PubMed Health⌕ Search

Biomedical subjects

Tom Binzegger

Publications and source records attributed to Tom Binzegger.

3 recordsLinked to original sources

A quantitative map of the circuit of cat primary visual cortex.

We developed a quantitative description of the circuits formed in cat area 17 by estimating the "weight" of the projections between different neuronal types. To achieve this, we made three-dimensional reconstructions of 39 single neurons and thalamic afferents labeled with horseradish peroxidase during intracellular recordings in vivo. These neurons served as representatives of the different types and provided the morphometrical data about the laminar distribution of the dendritic trees and synaptic boutons and the number of synapses formed by a given type of neuron. Extensive searches of the literature provided the estimates of numbers of the different neuronal types and their distribution across the cortical layers. Applying the simplification that synapses between different cell types are made in proportion to the boutons and dendrites that those cell types contribute to the neuropil in a given layer, we were able to estimate the probable source and number of synapses made between neurons in the six layers. The predicted synaptic maps were quantitatively close to the estimates derived from the experimental electron microscopic studies for the case of the main sources of excitatory and inhibitory input to the spiny stellate cells, which form a major target of layer 4 afferents. The map of the whole cortical circuit shows that there are very few "strong" but many "weak" excitatory projections, each of which may involve only a few percentage of the total complement of excitatory synapses of a single neuron.

Afferent Pathways↗

Axons in cat visual cortex are topologically self-similar.

The axonal arbors of the different types of neocortical and thalamic neurons appear highly dissimilar when viewed in conventional 2D reconstructions. Nevertheless, we have found that their one-dimensional metrics and topologies are surprisingly similar. To discover this, we analysed the axonal branching pattern of 39 neurons (23 spiny, 13 smooth and three thalamic axons) that were filled intracellularly with horseradish peroxidase (HRP) during in vivo experiments in cat area 17. The axons were completely reconstructed and translated into dendrograms. Topological, fractal and Horton-Strahler analyses indicated that axons of smooth and spiny neurons had similar complexity, length ratios (a measure of the relative increase in the length of collateral segments as the axon branches) and bifurcation ratios (a measure of the relative increase in the number of collateral segments as the axon branches). We show that a simple random branching model (Galton-Watson process) predicts with reasonable accuracy the bifurcation ratio, length ratio and collateral length distribution of the axonal arbors.

Animals↗

Chance or design? Some specific considerations concerning synaptic boutons in cat visual cortex.

To understand the rules by which axons lay down their synaptic boutons we analyzed the linear bouton distributions in 39 neurons (23 spiny, 13 smooth) and 3 thalamic axons, which were filled intracellularly with horseradish peroxidase (HRP) during in vivo experiments in cat area 17. The variation of the total number of boutons and the total axonal length was large (789-7,912 boutons, 12-126 mm). The overall linear bouton density for smooth cells was higher than that of spiny cells and thalamic afferents (mean +/- sd, 110 +/- 21 and 78 +/- 27 boutons per mm of axonal length). The distribution of boutons varied according to their location on the tree. Distal axon collaterals (first and second order segments in Horton-Strahler ordering) of smooth neurons had a 3.5 times higher, spiny cells and thalamic afferents a 2 times higher bouton density compared to the higher order (more proximal) segments. The distribution of interbouton intervals was positively skewed and similar for cells of the same type. In most cases a gamma-distribution fitted well, but the distributions had a tendency to have a heavier tail. To a first approximation these bouton distributions are consistent with both diffuse and specific models of interneuronal connections. Quite simple rules can explain these distributions and the connections between the different classes of neurons.

Animals↗