Cracking the Function of Layers in the Sensory Cortex

Lateral inhibition in V1 controls neural and perceptual contrast sensitivity

Lateral inhibition is a central principle in sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. However, the neurons, computations and mechanisms underlying cortical lateral inhibition remain debated, and its importance for perception remains unknown. Here we show that lateral inhibition from parvalbumin neurons in mouse primary visual cortex reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from somatostatin neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model, anatomical tracing and direct subthreshold measurements indicated that the larger spatial footprint for somatostatin versus parvalbumin synaptic inhibition explains this difference. Together, these results define cell-type-specific computational roles for lateral inhibition in primary visual cortex, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.

Preferential superficial cortical layer activation during seizure propagation

OBJECTIVE

Focal cortical seizures travel long distances from the onset zone, but the long-distance propagation pathways are uncertain. In vitro and in vivo imaging techniques have investigated the local spread of seizures but did not elucidate long-distance spread. Furthermore, classical studies in slices suggested seizure spread locally along deep cortical layers, whereas more recent in vivo imaging studies posit a role for superficial cortical layers in local spread.

METHODS

We imaged seizure-activated neurons using activity reporter mice and measured local field potentials (LFPs) using microelectrode arrays to map cortical seizure propagation in awake mice.

RESULTS

Frontal lobe onset seizures activate more neurons in superficial layers 2-3 than deep layers 5-6 throughout the cortex. LFP recordings demonstrate that seizures spread faster through the superficial than deep layers over long cortical distances of 3.5 mm. We also show that monosynaptically connected long-distance neurons are in the seizure circuit.

SIGNIFICANCE

We propose that long-distance cortical seizure spread occurs preferentially via synaptically connected superficial cortical neurons.

Neuropixels Opto: Combining high-resolution electrophysiology and optogenetics

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations, and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 1 cm shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent an unprecedented tool for recording, identifying, and manipulating neuronal populations.

A detailed theory of thalamic and cortical microcircuits for predictive visual inference

Understanding cortical microcircuitry requires theoretical models that can tease apart their computational logic from biological details. Although Bayesian inference serves as an abstract framework of cortical computation, precisely mapping concrete instantiations of computational models to biology under real-world tasks is necessary to produce falsifiable neural models. On the basis of a recent generative model, recursive cortical networks, that demonstrated excellent performance on vision benchmarks, we derive a theoretical cortical microcircuit by placing the requirements of the computational model within biological constraints. The derived model suggests precise algorithmic roles for the columnar and laminar feed-forward, feedback, and lateral connections, the thalamic pathway, blobs and interblobs, and the innate lineage-specific interlaminar connectivity within cortical columns. The model also explains several visual phenomena, including the subjective contour effect and neon-color spreading effect, with circuit-level precision. Our model and methodology provides a path forward in understanding cortical and thalamic computations.

Modulation by serotonin reveals preferred recurrent excitatory connectivity in layer II of rat neocortex

We reported that in layer II pyramidal cells of rat somatosensory cortex, 10 μM serotonin (5-HT) alters miniature excitatory postsynaptic current frequency in a subset of cells (47%, "responders", RC; "non-responders", NC otherwise) via 5-HT2 receptors (5-HT2R) but in all pairs reduced evoked excitatory postsynaptic current amplitude by ~50% (Agahari FA, Stricker C. 2021. Serotonergic modulation of spontaneous and evoked transmitter release in layer II pyramidal cells of rat somatosensory cortex. Cereb Cortex. 31:1182-1200. https://doi.org/10.1093/cercor/bhaa285.) suggestive of preferential connectivity. We provide different lines of evidence that distinguish these subsets. First, after 5-HT exposure, changes in miniature excitatory postsynaptic current, spontaneous EPSC frequency, or whole-cell noise (σw) were restricted to postsynaptic cells in pairs (PO) and RC but absent in presynaptic (PR) and NC. Second, exposure caused a large change in holding current with a small variability in NC, but a small one with a large variability in PO/RC. In addition, ΔRin in PO/RC was larger than in PR/NC, with a negative correlation between ΔIhold and ΔRin in NC, a positive in PO, but none in RC. Third, an unbiased classifier identified most PO as RC and all PR as NC. Our data establish two distinct sets of pyramidal cells having a preferred connectivity from NC → RC. 5-HT2R-mediated modulation of transmitter release may likely reduce the signal-to-noise ratio in the ipsilateral but leave the output to the contralateral side unaffected.

The geometry of correlated variability leads to highly suboptimal discriminative sensory coding

The brain represents the world through the activity of neural populations; however, whether the computational goal of sensory coding is to support discrimination of sensory stimuli or to generate an internal model of the sensory world is unclear. Correlated variability across a neural population (noise correlations) is commonly observed experimentally, and many studies demonstrate that correlated variability improves discriminative sensory coding compared to a null model with no correlations. However, such results do not address whether correlated variability is optimal for discriminative sensory coding. If the computational goal of sensory coding is discriminative, than correlated variability should be optimized to support that goal. We assessed optimality of noise correlations for discriminative sensory coding in diverse datasets by developing two novel null models, each with a biological interpretation. Across datasets, we found that correlated variability in neural populations leads to highly suboptimal discriminative sensory coding according to both null models. Furthermore, biological constraints prevent many subsets of the neural populations from achieving optimality, and subselecting based on biological criteria leaves red discriminative coding performance suboptimal. Finally, we show that optimal subpopulations are exponentially small as the population size grows. Together, these results demonstrate that the geometry of correlated variability leads to highly suboptimal discriminative sensory coding.NEW & NOTEWORTHY The brain represents the world through the activity of neural populations that exhibit correlated variability. We assessed optimality of correlated variability for discriminative sensory coding in diverse datasets by developing two novel null models. Across datasets, correlated variability in neural populations leads to highly suboptimal discriminative sensory coding according to both null models. Biological constraints prevent the neural populations from achieving optimality. Together, these results demonstrate that the geometry of correlated variability leads to highly suboptimal discriminative sensory coding.

Modeling of Blood Flow Dynamics in Rat Somatosensory Cortex

Background: The cerebral microvasculature forms a dense network of interconnected blood vessels where flow is modulated partly by astrocytes. Increased neuronal activity stimulates astrocytes to release vasoactive substances at the endfeet, altering the diameters of connected vessels. Methods: Our study simulated the coupling between blood flow variations and vessel diameter changes driven by astrocytic activity in the rat somatosensory cortex. We developed a framework with three key components: coupling between the vasculature and synthesized astrocytic morphologies, a fluid dynamics model to compute flow in each vascular segment, and a stochastic process replicating the effect of astrocytic endfeet on vessel radii. Results: The model was validated against experimental flow values from the literature across cortical depths. We found that local vasodilation from astrocyte activity increased blood flow, especially in capillaries, exhibiting a layer-specific response in deeper cortical layers. Additionally, the highest blood flow variability occurred in capillaries, emphasizing their role in cerebral perfusion regulation. We discovered that astrocytic activity impacted blood flow dynamics in a localized, clustered manner, with most vascular segments influenced by two to three neighboring endfeet. Conclusions: These insights enhance our understanding of neurovascular coupling and guide future research on blood flow-related diseases.

Layer-specific dynamics of local field potentials in monkey V1 during electrical stimulation

The mammalian neocortex, organized into six cellular layers or laminae, forms a cortical network within layers. Layer specific computations are crucial for sensory processing of visual stimuli within primary visual cortex. Laminar recordings of local field potentials (LFPs) are a powerful tool to study neural activity within cortical layers. Electric brain stimulation is widely used in basic neuroscience and in a large range of clinical applications. However, the layer-specific effects of electric stimulation on LFPs remain unclear. To address this gap, we conducted laminar LFP recordings of the primary visual cortex in monkeys while presenting a flash visual stimulus. Simultaneously, we applied a low frequency sinusoidal current to the occipital lobe with offset frequency to the flash stimulus repetition rate. We analyzed the modulation of visual-evoked potentials with respect to the applied phase of the electric stimulation. Our results reveal that only the deeper layers, but not the superficial layers, show phase-dependent changes in LFP components with respect to the applied current. Employing a cortical column model, we demonstrate that these in vivo observations can be explained by phase-dependent changes in the driving force within neurons of deeper layers. Our findings offer crucial insight into the selective modulation of cortical layers through electric stimulation, thus advancing approaches for more targeted neuromodulation.

Ex vivo propagation of synaptically-evoked cortical depolarizations in a mouse model of Alzheimer's disease at 20 Hz, 40 Hz, or 83 Hz

Sensory stimulations at 40 Hz gamma (but not any other frequency), have shown promise in reversing Alzheimer's disease (AD)-related pathologies. What distinguishes 40 Hz? We hypothesized that stimuli at 40 Hz might summate more efficiently (temporal summation) or propagate more efficiently between cortical layers (vertically), or along cortical laminas (horizontally), compared to inputs at 20 or 83 Hz. To investigate these hypotheses, we used brain slices from AD mouse model animals (5xFAD). Extracellular (synaptic) stimuli were delivered in cortical layer 4 (L4). Leveraging a fluorescent voltage indicator (VSFP) expressed in cortical pyramidal neurons, we simultaneously monitored evoked cortical depolarizations at multiple sites, at 1 kHz sampling frequency. Experimental groups (AD-Female, CTRL-Female, AD-Male, and CTRL-Male) were tested at three stimulation frequencies (20, 40, and 83 Hz). Despite our initial hypothesis, two parameters-temporal summation of voltage waveforms and the strength of propagation through the cortical neuropil-did not reveal any distinct advantage of 40 Hz stimulation. Significant physiological differences between AD and Control mice were found at all stimulation frequencies tested, while the 40 Hz stimulation frequency was not remarkable.

Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation

Objective.Micro-electrocorticographic (μECoG) arrays are able to record neural activities from the cortical surface, without the need to penetrate the brain parenchyma. Owing in part to small electrode sizes, previous studies have demonstrated that single-unit spikes could be detected from the cortical surface, and likely from Layer I neurons of the neocortex. Here we tested the ability to useμECoG arrays to decode, in rats, body position during open field navigation, through isolated single-unit activities.Approach. μECoG arrays were chronically implanted onto primary motor cortex (M1) of Wistar rats, and neural recording was performed in awake, behaving rats in an open-field enclosure. The signals were band-pass filtered between 300-3000 Hz. Threshold-crossing spikes were identified and sorted into distinct units based on defined criteria including waveform morphology and refractory period. Body positions were derived from video recordings. We used gradient-boosting machine to predict body position based on previous 100 ms of spike data, and correlation analyses to elucidate the relationship between position and spike patterns.Main results.Single-unit spikes could be extracted during chronic recording fromμECoG, and spatial position could be decoded from these spikes with a mean absolute error of prediction of 0.135 and 0.090 in the x- and y- dimensions (of a normalized range from 0 to 1), and Pearson's r of 0.607 and 0.571, respectively.Significance. μECoG can detect single-unit activities that likely arise from superficial neurons in the cortex and is a promising alternative to intracortical arrays, with the added benefit of scalability to cover large cortical surface with minimal incremental risks. More studies should be performed in human related to its use as brain-machine interface.

Nonuniform and pathway-specific laminar processing of spatial frequencies in the primary visual cortex of primates

The neocortex comprises six cortical layers that play a crucial role in information processing; however, it remains unclear whether laminar processing is consistent across all regions within a single cortex. In this study, we demonstrate diverse laminar response patterns in the primary visual cortex (V1) of three male macaque monkeys when exposed to visual stimuli at different spatial frequencies (SFs). These response patterns can be categorized into two groups. One group exhibit suppressed responses in the output layers for all SFs, while the other type shows amplified responses specifically at high SFs. Further analysis suggests that both magnocellular (M) and parvocellular (P) pathways contribute to the suppressive effect through feedforward mechanisms, whereas amplification is specific to local recurrent mechanisms within the parvocellular pathway. These findings highlight the non-uniform distribution of neural mechanisms involved in laminar processing and emphasize how pathway-specific amplification selectively enhances representations of high-SF information in primate V1.

Increased Excitability of Layer 2 Cortical Pyramidal Neurons in the Supplementary Motor Cortex Underlies High Cocaine-Seeking Behaviors

BACKGROUND

Most efforts in addiction research have focused on the involvement of the medial prefrontal cortex, including the infralimbic, prelimbic, and anterior cingulate cortical areas, in cocaine-seeking behaviors. However, no effective prevention or treatment for drug relapse is available.

METHODS

We focused instead on the motor cortex, including both the primary and supplementary motor areas (M1 and M2, respectively). Addiction risk was evaluated by testing cocaine seeking after intravenous self-administration (IVSA) of cocaine in Sprague Dawley rats. The causal relationship between the excitability of cortical pyramidal neurons (CPNs) in M1/M2 and addiction risk was explored by ex vivo whole-cell patch clamp recordings and in vivo pharmacological or chemogenetic manipulation.

RESULTS

Our recordings showed that on withdrawal day 45 (WD45) after IVSA, cocaine, but not saline, increased the excitability of CPNs in the cortical superficial layers (primarily layer 2, denoted L2) but not in layer 5 (L5) in M2. Bilateral microinjection of the GABAA (gamma-aminobutyric acid A) receptor agonist muscimol to the M2 area attenuated cocaine seeking on WD45. More specifically, chemogenetic inhibition of CPN excitability in L2 of M2 (denoted M2-L2) by the DREADD (designer receptor exclusively activated by designer drugs) agonist compound 21 prevented drug seeking on WD45 after cocaine IVSA. This chemogenetic inhibition of M2-L2 CPNs had no effects on sucrose seeking. In addition, neither pharmacological nor chemogenetic inhibition manipulations altered general locomotor activity.

CONCLUSIONS

Our results indicate that cocaine IVSA induces hyperexcitability in the motor cortex on WD45. Importantly, the increased excitability in M2, particularly in L2, could be a novel target for preventing drug relapse during withdrawal.

Laminar compartmentalization of attention modulation in area V4 aligns with the demands of visual processing hierarchy in the cortex

Attention selectively enhances neural responses to low contrast stimuli in visual area V4, a critical hub that sends projections both up and down the visual hierarchy. Veridical encoding of contrast information is a key computation in early visual areas, while later stages encoding higher level features benefit from improved sensitivity to low contrast. How area V4 meets these distinct information processing demands in the attentive state is unknown. We found that attentional modulation in V4 is cortical layer and cell-class specific. Putative excitatory neurons in the superficial layers show enhanced boosting of low contrast information, while those of deep layers exhibit contrast-independent scaling. Computational modeling suggested the extent of spatial integration of inhibitory neurons as the mechanism behind such laminar differences. Considering that superficial neurons are known to project to higher areas and deep layers to early visual areas, our findings suggest that the interactions between attention and contrast in V4 are compartmentalized, in alignment with the demands of the visual processing hierarchy.

Astrocytes adjust the dynamic range of cortical network activity to control modality-specific sensory information processing

Cortical neuron-astrocyte communication in response to peripheral sensory stimulation occurs in a topographic-, frequency-, and intensity-dependent manner. However, the contribution of this functional interaction to the processing of sensory inputs and consequent behavior remains unclear. We investigate the role of astrocytes in sensory information processing at circuit and behavioral levels by monitoring and manipulating astrocytic activity in vivo. We show that astrocytes control the dynamic range of the cortical network activity, optimizing its responsiveness to incoming sensory inputs. The astrocytic modulation of sensory processing contributes to setting the detection threshold for tactile and thermal behavior responses. The mechanism of such astrocytic control is mediated through modulation of inhibitory transmission to adjust the gain and sensitivity of responding networks. These results uncover a role for astrocytes in maintaining the cortical network activity in an optimal range to control behavior associated with specific sensory modalities.

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.

Single-neuron analysis of dendrites and axons reveals the network organization in mouse prefrontal cortex

The structures of dendrites and axons form the basis for the connectivity of neural network, but their precise relationship at single-neuron level remains unclear. Here we report the complete dendrite and axon morphology of nearly 2,000 neurons in mouse prefrontal cortex (PFC). We identified morphological variations of somata, dendrites and axons across laminar layers and PFC subregions and the general rules of somatodendritic scaling with cytoarchitecture. We uncovered 24 morphologically distinguishable dendrite subtypes in 1,515 pyramidal projection neurons and 405 atypical pyramidal projection neurons and spiny stellate neurons with unique axon projection patterns. Furthermore, correspondence analysis among dendrites, local axons and long-range axons revealed coherent morphological changes associated with electrophysiological phenotypes. Finally, integrative dendrite-axon analysis uncovered the organization of potential intra-column, inter-hemispheric and inter-column connectivity among projection neuron types in PFC. Together, our study provides a comprehensive structural repertoire for the reconstruction and analysis of PFC neural network.

Cortical depth-dependent human fMRI of resting-state networks using EPIK

Introduction

Recent laminar-fMRI studies have substantially improved understanding of the evoked cortical responses in multiple sub-systems; in contrast, the laminar component of resting-state networks spread over the whole brain has been less studied due to technical limitations. Animal research strongly suggests that the supragranular layers of the cortex play a critical role in maintaining communication within the default mode network (DMN); however, whether this is true in this and other human cortical networks remains unclear.

Methods

Here, we used EPIK, which offers unprecedented coverage at sub-millimeter resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers.

Results

Our results suggest that human DMN connectivity is primarily supported by intermediate and superficial layers of the cortex, and furthermore, the preferred cortical depth used for communication can vary from one network to another. In addition, the laminar connectivity profile of some networks showed a tendency to change upon engagement in a motor task. In line with these connectivity changes, we observed that the amplitude of the low-frequency-fluctuations (ALFF), as well as the regional homogeneity (ReHo), exhibited a different laminar slope when subjects were either performing a task or were in a resting state (less variation among laminae, i.e., lower slope, during task performance compared to rest).

Discussion

The identification of varied laminar profiles concerning network connectivity, ALFF, and ReHo, observed across two brain states (task vs. rest) has major implications for the characterization of network-related diseases and suggests the potential diagnostic value of laminar fMRI in psychiatric disorders, e.g., to differentiate the cortical dynamics associated with disease stages linked, or not linked, to behavioral changes. The evaluation of laminar-fMRI across the brain encompasses computational challenges; nonetheless, it enables the investigation of a new dimension of the human neocortex, which may be key to understanding neurological disorders from a novel perspective.

The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR, M, and CBV across cortical depth

Ultra-high field functional magnetic resonance imaging (fMRI) offers the spatial resolution to measure neuronal activity at the scale of cortical layers. However, cortical depth dependent vascularization differences, such as a higher prevalence of macro-vascular compartments near the pial surface, have a confounding effect on depth-resolved blood-oxygen-level dependent (BOLD) fMRI signals. In the current study, we use hypercapnic and hyperoxic breathing conditions to quantify the influence of all venous vascular and micro-vascular compartments on laminar BOLD fMRI, as measured with gradient-echo (GE) and spin-echo (SE) scan sequences, respectively. We find that all venous vascular and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-value parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately two and a half times larger for all venous vascular compartments combined compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in estimates of CBV changes between all venous vascular and micro-vascular compartments, although this relative difference was approximately uniform across cortical depth. Thus, our results suggest that fMRI BOLD signal differences across cortical depth are likely caused by differences in dilation properties between macro- and micro-vascular compartments.

Dexmedetomidine Preserves Activity of Neurons in Primary Somatosensory Cortex Compared to Propofol and Ketamine

General anesthesia has been shown to induce significant changes in the functional connectivity of the cerebral cortex. However, traditional methods such as electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) lack the spatial resolution to study the effects of general anesthesia on individual cortical neurons. This study aimed to use high-resolution two-photon imaging, which can provide single-neuron resolution, to investigate the characteristics of consciousness under general anesthesia. We used C57BL/6J and Thy1-GCamp6s mice and found that at similar levels of sedation, as measured by EEG, dexmedetomidine did not significantly inhibit the spontaneous activity of neuronal somata in the S1 cortex, but preserved the frequency of calcium events in neuronal spines. In contrast, propofol and ketamine dramatically inhibited the spontaneous activity of both neuronal somata and spines. The S1 cortex still responded to whisker stimulation under dexmedetomidine anesthesia, but not under propofol or ketamine anesthesia. Our results suggest that dexmedetomidine anesthesia has unique neuronal properties associated with its ability to facilitate easy awakening in the clinic. These findings provide insights into the development of more effective strategies for monitoring consciousness during general anesthesia.

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.

Lack of placental neurosteroid alters cortical development and female somatosensory function

Placental endocrine function is essential to fetal brain development. Placental hormones include neurosteroids such as allopregnanolone (ALLO), a regulator of neurodevelopmental processes via positive allosteric modulation of the GABAA receptor (GABAA-R). Using a mouse model (plKO) in which the gene encoding the ALLO synthesis enzyme is specifically deleted in trophoblasts, we previously showed that placental ALLO insufficiency alters cerebellar white matter development and leads to male-specific autistic-like behavior. We now demonstrate that the lack of placental ALLO causes female-predominant alterations of cortical development and function. Placental ALLO insufficiency disrupts cell proliferation in the primary somatosensory cortex (S1) in a sex-linked manner. Early changes are seen in plKO embryos of both sexes, but persist primarily in female offspring after birth. Adolescent plKO females show significant reduction in pyramidal neuron density, as well as somatosensory behavioral deficits as compared with plKO males and control littermates. Assessment of layer-specific markers in human postmortem cortices suggests that preterm infants may also have female-biased abnormalities in cortical layer specification as compared with term infants. This study establishes a novel and fundamental link between placental function and sex-linked long-term neurological outcomes, emphasizing the importance of the growing field of neuroplacentology.

Association between Cerebral Coordination Functions and Clinical Outcomes of Alzheimer's Dementia

Background: Alzheimer’s dementia (AD) is a degenerative disease that impairs cognitive function, initially, and then motor or other function, eventually. Motor coordination function impairment usually accompanies cognition impairment but it is seldom examined whether it can reflect the clinical outcomes of AD. Methods: 113 clinically diagnosed AD patients with a mean age of 78.9 ± 6.9 years underwent an annual neuropsychological assessment using the Mini-Mental State Examination (MMSE), the Cognitive Abilities Screening Instrument (CASI), the Sum of Boxes of Clinical Dementia Rating (CDR-SB), and the CDR. The cerebral coordination function was evaluated through correlations among 15 joints with a kinetic depth sensor annually. An intra-individual comparison of both cognitive and motor coordination functions was performed to examine their correlations. Results: The changes in coordination function in the lower limbs can significantly reflect the clinical outcomes, MMSE (p < 0.001), CASI (p = 0.006), CDR (p < 0.001), and CDR-SB (p < 0.001), but the changes in upper limbs can only reflect the clinical outcome in CDR (p < 0.001). Conclusions: The use of a kinetic depth sensor to determine the coordination between joints, especially in lower limbs, can significantly reflect the global functional and cognitive outcomes in AD. Such evaluations could be another biomarker used to evaluate non-cognitive outcomes in AD for clinical and research purposes.

Transformation of primary sensory cortical representations from layer 4 to layer 2

Sensory input arrives from thalamus in cortical layer (L) 4, which outputs predominantly to superficial layers. L4 to L2 thus constitutes one of the earliest cortical feedforward networks. Despite extensive study, the transformation performed by this network remains poorly understood. We use two-photon calcium imaging to record neural activity in L2-4 of primary vibrissal somatosensory cortex (vS1) as mice perform an object localization task with two whiskers. Touch responses sparsen and become more reliable from L4 to L2, with nearly half of the superficial touch response confined to ~1 % of excitatory neurons. These highly responsive neurons have broad receptive fields and can more accurately decode stimulus features. They participate disproportionately in ensembles, small subnetworks with elevated pairwise correlations. Thus, from L4 to L2, cortex transitions from distributed probabilistic coding to sparse and robust ensemble-based coding, resulting in more efficient and accurate representations.

A genetically identified population of layer 4 neurons in auditory cortex that contributes to pre-pulse inhibition of the acoustic startle response

A fundamental task faced by the auditory system is the detection of events that are signaled by fluctuations in sound. Spiking in auditory cortical neurons is critical for sound detection, but the causal roles of specific cell types and circuits are still mostly unknown. Here we tested the role of a genetically identified population of layer 4 auditory cortical neurons in sound detection. We measured sound detection using a common variant of pre-pulse inhibition of the acoustic startle response, in which a silent gap in background noise acts as a cue that attenuates startle. We used a Gpr26-Cre driver line, which we found expressed predominantly in layer 4 of auditory cortex. Photostimulation of these cells, which were responsive to gaps in noise, was sufficient to attenuate the startle reflex. Photosuppression of these cells reduced neural responses to gaps throughout cortex, and impaired behavioral gap detection. These data demonstrate that cortical Gpr26 neurons are both necessary and sufficient for top–down modulation of the acoustic startle reflex, and are thus likely to be involved in sound detection.

Neuropeptide System Regulation of Prefrontal Cortex Circuitry: Implications for Neuropsychiatric Disorders

Neuropeptides, a diverse class of signaling molecules in the nervous system, modulate various biological effects including membrane excitability, synaptic transmission and synaptogenesis, gene expression, and glial cell architecture and function. To date, most of what is known about neuropeptide action is limited to subcortical brain structures and tissue outside of the central nervous system. Thus, there is a knowledge gap in our understanding of neuropeptide function within cortical circuits. In this review, we provide a comprehensive overview of various families of neuropeptides and their cognate receptors that are expressed in the prefrontal cortex (PFC). Specifically, we highlight dynorphin, enkephalin, corticotropin-releasing factor, cholecystokinin, somatostatin, neuropeptide Y, and vasoactive intestinal peptide. Further, we review the implication of neuropeptide signaling in prefrontal cortical circuit function and use as potential therapeutic targets. Together, this review summarizes established knowledge and highlights unknowns of neuropeptide modulation of neural function underlying various biological effects while offering insights for future research. An increased emphasis in this area of study is necessary to elucidate basic principles of the diverse signaling molecules used in cortical circuits beyond fast excitatory and inhibitory transmitters as well as consider components of neuropeptide action in the PFC as a potential therapeutic target for neurological disorders. Therefore, this review not only sheds light on the importance of cortical neuropeptide studies, but also provides a comprehensive overview of neuropeptide action in the PFC to serve as a roadmap for future studies in this field.

From Analog to Digital Computing: Is Homo sapiens’ Brain on Its Way to Become a Turing Machine?

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is with computing, which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine.

Columnar Localization and Laminar Origin of Cortical Surface Electrical Potentials

Electrocorticography (ECoG) methodologically bridges basic neuroscience and understanding of human brains in health and disease. However, the localization of ECoG signals across the surface of the brain and the spatial distribution of their generating neuronal sources are poorly understood. To address this gap, we recorded from rat auditory cortex using customized μECoG, and simulated cortical surface electrical potentials with a full-scale, biophysically detailed cortical column model. Experimentally, μECoG-derived auditory representations were tonotopically organized and signals were anisotropically localized to less than or equal to ±200 μm, that is, a single cortical column. Biophysical simulations reproduce experimental findings and indicate that neurons in cortical layers V and VI contribute ∼85% of evoked high-gamma signal recorded at the surface. Cell number and synchrony were the primary biophysical properties determining laminar contributions to evoked μECoG signals, whereas distance was only a minimal factor. Thus, evoked μECoG signals primarily originate from neurons in the infragranular layers of a single cortical column.SIGNIFICANCE STATEMENT ECoG methodologically bridges basic neuroscience and understanding of human brains in health and disease. However, the localization of ECoG signals across the surface of the brain and the spatial distribution of their generating neuronal sources are poorly understood. We investigated the localization and origins of sensory-evoked ECoG responses. We experimentally found that ECoG responses were anisotropically localized to a cortical column. Biophysically detailed simulations revealed that neurons in layers V and VI were the primary sources of evoked ECoG responses. These results indicate that evoked ECoG high-gamma responses are primarily generated by the population spike rate of pyramidal neurons in layers V and VI of single cortical columns and highlight the possibility of understanding how microscopic sources produce mesoscale signals.

Layer-specific activation in human primary somatosensory cortex during tactile temporal prediction error processing

The human brain continuously generates predictions of incoming sensory input and calculates corresponding prediction errors from the perceived inputs to update internal predictions. In human primary somatosensory cortex (area 3b), different cortical layers are involved in receiving the sensory input and generation of error signals. It remains unknown, however, how the layers in the human area 3b contribute to the temporal prediction error processing. To investigate prediction error representation in the area 3b across layers, we acquired layer-specific functional magnetic resonance imaging (fMRI) data at 7T from human area 3b during a task of index finger poking with no-delay, short-delay and long-delay touching sequences. We demonstrate that all three tasks increased activity in both superficial and deep layers of area 3b compared to the random sensory input. The fMRI signal was differentially modulated solely in the deep layers rather than the superficial layers of area 3b by the delay time. Compared with the no-delay stimuli, activity was greater in the deep layers of area 3b during the short-delay stimuli but lower during the long-delay stimuli. This difference activity features in the superficial and deep layers suggest distinct functional contributions of area 3b layers to tactile temporal prediction error processing. The functional segregation in area 3b across layers may reflect that the excitatory and inhibitory interplay in the sensory cortex contributions to flexible communication between cortical layers or between cortical areas.

Response Selectivity of the Lateral Posterior Nucleus Axons Projecting to the Mouse Primary Visual Cortex

Neurons in the mouse primary visual cortex (V1) exhibit characteristic response selectivity to visual stimuli, such as orientation, direction and spatial frequency selectivity. Since V1 receives thalamic visual inputs from the lateral geniculate nucleus (LGN) and lateral posterior nucleus (LPN), the response selectivity of the V1 neurons could be influenced mostly by these inputs. However, it remains unclear how these two thalamic inputs contribute to the response selectivity of the V1 neurons. In this study, we examined the orientation, direction and spatial frequency selectivity of the LPN axons projecting to V1 and compared their response selectivity with our previous results of the LGN axons in mice. For this purpose, the genetically encoded calcium indicator, GCaMP6s, was locally expressed in the LPN using the adeno-associated virus (AAV) infection method. Visual stimulations were presented, and axonal imaging was conducted in V1 by two-photon calcium imaging in vivo. We found that LPN axons primarily terminate in layers 1 and 5 and, to a lesser extent, in layers 2/3 and 4 of V1, while LGN axons mainly terminate in layer 4 and, to a lesser extent, in layers 1 and 2/3 of V1. LPN axons send highly orientation- and direction-selective inputs to all the examined layers in V1, whereas LGN axons send highly orientation- and direction-selective inputs to layers 1 and 2/3 but low orientation and direction selective inputs to layer 4 in V1. The distribution of preferred orientation and direction was strongly biased toward specific orientations and directions in LPN axons, while weakly biased to cardinal orientations and directions in LGN axons. In spatial frequency tuning, both the LPN and LGN axons send selective inputs to V1. The distribution of preferred spatial frequency was more diverse in the LPN axons than in the LGN axons. In conclusion, LPN inputs to V1 are functionally different from LGN inputs and may have different roles in the orientation, direction and spatial frequency tuning of the V1 neurons.

Changes in the spatiotemporal pattern of spontaneous activity across a cortical column after noise trauma

In the auditory modality, noise trauma has often been used to investigate cortical plasticity as it causes cochlear hearing loss. One limitation of these past studies, however, is that the effects of noise trauma have been mostly documented at the granular layer, which is the main cortical recipient of thalamic inputs. Importantly, the cortex is composed of six different layers each having its own pattern of connectivity and specific role in sensory processing. The present study aims at investigating the effects of acute and chronic noise trauma on the laminar pattern of spontaneous activity in primary auditory cortex of the anesthetized guinea pig. We show that spontaneous activity is dramatically altered across cortical layers after acute and chronic noise-induced hearing loss. First, spontaneous activity was globally enhanced across cortical layers, both in terms of firing rate and amplitude of spike-triggered average of local field potentials. Second, current source density on (spontaneous) spike-triggered average of local field potentials indicates that current sinks develop in the supra- and infragranular layers. These latter results suggest that supragranular layers become a major input recipient and that the propagation of spontaneous activity over a cortical column is greatly enhanced after acute and chronic noise-induced hearing loss. We discuss the possible mechanisms and functional implications of these changes.

Double-μPeriscope, a tool for multilayer optical recordings, optogenetic stimulations or both

Intelligent behavior and cognitive functions in mammals depend on cortical microcircuits made up of a variety of excitatory and inhibitory cells that form a forest-like complex across six layers. Mechanistic understanding of cortical microcircuits requires both manipulation and monitoring of multiple layers and interactions between them. However, existing techniques are limited as to simultaneous monitoring and stimulation at different depths without damaging a large volume of cortical tissue. Here, we present a relatively simple and versatile method for delivering light to any two cortical layers simultaneously. The method uses a tiny optical probe consisting of two microprisms mounted on a single shaft. We demonstrate the versatility of the probe in three sets of experiments: first, two distinct cortical layers were optogenetically and independently manipulated; second, one layer was stimulated while the activity of another layer was monitored; third, the activity of thalamic axons distributed in two distinct cortical layers was simultaneously monitored in awake mice. Its simple-design, versatility, small-size, and low-cost allow the probe to be applied widely to address important biological questions.

Itch perception is reflected by neuronal ignition in the primary somatosensory cortex

Multiple cortical areas including the primary somatosensory cortex (S1) are activated during itch signal processing, yet cortical representation of itch perception remains unknown. Using novel miniature two-photon microscopic imaging in free-moving mice, we investigated the coding of itch perception in S1. We found that pharmacological inactivation of S1 abolished itch-induced scratching behavior, and the itch-induced scratching behavior could be well predicted by the activity of a fraction of layer 2/3 pyramidal neurons, suggesting that a subpopulation of S1 pyramidal neurons encoded itch perception, as indicated by immediate subsequent scratching behaviors. With a newly established optogenetics-based paradigm that allows precisely controlled pruritic stimulation, we found that a small fraction of S1 neurons exhibited an ignition-like pattern at the detection threshold of itch perception. Our study revealed the neural mechanism underlying itch perceptual coding in S1, thus paving the way for the study of cortical representation of itch perception at the single-neuron level in freely moving animals.

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

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

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

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

Control of Brain State Transitions with a Photoswitchable Muscarinic Agonist

The ability to control neural activity is essential for research not only in basic neuroscience, as spatiotemporal control of activity is a fundamental experimental tool, but also in clinical neurology for therapeutic brain interventions. Transcranial-magnetic, ultrasound, and alternating/direct current (AC/DC) stimulation are some available means of spatiotemporal controlled neuromodulation. There is also light-mediated control, such as optogenetics, which has revolutionized neuroscience research, yet its clinical translation is hampered by the need for gene manipulation. As a drug-based light-mediated control, the effect of a photoswitchable muscarinic agonist (Phthalimide-Azo-Iper (PAI)) on a brain network is evaluated in this study. First, the conditions to manipulate M2 muscarinic receptors with light in the experimental setup are determined. Next, physiological synchronous emergent cortical activity consisting of slow oscillations-as in slow wave sleep-is transformed into a higher frequency pattern in the cerebral cortex, both in vitro and in vivo, as a consequence of PAI activation with light. These results open the way to study cholinergic neuromodulation and to control spatiotemporal patterns of activity in different brain states, their transitions, and their links to cognition and behavior. The approach can be applied to different organisms and does not require genetic manipulation, which would make it translational to humans.

Creative Destruction: A Basic Computational Model of Cortical Layer Formation

One of the most characteristic properties of many vertebrate neural systems is the layered organization of different cell types. This cytoarchitecture exists in the cortex, the retina, the hippocampus, and many other parts of the central nervous system. The developmental mechanisms of neural layer formation have been subject to substantial experimental efforts. Here, we provide a general computational model for cortical layer formation in 3D physical space. We show that this multiscale, agent-based model, comprising two distinct stages of apoptosis, can account for the wide range of neuronal numbers encountered in different cortical areas and species. Our results demonstrate the phenotypic richness of a basic state diagram structure. Importantly, apoptosis allows for changing the thickness of one layer without automatically affecting other layers. Therefore, apoptosis increases the flexibility for evolutionary change in layer architecture. Notably, slightly changed gene regulatory dynamics recapitulate the characteristic properties observed in neurodevelopmental diseases. Overall, we propose a novel computational model using gene-type rules, exhibiting many characteristics of normal and pathological cortical development.

Circuit organization of the rodent medial prefrontal cortex

The prefrontal cortex (PFC) orchestrates higher brain function and becomes disrupted in many mental health disorders. The rodent medial PFC (mPFC) possesses an enormous variety of projection neurons and interneurons. These cells are engaged by long-range inputs from other brain regions involved in cognition, motivation, and emotion. They also communicate in the local network via specific connections between excitatory and inhibitory cells. In this review, we describe the cellular diversity of the rodent mPFC, the impact of long-range afferents, and the specificity of local microcircuits. We highlight similarities with and differences between other cortical areas, illustrating how the circuit organization of the mPFC may give rise to its unique functional roles.

Untangling the cortico-thalamo-cortical loop: cellular pieces of a knotty circuit puzzle

Functions of the neocortex depend on its bidirectional communication with the thalamus, via cortico-thalamo-cortical (CTC) loops. Recent work dissecting the synaptic connectivity in these loops is generating a clearer picture of their cellular organization. Here, we review findings across sensory, motor and cognitive areas, focusing on patterns of cell type-specific synaptic connections between the major types of cortical and thalamic neurons. We outline simple and complex CTC loops, and note features of these loops that appear to be general versus specialized. CTC loops are tightly interlinked with local cortical and corticocortical (CC) circuits, forming extended chains of loops that are probably critical for communication across hierarchically organized cerebral networks. Such CTC-CC loop chains appear to constitute a modular unit of organization, serving as scaffolding for area-specific structural and functional modifications. Inhibitory neurons and circuits are embedded throughout CTC loops, shaping the flow of excitation. We consider recent findings in the context of established CTC and CC circuit models, and highlight current efforts to pinpoint cell type-specific mechanisms in CTC loops involved in consciousness and perception. As pieces of the connectivity puzzle fall increasingly into place, this knowledge can guide further efforts to understand structure-function relationships in CTC loops.

Prefrontal deep projection neurons enable cognitive flexibility via persistent feedback monitoring

Cognitive flexibility, the ability to alter strategy according to changing stimulus-response-reward relationships, is critical for updating learned behavior. Attentional set-shifting, a test of cognitive flexibility, depends on the activity of prefrontal cortex (PFC). It remains unclear, however, what role PFC neurons play to support set-shifting. Using optogenetics and two-photon calcium imaging, we demonstrate that medial PFC activity does not bias sensorimotor responses during set-shifting, but rather enables set-shifting by encoding trial feedback information, a role it has been known to play in other contexts. Unexpectedly, the functional properties of PFC cells did not vary with their efferent projection targets. Instead, representations of trial feedback formed a topological gradient, with cells more strongly selective for feedback information located further from the pial surface, where afferent input from the anterior cingulate cortex was denser. These findings identify a critical role for deep PFC projection neurons in enabling set-shifting through behavioral feedback monitoring.

Circuit organization of the excitatory sensorimotor loop through hand/forelimb S1 and M1

Sensory-guided limb control relies on communication across sensorimotor loops. For active touch with the hand, the longest loop is the transcortical continuation of ascending pathways, particularly the lemnisco-cortical and corticocortical pathways carrying tactile signals via the cuneate nucleus, ventral posterior lateral (VPL) thalamus, and primary somatosensory (S1) and motor (M1) cortices to reach corticospinal neurons and influence descending activity. We characterized excitatory connectivity along this pathway in the mouse. In the lemnisco-cortical leg, disynaptic cuneate→VPL→S1 connections excited mainly layer (L) 4 neurons. In the corticocortical leg, S1→M1 connections from L2/3 and L5A neurons mainly excited downstream L2/3 neurons, which excite corticospinal neurons. The findings provide a detailed new wiring diagram for the hand/forelimb-related transcortical circuit, delineating a basic but complex set of cell-type-specific feedforward excitatory connections that selectively and extensively engage diverse intratelencephalic projection neurons, thereby polysynaptically linking subcortical somatosensory input to cortical motor output to spinal cord.

Flexible Frequency Switching in Adult Mouse Visual Cortex Is Mediated by Competition Between Parvalbumin and Somatostatin Expressing Interneurons

Neuronal networks in rodent primary visual cortex (V1) can generate oscillations in different frequency bands depending on the network state and the level of visual stimulation. High-frequency gamma rhythms, for example, dominate the network's spontaneous activity in adult mice but are attenuated upon visual stimulation, during which the network switches to the beta band instead. The spontaneous local field potential (LFP) of juvenile mouse V1, however, mainly contains beta rhythms and presenting a stimulus does not elicit drastic changes in network oscillations. We study, in a spiking neuron network model, the mechanism in adult mice allowing for flexible switches between multiple frequency bands and contrast this to the network structure in juvenile mice that lack this flexibility. The model comprises excitatory pyramidal cells (PCs) and two types of interneurons: the parvalbumin-expressing (PV) and the somatostatinexpressing (SOM) interneuron. In accordance with experimental findings, the pyramidal-PV and pyramidal-SOM cell subnetworks are associated with gamma and beta oscillations, respectively. In our model, they are both generated via a pyramidal-interneuron gamma (PING) mechanism, wherein the PCs drive the oscillations. Furthermore, we demonstrate that large but not small visual stimulation activates SOM cells, which shift the frequency of resting-state gamma oscillations produced by the pyramidal-PV cell subnetwork so that beta rhythms emerge. Finally, we show that this behavior is obtained for only a subset of PV and SOM interneuron projection strengths, indicating that their influence on the PCs should be balanced so that they can compete for oscillatory control of the PCs. In sum, we propose a mechanism by which visual beta rhythms can emerge from spontaneous gamma oscillations in a network model of the mouse V1; for this mechanism to reproduce V1 dynamics in adult mice, balance between the effective strengths of PV and SOM cells is required.

Analysis of segmentation ontology reveals the similarities and differences in connectivity onto L2/3 neurons in mouse V1

Quantitatively comparing brain-wide connectivity of different types of neuron is of vital importance in understanding the function of the mammalian cortex. Here we have designed an analytical approach to examine and compare datasets from hierarchical segmentation ontologies, and applied it to long-range presynaptic connectivity onto excitatory and inhibitory neurons, mainly located in layer 2/3 (L2/3), of mouse primary visual cortex (V1). We find that the origins of long-range connections onto these two general cell classes-as well as their proportions-are quite similar, in contrast to the inputs on to a cell type in L6. These anatomical data suggest that distal inputs received by the general excitatory and inhibitory classes of neuron in L2/3 overlap considerably.

Spatially mapped single-cell chromatin accessibility

High-throughput single-cell epigenomic assays can resolve cell type heterogeneity in complex tissues, however, spatial orientation is lost. Here, we present single-cell combinatorial indexing on Microbiopsies Assigned to Positions for the Assay for Transposase Accessible Chromatin, or sciMAP-ATAC, as a method for highly scalable, spatially resolved, single-cell profiling of chromatin states. sciMAP-ATAC produces data of equivalent quality to non-spatial sci-ATAC and retains the positional information of each cell within a 214 micron cubic region, with up to hundreds of tracked positions in a single experiment. We apply sciMAP-ATAC to assess cortical lamination in the adult mouse primary somatosensory cortex and in the human primary visual cortex, where we produce spatial trajectories and integrate our data with non-spatial single-nucleus RNA and other chromatin accessibility single-cell datasets. Finally, we characterize the spatially progressive nature of cerebral ischemic infarction in the mouse brain using a model of transient middle cerebral artery occlusion.

Spatial orientation of cells in an interconnected network is lost in high-throughput single-cell epigenomic assays. Here the authors present sciMAP-ATAC to produce spatially resolved single-cell ATAC-seq data.

Dynorphin/Kappa-Opioid Receptor System Modulation of Cortical Circuitry

Cortical circuits control a plethora of behaviors, from sensation to cognition. The cortex is enriched with neuropeptides and receptors that play a role in information processing, including opioid peptides and their cognate receptors. The dynorphin (DYN)/kappa-opioid receptor (KOR) system has been implicated in the processing of sensory and motivationally-charged emotional information and is highly expressed in cortical circuits. This is important as dysregulation of DYN/KOR signaling in limbic and cortical circuits has been implicated in promoting negative affect and cognitive deficits in various neuropsychiatric disorders. However, research investigating the role of this system in controlling cortical circuits and computations therein is limited. Here, we review the (1) basic anatomy of cortical circuits, (2) anatomical architecture of the cortical DYN/KOR system, (3) functional regulation of cortical synaptic transmission and microcircuit function by the DYN/KOR system, (4) regulation of behavior by the cortical DYN/KOR system, (5) implications for the DYN/KOR system for human health and disease, and (6) future directions and unanswered questions for the field. Further work elucidating the role of the DYN/KOR system in controlling cortical information processing and associated behaviors will be of importance to increasing our understanding of principles underlying neuropeptide modulation of cortical circuits, mechanisms underlying sensation and perception, motivated and emotional behavior, and cognition. Increased emphasis in this area of study will also aid in the identification of novel ways to target the DYN/KOR system to treat neuropsychiatric disorders.

Spatially Distributed Representation of Taste Quality in the Gustatory Insular Cortex of Behaving Mice

Visual, auditory, and somatosensory cortices are topographically organized, with neurons responding to similar sensory features clustering in adjacent portions of the cortex. Such topography has not been observed in the piriform cortex, whose responses to odorants are sparsely distributed across the cortex. The spatial organization of taste responses in the gustatory insular cortex (GC) is currently debated, with conflicting evidence from anesthetized rodents pointing to alternative and mutually exclusive models. Here, we rely on calcium imaging to determine how taste and task-related variables are represented in the superficial layers of GC of alert, licking mice. Our data show that the various stimuli evoke sparse responses from a combination of broadly and narrowly tuned neurons. Analysis of the distribution of responses over multiple spatial scales demonstrates that taste representations are distributed across the cortex, with no sign of spatial clustering or topography. Altogether, data presented here support the idea that the representation of taste qualities in GC of alert mice is sparse and distributed, analogous to the representation of odorants in piriform cortex.

Slow Waves Promote Sleep-Dependent Plasticity and Functional Recovery after Stroke

Functional recovery after stroke is associated with a remapping of neural circuits. This reorganization is often associated with low-frequency, high-amplitude oscillations in the peri-infarct zone in both rodents and humans. These oscillations are reminiscent of sleep slow waves (SW) and suggestive of a role for sleep in brain plasticity that occur during stroke recovery; however, direct evidence is missing. Using a stroke model in male mice, we showed that stroke was followed by a transient increase in NREM sleep accompanied by reduced amplitude and slope of ipsilateral NREM sleep SW. We next used 5 ms optical activation of Channelrhodopsin 2-expressing pyramidal neurons, or 200 ms silencing of Archeorhodopsin T-expressing pyramidal neurons, to generate local cortical UP, or DOWN, states, respectively, both sharing similarities with spontaneous NREM SW in freely moving mice. Importantly, we found that single optogenetically evoked SW (SWopto) in the peri-infarct zone, randomly distributed during sleep, significantly improved fine motor movements of the limb corresponding to the sensorimotor stroke lesion site compared with spontaneous recovery and control conditions, while motor strength remained unchanged. In contrast, SWopto during wakefulness had no effect. Furthermore, chronic SWopto during sleep were associated with local axonal sprouting as revealed by the increase of anatomic presynaptic and postsynaptic markers in the peri-infarct zone and corresponding contralesional areas to cortical circuit reorganization during stroke recovery. These results support a role for sleep SW in cortical circuit plasticity and sensorimotor recovery after stroke and provide a clinically relevant framework for rehabilitation strategies using neuromodulation during sleep.SIGNIFICANCE STATEMENT Brain stroke is one of the leading causes of death and major disabilities in the elderly worldwide. A better understanding of the pathophysiological mechanisms underlying spontaneous brain plasticity after stroke, together with an optimization of rehabilitative strategies, are essential to improve stroke treatments. Here, we investigate the role of optogenetically induced sleep slow waves in an animal model of ischemic stroke and identify sleep as a window for poststroke intervention that promotes neuroplasticity and facilitates sensorimotor recovery.

A Layer 3→5 Circuit in Auditory Cortex That Contributes to Pre-pulse Inhibition of the Acoustic Startle Response

While connectivity within sensory cortical circuits has been studied extensively, how these connections contribute to perception and behavior is not well understood. Here we tested the role of a circuit between layers 3 and 5 of auditory cortex in sound detection. We measured sound detection using a common variant of pre-pulse inhibition of the acoustic startle response, in which a silent gap in background noise acts as a cue that attenuates startle. We used the Nr5a-Cre driver line, which we found drove expression in the auditory cortex restricted predominantly to layer 3. Photoactivation of these cells evoked short-latency, highly reliable spiking in downstream layer 5 neurons, and attenuated startle responses similarly to gaps in noise. Photosuppression of these cells did not affect behavioral gap detection. Our data provide the first demonstration that direct activation of auditory cortical neurons is sufficient to attenuate the acoustic startle response, similar to the detection of a sound.

Circuit-Specific Plasticity of Callosal Inputs Underlies Cortical Takeover

Injury induces synaptic, circuit, and systems reorganization. After unilateral amputation or stroke, this functional loss disrupts the interhemispheric interaction between intact and deprived somatomotor cortices to recruit deprived cortex in response to intact limb stimulation. This recruitment has been implicated in enhanced intact sensory function. In other patients, maladaptive consequences such as phantom limb pain can occur. We used unilateral whisker denervation in male and female mice to detect circuitry alterations underlying interhemispheric cortical reorganization. Enhanced synaptic strength from the intact cortex via the corpus callosum (CC) onto deep neurons in deprived primary somatosensory barrel cortex (S1BC) has previously been detected. It was hypothesized that specificity in this plasticity may depend on to which area these neurons projected. Increased connectivity to somatomotor areas such as contralateral S1BC, primary motor cortex (M1) and secondary somatosensory cortex (S2) may underlie beneficial adaptations, while increased connectivity to pain areas like anterior cingulate cortex (ACC) might underlie maladaptive pain phenotypes. Neurons from the deprived S1BC that project to intact S1BC were hyperexcitable, had stronger responses and reduced inhibitory input to CC stimulation. M1-projecting neurons also showed increases in excitability and CC input strength that was offset with enhanced inhibition. S2 and ACC-projecting neurons showed no changes in excitability or CC input. These results demonstrate that subgroups of output neurons undergo dramatic and specific plasticity after peripheral injury. The changes in S1BC-projecting neurons likely underlie enhanced reciprocal connectivity of S1BC after unilateral deprivation consistent with the model that interhemispheric takeover supports intact whisker processing.SIGNIFICANCE STATEMENT Amputation, peripheral injury, and stroke patients experience widespread alterations in neural activity after sensory loss. A hallmark of this reorganization is the recruitment of deprived cortical space which likely aids processing and thus enhances performance on intact sensory systems. Conversely, this recruitment of deprived cortical space has been hypothesized to underlie phenotypes like phantom limb pain and hinder recovery. A mouse model of unilateral denervation detected remarkable specificity in alterations in the somatomotor circuit. These changes underlie increased reciprocal connectivity between intact and deprived cortical hemispheres. This increased connectivity may help explain the enhanced intact sensory processing detected in humans.

Laminar Subnetworks of Response Suppression in Macaque Primary Visual Cortex

Cortical inhibition plays an important role in information processing in the brain. However, the mechanisms by which inhibition and excitation are coordinated to generate functions in the six layers of the cortex remain unclear. Here, we measured laminar-specific responses to stimulus orientations in primary visual cortex (V1) of awake monkeys (male, Macaca mulatta). We distinguished inhibitory effects (suppression) from excitation, by taking advantage of the separability of excitation and inhibition in the orientation and time domains. We found two distinct types of suppression governing different layers. Fast suppression (FS) was strongest in input layers (4C and 6), and slow suppression (SS) was 3 times stronger in output layers (2/3 and 5). Interestingly, the two types of suppression were correlated with different functional properties measured with drifting gratings. FS was primarily correlated with orientation selectivity in input layers (r = -0.65, p < 10-9), whereas SS was primarily correlated with surround suppression in output layers (r = 0.61, p < 10-4). The earliest SS in layer 1 indicates the origin of cortical feedback for SS, in contrast to the feedforward/recurrent origin of FS. Our results reveal two V1 laminar subnetworks with different response suppression that may provide a general framework for laminar processing in other sensory cortices.SIGNIFICANCE STATEMENT This study sought to understand inhibitory effects (suppression) and their relationships with functional properties in the six different layers of the cortex. We found that the diversity of neural responses across layers in primary visual cortex (V1) could be fully explained by one excitatory and two suppressive components (fast and slow suppression). The distinct laminar distributions, origins, and functional roles of the two types of suppression provided a simplified representation of the differences between two V1 subnetworks (input network and output network). These results not only help to elucidate computational principles in macaque V1, but also provide a framework for general computation of cortical laminae in other sensory cortices.

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.