Connectional characteristics of areas in Walker's map of primate prefrontal cortex

doi:10.1016/S0925-2312(01)00397-6

Neurocomputing

Volumes 38–40, June 2001, Pages 741-746

https://doi.org/10.1016/S0925-2312(01)00397-6 Get rights and content

Abstract

Systematic collations and computational analyses of connectivity data from anatomical tract tracing can yield reliable and valuable insights into the principles governing cortical network organization. Based on an innovative databasing approach (http://www.cocomac.org) we present a preliminary analysis of the connectional organization of primate prefrontal cortex. Multivariate statistics of the connections between Walker's areas reveal distinct orbito-medial and lateral networks linked by anterior cingulate and dorsal prefrontal areas. Novel indices of areal network participation show that ventrolateral prefrontal cortex is a unique relay of information from lateral areas affecting the entire region.

Introduction

The organization of primate prefrontal cortex has remained controversial despite many structural and functional investigations. More reliable insights could arise from analyses of intra-prefrontal connectivity similar to those obtained previously for the two processing streams in the visual cortex or the global organization of the cortex in primates [8], [9]. Prerequisite for such a project is the comprehensive and systematic collation of connectivity information from the wealth of published anatomical tracing studies, and the reliable conversion of these diverse data into a comparable format, a common brain map of the prefrontal cortex. Over the last five years, we have designed and implemented an advanced framework for connectivity databases [5] and created algorithmic tools that successfully tackle the mapping problem between non-spatially defined cortical parcellation schemes [6]. In addition, we have developed and applied multivariate analytical tools that explored the global organizational principles inherent in these large connectivity data sets [1].

Section snippets

Methods

We performed a systematic collation of published tracing studies in the prefrontal cortex of macaque monkeys within the framework of the connectivity database CoCoMac (see http://www.cocomac.org). Data from 148 tracer injections were mapped into Walker's parcellation scheme (W,[7]) using objective relational transformation (ORT, [6]). The resulting connectivity matrix contained nearly complete (>90%) information on the existence and density of connectivity between Walker's cortical areas (Table

Results

Inspection of the connectivity matrix already indicated a conspicuous group of completely intra-connected areas W10, W11, W12, W13, W14, W25, which cover the entire orbital prefrontal cortex and the adjacent most rostral part of the cingulate gyrus on the medial surface (W25 is identical with Brodmann's area 32). This orbito-medial group of areas was seperated clearly from the lateral areas W8A, W8B, W45 and W46 (see also [2]).

More detailed information arose from hierarchical clustering of the

Discussion

Our data analysis, using the CoCoMac database, included nearly every published report on prefrontal cortical connectivity in macaque monkeys. Whereas many projections have been reported repeatedly and with high precision, there are no unambiguous reports on projections from Walker's area 8B to orbital areas W10,…,W14. This must be kept in mind when interpreting the analyses, where absence of information was treated like absence of a connection (see also [10]).

As opposed to previous informal

Rolf Kötter studied medicine and computer science in Germany, Britain and France. He leads the Computational Systems Neuroscience group at the Centre of Anatomy and Brain Research, Düsseldorf University, to establish structure-function relationships in the brain by experimental and computational approaches.

References (10)

C.C. Hilgetag et al.
Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat
Phil. Trans. R. Soc. Lond. B
(2000)
G. Northoff
Functional dissociation between medial and lateral orbitofrontal cortical spatiotemporal activation in negative and positive emotions: A combined FMRI/MEG study
Cereb. Cortex
(2000)
D. Öngür et al.
The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans
Cereb. Cortex
(2000)
A.C. Roberts et al.
The Prefrontal Cortex
(1998)
K.E. Stephan, L. Kamper, A. Bozkurt, G.A.P.C. Burns, M.P. Young, R. Kötter, CoCoMac: advanced database methodology for...

There are more references available in the full text version of this article.

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Claus C. Hilgetag studied Biophysics in Berlin, and Neuroscience in Edinburgh, Oxford and Newcastle. He is currently a Wellcome Trust International Fellow in the Department of Anatomy and Neurobiology, Boston University School of Medicine. His research focuses on the organization of brain connectivity and the neural mechanisms of spatial attention.

Klaas Enno Stephan studies medicine at the Heinrich-Heine University Düsseldorf and Computer Science at the University of Hagen. Working at the C.&O. Vogt Brain Research Institute in Düsseldorf with Rolf Kötter and Karl Zilles as well as with the Neural Systems Group of Malcolm Young at Newcastle. His research focuses on computational approaches to analysis of structural and functional connectivity in the brains of macaque and man.

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Connectional characteristics of areas in Walker's map of primate prefrontal cortex

Abstract

Introduction

Section snippets

Methods

Results

Discussion

Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat

Phil. Trans. R. Soc. Lond. B

Functional dissociation between medial and lateral orbitofrontal cortical spatiotemporal activation in negative and positive emotions: A combined FMRI/MEG study

Cereb. Cortex

The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans

Cereb. Cortex

The Prefrontal Cortex