Synaptic density on non-spiny dendrites in the cerebral cortex of the house mouse. A phosphotungstic acid study

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A modification of the phosphotungstic acid method was used to investigate long segments of non-spiny dendrites in the electron microscope. The number of synapses on these dendrites was counted. The density was 1.9 synapses per micron of dendritic length. Taking into account the synapses not contained in the sections, (which are thinner than the dendrites) one gets a real density of 3.3 synapses per micron. This is more than the average density of synapses along spiny dendrites. It demonstrates that spines are not necessary for large numbers of synaptic contacts.

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... So why do excitatory axons choose to contact neurons on spines, rather than on dendritic shafts? Why do neurons make tens of thousands of spines to receive excitatory inputs, when they have plenty of available membrane to accommodate them on their dendritic shafts in the first place (Braitenberg and Schü z, 1998; Schü z and Dortenmann, 1987)? This is what I define as the ''spine problem'': what exactly do spines contribute to the neuron? ...
Dendritic spines receive most excitatory connections in pyramidal cells and many other principal neurons. But why do neurons use spines, when they could accommodate excitatory contacts directly on their dendritic shafts? One suggestion is that spines serve to connect with passing axons, thus increasing the connectivity of the dendrites. Another hypothesis is that spines are biochemical compartments that enable input-specific synaptic plasticity. A third possibility is that spines have an electrical role, filtering synaptic potentials and electrically isolating inputs from each other. In this review, I argue that, when viewed from the perspective of the circuit function, these three functions dovetail with one another to achieve a single overarching goal: to implement a distributed circuit with widespread connectivity. Spines would endow these circuits with nonsaturating, linear integration and input-specific learning rules, which would enable them to function as neural networks, with emergent encoding and processing of information.
The cerebral cortex is supposed to be heavily involved in learning processes and has, therefore, been the object of many deprivation studies. However, even the study of the normal, not artifically perturbed brain during and after development may contribute to the question of anatomic traces of plasticity. The advantage of this alternative approach is that it is not necessary to expose animals to an artificial situation in which it may be difficult to distinguish between direct effects of learning and more indirect effects connected with the general condition of the animal. Here I summarize the results we have collected in recent years.
We shall now describe such cortical fields as easily leap to the eye, even to a superficial observer. We notice, however, that there are two different situations that may make a delimited region of cortex clearly stand out between its neighbours. An area may be defined by a boundary where the appearance of the layering abruptly changes. The classical example in human anatomy is the striate area (area 17, Brodmann). There are other areas, however, which equally leap to the eye, because of prominent characteristics, even if they may blend gradually into the appearance of surrounding areas. A well-known example for this is the giganto-pyramidal area, area 4, of the human cortex, which is well characterized by the enormous cell bodies of the Betz cells, but much less by its boundaries. We find examples for both in the mouse cortex. In the numbering of areas we shall follow Caviness (1975).
As soon as the Golgi technique made it possible to stain individual neurons in the tissue, dissecting them out, as it were, from the tangle of their intermingled processes, it became apparent that they come in a spectacular variety of shapes and sizes. The collection of illustrations in Cajal’s Histologie (1911) together with further drawings only recently made available in a translation of Cajal’s original papers (DeFelipe and Jones 1988) furnishes a panorama of this variety to which more recent publications (see papers in Peters and Jones 1984a onward) have added comparatively little. What improved staining techniques have shown recently however, particularly by means of dyes injected into the cell (Gilbert and Wiesel 1979 and many others; see Parnavelas 1984), is that the Golgi stain may occasionally leave part of the axonal tree unstained. We have already noted this when comparing our estimates of the axonal density obtained from Golgi pictures with those inferred by other means (Chap. 7). The general picture, however, has not changed much since Cajal and the old dilemma between an urge to differentiate neurons in an ever finer taxonomy, and the opposite urge to reduce the variety to a few simple categories is still with us today.
With the classical Golgi techniques, numerous types of neurons can be distinguished in the cerebral cortex, each with a specific dendritic geometry and pattern of axonal ramifications. In the present review we describe two techniques which allow quantification of synapses on identified neurons: (1) Golgi-rapid impregnation-gold toning-electron microscopy, and (2) Golgi-Kopsch impregnation-gold toning-electron microscopy in combination with staining of the tissue with ethanolic phosphotungstic acid (E-PTA). Both techniques were applied on neurons in the visual cortex of young and adult rabbits. By means of rotating and tilting specimens in the electron microscope, the nondistinctive ultrastructure of obliquely sectioned synapses can be circumvented, leading to precise estimates of asymmetrical vs. symmetrical synapses without complete reconstruction of the neuron. © 1992 Wiley-Liss, Inc.
Quantitative anatomical investigations provide the basis for functional models. In this study the density of neurons and synapses was measured in three different areas (8, 6, and 17) of the neocortex of the mouse. Both kinds of measurements were made on the same material, embedded in Epon/Araldit. In order to determine the synaptic density per mm3, the proportion of synaptic neuropil was also measured; it was found to be 84%. The cortical volume occupied by cell bodies of neurons and glia cells amounted to 12%, that by blood vessels to 4%. The total average was 9.2 × 104 neurons/mm3 and 7.2 × 108 synapses/mm3. About 11% of the synapses were of type II. The density of neurons increased with decreasing cortical thickness; thus the number of neurons under a given surface area was about constant. The synaptic density, on the other hand, was almost constant in the three areas, the number of synapses under a given cortical surface area tended, therefore, to increase with cortical thickness. The average number of synapses per neuron was 8,200, with a tendency to increase with increasing cortical thickness. Shrinkage of the tissue was also measured for various staining techniques. No shrinkage occurred during perfusion with 3.7% formaldehyde or with a solution of buffered paraformaldehyde and glutaraldehyde and during fixation in situ. Electron microscopical material showed almost no shrinkage, whereas Nissl-preparations on paraffin-embedded material had only 43% of their original volume. After Nissl stain on frozen sections the volume had shrunken to 68% and after Golgi impregnation and embedding in celloidin to 70%. The total volume of the neocortex was 112 mm3 (both hemispheres together). The total number of neurons was thus 1.0 × 107 and the total number of synapses 8.1 × 1010.
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