The Cajal Blue Brain Project (CBBP) was approved in 2009 for a period of 10 years (until 2018). This project has made it possible to create a multidisciplinary team of more than 50 researchers (anatomists, physiologists, mathematicians and computer scientists). As a result of the CBBP, several tools and new computational methods have been developed that represent an important technological contribution to the study of the brain.
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) .
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?"
Based on the idea that most connections are established by chemical point-to-point synapses, the terms ‘connectome’ and ‘synaptome’ have been proposed to facilitate the description of the maps of connections at different levels of resolution. The term connectome can be used to refer to maps at the macroscopic and mesoscopic levels, which also allows putative synaptic contacts to be mapped, while synaptome refers to the map of true synaptic contacts at the ultrastructural level (From the connectome to the synaptome: an epic love story, Science 330:1198-1201, 2010). Electron microscopy with serial section reconstruction is the gold standard method for tracing the connections. However, obtaining long series of sections is rather time-consuming and challenging. Consequently, the reconstruction of large tissue volumes is usually impossible.
The introduction of automated or semi-automated electron microscopy techniques at the turn of the century represented a major advance in the study of the synaptome as long series of consecutive sections can now be obtained with little user intervention. As this technology becomes more popular, it will have a huge impact on the study of the ultrastructure of the brain. Despite these high hopes, the principal drawback is that complete reconstructions of whole brains are only possible in some invertebrates or for relatively simple nervous systems, whereas for small mammals like the mouse, it is impossible to fully reconstruct the brain at the ultrastructural level. This is because the magnification needed to visualize and classify the synaptic junctions (i.e., excitatory and inhibitory) and to measure their sizes and shapes accurately enough yields relatively small images (in the order of tens of μm2). As a result, it is only possible to obtain incomplete synaptomes. It seems clear that only by combining studies at the macro-, meso-, and nano-scopic levels can we fully understand the structural arrangement of the brain as a whole.
It is important to emphasize that acquiring multiple samples at different scales (light and electron microscopy) allows us to obtain a dataset that can be statistically analyzed in search of general patterns of organization (Reconstruction and Simulation of Neocortical Microcircuitry. Cell 163:456-492, 201.). This multiple sampling approach assures unprecedented accuracy, since we obtain both precise quantitative data and statistical variability information. The data can be used to identify common and differing principles of organization and to develop algorithms to reconstruct synaptic connections for use in brain models (Figure Integration of microanatomical data).
Furthermore, it seems that the most appropriate approach to make neuroanatomical studies more significant is to link detailed structural data with the incomplete light and electron microscopy wiring diagrams and integrate this neuroanatomical information with genetic, molecular and physiological data. This integration would allow the generation of models that present the data in a form that can be used to reason, make predictions and suggest new hypotheses to discover new aspects of the structural and functional organization of the brain (e.g., Reconstruction and Simulation of Neocortical Microcircuitry. Cell 163:456-492, 201).
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.
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:
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.
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 brain, 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 used to reconstruct, refine, analyze and visualize structures in the brain. It's an open source application and it's functionalities can be expanded by plugins. It's currently available for Linux (Ubuntu based) and Windows machines with the only requirement of a 64 bits CPU.
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
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.
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:
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.
This technique has been incorporated into EspINA and SAS structures can be computed automatically from reconstructed synapses.
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
December 2018. Proyectos Cajal Blue Brain y Human Brain.
June 2018. Cajal Blue Brain Project: 10th Year.
December 2017. Cajal Blue Brain Project: 9th Year (issue 18)
December 2016. Cajal Blue Brain Project: 8th Year.
December 2015. Cell in the Blue Brain Framework.
June 2015. 2015 Project Reorganization.
December 2014. 2014 Project Structure.
December 2012. 2012 Cajal Blue Brain Project.
June 2012. Restructuring of the Cajal Blue Brain Project.
December 2011. Alzheimer 3n.
December 2010. Cajal Blue Brain in Science.
June 2010. Cajal Blue Brain Project on media.
December 2009. First Year of th Project.
June 2009. The Launching of the project.
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: