VIDEO ABSTRACT.

Neuroscience produces a vast amount of data from an enormous diversity of neurons. A neuronal classification system is essential to organize such data and the knowledge that is derived from them. Classification depends on the unequivocal identification of the features that distinguish one type of neuron from another. The problems inherent in this are particularly acute when studying cortical interneurons. To tackle this, we convened a representative group of researchers to agree on a set of terms to describe the anatomical, physiological and molecular features of GABAergic interneurons of the cerebral cortex. The resulting terminology might provide a stepping stone towards a future classification of these complex and heterogeneous cells. Consistent adoption will be important for the success of such an initiative, and we also encourage the active involvement of the broader scientific community in the dynamic evolution of this project.

The appearance of the neocortex, its expansion, and its differentiation in mammals, represents one of the principal episodes in the evolution of the vertebrate brain. One of the fundamental questions in neuroscience is what is special about the neocortex of humans and how does it differ from that of other species? It is clear that distinct cortical areas show important differences within both the same and different species, and this has led to some researchers emphasizing the similarities whereas others focus on the differences. In general, despite of the large number of different elements that contribute to neocortical circuits, it is thought that neocortical neurons are organized into multiple, small repeating microcircuits, based around pyramidal cells and their input-output connections. These inputs originate from extrinsic afferent systems, excitatory glutamatergic spiny cells (which include other pyramidal cells and spiny stellate cells), and inhibitory GABAergic interneurons. The problem is that the neuronal elements that make up the basic microcircuit are differentiated into subtypes, some of which are lacking or highly modified in different cortical areas or species. Furthermore, the number of neurons contained in a discrete vertical cylinder of cortical tissue varies across species. Additionally, it has been shown that the neuropil in different cortical areas of the human, rat and mouse has a characteristic layer specific synaptology. These variations most likely reflect functional differences in the specific cortical circuits. The laminar specific similarities between cortical areas and between species, with respect to the percentage, length and density of excitatory and inhibitory synapses, and to the number of synapses per neuron, might be considered as the basic cortical building bricks. In turn, the differences probably indicate the evolutionary adaptation of excitatory and inhibitory circuits to particular functions.

The advent of transmission electron microscopy (TEM) in the 1950s represented a fundamental step in the study of neuronal circuits. The application of this technique soon led to the realization that the number of synapses changes during the course of normal life, as well as under certain pathological or experimental circumstances. Since then, one of the main goals in neurosciences has been to define simple and accurate methods to estimate the magnitude of these changes. Contrary to analysing single sections, TEM reconstructions are extremely time-consuming and difficult. Therefore, most quantitative studies use stereological methods to define the three-dimensional characteristics of synaptic junctions that are studied in two dimensions. Here, to count the exact number of synapses per unit of volume we have applied a new three-dimensional reconstruction method that involves the combination of focused ion beam milling and scanning electron microscopy (FIB/SEM). We show that the images obtained with FIB/SEM are similar to those obtained with TEM, but with the advantage that FIB/SEM permits serial reconstructions of large volumes of tissue to be generated rapidly and automatically. Furthermore, we compared the estimates of the number of synapses obtained with stereological methods with the values obtained by FIB/SEM reconstructions. We concluded that FIB/SEM not only provides the actual number of synapses per volume but it is also much easier and faster to use than other currently available TEM methods. More importantly, it also avoids most of the errors introduced by stereological methods and overcomes the difficulties associated with these techniques.