SP2 Human Brain Organisation
Our goal in SP2 is to develop neuroscientific concepts, tools, knowledge and datasets to contribute to a better understanding of the human brain.
The data, methods and tools generated in SP2 helps to understand the multi-level and multi-scale organization of the human brain. Such results will be used to create and validate a first reconstruction and simulation of the human brain. Central elements are the functional and structural segregation of the human brain, and its inter-subject variability and genetic factors. The data contributes to the multimodal HBP Atlas (developed and populated in conjunction with SP5), spanning from the molecular, through the cellular, and up to the systems level. We study differences between the human brain and those of other species, particularly non-human primates and mouse (together with SP1). This will allow us to use transformed versions of data for mouse genes, transcripts, proteins, neuron morphologies, etc. to fill gaps in our knowledge of the structural organization of the human brain. We contribute to simulation and analysis of different aspects of brain function and behaviour (in collaboration with SP3, SP5, and SP6), based on detailed knowledge of the brain from molecular, cellular and circuit level (bottom-up) perspectives. We are also linked to SP4, which contributes top-down modelling at the systems and cognitive level. Considering the sheer complexity of the human brain, this research requires the development and application of big data analytics, which will be done in conjunction with SP7. By bringing in a broad range of expertise in human brain research, we will actively contribute to Co-Design Projects for developing the infrastructure of the HBP, in particular "Multi-Level Human Brain Atlas" (CDP3), "Visuo-Motor Integration" (CDP4), and "Modelling for Drug Discovery" (CDP6).
In the Ramp-Up Phase, we generated strategic multi-level data and methods on human brains. These incorporated the morphology of single neurons, regionally specific cellular numbers, activity and function of cortical layers, major connectivity constraints, and transmitter receptor distributions. We also established key pathways between brain regions using several techniques such as MRT, iEEG, immunohistochemistry, receptor autoradiography, cytoarchitectonic mapping, single-cell recordings, and polarized light imaging. We integrated non-human primate research via a Partnering Project to bridge the gap between rodent and human brains. SP2 data was used for simulation, and different maps were integrated into the Human Brain Atlas.
In SGA1, we will work on:
- Identify genetic factors involved in inter-individual variability
- Identify gene mutations involved in brain diseases
- Create a fundamental set of biological information, including genomics, transcriptomics and methylomics data, for a limited number of single cells and brain regions
Morphology and molecular architecture:
- Provide cytoarchitectonic probability maps of the human brain
- Provide multi-level, quantitative maps of cell and subcellular distributions and morphologies in selected regions
- Provide maps of quantitative receptor distributions
- Provide maps of fibre bundles, e.g U-fibres, and long distance fibre tracts, as well as quantitative measures of their microstructure
- Provide quantitative morphological data of selected fibre tracts and intracortical fibre architecture in the human brain using polarized light imaging and electron microscopy
Brain function, segregation, computational architecture and variability:
- Provide maps of the functional segregation of the human brain using fMRI
- Map features coded in columns of the higher visual and auditory cortex and provide models for processing top-down and bottom-up
- Provide models and data on the role of the six cortical layers arising from the architecture of neurons and their connections
- Provide a first mechanistic model of how neural activity is related to brain regions
- Provide information on the relationship between the variability of neurobiological features and inter-individual differences in behavioural phenotypes
- Provide Intracranial EEG recordings from patients and healthy controls
Methods, big data analytics & co-design:
- Link SP2's datasets and parcellations to the accepted template spaces
- Develop novel label propagation methods that make SP2 relevant to mining image data to SP8's Medical Informatics Platform, as well as to the wider scientific community
- Develop methods and high-performance computing production workflows
Data generated in SP2 will be further used for human-mouse brain comparisons (in collaboration with SP1) and delivered to the Platforms, e.g. to feed the HBP Human Brain Atlas and to be used for modelling and simulation experiments.
SP Leader: Katrin AMUNTS
Work Package Leaders:
- WP2.1 Human Neurogenomics: Thomas BOURGERON
- WP2.2 Morphology and Architecture of the Human Brain: A multi-level and multi-modal approach: Francesco PAVONE
- WP2.3 Function and Variability: Simon EICKHOFF
- WP2.4 Comparative Computational Architecture of Multi-Modal Processing Streams (Systems Physiology): Rainer GOEBEL
- WP2.5 Integrative Maps and Models: Jean-Francois MANGIN
- WP2.6 Co-design/Methods and Big Data Analytics: John ASHBURNER
- WP2.7 Coordination and Management: Katrin AMUNTS
Amunts, K., & Zilles, K. (2015). Architectonic mapping of the human brain beyond Brodmann. Neuron, 88: 1086-1107.
Beaujoin, J., Boumezbeur, F., Bernard, J., Axer, M., Mangin, J.-F., & Poupon, C. (2016). Post-mortem mapping of the inner connectivity of the human hippocampus using diffusion MRI at 11.7T. Proceedings of the 22nd Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2016: poster 4253.
Costantini, I., Ghobril, J.P., Di Giovanna, A.P., Mascaro, A.L.A., Silvestri, L., Müllenbroich, M.C., Onofri, L., Conti, V., Vanzi, F., Sacconi, L., Guerrini, R., Markram, H., Iannello, G. & Pavone, F.S. (2015). A versatile clearing agent for multi-modal brain imaging. Scientific Reports, 5: 9808.
Lefranc, S., Roca, P., Perrot, M., Poupon, C., Le Bihan, D., Mangin, J.F, & Rivière, D. (2016). Groupwise connectivity-based parcellation of the whole human cortical surface using watershed-driven dimension reduction. Medical Image Analysis, 30:11-29.
Mohan, H., Verhoog, M. B., Doreswamy, K. K., Eyal, G., Aardse, R., Lodder, B. N., Goriounova1, N. A., Asamoah, B., Brakspear, C., Groot, C., van der Sluis, S., Testa-Silva, G., Obermayer, J., Boudewijns, Z., Narayanan, R. T., Baayen, J. C., Segev, I., Mansvelder, H. D., & de Kock, C.P. (2015). Dendritic and Axonal Architecture of Individual Pyramidal Neurons across Layers of Adult Human Neocortex. Cerebral Cortex, 25: 4839-4853.
Self, M.W., Peters, J.C., Possel, J.K., Reithler, J., Goebel, R., Ris, P., Jeurissen, D., Reddy, L., Claus, S., Baayen, J.C., & Roelfsema, P.R. (2016). The effects of context and attention on spiking activity in human early visual cortex. PLoS Biology, 14: e1002420.
Zeineh, M.M., Palomero-Gallagher, N., Axer, M., Gräßel, D., Goubran, M., Wree, A., Woods, R., Amunts, K., & Zilles, K. (2016). Direct visualization and mapping of the spatial course of fiber tracts at microscopic resolution in the human hippocampus. Cerebral Cortex, doi: 10.1093/cercor/bhw010.