The structural basis of information transfer from medial temporal lobe to prefrontal cortex in the...

Neurocomputing 44–46 (2002) 753–758www.elsevier.com/locate/neucom

The structural basis of information transferfrom medial temporal lobe to prefrontal

cortex in the macaque monkeyAhmet Bozkurta , Lars Kampera , Klaas E. Stephanc;d ,

Rolf K1ottera;b;∗aComputational Systems Neuroscience Group, C. & O. Vogt Brain Research Institute,

Heinrich Heine University, Universit atsstr. 1, D-40225 Dusseldorf, GermanybDepartment of Anatomy II, Heinrich Heine University, Universit atsstr. 1, D-40225 Dusseldorf,

GermanycInstitute of Medicine, Research Centre J ulich, 52425 J ulich, Germany

dDepartment of Psychology, University of Newcastle-upon-Jyne, NE1 7RU Newcastle, UK

Abstract

A variety of functional studies have emphasized the importance of the medial temporal lobe(MTL) and prefrontal cortex (PFC) for episodic and working memory, respectively. We in-vestigated the structural basis of information transfer from MTL to PFC in primate cerebralcortex using the CoCoMac database (www.cocomac.org), coordinate-independent mapping pro-cedures, and multivariate statistics. In our meta-analysis, we found a clearly decreasing gradientof MTL projections to PFC: strongest from periallocortical regions and weakest from hippocam-pus proper. These projections roughly divide the PFC into medial and lateral groups of areas.c© 2002 Elsevier Science B.V. All rights reserved.

Keywords: Database; Connectivity; Multivariate analyses; Primate; Memory

1. Introduction

The cortical memory system is divided into several speci>c subsystems: for exam-ple, medial temporal lobe structures (MTL) are associated with episodic memory [4],whereas the prefrontal cortex (PFC) is part of the working memory network [7,10]. A

∗ Corresponding author. C. & O. Vogt Brain Research Institute, Heinrich Heine University, Universit1atsstr.1, D-40225 Dusseldorf, Germany. Tel.: +49-211-81-12095; fax: +49-211-81-12336.

E-mail address: rk@hirn.uni-duesseldorf.de (R. K1otter).

0925-2312/02/$ - see front matter c© 2002 Elsevier Science B.V. All rights reserved.PII: S0925 -2312(02)00468 -X

754 A. Bozkurt et al. / Neurocomputing 44–46 (2002) 753–758

challenging question is how these diLerent modalities of memory are integrated in var-ious cognitive contexts, including conscious selection of items from long-term episodicmemory in working memory tasks [2]. A >rst step towards understanding the relationbetween episodic and working memory is to unravel the neuroanatomical basis of in-formation transfer from MTL to PFC. Therefore, we investigated the detailed structureof MTL projections to the prefrontal cortex. In this article, we present the meta-analysisof a comprehensive large-scale network of anatomical projections from MTL to PFCby means of advanced database methods [11] and multivariate statistics [3,5,6].

2. Methods

Using the macaque connectivity database CoCoMac ([11], see www.cocomac.org),we systematically collated data from published articles comprising tracer injectionsin MTL or PFC in macaque monkeys. The MTL structures included in our analysiswere hippocampus proper (CA1–CA4 and DG), subicular complex (ProS, Sub, PreS,ParaS), parahippocampal (TF, TH, and TG), entorhinal (E) and perirhinal (35 and36) areas. Since anatomical reports used diLerent and partially incompatible maps,Objective Relational Transformation (ORT) [12] was used to map all data into acommon space, namely the parcellations proposed by Amaral et al. [1] and Rosene &Van Hoesen [9] for MTL, and Walker [13] for PFC.Since relative strengths of connections were scarcely reported, we evaluated pro-

jections in a binary fashion. We did not distinguish between unknown and absentprojections. Vectors of projection patterns were correlated using the simple matchingalgorithm for binary data (existing or absent projections). Subsequently, correlationvectors were analyzed by two independent multivariate statistical techniques, multi-dimensional scaling and hierarchical clustering, to reveal the overall topography ofsimilarity in connectional patterns between areas.

Hierarchical clustering (HCA) successively amalgamates areas according to hier-archical degrees of similarity between their connectivity patterns. This procedure wasperformed for eLerent projections from MTL to PFC.

Multidimensional scaling (MDS) interprets the correlations between inter-areal con-nectivity vectors as proximities in high-dimensional space. The resulting con>gurationsare projected into two dimensions under maximal preservation of the proximity ranking.Both MDS and HCA have previously been used for the analysis of neural connectivity(e.g. 6–8). In the present analysis, SYSTAT 9.0 (SPSS Inc.) under Windows NT 4.0was used, applying Kruskal’s STRESS formula 1 to MDS and an Euclidean metricwith complete linkage in the case of HCA (Table 1).

3. Results

The anatomical projection patterns were derived from 16 studies including more than90 tracer injections and 780 resulting labeled sizes.

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Table 1“0”, “1”, and no entry represent absent, existing, and unknown projections, respectively. Projection strengthswere not coded in this binary matrix

Source areas Target areas

W10 W11 W12 W13 W14 W24 W25 W8B W46 W9

E 1 1 1 0 1 035 1 0 0 1 1 1 1 136 0 0 1 1 1 0 0TF 0 1 1 1 1 1 1 1 1TG 1 1 1 1 1 1 1 0 1 1TH 0 1 1 1 1 0 1 1 1CA1 1 0 1 1 0 1 0CA2 0 0 0 0 0 0 0CA3 0 0 0 0 0 0 0CA4 0 0 0 0 0 0 0DG 0 0 0 0 0 0 0ProS 0 0 1 1 1 1 0Sub 1 0 1 0 1 1 1 0PreS 0 1 1 1 0 1 1ParaS 0 0 0 0 1

Using MDS and HCA, projections of MTL structures to the PFC could be groupedaccording to the similarity of sending and recipient brain regions, respectively. AmongMTL areas (Fig. 1), both statistical procedures showed a cluster consisting of areas DG,CA2-CA4, PreS, and ParaS, which have no or a unique pattern of projections to PFC.Other areas were sequentially arranged. Among these, TF and TH formed a second

group characterized by the most extensive projections to the PFC.The remaining areas with sparser projections formed clusters that varied between

MDS and HCA, respectively. MDS produced two subgroups, i.e. 35, E, and Sub, onthe one hand, and 36, CA1, and ProS, on the other hand. HCA con>rmed the closeassociation of areas 36 and ProS, but slightly regrouped the other areas (subgroupswith E + CA1 and 35 + Sub, respectively).MTL projections also grouped their prefrontal destination areas (Fig. 2): Orbito-medial

areas 10, 13, 14, 24, and 25 were contrasted by another group of areas that comprised8B, 9, 11, 12, and 46. This distinction roughly divides PFC into medial and lateralregions.

4. Discussion

Multivariate statistical analyses provided insights into the structural organization ofprojections from the MTL to the PFC. Concerning the MTL, there was a notableabsence of any projection from the hippocampus proper with the only exception ofthe hippocampal sub>eld CA1, which is the most peripheral of its areas. By contrast,

756 A. Bozkurt et al. / Neurocomputing 44–46 (2002) 753–758

Hierarchical cluster analysis

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

E

35

36

TFTG

TH

CA1

CA2CA3

CA4

DG

ProS

Sub

PreSParaS

Multidimensional scaling

-2 -1 0 1 2Dimension-1

-2

-1

0

1

2

Dim

ensi

on-2

TF

TG

TH

Sub

35

E

ProS

CA3

DGCA4

CA2

ParaS

36CA1

PreS

Distances

Fig. 1. Hierarchical cluster analyses (HCA, left) and multidimensional scaling (MDS, right) of medialtemporal areas according to similarity of their projections to the prefrontal cortex (PFC).

Hierarchical cluster analysis

0.0 0.1 0.2 0.3 0.4 0.5 0.6

W10

W9

Multidimensional scaling

-2 -1 0 1 2

Dimension-1

-2

-1

0

1

2

Dim

en

sio

n-2

W8B W9

W25

W13

W14

W24

W12

W46

W8B

W11

W11

W46W12

W10

W14

W25

W24

W13

Distances

Fig. 2. Hierarchical cluster analyses (left) and multidimensional scaling (right) of prefrontal areas accordingto similarity of projections from MTL.

those MTL areas that project most extensively to the PFC (TF, TG, TH) are positionedin its periallocortical and proviocortical rim. The remaining areas of the MTL showintermediate numbers of projections. Thus, we >nd a clear gradient of projections toPFC as we proceed from proviocortical via periallocortical regions to the allocortex.The distinguishing feature of the pre- and parasubiculum from other moderately

projecting MTL areas (35, 36, Sub, ProS, E, CA1) is the demonstration of projectionsto lateral prefrontal area 46, and their absence to orbitomedial area 14. Thus, besides agradient, we >nd evidence for a specialisation of MTL structures in their informationtransfer to the PFC with a prominent role of pre- and parasubiculum.

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Previous studies of intrinsic connectivity in the PFC [5] have shown a clear di-vision into medial and lateral networks. The orbital cortex, however, appeared fairlyhomogeneous when analysed using the parcellation scheme of Walker. Investigationof connections in a more detailed map of orbito-medial prefrontal cortex, however,revealed further diLerences between medial and orbital networks in relation to theirvisceromotor and sensory functions, respectively [8].In the context of information transfer from episodic to working memory it is notice-

able that a specialization exists both among MTL and PFC areas. For episodic memory,a common distinction is between anterior and posterior parts of the MTL [4]. As faras working memory is elaborated in prefrontal cortical networks there is a preferen-tial involvement of dorsolateral prefrontal areas (DLPFC, areas 8A and 46) [7,10]. Asshown by our meta-analysis, the MTL structures that are known to project to DLPFCare PreS and ParaS, as well as areas TF, TG, and TH. Thus, it would be expected thatthese areas, most prominently ParaS, which is known only to project to DLPFC, areresponsible for the transfer of information from episodic to working memory. Whetherthese areas are the neural substrates of episodic memory themselves, or whether theyrelay the information from other MTL structures including the hippocampus proper,remains unclear and will require additional detailed investigation of the connectivitywithin the temporal lobe.

Acknowledgements

Ahmet Bozkurt is indebted to the ‘German National Merit Foundation’ (Studiens-tiftung des deutschen Volkes) for their support. This study was supported by the DFG(LIS 4-554 95 (2) D1usseldorf).

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