Laminar analysis of excitatory local circuits in vibrissal motor and sensory cortical areas

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.

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.

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.

The Sensorimotor Basis of Whisker-Guided Anteroposterior Object Localization in Head-Fixed Mice

Active tactile perception combines directed motion with sensory signals to generate mental representations of objects in space. Competing models exist for how mice use these signals to determine the precise location of objects along their face. We tested six of these models using behavioral manipulations and statistical learning in head-fixed mice. Trained mice used a whisker to locate a pole in a continuous range of locations along the anteroposterior axis. Mice discriminated locations to ≤0.5 mm (<2°) resolution. Their motor program was noisy, adaptive to touch, and directed to the rewarded range. This exploration produced several sets of sensorimotor features that could discriminate location. Integration of two features, touch count and whisking midpoint at touch, was the simplest model that explained behavior best. These results show how mice locate objects at hyperacute resolution using a learned motor strategy and minimal set of mentally accessible sensorimotor features.

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.

Whisker-Mediated Touch System in Rodents: From Neuron to Behavior

A key question in systems neuroscience is to identify how sensory stimuli are represented in neuronal activity, and how the activity of sensory neurons in turn is “read out” by downstream neurons and give rise to behavior. The choice of a proper model system to address these questions, is therefore a crucial step. Over the past decade, the increasingly powerful array of experimental approaches that has become available in non-primate models (e.g., optogenetics and two-photon imaging) has spurred a renewed interest for the use of rodent models in systems neuroscience research. Here, I introduce the rodent whisker-mediated touch system as a structurally well-established and well-organized model system which, despite its simplicity, gives rise to complex behaviors. This system serves as a behaviorally efficient model system; known as nocturnal animals, along with their olfaction, rodents rely on their whisker-mediated touch system to collect information about their surrounding environment. Moreover, this system represents a well-studied circuitry with a somatotopic organization. At every stage of processing, one can identify anatomical and functional topographic maps of whiskers; “barrelettes” in the brainstem nuclei, “barreloids” in the sensory thalamus, and “barrels” in the cortex. This article provides a brief review on the basic anatomy and function of the whisker system in rodents.

Reduced sensory-evoked structural plasticity in the aging barrel cortex

Impairments in synaptic connectivity have been linked to cognitive deficits in age-related neurodegenerative disorders and healthy aging. However, the anatomical and structural bases of these impairments have not been identified yet. A hallmark of neural plasticity in young adults is short-term synaptic rearrangement, yet aged animals already display higher synaptic turnover rates at the baseline. Using two-photon excitation (2PE) microscopy, we explored if this elevated turnover alters the aged brain's response to plasticity. Following a sensory-evoked plasticity protocol involving whisker stimulation, aged mice display reduced spine dynamics (gain, loss, and turnover), decreased spine clustering, and lower spine stability when compared to young adult mice. These results suggest a deficiency of the cortical neurons of aged mice to structurally incorporate new sensory experiences, in the form of clustered, long-lasting synapses, into already existing cortical circuits. This research provides the first evidence linking experience-dependent plasticity with in vivo spine dynamics in the aged brain and supports a model of both reduced synaptic plasticity and reduced synaptic tenacity in the aged somatosensory system.

State-aware detection of sensory stimuli in the cortex of the awake mouse

Cortical responses to sensory inputs vary across repeated presentations of identical stimuli, but how this trial-to-trial variability impacts detection of sensory inputs is not fully understood. Using multi-channel local field potential (LFP) recordings in primary somatosensory cortex (S1) of the awake mouse, we optimized a data-driven cortical state classifier to predict single-trial sensory-evoked responses, based on features of the spontaneous, ongoing LFP recorded across cortical layers. Our findings show that, by utilizing an ongoing prediction of the sensory response generated by this state classifier, an ideal observer improves overall detection accuracy and generates robust detection of sensory inputs across various states of ongoing cortical activity in the awake brain, which could have implications for variability in the performance of detection tasks across brain states.

Establishing the link between neural activity and behavior is a central goal of neuroscience. One context in which to examine this link is in a sensory detection task, in which an animal is trained to report the presence of a barely perceptible sensory stimulus. In such tasks, both sensory responses in the brain and behavioral responses are highly variable. A simple hypothesis, originating in signal detection theory, is that perceived inputs generate neural activity that cross some threshold for detection. According to this hypothesis, sensory response variability would predict behavioral variability, but previous studies have not born out this prediction. Further complicating the picture, sensory response variability is partially dependent on the ongoing state of cortical activity, and we wondered whether this could resolve the mismatch between response variability and behavioral variability. Here, we use a computational approach to study an adaptive observer that utilizes an ongoing prediction of sensory responsiveness to detect sensory inputs. This observer has higher overall accuracy than the standard ideal observer. Moreover, because of the adaptation, the observer breaks the direct link between neural and behavioral variability, which could resolve discrepancies arising in past studies. We suggest new experiments to test our theory.

Posterior thalamic nucleus axon terminals have different structure and functional impact in the motor and somatosensory vibrissal cortices

Rodents extract information about nearby objects from the movement of their whiskers through dynamic computations that are carried out by a network of forebrain structures that includes the thalamus and the primary sensory (S1BF) and motor (M1wk) whisker cortices. The posterior nucleus (Po), a higher order thalamic nucleus, is a key hub of this network, receiving cortical and brainstem sensory inputs and innervating both motor and sensory whisker-related cortical areas. In a recent study in rats, we showed that Po inputs differently impact sensory processing in S1BF and M1wk. Here, in C57BL/6 mice, we measured Po synaptic bouton layer distribution and size, compared cortical unit response latencies to "in vivo" Po activation, and pharmacologically examined the glutamatergic receptor mechanisms involved. We found that, in S1BF, a large majority (56%) of Po axon varicosities are located in layer (L)5a and only 12% in L2-L4, whereas in M1wk this proportion is inverted to 18% and 55%, respectively. Light and electron microscopic measurements showed that Po synaptic boutons in M1wk layers 3-4 are significantly larger (~ 50%) than those in S1BF L5a. Electrical Po stimulation elicits different area-specific response patterns. In S1BF, responses show weak or no facilitation, and involve both ionotropic and metabotropic glutamate receptors, whereas in M1wk, unit responses exhibit facilitation to repetitive stimulation and involve ionotropic NMDA glutamate receptors. Because of the different laminar distribution of axon terminals, synaptic bouton size and receptor mechanisms, the impact of Po signals on M1wk and S1BF, although simultaneous, is likely to be markedly different.

A Sensorimotor Pathway via Higher-Order Thalamus

We now know that sensory processing in cortex occurs not only via direct communication between primary to secondary areas, but also via their parallel cortico-thalamo-cortical (i.e., trans-thalamic) pathways. Both corticocortical and trans-thalamic pathways mainly signal through glutamatergic class 1 (driver) synapses, which have robust and efficient synaptic dynamics suited for the transfer of information such as receptive field properties, suggesting the importance of class 1 synapses in feedforward, hierarchical processing. However, such a parallel arrangement has only been identified in sensory cortical areas: visual, somatosensory, and auditory. To test the generality of trans-thalamic pathways, we sought to establish its presence beyond purely sensory cortices to determine whether there is a trans-thalamic pathway parallel to the established primary somatosensory (S1) to primary motor (M1) pathway. We used trans-synaptic viral tracing, optogenetics in slice preparations, and bouton size analysis in the mouse (both sexes) to document that a circuit exists from layer 5 of S1 through the posterior medial nucleus of the thalamus to M1 with glutamatergic class 1 properties. This represents a hitherto unknown, robust sensorimotor linkage and suggests that the arrangement of parallel direct and trans-thalamic corticocortical circuits may be present as a general feature of cortical functioning.SIGNIFICANCE STATEMENT During sensory processing, feedforward pathways carry information such as receptive field properties via glutamatergic class 1 synapses, which have robust and efficient synaptic dynamics. As expected, class 1 synapses subserve the feedforward projection from primary to secondary sensory cortex, but also a route through specific higher-order thalamic nuclei, creating a parallel feedforward trans-thalamic pathway. We now extend the concept of cortical areas being connected via parallel, direct, and trans-thalamic circuits from purely sensory cortices to a sensorimotor cortical circuit (i.e., primary sensory cortex to primary motor cortex). This suggests a generalized arrangement for corticocortical communication.

Superficial Layers Suppress the Deep Layers to Fine-tune Cortical Coding

The descending microcircuit from layer 2/3 (L2/3) to layer 5 (L5) is one of the strongest excitatory pathways in the cortex, presumably forming a core component of its feedforward hierarchy. To date, however, no experiments have selectively tested the impact of L2/3 activity on L5 during active sensation. We used optogenetic, cell-type-specific manipulation of L2/3 neurons in the barrel cortex of actively sensing mice (of either sex) to elucidate the significance of this pathway to sensory coding in L5. Contrary to standard models, activating L2/3 predominantly suppressed spontaneous activity in L5, whereas deactivating L2/3 mainly facilitated touch responses in L5. Somatostatin interneurons are likely important to this suppression because their optogenetic deactivation significantly altered the functional impact of L2/3 onto L5. The net effect of L2/3 was to enhance the stimulus selectivity and expand the range of L5 output. These data imply that the core cortical pathway increases the selectivity and expands the range of cortical output through feedforward inhibition.SIGNIFICANCE STATEMENT The primary sensory cortex contains six distinct layers that interact to form the basis of our perception. While rudimentary patterns of connectivity between the layers have been outlined quite extensively in vitro, functional relationships in vivo, particularly during active sensation, remain poorly understood. We used cell-type-specific optogenetics to test the functional relationship between layer 2/3 and layer 5. Surprisingly, we discovered that L2/3 primarily suppresses cortical output from L5. The recruitment of somatostatin-positive interneurons is likely fundamental to this relationship. The net effect of this translaminar suppression is to enhance the selectivity and expand the range of receptive fields, therefore potentially sharpening the perception of space.

Topographic precision in sensory and motor corticostriatal projections varies across cell type and cortical area

The striatum shows general topographic organization and regional differences in behavioral functions. How corticostriatal topography differs across cortical areas and cell types to support these distinct functions is unclear. This study contrasted corticostriatal projections from two layer 5 cell types, intratelencephalic (IT-type) and pyramidal tract (PT-type) neurons, using viral vectors expressing fluorescent reporters in Cre-driver mice. Corticostriatal projections from sensory and motor cortex are somatotopic, with a decreasing topographic specificity as injection sites move from sensory to motor and frontal areas. Topographic organization differs between IT-type and PT-type neurons, including injections in the same site, with IT-type neurons having higher topographic stereotypy than PT-type neurons. Furthermore, IT-type projections from interconnected cortical areas have stronger correlations in corticostriatal targeting than PT-type projections do. As predicted by a longstanding model, corticostriatal projections of interconnected cortical areas form parallel circuits in the basal ganglia.

Generic dynamic causal modelling: An illustrative application to Parkinson's disease

We present a technical development in the dynamic causal modelling of electrophysiological responses that combines qualitatively different neural mass models within a single network. This affords the option to couple various cortical and subcortical nodes that differ in their form and dynamics. Moreover, it enables users to implement new neural mass models in a straightforward and standardized way. This generic framework hence supports flexibility and facilitates the exploration of increasingly plausible models. We illustrate this by coupling a basal ganglia-thalamus model to a (previously validated) cortical model developed specifically for motor cortex. The ensuing DCM is used to infer pathways that contribute to the suppression of beta oscillations induced by dopaminergic medication in patients with Parkinson's disease. Experimental recordings were obtained from deep brain stimulation electrodes (implanted in the subthalamic nucleus) and simultaneous magnetoencephalography. In line with previous studies, our results indicate a reduction of synaptic efficacy within the circuit between the subthalamic nucleus and external pallidum, as well as reduced efficacy in connections of the hyperdirect and indirect pathway leading to this circuit. This work forms the foundation for a range of modelling studies of the synaptic mechanisms (and pathophysiology) underlying event-related potentials and cross-spectral densities.

Specialized Subpopulations of Deep-Layer Pyramidal Neurons in the Neocortex: Bridging Cellular Properties to Functional Consequences

Neocortical pyramidal neurons with somata in layers 5 and 6 are among the most visually striking and enigmatic neurons in the brain. These deep-layer pyramidal neurons (DLPNs) integrate a plethora of cortical and extracortical synaptic inputs along their impressive dendritic arbors. The pattern of cortical output to both local and long-distance targets is sculpted by the unique physiological properties of specific DLPN subpopulations. Here we revisit two broad DLPN subpopulations: those that send their axons within the telencephalon (intratelencephalic neurons) and those that project to additional target areas outside the telencephalon (extratelencephalic neurons). While neuroscientists across many subdisciplines have characterized the intrinsic and synaptic physiological properties of DLPN subpopulations, our increasing ability to selectively target and manipulate these output neuron subtypes advances our understanding of their distinct functional contributions. This Viewpoints article summarizes our current knowledge about DLPNs and highlights recent work elucidating the functional differences between DLPN subpopulations.

Electrically Controlled Neurochemical Release from Dual-Layer Conducting Polymer Films for Precise Modulation of Neural Network Activity in Rat Barrel Cortex

Implantable microelectrode arrays (MEAs) are important tools for investigating functional neural circuits and treating neurological diseases. Precise modulation of neural activity may be achieved by controlled delivery of neurochemicals directly from coatings on MEA electrode sites. In this study, a novel dual-layer conductive polymer/acid functionalized carbon nanotube (fCNT) microelectrode coating is developed to better facilitate the loading and controlled delivery of the neurochemical 6,7-dinitroquinoxaline-2,3-dione (DNQX). The base layer coating is consisted of poly(3,4-ethylenedioxythiophene/fCNT and the top layer is consisted of polypyrrole/fCNT/DNQX. The dual-layer coating is capable of both loading and electrically releasing DNQX and the release dynamic is characterized with fluorescence microscopy and mathematical modeling. In vivo DNQX release is demonstrated in rat somatosensory cortex. Sensory-evoked neural activity is immediately (<1s) and locally (<446 µm) suppressed by electrically triggered DNQX release. Furthermore, a single DNQX-loaded, dual-layer coating is capable of inducing effective neural inhibition for at least 26 times without observable degradation in efficacy. Incorporation of the novel drug releasing coating onto individual MEA electrodes offers many advantages over alternative methods by increasing spatial-temporal precision and improving drug selection flexibility without increasing the device's size.

Studies of cortical connectivity using optical circuit mapping methods

An important consideration when probing the function of any neuron is to uncover the source of synaptic input onto the cell, its intrinsic physiology and efferent targets. Over the years, electrophysiological approaches have generated considerable insight into these properties in a variety of cortical neuronal subtypes and circuits. However, as researchers explore neuronal function in greater detail, they are increasingly turning to optical techniques to bridge the gap between local network interactions and behaviour. The application of optical methods has increased dramatically over the past decade, spurred on by the optogenetic revolution. In this review, we provide an account of recent innovations, providing researchers with a primer detailing circuit mapping strategies in the cerebral cortex. We will focus on technical aspects of performing neurotransmitter uncaging and channelrhodopsin-assisted circuit mapping, with the aim of identifying common pitfalls that can negatively influence the collection of reliable data.

Connectivity motifs of inhibitory neurons in the mouse Auditory Cortex

Connectivity determines the function of neural circuits and it is the gateway to behavioral output. The emergent properties of the Auditory Cortex (ACx) have been difficult to unravel partly due to our assumption that it is organized similarly to other sensory areas. But detailed investigations of its functional connectivity have begun to reveal significant differences from other cortical areas that perform different functions. Using Laser Scanning Photostimulation we previously discovered unique circuit features in the ACx. Specifically, we found that the functional asymmetry of the ACx (tonotopy and isofrequency axes) is reflected in the local circuitry of excitatory inputs to Layer 3 pyramidal neurons. In the present study we extend the functional wiring diagram of the ACx with an investigation of the connectivity patterns of inhibitory subclasses. We compared excitatory input to parvalbumin (PV) and somatostatin (SOM)-expressing interneurons and found distinct circuit-motifs between and within these subpopulations. Moreover, these connectivity motifs emerged as intrinsic differences between the left and right ACx. Our results support a functional circuit based approach to understand the role of inhibitory neurons in auditory processing.

Two-color, one-photon uncaging of glutamate and GABA

Neuronal cells receive a variety of excitatory and inhibitory signals which they process to generate an output signal. In order to study the interaction between excitatory and inhibitory receptors with exogenously applied transmitters in the same preparation, two caging chromophores attached to glutamate and GABA were developed that were selectively photolyzed by different wavelengths of light. This technique has the advantage that the biologically inactive caged compound can be applied at equilibrium prior to the near instantaneous release of the transmitters. This method therefore mimics the kinetics of endogenously released transmitters that is otherwise not possible in brain slice preparations. Repeated photolysis with either of the two wavelengths resulted in GABA- or glutamate-induced activation of both ionotropic and metabotropic receptors to evoke reproducible currents. With these compounds, the interaction between inhibitory and excitatory receptors was examined using whole field photolysis.

Computations in the deep vs superficial layers of the cerebral cortex

A fundamental question is how the cerebral neocortex operates functionally, computationally. The cerebral neocortex with its superficial and deep layers and highly developed recurrent collateral systems that provide a basis for memory-related processing might perform somewhat different computations in the superficial and deep layers. Here we take into account the quantitative connectivity within and between laminae. Using integrate-and-fire neuronal network simulations that incorporate this connectivity, we first show that attractor networks implemented in the deep layers that are activated by the superficial layers could be partly independent in that the deep layers might have a different time course, which might because of adaptation be more transient and useful for outputs from the neocortex. In contrast the superficial layers could implement more prolonged firing, useful for slow learning and for short-term memory. Second, we show that a different type of computation could in principle be performed in the superficial and deep layers, by showing that the superficial layers could operate as a discrete attractor network useful for categorisation and feeding information forward up a cortical hierarchy, whereas the deep layers could operate as a continuous attractor network useful for providing a spatially and temporally smooth output to output systems in the brain. A key advance is that we draw attention to the functions of the recurrent collateral connections between cortical pyramidal cells, often omitted in canonical models of the neocortex, and address principles of operation of the neocortex by which the superficial and deep layers might be specialized for different types of attractor-related memory functions implemented by the recurrent collaterals.

Long-range cortical dynamics: a perspective from the mouse sensorimotor whisker system

In the mammalian neocortex, the capacity to dynamically route and coordinate the exchange of information between areas is a critical feature of cognitive function, enabling processes such as higher-level sensory processing and sensorimotor integration. Despite the importance attributed to long-range connections between cortical areas, their exact operations and role in cortical function remain an open question. In recent years, progress has been made in understanding long-range cortical circuits through work focused on the mouse sensorimotor whisker system. In this review, we examine recent studies dissecting long-range circuits involved in whisker sensorimotor processing as an entry point for understanding the rules that govern long-range cortical circuit function.

Circuit changes in motor cortex during motor skill learning

Motor cortex is important for motor skill learning, particularly the dexterous skills necessary for our favorite sports and careers. We are especially interested in understanding how plasticity in motor cortex contributes to skill learning. Although human studies have been helpful in understanding the importance of motor cortex in learning skilled tasks, animal models are necessary for achieving a detailed understanding of the circuitry underlying these behaviors and the changes that occur during training. We review data from these models to try to identify sites of plasticity in motor cortex, focusing on rodents asa model system. Rodent neocortex contains well-differentiated motor and sensory regions, as well as neurons expressing similar genetic markers to many of the same circuit components in human cortex. Furthermore, rodents have circuit mapping tools for labeling, targeting, and manipulating these cell types as circuit nodes. Crucially, the projection from rodent primary somatosensory cortex to primary motor cortex is a well-studied corticocortical projection and a model of sensorimotor integration. We first summarize some of the descending pathways involved in making dexterous movements, including reaching. We then describe local and long-range circuitry in mouse motor cortex, summarizing structural and functional changes associated with motor skill acquisition. We then address which specific connections might be responsible for plasticity. For insight into the range of plasticity mechanisms employed by cortex, we review plasticity in sensory systems. The similarities and differences between motor cortex plasticity and critical periods of plasticity in sensory systems are discussed.

A Corticocortical Circuit Directly Links Retrosplenial Cortex to M2 in the Mouse

Retrosplenial cortex (RSC) is a dorsomedial parietal area involved in a range of cognitive functions, including episodic memory, navigation, and spatial memory. Anatomically, the RSC receives inputs from dorsal hippocampal networks and in turn projects to medial neocortical areas. A particularly prominent projection extends rostrally to the posterior secondary motor cortex (M2), suggesting a functional corticocortical link from the RSC to M2 and thus a bridge between hippocampal and neocortical networks involved in mnemonic and sensorimotor aspects of navigation. We investigated the cellular connectivity in this RSC→M2 projection in the mouse using optogenetic photostimulation, retrograde labeling, and electrophysiology. Axons from RSC formed monosynaptic excitatory connections onto M2 pyramidal neurons across layers and projection classes, including corticocortical/intratelencephalic neurons (reciprocally and callosally projecting) in layers 2-6, pyramidal tract neurons (corticocollicular, corticopontine) in layer 5B, and, to a lesser extent, corticothalamic neurons in layer 6. In addition to these direct connections, disynaptic connections were made via posterior parietal cortex (RSC→PPC→M2) and anteromedial thalamus (RSC→AM→M2). In the reverse direction, axons from M2 monosynaptically excited M2-projecting corticocortical neurons in the RSC, especially in the superficial layers of the dysgranular region. These findings establish an excitatory RSC→M2 corticocortical circuit that engages diverse types of excitatory projection neurons in the downstream area, suggesting a basis for direct communication from dorsal hippocampal networks involved in spatial memory and navigation to neocortical networks involved in diverse aspects of sensorimotor integration and motor control.

SIGNIFICANCE STATEMENT

Corticocortical pathways interconnect cortical areas extensively, but the cellular connectivity in these pathways remains largely uncharacterized. Here, we show that a posterior part of secondary motor cortex receives corticocortical axons from the rostral retrosplenial cortex (RSC) and these form monosynaptic excitatory connections onto a wide spectrum of excitatory projection neurons in this area. Our results define a cellular basis for direct communication from RSC to this medial frontal area, suggesting a direct link from dorsal hippocampal networks involved in spatial cognition and navigation (the "map") to sensorimotor networks involved the control of movement (the "motor").

Organization of orientation-specific whisker deflection responses in layer 2/3 of mouse somatosensory cortex

The rodent whisker-barrel system is characterized by its patterned somatotopic mapping between the sensory periphery and multiple regions of the brain. While somatotopy in the whisker system is established, we know far less about how preferences for stimulus orientation or other features are organized. Mouse somatosensation is an increasingly popular model for circuit-based dissection of perceptual decision making and learning, yet our understanding of how stimulus feature representations are organized in the cortex is incomplete. Here, we used in vivo two-photon calcium imaging to monitor activity of populations of layer (L) 2/3 neurons in the mouse primary somatosensory cortex during deflections of a single whisker in two orthogonal orientations (azimuthal or elevational). We split the population response to whisker deflections into an orientation-specific component and a non-specific component that reflected overall excitability in response to deflection of a single whisker. Orientation-specific responses were organized in a locally heterogeneous and spatially distributed manner. Correlations in the stimulus-independent trial-to-trial variability of pairs of neurons were higher among neurons that preferred the same orientation. These correlations depended on similarity in both orientation-specific and non-specific components of responses to single-whisker deflections. Our results shed light on L2/3 organization in mouse somatosensory cortex, and lay a foundation for dissecting circuit mechanisms of perceptual learning and decision-making during orientation discrimination tasks.

Does layer 4 in the barrel cortex function as a balanced circuit when responding to whisker movements?

Neurons in one barrel in layer 4 (L4) in the mouse vibrissa somatosensory cortex are innervated mostly by neurons from the VPM nucleus and by other neurons within the same barrel. During quiet wakefulness or whisking in air, thalamic inputs vary slowly in time, and excitatory neurons rarely fire. A barrel in L4 contains a modest amount of neurons; the synaptic conductances are not very strong and connections are not sparse. Are the dynamical properties of the L4 circuit similar to those expected from fluctuation-dominated, balanced networks observed for large, strongly coupled and sparse cortical circuits? To resolve this question, we analyze a network of 150 inhibitory parvalbumin-expressing fast-spiking inhibitory interneurons innervated by the VPM thalamus with random connectivity, without or with 1600 low-firing excitatory neurons. Above threshold, the population-average firing rate of inhibitory cortical neurons increases linearly with the thalamic firing rate. The coefficient of variation CV is somewhat less than 1. Moderate levels of synchrony are induced by converging VPM inputs and by inhibitory interaction among neurons. The strengths of excitatory and inhibitory currents during whisking are about three times larger than threshold. We identify values of numbers of presynaptic neurons, synaptic delays between inhibitory neurons, and electrical coupling within the experimentally plausible ranges for which spike synchrony levels are low. Heterogeneity in in-degrees increases the width of the firing rate distribution to the experimentally observed value. We conclude that an L4 circuit in the low-synchrony regime exhibits qualitative dynamical properties similar to those of balanced networks.

A Map of Anticipatory Activity in Mouse Motor Cortex

Activity in the mouse anterior lateral motor cortex (ALM) instructs directional movements, often seconds before movement initiation. It is unknown whether this preparatory activity is localized to ALM or widely distributed within motor cortex. Here we imaged activity across motor cortex while mice performed a whisker-based object localization task with a delayed, directional licking response. During tactile sensation and the delay epoch, object location was represented in motor cortex areas that are medial and posterior relative to ALM, including vibrissal motor cortex. Preparatory activity appeared first in deep layers of ALM, seconds before the behavioral response, and remained localized to ALM until the behavioral response. Later, widely distributed neurons represented the outcome of the trial. Cortical area was more predictive of neuronal selectivity than laminar location or axonal projection target. Motor cortex therefore represents sensory, motor, and outcome information in a spatially organized manner.

Deconstructing the cortical column in the barrel cortex

The question of what function is served by the cortical column has occupied neuroscientists since its original description some 60years ago. The answer seems tractable in the somatosensory cortex when considering the inputs to the cortical column and the early stages of information processing, but quickly breaks down once the multiplicity of output streams and their sub-circuits are brought into consideration. This article describes the early stages of information processing in the barrel cortex, through generation of the center and surround receptive field components of neurons that subserve integration of multi whisker information, before going on to consider the diversity of properties exhibited by the layer 5 output neurons. The layer 5 regular spiking (RS) neurons differ from intrinsic bursting (IB) neurons in having different input connections, plasticity mechanisms and corticofugal projections. In particular, layer 5 RS cells employ noise reduction and homeostatic plasticity mechanism to preserve and even increase information transfer, while IB cells use more conventional Hebbian mechanisms to achieve a similar outcome. It is proposed that the rodent analog of the dorsal and ventral streams, a division reasonably well established in primate cortex, might provide a further level of organization for RS cell function and hence sub-circuit specialization.

Similarity in Neuronal Firing Regimes across Mammalian Species

The architectonic subdivisions of the brain are believed to be functional modules, each processing parts of global functions. Previously, we showed that neurons in different regions operate in different firing regimes in monkeys. It is possible that firing regimes reflect differences in underlying information processing, and consequently the firing regimes in homologous regions across animal species might be similar. We analyzed neuronal spike trains recorded from behaving mice, rats, cats, and monkeys. The firing regularity differed systematically, with differences across regions in one species being greater than the differences in similar areas across species. Neuronal firing was consistently most regular in motor areas, nearly random in visual and prefrontal/medial prefrontal cortical areas, and bursting in the hippocampus in all animals examined. This suggests that firing regularity (or irregularity) plays a key role in neural computation in each functional subdivision, depending on the types of information being carried.

SIGNIFICANCE STATEMENT

By analyzing neuronal spike trains recorded from mice, rats, cats, and monkeys, we found that different brain regions have intrinsically different firing regimes that are more similar in homologous areas across species than across areas in one species. Because different regions in the brain are specialized for different functions, the present finding suggests that the different activity regimes of neurons are important for supporting different functions, so that appropriate neuronal codes can be used for different modalities.

Mechanisms underlying a thalamocortical transformation during active tactile sensation

During active somatosensation, neural signals expected from movement of the sensors are suppressed in the cortex, whereas information related to touch is enhanced. This tactile suppression underlies low-noise encoding of relevant tactile features and the brain’s ability to make fine tactile discriminations. Layer (L) 4 excitatory neurons in the barrel cortex, the major target of the somatosensory thalamus (VPM), respond to touch, but have low spike rates and low sensitivity to the movement of whiskers. Most neurons in VPM respond to touch and also show an increase in spike rate with whisker movement. Therefore, signals related to self-movement are suppressed in L4. Fast-spiking (FS) interneurons in L4 show similar dynamics to VPM neurons. Stimulation of halorhodopsin in FS interneurons causes a reduction in FS neuron activity and an increase in L4 excitatory neuron activity. This decrease of activity of L4 FS neurons contradicts the "paradoxical effect" predicted in networks stabilized by inhibition and in strongly-coupled networks. To explain these observations, we constructed a model of the L4 circuit, with connectivity constrained by in vitro measurements. The model explores the various synaptic conductance strengths for which L4 FS neurons actively suppress baseline and movement-related activity in layer 4 excitatory neurons. Feedforward inhibition, in concert with recurrent intracortical circuitry, produces tactile suppression. Synaptic delays in feedforward inhibition allow transmission of temporally brief volleys of activity associated with touch. Our model provides a mechanistic explanation of a behavior-related computation implemented by the thalamocortical circuit.

We study how information is transformed between connected brain areas: the thalamus, the gateway to the cortex, and layer 4 (L4) in cortex, which is the first station to process sensory input from the thalamus. When mice perform an active object localization task with their whiskers, thalamic neurons and inhibitory fast-spiking (FS) interneurons in L4 encode whisker movement and touch, whereas L4 excitatory neurons respond almost exclusively to touch. To explain these observations, we constructed a computational model based on measured circuit parameters. The model reveals that without touch, when thalamic activity varies slowly, strong inhibition from FS neurons prevents activity in L4 excitatory neurons. Brief and strong touch-induced thalamic activity excites both excitatory and FS neurons in L4. FS neurons inhibit excitatory neurons with a delay of approximately 1 ms relative to ascending excitation, allowing L4 excitatory neurons to spike. Our results demonstrate that cortical circuits exploit synaptic delays for fast computations. Similar mechanisms likely also operate for rapid stimuli in the visual and auditory systems.

D3 Receptors Regulate Excitability in a Unique Class of Prefrontal Pyramidal Cells

The D3 dopamine receptor, a member of the G_i-coupled D2 family of dopamine receptors, is expressed throughout limbic circuits affected in neuropsychiatric disorders, including prefrontal cortex (PFC). These receptors are important for prefrontal executive function because pharmacological and genetic manipulations that affect prefrontal D3 receptors alter anxiety, social interaction, and reversal learning. However, the mechanisms by which D3 receptors regulate prefrontal circuits and whether D3 receptors regulate specific prefrontal subnetworks remains unknown. Here, we combine dopamine receptor reporter lines, anatomical tracing techniques, and electrophysiology to show that D3 receptor expression defines a novel subclass of layer 5 glutamatergic pyramidal cell in mouse PFC (either sex). D3-receptor-expressing pyramidal neurons are electrophysiologically and anatomically separable from neighboring neurons expressing D1 or D2 receptors based on their dendritic morphology and subthreshold and suprathreshold intrinsic excitability. D3-receptor-expressing neurons send axonal projections to intratelencephalic (IT) targets, including contralateral cortex, nucleus accumbens, and basolateral amygdala. Within these neurons, D3 receptor activation was found to regulate low-voltage-activated Ca_V3.2 calcium channels localized to the axon initial segment, which suppressed action potential (AP) excitability, particularly when APs occurred at high frequency. Therefore, these data indicate that D3 receptors regulate the excitability of a unique, IT prefrontal cell population, thereby defining novel circuitry and cellular actions for D3 receptors in PFC.SIGNIFICANCE STATEMENT The D3 dopamine receptor, a member of the G_i-coupled D2 family of dopamine receptors, are expressed throughout limbic circuits, including prefrontal cortex (PFC). They are of broad interest as a site for therapeutic intervention in serious mental illness, yet we know very little about their distribution or function within PFC. Here, we show that D3 receptors define a unique population of glutamatergic principal cells in mouse PFC that largely lack expression of D1 or D2 receptors. Within these cells, we find that D3 receptors regulate the ability to generate high-frequency action potential bursts through mechanisms not supported by other dopamine receptors. These results define unique circuitry and cellular actions for D3 receptors in regulating PFC networks.

Movement Initiation Signals in Mouse Whisker Motor Cortex

Frontal cortex plays a central role in the control of voluntary movements, which are typically guided by sensory input. Here, we investigate the function of mouse whisker primary motor cortex (wM1), a frontal region defined by dense innervation from whisker primary somatosensory cortex (wS1). Optogenetic stimulation of wM1 evokes rhythmic whisker protraction (whisking), whereas optogenetic inactivation of wM1 suppresses initiation of whisking. Whole-cell membrane potential recordings and silicon probe recordings of action potentials reveal layer-specific neuronal activity in wM1 at movement initiation, and encoding of fast and slow parameters of movements during whisking. Interestingly, optogenetic inactivation of wS1 caused hyperpolarization and reduced firing in wM1, together with reduced whisking. Optogenetic stimulation of wS1 drove activity in wM1 with complex dynamics, as well as evoking long-latency, wM1-dependent whisking. Our results advance understanding of a well-defined frontal region and point to an important role for sensory input in controlling motor cortex.

Neural Elements for Predictive Coding

Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backward in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many ‘illusory’ instances of perception where what is seen (heard, etc.) is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forward and backward pathways should be completely separate, given their functional distinction; this aspect of circuitry – that neurons with extrinsically bifurcating axons do not project in both directions – has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy) formulation of predictive coding is combined with the classic ‘canonical microcircuit’ and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a) updates in the microcircuitry of primate visual cortex, and (b) rapid technical advances made possible by transgenic neural engineering in the mouse. The exercise highlights a number of recurring themes, amongst them the consideration of interneuron diversity as a spur to theoretical development and the potential for specifying a pyramidal neuron’s function by its individual ‘connectome,’ combining its extrinsic projection (forward, backward or subcortical) with evaluation of its intrinsic network (e.g., unidirectional versus bidirectional connections with other pyramidal neurons).

Brain Computation Is Organized via Power-of-Two-Based Permutation Logic

There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2ⁱ–1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex.

Synaptic scaling rule preserves excitatory-inhibitory balance and salient neuronal network dynamics

The balance between excitation and inhibition (E-I balance) is maintained across brain regions though the network size, strength and number of synaptic connections, and connection architecture may vary substantially. We use a culture preparation to examine the homeostatic synaptic scaling rules that produce E-I balance and in vivo-like activity. We show that synaptic strength scales with the number of connections K as ∼ , close to the ideal theoretical value. Using optogenetic techniques, we delivered spatiotemporally patterned stimuli to neurons and confirmed key theoretical predictions: E-I balance is maintained, active decorrelation occurs and the spiking correlation increases with firing rate. Moreover, the trial-to-trial response variability decreased during stimulation, as observed in vivo. These results-obtained in generic cultures, predicted by theory and observed in the intact brain-suggest that the synaptic scaling rule and resultant dynamics are emergent properties of networks in general.

Layer 4 fast-spiking interneurons filter thalamocortical signals during active somatosensation

We rely on movement to explore the environment, for example, by palpating an object. In somatosensory cortex, activity related to movement of digits or whiskers is suppressed, which could facilitate detection of touch. Movement-related suppression is generally assumed to involve corollary discharges. Here we uncovered a thalamocortical mechanism in which cortical fast-spiking interneurons, driven by sensory input, suppress movement-related activity in layer 4 (L4) excitatory neurons. In mice locating objects with their whiskers, neurons in the ventral posteromedial nucleus (VPM) fired in response to touch and whisker movement. Cortical L4 fast-spiking interneurons inherited these responses from VPM. In contrast, L4 excitatory neurons responded mainly to touch. Optogenetic experiments revealed that fast-spiking interneurons reduced movement-related spiking in excitatory neurons, enhancing selectivity for touch-related information during active tactile sensation. These observations suggest a fundamental computation performed by the thalamocortical circuit to accentuate salient tactile information.

Whisker row deprivation affects the flow of sensory information through rat barrel cortex

Sensory cortical plasticity is usually quantified by changes in evoked firing rate. In this study we quantified plasticity by changes in sensory detection performance using Chernoff information and receiver operating characteristic analysis. We found that whisker deprivation causes a change in information flow within the cortical layers and that layer 5 regular-spiking cells, despite showing only a small potentiation of short-latency input, show the greatest increase in information content for the spared input partly by decreasing their spontaneous activity.

Whisker trimming causes substantial reorganization of neuronal response properties in barrel cortex. However, little is known about experience-dependent rerouting of sensory processing following sensory deprivation. To address this, we performed in vivo intracellular recordings from layers 2/3 (L2/3), layer 4 (L4), layer 5 regular-spiking (L5RS), and L5 intrinsically bursting (L5IB) neurons and measured their multiwhisker receptive field at the level of spiking activity, membrane potential, and synaptic conductance before and after sensory deprivation. We used Chernoff information to quantify the “sensory information” contained in the firing patterns of cells in response to spared and deprived whisker stimulation. In the control condition, information for flanking-row and same-row whiskers decreased in the order L4, L2/3, L5IB, L5RS. However, after whisker-row deprivation, spared flanking-row whisker information was reordered to L4, L5RS, L5IB, L2/3. Sensory information from the trimmed whiskers was reduced and delayed in L2/3 and L5IB neurons, whereas sensory information from spared whiskers was increased and advanced in L4 and L5RS neurons. Sensory information from spared whiskers was increased in L5IB neurons without a latency change. L5RS cells exhibited the largest changes in sensory information content through an atypical plasticity combining a significant decrease in spontaneous activity and an increase in a short-latency excitatory conductance.

NEW & NOTEWORTHY Sensory cortical plasticity is usually quantified by changes in evoked firing rate. In this study we quantified plasticity by changes in sensory detection performance using Chernoff information and receiver operating characteristic analysis. We found that whisker deprivation causes a change in information flow within the cortical layers and that layer 5 regular-spiking cells, despite showing only a small potentiation of short-latency input, show the greatest increase in information content for the spared input partly by decreasing their spontaneous activity.

Target-specific M1 inputs to infragranular S1 pyramidal neurons

The functional role of input from the primary motor cortex (M1) to primary somatosensory cortex (S1) is unclear; one key to understanding this pathway may lie in elucidating the cell-type specific microcircuits that connect S1 and M1. Recently, we discovered that a subset of pyramidal neurons in the infragranular layers of S1 receive especially strong input from M1 (Kinnischtzke AK, Simons DJ, Fanselow EE. Cereb Cortex 24: 2237-2248, 2014), suggesting that M1 may affect specific classes of pyramidal neurons differently. Here, using combined optogenetic and retrograde labeling approaches in the mouse, we examined the strengths of M1 inputs to five classes of infragranular S1 neurons categorized by their projections to particular cortical and subcortical targets. We found that the magnitude of M1 synaptic input to S1 pyramidal neurons varies greatly depending on the projection target of the postsynaptic neuron. Of the populations examined, M1-projecting corticocortical neurons in L6 received the strongest M1 inputs, whereas ventral posterior medial nucleus-projecting corticothalamic neurons, also located in L6, received the weakest. Each population also possessed distinct intrinsic properties. The results suggest that M1 differentially engages specific classes of S1 projection neurons, thereby regulating the motor-related influence S1 exerts over subcortical structures.

Traumatic Brain Injury and Neuronal Functionality Changes in Sensory Cortex

Traumatic brain injury (TBI), caused by direct blows to the head or inertial forces during relative head-brain movement, can result in long-lasting cognitive and motor deficits which can be particularly consequential when they occur in young people with a long life ahead. Much is known of the molecular and anatomical changes produced in TBI but much less is known of the consequences of these changes to neuronal functionality, especially in the cortex. Given that much of our interior and exterior lives are dependent on responsiveness to information from and about the world around us, we have hypothesized that a significant contributor to the cognitive and motor deficits seen after TBI could be changes in sensory processing. To explore this hypothesis, and to develop a model test system of the changes in neuronal functionality caused by TBI, we have examined neuronal encoding of simple and complex sensory input in the rat’s exploratory and discriminative tactile system, the large face macrovibrissae, which feeds to the so-called “barrel cortex” of somatosensory cortex. In this review we describe the short-term and long-term changes in the barrel cortex encoding of whisker motion modeling naturalistic whisker movement undertaken by rats engaged in a variety of tasks. We demonstrate that the most common form of TBI results in persistent neuronal hyperexcitation specifically in the upper cortical layers, likely due to changes in inhibition. We describe the types of cortical inhibitory neurons and their roles and how selective effects on some of these could produce the particular forms of neuronal encoding changes described in TBI, and then generalize to compare the effects on inhibition seen in other forms of brain injury. From these findings we make specific predictions as to how non-invasive extra-cranial electrophysiology can be used to provide the high-precision information needed to monitor and understand the temporal evolution of changes in neuronal functionality in humans suffering TBI. Such detailed understanding of the specific changes in an individual patient’s cortex can allow for treatment to be tailored to the neuronal changes in that particular patient’s brain in TBI, a precision that is currently unavailable with any technique.

A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity

The prefrontal cortex is centrally involved in a wide range of cognitive functions and their impairment in psychiatric disorders. Yet, the computational principles that govern the dynamics of prefrontal neural networks, and link their physiological, biochemical and anatomical properties to cognitive functions, are not well understood. Computational models can help to bridge the gap between these different levels of description, provided they are sufficiently constrained by experimental data and capable of predicting key properties of the intact cortex. Here, we present a detailed network model of the prefrontal cortex, based on a simple computationally efficient single neuron model (simpAdEx), with all parameters derived from in vitro electrophysiological and anatomical data. Without additional tuning, this model could be shown to quantitatively reproduce a wide range of measures from in vivo electrophysiological recordings, to a degree where simulated and experimentally observed activities were statistically indistinguishable. These measures include spike train statistics, membrane potential fluctuations, local field potentials, and the transmission of transient stimulus information across layers. We further demonstrate that model predictions are robust against moderate changes in key parameters, and that synaptic heterogeneity is a crucial ingredient to the quantitative reproduction of in vivo-like electrophysiological behavior. Thus, we have produced a physiologically highly valid, in a quantitative sense, yet computationally efficient PFC network model, which helped to identify key properties underlying spike time dynamics as observed in vivo, and can be harvested for in-depth investigation of the links between physiology and cognition.

Computational network models are an important tool for linking physiological and neuro-dynamical processes to cognition. However, harvesting network models for this purpose may less depend on how much biophysical detail is included, but more on how well the model can capture the functional network physiology. Here, we present the first network model of the prefrontal cortex which has not only its single neuron properties and anatomical layout tightly constrained by experimental data, but is also able to quantitatively reproduce a large range of spiking, field potential, and membrane voltage statistics obtained from in vivo data, without need of specific parameter tuning. It thus represents a novel computational tool for addressing questions about the neuro-dynamics of cognition in health and disease.

Inhibitory Circuits in Cortical Layer 5

Inhibitory neurons play a fundamental role in cortical computation and behavior. Recent technological advances, such as two photon imaging, targeted in vivo recording, and molecular profiling, have improved our understanding of the function and diversity of cortical interneurons, but for technical reasons most work has been directed towards inhibitory neurons in the superficial cortical layers. Here we review current knowledge specifically on layer 5 (L5) inhibitory microcircuits, which play a critical role in controlling cortical output. We focus on recent work from the well-studied rodent barrel cortex, but also draw on evidence from studies in primary visual cortex and other cortical areas. The diversity of both deep inhibitory neurons and their pyramidal cell targets make this a challenging but essential area of study in cortical computation and sensory processing.

Sensorimotor Convergence in Circuitry of the Motor Cortex

Scientists and philosophers have long appreciated that active somatosensation requires the sensory and motor systems to exchange information about body the body's movements as well as touch in order to accurately interpret incoming somatosensory information and plan future movements. However, the circuitry underlying this sensory and motor integration is complicated and is difficult to study without tools to label specific cellular components in the various brain regions involved. Here, I review the general pathways that convey ascending sensory and descending motor information, using the rodent whisker system as a model to take advantage of the cell type specificity possible in this model. I then detail the circuits in motor cortex in which incoming information from somatosensory cortex and thalamus is integrated. I close with a brief description of changes in these circuits during motor learning.

Voltage imaging to understand connections and functions of neuronal circuits

Understanding of the cellular mechanisms underlying brain functions such as cognition and emotions requires monitoring of membrane voltage at the cellular, circuit, and system levels. Seminal voltage-sensitive dye and calcium-sensitive dye imaging studies have demonstrated parallel detection of electrical activity across populations of interconnected neurons in a variety of preparations. A game-changing advance made in recent years has been the conceptualization and development of optogenetic tools, including genetically encoded indicators of voltage (GEVIs) or calcium (GECIs) and genetically encoded light-gated ion channels (actuators, e.g., channelrhodopsin2). Compared with low-molecular-weight calcium and voltage indicators (dyes), the optogenetic imaging approaches are 1) cell type specific, 2) less invasive, 3) able to relate activity and anatomy, and 4) facilitate long-term recordings of individual cells' activities over weeks, thereby allowing direct monitoring of the emergence of learned behaviors and underlying circuit mechanisms. We highlight the potential of novel approaches based on GEVIs and compare those to calcium imaging approaches. We also discuss how novel approaches based on GEVIs (and GECIs) coupled with genetically encoded actuators will promote progress in our knowledge of brain circuits and systems.

Specific Targeting of the Basolateral Amygdala to Projectionally Defined Pyramidal Neurons in Prelimbic and Infralimbic Cortex

Adjacent prelimbic (PL) and infralimbic (IL) regions in the medial prefrontal cortex have distinct roles in emotional learning. A complete mechanistic understanding underlying this dichotomy remains unclear. Here we explored targeting of specific PL and IL neurons by the basolateral amygdala (BLA), a limbic structure pivotal in pain and fear processing. In mice, we used retrograde labeling, brain-slice recordings, and adenoviral optogenetics to dissect connectivity of ascending BLA input onto PL and IL neurons projecting to the periaqueductal gray (PAG) or the amygdala. We found differential targeting of BLA projections to PL and IL cortex. Activating BLA projections evoked excitatory and inhibitory responses in cortico-PAG (CP) neurons in layer 5 (L5) of both PL and IL cortex. However, all inhibitory responses were polysynaptic and monosynaptic BLA input was stronger to CP neurons in IL cortex. Conversely, the BLA preferentially targeted corticoamygdalar (CA) neurons in layer 2 (L2) of PL over IL cortex. We also reveal that BLA input is projection specific by showing preferential targeting of L5 CP neurons over neighboring L3/5 CA neurons in IL cortex. We conclude by showing that BLA input is laminar-specific by producing stronger excitatory responses CA neurons in L3/5 compared with L2 in IL cortex. Collectively, this study reveals differential targeting of the BLA to PL and IL cortex, which depends both on laminar location and projection target of cortical neurons. Overall, our findings should have important implications for understanding the processing of pain and fear input by the PL and IL cortex.

Primary visual cortex shows laminar-specific and balanced circuit organization of excitatory and inhibitory synaptic connectivity

KEY POINTS

Using functional mapping assays, we conducted a quantitative assessment of both excitatory and inhibitory synaptic laminar connections to excitatory neurons in layers 2/3-6 of the mouse visual cortex (V1). Laminar-specific synaptic wiring diagrams of excitatory neurons were constructed on the basis of circuit mapping. The present study reveals that that excitatory and inhibitory synaptic connectivity is spatially balanced across excitatory neuronal networks in V1.

ABSTRACT

In the mammalian neocortex, excitatory neurons provide excitation in both columnar and laminar dimensions, which is modulated further by inhibitory neurons. However, our understanding of intracortical excitatory and inhibitory synaptic inputs in relation to principal excitatory neurons remains incomplete, and it is unclear how local excitatory and inhibitory synaptic connections to excitatory neurons are spatially organized on a layer-by-layer basis. In the present study, we combined whole cell recordings with laser scanning photostimulation via glutamate uncaging to map excitatory and inhibitory synaptic inputs to single excitatory neurons throughout cortical layers 2/3-6 in the mouse primary visual cortex (V1). We find that synaptic input sources of excitatory neurons span the radial columns of laminar microcircuits, and excitatory neurons in different V1 laminae exhibit distinct patterns of layer-specific organization of excitatory inputs. Remarkably, the spatial extent of inhibitory inputs of excitatory neurons for a given layer closely mirrors that of their excitatory input sources, indicating that excitatory and inhibitory synaptic connectivity is spatially balanced across excitatory neuronal networks. Strong interlaminar inhibitory inputs are found, particularly for excitatory neurons in layers 2/3 and 5. This differs from earlier studies reporting that inhibitory cortical connections to excitatory neurons are generally localized within the same cortical layer. On the basis of the functional mapping assays, we conducted a quantitative assessment of both excitatory and inhibitory synaptic laminar connections to excitatory cells at single cell resolution, establishing precise layer-by-layer synaptic wiring diagrams of excitatory neurons in the visual cortex.

Calcium regulation of HCN channels supports persistent activity in a multiscale model of neocortex

Neuronal persistent activity has been primarily assessed in terms of electrical mechanisms, without attention to the complex array of molecular events that also control cell excitability. We developed a multiscale neocortical model proceeding from the molecular to the network level to assess the contributions of calcium (Ca(2+)) regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in providing additional and complementary support of continuing activation in the network. The network contained 776 compartmental neurons arranged in the cortical layers, connected using synapses containing AMPA/NMDA/GABAA/GABAB receptors. Metabotropic glutamate receptors (mGluR) produced inositol triphosphate (IP3) which caused the release of Ca(2+) from endoplasmic reticulum (ER) stores, with reuptake by sarco/ER Ca(2+)-ATP-ase pumps (SERCA), and influence on HCN channels. Stimulus-induced depolarization led to Ca(2+) influx via NMDA and voltage-gated Ca(2+) channels (VGCCs). After a delay, mGluR activation led to ER Ca(2+) release via IP3 receptors. These factors increased HCN channel conductance and produced firing lasting for ∼1min. The model displayed inter-scale synergies among synaptic weights, excitation/inhibition balance, firing rates, membrane depolarization, Ca(2+) levels, regulation of HCN channels, and induction of persistent activity. The interaction between inhibition and Ca(2+) at the HCN channel nexus determined a limited range of inhibition strengths for which intracellular Ca(2+) could prepare population-specific persistent activity. Interactions between metabotropic and ionotropic inputs to the neuron demonstrated how multiple pathways could contribute in a complementary manner to persistent activity. Such redundancy and complementarity via multiple pathways is a critical feature of biological systems. Mediation of activation at different time scales, and through different pathways, would be expected to protect against disruption, in this case providing stability for persistent activity.

Neural coding in barrel cortex during whisker-guided locomotion

Animals seek out relevant information by moving through a dynamic world, but sensory systems are usually studied under highly constrained and passive conditions that may not probe important dimensions of the neural code. Here, we explored neural coding in the barrel cortex of head-fixed mice that tracked walls with their whiskers in tactile virtual reality. Optogenetic manipulations revealed that barrel cortex plays a role in wall-tracking. Closed-loop optogenetic control of layer 4 neurons can substitute for whisker-object contact to guide behavior resembling wall tracking. We measured neural activity using two-photon calcium imaging and extracellular recordings. Neurons were tuned to the distance between the animal snout and the contralateral wall, with monotonic, unimodal, and multimodal tuning curves. This rich representation of object location in the barrel cortex could not be predicted based on simple stimulus-response relationships involving individual whiskers and likely emerges within cortical circuits.

DOI:http://dx.doi.org/10.7554/eLife.12559.001

Mice are primarily nocturnal animals that rely on their whiskers to navigate dark underground burrows and winding corridors. When a whisker touches an object, cells called neurons at the base of the whiskers produce electrical signals that are relayed to other neurons in an area of the brain called the barrel cortex. However, it is not clear how information is encoded in these electrical signals, in part, because it is technically challenging to collect data about neuron activity and behavior while the mice move around.

To overcome these difficulties, Sofroniew, Vlasov et al. used a touch-based (or 'tactile') virtual reality system to study how mice navigate along corridors. The system simulated the contact the whiskers would have with the walls of a winding corridor. This was achieved by moving the walls with motors while holding the mouse still enough to be able to measure the activity of neurons in the barrel cortex and observe the behavior of the animal.

The experiments show that the electrical signals in the barrel cortex encode information about motion as well as the distance between the mouse and the wall. For example, some neurons in the barrel cortex were only activated when a mouse was a particular distance from the walls. The experiments suggest that the barrel cortex processes signals received from several whiskers to build an overall picture of the locations and shapes of objects.

Sofroniew, Vlasov et al. also used a technique called optogenetics to deliberately activate particular neurons in a manner that mimics their activity patterns during interactions with walls. In the absence of walls, the optogenetic stimuli guided the behavior of the mice so that they tracked along the paths of 'illusory' corridors. Together, these findings reveal the neural code in the barrel cortex that allows mice to navigate by touch.

DOI:http://dx.doi.org/10.7554/eLife.12559.002

Connectivity of mouse somatosensory and prefrontal cortex examined with trans-synaptic tracing

Information processing in neocortical circuits requires integrating inputs over a wide range of spatial scales, from local microcircuits to long-range cortical and subcortical connections. We used rabies virus-based trans-synaptic tracing to analyze the laminar distribution of local and long-range inputs to pyramidal neurons in the mouse barrel cortex and medial prefrontal cortex (mPFC). New findings in barrel cortex include substantial inputs from layer 3 (L3) to L6, prevalent translaminar inhibitory inputs, and long-range inputs to L2/3 or L5/6 preferentially from L2/3 or L5/6 of input cortical areas, respectively. These layer-specific input patterns are largely independent of NMDA receptor function in the recipient neurons. mPFC L5 receive proportionally more long-range inputs and more local inhibitory inputs than barrel cortex L5. These results provide new insight into the organization and development of neocortical networks and identify important differences in the circuit organization in sensory and association cortices.

Low-noise encoding of active touch by layer 4 in the somatosensory cortex

Cortical spike trains often appear noisy, with the timing and number of spikes varying across repetitions of stimuli. Spiking variability can arise from internal (behavioral state, unreliable neurons, or chaotic dynamics in neural circuits) and external (uncontrolled behavior or sensory stimuli) sources. The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked. We recorded from excitatory barrel cortex neurons in layer 4 during active behavior, where mice control tactile input through learned whisker movements. Touch was the dominant sensorimotor feature, with &gt;70% spikes occurring in millisecond timescale epochs after touch onset. The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum. Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise.

The Functional Organization of Neocortical Networks Investigated in Slices with Local Field Recordings and Laser Scanning Photostimulation

The organization of cortical networks can be investigated functionally in brain slices. Laser scanning photostimulation (LSPS) with glutamate-uncaging allows for a rapid survey of all connections impinging on single cells recorded in patch-clamp. We sought to develop a variant of the method that would allow for a more exhaustive mapping of neuronal networks at every experiment. We found that the extracellular field recordings could be used to detect synaptic responses evoked by LSPS. One to two electrodes were placed in all six cortical layers of barrel cortex successively and maps were computed from the size of synaptic negative local field potentials. The field maps displayed a laminar organization similar to the one observed in maps computed from excitatory postsynaptic currents recorded in patch-clamp mode. Thus, LSPS combined with field recording is an interesting alternative to obtain for every animal tested a comprehensive map of the excitatory intracortical network.

From a meso- to micro-scale connectome: array tomography and mGRASP

Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors.