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There exist two major types of striatum-targeting neocortical neurons, specifically, intratelencephalic (IT) neurons and pyramidal-tract (PT) neurons. Regarding their striatal projections, it was once suggested that IT axons are extended whereas PT axons are primarily focal. However, subsequent study with an increased number of well-stained extended axons concluded that such an apparent distinction was spurious due to limited sample size. Recent work using genetically labeled neurons reintroduced the differential spatial extent of the striatal projections of IT and PT neurons through population-level analyses, complemented by observations of single axons. However, quantitative IT vs. PT comparison of a large number of axons remained to be conducted. We analyzed the data of axonal end-points of 161 IT neurons and 33 PT neurons in the MouseLight database (http://ml-neuronbrowser.janelia.org/). The number of axonal end-points in the ipsilateral striatum exhibits roughly monotonically decreasing distributions in both neuron types. Excluding neurons with no ipsilateral end-point, the distributions of the logarithm of the number of ipsilateral end-points are considerably overlapped between IT and PT neurons, although the proportion of neurons having more than 50 ipsilateral end-points is somewhat larger in IT neurons than in PT neurons. Looking at more details, among IT subpopulations in the secondary motor area (MOs), layer 5 neurons and bilateral striatum-targeting layer 2/3 neurons, but not contralateral striatum-non-targeting layer 2/3 neurons, have a larger number of ipsilateral end-points than MOs PT neurons. We also found that IT ipsilateral striatal axonal end-points are on average more widely distributed than PT end-points, especially in the medial-lateral direction. These results indicate that IT and PT striatal axons differ in the frequencies and spatial extent of end-points while there are wide varieties within each neuron type.

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.

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.

Quantitative analysis of anatomical synaptic connectivity in microcircuits depends upon accurate 3-dimentional 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 three-dimensional 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 3-dimentional 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.

During cortical network activity, recurrent synaptic excitation among pyramidal neurons is approximately balanced by synaptic inhibition, which is provided by a vast diversity of inhibitory interneurons. The relative contributions of different interneuron subtypes to inhibitory tone during cortical network activity is not well-understood. We previously showed that many of the major interneuron subtypes in mouse barrel cortex are highly active during Up states (Neske et al., 2015); while fast-spiking (FS), parvalbumin (PV)- positive cells were the most active interneuron subtype, many non-fast-spiking (NFS), PV-negative interneurons were as active or more active than neighboring pyramidal cells. This suggests that the NFS cells could play a role in maintaining or modulating Up states. Here, using optogenetic techniques, we further dissected the functional roles during Up states of two major NFS, PV-negative interneuron subtypes: somatostatin (SOM)- positive cells and vasoactive intestinal peptide (VIP)-positive cells. We found that while pyramidal cell excitability during Up states significantly increased when SOM cells were optogenetically silenced, VIP cells did not influence pyramidal cell excitability either upon optogenetic silencing or activation. VIP cells failed to contribute to Up states despite their ability to inhibit SOM cells strongly. We suggest that the contribution of VIP cells to the excitability of pyramidal cells may vary with cortical state. [ABSTRACT FROM AUTHOR]

The most typical and well known inhibitory action in the cortical microcircuit is a strong inhibition on the target neuron by axo-somatic synapses. However, it has become clear that synaptic inhibition in the cortex is much more diverse and complicated. Firstly, at least ten or more inhibitory non-pyramidal cell subtypes engage in diverse inhibitory functions to produce the elaborate activity characteristic of the different cortical states. Each distinct non-pyramidal cell subtype has its own independent inhibitory function. Secondly, the inhibitory synapses innervate different neuronal domains, such as axons, spines, dendrites and soma, and their inhibitory postsynaptic potential (IPSP) size is not uniform. Thus, cortical inhibition is highly complex, with a wide variety of anatomical and physiological modes. Moreover, the functional significance of the various inhibitory synapse innervation styles and their unique structural dynamic behaviors differ from those of excitatory synapses. In this review, we summarize our current understanding of the inhibitory mechanisms of the cortical microcircuit. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses the diversity of innovative neural circuit research in Japan.