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The fractions of short- and long-range connections in the visual cortex

Proc Natl Acad Sci U S A. 2009 Mar 3;106(9):3555-60. doi: 10.1073/pnas.0810390106. Epub 2009 Feb 12.

Abstract

When analyzing synaptic connectivity in a brain tissue slice, it is difficult to discern between synapses made by local neurons and those arising from long-range axonal projections. We analyzed a data set of excitatory neurons and inhibitory basket cells reconstructed from cat primary visual cortex in an attempt to provide a quantitative answer to the question: What fraction of cortical synapses is local, and what fraction is mediated by long-range projections? We found an unexpectedly high proportion of nonlocal synapses. For example, 92% of excitatory synapses near the axis of a 200-microm-diameter iso-orientation column come from neurons located outside the column, and this fraction remains high--76%--even for an 800-micromocular dominance column. The long-range nature of connectivity has dramatic implications for experiments in cortical tissue slices. Our estimate indicates that in a 300-microm-thick section cut perpendicularly to the cortical surface, the number of viable excitatory synapses is reduced to about 10%, and the number of synapses made by inhibitory basket cell axons is reduced to 38%. This uneven reduction in the numbers of excitatory and inhibitory synapses changes the excitation-inhibition balance by a factor of 3.8 toward inhibition, and may result in cortical tissue that is less excitable than in vivo. We found that electrophysiological studies conducted in tissue sections may significantly underestimate the extent of cortical connectivity; for example, for some projections, the reported probabilities of finding connected nearby neuron pairs in slices could understate the in vivo probabilities by a factor of 3.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cats
  • Visual Cortex / anatomy & histology*
  • Visual Cortex / physiology*