Important Factors for the Three-Dimensional Reconstruction of Neuronal Structures from Serial Ultrathin Sections

Quantitative analysis of anatomical synaptic connectivity in microcircuits depends upon accurate three-dimensional (3D) reconstructions of synaptic ultrastructure using electron microscopy of serial ultrathin sections. Here we address two pitfalls in current methodology that lead to inaccurate reconstructions and compromise conclusions drawn from the data. The first pitfall is inaccurate determination of ultrathin section thickness, which negatively affects the 3D shape of reconstructions and therefore impairs quantitative measurement of synaptic structures. Secondly, current methodology significantly underestimates the number of synaptic junctions, with only two-thirds or less of genuine synaptic contacts being identified in dendrites that radiate within the plane of section. Here we propose a new methodology utilizing precise optical measurements of section thickness and successive observations of synaptic elements across serial ultrathin sections that corrects for these limitations to allow accurate 3D reconstruction of synaptic ultrastructure. We use this methodology to reveal that parvalbumin-expressing cortical interneurons have a much higher synaptic density than previously shown. This result suggests that this technique will be useful for re-examining synaptic connectivity of other cell types

A Dual Role Hypothesis of the Cortico-Basal-Ganglia Pathways: Opponency and Temporal Difference Through Dopamine and Adenosine

The hypothesis that the basal-ganglia direct and indirect pathways represent goodness (or benefit) and badness (or cost) of options, respectively, explains a wide range of phenomena. However, this hypothesis, named the Opponent Actor Learning (OpAL), still has limitations. Structurally, the OpAL model does not incorporate differentiation of the two types of cortical inputs to the basal-ganglia pathways received from intratelencephalic (IT) and pyramidal-tract (PT) neurons. Functionally, the OpAL model does not describe the temporal-difference (TD)-type reward-prediction-error (RPE), nor explains how RPE is calculated in the circuitry connecting to the DA neurons. In fact, there is a different hypothesis on the basal-ganglia pathways and DA, named the Cortico-Striatal-Temporal-Difference (CS-TD) model. The CS-TD model differentiates the IT and PT inputs, describes the TD-type RPE, and explains how TD-RPE is calculated. However, a critical difficulty in this model lies in its assumption that DA induces the same direction of plasticity in both direct and indirect pathways, which apparently contradicts the experimentally observed opposite effects of DA on these pathways. Here, we propose a new hypothesis that integrates the OpAL and CS-TD models. Specifically, we propose that the IT-basal-ganglia pathways represent goodness/badness of current options while the PT-indirect pathway represents the overall value of the previously chosen option, and both of these have influence on the DA neurons, through the basal-ganglia output, so that a variant of TD-RPE is calculated. A key assumption is that opposite directions of plasticity are induced upon phasic activation of DA neurons in the IT-indirect pathway and PT-indirect pathway because of different profiles of IT and PT inputs. Specifically, at PT→indirect-pathway-medium-spiny-neuron (iMSN) synapses, sustained glutamatergic inputs generate rich adenosine, which allosterically prevents DA-D2 receptor signaling and instead favors adenosine-A2A receptor signaling. Then, phasic DA-induced phasic adenosine, which reflects TD-RPE, causes long-term synaptic potentiation. In contrast, at IT→iMSN synapses where adenosine is scarce, phasic DA causes long-term synaptic depression via D2 receptor signaling. This new Opponency and Temporal-Difference (OTD) model provides unique predictions, part of which is potentially in line with recently reported activity patterns of neurons in the globus pallidus externus on the indirect pathway

Direction- and distance-dependent interareal connectivity of pyramidal cell subpopulations in the rat frontal cortex

The frontal cortex plays an important role in the initiation and execution of movements via widespread projections to various cortical and subcortical areas. Layer 2/3 (L2/3) pyramidal cells in the frontal cortex send axons mainly to other ipsilateral/contralateral cortical areas. Subpopulations of layer 5 (L5) pyramidal cells that selectively project to the pontine nuclei or to the contralateral cortex [commissural (COM) cells] also target diverse and sometimes overlapping ipsilateral cortical areas. However, little is known about target area-dependent participation in ipsilateral corticocortical (iCC) connections by subclasses of L2/3 and L5 projection neurons. To better understand the functional hierarchy between cortical areas, we compared iCC connectivity between the secondary motor cortex (M2) and adjacent areas, such as the orbitofrontal and primary motor cortices, and distant non-frontal areas, such as the perirhinal and posterior parietal cortices. We particularly assessed the laminar distribution of iCC cells and fibers, and identified the subtypes of pyramidal cells participating in those projections. For connections between M2 and frontal areas, L2/3 and L5 cells in both areas contributed to reciprocal projections, which can be viewed as “bottom-up” or “top-down” on the basis of their differential targeting of cortical lamina. In connections between M2 and non-frontal areas, neurons participating in bottom-up and top-down projections were segregated into the different layers: bottom-up projections arose primarily from L2/3 cells, while top-down projections were dominated by L5 COM cells. These findings suggest that selective participation in iCC connections by pyramidal cell subtypes lead to directional connectivity between M2 and other cortical areas. Based on these findings, we propose a provisional unified framework of interareal hierarchy within the frontal cortex, and discuss the interaction of local circuits with long-range interareal connections

Large Volume Electron Microscopy and Neural Microcircuit Analysis

One recent technical innovation in neuroscience is microcircuit analysis using three-dimensional reconstructions of neural elements with a large volume Electron microscopy (EM) data set. Large-scale data sets are acquired with newly-developed electron microscope systems such as automated tape-collecting ultramicrotomy (ATUM) with scanning EM (SEM), serial block-face EM (SBEM) and focused ion beam-SEM (FIB-SEM). Currently, projects are also underway to develop computer applications for the registration and segmentation of the serially-captured electron micrographs that are suitable for analyzing large volume EM data sets thoroughly and efficiently. The analysis of large volume data sets can bring innovative research results. These recently available techniques promote our understanding of the functional architecture of the brain