A barrel-related interneuron in layer 4 of rat somatosensory cortex with a high intrabarrel connectivity

Inter and intralaminar excitation of parvalbumin interneurons in mouse barrel cortex

Parvalbumin (PV) interneurons are inhibitory fast-spiking cells with essential roles in directing the flow of information through cortical circuits. These neurons set the balance between excitation and inhibition and control rhythmic activity. PV interneurons differ between cortical layers in their morphology, circuitry, and function, but how their electrophysiological properties vary has received little attention. Here we investigate responses of PV interneurons in different layers of primary somatosensory barrel cortex (BC) to different excitatory inputs. With the genetically-encoded hybrid voltage sensor, hVOS, we recorded voltage changes in many L2/3 and L4 PV interneurons simultaneously, with stimulation applied to either L2/3 or L4. A semi-automated procedure was developed to identify small regions of interest corresponding to single responsive PV interneurons. Amplitude, half-width, and rise-time were greater for PV interneurons residing in L2/3 compared to L4. Stimulation in L2/3 elicited responses in both L2/3 and L4 with longer latency compared to stimulation in L4. These differences in latency between layers could influence their windows for temporal integration. Thus, PV interneurons in different cortical layers of BC respond in a layer specific and input specific manner, and these differences have potential roles in cortical computations.

Conditioning and pseudoconditioning differently change intrinsic excitability of inhibitory interneurons in the neocortex

Many studies indicate a broad role of various classes of GABAergic interneurons in the processes related to learning. However, little is known about how the learning process affects intrinsic excitability of specific classes of interneurons in the neocortex. To determine this, we employed a simple model of conditional learning in mice where vibrissae stimulation was used as a conditioned stimulus and a tail shock as an unconditioned one. In vitro whole-cell patch-clamp recordings showed an increase in intrinsic excitability of low-threshold spiking somatostatin-expressing interneurons (SST-INs) in layer 4 (L4) of the somatosensory (barrel) cortex after the conditioning paradigm. In contrast, pseudoconditioning reduced intrinsic excitability of SST-LTS, parvalbumin-expressing interneurons (PV-INs), and vasoactive intestinal polypeptide-expressing interneurons (VIP-INs) with accommodating pattern in L4 of the barrel cortex. In general, increased intrinsic excitability was accompanied by narrowing of action potentials (APs), whereas decreased intrinsic excitability coincided with AP broadening. Altogether, these results show that both conditioning and pseudoconditioning lead to plastic changes in intrinsic excitability of GABAergic interneurons in a cell-specific manner. In this way, changes in intrinsic excitability can be perceived as a common mechanism of learning-induced plasticity in the GABAergic system.

The Anterolateral Barrel Subfield Differs from the Posteromedial Barrel Subfield in the Morphology and Cell Density of Parvalbumin-Positive GABAergic Interneurons

Layer 4 of the rodent somatosensory cortex has unitary structures called barrels that receive tactile information from individual vibrissae. Barrels in the anterolateral barrel subfield (ALBSF) are much smaller and have gained less attention than larger barrels in the posteromedial barrel subfield (PMBSF), though the former outnumber the latter. We compared the morphological features of barrels between the ALBSF and PMBSF in male mice using deformation-free tangential sections and confocal optical slice-based, precise reconstructions of barrels. The average volume of a single barrel in the ALBSF was 34.7% of that in the PMBSF, but the numerical density of parvalbumin (PV)-positive interneurons in the former was 1.49 times higher than that in the latter. Moreover, PV neuron density in septa was 2.08 times higher in the ALBSF than that in the PMBSF. The proportions of PV neuron number to both all neuron number and all GABAergic neuron number in the ALBSF were also higher than those in the PMBSF. Somata of PV neurons in barrels and septa in the ALBSF received 1.64 and 1.50 times more vesicular glutamate transporter Type 2-labeled boutons than those in the PMBSF, suggesting more potent feedforward inhibitory circuits in the ALBSF. The mode of connectivity through dendritic gap junctions among PV neurons also differed between the ALBSF and PMBSF. Clusters of smaller unitary structures containing a higher density of representative GABAergic interneurons with differential morphological features in the ALBSF suggest a division of functional roles in the two vibrissa-barrel systems, as has been demonstrated by behavioral studies.

Inter and Intralaminar Excitation of Parvalbumin Interneurons in Mouse Barrel Cortex

Parvalbumin (PV) interneurons are inhibitory fast-spiking cells with essential roles in directing the flow of information through cortical circuits. These neurons set the balance between excitation and inhibition, control rhythmic activity, and have been linked to disorders including autism spectrum and schizophrenia. PV interneurons differ between cortical layers in their morphology, circuitry, and function, but how their electrophysiological properties vary has received little attention. Here we investigate responses of PV interneurons in different layers of primary somatosensory barrel cortex (BC) to different excitatory inputs. With the genetically-encoded hybrid voltage sensor, hVOS, we recorded voltage changes simultaneously in many L2/3 and L4 PV interneurons to stimulation in either L2/3 or L4. Decay-times were consistent across L2/3 and L4. Amplitude, half-width, and rise-time were greater for PV interneurons residing in L2/3 compared to L4. Stimulation in L2/3 elicited responses in both L2/3 and L4 with longer latency compared to stimulation in L4. These differences in latency between layers could influence their windows for temporal integration. Thus PV interneurons in different cortical layers of BC show differences in response properties with potential roles in cortical computations.

Unitary synaptic responses of parvalbumin interneurons evoked by excitatory neurons in the mouse barrel cortex

The mammalian cortex integrates and processes information to transform sensory inputs into perceptions and motor outputs. These operations are performed by networks of excitatory and inhibitory neurons distributed through the cortical layers. Parvalbumin interneurons (PVIs) are the most abundant type of inhibitory cortical neuron. With axons projecting within and between layers, PVIs supply feedforward and feedback inhibition to control and modulate circuit function. Distinct populations of excitatory neurons recruit different PVI populations, but the specializations of these synapses are poorly understood. Here, we targeted a genetically encoded hybrid voltage sensor to PVIs and used fluorescence imaging in mouse somatosensory cortex slices to record their voltage changes. Stimulating a single visually identified excitatory neuron with small-tipped theta-glass electrodes depolarized multiple PVIs, and a common threshold suggested that stimulation elicited unitary synaptic potentials in response to a single excitatory neuron. Excitatory neurons depolarized PVIs in multiple layers, with the most residing in the layer of the stimulated neuron. Spiny stellate cells depolarized PVIs more strongly than pyramidal cells by up to 77%, suggesting a greater role for stellate cells in recruiting PVI inhibition and controlling cortical computations. Response half-width also varied between different excitatory inputs. These results demonstrate functional differences between excitatory synapses on PVIs.

Sharp Tuning of Head Direction and Angular Head Velocity Cells in the Somatosensory Cortex

Head direction (HD) cells form a fundamental component in the brain's spatial navigation system and are intricately linked to spatial memory and cognition. Although HD cells have been shown to act as an internal neuronal compass in various cortical and subcortical regions, the neural substrate of HD cells is incompletely understood. It is reported that HD cells in the somatosensory cortex comprise regular-spiking (RS, putative excitatory) and fast-spiking (FS, putative inhibitory) neurons. Surprisingly, somatosensory FS HD cells fire in bursts and display much sharper head-directionality than RS HD cells. These FS HD cells are nonconjunctive, rarely theta rhythmic, sparsely connected and enriched in layer 5. Moreover, sharply tuned FS HD cells, in contrast with RS HD cells, maintain stable tuning in darkness; FS HD cells' coexistence with RS HD cells and angular head velocity (AHV) cells in a layer-specific fashion through the somatosensory cortex presents a previously unreported configuration of spatial representation in the neocortex. Together, these findings challenge the notion that FS interneurons are weakly tuned to sensory stimuli, and offer a local circuit organization relevant to the generation and transmission of HD signaling in the brain.

The impact of neuron morphology on cortical network architecture

The neurons in the cerebral cortex are not randomly interconnected. This specificity in wiring can result from synapse formation mechanisms that connect neurons, depending on their electrical activity and genetically defined identity. Here, we report that the morphological properties of the neurons provide an additional prominent source by which wiring specificity emerges in cortical networks. This morphologically determined wiring specificity reflects similarities between the neurons’ axo-dendritic projections patterns, the packing density, and the cellular diversity of the neuropil. The higher these three factors are, the more recurrent is the topology of the network. Conversely, the lower these factors are, the more feedforward is the network’s topology. These principles predict the empirically observed occurrences of clusters of synapses, cell type-specific connectivity patterns, and nonrandom network motifs. Thus, we demonstrate that wiring specificity emerges in the cerebral cortex at subcellular, cellular, and network scales from the specific morphological properties of its neuronal constituents.

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Neuronal network architectures reflect the morphologies of their constituents

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Morphology predicts nonrandom connectivity from subcellular to network scales

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Morphology predicts connectivity patterns consistent with those observed empirically

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Neuron morphology is a major source for wiring specificity in the cerebral cortex

Cell-Type Specific Neuromodulation of Excitatory and Inhibitory Neurons via Muscarinic Acetylcholine Receptors in Layer 4 of Rat Barrel Cortex

The neuromodulator acetylcholine (ACh) plays an important role in arousal, attention, vigilance, learning and memory. ACh is released during different behavioural states and affects the brain microcircuit by regulating neuronal and synaptic properties. Here, we investigated how a low concentration of ACh (30 μM) affects the intrinsic properties of electrophysiologically and morphologically identified excitatory and inhibitory neurons in layer 4 (L4) of rat barrel cortex. ACh altered the membrane potential of L4 neurons in a heterogeneous manner. Nearly all L4 regular spiking (RS) excitatory neurons responded to bath-application of ACh with a M4 muscarinic ACh receptor-mediated hyperpolarisation. In contrast, in the majority of L4 fast spiking (FS) and non-fast spiking (nFS) interneurons 30 μM ACh induced a depolarisation while the remainder showed a hyperpolarisation or no response. The ACh-induced depolarisation of L4 FS interneurons was much weaker than that in L4 nFS interneurons. There was no clear difference in the response to ACh for three morphological subtypes of L4 FS interneurons. However, in four morpho-electrophysiological subtypes of L4 nFS interneurons, VIP+-like interneurons showed the strongest ACh-induced depolarisation; occasionally, even action potential firing was elicited. The ACh-induced depolarisation in L4 FS interneurons was exclusively mediated by M1 muscarinic ACh receptors; in L4 nFS interneurons it was mainly mediated by M1 and/or M3/5 muscarinic ACh receptors. In a subset of L4 nFS interneurons, a co-operative activation of muscarinic and nicotinic ACh receptors was also observed. The present study demonstrates that low-concentrations of ACh affect different L4 neuron types in a cell-type specific way. These effects result from a specific expression of different muscarinic and/or nicotinic ACh receptors on the somatodendritic compartments of L4 neurons. This suggests that even at low concentrations ACh may tune the excitability of L4 excitatory and inhibitory neurons and their synaptic microcircuits differentially depending on the behavioural state during which ACh is released.

Cortical Representation of Touch in Silico

With its six layers and ~ 12,000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents'. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortex's granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.

Synchronous inhibitory synaptic inputs to layer II/III pyramidal neurons in the murine barrel cortex

The barrel cortex exhibits obvious columnar organization. Although GABAergic inhibition plays a critical role in regulating neural excitation in response to mechanical stimuli applied to whiskers, the profiles of synchronous events for inhibitory synaptic transmission in intracolumnar and transcolumnar pyramidal neurons remain unknown. To explore a functional mechanism of synchronous inhibition of pyramidal neurons, we performed paired whole-cell patch-clamp recordings and recorded spontaneous inhibitory postsynaptic currents (sIPSCs) from layer II/III pyramidal neurons. A cross-correlogram of sIPSCs (1 ms bin) was used to detect synchronous sIPSCs. Synchronous neuron pairs were defined as those whose peak number of sIPSCs between -3 and 3 ms exceeded the mean + 2 SD of the number of sIPSCs in the period of -50 to 50 ms minus the number in that of -3 to 3 ms period. In the recording of pyramidal neurons located in the same column (intracolumn), 61.5% of neuron pairs were classified as synchronous neuron pairs, while 52.6% of pyramidal neuron pairs in adjacent columns (transcolumn) were defined as synchronous neuron pairs. The amplitude of synchronous sIPSCs was comparable to that of asynchronous sIPSCs in asynchronous neuron pairs, whereas that of synchronous sIPSCs was larger than that of asynchronous sIPSCs in synchronous neuron pairs. Synchronicity of sIPSCs did not depend on the distance of neuron pairs. These results suggest that layer II/III pyramidal neurons receive synchronous inhibitory synaptic inputs generated by a certain type of GABAergic interneuron that induces large IPSCs in pyramidal neurons, likely to be fast-spiking cells.

Mechanisms Underlying Target Selectivity for Cell Types and Subcellular Domains in Developing Neocortical Circuits

The cerebral cortex contains numerous neuronal cell types, distinguished by their molecular identity as well as their electrophysiological and morphological properties. Cortical function is reliant on stereotyped patterns of synaptic connectivity and synaptic function among these neuron types, but how these patterns are established during development remains poorly understood. Selective targeting not only of different cell types but also of distinct postsynaptic neuronal domains occurs in many brain circuits and is directed by multiple mechanisms. These mechanisms include the regulation of axonal and dendritic guidance and fine-scale morphogenesis of pre- and postsynaptic processes, lineage relationships, activity dependent mechanisms and intercellular molecular determinants such as transmembrane and secreted molecules, many of which have also been implicated in neurodevelopmental disorders. However, many studies of synaptic targeting have focused on circuits in which neuronal processes target different lamina, such that cell-type-biased connectivity may be confounded with mechanisms of laminar specificity. In the cerebral cortex, each cortical layer contains cell bodies and processes from intermingled neuronal cell types, an arrangement that presents a challenge for the development of target-selective synapse formation. Here, we address progress and future directions in the study of cell-type-biased synaptic targeting in the cerebral cortex. We highlight challenges to identifying developmental mechanisms generating stereotyped patterns of intracortical connectivity, recent developments in uncovering the determinants of synaptic target selection during cortical synapse formation, and current gaps in the understanding of cortical synapse specificity.

IgSF11 homophilic adhesion proteins promote layer-specific synaptic assembly of the cortical interneuron subtype

The most prominent structural hallmark of the mammalian neocortical circuitry is the layer-based organization of specific cell types and synaptic inputs. Accordingly, cortical inhibitory interneurons (INs), which shape local network activity, exhibit subtype-specific laminar specificity of synaptic outputs. However, the underlying molecular mechanisms remain unknown. Here, we demonstrate that Immunoglobulin Superfamily member 11 (IgSF11) homophilic adhesion proteins are preferentially expressed in one of the most distinctive IN subtypes, namely, chandelier cells (ChCs) that specifically innervate axon initial segments of pyramidal neurons (PNs), and their synaptic laminar target. Loss-of-function experiments in either ChCs or postsynaptic cells revealed that IgSF11 is required for ChC synaptic development in the target layer. While overexpression of IgSF11 in ChCs enlarges ChC presynaptic boutons, expressing IgSF11 in nontarget layers induces ectopic ChC synapses. These findings provide evidence that synapse-promoting adhesion proteins, highly localized to synaptic partners, determine the layer-specific synaptic connectivity of the cortical IN subtype.

Cellular connectomes as arbiters of local circuit models in the cerebral cortex

With the availability of cellular-resolution connectivity maps, connectomes, from the mammalian nervous system, it is in question how informative such massive connectomic data can be for the distinction of local circuit models in the mammalian cerebral cortex. Here, we investigated whether cellular-resolution connectomic data can in principle allow model discrimination for local circuit modules in layer 4 of mouse primary somatosensory cortex. We used approximate Bayesian model selection based on a set of simple connectome statistics to compute the posterior probability over proposed models given a to-be-measured connectome. We find that the distinction of the investigated local cortical models is faithfully possible based on purely structural connectomic data with an accuracy of more than 90%, and that such distinction is stable against substantial errors in the connectome measurement. Furthermore, mapping a fraction of only 10% of the local connectome is sufficient for connectome-based model distinction under realistic experimental constraints. Together, these results show for a concrete local circuit example that connectomic data allows model selection in the cerebral cortex and define the experimental strategy for obtaining such connectomic data.

Sensing and processing whisker deflections in rodents

The classical view of sensory information mainly flowing into barrel cortex at layer IV, moving up for complex feature processing and lateral interactions in layers II and III, then down to layers V and VI for output and corticothalamic feedback is becoming increasingly undermined by new evidence. We review the neurophysiology of sensing and processing whisker deflections, emphasizing the general processing and organisational principles present along the entire sensory pathway—from the site of physical deflection at the whiskers to the encoding of deflections in the barrel cortex. Many of these principles support the classical view. However, we also highlight the growing number of exceptions to these general principles, which complexify the system and which investigators should be mindful of when interpreting their results. We identify gaps in the literature for experimentalists and theorists to investigate, not just to better understand whisker sensation but also to better understand sensory and cortical processing.

A network model of the barrel cortex combined with a differentiator detector reproduces features of the behavioral response to single-neuron stimulation

The stimulation of a single neuron in the rat somatosensory cortex can elicit a behavioral response. The probability of a behavioral response does not depend appreciably on the duration or intensity of a constant stimulation, whereas the response probability increases significantly upon injection of an irregular current. Biological mechanisms that can potentially suppress a constant input signal are present in the dynamics of both neurons and synapses and seem ideal candidates to explain these experimental findings. Here, we study a large network of integrate-and-fire neurons with several salient features of neuronal populations in the rat barrel cortex. The model includes cellular spike-frequency adaptation, experimentally constrained numbers and types of chemical synapses endowed with short-term plasticity, and gap junctions. Numerical simulations of this model indicate that cellular and synaptic adaptation mechanisms alone may not suffice to account for the experimental results if the local network activity is read out by an integrator. However, a circuit that approximates a differentiator can detect the single-cell stimulation with a reliability that barely depends on the length or intensity of the stimulus, but that increases when an irregular signal is used. This finding is in accordance with the experimental results obtained for the stimulation of a regularly-spiking excitatory cell.

It is widely assumed that only a large group of neurons can encode a stimulus or control behavior. This tenet of neuroscience has been challenged by experiments in which stimulating a single cortical neuron has had a measurable effect on an animal’s behavior. Recently, theoretical studies have explored how a single-neuron stimulation could be detected in a large recurrent network. However, these studies missed essential biological mechanisms of cortical networks and are unable to explain more recent experiments in the barrel cortex. Here, to describe the stimulated brain area, we propose and study a network model endowed with many important biological features of the barrel cortex. Importantly, we also investigate different readout mechanisms, i.e. ways in which the stimulation effects can propagate to other brain areas. We show that a readout network which tracks rapid variations in the local network activity is in agreement with the experiments. Our model demonstrates a possible mechanism for how the stimulation of a single neuron translates into a signal at the population level, which is taken as a proxy of the animal’s response. Our results illustrate the power of spiking neural networks to properly describe the effects of a single neuron’s activity.

Seasonal plasticity in the adult somatosensory cortex

To survive, animals need to adapt to changes of their ecosystem by changing their behaviors or even morphing the organs responsible for generating these behaviors. Small mammals have a high metabolic rate, and to balance energy deficits during winter they can decrease their brain and body size, a phenomenon termed Dehnel’s effect. We find specific seasonal changes in the brain of the smallest terrestrial mammal, the Etruscan shrew. Their cortex shrinks in the winter, with layer-width and neuron number reduction in the energetically expensive somatosensory cortical layer 4. Imaging of neural activity revealed reduced suppressive responses to whisker touch during winter, indicating that such cortical adaptation may have synergistic functional and behavioral effects in addition to direct metabolic benefits.

Seasonal cycles govern life on earth, from setting the time for the mating season to influencing migrations and governing physiological conditions like hibernation. The effect of such changing conditions on behavior is well-appreciated, but their impact on the brain remains virtually unknown. We investigate long-term seasonal changes in the mammalian brain, known as Dehnel’s effect, where animals exhibit plasticity in body and brain sizes to counter metabolic demands in winter. We find large seasonal variation in cellular architecture and neuronal activity in the smallest terrestrial mammal, the Etruscan shrew, Suncus etruscus. Their brain, and specifically their neocortex, shrinks in winter. Shrews are tactile hunters, and information from whiskers first reaches the somatosensory cortex layer 4, which exhibits a reduced width (−28%) in winter. Layer 4 width (+29%) and neuron number (+42%) increase the following summer. Activity patterns in the somatosensory cortex show a prominent reduction of touch-suppressed neurons in layer 4 (−55%), the most metabolically active layer. Loss of inhibitory gating occurs with a reduction in parvalbumin-positive interneurons, one of the most active neuronal subtypes and the main regulators of inhibition in layer 4. Thus, a reduction in neurons in layer 4 and particularly parvalbumin-positive interneurons may incur direct metabolic benefits. However, changes in cortical balance can also affect the threshold for detecting sensory stimuli and impact prey choice, as observed in wild shrews. Thus, seasonal neural adaptation can offer synergistic metabolic and behavioral benefits to the organism and offer insights on how neural systems show adaptive plasticity in response to ecological demands.

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.

Myelination of parvalbumin interneurons shapes the function of cortical sensory inhibitory circuits

Myelination of projection neurons by oligodendrocytes is key to optimize action potential conduction over long distances. However, a large fraction of myelin enwraps the axons of parvalbumin-positive fast-spiking interneurons (FSI), exclusively involved in local cortical circuits. Whether FSI myelination contributes to the fine‐tuning of intracortical networks is unknown. Here we demonstrate that FSI myelination is required for the establishment and maintenance of the powerful FSI-mediated feedforward inhibition of cortical sensory circuits. The disruption of GABAergic synaptic signaling of oligodendrocyte precursor cells prior to myelination onset resulted in severe FSI myelination defects characterized by longer internodes and nodes, aberrant myelination of branch points and proximal axon malformation. Consequently, high-frequency FSI discharges as well as FSI-dependent postsynaptic latencies and strengths of excitatory neurons were reduced. These dysfunctions generated a strong excitation-inhibition imbalance that correlated with whisker-dependent texture discrimination impairments. FSI myelination is therefore critical for the function of mature cortical inhibitory circuits.

Myelination optimizes conduction speed of excitatory neurons. However, whether myelination of interneurons (INs) refines cortical networks is unclear. Here, the authors show that INs myelination shapes feedforward inhibition of mouse cortical sensory circuits and impacts whisker-mediated behaviour.

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.

Biphasic Impact of Prenatal Inflammation and Macrophage Depletion on the Wiring of Neocortical Inhibitory Circuits

The etiology of neurodevelopmental disorders is linked to defects in parvalbumin (PV)-expressing cortical interneurons and to prenatal immune challenges. Mouse models of maternal immune activation (MIA) and microglia deficits increase the postnatal density of PV interneurons, raising the question of their functional integration. Here, we show that MIA and embryonic depletion of macrophages including microglia have a two-step impact on PV interneurons wiring onto their excitatory target neurons in the barrel cortex. In adults, both challenges reduced the inhibitory drive from PV interneurons, as reported in neurodevelopmental disorders. In juveniles, however, we found an increased density of PV neurons, an enhanced strength of unitary connections onto excitatory cells, and an aberrant horizontal inhibition with a reduced lateral propagation of sensory inputs in vivo. Our results provide a comprehensive framework for understanding the impact of prenatal immune challenges onto the developmental trajectory of inhibitory circuits that leads to pathological brain wiring.

Effects of Cortical Cooling on Activity Across Layers of the Rat Barrel Cortex

Moderate cortical cooling is known to suppress slow oscillations and to evoke persistent cortical activity. However, the cooling-induced changes in electrical activity across cortical layers remain largely unknown. Here, we performed multi-channel local field potential (LFP) and multi-unit activity (MUA) recordings with linear silicone probes through the layers of single cortical barrel columns in urethane-anesthetized rats under normothermia (38°C) and during local cortical surface cooling (30°C). During cortically generated slow oscillations, moderate cortical cooling decreased delta wave amplitude, delta-wave occurrence, the duration of silent states, and delta wave-locked MUA synchronization. Moderate cortical cooling increased total time spent in the active state and decreased total time spent in the silent state. Cooling-evoked changes in the MUA firing rate in cortical layer 5 (L5) varied from increase to decrease across animals, and the polarity of changes in L5 MUA correlated with changes in total time spent in the active state. The decrease in temperature reduced MUA firing rates in all other cortical layers. Sensory-evoked MUA responses also decreased during cooling through all cortical layers. The cooling-dependent slowdown was detected at the fast time-scale with a decreased frequency of sensory-evoked high-frequency oscillations (HFO). Thus, moderate cortical cooling suppresses slow oscillations and desynchronizes neuronal activity through all cortical layers, and is associated with reduced firing across all cortical layers except L5, where cooling induces variable and non-consistent changes in neuronal firing, which are common features of the transition from slow-wave synchronization to desynchronized activity in the barrel cortex.

Density Visualization Pipeline: A Tool for Cellular and Network Density Visualization and Analysis

Neuron classification is an important component in analyzing network structure and quantifying the effect of neuron topology on signal processing. Current quantification and classification approaches rely on morphology projection onto lower-dimensional spaces. In this paper a 3D visualization and quantification tool is presented. The Density Visualization Pipeline (DVP) computes, visualizes and quantifies the density distribution, i.e., the "mass" of interneurons. We use the DVP to characterize and classify a set of GABAergic interneurons. Classification of GABAergic interneurons is of crucial importance to understand on the one hand their various functions and on the other hand their ubiquitous appearance in the neocortex. 3D density map visualization and projection to the one-dimensional x, y, z subspaces show a clear distinction between the studied cells, based on these metrics. The DVP can be coupled to computational studies of the behavior of neurons and networks, in which network topology information is derived from DVP information. The DVP reads common neuromorphological file formats, e.g., Neurolucida XML files, NeuroMorpho.org SWC files and plain ASCII files. Full 3D visualization and projections of the density to 1D and 2D manifolds are supported by the DVP. All routines are embedded within the visual programming IDE VRL-Studio for Java which allows the definition and rapid modification of analysis workflows.

Gap Junctions Interconnect Different Subtypes of Parvalbumin-Positive Interneurons in Barrels and Septa with Connectivity Unique to Each Subtype

Parvalbumin (PV)-positive interneurons form dendritic gap junctions with one another, but the connectivity among gap junction-coupled dendrites remains uninvestigated in most neocortical areas. We visualized gap junctions in layer 4 of the mouse barrel cortex and examined their structural details. PV neurons were divided into 4 types based on the location of soma and dendrites within or outside barrels. Type 1 neurons that had soma and all dendrites inside a barrel, considered most specific to single vibrissa-derived signals, unexpectedly formed gap junctions only with other types but never with each other. Type 2 neurons inside a barrel elongated dendrites outward, forming gap junctions within a column that contained the home barrel. Type 3 neurons located outside barrels established connections with all types including Type 4 neurons that were confined inside the inter-barrel septa. The majority (33/38, 86.8%) of dendritic gap junctions were within 75 μm from at least 1 of 2 paired somata. All types received vesicular glutamate transporter 2-positive axon terminals preferentially on somata and proximal dendrites, indicating the involvement of all types in thalamocortical feedforward regulation in which proximal gap junctions may also participate. These structural organizations provide a new morphological basis for regulatory mechanisms in barrel cortex.

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.

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

Anatomical Correlates of Local, Translaminar, and Transcolumnar Inhibition by Layer 6 GABAergic Interneurons in Somatosensory Cortex

In the vibrissal area of rodent somatosensory cortex, information on whisker stimulation is processed by neuronal networks in a corresponding cortical column. To understand how sensory stimuli are represented in a column, it is essential to identify cell types constituting these networks. Layer 6 (L6) comprises 25% of all neurons in a column. In rats, 430 of these are inhibitory interneurons (INs). Little is known about the axon projection of L6 INs with reference to columnar and laminar organization. We quantified axonal projections of L6 INs (n = 68) with reference to columns and layers in somatosensory cortex of rats. We found distinct projection types differentially targeting layers of a cortical column. The majority of L6 INs did not show a column-specific innervation, densely projecting to neighboring columns as well as the home column. However, a small fraction targeted granular and supragranular layers, where axon projections were confined to the home column. We also quantified putative innervation of pyramidal cells as a functional correlate of axonal distribution. Electrophysiological properties were not correlated to axon projection. The quantitative data on axonal projections and electrophysiological properties of L6 INs can guide future studies investigating cortical processing of sensory information at the single cell level.

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.

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.

Towards Differential Connectomics with NeuroVIISAS

The comparison of connectomes is an essential step to identify changes in structural and functional neuronal networks. However, the connectomes themselves as well as the comparisons of connectomes could be manifold. In most applications, comparisons of connectomes are applied to specific sets of data. In many studies collections of scripts are applied optimized for certain species (non-generic approaches) or diseases (control versus disease group connectomes). These collections of scripts have a limited functionality which do not support functional and topographic mappings of connectomes (hemispherical asymmetries, peripheral nervous system). The platform-independent and generic neuroVIISAS framework is built to circumvent limitations that come with variants of nomenclatures, connectivity lists and connectional hierarchies as well as restrictions to structural connectome analyses. A new analytical module is introduced into the framework to compare different types of connectomes and different representations of the same connectome within a unique software environment. As an example a differential analysis of the partial connectome of the laboratory rat that is based on virus tract tracing with the same regions of non-virus tract tracing has been performed. A relatively large connectional coherence between the two different techniques was found. However, some detected connections are described by virus tract-tracing only.

Morphological and Functional Characterization of Non-fast-Spiking GABAergic Interneurons in Layer 4 Microcircuitry of Rat Barrel Cortex

GABAergic interneurons are notorious for their heterogeneity, despite constituting a small fraction of the neuronal population in the neocortex. Classification of interneurons is crucial for understanding their widespread cortical functions as they provide a complex and dynamic network, balancing excitation and inhibition. Here, we investigated different types of non-fast-spiking (nFS) interneurons in Layer 4 (L4) of rat barrel cortex using whole-cell patch-clamp recordings with biocytin-filling. Based on a quantitative analysis on a combination of morphological and electrophysiological parameters, we identified 5 distinct types of L4 nFS interneurons: 1) trans-columnar projecting interneurons, 2) locally projecting non-Martinotti-like interneurons, 3) supra-granular projecting Martinotti-like interneurons, 4) intra-columnar projecting VIP-like interneurons, and 5) locally projecting neurogliaform-like interneurons. Trans-columnar projecting interneurons are one of the most striking interneuron types, which have not been described so far in Layer 4. They feature extensive axonal collateralization not only in their home barrel but also in adjacent barrels. Furthermore, we identified that most of the L4 nFS interneurons express somatostatin, while few are positive for the transcription factor Prox1. The morphological and electrophysiological characterization of different L4 nFS interneuron types presented here provides insights into their synaptic connectivity and functional role in cortical information processing.

Distribution Patterns of Three Molecularly Defined Classes of GABAergic Neurons Across Columnar Compartments in Mouse Barrel Cortex

The mouse somatosensory cortex is an excellent model to study the structural basis of cortical information processing, since it possesses anatomically recognizable domains that receive different thalamic inputs, which indicates spatial segregation of different processing tasks. In this work we examined three genetically labeled, non-overlapping subpopulations of GABAergic neurons: parvalbumin- (PV+), somatostatin- (SST+), and vasoactive intestinal polypeptide-expressing (VIP+) cells. Each of these subpopulations displayed a unique cellular distribution pattern across layers. In terms of columnar localization, the distribution of these three populations was not quantitatively different between barrel-related versus septal compartments in most layers. However, in layer IV (LIV), SST+, and VIP+, but not PV+ neurons preferred the septal compartment over barrels. The examined cell types showed a tendency toward differential distribution in supragranular and infragranular barrel-related versus septal compartments, too. Our data suggests that the location of GABAergic neuron cell bodies correlates with the spatial pattern of cortical domains receiving different kinds of thalamic input. Thus, at least in LIV, lemniscal inputs present a close spatial relation preferentially to PV+ cells whereas paralemniscal inputs target compartments in which more SST+ and VIP+ cells are localized. Our findings suggest pathway-specific roles for neocortical GABAergic neurons.

Inhibitory Connectivity Dominates the Fan Cell Network in Layer II of Lateral Entorhinal Cortex

Fan cells in layer II of the lateral entorhinal cortex (LEC) form a main component of the projection to the dentate gyrus, CA3 and CA2 of the hippocampal formation. This projection has a counterpart originating from stellate cells in layer II of the medial entorhinal cortex (MEC). Available evidence suggests that the two pathways carry different information, exemplified by a difference in spatial tuning of cells in LEC and MEC. The grid cell, a prominent position-modulated cell type present in MEC, has been postulated to derive its characteristic hexagonal firing pattern from dominant disynaptic inhibitory connections between hippocampal-projecting stellate cells. Given that grid cells have not been described in LEC, we aim to describe the local synaptic connectivity of fan cells, to explore whether the network architecture is similar to that of the MEC stellate cell. Using a combination of in vitro multicell electrophysiological and optogenetic approaches in acute slices from rodents of either sex, we show that excitatory connectivity between fan cells is very sparse. Fan cells connect preferentially with two distinct types of inhibitory interneurons, suggesting disynaptic inhibitory coupling as the main form of communication among fan cells. These principles are similar to those reported for stellate cells in MEC, indicating an overall comparable local circuit architecture of the main hippocampal-projecting cell types in the lateral and medial entorhinal cortex.SIGNIFICANCE STATEMENT Our data provide the first description of the synaptic microcircuit of hippocampal-projecting layer II cells in the lateral entorhinal cortex. We show that these cells make infrequent monosynaptic connections with each other, and that they preferentially communicate through a disynaptic inhibitory network. This is similar to the microcircuit of hippocampal-projecting stellate cells in layer II of the medial entorhinal cortex, but dissimilar to the connectivity observed in layer 2 of neocortex. In medial entorhinal cortex, the observed network structure has been proposed to underlie the firing pattern of grid cells. This opens the possibility that layer II cells in lateral entorhinal cortex exhibit regular firing patterns in an unexplored domain.

Criteria on Balance, Stability, and Excitability in Cortical Networks for Constraining Computational Models

During ongoing and Up state activity, cortical circuits manifest a set of dynamical features that are conserved across these states. The present work systematizes these phenomena by three notions: excitability, the ability to sustain activity without external input; balance, precise coordination of excitatory and inhibitory neuronal inputs; and stability, maintenance of activity at a steady level. Slice preparations exhibiting Up states demonstrate that balanced activity can be maintained by small local circuits. While computational models of cortical circuits have included different combinations of excitability, balance, and stability, they have done so without a systematic quantitative comparison with experimental data. Our study provides quantitative criteria for this purpose, by analyzing in-vitro and in-vivo neuronal activity and characterizing the dynamics on the neuronal and population levels. The criteria are defined with a tolerance that allows for differences between experiments, yet are sufficient to capture commonalities between persistently depolarized cortical network states and to help validate computational models of cortex. As test cases for the derived set of criteria, we analyze three widely used models of cortical circuits and find that each model possesses some of the experimentally observed features, but none satisfies all criteria simultaneously, showing that the criteria are able to identify weak spots in computational models. The criteria described here form a starting point for the systematic validation of cortical neuronal network models, which will help improve the reliability of future models, and render them better building blocks for larger models of the brain.

Adenosine Differentially Modulates Synaptic Transmission of Excitatory and Inhibitory Microcircuits in Layer 4 of Rat Barrel Cortex

Adenosine is considered to be a key regulator of sleep homeostasis by promoting slow-wave sleep through inhibition of the brain's arousal centers. However, little is known about the effect of adenosine on neuronal network activity at the cellular level in the neocortex. Here, we show that adenosine differentially modulates synaptic transmission between different types of neurons in cortical layer 4 (L4) through activation of pre- and/or postsynaptically located adenosine A1 receptors. In recurrent excitatory connections between L4 spiny neurons, adenosine suppresses synaptic transmission through activation of both pre- and postsynaptic A1 receptors. In reciprocal excitatory and inhibitory connections between L4 spiny neurons and interneurons, adenosine strongly suppresses excitatory transmission via activating presynaptic A1 receptors but only slightly suppresses inhibitory transmission via activating postsynaptic A1 receptors. Adenosine has no effect on inhibitory transmission between L4 interneurons. The effect of adenosine is concentration dependent and first visible at a concentration of 1 μM. The effect of adenosine is blocked by the specific A1 receptor antagonist, 8-cyclopentyltheophylline or the nonspecific adenosine receptor antagonist, caffeine. By differentially affecting excitatory and inhibitory synaptic transmission, adenosine changes the excitation-inhibition balance and causes an overall shift to lower excitability in L4 primary somatosensory (barrel) cortical microcircuits.

SynEM, automated synapse detection for connectomics

Nerve tissue contains a high density of chemical synapses, about 1 per µm3 in the mammalian cerebral cortex. Thus, even for small blocks of nerve tissue, dense connectomic mapping requires the identification of millions to billions of synapses. While the focus of connectomic data analysis has been on neurite reconstruction, synapse detection becomes limiting when datasets grow in size and dense mapping is required. Here, we report SynEM, a method for automated detection of synapses from conventionally en-bloc stained 3D electron microscopy image stacks. The approach is based on a segmentation of the image data and focuses on classifying borders between neuronal processes as synaptic or non-synaptic. SynEM yields 97% precision and recall in binary cortical connectomes with no user interaction. It scales to large volumes of cortical neuropil, plausibly even whole-brain datasets. SynEM removes the burden of manual synapse annotation for large densely mapped connectomes.

Inhibitory interneurons and their circuit motifs in the many layers of the barrel cortex

Recent years have seen substantial progress in studying the structural and functional properties of GABAergic interneurons and their roles in the neuronal networks of barrel cortex. Although GABAergic interneurons represent only about 12% of the total number of neocortical neurons, they are extremely diverse with respect to their structural and functional properties. It has become clear that barrel cortex interneurons not only serve the maintenance of an appropriate excitation/inhibition balance but also are directly involved in sensory processing. In this review we present different interneuron types and their axonal projection pattern framework in the context of the laminar and columnar organization of the barrel cortex. The main focus is here on the most prominent interneuron types, i.e. basket cells, chandelier cells, Martinotti cells, bipolar/bitufted cells and neurogliaform cells, but interneurons with more unusual axonal domains will also be mentioned. We describe their developmental origin, their classification with respect to molecular, morphological and intrinsic membrane and synaptic properties. Most importantly, we will highlight the most prominent circuit motifs these interneurons are involved in and in which way they serve feed-forward inhibition, feedback inhibition and disinhibition. Finally, this will be put into context to their functional roles in sensory signal perception and processing in the whisker system and beyond.

The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks

Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuation-driven dynamics despite structural heterogeneity in cortical circuits.

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Structural heterogeneity threatens the dynamic balance of excitation and inhibition

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Reconstruction of cortical networks reveals significant structural heterogeneity

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Spike-frequency adaptation can act locally to facilitate global balance

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Inhibitory homeostatic plasticity can compensate for structural imbalance

Cortical Neural Computation by Discrete Results Hypothesis

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation.

Robustness of sensory-evoked excitation is increased by inhibitory inputs to distal apical tuft dendrites

Cortical inhibitory interneurons (INs) are subdivided into a variety of morphologically and functionally specialized cell types. How the respective specific properties translate into mechanisms that regulate sensory-evoked responses of pyramidal neurons (PNs) remains unknown. Here, we investigated how INs located in cortical layer 1 (L1) of rat barrel cortex affect whisker-evoked responses of L2 PNs. To do so we combined in vivo electrophysiology and morphological reconstructions with computational modeling. We show that whisker-evoked membrane depolarization in L2 PNs arises from highly specialized spatiotemporal synaptic input patterns. Temporally L1 INs and L2-5 PNs provide near synchronous synaptic input. Spatially synaptic contacts from L1 INs target distal apical tuft dendrites, whereas PNs primarily innervate basal and proximal apical dendrites. Simulations of such constrained synaptic input patterns predicted that inactivation of L1 INs increases trial-to-trial variability of whisker-evoked responses in L2 PNs. The in silico predictions were confirmed in vivo by L1-specific pharmacological manipulations. We present a mechanism-consistent with the theory of distal dendritic shunting-that can regulate the robustness of sensory-evoked responses in PNs without affecting response amplitude or latency.

Electrophysiological and morphological characterization of neuronal microcircuits in acute brain slices using paired patch-clamp recordings

The combination of patch clamp recordings from two (or more) synaptically coupled neurons (paired recordings) in acute brain slice preparations with simultaneous intracellular biocytin filling allows a correlated analysis of their structural and functional properties. With this method it is possible to identify and characterize both pre- and postsynaptic neurons by their morphology and electrophysiological response pattern. Paired recordings allow studying the connectivity patterns between these neurons as well as the properties of both chemical and electrical synaptic transmission. Here, we give a step-by-step description of the procedures required to obtain reliable paired recordings together with an optimal recovery of the neuron morphology. We will describe how pairs of neurons connected via chemical synapses or gap junctions are identified in brain slice preparations. We will outline how neurons are reconstructed to obtain their 3D morphology of the dendritic and axonal domain and how synaptic contacts are identified and localized. We will also discuss the caveats and limitations of the paired recording technique, in particular those associated with dendritic and axonal truncations during the preparation of brain slices because these strongly affect connectivity estimates. However, because of the versatility of the paired recording approach it will remain a valuable tool in characterizing different aspects of synaptic transmission at identified neuronal microcircuits in the brain.

Generation of dense statistical connectomes from sparse morphological data

Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and subcellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results.