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Claus C Hilgetag

Publications and source records attributed to Claus C Hilgetag.

3 recordsLinked to original sources
bioRxiv2016

Cytoarchitectonic similarity is a wiring principle of the human connectome

Understanding the wiring diagram of the human cerebral cortex is a fundamental challenge in neuroscience. Elemental aspects of its organization remain elusive. Here we examine which structural traits of cortical regions, particularly their cytoarchitecture and thickness, relate to the existence and strength of inter-regional connections. We use the architecture data from the classic work of von Economo and Koskinas and state-of-the-art diffusion-based connectivity data from the Human Connectome Project. Our results reveal a prominent role of the cytoarchitectonic similarity of supragranular layers for predicting the existence and strength of connections. In contrast, cortical thickness similarity was not related to the existence or strength of connections. These results are in line with findings for non-human mammalian cerebral cortices, suggesting overarching wiring principles of the mammalian cerebral cortex. The results invite hypotheses about evolutionary conserved neurobiological mechanisms that give rise to the relation of cytoarchitecture and connectivity in the human cerebral cortex.

Neuroscience↗
bioRxiv2015

Principles of ipsilateral and contralateral cortico-cortical connectivity in the mouse

Structural connectivity among cortical areas provides the substrate for information exchange in the brain and is characterized by the presence or absence of connections between specific areas. What principles govern this cortical wiring diagram? Here, we investigate the relation of physical distance and cytoarchitecture with the connectional architecture of the mouse cortex. Moreover, we examine the relation between patterns of ipsilateral and contralateral connections. Our analysis reveals a mirrored and attenuated organization of contralateral connections when compared to ipsilateral connections. Both spatial proximity and cytoarchitectonic similarity of cortical areas are related to the presence or absence of connections. Notably, our analysis demonstrated that these factors conjointly relate better to cortico-cortical connectivity than each factor in isolation, and that the two factors contribute differently to ipsilateral and contralateral connectivity. Distance is more tightly related to the presence or absence of ipsilateral connections, but its contribution greatly diminishes for contralateral connections, while the contribution of cytoarchitectonic similarity remains stable. Our results, conjointly with similar findings in the cat and macaque cortex, suggest that a common set of principles underlies the macroscale wiring of mammalian brains.

Neuroscience↗
bioRxiv2015

Building the Ferretome

Databases of structural connections of the mammalian brain, such as CoCoMac (cocomac.g-node.org) or BAMS (brancusi.usc.edu), are valuable resources for the analysis of brain connectivity and the modeling of brain dynamics in species such as the non-human primate or the rodent, and have also contributed to the computational modeling of the human brain. Another model species that is widely used in electrophysiological or developmental studies is the ferret; however, no systematic compilation of brain connectivity is currently available for this species. Thus, we have started developing a database of anatomical connections and architectonic features of the ferret brain (the Ferretome, www.ferretome.org). The main goals of this database project are: (1) to assemble structural information on the ferret brain that is currently widely distributed in the literature or in different in-house laboratory databases into a single resource which is open to the scientific community; (2) to try and build an extendable community resource that is beneficial to researchers in neuroinformatics and computational neuroscience, as well as to neuroanatomists, by adding value to their data through algorithms for efficient data representation, analysis and visualization; (3) to create techniques for the representation of quantitative and raw data; and (4) to expand existing database ontologies in order to accommodate further neuroarchitectural information for identifying essential relations between brain structure and connections.\n\nThe Ferretome database has adapted essential features of the CoCoMac methodology and legacy. In particular, its data model is derived from CoCoMac. It also uses a semantic parcellation of ferret brain regions as well as a logical brain maps transformation algorithm (objective relational transformation, ORT). The database is being developed in MySQL and has been populated with literature reports on tract tracing observations in the ferret brain using a custom-designed web interface that allows efficient and validated simultaneous input and proofreading by multiple curators. The database is also equipped with a web interface for generating output data that was designed with non-computer science specialist users in mind. This interface can be extended to produce connectivity matrices in several formats including a graphical representation superimposed on established ferret brain maps. An important feature of the Ferretome database is the possibility to trace back entries in connectivity matrices to the original studies archived in the system.\n\nCurrently, the Ferretome contains 50 reports on connections comprising 20 injection reports with more than 150 labeled source and target areas, the majority reflecting connectivity of subcortical nuclei. We hope that the Ferretome database will become a useful resource for neuroinformatics and neural modeling, and will support studies of the ferret brain as well as facilitate advances in comparative studies of mesoscopic brain connectivity.

Neuroscience↗