Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac)

Abstract

The need to integrate massively increasing amounts of data on the mammalian brain has driven several ambitious neuroscientific database projects that were started during the last decade. Databasing the brain's anatomical connectivity as delivered by tracing studies is of particular importance as these data characterize fundamental structural constraints of the complex and poorly understood functional interactions between the components of real neural systems. Previous connectivity databases have been crucial for analysing anatomical brain circuitry in various species and have opened exciting new ways to interpret functional data, both from electrophysiological and from functional imaging studies. The eventual impact and success of connectivity databases, however, will require the resolution of several methodological problems that currently limit their use. These problems comprise four main points: (i) objective representation of coordinate–free, parcellation–based data, (ii) assessment of the reliability and precision of individual data, especially in the presence of contradictory reports, (iii) data mining and integration of large sets of partially redundant and contradictory data, and (iv) automatic and reproducible transformation of data between incongruent brain maps. Here, we present the specific implementation of the ‘collation of connectivity data on the macaque brain’ (CoCoMac) database (http://www.cocomac.org). The design of this database addresses the methodological challenges listed above, and focuses on experimental and computational neuroscientists' needs to flexibly analyse and process the large amount of published experimental data from tracing studies. In this article, we explain step–by–step the conceptual rationale and methodology of CoCoMac and demonstrate its practical use by an analysis of connectivity in the prefrontal cortex.

MR connectomics: Principles and challenges

“…Chemical tracing certainly has an important role to play in animal models where some species have been explored relatively extensively-though incompletely and not homogenously (Schmahmann and Pandya, 2006). The macaque is a notable example, where extensive tracing literature is available and has even been collected into a database called CoCoMac (Stephan et al, 2001). Such data is generated from a very heterogeneous material (different individual animals or different species, different techniques) and therefore its consistency and quantification is problematic.…”

“…Visionary work has been done by Rolf Kötter and his colleagues several years ago for the Macaque (Stephan et al, 2001). They developed an open database collecting and organizing a very large amount of Macaque tracing studies (www.cocomac.org).…”

“…In addition to the important advances achieved in chemical tracing methods major initiatives are appearing to use information technology and computer science in order to collect data at highthroughput and to organize data in large databases (Bohland et al, 2009;Stephan et al, 2001). This is not only the case for chemical tracing technology but also for human in vivo imaging with the advent of diffusion MRI technology that has made tremendous progress over the last 10 years.…”

Free-energy and the brain

“…This order is preserved on both an evolutionary and somatic time-scale. The amount of reproducible anatomic information pertaining to the brain is now so vast it can only be organised electronically (e.g., Stephan et al 2001). Furthermore, the brain's spatiotemporal responses, elicited experimentally, are sufficiently reproducible that they support whole fields of neuroscience (e.g., human brain mapping).…”

Feature-reduction and semi-simulated data in functional connectivity-based cortical parcellation

“…The ability to identify these regions is fundamental to evaluation of the normal and/or abnormal brain functions associated with neurological disorders. Although a surge of microarchitectonic and invasive tracer studies has provided substantial microarchitecture and connectivity information regarding cortical parcellation in non-human primates [1,2] , similar evidence concerning the parcellation of the human brain is scarce; it is mostly limited to postmortem observations based on microarchitecture [3][4][5][6][7] or on anatomical landmarks [8] . However, parcellation based on anatomical landmarks and microarchitecture does not always provide accurate functional segregation between distinct areas [9] .…”