic Press. Journal of Systems Architecture.
  • Bengoetxea, E., Larrañaga, P., Bielza, C., Fernández del Pozo, J.A. (2010) Optimal Row and Column Ordering to Improve Table Interpretation Using Estimation of Distribution Algorithms, Journal of Heuristics, DOI 10.1007/s10732-010-9145-z
  • C. Echegoyen, A. Mendiburu, R. Santana and J. A. Lozano. Towards understanding EDAs based on Bayesian networks through a quantitative analysis. IEEE Transactions on Evolutionary Computation. Accepted for publication.
  • C. Echegoyen, A. Mendiburu, R. Santana, and J. A. Lozano. Analyzing the k Most Probable Solutions in EDAs based on Bayesian Networks. In Exploitation of linkage learning in evolutionary algorithms. Evolutionary Learning and Optimization. Springer. Y.-P. Chen editor. 2010.

2011 CBBP Scientific Publications

  • From the Connectome to the Synaptome: An Epic Love Story. DeFelipe J. Science 26 November 2010: Vol. 330 no. 6008 pp. 1198-1201 DOI: 10.1126/science.1193378
  • Elston G, Benavides-Piccione R, Elston A, Manger P and Defelipe J (2011). Pyramidal cells in prefrontal cortex: comparative observations reveal unparalleled specializations in neuronal structure among primate species. Front. Neuroanat. 5:2. doi: 10.3389/fnana.2011.00002
  • López, PL, Bielza C, Larrañaga P, Benavides-Piccione R, DeFelipe J (2011) Models and simulation of 3D neuronal dendritic trees using Bayesian networks. Neuroinformatics (in press).
  • Alonso-Nanclares L, Kastanauskaite A, Rodriguez JR, Gonzalez-Soriano J, DeFelipe J (2011) A stereological study of synapse number in the epileptic human hippocampus. Front. Neuroanat. 5:8. doi: 10.3389/fnana.2011.00008
  • DeFelipe J (2011) The evolution of the brain, the human nature of cortical circuits and intellectual creativity. Front. Neuroanat. 5:29.
  • Blazquez-Llorca L, Garcia-Marin V, Merino-Serrais P, Avila J and DeFelipe J (2011) Abnormal tau phosphorylation in the thorny excrescences of CA3 hippocampal neurons in patients with Alzheimer’s. J Alzheimer Disease 26: 683-698.
  • Sánchez-Ponce D, Blazquez-Llorca L, DeFelipe J, Garrido JJ, Muñoz A (2011) Co-localization of α-actinin and synaptopodin in the pyramidal cell axon initial segment. Cereb Cortex (in press).
  • S. Knafo, C. Venero, C. Sánchez-Puelles, I. Pereda-Peréz, A. Franco, C. Sandi, L.M. Suárez, J.M. Solís, L. Alonso-Nanclares, E.D. Martín, P. Merino-Serrais, E. Borcel, S. Li, Y. Chen, J. Gonzalez-Soriano , V. Berezin, E. Bock, J. De Felipe, J.A. Esteban. Facilitation of AMPA receptor synaptic delivery as a molecular mechanism for cognitive enhancement. PLoS Biology (in press).
  • Mara et al Dyrk1A influences neuronal morphogenesis through regulation of cytoskeletal dynamics in mammalian cortical neuron. Cerebr Corteex (in press).
  • Franco A, Knafo S, Banon-Rodriguez I, Merino-Serrais P, Fernaud-Espinosa I, Nieto M, Garrido JJ, Esteban JA, Wandosell F, Anton IM. (2011) WIP Is a Negative Regulator of Neuronal Maturation and Synaptic Activity. Cereb Cortex. Aug 1. [Epub ahead of print].
  • Merino-Serrais P, Knafo S, Alonso-Nanclares L, Fernaud-Espinosa I, Defelipe J (2011). Layer-specific alterations to CA1 dendritic spines in a mouse model of Alzheimer's disease. Hippocampus 21(10):1037-1044.
  • Sánchez-Ponce D, Muñoz A, Garrido JJ (2011) Casein kinase 2 and microtubules control axon initial segment formation. Moll and Cell Neurosci 46: 222- 234
  • Sánchez-Ponce D, DeFelipe J, Garrido JJ, AMuñoz A (2011) Maturation of the cisternal organelle in the hippocampal neuron’s axon initial segment. Moll and Cell Neurosci 48: 104-116
  • Sánchez-Ponce D, Blázquez Llorca L, DeFelipe J, Garrido JJ, Alberto Muñoz (2011) Colocalization of α-actinin and synaptopodin in the pyramidal cell axon initial segment. Cerebral Cortex Epub Sep 21
  • León G, DeFelipe J, Muñoz A 2011 Effects of amyloid-beta plaque proximity on the axon initial segment of pyramidal cells. Journal of Alzheimer’s Disease. In Press
  • J. Morales, L. Alonso-Nanclares, J. R. Rodríguez, A. Merchán-Pérez, J. de Felipe, A. Rodríguez. "Fast interactive quantification of synapses in the cerebral cortex” International Journal of Artificial Intelligence Tools. World Scientific Publishing Co. ISSN 0218-2130 DOI: 10.1142/S0218213011000139 Vol.: 20(2) Pages: 239-252 Apr., 2011
  • Navarrete M, Perea G, Fernandez de Sevilla D, Gómez-Gonzalo M, Nuñez A, Martín E and Araque A (2012) Astrocytes mediate in vivo cholinergic-induced synaptic plasticity. PLoS Biology 10: e1001259.
  • Navarrete M, Perea G, Maglio L, Pastor J, García de Sola R and Araque A (2011) Astrocyte-neuron signaling in human brain tissue. Cerebral Cortex, under revision.
  • Araque A, Navarrete M (2011). Electrically driven insulation in the central nervous system. Science 333: 1587-1588.
  • Navarrete M, Araque A (2011) Basal synaptic transmission: astrocytes rule! Cell 146: 675-677.
  • Porto-Pazos AB, Veiguela N, Mesejo P, Navarrete M, Alvarellos A, Ibáñez O, Pazos A, Araque A (2011) Artificial astrocytes improve neural network performance. PLoS One 6:e19109.
  • Guerra, L., McGarry, L., Robles, V., Bielza, C., Larrañaga, P., Yuste, R. (2011). Comparison between supervised and unsupervised classification of neuronal cell types: A case study. Developmental Neurobiology, 71 (1), 71-82.
  • R. Santana, C. Bielza, P. Larrañaga (2011). Optimizing brain networks topologies using multiobjective evolutionary computation. Neurinformatics, 9 (1), 3-19.
  • P. López-Cruz, C. Bielza, P. Larrañaga, R. Benavides-Piccione, J. DeFelipe (2011). Models and simulation of 3D neuronal dendritic trees using Bayesian networks. Neuroinformatics, 347-369.
  • D. Vidaurre, C. Bielza, P. Larrañaga (2011). On nonlinearity in neural encoding models applied to the primary visual cortex. Network: Computation in Neural Systems, 22 (1-4), 97-125.
  • D. Vidaurre, C. Bielza, P. Larrañaga (2011). Lazy lasso for local regression. Computational Statistics DOI: 10.1007/s00180-011-0274-0. In Press.
  • R. Armañanzas, P. Larrañaga, C. Bielza (2011). Ensemble transcript interaction networks: A case study on Alzheimer’s disease. Computer Methods and Programs in Biomedicine. In Press.
  • D. Vidaurre, C. Bielza, P. Larrañaga (2011). Forward stagewise naive Bayes. Progress in Artificial Intelligence. In Press. (with application to fMRI data analysis).
  • Vidaurre, D., Bielza, C. & Larrañaga, P. (2011). An L1-regularized naive Bayes-inspired classifier for discarding redundant predictors. Submitted to International Journal of Pattern Recognition and Artificial Intelligence. (with application to fMRI data analysis).
  • J. Morales, L. Alonso-Nanclares, J. R. Rodríguez, A. Merchán-Pérez, J. de Felipe, A. Rodríguez. "Fast interactive quantification of synapses in the cerebral cortex” International Journal of Artificial Intelligence Tools. World Scientific Publishing Co. ISSN 0218-2130 DOI: 10.1142/S0218213011000139 Vol.: 20(2) Pages: 239-252 Apr., 2011
  • J. Morales, L. Alonso-Nanclares, J. R. Rodríguez, J. de Felipe, A. Rodríguez and A. Merchán-Pérez. "ESPINA: a tool for the automated segmentation and counting of synapses in large stacks of electron microscopy images” Frontiers in Neuroanatomy ISSN 1662-5129 DOI: 10.3389/fnana.2011.00018 Vol.: 5(18) Pages: 1-8 Date: Mar., 2011.

Other Publications

  • Higuera-Matas, A., Montoya, G.L., Coria, S.M., MIGUÉNS, M., García-Lecumberri, C., and Ambrosio, E (2011). Differential gene expression in the nucleus accumbens and frontal cortex of Lewis and Fischer 344 rats relevant to drug addiction. Current Neuropharmacology 9(1):143-150.
  • Higuera-Matas A, Soto-Montenegro ML, Montoya GL, García-Vázquez V, Pascau J, MIGUÉNS M, Del Olmo N, Vaquero JJ, García-Lecumberri C, Desco M, Ambrosio E (2011). Chronic Cannabinoid Administration to Periadolescent Rats Modulates the Metabolic Response to Acute Cocaine in the Adult Brain. Mol Imaging Biol 13(3): 411-415.
  • Miguens M., Coria SM., Higuera-Matas A., Fole A., Ambrosio E., Del Olmo N. (2011). Depotentiation of hippocampal long-term potentiation depends on genetic background and is modulated by cocaine self-administration. Neuroscience 187: 36-42.
  • DeFelipe J and Sotelo C (2011) Goodbye Ted (an Obituary for Edward G. Jones). Front. Neuroanat. 5:44. doi: 10.3389/fnana.2011.00044
  • Alejandro Higuera-Matas, Miguel Miguens, Nuria del Olmo, Carmen García-Lecumberri and Emilio Ambrosio. Neural Changes Developed during the Extinction of Cocaine Self-Administration Behavior. Pharmaceuticals 2011, 4, 1315-1327; doi: 10.3390/ph4101315.
  • Armañanzas, R., Bielza, C., Larrañaga, P. & Martínez-Martín, P. (2011). Restating Parkinson's disease severity indices by means of non-motor criteria. Technical Report, UPM-FI/DIA/2011-2.

2012 CBBP Scientific Publications

  • Benavides-Piccione R, Fernaud-Espinosa I, Robles V, Yuste R, DeFelipe J. Age-Based Comparison of Human Dendritic Spine Structure Using Complete Three-Dimensional Reconstructions. Cereb Cortex. 2012 Jun 17
  • Morales J, Benavides-Piccione R, Rodríguez A, Pastor L, Yuste R, DeFelipe J. Three-Dimensional Analysis of Spiny Dendrites Using Straightening and Unrolling Transforms. Neuroinformatics. 2012 May 27
  • Knafo S, Venero C, Sánchez-Puelles C, Pereda-Peréz I, Franco A, Sandi C, Suárez LM, Solís JM, Alonso-Nanclares L, Martín ED, Merino-Serrais P, Borcel E, Li S, Chen Y, Gonzalez-Soriano J, Berezin V, Bock E, DeFelipe J, Esteban JA. Facilitation of AMPA receptor synaptic delivery as a molecular mechanism for cognitive enhancement. PLoS Biol. 2012 Feb; 10 (2):e1001262. Epub 2012 Feb 21.
  • Martinez de Lagran M, Benavides-Piccione R, Ballesteros-Yañez I, Calvo M, Morales M, Fillat C, DeFelipe J, Ramakers GJ, Dierssen M. Dyrk1A Influences Neuronal Morphogenesis Through Regulation of Cytoskeletal Dynamics in Mammalian Cortical Neurons. Cereb Cortex. 2012 Jan 2.
  • DeFelipe J, Markram H, Rockland KS. The neocortical column. Front Neuroanat. 2012. 6: 22. Epub 2012 Jun 26
  • Avila J, León-Espinosa G, García E, García-Escudero V, Hernández F, DeFelipe J. Tau Phosphorylation by GSK3 in Different Conditions. Int J Alzheimers Dis. 2012; 2012:578373. Epub 2012 May 17.
  • León-Espinosa G, DeFelipe J, Muñoz A. Effects of amyloid-β plaque proximity on the axon initial segment of pyramidal cells. J Alzheimers Dis. 2012; 29 (4):841-52.
  • Rockland KS, DeFelipe J (2012) Cortical GABAergic neurons: stretching it. Front Neuroanat. 2012; 6:16. Epub 2012 May 31. Front Neuroanat. 2012; 6: 22.
  • Jimenez-Mateos EM, Engel T, Merino-Serrais P, McKiernan RC, Tanaka K, Mouri G, Sano T, O'Tuathaigh C, Waddington JL, Prenter S, Delanty N, Farrell MA, O'Brien DF, Conroy RM, Stallings RL, Defelipe J, Henshall DC (2012). Silencing microRNA-134 produces neuroprotective and prolonged seizure-suppressive effects. Nat Med. 18:1087-1094.
  • Sánchez-Ponce D, DeFelipe J, Garrido JJ, Muñoz A (2012) Developmental expression of Kv potassium channels at the axon initial segment of cultured hippocampal neurons. Plos One 7 (10):e48557. doi: 10.1371/journal.pone.0048557.
  • Merchán-Pérez A, Rodríguez J-R, González S, Robles V, DeFelipe J, Larrañaga P and Bielza C. Three-Dimensional Spatial Distribution of Synapses in the Neocortex: A Dual-Beam Electron Microscopy Study. Cerebral Cortex, in press.
  • Inan M, Blazquez-Llorca L, Merchan-Perez A, Anderson SA, DeFelipe J and Yuste R Dense and Overlapping Innervation of Pyramidal Neurons by Neocortical Chandelier Cells. Journal of Neuroscience, in press.
  • Llorens-Martín M, Fuster-Matanzo A, Teixeira CM, Jurado-Arjona J, Ulloa F, Defelipe J, Rábano A, Hernández F, Soriano E, Avila J. GSK-3β overexpression causes reversible alterations on postsynaptic densities and dendritic morphology of hippocampal granule neurons in vivo. Mol Psychiatry. doi: 10.1038/mp.2013.4. [Epub ahead of print]
  • Blazquez-Llorca L, Merchán-Pérez A, Rodríguez R, Gascón J, Defelipe J (2013) FIB/SEM Technology and Alzheimer's Disease: Three-Dimensional Analysis of Human Cortical Synapses. J Alzheimers Dis. [Epub ahead of print]
  • Leon-Espinosa G, Garcia E, Garcia-Escudero V, Hernandez F DeFelipe J, Avila,J Changes in tau phosphorylation in hibernating rodents. J Neurosci Res (in press)
  • Merino-Serrais P, Benavides-Piccione R, Blazquez-Llorca L, Kastanauskaite A, Rábano A, Avila J, DeFelipe J The influence of phosphotau on dendritic spines of cortical pyramidal neurons in Alzheimer’s disease patients. Brain (in press)
  • Alonso-Nanclares L, Merino-Serrais P, Gonzalez S, DeFelipe J. Synaptic changes in the dentate gyrus of app/ps1 transgenic mice revealed by electron microscopy. J Neuropathol Exp Neurol (in press)
  • Pedro L. López-Cruz, Pedro Larrañaga, Javier DeFelipe, Concha Bielza. Bayesian network modeling of the consensus between experts: An application to neuron classification. International Journal of Approximate Reasoning: accepted.
  • DeFelipe J, López-Cruz PL, Benavides-Piccione R, Bielza C, Larrañaga, et al. Classification and nomenclature of neocortical GABAergic interneurons. Nature Reviews Neuroscience: accepted.
  • Merchán-Pérez A, Rodríguez J-R, González S, Robles V, DeFelipe J, Larrañaga P and Bielza C. Three-Dimensional Spatial Distribution of Synapses in the Neocortex: A Dual-Beam Electron Microscopy Study. Cerebral Cortex, in press.
  • Larrañaga P, Concha Bielza C, DeFelipe J. Alan Turing y la neurociencia. Mente y Cerebro, 57, 49–51.
  • Santana, R., Bielza, C. & Larrañaga, P. Conductance interaction identification by means of Boltzmann distribution and mutual information analysis in conductance-based neuron models. BMC Neuroscience, 13(Suppl 1), P100.
  • Armañanzas, R., Larrañaga, P., Bielza, C. Ensemble transcript interaction networks: A case study on Alzheimer's disease. Computer Methods and Programs in Biomedicine, 108(1), 442-450.
  • Borchani, H., Bielza, C., Martínez-Martín, P., Larrañaga, P. Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39). Journal of Biomedical Informatics, 45, 1175-1184.
  • Morales, D., Vives-Gilabert, Y., Gómez-Ansón, B., Bengoetxea, E., Larrañaga, P., Bielza, C., Pagonabarraga, J., Kulisevsky, J., Corcuera-Solano, I., Delfino, M. Predicting dementia development in Parkinson's disease using Bayesian network classifiers. Psychiatry Research: NeuroImaging, accepted.
  • Santana, R., Bielza, C., Larrañaga, P. Regularized logistic regression and multi-objective variable selection for classifying MEG data. Biological Cybernetics, 106(6-7), 389-405.
  • Vidaurre, D., Bielza, C., Larrañaga, P. Lazy lasso for local regression. Computational Statistics, 27(3), 531-550 (with application to fMRI data analysis).
  • Vidaurre, D., Rodríguez, E.E., Bielza, C., Larrañaga, P., Rudomin, P. A new feature extraction method for signal classification applied to cat spinal cord signals. Journal of Neural Engineering, accepted.
  • Vidaurre, D., Bielza, C., Larrañaga, P. Classification of neural signals from sparse autoregressive features. Neurocomputing: accepted.
  • García-Bilbao, A., Armañanzas, R., Ispizua, Z., Calvo, B., Alonso-Varona, A., Inza, I., Larrañaga, P., López-Vivanco, G., Suárez-Merino, B., Betanzos, M. Identification of a biomarker panel for colorectal cancer diagnosis. BMC Cancer, 12(43).
  • García-Torres, M., Armañanzas, R., Bielza, C. & Larrañaga, P. (2013). Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Information Sciences, 222, 229-246.
  • Borchani, H., Bielza, C., Larrañaga, P., Toro, C. Learning multi-dimensional Bayesian network classifiers using Markov blankets: A case study in the prediction of HIV-1 reverse transcriptase and protease inhibitors. Artificial Intelligence In Medicine, accepted.
  • Guerra, L., V. Robles, Bielza, C., Larrañaga, P. A comparison of clustering quality indices using outliers and noise. Intelligent Data Analysis, 16(4), 703-715.
  • Ibañez, A., Bielza, C., Larrañaga, P. Relationship among research collaboration, number of documents and number of citations. A case study in Spanish computer science production in 2000-2009. Scientometrics, accepted.
  • Ibañez, A., Bielza, C., Larrañaga, P. Analysis of scientific activity in Spanish public universities in the area of computer science. Revista Española de Documentación Científica, accepted.
  • Larrañaga P., Bielza, C. Alan Turing and Bayesian statistics. Mathware & Soft Computing Magazine, 19, 2, 23-24.
  • Larrañaga, P., Karshenas, H., Bielza, C., Santana, R. A review on probabilistic graphical models in evolutionary computation. Journal of Heuristics, 18(5), 795-819.
  • P. Larrañaga, H. Karshenas, C. Bielza, R. Santana. A Review on Evolutionary Algorithms in Bayesian Network Learning and Inference Tasks. Information Sciences, accepted.
  • H. Karshenas, R. Santana, C. Bielza, P. Larrañaga. Regularized Continuous Estimation of Distribution Algorithms. Applied Soft Computing, accepted.
  • Morales J, Benavides-Piccione R, Rodríguez A, Pastor L, Yuste R, DeFelipe J. “Three-dimensional analysis of spiny dendrites using straightening and unrolling transforms” Neuroinformatics Springer Verlag. Vol. 10 No. 4 ISSN 1539-2791 DOI: 10.1007/s12021-012-9153-2 pp. 391-407. 2012 Indexed: JCR
  • Merchán-Pérez A, Rodríguez J-R, González S, Robles V, DeFelipe J, Larrañaga P and Bielza C. Three-Dimensional Spatial Distribution of Synapses in the Neocortex: A Dual-Beam Electron Microscopy Study. Cerebral Cortex, in press.
  • García JA, Peña JM,. McHugh S, Jérusalem A. A model of the spatially dependent mechanical properties of the axon during its growth. Computational Modeling in Engineering & Science (CMES), in press.
  • Jérusalem A, Dao M. Continuum modeling of neuronal cell under blast loading. Acta Biomaterialia, 8 (9), 3360-3371, 2012
  • Navarrete M, Perea G, Maglio L, Pastor J, de Sola RG, Araque A (2012) Astrocyte calcium signal and gliotransmission in human brain tissue. Cerebral Cortex (in press)
  • Navarrete M, Perea G, Fernandez de Sevilla D, Gómez-Gonzalo M, Núñez A, Martín ED, Araque A (2012) Astrocytes mediate in vivo cholinergic-induced synaptic plasticity. Plos Biology 10: e1001259.
  • Zorec R, Araque A, Carmignoto G, Haydon PG, Verkhratsky A, Parpura V (2012) Astroglial excitability and gliotransmission: An appraisal of Ca2+ as a signaling route. ASN Neuro 4: e00080.

Other CBBP Publications

  • Karshenas, H., Santana, R., Bielza, C., Larrañaga, P. Continuous Estimation of Distribution Algorithms Based on Factorized Gaussian Markov Networks. In Adaptation, Learning & Optimization. Series Vol. 14 (editors), Markov Networks in Evolutionary Algorithms. Springer
  • Gonzalez S. Análisis de simulación de Sinapsis. Technical report.
  • Gracia A and S. Gonzalez S. MedVir aplicado a la morfología de las neuronas. Technical report.
  • Alonso-Nanclares L, Merino-Serrais P, Gonzalez S, DeFelipe J. Synaptic changes in the dentate gyrus of app/ps1 transgenic mice revealed by electron microscopy. J Neuropathol Exp Neurol (in press)

Other Publications

  • Peña JM. El Futuro de la Fármaco-Economía: Minería de datos y supercomputación, in “Fármaco-Economía” Monográficas de Oncología Médica, to appear 2012

2013 CBBP Scientific Publications

  • Benavides-Piccione R, Fernaud-Espinosa I, Robles V, Yuste R, DeFelipe J. Age-Based Comparison of Human Dendritic Spine Structure Using Complete Three-Dimensional Reconstructions. Cereb Cortex. 2012 Jun 17
  • Armañanzas R, Alonso-Nanclares L, DeFelipe-Oroquieta J, Kastanauskaite A, de Sola R G, DeFelipe J, Bielza C, Larrañaga P (2013). Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery. PLoS ONE, 8 (4), e62819. PMID: 23646148
  • Alonso-Nanclares L, Merino-Serrais P, Gonzalez S, DeFelipe J (2013). Synaptic changes in the dentate gyrus of APP/PS1 transgenic mice reveales by electron microscopy. Journal of Neuropathology and Experimental Neurology 72(5): 386-95. Doi: 10.1097/ NEN.0b013e31828d41ec. PMID: 23584198.
  • LaTorre A, Alonso-Nanclares L, Muelas, S, Peña JM, DeFelipe J (2013). Segmentation of Neuronal Nuclei Based on Clump Splitting and a Two-step Binarization of Images. Expert Systems with Applications, 40 (16): 6521-30.
  • Alonso-Nanclares L and DeFelipe J (2013). Alterations of the microvascular network in the sclerotic hippocampus of patients with temporal lobe epilepsy. Epilepsy and Behaviour (in press)
  • LaTorre A, Alonso-Nanclares L, Muelas, S, Peña JM, DeFelipe J (2013). 3D Segmentations of Neuronal Nuclei from Confocal Microscope Image Stacks. Front. Neuroanat. 7:49. doi:10.3389/fnana.2013.00049
  • Blazquez-Llorca, L., Merchán-Pérez, A., Rodríguez, J.-R., Gascón, J., and Defelipe, J. (2013). FIB/SEM Technology and Alzheimer’s Disease: Three-Dimensional Analysis of Human Cortical Synapses. J. Alzheimers Dis. 34, 995–1013.
  • Inan, M., Blázquez-Llorca, L., Merchán-Pérez, A., Anderson, S. A., Defelipe, J., and Yuste, R. (2013). Dense and overlapping innervation of pyramidal neurons by chandelier cells. J. Neurosci. 33, 1907–1914.
  • Merchán-Pérez, A., Rodríguez, J.-R., González, S., Robles, V., DeFelipe, J., Larrañaga, P., and Bielza, C. (2013). Three-Dimensional Spatial Distribution of Synapses in the Neocortex: A Dual-Beam Electron Microscopy Study. Cereb. Cortex, bht018.
  • Montes, J., Gomez, E., Merchán-Pérez, A., DeFelipe, J., and Peña, J.-M. (2013). A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses. PLoS ONE 8, e68888.
  • Morales, J., Rodríguez, A., Rodríguez, J.-R., DeFelipe, J., and Merchán-Pérez, A. (2013). Characterization and extraction of the synaptic apposition surface for synaptic geometry analysis. Front. Neuroanat 7, 20.
  • Benavides-Piccione R, Fernaud-Espinosa I, Robles V, Yuste R, DeFelipe J (2013) Age-Based Comparison of Human Dendritic Spine Structure Using Complete Three-Dimensional Reconstructions. Cereb Cortex 23:1798-1810.
  • DeFelipe J, López-Cruz PL, Benavides-Piccione R, Bielza C, Larrañaga P, Anderson S, Burkhalter A, Cauli B, Fairén A, Feldmeyer D, Fishell G, Fitzpatrick D, Freund TF, González-Burgos G, Hestrin S, Hill S, Hof PR, Huang J, Jones EG, Kawaguchi Y, Kisvárday Z, Kubota Y, Lewis DA, Marín O, Markram H, McBain CJ, Meyer HS, Monyer H, Nelson SB, Rockland K, Rossier J, Rubenstein JL, Rudy B, Scanziani M, Shepherd GM, Sherwood CC, Staiger JF, Tamás G, Thomson A, Wang Y, Yuste R, Ascoli GA (2013). New insights into the classification and nomenclature of cortical GABAergic interneurons. Nature Neuroscience 14:202-216.
  • Llorens-Martín M, Fuster-Matanzo A, Teixeira CM, Jurado-Arjona J, Ulloa F, Defelipe J, Rábano A, Hernández F, Soriano E, Avila J. GSK-3β overexpression causes reversible alterations on postsynaptic densities and dendritic morphology of hippocampal granule neurons in vivo. Mol Psychiatry. 2013 Apr; 18(4):451-60.
  • Leon-Espinosa G, Garcia E, Garcia-Escudero V, Hernandez F DeFelipe J, Avila,J (2013) Changes in tau phosphorylation in hibernating rodents. J Neurosci Res. J Neurosci Res. 2013 Apr 19. doi: 10.1002/jnr.23220.
  • Miguéns M, Kastanauskaite A, Coria SM, Selvas A, Ballesteros-Yañez I, Defelipe J, Ambrosio E (2013) The Effects of Cocaine Self-Administration on Dendritic Spine Density in the Rat Hippocampus Are Dependent on Genetic Background. Cereb Cortex. 2013 Aug 21. [Epub ahead of print]
  • Brito JP, Mata S, Bayona S, Pastor L, Defelipe J, Benavides-Piccione R. (2013) Neuronize: a tool for building realistic neuronal cell morphologies. Front Neuroanat. 2013; 7:15. doi: 10.3389/fnana.2013.00015.
  • Merino-Serrais P, Benavides-Piccione R, Blazquez-Llorca L, Kastanauskaite A, Rábano A, Avila J, DeFelipe J (2013) The influence of phosphotau on dendritic spines of cortical pyramidal neurons in Alzheimer’s disease patients. Brain 136:1913-1928.
  • Llorens-Martín M, Fuster-Matanzo A, Teixeira CM, Jurado-Arjona J, Ulloa F, Defelipe J, Rábano A, Hernández F, Soriano E, Avila J. (2013) Alzheimer disease-like cellular phenotype of newborn granule neurons can be reversed in GSK-3β-overexpressing mice. Mol Psychiatry. 18(4):395. doi: 10.1038/mp.2013.27
  • López-Cruz, P.L., Larrañaga, P., DeFelipe, J., Bielza, C. (2014) Bayesian network modeling of the consensus between experts: An application to neuron classification. International Journal of Approximate Reasoning 55 (1): 3-22. In Press
  • Alejandro Antón-Fernández, Pablo Rubio-Garrido, Javier DeFelipe, and Alberto Muñoz (2013) Selective presence of a giant saccular organelle in the axon initial segment of a subpopulation of layer V pyramidal neurons. Brain Structure and Function. [Epub ahead of print].
  • P. Toharia, J. Morales, O. de Juan, I. Fernaud-Espinosa, A. Rodríguez, J. DeFelipe, Musical representation of dendritic spine distribution: a new exploratory tool, Neuroinformatics Springer Verlag. ISSN 1539-2791 DOI: 10.1007/s12021-013-9195-0 (in, press) pp. 13
  • R. Armañanzas, C. Bielza, K.R. Chaudhuri, P. Martínez-Martín, P. Larrañaga (2013). Unveiling relevant non-motor Parkinson’s disease severity symptoms using a machine learning approach. Artificial Intelligence in Medicine, 58(3), 195–202.
  • H. Borchani, C. Bielza, P. Martínez-Martín, P. Larrañaga (2013). Predicting EQ-5D from the Parkinson’s disease questionnaire using multi-dimensional Bayesian network classifiers. Biomedical Engineering: Applications, Basis and Communications, in press.
  • D. Morales, Y. Vives-Gilabert, B. Gómez-Ansón, E. Bengoetxea, P. Larrañaga, C. Bielza, J. Pagonabarraga, J. Kulisevsky, I. Corcuera-Solano, M. Delfino (2013). Predicting dementia development in Parkinson's disease using Bayesian network classifiers. Psychiatry Research: NeuroImaging, 213, 92-98
  • R. Santana, L. McGarry, C. Bielza, P. Larrañaga, R. Yuste (2013). Classification of neocortical interneurons using affinity propagation. Frontiers in Neural Circuits, in press.
  • D. Vidaurre, C. Bielza, P. Larrañaga (2013). Classification of neural signals from sparse autoregressive features. Neurocomputing, 111, 21–26.
  • C. Bielza, J.A. Fernández del Pozo, P. Larrañaga (2013). Parameter control of genetic algorithms by learning and simulation of Bayesian Networks. A case study for the optimal ordering of tables. Journal of Computer Science and Technology, 28(4), 720–731.
  • H. Borchani, C. Bielza, C. Toro, P. Larrañaga (2013). Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers. Artificial Intelligence in Medicine, 57(3), 219–229.
  • M. García-Torres, R. Armañanzas, C. Bielza, P. Larrañaga (2013). Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Information Sciences, 222, 229–246.
  • L. Guerra, C. Bielza, V. Robles, P. Larrañaga (2013). Semi-supervised projected model-based clustering. Data Mining and Knowledge Discovery, in press.
  • A. Ibáñez, C. Bielza, P. Larrañaga (2013). Análisis de la actividad científica de las universidades públicas españolas en el área de las tecnologías informáticas. Revista Española de Documentación Científica, 36(1), e002
  • A. Ibáñez, C. Bielza, P. Larrañaga (2013). Cost-sensitive selective naive Bayes classifiers for predicting the increase of the h-index for scientific journals. Neurocomputing, in press.
  • A. Ibáñez, P. Larrañaga, C. Bielza (2013). Cluster methods for assessing research performance: Exploring Spanish computer science. Scientometrics, in press.
  • A. Ibáñez, C. Bielza, P. Larrañaga (2013). Relationship among research collaboration, number of documents and number of citations. A case study in Spanish computer science production in 2000-2009. Scientometrics, in press.
  • H. Karshenas, R. Santana, C. Bielza, P. Larrañaga (2013). Multi-objective estimation of distribution algorithms based on joint modeling of objectives and variables. IEEE Transactions on Evolutionary Computation, in press.
  • H. Karshenas, R. Santana, C. Bielza, P. Larrañaga (2013). Regularized continuous estimation of distribution algorithms. Applied Soft Computing, 13(5), 2412-2432.
  • P. Larrañaga, H. Karshenas, C. Bielza, R. Santana (2013). A review on evolutionary algorithms in Bayesian network learning and inference tasks. Information Sciences, 233, 109–125.
  • P.L. López-Cruz, C. Bielza, P. Larrañaga (2013). Directional naive Bayes classifiers. Pattern Analysis and Applications, in press.
  • P.L. López-Cruz, C. Bielza, P. Larrañaga (2013). Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation. International Journal of Approximate Reasoning, in press.
  • J. Read, C. Bielza, P. Larrañaga (2013). Multi-dimensional classification with super-classes. IEEE Transactions on Knowledge and Data Engineering, in press.
  • R. Santana, R. Armañanzas, C. Bielza, P. Larrañaga (2013). Network measures for information extraction in evolutionary algorithms. International Journal of Computational Intelligence Systems, 6(6), 1163-1188.
  • E. Sucar, C. Bielza,  E. F. Morales, P. Hernández-Leal,  J. H. Zaragoza,  P. Larrañaga (2013). Multi-label classification with Bayesian network-based chain classifiers. Pattern Recognition Letters, in press.
  • D. Vidaurre, C. Bielza, P. Larrañaga (2013). A survey of L1 regression. International Statistical Review, in press.
  • D. Vidaurre, C. Bielza, P. Larrañaga (2013). An L1-regularized naive Bayes-inspired classifier for discarding redundant predictors. International Journal on Artificial Intelligence Tools, 22(4), 1350019.
  • D. Vidaurre, M. van Gerven, C. Bielza, P. Larrañaga, T. Heskes (2013). Bayesian partial least squares. Neural Computation, in press.
  • D. Vidaurre, C. Bielza, P. Larrañaga (2013). Sparse regularized local regression. Computational Statistics and Data Analysis, 62, 122–135.
  • Pablo Márquez-Neila, Luis Baumela, Luis Alvarez. A morphological approach to curvature-based evolution of curves and surfaces, IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 36(1), pp. 2-17, 2014.
  • A. Jérusalem, J.A. García, A. Merchán-Pérez and J.M. Peña, A computational model coupling mechanics and electrophysiology in spinal cord injury Biomechanics and Modeling in Mechanobiology, (in press)
  • Araque A, Camignoto G, Haydon PG, Oliet SH, Robitaille R, Volterra A (2014) Gliotransmitters travel in time and space. Neuron (in press).
  • Fields RD, Araque A, Johansen-Berg H, Lim SS, Lynch G, Nave KA, Nedergaard M, Perez R, Sejnowski T, Wake H (2013) Glial Biology in Learning and Cognition. The Neuroscientist (in press).
  • Pérez-Alvarez A, Araque A, Martín ED (2013) Confocal microscopy for astrocyte in vivo imaging: Recycle and reuse in microscopy. Frontiers in Cellular Neuroscience 7:51.
  • Pérez-Alvarez A, Araque A (2013) Astrocyte-neuron interaction at Tripartite Synapses. Current Drug Targets 14:1220-1224.
  • Navarrete M, Perea G, Maglio L, Pastor J, de Sola RG, Araque A (2013) Astrocyte calcium signal and gliotransmission in human brain tissue. Cerebral Cortex 23: 1240-1246.

Other CBBP Publications

  • Comment by Javier DeFelipe on: Stem Cells Treat Epileptic Symptoms in Mice. Alzheimer Research Forum. May 8, 2013. Available at http://www.alzforum.org/new/detail.asp?id=3483. Accessed May 17, 2013
  • DeFelipe J. Análisis del cerebro: innovación tecnológica y estrategia interdisciplinar. CIC NETWORK 24-28, 2013.
  • DeFelipe J. Cajal's Butterflies of the Soul. OUPblog as it continues to be a popular title at SFN.
  • DeFelipe J, Alonso-Nanclares L (2013). The Synapse: differences between men and women. In: D.W. Pfaff and Y. Christen (eds.), Multiple Origins of Sex Differences in Brain, Research and Perspectives in Endocrine Interactions. Springer-Verlag, Berlin Heidelberg (DOI 10.1007/978-3-642-33721-5_4)
  • DeFelipe J (2013) Cajal and the discovery of a new artistic world: The neuronal forest. Prog Brain Res. 2013; 203:201-220. In: The Fine Arts, Neurology and Neuroscience: History and Modem Perspectives. Eds: Stanley Finger, Dahlia Zajdel, Francois Boller and Julien Bogousslavsky. Elsevier, New York
  • C. Bielza, A. Salmerón, A. Alonso-Betanzos, J.I. Hidalgo, L. Martínez, A. Troncoso, E. Corchado, J.M. Corchado (Eds.) (2013). Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence, Vol 8109. Springer. 404 pages. ISBN: 978-3-642-40642-3.
  • C. Bielza, A. Salmerón (Eds.) (2013). Actas de la XV Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2013). 158 pages. ISBN: 978-84-695-8348-7.
  • C. Bielza, P. Larrañaga (2013). More than 20 entries in Concise Encyclopaedia of Bioinformatics and Computational Biology. Wiley.
  • L. Guerra, R. Benavides-Piccione, C. Bielza, V. Robles, J. DeFelipe, P. Larrañaga (2013). Semi-supervised projected clustering for classifying GABAergic interneurons. Artificial Intelligence in Medicine 2013, Lecture Notes in Artificial Intelligence 7885, pages 156-165, Springer.
  • P.L. Lopez-Cruz, C. Bielza, P. Larrañaga (2013). Learning conditional linear Gaussian classifiers with probabilistic class labels. Advances in Artificial Intelligence. Lecture Notes in Computer Science 8109, pages 139-148, Springer.
  • P.L. Lopez-Cruz, T.D. Nielsen, C. Bielza, P. Larrañaga (2013). Learning mixtures of polynomials of conditional densities from data. Advances in Artificial Intelligence. Lecture Notes in Computer Science 8109, pages 363-372, Springer.
  • B. Mihaljevic, P. Larrañaga, C. Bielza (2013). Augmented semi-naive Bayes classifier. Advances in Artificial Intelligence. Lecture Notes in Computer Science 8109, pages159-167, Springer.
  • R. Santana, C., Bielza, P. Larrañaga (2013). Changing conduction delays to maximize the number of polychronous groups with an estimation of distribution algorithm. Technical Report, UPM-FI/DIA/2013-1, Technical University of Madrid.13 pages.
  • Kendrick Cetina, Pablo Márquez-Neila, Luis Baumela. Un Estudio Comparativo de Descriptores de Caracteríısticas para la Segmentación de Sinapsis y Mitocondrias. En Actas del III Workshop de Reconocimiento de Formas y Análisis de Imágenes, pp. 25-28, Septiembre 2013.
  • Luis Baumela (Editor).Actas del III Workshop de Reconocimiento de Formas y Análisis de Imágenes. Madrid. 19 de septiembre de 2013. ISBN: 978-84-695-8332-6.
  • Araque A, Navarrete M (2013) El ayer y hoy de los astrocitos. Mente y Cerebro 60: 86-91.

Other Publications

  • P. Toharia, O. D. Robles, J. L. Bosque, Á. Rodríguez, Scalable shot boundary detection, Journal of Supercomputing. Springer Verlag. ISSN 0920-8542 DOI: 10.1007/s11227-012-0784-8 64(1): 89-99 Apr. 2013
  • Validation of a Virtual Reality Knee Arthroscopy Simulator for Surgical Training. Akhtar, K; Bayona, S.; Bello, F; Gupte, CM; Cobbs, JP; Arthroscopy: The Journal of Arthroscopic & Related Surgery. Volumen: Vol 29, 10 Pág. 138 -139. Fecha: 2013/10/31, 2013. Editorial: WB Saunders, Elsevier. ISSN: 07498063. doi: 10.1016/j.arthro.2013.07.177.
  • On-Board Multi-GPU Molecular Dynamics. Marcos Novalbos, Jaime Gonzalez, Miguel Angel Otaduy, Alvaro Lopez-Medrano, Alberto Sanchez: Euro-Par 2013: 862-873, August 2013
  • Assessing Skills Decay on a Knee Arthroscopy Simulator. Akhtar, K; Wijendra, A; Bayona,S.; Gupte,CM; Bello,F; Standfield, N.; Cobbs, JP; Arthroscopy: The Journal of Arthroscopic & Related Surgery. Volumen: Vol 29, 10 Pág. 139-139. Fecha: 2013/10/31, 2013 WB Saunders, Elsevier, ISSN: 07498063 doi: 10.1016/j.arthro.2013.07.177
  • GMonE: A complete approach to cloud monitoring. Jesús Montes, Alberto Sánchez, Bunjamin Memishi, Maria s. Pérez, Gabriel Antoniou. Future Generation Computer Systems. Volume 29, Issue 8, 2026—2040, October 2013
  • Jose L. Bosque, Pablo Toharia, Oscar D. Robles, Luis Pastor. "Impact of Information Exchange Policies in Load Balancing Algorithms". Journal of Supercomputing, under review.

Contact

The Cajal Blue Brain project is managed and developed almost entirely at the Polytechnic University of Madrid (UPM), Campus Montegancedo. Researchers and engineers are located in two locations, the Center for Biomedical Technology (CTB) and the Supercomputing and Visualization Center of Madrid (CeSViMa), CTB being the headquarters project.

If you are interested in the project and / or wish to have more information about it, they can get through social networks, VCard, QR code, or the contact form shown below:

Contact
Cajal Blue Brain Project
Centro de Tecnología Biomédica (CTB)
Campus de Montegancedo, Universidad Politécnica de Madrid
Pozuelo de Alarcon, 28223 Madrid, España
f
T
G
Y
Responsive image

Contact Form