Time frame: 2017-2020
Origin: FLAG-ERA JTC2017
Funding: Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, National Institutes of Health (NIH), Ministry of Economy and Competitiveness, ANR
Comparative Investigation of the Cortical Circuits in Mouse, Non-human primate and Human
The proposal investigates the differences in physiology, anatomy and organization of the cortex in mouse, non-human primate (NHP) and human. This work will require tight col-laborations between physiologists, anatomists and theoreticians. Our capacity to success-fully integrate across these approaches is strongly supported by the numerous joint publi-cations linking these disciplines in leading international journals by the PI’s of the consor-tium.
Anatomy: Tract-tracing will be used to build macaque and mouse inter-areal corti-cal connectomes. This work will generate large data bases on inter-areal connection weights and quantitative measures of laminar distributions as well as atlases of mouse and macaque. The structural basis of hierarchy and local-global integration will be inves-tigated with viral tracers that will be used to map the long distance and local input to the parent neurons of feedforward and feedback connections in visual cortex of mouse and macaque.
Physiology: Hierarchical processing in the human, NHP and mouse brains will be compared using electrophysiological and imaging approaches and together with the tract tracing, will inform embedded large-scale dynamic models of inter-areal processing in the cortex.
Differences in the inter-areal matrix density lead to widely different core structures across the three species, which will be explored by weighted network structural analysis, thereby revealing the core-periphery organization, which we hypothesize could be relevant to the Global Workspace theory of consciousness (Figure 4). We will manipulate consciousness with anesthetics and stimulation techniques in macaque and mouse thereby exploring Global Neuronal Workspace function via auditory signatures of consciousness in a predic-tive coding paradigm.
Modeling: Conditional Granger causality analysis on multi-variate time series recordings will help identify functional subnetwork motifs, in order to explore the links between structural and dynamical features in the networks across the three spe-cies. Whole-brain computational modeling will address the functional role of the underly-ing anatomy by studying in silico information theoretical measures of integration and seg-regation allowing topological hierarchical analyses of effective connectivity as opposed to anatomical or functional connectivity. Altogether, the project aims to provide quantitative metrics of differences in brain organization related to changes in brain size and order, and will demonstrably underpin the relevance of investigations in the mouse and macaque for understanding the human brain.
Objective 1 and 2 will generate high quality connectivity data to be integrated into the HBP SP5 platform, and this will be facilitated by collaborating with Rembrandt Bakker as a dedicated platform integration scientist. These data will be integrated into the HBP SP5 Neuroinformatics Platform (Jan Bjaalie).
Objective 3 will benefit from integration into HBP SP2, by exploring the roles of feedforward and feedback processing. SP3 investigates cognitive functions. This work will be of relevance for SP4 and SP5 and we have contacted Markus Diesmann and Paul Tiesinga to prepare the integration of this work into HBP.
Collaboration with HBP
Our multimodal data (axonal tracing, ECoG, MEG, fMRI-EEG) will contribute to simulating the brain, via refinement of models in HBP (4.2.3 “Multi-area multi-layer spiking cortical models” led by Sacha van Albada). The macaque and marmoset ECoG data is complementary to fMRI and electrophysiological data to be gathered by Rainer Goebel and Wim Vanduffel. Our tract-tracing mouse connectome will be relevant to SP5 Task 5.2.5 ‘Predictive Neuroinformatics’ headed by Paul Tiesinga. Together, our data and that of the HBP will constitute a wide range of anatomical and activity data from different modalities required to test the reliability of large-scale brain models.