Elsevier

NeuroImage

Volume 134, 1 July 2016, Pages 685-702
NeuroImage

The primate connectome in context: Principles of connections of the cortical visual system

https://doi.org/10.1016/j.neuroimage.2016.04.017Get rights and content

Highlights

  • Comparison of models for cortical connections

  • Analysis of extensive connectivity data of the macaque visual system

  • Cortical type and density relate to connection existence and laminar patterns.

  • Distance and cortical thickness relate less consistently to connections.

  • The findings strongly support a structural model of cortical connectivity.

Abstract

Which principles determine the organization of the intricate network formed by nerve fibers that link the primate cerebral cortex? We addressed this issue for the connections of primate visual cortices by systematically analyzing how the existence or absence of connections, their density as well as laminar patterns of projection origins and terminations are correlated with distance, similarity in cortical type as well as neuronal density or the thickness of cortical areas. Analyses were based on four extensive compilations of qualitative as well as quantitative data for connections of the primate visual cortical system in macaque monkeys (Felleman and Van Essen 1991; Barbas 1986; Barbas and Rempel-Clower 1997; Barone et al. 2000; Markov et al. 2014). Distance and thickness similarity were not consistently correlated with connection features, but similarity of cortical type, determined by qualitative features of laminar differentiation, or measured quantitatively as the areas' overall neuronal density, was a reliable predictor for the existence of connections between areas. Cortical type similarity was also consistently and closely correlated with characteristic laminar connection profiles: structurally dissimilar areas had origin and termination patterns that were biased to the upper or deep cortical layers, while similar areas showed more bilaminar origins and terminations. These results suggest that patterns of corticocortical connections of primate visual cortices are closely linked to the stratified architecture of the cerebral cortex. In particular, the regularity of laminar projection origins and terminations arises from the structural differences between cortical areas. The observed integration of projections with the intrinsic cortical architecture provides a structural basis for advanced theories of cortical organization and function.

Introduction

Macroscopic connections among cortical areas form intricate networks for neural communication (Van Essen et al., 2013). These networks are neither completely nor randomly wired, and their organization has been the subject of extensive investigations (reviewed in Sporns et al., 2004, Bullmore and Sporns, 2009, Sporns, 2010).

An essential question is what determines the existence or absence of connections, since not all possible connections exist. A starting point is the observation that neighboring areas or neighbors-one-over are frequently connected (Barbas and Pandya, 1989), accounting for about half of the connections in primate visual cortex (Young, 1992). While proximity may contribute to the formation of connections (Ercsey-Ravasz et al., 2013), it cannot be the only factor, because some connections extend across considerable distances (e.g., Barbas and Mesulam, 1981, Kaiser and Hilgetag, 2006, Markov et al., 2013). Another model suggests that connections are formed between areas of similar thickness (He et al., 2007, Bassett et al., 2008, He et al., 2008, Liu et al., 2008, Bassett and Bullmore, 2009, He et al., 2009). Alternatively, a structural model posits that similarities in overall laminar organization (Barbas, 1986, Barbas and Rempel-Clower, 1997, Medalla and Barbas, 2006) help explain the presence and patterns of connections (Barbas and Rempel-Clower, 1997, Barbas et al., 2005a).

An important feature of connections is their strength – the number of neurons in a pathway – that may help estimate functional impact (Vanduffel et al., 1997). Strength varies considerably across pathways (MacNeil et al., 1997, Scannell et al., 2000, Hilgetag and Grant, 2000) and possesses a logarithmic (Scannell et al., 2000) or lognormal (Markov et al., 2011) global distribution, where a few pathways are very dense and most others are either sparse or absent. The factors that underlie this distribution are still incompletely understood (Kaiser et al., 2009).

A further question concerns the laminar patterns of connections, reviewed in Felleman and Van Essen (1991), which emanate and terminate in functionally distinct laminar micro-environments (Barbas et al., 2005b). Laminar patterns of connections are diverse but strikingly repetitive. For example, in the cortical visual system, connections can be arranged into sequences or hierarchies. In such sequences, projections that mostly originate from upper cortical layers and terminate in the middle-to-deep layers (‘feedforward’) point in one direction, while the reciprocal (‘feedback’) projections that mostly originate from deep layers and terminate in upper cortical layers point in the opposite direction of the sequence. Most visual projections fit such a scheme, with only 6 violations out of 318 patterns (Hilgetag et al., 1996). By contrast, if such arrangements are attempted for randomly assigned projection patterns, a large number of disagreements (> 100) remain (Hilgetag et al., 2000b). Thus, laminar projection patterns demonstrate a remarkably regular motif in cortical organization. It has been suggested that the regularity depends on cortical structure (Barbas, 1986, Barbas and Rempel-Clower, 1997), physical distance (Bullier and Nowak, 1995), or hierarchical rank (Barone et al., 2000).

Here we systematically investigated factors that contribute to the organization of cortical connections, by quantitative hypothesis testing based on distinct proposed models. To test these models, we studied extensive data from various sources to increase the reliability and generality of the findings: a collation of qualitatively described primate visual connections (Felleman and Van Essen, 1991); quantitative datasets from the laboratory of Kennedy (Barone et al., 2000, Markov et al., 2014); and newly compiled quantitative data on connections and cortical structure from our laboratory (Barbas, 1986, Barbas and Rempel-Clower, 1997). The primate visual cortical system is ideal for this study, because extensive available data make it possible to test to what extent alternative models, based on differences in distance, cortical thickness, or cortical structure between connected areas, best account for the existence, absence, density and laminar distribution of connections. Preliminary results from this study were presented in abstract form (Hilgetag et al., 2008).

Section snippets

Connection datasets

We analyzed the following four datasets which provide qualitative and quantitative information on the existence or absence, strength, as well as laminar patterns of projection neurons in the primate visual cortex in macaque monkeys. These data include the landmark compilation of Felleman and Van Essen of visual connections (Felleman and Van Essen, 1991), two sets of quantitative laminar projection patterns for visual projections (Barone et al., 2000, Markov et al., 2014), as well as a partly

Overview

We first investigated the relationship between different structural features of the cortex and the existence or absence of connections, as well as relative projection strength. We then related the structural cortical features to laminar origin and, where available, laminar termination patterns of corticocortical pathways. Both aspects of the analyses were considered in turn for the global visual dataset, as well as for the quantitative database of visual-prefrontal projections (Barbas, 1986,

Overview

Using four extensive datasets of visual connections, we demonstrate that cortical structure and connections are closely linked. Structure is captured by a few salient parameters, including neuronal density and laminar structure distilled into a few cortical types seen throughout the cortical mantle (Barbas, 2015). Differences in these parameters between areas successfully predict essential connection features, including their presence or absence, density and laminar distribution of connection

Conflict of interest

The authors declare no competing financial interests.

Acknowledgments

CCH and SB were supported by DFG Collaborative Research Center Grant SFB 936/A1. CCH was also supported by DFG Collaborative Research Center Grant TRR 169/A2. MM was supported by NIMH (National Institute of Mental Health) grant K99 MH101234. HB was supported by grants from NIH (NINDS R01NS024760; and NIMH, R01MH057414) and CELEST, an NSF Science of Learning Center (NSF OMA-0835976).

References (106)

  • C.C. Hilgetag et al.

    Cytoarchitectural differences are a key determinant of laminar projection origins in the visual cortex

    NeuroImage

    (2010)
  • C.C. Hilgetag et al.

    Classes and gradients of prefrontal cortical organization in the primate

    Neurocomputing

    (2002)
  • J. Hyvarinen

    Regional distribution of functions in parietal association area 7 of the monkey

    Brain Res.

    (1981)
  • M. Kaiser et al.

    Development of multi-cluster cortical networks by time windows for spatial growth

    Neurocomputing

    (2007)
  • J.P. Lerch et al.

    Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI

    NeuroImage

    (2006)
  • M. Medalla et al.

    Synapses with inhibitory neurons differentiate anterior cingulate from dorsolateral prefrontal pathways associated with cognitive control

    Neuron

    (2009)
  • G. Michalareas et al.

    Alpha-beta and gamma rhythms subserve feedback and feedforward influences among human visual cortical areas

    Neuron

    (2016)
  • J.W. Neal et al.

    The cortico-cortical connections within the parieto-temporal lobe of area PG, 7a, in the monkey

    Brain Res.

    (1988)
  • A.T. Reid et al.

    Optimization of cortical hierarchies with continuous scales and ranges

    NeuroImage

    (2009)
  • C. Schmitz et al.

    Design-based stereology in neuroscience

    Neuroscience

    (2005)
  • B. Seltzer et al.

    Converging visual and somatic sensory cortical input to the intraparietal sulcus of the rhesus monkey

    Brain Res.

    (1980)
  • O. Sporns et al.

    Organization, development and function of complex brain networks

    Trends Cogn. Sci.

    (2004)
  • D.C. Van Essen et al.

    The WU-Minn human connectome project: an overview

    NeuroImage

    (2013)
  • G.W. Van Hoesen et al.

    Some connections of the entorhinal (area 28) and perirhinal (area 35) cortices of the rhesus monkey. III. Efferent connections

    Brain Res.

    (1975)
  • M.C. Anderson et al.

    Prefrontal-hippocampal pathways underlying inhibitory control over memory

    Neurobiol. Learn. Mem.

    (2015)
  • H. Barbas

    Pattern in the laminar origin of corticocortical connections

    J. Comp. Neurol.

    (1986)
  • H. Barbas

    Anatomic organization of basoventral and mediodorsal visual recipient prefrontal regions in the rhesus monkey

    J. Comp. Neurol.

    (1988)
  • H. Barbas

    General cortical and special prefrontal connections: principles from structure to function

    Annu. Rev. Neurosci.

    (2015)
  • H. Barbas et al.

    Organization of afferent input to subdivisions of area 8 in the Rhesus monkey

    J. Comp. Neurol.

    (1981)
  • H. Barbas et al.

    Architecture and intrinsic connections of the prefrontal cortex in the Rhesus monkey

    J. Comp. Neurol.

    (1989)
  • H. Barbas et al.

    Cortical structure predicts the pattern of corticocortical connections

    Cereb. Cortex

    (1997)
  • H. Barbas et al.

    Medial prefrontal cortices are unified by common connections with superior temporal cortices and distinguished by input from memory-related areas in the rhesus monkey

    J. Comp. Neurol.

    (1999)
  • H. Barbas et al.

    Parallel organization of contralateral and ipsilateral prefrontal cortical projections in the rhesus monkey

    BMC Neurosci.

    (2005)
  • H. Barbas et al.

    Relationship of prefrontal connections to inhibitory systems in superior temporal areas in the rhesus monkey

    Cereb. Cortex

    (2005)
  • P. Barone et al.

    Laminar distribution of neurons in extrastriate areas projecting to visual areas V1 and V4 correlates with the hierarchical rank and indicates the operation of a distance rule

    J. Neurosci.

    (2000)
  • D.S. Bassett et al.

    Human brain networks in health and disease

    Curr. Opin. Neurol.

    (2009)
  • D.S. Bassett et al.

    Hierarchical organization of human cortical networks in health and schizophrenia

    J. Neurosci.

    (2008)
  • S.F. Beul et al.

    Towards a “canonical” agranular cortical microcircuit

    Front. Neuroanat.

    (2015)
  • S.F. Beul et al.

    A predictive model of the cat cortical connectome based on cytoarchitecture and distance

    Brain Struct. Funct.

    (2015)
  • D. Boussaoud et al.

    Visual topography of area TEO in the macaque

    J. Comp. Neurol.

    (1991)
  • E. Bullmore et al.

    Complex brain networks: graph theoretical analysis of structural and functional systems

    Nat. Rev. Neurosci.

    (2009)
  • J.G. Bunce et al.

    Parallel prefrontal pathways reach distinct excitatory and inhibitory systems in memory-related rhinal cortices

    J. Comp. Neurol.

    (2013)
  • Y. Chen et al.

    Trade-off between multiple constraints enables simultaneous formation of modules and hubs in neural systems

    PLoS Comput. Biol.

    (2013)
  • C.E. Collins et al.

    Neuron densities vary across and within cortical areas in primates

    Proc. Natl. Acad. Sci. U. S. A.

    (2010)
  • S.-L. Ding et al.

    Borders, extent, and topography of human perirhinal cortex as revealed using multiple modern neuroanatomical and pathological markers

    Hum. Brain Mapp.

    (2010)
  • S.M. Dombrowski et al.

    Quantitative architecture distinguishes prefrontal cortical systems in the rhesus monkey

    Cereb. Cortex

    (2001)
  • M.J. Donoghue et al.

    Molecular gradients and compartments in the embryonic primate cerebral cortex

    Cereb. Cortex

    (1999)
  • D.J. Felleman et al.

    Distributed hierarchical processing in the primate cerebral cortex

    Cereb. Cortex

    (1991)
  • R.W. Floyd

    Algorithm 97: shortest path

    Commun. ACM

    (1962)
  • K. Friston

    A theory of cortical responses

    Philos. Trans. R. Soc. B

    (2005)
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