Recent advances have established that intralaminar and interlaminar excitatory networks between neocortical pyramidal cells are specialized into subnetworks. Here, we have investigated how the ...commissural system organizes the intracortical excitatory subnetworks to communicate between cortical hemispheres. Whole-cell recordings were obtained from callosal projection neurons commissural (COM) cells, identified by in vivo injection of retrograde fluorescent tracer into one hemisphere, in rat frontal cortical slices. We found that layer V (L5) COM cells were heterogeneous in physiological and morphological properties that correlated with projection patterns to contralateral and ipsilateral cortical areas. The probability of synaptically connected pairs of L5 COM cells was higher in cell pairs of the same firing subtypes than that in different cell subtype pairs. In interlaminar connections, layer II/III (L2/3) COM cells preferentially innervated L5 COM cells. Moreover, pairs of the same L5 COM subtypes were more likely to share inputs from L2/3 COM cells than were different COM subtype cell pairs. In addition, common inputs from L2/3 COM cells were frequently observed in L5 pairs of corticopontine cells and given firing subtypes of COM cells. Our results suggest that callosal communications are achieved via several distinct COM cell subnetworks differentiated according to the ipsilateral corticocortical and subcortical projection patterns.
The basal ganglia play key roles in adaptive behaviors guided by reward and punishment. However, despite accumulating knowledge, few studies have tested how heterogeneous signals in the basal ganglia ...are organized and coordinated for goal-directed behavior. In this study, we investigated neuronal signals of the direct and indirect pathways of the basal ganglia as rats performed a lever push/pull task for a probabilistic reward. In the dorsomedial striatum, we found that optogenetically and electrophysiologically identified direct pathway neurons encoded reward outcomes, whereas indirect pathway neurons encoded no-reward outcome and next-action selection. Outcome coding occurred in association with the chosen action. In support of pathway-specific neuronal coding, light activation induced a bias on repeat selection of the same action in the direct pathway, but on switch selection in the indirect pathway. Our data reveal the mechanisms underlying monitoring and updating of action selection for goal-directed behavior through basal ganglia circuits.
•Firing of striatal direct and indirect pathway neurons changes at action selection•Action, outcomes, and next action are encoded in a pathway-specific manner•Outcome coding occurred in association with the chosen action•Activation of direct and indirect pathways biases toward repeat or switch, respectively
In rats performing reward-oriented action selection, we demonstrate that striatal direct pathway neurons encode chosen action-associated reward and indirect pathway neurons encode no-reward outcomes and next selection. Activation of direct or indirect pathways biases toward repeating or switching actions, respectively.
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.
The thalamus is the hub through which neural signals are transmitted from the basal ganglia and cerebellum to the neocortex. However, thalamocortical axonal activity during motor learning remains ...largely undescribed. We conducted two-photon calcium imaging of thalamocortical axonal activity in the motor cortex of mice learning a self-initiated lever-pull task. Layer 1 (L1) axons came to exhibit activity at lever-pull initiation and termination, while layer 3 (L3) axons did so at lever-pull initiation. L1 population activity had a sequence structure related to both lever-pull duration and reproducibility. Stimulation of the substantia nigra pars reticulata activated more L1 than L3 axons, whereas deep cerebellar nuclei (DCN) stimulation did the opposite. Lesions to either the dorsal striatum or the DCN impaired motor learning and disrupted temporal dynamics in both layers. Thus, layer-specific thalamocortical signals evolve with the progression of learning, which requires both the basal ganglia and cerebellar activities.
•Thalamocortical (TC) axon activity reflects motor representations during learning•TC axon activation induces movement and their inactivation impairs motor learning•TC axons in layers 1 and 3 diverge to show distinct movement-locked activities•Evolving TC axon activity in each layer requires the basal ganglia and cerebellum
Tanaka et al. show that patterns of layer-specific thalamocortical axon activity involving signals from the basal ganglia and cerebellum evolve during learning of a self-initiated motor task. The progression of this activity is impaired by lesions to either region.
Corticostriatal pyramidal cells are heterogeneous in the frontal cortex. Here, we show that subpopulations of corticostriatal neurons in the rat frontal cortex are selectively connected with each ...other based on their subcortical targets. Using paired recordings of retrogradely labeled cells, we investigated the synaptic connectivity between two projection cell types: those projecting to the pons corticopontine (CPn) cell, often with collaterals to the striatum, and those projecting to both sides of the striatum but not to the pons crossed corticostriatal (CCS) cell. The two types were morphologically differentiated in regard to their apical tufts. The dendritic morphologies of CCS cells were correlated with their somatic depth within the cortex. CCS cells had reciprocal synaptic connections with each other and also provided synaptic input to CPn cells. However, connections from CPn to CCS cells were rarely found, even in pairs showing CCS to CPn connectivity. Additionally, CCS cells preferentially innervated the basal dendrites of other CCS cells but made contacts onto both the basal and apical dendrites of CPn cells. The amplitude of synaptic responses was to some extent correlated with the contact site number. Ratios of the EPSC amplitude to the contact number tended to be larger in the CCS to CCS connection. Therefore, our data demonstrate that these two types of corticostriatal cells distinct in their dendritic morphologies show directional and domain-dependent preferences in their synaptic connectivity.
The frontal cortical areas make a coordinated response that generates appropriate behavior commands, using individual local circuits with corticostriatal and corticocortical connections in longer ...time scales than sensory areas. In secondary motor cortex (M2), situated between the prefrontal and primary motor areas, major subtypes of layer 5 corticostriatal cells are crossed-corticostriatal (CCS) cells innervating both sides of striatum, and corticopontine (CPn) cells projecting to the ipsilateral striatum and pontine nuclei. CCS cells innervate CPn cells unidirectionally: the former are therefore hierarchically higher than the latter among L5 corticostriatal cells. CCS cells project directly to both frontal and nonfrontal areas. On the other hand, CPn cells innervate the thalamus and layer 1a of frontal areas, where thalamic fibers relaying basal ganglia outputs are distributed. Thus, CCS cells can make activities of frontal areas in concert with those of nonfrontal area using corticocortical loops, whereas CPn cells are more involved in closed corticostriatal loops than CCS cells. Since reciprocal connections between CPn cells with facilitatory synapses may be related to persistent activity, CPn cells play a key role of longer time constant processes in corticostriatal as well as in corticocortical loops between the frontal areas.
A prominent feature of neocortical pyramidal cells (PCs) is their numerous projections to diverse brain areas. In layer 5 (L5) of the rat frontal cortex, there are 2 major subtypes of PCs that differ ...in their long-range axonal projections, corticopontine (CPn) cells and crossed corticostriatal (CCS) cells. The outputs of these L5 PCs can be regulated by feedback inhibition from neighboring cortical GABAergic cells. Two major subtypes of GABAergic cells are parvalbumin (PV)-positive and somatostatin (SOM)-positive cells. PV cells have a fast-spiking (FS) firing pattern, while SOM cells have a low threshold spike (LTS) and regular spiking. In this study, we found that the 2 PC subtypes in L5 selectively make recurrent connections with LTS cells. The connection patterns correlated with the morphological and physiological diversity of LTS cells. LTS cells with high input resistance (Ri) exhibited more compact dendrites and more rebound spikes than LTS cells with low Ri, which had vertically elongated dendrites. LTS subgroups differently inhibited the PC subtypes, although FS cells made nonselective connections with both projection subtypes. These results demonstrate a novel recurrent network of inhibitory and projection-specific excitatory neurons within the neocortex.
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.
Whether neocortical γ-aminobutyric acid (GABA) cells are composed of a limited number of distinct classes of neuron, or whether they are continuously differentiated with much higher diversity, ...remains a contentious issue for the field. Most GABA cells of rat frontal cortex have at least 1 of 6 chemical markers (parvalbumin, calretinin, alpha-actinin-2, somatostatin, vasoactive intestinal polypeptide, and cholecystokinin), with each chemical class comprising several distinct neuronal subtypes having specific physiological and morphological characteristics. To better clarify GABAergic neuron diversity, we assessed the colocalization of these 6 chemical markers with corticotropin-releasing factor (CRF), neuropeptide Y (NPY), the substance P receptor (SPR), and nitric oxide synthase (NOS); these 4 additional chemical markers suggested to be expressed diversely or specifically among cortical GABA cells. We further correlated morphological and physiological characteristics of identified some chemical subclasses of inhibitory neurons. Our results reveal expression specificity of CRF, NPY, SPR, and NOS in morphologically and physiologically distinct interneuron classes. These observations support the existence of a limited number of functionally distinct subtypes of GABA cells in the neocortex.
Midbrain dopamine neurons supposedly encode reward prediction error, but how error signals are computed remains elusive. Here, we propose a mechanism based on recent findings regarding ...corticostriatal circuits. Specifically, we propose that two distinct subpopulations of corticostriatal neurons differentially represent the animal's current and previous states/actions through unidirectional connectivity from one subpopulation to the other and strong recurrent excitation that exists only within the recipient subpopulation. These corticostriatal subpopulations selectively connect to the direct and indirect pathways of the basal ganglia, such that the temporal difference between the values of current and previous states/actions – the core of the error signal – can be computed. Our hypothesis suggests a unified view of basal ganglia functions and has important clinical implications.
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