Literature DB >> 10703041

Uniformity, specificity and variability of corticocortical connectivity.

C C Hilgetag1, S Grant.   

Abstract

In many studies of the mammalian brain, subjective assessments of connectivity patterns and connection strengths have been used to subdivide the cortex into separate but linked areas and to make deductions about the flow of information through the cortical network. Here we describe the results of applying statistical analyses to quantitative corticocortical connection data, and the conclusions that can be drawn from such quantitative approaches. Injections of the tracer WGA-HRP were made into different visual areas either side of the middle suprasylvian sulcus (MSS) in 11 adult cats. Retrogradely labelled cells produced by these injections were counted in selected coronal sections taken at regularly spaced intervals (1 mm) through the entire visual cortex, and their cumulative sums and relative proportions in each of 16 recognized visual cortical areas were computed. The surface dimensions of these areas were measured in each cat, from contour lines made on enlarged drawings of the same sections. A total of 116,149 labelled neurons were assigned to all visual cortical areas in the 11 cats, with 5212 others excluded because of their uncertain location. The distribution of relative connection strengths, that is, the percentage of labelled cells per cortical area, was evaluated using non-parametric cluster analyses and Monte Carlo simulation, and relationships between connection strength and area size were examined by linear regression. The absolute size of each visual cortical area was uniform across individual cats, whereas the strengths of connections between the same area pairs were extremely variable for injections in different animals. The overall distribution of labelling strengths for corticocortical connections was continuous and monotonic, rather than inherently clustered, with the highest frequencies presented by the absent (zero density) and the very-low-density connections. These two categories could not, on analytical grounds, be separated from each other. Thus it seems that any subjective description of corticocortical connectivity strengths by ordinal classes (such as 'absent', 'weak', 'moderate' or 'strong') imposes a categorization on the data, rather than recognizes a structure inherent in the data themselves. Despite the great variability of connections, similarities in the distribution profiles for the relative strengths of labelled cells in all areas could be used to identify clusters of different injection sites in the MSS. This supported the conclusion that there are four connectionally distinct subdivisions of this cortex, corresponding to areas 21a, PMLS and AMLS (in the medial bank) and to area PLLS (in the lateral bank). Even for tracer deposits in the same cortical subdivision, however, the strength of connections projecting to the site from other cortical areas varied greatly across injection in different individual animals. We further demonstrated that, on average, the strength of connections originating from any given cortical area was positively and linearly correlated with the size of its surface dimensions. When analysed by specific injection site location, however, this relationship was shown to hold for the individual connections to the medial bank MSS areas, but not for connections leading to the lateral bank area. The data suggest that connectivity of the cat's visual cortex possesses a number of uniform global features, which are locally organized in such a way as to give each cortical area unique characteristics.

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Year:  2000        PMID: 10703041      PMCID: PMC1692717          DOI: 10.1098/rstb.2000.0546

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  40 in total

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Journal:  Perception       Date:  1998       Impact factor: 1.490

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Journal:  J Comp Neurol       Date:  1984-10-10       Impact factor: 3.215

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Journal:  J Comp Neurol       Date:  1980-09-01       Impact factor: 3.215

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  18 in total

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Review 3.  Inferring causality in brain images: a perturbation approach.

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

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6.  A surface-based analysis of hemispheric asymmetries and folding of cerebral cortex in term-born human infants.

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7.  Graded classes of cortical connections: quantitative analyses of laminar projections to motion areas of cat extrastriate cortex.

Authors:  Simon Grant; Claus C Hilgetag
Journal:  Eur J Neurosci       Date:  2005-08       Impact factor: 3.386

8.  Network structure implied by initial axon outgrowth in rodent cortex: empirical measurement and models.

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9.  Hierarchical information-based clustering for connectivity-based cortex parcellation.

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10.  Connectivity-based structural and functional parcellation of the human cortex using diffusion imaging and tractography.

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Journal:  Front Neuroanat       Date:  2012-08-29       Impact factor: 3.856

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