The columnar and laminar organization of inhibitory connections to neocortical excitatory cells

The cerebellum and the Mirror Neuron System: A matter of inhibition? From neurophysiological evidence to neuromodulatory implications. A narrative review

Mirror neurons show activity during both the execution (AE) and observation of actions (AO). The Mirror Neuron System (MNS) could be involved during motor imagery (MI) as well. Extensive research suggests that the cerebellum is interconnected with the MNS and may be critically involved in its activities. We gathered evidence on the cerebellum's role in MNS functions, both theoretically and experimentally. Evidence shows that the cerebellum plays a major role during AO and MI and that its lesions impair MNS functions likely because, by modulating the activity of cortical inhibitory interneurons with mirror properties, the cerebellum may contribute to visuomotor matching, which is fundamental for shaping mirror properties. Indeed, the cerebellum may strengthen sensory-motor patterns that minimise the discrepancy between predicted and actual outcome, both during AE and AO. Furthermore, through its connections with the hippocampus, the cerebellum might be involved in internal simulations of motor programs during MI. Finally, as cerebellar neuromodulation might improve its impact on MNS activity, we explored its potential neurophysiological and neurorehabilitation implications.

Optogenetic Determination of Dynamic and Cell-Type-Specific Inhibitory Reversal Potentials

The reversal potential refers to the membrane potential at which the net current flow through a channel reverses direction. The reversal potential is determined by transmembrane ion gradients and, in turn, determines how the channel's activity will affect the membrane potential. Traditional investigation into the reversal potential of inhibitory ligand-gated ion channels (EInh) has relied upon the activation of endogenous receptors, such as the GABA-A receptor (GABAAR). There are, however, challenges associated with activating endogenous receptors, including agonist delivery, isolating channel responses, and the effects of receptor saturation and desensitization. Here, we demonstrate the utility of using a light-gated anion channel, stGtACR2, to probe EInh in the rodent brain. Using mice of both sexes, we demonstrate that the properties of this optically activated channel make it a suitable proxy for studying GABAAR receptor-mediated inhibition. We validate this agonist-independent optogenetic strategy in vitro and in vivo and further show how it can accurately capture differences in EInh dynamics following manipulations of endogenous ion fluxes. This allows us to explore distinct resting EInh differences across genetically defined neuronal subpopulations. Using this approach to challenge ion homeostasis mechanisms in neurons, we uncover cell-specific EInh dynamics that are supported by the differential expression of endogenous ion handling mechanisms. Our findings therefore establish an effective optical strategy for revealing novel aspects of inhibitory reversal potentials and thereby expand the repertoire of optogenetics.

Data-driven multiscale computational models of cortical and subcortical regions

Data-driven computational models of neurons, synapses, microcircuits, and mesocircuits have become essential tools in modern brain research. The goal of these multiscale models is to integrate and synthesize information from different levels of brain organization, from cellular properties, dendritic excitability, and synaptic dynamics to microcircuits, mesocircuits, and ultimately behavior. This article surveys recent advances in the genesis of data-driven computational models of mammalian neural networks in cortical and subcortical areas. I discuss the challenges and opportunities in developing data-driven multiscale models, including the need for interdisciplinary collaborations, the importance of model validation and comparison, and the potential impact on basic and translational neuroscience research. Finally, I highlight future directions and emerging technologies that will enable more comprehensive and predictive data-driven models of brain function and dysfunction.

Agranular frontal cortical microcircuit underlying cognitive control in macaques

The error-related negativity and an N2-component recorded over medial frontal cortex index core functions of cognitive control. While they are known to originate from agranular frontal areas, the underlying microcircuit mechanisms remain elusive. Most insights about microcircuit function have been derived from variations of the so-called canonical microcircuit model. These microcircuit architectures are based extensively on studies from granular sensory cortical areas in monkeys, cats, and rodents. However, evidence has shown striking cytoarchitectonic differences across species and differences in the functional relationships across cortical layers in agranular compared to granular sensory areas. In this minireview, we outline a tentative microcircuit model underlying cognitive control in the agranular frontal cortex of primates. The model incorporates the main GABAergic interneuron subclasses with specific laminar arrangements and target regions on pyramidal cells. We emphasize the role of layer 5 pyramidal cells in error and conflict detection. We offer several specific questions necessary for creating a specific intrinsic microcircuit model of the agranular frontal cortex.

Optogenetics 2.0: challenges and solutions towards a quantitative probing of neural circuits

To exploit the full potential of optogenetics, we need to titrate and tailor optogenetic methods to emulate naturalistic circuit function. For that, the following prerequisites need to be met: first, we need to target opsin expression not only to genetically defined neurons per se, but to specifically target a functional node. Second, we need to assess the scope of optogenetic modulation, i.e. the fraction of optogenetically modulated neurons. Third, we need to integrate optogenetic control in a closed loop setting. Fourth, we need to further safe and stable gene expression and light delivery to bring optogenetics to the clinics. Here, we review these concepts for the human and rodent brain.

Active cortical networks promote shunting fast synaptic inhibition in vivo

Fast synaptic inhibition determines neuronal response properties in the mammalian brain and is mediated by chloride-permeable ionotropic GABA-A receptors (GABAARs). Despite their fundamental role, it is still not known how GABAARs signal in the intact brain. Here, we use in vivo gramicidin recordings to investigate synaptic GABAAR signaling in mouse cortical pyramidal neurons under conditions that preserve native transmembrane chloride gradients. In anesthetized cortex, synaptic GABAARs exert classic hyperpolarizing effects. In contrast, GABAAR-mediated synaptic signaling in awake cortex is found to be predominantly shunting. This is due to more depolarized GABAAR equilibrium potentials (EGABAAR), which are shown to result from the high levels of synaptic activity that characterize awake cortical networks. Synaptic EGABAAR observed in awake cortex facilitates the desynchronizing effects of inhibitory inputs upon local networks, which increases the flexibility of spiking responses to external inputs. Our findings therefore suggest that GABAAR signaling adapts to optimize cortical functions.

Generation and propagation of bursts of activity in the developing basal ganglia

The neonatal brain is characterized by intermittent bursts of oscillatory activity interspersed by relative silence. Although well-characterized for many cortical areas, to what extent these propagate and interact with subcortical brain areas is largely unknown. Here, early network activity was recorded from the developing basal ganglia, including motor/somatosensory cortex, dorsal striatum, and intralaminar thalamus, during the first postnatal weeks in mice. An unsupervised detection and classification method revealed two main classes of bursting activity, namely spindle bursts and nested gamma spindle bursts, characterized by oscillatory activity at ~ 10 and ~ 30 Hz frequencies, respectively. These were reliably identified across all three brain regions and exhibited region-specific differences in their structural, spectral, and developmental characteristics. Bursts of the same type often co-occurred in different brain regions and coherence and cross-correlation analyses reveal dynamic developmental changes in their interactions. The strongest interactions were seen for cortex and striatum, from the first postnatal week onwards, and cortex appeared to drive burst events in subcortical regions. Together, these results provide the first detailed description of early network activity within the developing basal ganglia and suggest that cortex is one of the main drivers of activity in downstream nuclei during this postnatal period.

Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics

Understanding cortical function requires studying multiple scales: molecular, cellular, circuit, and behavioral. We develop a multiscale, biophysically detailed model of mouse primary motor cortex (M1) with over 10,000 neurons and 30 million synapses. Neuron types, densities, spatial distributions, morphologies, biophysics, connectivity, and dendritic synapse locations are constrained by experimental data. The model includes long-range inputs from seven thalamic and cortical regions and noradrenergic inputs. Connectivity depends on cell class and cortical depth at sublaminar resolution. The model accurately predicts in vivo layer- and cell-type-specific responses (firing rates and LFP) associated with behavioral states (quiet wakefulness and movement) and experimental manipulations (noradrenaline receptor blockade and thalamus inactivation). We generate mechanistic hypotheses underlying the observed activity and analyzed low-dimensional population latent dynamics. This quantitative theoretical framework can be used to integrate and interpret M1 experimental data and sheds light on the cell-type-specific multiscale dynamics associated with several experimental conditions and behaviors.

Foramen lacerum impingement of trigeminal nerve root as a rodent model for trigeminal neuralgia

Trigeminal neuralgia (TN) is a classic neuralgic pain condition with distinct clinical characteristics. Modeling TN in rodents is challenging. Recently, we found that a foramen in the rodent skull base, the foramen lacerum, provides direct access to the trigeminal nerve root. Using this access, we developed a foramen lacerum impingement of trigeminal nerve root (FLIT) model and observed distinct pain-like behaviors in rodents, including paroxysmal asymmetric facial grimaces, head tilt when eating, avoidance of solid chow, and lack of wood chewing. The FLIT model recapitulated key clinical features of TN, including lancinating pain-like behavior and dental pain-like behavior. Importantly, when compared with a trigeminal neuropathic pain model (infraorbital nerve chronic constriction injury [IoN-CCI]), the FLIT model was associated with significantly higher numbers of c-Fos-positive cells in the primary somatosensory cortex (S1), unraveling robust cortical activation in the FLIT model. On intravital 2-photon calcium imaging, synchronized S1 neural dynamics were present in the FLIT but not the IoN-CCI model, revealing differential implication of cortical activation in different pain models. Taken together, our results indicate that FLIT is a clinically relevant rodent model of TN that could facilitate pain research and therapeutics development.

Spatial Distribution of Inhibitory Innervations of Excitatory Pyramidal Cells by Major Interneuron Subtypes in the Auditory Cortex

Mental disorders, characterized by the National Institute of Mental Health as disruptions in neural circuitry, currently account for 13% of the global incidence of such disorders. An increasing number of studies suggest that imbalances between excitatory and inhibitory neurons in neural networks may be a crucial mechanism underlying mental disorders. However, the spatial distribution of inhibitory interneurons in the auditory cortex (ACx) and their relationship with excitatory pyramidal cells (PCs) remain elusive. In this study, we employed a combination of optogenetics, transgenic mice, and patch-clamp recording on brain slices to investigate the microcircuit characteristics of different interneurons (PV, SOM, and VIP) and the spatial pattern of inhibitory inhibition across layers 2/3 to 6 in the ACx. Our findings revealed that PV interneurons provide the strongest and most localized inhibition with no cross-layer innervation or layer specificity. Conversely, SOM and VIP interneurons weakly regulate PC activity over a broader range, exhibiting distinct spatial inhibitory preferences. Specifically, SOM inhibitions are preferentially found in deep infragranular layers, while VIP inhibitions predominantly occur in upper supragranular layers. PV inhibitions are evenly distributed across all layers. These results suggest that the input from inhibitory interneurons to PCs manifests in unique ways, ensuring that both strong and weak inhibitory inputs are evenly dispersed throughout the ACx, thereby maintaining a dynamic excitation-inhibition balance. Our findings contribute to understanding the spatial inhibitory characteristics of PCs and inhibitory interneurons in the ACx at the circuit level, which holds significant clinical implications for identifying and targeting abnormal circuits in auditory system diseases.

Correlated Somatosensory Input in Parvalbumin/Pyramidal Cells in Mouse Motor Cortex

In mammalian cortex, feedforward excitatory connections recruit feedforward inhibition. This is often carried by parvalbumin (PV+) interneurons, which may densely connect to local pyramidal (Pyr) neurons. Whether this inhibition affects all local excitatory cells indiscriminately or is targeted to specific subnetworks is unknown. Here, we test how feedforward inhibition is recruited by using two-channel circuit mapping to excite cortical and thalamic inputs to PV+ interneurons and Pyr neurons to mouse primary vibrissal motor cortex (M1). Single Pyr and PV+ neurons receive input from both cortex and thalamus. Connected pairs of PV+ interneurons and excitatory Pyr neurons receive correlated cortical and thalamic inputs. While PV+ interneurons are more likely to form local connections to Pyr neurons, Pyr neurons are much more likely to form reciprocal connections with PV+ interneurons that inhibit them. This suggests that Pyr and PV ensembles may be organized based on their local and long-range connections, an organization that supports the idea of local subnetworks for signal transduction and processing. Excitatory inputs to M1 can thus target inhibitory networks in a specific pattern which permits recruitment of feedforward inhibition to specific subnetworks within the cortical column.

Model-Based Approach Shows ON Pathway Afferents Elicit a Transient Decrease of V1 Responses

Neurons in the primary visual cortex (V1) receive excitation and inhibition from distinct parallel pathways processing lightness (ON) and darkness (OFF). V1 neurons overall respond more strongly to dark than light stimuli, consistent with a preponderance of darker regions in natural images, as well as human psychophysics. However, it has been unclear whether this "dark-dominance" is because of more excitation from the OFF pathway or more inhibition from the ON pathway. To understand the mechanisms behind dark-dominance, we record electrophysiological responses of individual simple-type V1 neurons to natural image stimuli and then train biologically inspired convolutional neural networks to predict the neurons' responses. Analyzing a sample of 71 neurons (in anesthetized, paralyzed cats of either sex) has revealed their responses to be more driven by dark than light stimuli, consistent with previous investigations. We show that this asymmetry is predominantly because of slower inhibition to dark stimuli rather than to stronger excitation from the thalamocortical OFF pathway. Consistent with dark-dominant neurons having faster responses than light-dominant neurons, we find dark-dominance to solely occur in the early latencies of neurons' responses. Neurons that are strongly dark-dominated also tend to be less orientation-selective. This novel approach gives us new insight into the dark-dominance phenomenon and provides an avenue to address new questions about excitatory and inhibitory integration in cortical neurons.SIGNIFICANCE STATEMENT Neurons in the early visual cortex respond on average more strongly to dark than to light stimuli, but the mechanisms behind this bias have been unclear. Here we address this issue by combining single-unit electrophysiology with a novel machine learning model to analyze neurons' responses to natural image stimuli in primary visual cortex. Using these techniques, we find slower inhibition to light than to dark stimuli to be the leading mechanism behind stronger dark responses. This slower inhibition to light might help explain other empirical findings, such as why orientation selectivity is weaker at earlier response latencies. These results demonstrate how imbalances in excitation versus inhibition can give rise to response asymmetries in cortical neuron responses.

Rostral and caudal basolateral amygdala engage distinct circuits in the prelimbic and infralimbic prefrontal cortex

Connections from the basolateral amygdala (BLA) to medial prefrontal cortex (PFC) regulate memory and emotion and become disrupted in neuropsychiatric disorders. The diverse roles attributed to interactions between the BLA and PFC may reflect multiple circuits nested within a wider network. To examine these circuits, we first used retrograde and anterograde anatomy to show that the rostral BLA (rBLA) and caudal BLA (cBLA) differentially project to prelimbic (PL) and infralimbic (IL) subregions of the mouse PFC. Using ex vivo whole-cell recordings and optogenetics, we then assessed which neuronal subtypes are targeted, showing that rBLA preferentially drives layer 2 (L2) cortico-amygdalar (CA) neurons in PL, whereas cBLA drives layer 5 (L5) pyramidal tract (PT) neurons in IL. We next combined in vivo silicon probe recordings and optogenetics to confirm that cBLA mainly influences IL L5, whereas rBLA primarily activates PL L2, but also evokes polysynaptic activity in PL L5. Lastly, we used soma-tagged optogenetics to explore the local circuits linking superficial and deep layers of PL, showing how rBLA can engage L2 CA neurons to impact L5 PT neuron activity. Together, our findings delineate how subregions of the BLA target distinct networks within the PFC and differentially influence output from PL and IL.

Functional interactions among neurons within single columns of macaque V1

Recent developments in high-density neurophysiological tools now make it possible to record from hundreds of single neurons within local, highly interconnected neural networks. Among the many advantages of such recordings is that they dramatically increase the quantity of identifiable, functional interactions between neurons thereby providing an unprecedented view of local circuits. Using high-density, Neuropixels recordings from single neocortical columns of primary visual cortex in nonhuman primates, we identified 1000s of functionally interacting neuronal pairs using established crosscorrelation approaches. Our results reveal clear and systematic variations in the synchrony and strength of functional interactions within single cortical columns. Despite neurons residing within the same column, both measures of interactions depended heavily on the vertical distance separating neuronal pairs, as well as on the similarity of stimulus tuning. In addition, we leveraged the statistical power afforded by the large numbers of functionally interacting pairs to categorize interactions between neurons based on their crosscorrelation functions. These analyses identified distinct, putative classes of functional interactions within the full population. These classes of functional interactions were corroborated by their unique distributions across defined laminar compartments and were consistent with known properties of V1 cortical circuitry, such as the lead-lag relationship between simple and complex cells. Our results provide a clear proof-of-principle for the use of high-density neurophysiological recordings to assess circuit-level interactions within local neuronal networks.

Organization of Cortical and Thalamic Input to Inhibitory Neurons in Mouse Motor Cortex

Intracortical inhibition in motor cortex (M1) regulates movement and motor learning. If cortical and thalamic inputs target different inhibitory cell types in different layers, then these afferents may play different roles in regulating M1 output. Using mice of both sexes, we quantified input to two main classes of M1 interneurons, parvalbumin+ (PV+) cells and somatostatin+ (SOM+) cells, using monosynaptic rabies tracing. We then compared anatomic and functional connectivity based on synaptic strength from sensory cortex and thalamus. Functionally, each input innervated M1 interneurons with a unique laminar profile. Different interneuron types were excited in a distinct, complementary manner, suggesting feedforward inhibition proceeds selectively via distinct circuits. Specifically, somatosensory cortex (S1) inputs primarily targeted PV+ neurons in upper layers (L2/3) but SOM+ neurons in middle layers (L5). Somatosensory thalamus [posterior nucleus (PO)] inputs targeted PV+ neurons in middle layers (L5). In contrast to sensory cortical areas, thalamic input to SOM+ neurons was equivalent to that of PV+ neurons. Thus, long-range excitatory inputs target inhibitory neurons in an area and a cell type-specific manner, which contrasts with input to neighboring pyramidal cells. In contrast to feedforward inhibition providing generic inhibitory tone in cortex, circuits are selectively organized to recruit inhibition matched to incoming excitatory circuits.SIGNIFICANCE STATEMENT M1 integrates sensory information and frontal cortical inputs to plan and control movements. Although inputs to excitatory cells are described, the synaptic circuits by which these inputs drive specific types of M1 interneurons are unknown. Anatomical results with rabies tracing and physiological quantification of synaptic strength shows that two main classes of inhibitory cells (PV+ and SOM+ interneurons) both receive substantial cortical and thalamic input, in contrast to interneurons in sensory areas (where thalamic input strongly prefers PV+ interneurons). Further, each input studied targets PV+ and SOM+ interneurons in a different fashion, suggesting that separate, specific circuits exist for recruitment of feedforward inhibition.

Functional and structural features of L2/3 pyramidal cells continuously covary with pial depth in mouse visual cortex

Pyramidal cells of neocortical layer 2/3 (L2/3 PyrCs) integrate signals from numerous brain areas and project throughout the neocortex. These PyrCs show pial depth-dependent functional and structural specializations, indicating participation in different functional microcircuits. However, whether these depth-dependent differences result from separable PyrC subtypes or whether their features display a continuum correlated with pial depth is unknown. Here, we assessed the stimulus selectivity, electrophysiological properties, dendritic morphology, and excitatory and inhibitory connectivity across the depth of L2/3 in the binocular visual cortex of mice. We find that the apical, but not the basal dendritic tree structure, varies with pial depth, which is accompanied by variation in subthreshold electrophysiological properties. Lower L2/3 PyrCs receive increased input from L4, while upper L2/3 PyrCs receive a larger proportion of intralaminar input. In vivo calcium imaging revealed a systematic change in visual responsiveness, with deeper PyrCs showing more robust responses than superficial PyrCs. Furthermore, deeper PyrCs are more driven by contralateral than ipsilateral eye stimulation. Importantly, the property value transitions are gradual, and L2/3 PyrCs do not display discrete subtypes based on these parameters. Therefore, L2/3 PyrCs' multiple functional and structural properties systematically correlate with their depth, forming a continuum rather than discrete subtypes.

Rate and oscillatory switching dynamics of a multilayer visual microcircuit model

The neocortex is organized around layered microcircuits consisting of a variety of excitatory and inhibitory neuronal types which perform rate- and oscillation-based computations. Using modeling, we show that both superficial and deep layers of the primary mouse visual cortex implement two ultrasensitive and bistable switches built on mutual inhibitory connectivity motives between somatostatin, parvalbumin, and vasoactive intestinal polypeptide cells. The switches toggle pyramidal neurons between high and low firing rate states that are synchronized across layers through translaminar connectivity. Moreover, inhibited and disinhibited states are characterized by low- and high-frequency oscillations, respectively, with layer-specific differences in frequency and power which show asymmetric changes during state transitions. These findings are consistent with a number of experimental observations and embed firing rate together with oscillatory changes within a switch interpretation of the microcircuit.

Cascaded normalizations for spatial integration in the primary visual cortex of primates

Spatial integration of visual information is an important function in the brain. However, neural computation for spatial integration in the visual cortex remains unclear. In this study, we recorded laminar responses in V1 of awake monkeys driven by visual stimuli with grating patches and annuli of different sizes. We find three important response properties related to spatial integration that are significantly different between input and output layers: neurons in output layers have stronger surround suppression, smaller receptive field (RF), and higher sensitivity to grating annuli partially covering their RFs. These interlaminar differences can be explained by a descriptive model composed of two global divisions (normalization) and a local subtraction. Our results suggest suppressions with cascaded normalizations (CNs) are essential for spatial integration and laminar processing in the visual cortex. Interestingly, the features of spatial integration in convolutional neural networks, especially in lower layers, are different from our findings in V1.

Serotonergic regulation of bipolar cell survival in the developing cerebral cortex

One key factor underlying the functional balance of cortical networks is the ratio of excitatory and inhibitory neurons. The mechanisms controlling the ultimate number of interneurons are beginning to be elucidated, but to what extent similar principles govern the survival of the large diversity of cortical inhibitory cells remains to be investigated. Here, we investigate the mechanisms regulating developmental cell death in neurogliaform cells, bipolar cells, and basket cells, the three main populations of interneurons originating from the caudal ganglionic eminence and the preoptic region. We found that all three subclasses of interneurons undergo activity-dependent programmed cell death. However, while neurogliaform cells and basket cells require glutamatergic transmission to survive, the final number of bipolar cells is instead modulated by serotonergic signaling. Together, our results demonstrate that input-specific modulation of neuronal activity controls the survival of cortical interneurons during the critical period of programmed cell death.

Intracortical current steering shifts the location of evoked neural activity

Objective.Intracortical visual prostheses are being developed to restore sight in people who are blind. The resolution of artificial vision is dictated by the location, proximity and number of electrodes implanted in the brain. However, increasing electrode count and proximity is traded off against tissue damage. Hence, new stimulation methods are needed that can improve the resolution of artificial vision without increasing the number of electrodes. We investigated whether a technique known as current steering can improve the resolution of artificial vision provided by intracortical prostheses without increasing the number of physical electrodes in the brain.Approach.We explored how the locus of neuronal activation could be steered when low amplitude microstimulation was applied simultaneously to two intracortical electrodes. A 64-channel, four-shank electrode array was implanted into the visual cortex of rats (n= 7). The distribution of charge ranged from single-electrode stimulation (100%:0%) to an equal distribution between the two electrodes (50%:50%), thereby steering the current between the physical electrodes. The stimulating electrode separation varied between 300 and 500μm. The peak of the evoked activity was defined as the 'virtual electrode' location.Main results.Current steering systematically shifted the virtual electrode on average between the stimulating electrodes as the distribution of charge was moved from one stimulating electrode to another. This effect was unclear in single trials due to the limited sampling of neurons. A model that scales the cortical response to each physical electrode when stimulated in isolation predicts the evoked virtual electrode response. Virtual electrodes were found to elicit a neural response as effectively and predictably as physical electrodes within cortical tissue on average.Significance.Current steering could be used to increase the resolution of intracortical electrode arrays without altering the number of physical electrodes which will reduce neural tissue damage, power consumption and potential heat dispersion issues.

Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure

Simulating the brain-body-environment trinity in closed loop is an attractive proposal to investigate how perception, motor activity and interactions with the environment shape brain activity, and vice versa. The relevance of this embodied approach, however, hinges entirely on the modeled complexity of the various simulated phenomena. In this article, we introduce a software framework that is capable of simulating large-scale, biologically realistic networks of spiking neurons embodied in a biomechanically accurate musculoskeletal system that interacts with a physically realistic virtual environment. We deploy this framework on the high performance computing resources of the EBRAINS research infrastructure and we investigate the scaling performance by distributing computation across an increasing number of interconnected compute nodes. Our architecture is based on requested compute nodes as well as persistent virtual machines; this provides a high-performance simulation environment that is accessible to multi-domain users without expert knowledge, with a view to enable users to instantiate and control simulations at custom scale via a web-based graphical user interface. Our simulation environment, entirely open source, is based on the Neurorobotics Platform developed in the context of the Human Brain Project, and the NEST simulator. We characterize the capabilities of our parallelized architecture for large-scale embodied brain simulations through two benchmark experiments, by investigating the effects of scaling compute resources on performance defined in terms of experiment runtime, brain instantiation and simulation time. The first benchmark is based on a large-scale balanced network, while the second one is a multi-region embodied brain simulation consisting of more than a million neurons and a billion synapses. Both benchmarks clearly show how scaling compute resources improves the aforementioned performance metrics in a near-linear fashion. The second benchmark in particular is indicative of both the potential and limitations of a highly distributed simulation in terms of a trade-off between computation speed and resource cost. Our simulation architecture is being prepared to be accessible for everyone as an EBRAINS service, thereby offering a community-wide tool with a unique workflow that should provide momentum to the investigation of closed-loop embodiment within the computational neuroscience community.

Computational Concepts for Reconstructing and Simulating Brain Tissue

It has previously been shown that it is possible to derive a new class of biophysically detailed brain tissue models when one computationally analyzes and exploits the interdependencies or the multi-modal and multi-scale organization of the brain. These reconstructions, sometimes referred to as digital twins, enable a spectrum of scientific investigations. Building such models has become possible because of increase in quantitative data but also advances in computational capabilities, algorithmic and methodological innovations. This chapter presents the computational science concepts that provide the foundation to the data-driven approach to reconstructing and simulating brain tissue as developed by the EPFL Blue Brain Project, which was originally applied to neocortical microcircuitry and extended to other brain regions. Accordingly, the chapter covers aspects such as a knowledge graph-based data organization and the importance of the concept of a dataset release. We illustrate algorithmic advances in finding suitable parameters for electrical models of neurons or how spatial constraints can be exploited for predicting synaptic connections. Furthermore, we explain how in silico experimentation with such models necessitates specific addressing schemes or requires strategies for an efficient simulation. The entire data-driven approach relies on the systematic validation of the model. We conclude by discussing complementary strategies that not only enable judging the fidelity of the model but also form the basis for its systematic refinements.

Transcranial Magnetic Stimulation and Neocortical Neurons: The Micro-Macro Connection

Understanding the operation of cortical circuits is an important and necessary task in both neuroscience and neurorehabilitation. The functioning of the neocortex results from integrative neuronal activity, which can be probed non-invasively by transcranial magnetic stimulation (TMS). Despite a clear indication of the direct involvement of cortical neurons in TMS, no explicit connection model has been made between the microscopic neuronal landscape and the macroscopic TMS outcome. Here we have performed an integrative review of multidisciplinary evidence regarding motor cortex neurocytology and TMS-related neurophysiology with the aim of elucidating the micro–macro connections underlying TMS. Neurocytological evidence from animal and human studies has been reviewed to describe the landscape of the cortical neurons covering the taxonomy, morphology, circuit wiring, and excitatory–inhibitory balance. Evidence from TMS studies in healthy humans is discussed, with emphasis on the TMS pulse and paradigm selectivity that reflect the underlying neural circuitry constitution. As a result, we propose a preliminary neuronal model of the human motor cortex and then link the TMS mechanisms with the neuronal model by stimulus intensity, direction of induced current, and paired-pulse timing. As TMS bears great developmental potential for both a probe and modulator of neural network activity and neurotransmission, the connection model will act as a foundation for future combined studies of neurocytology and neurophysiology, as well as the technical advances and application of TMS.

Synaptic connectivity to L2/3 of primary visual cortex measured by two-photon optogenetic stimulation

Understanding cortical microcircuits requires thorough measurement of physiological properties of synaptic connections formed within and between diverse subclasses of neurons. Towards this goal, we combined spatially precise optogenetic stimulation with multicellular recording to deeply characterize intralaminar and translaminar monosynaptic connections to supragranular (L2/3) neurons in the mouse visual cortex. The reliability and specificity of multiphoton optogenetic stimulation were measured across multiple Cre lines, and measurements of connectivity were verified by comparison to paired recordings and targeted patching of optically identified presynaptic cells. With a focus on translaminar pathways, excitatory and inhibitory synaptic connections from genetically defined presynaptic populations were characterized by their relative abundance, spatial profiles, strength, and short-term dynamics. Consistent with the canonical cortical microcircuit, layer 4 excitatory neurons and interneurons within L2/3 represented the most common sources of input to L2/3 pyramidal cells. More surprisingly, we also observed strong excitatory connections from layer 5 intratelencephalic neurons and potent translaminar inhibition from multiple interneuron subclasses. The hybrid approach revealed convergence to and divergence from excitatory and inhibitory neurons within and across cortical layers. Divergent excitatory connections often spanned hundreds of microns of horizontal space. In contrast, divergent inhibitory connections were more frequently measured from postsynaptic targets near each other.

TMS with fast and accurate electronic control: Measuring the orientation sensitivity of corticomotor pathways

BACKGROUND

Transcranial magnetic stimulation (TMS) coils allow only a slow, mechanical adjustment of the stimulating electric field (E-field) orientation in the cerebral tissue. Fast E-field control is needed to synchronize the stimulation with the ongoing brain activity. Also, empirical models that fully describe the relationship between evoked responses and the stimulus orientation and intensity are still missing.

OBJECTIVE

We aimed to (1) develop a TMS transducer for manipulating the E-field orientation electronically with high accuracy at the neuronally meaningful millisecond-level time scale and (2) devise and validate a physiologically based model describing the orientation selectivity of neuronal excitability.

METHODS

We designed and manufactured a two-coil TMS transducer. The coil windings were computed with a minimum-energy optimization procedure, and the transducer was controlled with our custom-made electronics. The electronic E-field control was verified with a TMS characterizer. The motor evoked potential amplitude and latency of a hand muscle were mapped in 3° steps of the stimulus orientation in 16 healthy subjects for three stimulation intensities. We fitted a logistic model to the motor response amplitude.

RESULTS

The two-coil TMS transducer allows one to manipulate the pulse orientation accurately without manual coil movement. The motor response amplitude followed a logistic function of the stimulus orientation; this dependency was strongly affected by the stimulus intensity.

CONCLUSION

The developed electronic control of the E-field orientation allows exploring new stimulation paradigms and probing neuronal mechanisms. The presented model helps to disentangle the neuronal mechanisms of brain function and guide future non-invasive stimulation protocols.

Contribution of animal models toward understanding resting state functional connectivity

Functional connectivity, which reflects the spatial and temporal organization of intrinsic activity throughout the brain, is one of the most studied measures in human neuroimaging research. The noninvasive acquisition of resting state functional magnetic resonance imaging (rs-fMRI) allows the characterization of features designated as functional networks, functional connectivity gradients, and time-varying activity patterns that provide insight into the intrinsic functional organization of the brain and potential alterations related to brain dysfunction. Functional connectivity, hence, captures dimensions of the brain's activity that have enormous potential for both clinical and preclinical research. However, the mechanisms underlying functional connectivity have yet to be fully characterized, hindering interpretation of rs-fMRI studies. As in other branches of neuroscience, the identification of the neurophysiological processes that contribute to functional connectivity largely depends on research conducted on laboratory animals, which provide a platform where specific, multi-dimensional investigations that involve invasive measurements can be carried out. These highly controlled experiments facilitate the interpretation of the temporal correlations observed across the brain. Indeed, information obtained from animal experimentation to date is the basis for our current understanding of the underlying basis for functional brain connectivity. This review presents a compendium of some of the most critical advances in the field based on the efforts made by the animal neuroimaging community.

A model integrating multiple processes of synchronization and coherence for information instantiation within a cortical area

What is the form of dynamic, e.g., sensory, information in the mammalian cortex? Information in the cortex is modeled as a coherence map of a mixed chimera state of synchronous, phasic, and disordered minicolumns. The theoretical model is built on neurophysiological evidence. Complex spatiotemporal information is instantiated through a system of interacting biological processes that generate a synchronized cortical area, a coherent aperture. Minicolumn elements are grouped in macrocolumns in an array analogous to a phased-array radar, modeled as an aperture, a "hole through which radiant energy flows." Coherence maps in a cortical area transform inputs from multiple sources into outputs to multiple targets, while reducing complexity and entropy. Coherent apertures can assume extremely large numbers of different information states as coherence maps, which can be communicated among apertures with corresponding very large bandwidths. The coherent aperture model incorporates considerable reported research, integrating five conceptually and mathematically independent processes: 1) a damped Kuramoto network model, 2) a pumped area field potential, 3) the gating of nearly coincident spikes, 4) the coherence of activity across cortical lamina, and 5) complex information formed through functions in macrocolumns. Biological processes and their interactions are described in equations and a functional circuit such that the mathematical pieces can be assembled the same way the neurophysiological ones are. The model can be conceptually convolved over the specifics of local cortical areas within and across species. A coherent aperture becomes a node in a graph of cortical areas with a corresponding distribution of information.

Up and Down States During Slow Oscillations in Slow-Wave Sleep and Different Levels of Anesthesia

Slow oscillations are a pattern of synchronized network activity generated by the cerebral cortex. They consist of Up and Down states, which are periods of activity interspersed with periods of silence, respectively. However, even when this is a unique dynamic regime of transitions between Up and Down states, this pattern is not constant: there is a range of oscillatory frequencies (0.1-4 Hz), and the duration of Up vs. Down states during the cycles is variable. This opens many questions. Is there a constant relationship between the duration of Up and Down states? How much do they vary across conditions and oscillatory frequencies? Are there different sub regimes within the slow oscillations? To answer these questions, we aimed to explore a concrete aspect of slow oscillations, Up and Down state durations, across three conditions: deep anesthesia, light anesthesia, and slow-wave sleep (SWS), in the same chronically implanted rats. We found that light anesthesia and SWS have rather similar properties, occupying a small area of the Up and Down state duration space. Deeper levels of anesthesia occupy a larger region of this space, revealing that a large variety of Up and Down state durations can emerge within the slow oscillatory regime. In a network model, we investigated the network parameters that can explain the different points within our bifurcation diagram in which slow oscillations are expressed.

The CSF-Contacting Nucleus Receives Anatomical Inputs From the Cerebral Cortex: A Combination of Retrograde Tracing and 3D Reconstruction Study in Rat

Objective

This study aimed to investigate the direct monosynaptic projections from cortical functional regions to the cerebrospinal fluid (CSF)-contacting nucleus for understanding the functions of the CSF-contacting nucleus.

Methods

The Sprague-Dawley rats received cholera toxin B subunit (CB) injections into the CSF-contacting nucleus. After 7-10 days of survival time, the rats were perfused, and the whole brain and spinal cord were sliced under a freezing microtome at 40 μm. All sections were treated with the CB immunofluorescence reaction. The retrogradely labeled neurons in different cortical areas were revealed under a confocal microscope. The distribution features were further illustrated under 3D reconstruction.

Results

The retrogradely labeled neurons were identified in the olfactory, orbital, cingulate, insula, retrosplenial, somatosensory, motor, visual, auditory, association, rhinal, and parietal cortical areas. A total of 12 functional areas and 34 functional subregions showed projections to the CSF-contacting nucleus in different cell intensities.

Conclusion

According to the connectivity patterns, we conclude that the CSF-contacting nucleus participates in cognition, emotion, pain, visceral activity, etc. The present study firstly reveals the cerebral cortex→CSF-contacting nucleus connections, which implies the multiple functions of this special nucleus in neural and body fluid regulations.

Prior expectations evoke stimulus-specific activity in the deep layers of the primary visual cortex

The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus-specific activity selectively in the deep layers of the primary visual cortex (V1). These findings are in line with predictive processing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and thereby shed light on the computational architecture of cortex.

The way we perceive the world is strongly influenced by our expectations, but the neural circuitry through which the brain achieves this remains unknown. A study using ultra-high field fMRI reveals that prior expectations evoke stimulus-specific signals in the deep layers of the primary visual cortex.

Primary motor cortex in Parkinson's disease: Functional changes and opportunities for neurostimulation

Movement abnormalities of Parkinson's disease (PD) arise from disordered neural activity in multiple interconnected brain structures. The planning and execution of movement requires recruitment of a heterogeneous collection of pyramidal projection neurons in the primary motor cortex (M1). The neural representations of movement in M1 single-cell and field potential recordings are directly and indirectly influenced by the midbrain dopaminergic neurons that degenerate in PD. This review examines M1 functional alterations in PD as uncovered by electrophysiological recordings and neurostimulation studies in patients and experimental animal models. Dysfunction of the parkinsonian M1 depends on the severity and/or duration of dopamine-depletion and the species examined, and is expressed as alterations in movement-related firing dynamics; functional reorganisation of local circuits; and changes in field potential beta oscillations. Neurostimulation methods that modulate M1 activity directly (e.g., transcranial magnetic stimulation) or indirectly (subthalamic nucleus deep brain stimulation) improve motor function in PD patients, showing that targeted neuromodulation of M1 is a realistic therapy. We argue that the therapeutic profile of M1 neurostimulation is likely to be greatly enhanced with alternative technologies that permit cell-type specific control and incorporate feedback from electrophysiological biomarkers measured locally.

A Minimal Biophysical Model of Neocortical Pyramidal Cells: Implications for Frontal Cortex Microcircuitry and Field Potential Generation

Ca²⁺ spikes initiated in the distal trunk of layer 5 pyramidal cells (PCs) underlie nonlinear dynamic changes in the gain of cellular response, critical for top-down control of cortical processing. Detailed models with many compartments and dozens of ionic channels can account for this Ca²⁺ spike-dependent gain and associated critical frequency. However, current models do not account for all known Ca²⁺-dependent features. Previous attempts to include more features have required increasing complexity, limiting their interpretability and utility for studying large population dynamics. We overcome these limitations in a minimal two-compartment biophysical model. In our model, a basal-dendrites/somatic compartment included fast-inactivating Na⁺ and delayed-rectifier K⁺ conductances, while an apical-dendrites/trunk compartment included persistent Na⁺, hyperpolarization-activated cation (I _h ), slow-inactivating K⁺, muscarinic K⁺, and Ca²⁺ L-type. The model replicated the Ca²⁺ spike morphology and its critical frequency plus three other defining features of layer 5 PC synaptic integration: linear frequency-current relationships, back-propagation-activated Ca²⁺ spike firing, and a shift in the critical frequency by blocking I _h Simulating 1000 synchronized layer 5 PCs, we reproduced the current source density patterns evoked by Ca²⁺ spikes and describe resulting medial-frontal EEG on a male macaque monkey. We reproduced changes in the current source density when I _h was blocked. Thus, a two-compartment model with five crucial ionic currents in the apical dendrites reproduces all features of these neurons. We discuss the utility of this minimal model to study the microcircuitry of agranular areas of the frontal lobe involved in cognitive control and responsible for event-related potentials, such as the error-related negativity.SIGNIFICANCE STATEMENT A minimal model of layer 5 pyramidal cells replicates all known features crucial for distal synaptic integration in these neurons. By redistributing voltage-gated and returning transmembrane currents in the model, we establish a theoretical framework for the investigation of cortical microcircuit contribution to intracranial local field potentials and EEG. This tractable model will enable biophysical evaluation of multiscale electrophysiological signatures and computational investigation of cortical processing.

The Spatial Extent of Optogenetic Silencing in Transgenic Mice Expressing Channelrhodopsin in Inhibitory Interneurons

Optogenetic stimulation of inhibitory interneurons has become a commonly used strategy for silencing neuronal activity. This is typically achieved using transgenic mice expressing excitatory opsins in inhibitory interneurons throughout the brain, raising the question of how spatially extensive the resulting inhibition is. Here, we characterize neuronal silencing in VGAT-ChR2 mice, which express channelrhodopsin-2 in inhibitory interneurons, as a function of light intensity and distance from the light source in several cortical and subcortical regions. We show that light stimulation, even at relatively low intensities, causes inhibition not only in brain regions targeted for silencing but also in their subjacent areas. In contrast, virus-mediated expression of an inhibitory opsin enables robust silencing that is restricted to the region of opsin expression. Our results reveal important constraints on using inhibitory interneuron activation to silence neuronal activity and emphasize the necessity of carefully controlling light stimulation parameters when using this silencing strategy.

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

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

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.

Functional interrogation of neural circuits with virally transmitted optogenetic tools

The vertebrate brain comprises a plethora of cell types connected by intertwined pathways. Optogenetics enriches the neuroscientific tool set for disentangling these neuronal circuits in a manner which exceeds the spatio-temporal precision of previously existing techniques. Technically, optogenetics can be divided in three types of optical and genetic combinations: (1) it is primarily understood as the manipulation of the activity of genetically modified cells (typically neurons) with light, i.e. optical actuators. (2) A second combination refers to visualizing the activity of genetically modified cells (again typically neurons), i.e. optical sensors. (3) A completely different interpretation of optogenetics refers to the light activated expression of a genetically induced construct. Here, we focus on the first two types of optogenetics, i.e. the optical actuators and sensors in an attempt to give an overview into the topic. We first cover methods to express opsins into neurons and introduce strategies of targeting specific neuronal populations in different animal species. We then summarize combinations of optogenetics with behavioral read out and neuronal imaging. Finally, we give an overview of the current state-of-the-art and an outlook on future perspectives.

Circuitry Underlying Experience-Dependent Plasticity in the Mouse Visual System

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

The human motor cortex microcircuit: insights for neurodegenerative disease

The human motor cortex comprises a microcircuit of five interconnected layers with different cell types. In this Review, we use a layer-specific and cell-specific approach to integrate physiological accounts of this motor cortex microcircuit with the pathophysiology of neurodegenerative diseases affecting motor functions. In doing so we can begin to link motor microcircuit pathology to specific disease stages and clinical phenotypes. Based on microcircuit physiology, we can make future predictions of axonal loss and microcircuit dysfunction. With recent advances in high-resolution neuroimaging we can then test these predictions in humans in vivo, providing mechanistic insights into neurodegenerative disease.

Computational Investigation of Contributions from Different Subtypes of Interneurons in Prefrontal Cortex for Information Maintenance

Interneurons play crucial roles in neocortex associated with high-level cognitive functions; however, the specific division of labor is still under investigation. Interneurons are exceptionally diverse in their morphological appearance and functional properties. In this study, we modify a prefrontal multicolumn circuit in which five subtypes of inhibitory interneurons play distinct roles in the maintenance of transient information. These interneurons are classified according to the extending range of axonal projections. Our work simplifies the division of labor between different types of interneurons for the maintenance of information and the principle of functional redundancy of the brain from the perspective of computational modeling. This model presents a framework to understand the cooperation between different interneurons in a recurrent cortical circuit.

Enhancer-Driven Gene Expression (EDGE) enables the generation of cell type specific tools for the analysis of neural circuits

As in all circuits, fully understanding how neural circuits operate requires the ability to specifically manipulate individual circuit elements, i.e. particular neuronal cell types. While recent years saw the development of molecular genetic tools allowing one to control and monitor neuronal activity, progress is limited by the ability to express such transgenes specifically enough. This goal is complicated by the fact that we are only beginning to understand how many cell types exist in the mammalian brain. Obtaining neuronal cell type-specific expression requires co-opting the genetic machinery which specifies their striking diversity, typically done by making transgenic animals using promoters expressing in neurons. However, while the vast majority of genes express in the brain, they almost always express in multiple cell types, meaning native promoters are not specific enough. We have recently taken a new approach to increase the specificity of transgene expression based upon identifying the distal cis-regulatory genomic elements (i.e. enhancers) uniquely active in a brain region and combining them with a heterologous minimal promoter. Termed Enhancer-Driven Gene Expression (EDGE), it allows for the generation of transgenic animals targeting the cell types of any brain region with far greater specificity than can be obtained with native promoters. Moreover, their small size allows for the generation of cell-specific viral vectors, conceivably enabling circuit-specific manipulations to any species.

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

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

Functional Logic of Layer 2/3 Inhibitory Connectivity in the Ferret Visual Cortex

Understanding how cortical inhibition shapes circuit function requires identifying the connectivity rules relating the response properties of inhibitory interneurons and their postsynaptic targets. Here we explore the orientation tuning of layer 2/3 inhibitory inputs in the ferret visual cortex using a combination of in vivo axon imaging, functional input mapping, and physiology. Inhibitory boutons exhibit robust orientation-tuned responses with preferences that can differ significantly from the cortical column in which they reside. Inhibitory input fields measured with patterned optogenetic stimulation and intracellular recordings revealed that these inputs originate from a wide range of orientation domains, inconsistent with a model of co-tuned inhibition and excitation. Intracellular synaptic conductance measurements confirm that individual neurons can depart from a co-tuned regime. Our results argue against a simple rule for the arrangement of inhibitory inputs supplied by layer 2/3 circuits and suggest that heterogeneity in presynaptic inhibitory networks contributes to neural response properties.

Unlimited Genetic Switches for Cell-Type-Specific Manipulation

Gaining independent genetic access to discrete cell types is critical to interrogate their biological functions as well as to deliver precise gene therapy. Transcriptomics has allowed us to profile cell populations with extraordinary precision, revealing that cell types are typically defined by a unique combination of genetic markers. Given the lack of adequate tools to target cell types based on multiple markers, most cell types remain inaccessible to genetic manipulation. Here we present CaSSA, a platform to create unlimited genetic switches based on CRISPR/Cas9 (Ca) and the DNA repair mechanism known as single-strand annealing (SSA). CaSSA allows engineering of independent genetic switches, each responding to a specific gRNA. Expressing multiple gRNAs in specific patterns enables multiplex cell-type-specific manipulations and combinatorial genetic targeting. CaSSA is a new genetic tool that conceptually works as an unlimited number of recombinases and will facilitate genetic access to cell types in diverse organisms.

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.

Precise Long-Range Microcircuit-to-Microcircuit Communication Connects the Frontal and Sensory Cortices in the Mammalian Brain

The frontal area of the cerebral cortex provides long-range inputs to sensory areas to modulate neuronal activity and information processing. These long-range circuits are crucial for accurate sensory perception and complex behavioral control; however, little is known about their precise circuit organization. Here we specifically identified the presynaptic input neurons to individual excitatory neuron clones as a unit that constitutes functional microcircuits in the mouse sensory cortex. Interestingly, the long-range input neurons in the frontal but not contralateral sensory area are spatially organized into discrete vertical clusters and preferentially form synapses with each other over nearby non-input neurons. Moreover, the assembly of distant presynaptic microcircuits in the frontal area depends on the selective synaptic communication of excitatory neuron clones in the sensory area that provide inputs to the frontal area. These findings suggest that highly precise long-range reciprocal microcircuit-to-microcircuit communication mediates frontal-sensory area interactions in the mammalian cortex.

Role of the inhibitory system in shaping the BOLD fMRI response

The shape of the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal can vary considerably even across structures of the same sensory pathway. Here, we characterized the temporal behavior of the stimulus-evoked BOLD response in the primary cortical and subcortical regions of the visual and somatosensory whisker systems in awake rabbits. Despite similar BOLD responses in the thalamic nuclei, considerable differences in shape and duration emerged between the sensory cortices. Whereas the BOLD response in the whisker barrel cortex (WBC) was non-adaptive, BOLD in the visual cortex (V1) showed adaptation similar to simultaneously-recorded LFP and single unit activity. Analysis of baseline neuronal activity revealed significantly lower firing rates in V1 vs. WBC. We hypothesized that these changes point to region-dependent differences in the inhibitory systems which shape the hemodynamic response in each structure. To test the effect of neuronal baseline level inhibition on the BOLD signal shape, we locally injected the GABA_A agonist muscimol in WBC. Adaptation emerged in the BOLD response after injection, along with an overall decrease in baseline firing rate. These findings point to the importance of region-specific inhibitory shaping in determining the temporal behavior of the BOLD response in different brain areas.

Perturbing low dimensional activity manifolds in spiking neuronal networks

Several recent studies have shown that neural activity in vivo tends to be constrained to a low-dimensional manifold. Such activity does not arise in simulated neural networks with homogeneous connectivity and it has been suggested that it is indicative of some other connectivity pattern in neuronal networks. In particular, this connectivity pattern appears to be constraining learning so that only neural activity patterns falling within the intrinsic manifold can be learned and elicited. Here, we use three different models of spiking neural networks (echo-state networks, the Neural Engineering Framework and Efficient Coding) to demonstrate how the intrinsic manifold can be made a direct consequence of the circuit connectivity. Using this relationship between the circuit connectivity and the intrinsic manifold, we show that learning of patterns outside the intrinsic manifold corresponds to much larger changes in synaptic weights than learning of patterns within the intrinsic manifold. Assuming larger changes to synaptic weights requires extensive learning, this observation provides an explanation of why learning is easier when it does not require the neural activity to leave its intrinsic manifold.

Thalamocortical dynamics underlying spontaneous transitions in beta power in Parkinsonism

Parkinson's disease (PD) is a neurodegenerative condition in which aberrant oscillatory synchronization of neuronal activity at beta frequencies (15–35 Hz) across the cortico-basal ganglia-thalamocortical circuit is associated with debilitating motor symptoms, such as bradykinesia and rigidity. Mounting evidence suggests that the magnitude of beta synchrony in the parkinsonian state fluctuates over time, but the mechanisms by which thalamocortical circuitry regulates the dynamic properties of cortical beta in PD are poorly understood. Using the recently developed generic Dynamic Causal Modelling (DCM) framework, we recursively optimized a set of plausible models of the thalamocortical circuit (n = 144) to infer the neural mechanisms that best explain the transitions between low and high beta power states observed in recordings of field potentials made in the motor cortex of anesthetized Parkinsonian rats. Bayesian model comparison suggests that upregulation of cortical rhythmic activity in the beta-frequency band results from changes in the coupling strength both between and within the thalamus and motor cortex. Specifically, our model indicates that high levels of cortical beta synchrony are mainly achieved by a delayed (extrinsic) input from thalamic relay cells to deep pyramidal cells and a fast (intrinsic) input from middle pyramidal cells to superficial pyramidal cells. From a clinical perspective, our study provides insights into potential therapeutic strategies that could be utilized to modulate the network mechanisms responsible for the enhancement of cortical beta in PD. Specifically, we speculate that cortical stimulation aimed to reduce the enhanced excitatory inputs to either the superficial or deep pyramidal cells could be a potential non-invasive therapeutic strategy for PD.

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Coupling changes within and between circuit nodes lead to cortical beta enhancement.

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Input propagation delays play a crucial role in the up-regulation of cortical beta.

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Beta power could be modulated by altering lamina specific inputs.

Synaptic mechanisms underlying the intense firing of neocortical layer 5B pyramidal neurons in response to cortico-cortical inputs

In the neocortex, large layer 5B pyramidal neurons implement a high-density firing code. In contrast, other subtypes of pyramidal neurons, including those in layer 2/3, are functionally characterized by their sparse firing rate. Here, we investigate the synaptic basis of this behavior by comparing the properties of the postsynaptic responses evoked by cortical inputs in layer 5B and layer 2/3 pyramidal neurons in vitro. We demonstrate that a major determinant of the larger responsiveness of layer 5B with respect to layer 2/3 pyramidal neurons is the different properties in their inhibitory postsynaptic currents (IPSCs): layer 5B pyramidal neurons have IPSCs of lower amplitude and the temporal delay between the excitatory and inhibitory synaptic components is also larger in these cells. Our data also suggest that this difference depends on the lower gain of the cortical response of layer 5 parvalbumin-positive fast-spiking (PV-FS) interneurons with respect to PV-FS cells from layer 2/3. We propose that, while superficial PV-FS interneurons are well suited to provide a powerful feed-forward inhibitory control of pyramidal neuron responses, layer 5 PV-FS interneurons are mainly engaged in a feedback inhibitory loop and only after a substantial recruitment of surrounding pyramidal cells do they respond to an external input.