The excitatory neuronal network of the C2 barrel column in mouse primary somatosensory cortex

In vivo voltage-sensitive dye imaging of mouse cortical activity with mesoscopic optical tomography

Significance: Cellular layering is a hallmark of the mammalian neocortex with layer and cell type-specific connections within the cortical mantle and subcortical connections. A key challenge in studying circuit function within the neocortex is to understand the spatial and temporal patterns of information flow between different columns and layers. Aim: We aimed to investigate the three-dimensional (3D) layer- and area-specific interactions in mouse cortex in vivo. Approach: We applied a new promising neuroimaging method-fluorescence laminar optical tomography in combination with voltage-sensitive dye imaging (VSDi). VSDi is a powerful technique for interrogating membrane potential dynamics in assemblies of cortical neurons, but it is traditionally used for two-dimensional (2D) imaging. Our mesoscopic technique allows visualization of neuronal activity in a 3D manner with high temporal resolution. Results: We first demonstrated the depth-resolved capability of 3D mesoscopic imaging technology in Thy1-ChR2-YFP transgenic mice. Next, we recorded the long-range functional projections between sensory cortex (S1) and motor cortex (M1) in mice, in vivo, following single whisker deflection. Conclusions: The results show that mesoscopic imaging technique has the potential to investigate the layer-specific neural connectivity in the mouse cortex in vivo. Combination of mesoscopic imaging technique with optogenetic control strategy is a promising platform for determining depth-resolved interactions between cortical circuit elements.

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks

A basic—yet nontrivial—function which neocortical circuitry must satisfy is the ability to maintain stable spiking activity over time. Stable neocortical activity is asynchronous, critical, and low rate, and these features of spiking dynamics contribute to efficient computation and optimal information propagation. However, it remains unclear how neocortex maintains this asynchronous spiking regime. Here we algorithmically construct spiking neural network models, each composed of 5000 neurons. Network construction synthesized topological statistics from neocortex with a set of objective functions identifying naturalistic low-rate, asynchronous, and critical activity. We find that simulations run on the same topology exhibit sustained asynchronous activity under certain sets of initial membrane voltages but truncated activity under others. Synchrony, rate, and criticality do not provide a full explanation of this dichotomy. Consequently, in order to achieve mechanistic understanding of sustained asynchronous activity, we summarized activity as functional graphs where edges between units are defined by pairwise spike dependencies. We then analyzed the intersection between functional edges and synaptic connectivity- i.e. recruitment networks. Higher-order patterns, such as triplet or triangle motifs, have been tied to cooperativity and integration. We find, over time in each sustained simulation, low-variance periodic transitions between isomorphic triangle motifs in the recruitment networks. We quantify the phenomenon as a Markov process and discover that if the network fails to engage this stereotyped regime of motif dominance “cycling”, spiking activity truncates early. Cycling of motif dominance generalized across manipulations of synaptic weights and topologies, demonstrating the robustness of this regime for maintenance of network activity. Our results point to the crucial role of excitatory higher-order patterns in sustaining asynchronous activity in sparse recurrent networks. They also provide a possible explanation why such connectivity and activity patterns have been prominently reported in neocortex.

Neocortical spiking activity tends to be low-rate and non-rhythmic, and to operate near the critical point of a phase transition. It remains unclear how this kind of spiking activity can be maintained within a neuronal network. Neurons are leaky and individual synaptic connections are sparse and weak, making the maintenance of an asynchronous regime a nontrivial problem. Higher order patterns involving more than two units abound in neocortex, and several lines of evidence suggest that they may be instrumental for brain function. For example, stable activity in vivo displays elevated clustering dominated by specific three-node (triplet) motifs. In this study we demonstrate a link between the maintenance of asynchronous activity and triplet motifs. We algorithmically build spiking neural network models to mimic the topology of neocortex and the spiking statistics that characterize wakefulness. We show that higher order coordination of synapses is always present during sustained asynchronous activity. Coordination takes the form of transitions in time between specific triangle motifs. These motifs summarize the way spikes traverse the underlying synaptic topology. The results of our model are consistent with numerous experimental observations, and their generalizability to other weakly and sparsely connected networks is predicted.

Behavioral and Neural Bases of Tactile Shape Discrimination Learning in Head-Fixed Mice

Tactile shape recognition requires the perception of object surface angles. We investigate how neural representations of object angles are constructed from sensory input and how they reorganize across learning. Head-fixed mice learned to discriminate object angles by active exploration with one whisker. Calcium imaging of layers 2-4 of the barrel cortex revealed maps of object-angle tuning before and after learning. Three-dimensional whisker tracking demonstrated that the sensory input components that best discriminate angles (vertical bending and slide distance) also have the greatest influence on object-angle tuning. Despite the high turnover in active ensemble membership across learning, the population distribution of object-angle tuning preferences remained stable. Angle tuning sharpened, but only in neurons that preferred trained angles. This was correlated with a selective increase in the influence of the most task-relevant sensory component on object-angle tuning. These results show how discrimination training enhances stimulus selectivity in the primary somatosensory cortex while maintaining perceptual stability.

The Synaptic Organization of Layer 6 Circuits Reveals Inhibition as a Major Output of a Neocortical Sublamina

The canonical cortical microcircuit has principally been defined by interlaminar excitatory connections among the six layers of the neocortex. However, excitatory neurons in layer 6 (L6), a layer whose functional organization is poorly understood, form relatively rare synaptic connections with other cortical excitatory neurons. Here, we show that the vast majority of parvalbumin inhibitory neurons in a sublamina within L6 send axons through the cortical layers toward the pia. These interlaminar inhibitory neurons receive local synaptic inputs from both major types of L6 excitatory neurons and receive stronger input from thalamocortical afferents than do neighboring pyramidal neurons. The distribution of these interlaminar interneurons and their synaptic connectivity further support a functional subdivision within the standard six layers of the cortex. Positioned to integrate local and long-distance inputs in this sublayer, these interneurons generate an inhibitory interlaminar output. These findings call for a revision to the canonical cortical microcircuit.

Neuronal Circuits in Barrel Cortex for Whisker Sensory Perception

The array of whiskers on the snout provides rodents with tactile sensory information relating to the size, shape and texture of objects in their immediate environment. Rodents can use their whiskers to detect stimuli, distinguish textures, locate objects and navigate. Important aspects of whisker sensation are thought to result from neuronal computations in the whisker somatosensory cortex (wS1). Each whisker is individually represented in the somatotopic map of wS1 by an anatomical unit named a 'barrel' (hence also called barrel cortex). This allows precise investigation of sensory processing in the context of a well-defined map. Here, we first review the signaling pathways from the whiskers to wS1, and then discuss current understanding of the various types of excitatory and inhibitory neurons present within wS1. Different classes of cells can be defined according to anatomical, electrophysiological and molecular features. The synaptic connectivity of neurons within local wS1 microcircuits, as well as their long-range interactions and the impact of neuromodulators, are beginning to be understood. Recent technological progress has allowed cell-type-specific connectivity to be related to cell-type-specific activity during whisker-related behaviors. An important goal for future research is to obtain a causal and mechanistic understanding of how selected aspects of tactile sensory information are processed by specific types of neurons in the synaptically connected neuronal networks of wS1 and signaled to downstream brain areas, thus contributing to sensory-guided decision-making.

Estimation of the number of synapses in the hippocampus and brain-wide by volume electron microscopy and genetic labeling

Determining the number of synapses that are present in different brain regions is crucial to understand brain connectivity as a whole. Membrane-associated guanylate kinases (MAGUKs) are a family of scaffolding proteins that are expressed in excitatory glutamatergic synapses. We used genetic labeling of two of these proteins (PSD95 and SAP102), and Spinning Disc confocal Microscopy (SDM), to estimate the number of fluorescent puncta in the CA1 area of the hippocampus. We also used FIB-SEM, a three-dimensional electron microscopy technique, to calculate the actual numbers of synapses in the same area. We then estimated the ratio between the three-dimensional densities obtained with FIB-SEM (synapses/µm³) and the bi-dimensional densities obtained with SDM (puncta/100 µm²). Given that it is impractical to use FIB-SEM brain-wide, we used previously available SDM data from other brain regions and we applied this ratio as a conversion factor to estimate the minimum density of synapses in those regions. We found the highest densities of synapses in the isocortex, olfactory areas, hippocampal formation and cortical subplate. Low densities were found in the pallidum, hypothalamus, brainstem and cerebellum. Finally, the striatum and thalamus showed a wide range of synapse densities.

Firing rate homeostasis counteracts changes in stability of recurrent neural networks caused by synapse loss in Alzheimer's disease

The impairment of cognitive function in Alzheimer's disease is clearly correlated to synapse loss. However, the mechanisms underlying this correlation are only poorly understood. Here, we investigate how the loss of excitatory synapses in sparsely connected random networks of spiking excitatory and inhibitory neurons alters their dynamical characteristics. Beyond the effects on the activity statistics, we find that the loss of excitatory synapses on excitatory neurons reduces the network's sensitivity to small perturbations. This decrease in sensitivity can be considered as an indication of a reduction of computational capacity. A full recovery of the network's dynamical characteristics and sensitivity can be achieved by firing rate homeostasis, here implemented by an up-scaling of the remaining excitatory-excitatory synapses. Mean-field analysis reveals that the stability of the linearised network dynamics is, in good approximation, uniquely determined by the firing rate, and thereby explains why firing rate homeostasis preserves not only the firing rate but also the network's sensitivity to small perturbations.

Circuitry Underlying Experience-Dependent Plasticity in the Mouse Visual System

Since the discovery of ocular dominance plasticity, neuroscientists have understood that changes in visual experience during a discrete developmental time, the critical period, trigger robust changes in the visual cortex. State-of-the-art tools used to probe connectivity with cell-type-specific resolution have expanded the understanding of circuit changes underlying experience-dependent plasticity. Here, we review the visual circuitry of the mouse, describing projections from retina to thalamus, between thalamus and cortex, and within cortex. We discuss how visual circuit development leads to precise connectivity and identify synaptic loci, which can be altered by activity or experience. Plasticity extends to visual features beyond ocular dominance, involving subcortical and cortical regions, and connections between cortical inhibitory interneurons. Experience-dependent plasticity contributes to the alignment of networks spanning retina to thalamus to cortex. Disruption of this plasticity may underlie aberrant sensory processing in some neurodevelopmental disorders.

Three-dimensional synaptic organization of the human hippocampal CA1 field

The hippocampal CA1 field integrates a wide variety of subcortical and cortical inputs, but its synaptic organization in humans is still unknown due to the difficulties involved studying the human brain via electron microscope techniques. However, we have shown that the 3D reconstruction method using Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) can be applied to study in detail the synaptic organization of the human brain obtained from autopsies, yielding excellent results. Using this technology, 24,752 synapses were fully reconstructed in CA1, revealing that most of them were excitatory, targeting dendritic spines and displaying a macular shape, regardless of the layer examined. However, remarkable differences were observed between layers. These data constitute the first extensive description of the synaptic organization of the neuropil of the human CA1 region.

Edge of Chaos and Avalanches in Neural Networks with Heavy-Tailed Synaptic Weight Distribution

We propose an analytically tractable neural connectivity model with power-law distributed synaptic strengths. When threshold neurons with biologically plausible number of incoming connections are considered, our model features a continuous transition to chaos and can reproduce biologically relevant low activity levels and scale-free avalanches, i.e., bursts of activity with power-law distributions of sizes and lifetimes. In contrast, the Gaussian counterpart exhibits a discontinuous transition to chaos and thus cannot be poised near the edge of chaos. We validate our predictions in simulations of networks of binary as well as leaky integrate-and-fire neurons. Our results suggest that heavy-tailed synaptic distribution may form a weakly informative sparse-connectivity prior that can be useful in biological and artificial adaptive systems.

The Spectrum of Asynchronous Dynamics in Spiking Networks as a Model for the Diversity of Non-rhythmic Waking States in the Neocortex

The awake cortex exhibits diverse non-rhythmic network states. However, how these states emerge and how each state impacts network function is unclear. Here, we demonstrate that model networks of spiking neurons with moderate recurrent interactions display a spectrum of non-rhythmic asynchronous dynamics based on the level of afferent excitation, from afferent input-dominated (AD) regimes, characterized by unbalanced synaptic currents and sparse firing, to recurrent input-dominated (RD) regimes, characterized by balanced synaptic currents and dense firing. The model predicted regime-specific relationships between different neural biophysical properties, which were all experimentally validated in the somatosensory cortex (S1) of awake mice. Moreover, AD regimes more precisely encoded spatiotemporal patterns of presynaptic activity, while RD regimes better encoded the strength of afferent inputs. These results provide a theoretical foundation for how recurrent neocortical circuits generate non-rhythmic waking states and how these different states modulate the processing of incoming information.

Inhibition stabilization is a widespread property of cortical networks

Many cortical network models use recurrent coupling strong enough to require inhibition for stabilization. Yet it has been experimentally unclear whether inhibition-stabilized network (ISN) models describe cortical function well across areas and states. Here, we test several ISN predictions, including the counterintuitive (paradoxical) suppression of inhibitory firing in response to optogenetic inhibitory stimulation. We find clear evidence for ISN operation in mouse visual, somatosensory, and motor cortex. Simple two-population ISN models describe the data well and let us quantify coupling strength. Although some models predict a non-ISN to ISN transition with increasingly strong sensory stimuli, we find ISN effects without sensory stimulation and even during light anesthesia. Additionally, average paradoxical effects result only with transgenic, not viral, opsin expression in parvalbumin (PV)-positive neurons; theory and expression data show this is consistent with ISN operation. Taken together, these results show strong coupling and inhibition stabilization are common features of the cortex.

Cortical Coding of Whisking Phase during Surface Whisking

In rodent whisker sensation, whisker position signals, including whisking phase, are integrated with touch signals to enable spatially accurate tactile perception, but other functions of phase coding are unclear. We investigate how phase coding affects the neural coding of surface features during surface whisking. In mice performing rough-smooth discrimination, S1 units exhibit much stronger phase tuning during surface whisking than in prior studies of whisking in air. Among putative pyramidal cells, preferred phase tiles phase space, but protraction phases are strongly over-represented. Fast-spiking units are nearly all protraction tuned. This protraction bias increases the coding of stick-slip whisker events during protraction, suggesting that surface features are preferentially encoded during protraction. Correspondingly, protraction-tuned units encode rough-smooth texture better than retraction-tuned units and encode the precise spatial location of surface ridges with higher acuity. This suggests that protraction is the main information-gathering phase for high-resolution surface features, with phase coding organized to support this function.

Information filtering by coincidence detection of synchronous population output: analytical approaches to the coherence function of a two-stage neural system

Information about time-dependent sensory stimuli is encoded in the activity of neural populations; distinct aspects of the stimulus are read out by different types of neurons: while overall information is perceived by integrator cells, so-called coincidence detector cells are driven mainly by the synchronous activity in the population that encodes predominantly high-frequency content of the input signal (high-pass information filtering). Previously, an analytically accessible statistic called the partial synchronous output was introduced as a proxy for the coincidence detector cell's output in order to approximate its information transmission. In the first part of the current paper, we compare the information filtering properties (specifically, the coherence function) of this proxy to those of a simple coincidence detector neuron. We show that the latter's coherence function can indeed be well-approximated by the partial synchronous output with a time scale and threshold criterion that are related approximately linearly to the membrane time constant and firing threshold of the coincidence detector cell. In the second part of the paper, we propose an alternative theory for the spectral measures (including the coherence) of the coincidence detector cell that combines linear-response theory for shot-noise driven integrate-and-fire neurons with a novel perturbation ansatz for the spectra of spike-trains driven by colored noise. We demonstrate how the variability of the synaptic weights for connections from the population to the coincidence detector can shape the information transmission of the entire two-stage system.

Anatomically revealed morphological patterns of pyramidal neurons in layer 5 of the motor cortex

Neuronal cell types are essential to the comprehensive understanding of the neuronal function and neuron can be categorized by their anatomical property. However, complete morphology data for neurons with a whole brain projection, for example the pyramidal neurons in the cortex, are sparse because it is difficult to trace the neuronal fibers across the whole brain and acquire the neuron morphology at the single axon resolution. Thus the cell types of pyramidal neurons have yet to be studied at the single axon resolution thoroughly. In this work, we acquire images for a Thy1 H-line mouse brain using a fluorescence micro-optical sectioning tomography system. Then we sample 42 pyramidal neurons whose somata are in the layer 5 of the motor cortex and reconstruct their morphology across the whole brain. Based on the reconstructed neuronal anatomy, we analyze the axonal and dendritic fibers of the neurons in addition to the soma spatial distributions, and identify two axonal projection pattern of pyramidal tract neurons and two dendritic spreading patterns of intratelencephalic neurons. The raw image data are available upon request as an additional asset to the community. The morphological patterns identified in this work can be a typical representation of neuron subtypes and reveal the possible input-output function of a single pyramidal neuron.

Temporal Sharpening of Sensory Responses by Layer V in the Mouse Primary Somatosensory Cortex

The timing of stimulus-evoked spikes encodes information about sensory stimuli. Here we studied the neural circuits controlling this process in the mouse primary somatosensory cortex. We found that brief optogenetic activation of layer V pyramidal cells just after whisker deflection modulated the membrane potential of neurons and interrupted their long-latency whisker responses, increasing their accuracy in encoding whisker deflection time. In contrast, optogenetic inhibition of layer V during either passive whisker deflection or active whisking decreased accuracy in encoding stimulus or touch time, respectively. Suppression of layer V pyramidal cells increased reaction times in a texture discrimination task. Moreover, two-color optogenetic experiments revealed that cortical inhibition was efficiently recruited by layer V stimulation and that it mainly involved activation of parvalbumin-positive rather than somatostatin-positive interneurons. Layer V thus performs behaviorally relevant temporal sharpening of sensory responses through circuit-specific recruitment of cortical inhibition.

Axonal Na+ channels detect and transmit levels of input synchrony in local brain circuits

Sensory processing requires mechanisms of fast coincidence detection to discriminate synchronous from asynchronous inputs. Spike threshold adaptation enables such a discrimination but is ineffective in transmitting this information to the network. We show here that presynaptic axonal sodium channels read and transmit precise levels of input synchrony to the postsynaptic cell by modulating the presynaptic action potential (AP) amplitude. As a consequence, synaptic transmission is facilitated at cortical synapses when the presynaptic spike is produced by synchronous inputs. Using dual soma-axon recordings, imaging, and modeling, we show that this facilitation results from enhanced AP amplitude in the axon due to minimized inactivation of axonal sodium channels. Quantifying local circuit activity and using network modeling, we found that spikes induced by synchronous inputs produced a larger effect on network activity than spikes induced by asynchronous inputs. Therefore, this input synchrony-dependent facilitation may constitute a powerful mechanism, regulating synaptic transmission at proximal synapses.

Multiple Morphological Factors Underlie Experience-Dependent Cross-Modal Plasticity in the Developing Sensory Cortices

Sensory experience regulates the structural and functional wiring of sensory cortices. In previous work, we showed that whisker deprivation (WD) from birth not only reduced excitatory synaptic transmission of layer (L) 2/3 pyramidal neurons of the correspondent barrel cortex in mice, but also cross-modally reduced synaptic transmission of L2/3 pyramidal neurons in other sensory cortices. Here, we used in utero electroporation, in combination with optical clearing, to examine the main morphological components regulating neural circuit wiring, namely presynaptic bouton density, spine density, as well as dendrite and axon arbor lengths. We found that WD from P0 to P14 reduced presynaptic bouton density in both L4 and L2/3 inputs to L2/3 pyramidal neurons, as well as spine density across the dendritic tree of L2/3 pyramidal neurons, in the barrel field of the primary somatosensory cortex. The cross-modal effects in the primary auditory cortex were manifested mostly as reduced dendrite and axon arbor size, as well as reduced bouton density of L2/3 inputs. Increasing sensory experience by rearing mice in an enriched environment rescued the effects of WD. Together, these results demonstrate that multiple morphological factors contribute to experience-dependent structural plasticity during early wiring of the sensory cortices.

Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity

Coarse-graining microscopic models of biological neural networks to obtain mesoscopic models of neural activities is an essential step towards multi-scale models of the brain. Here, we extend a recent theory for mesoscopic population dynamics with static synapses to the case of dynamic synapses exhibiting short-term plasticity (STP). The extended theory offers an approximate mean-field dynamics for the synaptic input currents arising from populations of spiking neurons and synapses undergoing Tsodyks-Markram STP. The approximate mean-field dynamics accounts for both finite number of synapses and correlation between the two synaptic variables of the model (utilization and available resources) and its numerical implementation is simple. Comparisons with Monte Carlo simulations of the microscopic model show that in both feedforward and recurrent networks, the mesoscopic mean-field model accurately reproduces the first- and second-order statistics of the total synaptic input into a postsynaptic neuron and accounts for stochastic switches between Up and Down states and for population spikes. The extended mesoscopic population theory of spiking neural networks with STP may be useful for a systematic reduction of detailed biophysical models of cortical microcircuits to numerically efficient and mathematically tractable mean-field models.

Whole-Neuron Synaptic Mapping Reveals Spatially Precise Excitatory/Inhibitory Balance Limiting Dendritic and Somatic Spiking

The balance between excitatory and inhibitory (E and I) synapses is thought to be critical for information processing in neural circuits. However, little is known about the spatial principles of E and I synaptic organization across the entire dendritic tree of mammalian neurons. We developed a new open-source reconstruction platform for mapping the size and spatial distribution of E and I synapses received by individual genetically-labeled layer 2/3 (L2/3) cortical pyramidal neurons (PNs) in vivo. We mapped over 90,000 E and I synapses across twelve L2/3 PNs and uncovered structured organization of E and I synapses across dendritic domains as well as within individual dendritic segments. Despite significant domain-specific variation in the absolute density of E and I synapses, their ratio is strikingly balanced locally across dendritic segments. Computational modeling indicates that this spatially precise E/I balance dampens dendritic voltage fluctuations and strongly impacts neuronal firing output.

Cell type composition and circuit organization of clonally related excitatory neurons in the juvenile mouse neocortex

Clones of excitatory neurons derived from a common progenitor have been proposed to serve as elementary information processing modules in the neocortex. To characterize the cell types and circuit diagram of clonally related excitatory neurons, we performed multi-cell patch clamp recordings and Patch-seq on neurons derived from Nestin-positive progenitors labeled by tamoxifen induction at embryonic day 10.5. The resulting clones are derived from two radial glia on average, span cortical layers 2-6, and are composed of a random sampling of transcriptomic cell types. We find an interaction between shared lineage and connection type: related neurons are more likely to be connected vertically across cortical layers, but not laterally within the same layer. These findings challenge the view that related neurons show uniformly increased connectivity and suggest that integration of vertical intra-clonal input with lateral inter-clonal input may represent a developmentally programmed connectivity motif supporting the emergence of functional circuits.

Recurrent interactions in local cortical circuits

Most cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing pattern completion and other computations^1-4. Cortical circuits contain subnetworks that consist of neurons with similar receptive fields and increased connectivity relative to the network average^5,6. Cortical neurons that encode different types of information are spatially intermingled and distributed over large brain volumes^5-7, and this complexity has hindered attempts to probe the function of these subnetworks by perturbing them individually⁸. Here we use computational modelling, optical recordings and manipulations to probe the function of recurrent coupling in layer 2/3 of the mouse vibrissal somatosensory cortex during active tactile discrimination. A neural circuit model of layer 2/3 revealed that recurrent excitation enhances sensory signals by amplification, but only for subnetworks with increased connectivity. Model networks with high amplification were sensitive to damage: loss of a few members of the subnetwork degraded stimulus encoding. We tested this prediction by mapping neuronal selectivity⁷ and photoablating^9,10 neurons with specific selectivity. Ablation of a small proportion of layer 2/3 neurons (10-20, less than 5% of the total) representing touch markedly reduced responses in the spared touch representation, but not in other representations. Ablations most strongly affected neurons with stimulus responses that were similar to those of the ablated population, which is also consistent with network models. Recurrence among cortical neurons with similar selectivity therefore drives input-specific amplification during behaviour.

Activity Dependent and Independent Determinants of Synaptic Size Diversity

The extraordinary diversity of excitatory synapse sizes is commonly attributed to activity-dependent processes that drive synaptic growth and diminution. Recent studies also point to activity-independent size fluctuations, possibly driven by innate synaptic molecule dynamics, as important generators of size diversity. To examine the contributions of activity-dependent and independent processes to excitatory synapse size diversity, we studied glutamatergic synapse size dynamics and diversification in cultured rat cortical neurons (both sexes), silenced from plating. We found that in networks with no history of activity whatsoever, synaptic size diversity was no less extensive than that observed in spontaneously active networks. Synapses in silenced networks were larger, size distributions were broader, yet these were rightward-skewed and similar in shape when scaled by mean synaptic size. Silencing reduced the magnitude of size fluctuations and weakened constraints on size distributions, yet these were sufficient to explain synaptic size diversity in silenced networks. Model-based exploration followed by experimental testing indicated that silencing-associated changes in innate molecular dynamics and fluctuation characteristics might negatively impact synaptic persistence, resulting in reduced synaptic numbers. This, in turn, would increase synaptic molecule availability, promote synaptic enlargement, and ultimately alter fluctuation characteristics. These findings suggest that activity-independent size fluctuations are sufficient to fully diversify glutamatergic synaptic sizes, with activity-dependent processes primarily setting the scale rather than the shape of size distributions. Moreover, they point to reciprocal relationships between synaptic size fluctuations, size distributions, and synaptic numbers mediated by the innate dynamics of synaptic molecules as they move in, out, and between synapses.SIGNIFICANCE STATEMENT Sizes of glutamatergic synapses vary tremendously, even when formed on the same neuron. This diversity is commonly thought to reflect the outcome of activity-dependent forms of synaptic plasticity, yet activity-independent processes might also play some part. Here we show that in neurons with no history of activity whatsoever, synaptic sizes are no less diverse. We show that this diversity is the product of activity-independent size fluctuations, which are sufficient to generate a full repertoire of synaptic sizes at correct proportions. By combining modeling and experimentation we expose reciprocal relationships between size fluctuations, synaptic sizes and synaptic counts, and show how these phenomena might be connected through the dynamics of synaptic molecules as they move in, out, and between synapses.

Unveiling the Synaptic Function and Structure Using Paired Recordings From Synaptically Coupled Neurons

Synaptic transmission between neurons is the basic mechanism for information processing in cortical microcircuits. To date, paired recording from synaptically coupled neurons is the most widely used method which allows a detailed functional characterization of unitary synaptic transmission at the cellular and synaptic level in combination with a structural characterization of both pre- and postsynaptic neurons at the light and electron microscopic level. In this review, we will summarize the many applications of paired recordings to investigate synaptic function and structure. Paired recordings have been used to study the detailed electrophysiological and anatomical properties of synaptically coupled cell pairs within a synaptic microcircuit; this is critical in order to understand the connectivity rules and dynamic properties of synaptic transmission. Paired recordings can also be adopted for quantal analysis of an identified synaptic connection and to study the regulation of synaptic transmission by neuromodulators such as acetylcholine, the monoamines, neuropeptides, and adenosine etc. Taken together, paired recordings from synaptically coupled neurons will remain a very useful approach for a detailed characterization of synaptic transmission not only in the rodent brain but also that of other species including humans.

Human in vitro systems for examining synaptic function and plasticity in the brain

The human brain shows remarkable complexity in its cellular makeup and function, which are distinct from nonhuman species, signifying the need for human-based research platforms for the study of human cellular neurophysiology and neuropathology. However, the use of adult human brain tissue for research purposes is hampered by technical, methodological, and accessibility challenges. One of the major problems is the limited number of in vitro systems that, in contrast, are readily available from rodent brain tissue. With recent advances in the optimization of protocols for adult human brain preparations, there is a significant opportunity for neuroscientists to validate their findings in human-based systems. This review addresses the methodological aspects, advantages, and disadvantages of human neuron in vitro systems, focusing on the unique properties of human neurons and synapses in neocortical microcircuits. These in vitro models provide the incomparable advantage of being a direct representation of the neurons that have formed part of the human brain until the point of recording, which cannot be replicated by animal models nor human stem-cell systems. Important distinct cellular mechanisms are observed in human neurons that may underlie the higher order cognitive abilities of the human brain. The use of human brain tissue in neuroscience research also raises important ethical, diversity, and control tissue limitations that need to be considered. Undoubtedly however, these human neuron systems provide critical information to increase the potential of translation of treatments from the laboratory to the clinic in a way animal models are failing to provide.

Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex

Mouse primary somatosensory barrel cortex (wS1) processes whisker sensory information, receiving input from two distinct thalamic nuclei. The first-order ventral posterior medial (VPM) somatosensory thalamic nucleus most densely innervates layer 4 (L4) barrels, whereas the higher-order posterior thalamic nucleus (medial part, POm) most densely innervates L1 and L5A. We optogenetically stimulated VPM or POm axons, and recorded evoked excitatory postsynaptic potentials (EPSPs) in different cell-types across cortical layers in wS1. We found that excitatory neurons and parvalbumin-expressing inhibitory neurons received the largest EPSPs, dominated by VPM input to L4 and POm input to L5A. In contrast, somatostatin-expressing inhibitory neurons received very little input from either pathway in any layer. Vasoactive intestinal peptide-expressing inhibitory neurons received an intermediate level of excitatory input with less apparent layer-specificity. Our data help understand how wS1 neocortical microcircuits might process and integrate sensory and higher-order inputs.

Combined Positive and Negative Feedback Allows Modulation of Neuronal Oscillation Frequency during Sensory Processing

A key step in sensory information processing involves modulation and integration of neuronal oscillations in disparate frequency bands, a poorly understood process. Here, we investigate how top-down input causes frequency changes in slow oscillations during sensory processing and, in turn, how the slow oscillations are combined with fast oscillations (which encode sensory input). Using experimental connectivity patterns and strengths of interneurons, we develop a system-level model of a neuronal circuit controlling these oscillatory behaviors, allowing us to understand the mechanisms responsible for the observed oscillatory behaviors. Our analysis discovers a circuit capable of producing the observed oscillatory behaviors and finds that a detailed balance in the strength of synaptic connections is the critical determinant to produce such oscillatory behaviors. We not only uncover how disparate frequency bands are modulated and combined but also give insights into the causes of abnormal neuronal activities present in brain disorders.

Dendrite-Specific Amplification of Weak Synaptic Input during Network Activity In Vivo

Excitatory synaptic input reaches the soma of a cortical excitatory pyramidal neuron via anatomically segregated apical and basal dendrites. In vivo, dendritic inputs are integrated during depolarized network activity, but how network activity affects apical and basal inputs is not understood. Using subcellular two-photon stimulation of Channelrhodopsin2-expressing layer 2/3 pyramidal neurons in somatosensory cortex, nucleus-specific thalamic optogenetic stimulation, and paired recordings, we show that slow, depolarized network activity amplifies small-amplitude synaptic inputs targeted to basal dendrites but reduces the amplitude of all inputs from apical dendrites and the cell soma. Intracellular pharmacology and mathematical modeling suggests that the amplification of weak basal inputs is mediated by postsynaptic voltage-gated channels. Thus, network activity dynamically reconfigures the relative somatic contribution of apical and basal inputs and could act to enhance the detectability of weak synaptic inputs.

Layer 2/3 Pyramidal Neurons Control the Gain of Cortical Output

Initial anatomical and physiological studies suggested that sensory information relayed from the periphery by the thalamus is serially processed in primary sensory cortical areas. It is thought to propagate from layer 4 (L4) up to L2/3 and down to L5, which constitutes the main output of the cortex. However, more recent experiments point toward the existence of a direct processing of thalamic input by L5 neurons. Therefore, the role of L2/3 neurons in the sensory processing operated by L5 neurons is now highly debated. Using cell type-specific and reversible optogenetic manipulations in the somatosensory cortex of both anesthetized and awake mice, we demonstrate that L2/3 pyramidal neurons play a major role in amplifying sensory-evoked responses in L5 neurons. The amplification effect scales with the velocity of the sensory stimulus, indicating that L2/3 pyramidal neurons implement gain control in deep-layer neurons.

Large-Scale Simulation of a Layered Cortical Sheet of Spiking Network Model Using a Tile Partitioning Method

One of the grand challenges for computational neuroscience and high-performance computing is computer simulation of a human-scale whole brain model with spiking neurons and synaptic plasticity using supercomputers. To achieve such a simulation, the target network model must be partitioned onto a number of computational nodes, and the sub-network models are executed in parallel while communicating spike information across different nodes. However, it remains unclear how the target network model should be partitioned for efficient computing on next generation of supercomputers. Specifically, reducing the communication of spike information across compute nodes is essential, because of the relatively slower network performance than processor and memory. From the viewpoint of biological features, the cerebral cortex and cerebellum contain 99% of neurons and synapses and form layered sheet structures. Therefore, an efficient method to split the network should exploit the layered sheet structures. In this study, we indicate that a tile partitioning method leads to efficient communication. To demonstrate it, a simulation software called MONET (Millefeuille-like Organization NEural neTwork simulator) that partitions a network model as described above was developed. The MONET simulator was implemented on the Japanese flagship supercomputer K, which is composed of 82,944 computational nodes. We examined a performance of calculation, communication and memory consumption in the tile partitioning method for a cortical model with realistic anatomical and physiological parameters. The result showed that the tile partitioning method drastically reduced communication data amount by replacing network communication with DRAM access and sharing the communication data with neighboring neurons. We confirmed the scalability and efficiency of the tile partitioning method on up to 63,504 compute nodes of the K computer for the cortical model. In the companion paper by Yamaura et al., the performance for a cerebellar model was examined. These results suggest that the tile partitioning method will have advantage for a human-scale whole-brain simulation on exascale computers.

Cortical Output Is Gated by Horizontally Projecting Neurons in the Deep Layers

Pyramidal tract neurons (PTs) represent the major output cell type of the mammalian neocortex. Here, we report the origins of the PTs’ ability to respond to a broad range of stimuli with onset latencies that rival or even precede those of their intracortical input neurons. We find that neurons with extensive horizontally projecting axons cluster around the deep-layer terminal fields of primary thalamocortical axons. The strategic location of these corticocortical neurons results in high convergence of thalamocortical inputs, which drive reliable sensory-evoked responses that precede those in other excitatory cell types. The resultant fast and horizontal stream of excitation provides PTs throughout the cortical area with input that acts to amplify additional inputs from thalamocortical and other intracortical populations. The fast onsets and broadly tuned characteristics of PT responses hence reflect a gating mechanism in the deep layers, which assures that sensory-evoked input can be reliably transformed into cortical output.

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Simulations predict in vivo responses for major output cell type of the neocortex

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Simulations reveal strategy how to test the origins of cortical output empirically

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Manipulations confirm that deep-layer corticocortical neurons gate cortical output

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Gating of cortical output originates from deep-layer thalamocortical input stratum

High-throughput microcircuit analysis of individual human brains through next-generation multineuron patch-clamp

Comparing neuronal microcircuits across different brain regions, species and individuals can reveal common and divergent principles of network computation. Simultaneous patch-clamp recordings from multiple neurons offer the highest temporal and subthreshold resolution to analyse local synaptic connectivity. However, its establishment is technically complex and the experimental performance is limited by high failure rates, long experimental times and small sample sizes. We introduce an in vitro multipatch setup with an automated pipette pressure and cleaning system facilitating recordings of up to 10 neurons simultaneously and sequential patching of additional neurons. We present hardware and software solutions that increase the usability, speed and data throughput of multipatch experiments which allowed probing of 150 synaptic connections between 17 neurons in one human cortical slice and screening of over 600 connections in tissue from a single patient. This method will facilitate the systematic analysis of microcircuits and allow unprecedented assessment of inter-individual variability.

Embryonic progenitor pools generate diversity in fine-scale excitatory cortical subnetworks

The mammalian neocortex is characterized by a variety of neuronal cell types and precise arrangements of synaptic connections, but the processes that generate this diversity are poorly understood. Here we examine how a pool of embryonic progenitor cells consisting of apical intermediate progenitors (aIPs) contribute to diversity within the upper layers of mouse cortex. In utero labeling combined with single-cell RNA-sequencing reveals that aIPs can generate transcriptionally defined glutamatergic cell types, when compared to neighboring neurons born from other embryonic progenitor pools. Whilst sharing layer-associated morphological and functional properties, simultaneous patch clamp recordings and optogenetic studies reveal that aIP-derived neurons exhibit systematic biases in both their intralaminar monosynaptic connectivity and the post-synaptic partners that they target within deeper layers of cortex. Multiple cortical progenitor pools therefore represent an important factor in establishing diversity amongst local and long-range fine-scale glutamatergic connectivity, which generates subnetworks for routing excitatory synaptic information.

Spatiotemporal constraints on optogenetic inactivation in cortical circuits

Optogenetics allows manipulations of genetically and spatially defined neuronal populations with excellent temporal control. However, neurons are coupled with other neurons over multiple length scales, and the effects of localized manipulations thus spread beyond the targeted neurons. We benchmarked several optogenetic methods to inactivate small regions of neocortex. Optogenetic excitation of GABAergic neurons produced more effective inactivation than light-gated ion pumps. Transgenic mice expressing the light-dependent chloride channel GtACR1 produced the most potent inactivation. Generally, inactivation spread substantially beyond the photostimulation light, caused by strong coupling between cortical neurons. Over some range of light intensity, optogenetic excitation of inhibitory neurons reduced activity in these neurons, together with pyramidal neurons, a signature of inhibition-stabilized neural networks ('paradoxical effect'). The offset of optogenetic inactivation was followed by rebound excitation in a light dose-dependent manner, limiting temporal resolution. Our data offer guidance for the design of in vivo optogenetics experiments.

A Non-canonical Feedback Circuit for Rapid Interactions between Somatosensory Cortices

Sensory perception depends on interactions among cortical areas. These interactions are mediated by canonical patterns of connectivity in which higher areas send feedback projections to lower areas via neurons in superficial and deep layers. Here, we probed the circuit basis of interactions among two areas critical for touch perception in mice, whisker primary (wS1) and secondary (wS2) somatosensory cortices. Neurons in layer 4 of wS2 (S2_L4) formed a major feedback pathway to wS1. Feedback from wS2 to wS1 was organized somatotopically. Spikes evoked by whisker deflections occurred nearly as rapidly in wS2 as in wS1, including among putative S2_L4 → S1 feedback neurons. Axons from S2_L4 → S1 neurons sent stimulus orientation-specific activity to wS1. Optogenetic excitation of S2_L4 neurons modulated activity across both wS2 and wS1, while inhibition of S2_L4 reduced orientation tuning among wS1 neurons. Thus, a non-canonical feedback circuit, originating in layer 4 of S2, rapidly modulates early tactile processing.

Cellular and synaptic phenotypes lead to disrupted information processing in Fmr1-KO mouse layer 4 barrel cortex

Sensory hypersensitivity is a common and debilitating feature of neurodevelopmental disorders such as Fragile X Syndrome (FXS). How developmental changes in neuronal function culminate in network dysfunction that underlies sensory hypersensitivities is unknown. By systematically studying cellular and synaptic properties of layer 4 neurons combined with cellular and network simulations, we explored how the array of phenotypes in Fmr1-knockout (KO) mice produce circuit pathology during development. We show that many of the cellular and synaptic pathologies in Fmr1-KO mice are antagonistic, mitigating circuit dysfunction, and hence may be compensatory to the primary pathology. Overall, the layer 4 network in the Fmr1-KO exhibits significant alterations in spike output in response to thalamocortical input and distorted sensory encoding. This developmental loss of layer 4 sensory encoding precision would contribute to subsequent developmental alterations in layer 4-to-layer 2/3 connectivity and plasticity observed in Fmr1-KO mice, and circuit dysfunction underlying sensory hypersensitivity.

Progressive Circuit Changes during Learning and Disease

A critical step toward understanding cognition, learning, and brain dysfunction will be identification of the underlying cellular computations that occur in and across discrete brain areas, as well as how they are progressively altered by experience or disease. These computations will be revealed by targeted analyses of the neurons that perform these calculations, defined not only by their firing properties but also by their molecular identity and how they are wired within the local and broad-scale network of the brain. New studies that take advantage of sophisticated genetic tools for cell-type-specific identification and control are revealing how learning and neurological disorders initiate and successively change the properties of defined neural circuits. Understanding the temporal sequence of adaptive or pathological synaptic changes across multiple synapses within a network will shed light into how small-scale neural circuits contribute to higher cognitive functions during learning and disease.

Cell Class-Dependent Intracortical Connectivity and Output Dynamics of Layer 6 Projection Neurons of the Rat Primary Visual Cortex

Neocortical information processing is powerfully influenced by the activity of layer 6 projection neurons through control of local intracortical and subcortical circuitry. Morphologically distinct classes of layer 6 projection neuron have been identified in the mammalian visual cortex, which exhibit contrasting receptive field properties, but little information is available on their functional specificity. To address this we combined anatomical tracing techniques with high-resolution patch-clamp recording to identify morphological and functional distinct classes of layer 6 projection neurons in the rat primary visual cortex, which innervated separable subcortical territories. Multisite whole-cell recordings in brain slices revealed that corticoclaustral and corticothalamic layer 6 projection neurons exhibited similar somatically recorded electrophysiological properties. These classes of layer 6 projection neurons were sparsely and reciprocally synaptically interconnected, but could be differentiated by cell-class, but not target-cell-dependent rules of use-dependent depression and facilitation of unitary excitatory synaptic output. Corticoclaustral and corticothalamic layer 6 projection neurons were differentially innervated by columnar excitatory circuitry, with corticoclaustral, but not corticothalamic, neurons powerfully driven by layer 4 pyramidal neurons, and long-range pathways conveyed in neocortical layer 1. Our results therefore reveal projection target-specific, functionally distinct, streams of layer 6 output in the rodent neocortex.

Mind the last spike - firing rate models for mesoscopic populations of spiking neurons

The dominant modeling framework for understanding cortical computations are heuristic firing rate models. Despite their success, these models fall short to capture spike synchronization effects, to link to biophysical parameters and to describe finite-size fluctuations. In this opinion article, we propose that the refractory density method (RDM), also known as age-structured population dynamics or quasi-renewal theory, yields a powerful theoretical framework to build rate-based models for mesoscopic neural populations from realistic neuron dynamics at the microscopic level. We review recent advances achieved by the RDM to obtain efficient population density equations for networks of generalized integrate-and-fire (GIF) neurons - a class of neuron models that has been successfully fitted to various cell types. The theory not only predicts the nonstationary dynamics of large populations of neurons but also permits an extension to finite-size populations and a systematic reduction to low-dimensional rate dynamics. The new types of rate models will allow a re-examination of models of cortical computations under biological constraints.

A Corticothalamic Circuit for Refining Tactile Encoding

A fundamental task for the brain is to determine which aspects of the continuous flow of information is the most relevant in a given behavioral situation. The information flow is regulated via dynamic interactions between feedforward and feedback pathways. One such pathway is via corticothalamic feedback. Layer 6 (L6) corticothalamic (CT) cells make both cortical and thalamic connections and, therefore, are key modulators of activity in both areas. The functional properties of L6 CT cells in sensory processing were investigated in the mouse whisker system. Optogenetic activation of L6 CT neurons decreased spontaneous spiking, with the net effect that a whisker-evoked response was more accurately detected (larger evoked-to-spontaneous spiking ratio) but at the expense of reducing the response probability. In addition, L6 CT activation decreases sensory adaptation in both the thalamus and cortex. L6 CT activity can thus tune the tactile system, depending on the behaviorally relevant tactile input.

Ipsi- and contralateral corticocortical projection-dependent subcircuits in layer 2 of the rat frontal cortex

In the neocortex, both layer 2/3 and layer 5 contain corticocortical pyramidal cells projecting to other cortices. We previously found that among L5 pyramidal cells of the secondary motor cortex (M2), not only intratelencephalic projection cells but also pyramidal tract cells innervate ipsilateral cortices and that the two subtypes are different in corticocortical projection diversity and axonal laminar distributions. Layer 2/3 houses intratelencephalically projecting pyramidal cells that also innervate multiple ipsilateral and contralateral cortices. However, it remained unclear whether layer 2/3 pyramidal cells can be divided into projection subtypes each with distinct innervation to specific targets. In the present study we show that layer 2 pyramidal cells are organized into subcircuits on the basis of corticocortical projection targets. Layer 2 corticocortical cells of the same projection subtype were monosynaptically connected. Between the contralaterally and ipsilaterally projecting corticocortical cells, the monosynaptic connection was more common from the former to the latter. We also found that ipsilaterally and contralaterally projecting corticocortical cell subtypes differed in their morphological and physiological characteristics. Our results suggest that layer 2 transfers separate outputs from M2 to individual cortices and that its subcircuits are hierarchically organized to form the discrete corticocortical outputs.

NEW & NOTEWORTHY Pyramidal cell subtypes and their dependent subcircuits are well characterized in cortical layer 5, but much less is understood for layer 2/3. We demonstrate that in layer 2 of the rat secondary motor cortex, ipsilaterally and contralaterally projecting corticocortical cells are largely segregated. These layer 2 cell subtypes differ in dendrite morphological and intrinsic electrophysiological properties, and form subtype-dependent connections. Our results suggest that layer 2 pyramidal cells form distinct subcircuits to provide discrete corticocortical outputs.

Mapping Brain-Wide Afferent Inputs of Parvalbumin-Expressing GABAergic Neurons in Barrel Cortex Reveals Local and Long-Range Circuit Motifs

Parvalbumin (PV)-expressing GABAergic neurons are the largest class of inhibitory neocortical cells. We visualize brain-wide, monosynaptic inputs to PV neurons in mouse barrel cortex. We develop intersectional rabies virus tracing to specifically target GABAergic PV cells and exclude a small fraction of excitatory PV cells from our starter population. Local inputs are mainly from layer (L) IV and excitatory cells. A small number of inhibitory inputs originate from LI neurons, which connect to LII/III PV neurons. Long-range inputs originate mainly from other sensory cortices and the thalamus. In visual cortex, most transsynaptically labeled neurons are located in LIV, which contains a molecularly mixed population of projection neurons with putative functional similarity to LIII neurons. This study expands our knowledge of the brain-wide circuits in which PV neurons are embedded and introduces intersectional rabies virus tracing as an applicable tool to dissect the circuitry of more clearly defined cell types.

Mouse corticospinal system comprises different functional neuronal ensembles depending on their hodology

BACKGROUND

Movement performance depends on the synaptic interactions generated by coherent parallel sensorimotor cortical outputs to different downstream targets. The major outputs of the neocortex to subcortical structures are driven by pyramidal tract neurons (PTNs) located in layer 5B. One of the main targets of PTNs is the spinal cord through the corticospinal (CS) system, which is formed by a complex collection of distinct CS circuits. However, little is known about intracortical synaptic interactions that originate CS commands and how different populations of CS neurons are functionally organized. To further understand the functional organization of the CS system, we analyzed the activity of unambiguously identified CS neurons projecting to different zones of the same spinal cord segment using two-photon calcium imaging and retrograde neuronal tracers.

RESULTS

Sensorimotor cortex slices obtained from transgenic mice expressing GCaMP6 funder the Thy1 promoter were used to analyze the spontaneous calcium transients in layer 5 pyramidal neurons. Distinct subgroups of CS neurons projecting to dorsal horn and ventral areas of the same segment show more synchronous activity between them than with other subgroups.

CONCLUSIONS

The results indicate that CS neurons projecting to different spinal cord zones segregated into functional ensembles depending on their hodology, suggesting that a modular organization of CS outputs controls sensorimotor behaviors in a coordinated manner.

Layer-specific modulation of pyramidal cell excitability by electroconvulsive shock

Dysregulation of cortical excitability crucially involves in behavioral and cognitive deficits of neurodegenerative and neuropsychiatric diseases. Electroconvulsive shock (ECS) changes neuronal excitability and has been used in the therapy of major depressive disorder and mood disorders. However, the action and the targets of the ECS in the cortical circuits are still poorly understood. Here we show that the ECS differently changes intrinsic properties of pyramidal cells (PCs) among superficial and deep layers. In layer 2/3 PCs, the ECS induced membrane hyperpolarization and the reduction of input resistances. In layer 5 PCs, the ECS also induced membrane hyperpolarization but had little effects on input resistances. In layer 6 PCs, the ECS had no effects on both of resting membrane potentials and input resistances. In addition, the ECS reduced the firing frequency of PCs in layer 2/3 but not in both layers 5 and 6. We further examined the ECS-induced changes in the influx of Ca²⁺ currents, and observed an enhanced Ca²⁺ currents in PCs of both layers 2/3 and 5 but not of layer 6. Thus, this study suggests the layer-specific suppression of PC excitability which will underlie the mechanism of the ECS action on the cortical activity.

Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas

Layer 4 (L4) of mammalian neocortex plays a crucial role in cortical information processing, yet a complete census of its cell types and connectivity remains elusive. Using whole-cell recordings with morphological recovery, we identified one major excitatory and seven inhibitory types of neurons in L4 of adult mouse visual cortex (V1). Nearly all excitatory neurons were pyramidal and all somatostatin-positive (SOM+) non-fast-spiking interneurons were Martinotti cells. In contrast, in somatosensory cortex (S1), excitatory neurons were mostly stellate and SOM+ interneurons were non-Martinotti. These morphologically distinct SOM+ interneurons corresponded to different transcriptomic cell types and were differentially integrated into the local circuit with only S1 neurons receiving local excitatory input. We propose that cell type specific circuit motifs, such as the Martinotti/pyramidal and non-Martinotti/stellate pairs, are used across the cortex as building blocks to assemble cortical circuits.

Temporal-specific complexity of spiking patterns in spontaneous activity induced by a dual complex network structure

Temporal fluctuation of neural activity in the brain has an important function in optimal information processing. Spontaneous activity is a source of such fluctuation. The distribution of excitatory postsynaptic potentials (EPSPs) between cortical pyramidal neurons can follow a log-normal distribution. Recent studies have shown that networks connected by weak synapses exhibit characteristics of a random network, whereas networks connected by strong synapses have small-world characteristics of small path lengths and large cluster coefficients. To investigate the relationship between temporal complexity spontaneous activity and structural network duality in synaptic connections, we executed a simulation study using the leaky integrate-and-fire spiking neural network with log-normal synaptic weight distribution for the EPSPs and duality of synaptic connectivity, depending on synaptic weight. We conducted multiscale entropy analysis of the temporal spiking activity. Our simulation demonstrated that, when strong synaptic connections approach a small-world network, specific spiking patterns arise during irregular spatio-temporal spiking activity, and the complexity at the large temporal scale (i.e., slow frequency) is enhanced. Moreover, we confirmed through a surrogate data analysis that slow temporal dynamics reflect a deterministic process in the spiking neural networks. This modelling approach may improve the understanding of the spatio-temporal complex neural activity in the brain.

Propagation of temporal and rate signals in cultured multilayer networks

Analyses of idealized feedforward networks suggest that several conditions have to be satisfied in order for activity to propagate faithfully across layers. Verifying these concepts experimentally has been difficult owing to the vast number of variables that must be controlled. Here, we cultured cortical neurons in a chamber with sequentially connected compartments, optogenetically stimulated individual neurons in the first layer with high spatiotemporal resolution, and then monitored the subthreshold and suprathreshold potentials in subsequent layers. Brief stimuli delivered to the first layer evoked a short-latency transient response followed by sustained activity. Rate signals, carried by the sustained component, propagated reliably through 4 layers, unlike idealized feedforward networks, which tended strongly towards synchrony. Moreover, temporal jitter in the stimulus was transformed into a rate code and transmitted to the last layer. This novel mode of propagation occurred in the balanced excitatory-inhibitory regime and is mediated by NMDA-mediated receptors and recurrent activity.

Recruitment of GABAergic Interneurons in the Barrel Cortex during Active Tactile Behavior

Neural computation involves diverse types of GABAergic inhibitory interneurons that are integrated with excitatory (E) neurons into precisely structured circuits. To understand how each neuron type shapes sensory representations, we measured firing patterns of defined types of neurons in the barrel cortex while mice performed an active, whisker-dependent object localization task. Touch excited fast-spiking (FS) interneurons at short latency, followed by activation of E neurons and somatostatin-expressing (SST) interneurons. Touch only weakly modulated vasoactive intestinal polypeptide-expressing (VIP) interneurons. Voluntary whisker movement activated FS neurons in the ventral posteromedial nucleus (VPM) target layers, a subset of SST neurons and a majority of VIP neurons. Together, FS neurons track thalamic input, mediating feedforward inhibition. SST neurons monitor local excitation, providing feedback inhibition. VIP neurons are activated by non-sensory inputs, disinhibiting E and FS neurons. Our data reveal rules of recruitment for interneuron types during behavior, providing foundations for understanding computation in cortical microcircuits.