A genuine layer 4 in motor cortex with prototypical synaptic circuit connectivity

Cortical dynamics in hand/forelimb S1 and M1 evoked by brief photostimulation of the mouse's hand

Spiking activity along synaptic circuits linking primary somatosensory (S1) and motor (M1) areas is fundamental for sensorimotor integration in cortex. Circuits along the ascending somatosensory pathway through mouse hand/forelimb S1 and M1 were recently described in detail (Yamawaki et al., 2021). Here, we characterize the peripherally evoked spiking dynamics in these two cortical areas. Brief (5 ms) optogenetic photostimulation of the hand generated short (~25 ms) barrages of activity first in S1 (onset latency 15 ms) then M1 (10 ms later). The estimated propagation speed was 20-fold faster from hand to S1 than from S1 to M1. Amplitudes in M1 were strongly attenuated. Responses were typically triphasic, with suppression and rebound following the initial peak. Evoked activity in S1 was biased to middle layers, consistent with thalamocortical connectivity, while that in M1 was biased to upper layers, consistent with corticocortical connectivity. Parvalbumin (PV) inhibitory interneurons were involved in each phase, accounting for three quarters of the initial spikes generated in S1, and their selective photostimulation sufficed to evoke suppression and rebound in both S1 and M1. Partial silencing of S1 by PV activation during hand stimulation reduced the M1 sensory responses. Overall, these results characterize how evoked spiking activity propagates along the hand/forelimb transcortical loop, and illuminate how in vivo cortical dynamics relate to the underlying synaptic circuit organization in this system.

7 Tesla magnetic resonance spectroscopy estimates of GABA concentration relate to physiological measures of tonic inhibition in the human motor cortex

GABAergic neurotransmission within the cortex plays a key role in learning and is altered in several brain diseases. Quantification of bulk GABA in the human brain is typically obtained by magnetic resonance spectroscopy (MRS). However, the interpretation of MRS-GABA is still debated. A recent mathematical simulation contends that MRS detects extrasynaptic GABA, mediating tonic inhibition. Nevertheless, no empirical data have yet confirmed this hypothesis. Here we collected ultra-high-field 7 Tesla MRS and transcranial magnetic stimulation coupled with high-density electroencephalography (TMS-hdEEG) from the motor cortex of 20 healthy participants (age 23.95 ± 6.4 years), while they were at rest. We first applied a neural mass model (NMM) to TMS-evoked potentials to disentangle the contribution of different GABAergic pools. We then assessed to which of these different pools MRS-GABA was related to by means of parametric empirical Bayesian (PEB) analysis. We found that MRS-GABA was mostly positively related to the NMM-derived measures of tonic inhibition and overall functionality of the GABAergic synapse. This relationship was reliable enough to predict MRS-GABA from NMM-GABA. These findings clarify the mesoscopic underpinnings of GABA levels measured by MRS. Our work will help fulfil the promises of MRS-GABA, enhancing our understanding of human behaviour, brain physiology and pathophysiology. KEY POINTS: GABA neurotransmission is essential for synaptic plasticity and learning (especially motor learning) and is altered in several brain disorders, such as epilepsy and stroke. Quantification of GABA in the human brain is typically obtained by magnetic resonance spectroscopy (MRS). However, the interpretation of MRS-GABA is still debated. By using a biophysical neural mass model, here we show that MRS-GABA relates to physiological measures of tonic inhibition in the human cortex.

Decreased cellular excitability of pyramidal tract neurons in primary motor cortex leads to paradoxically increased network activity in simulated parkinsonian motor cortex

Recent evidence suggests that the primary motor cortex (M1) layer 5B pyramidal tract (PT5B) neurons show a decreased intrinsic excitability in mouse models of parkinsonism, which perhaps plays an important role in the pathophysiology of parkinsonian motor symptoms. PT5B neurons project to outputs in the brainstem and the spinal cord, leading to the direct motor expression of Parkinson's disease (PD) pathology. We set out to explore how the decreased PT5B neuron excitability influences the activity patterns of the M1 network. Using NEURON/NetPyNE simulators, we implemented detailed computer simulations of PT5B neurons based on control and 6-OHDA-treated mouse slice data. We placed these PT5B cells in an in vivo M1 network simulation, driven by ascending input from the thalamus and from other cortical areas. Simulated 6-OHDA-treated mouse PT5B neurons in an otherwise unmodified simulated M1 network resulted in major changes in LFP oscillatory power in the parkinsonian condition: an order of magnitude increase in beta band power around 15 Hz in the rest state and a lesser increase in beta power in the parkinsonian activated (movement) state. We demonstrated that relatively small changes in PT5B neuron excitability altered the patterns of activity throughout the M1 circuit. In particular, the decreased PT5B neuron excitability resulted in increased beta band power, which is a signature of PD pathophysiology.

Self-organized and self-sustained ensemble activity patterns in simulation of mouse primary motor cortex

The idea of self-organized signal processing in the cerebral cortex has become a focus of research since Beggs and Plentz1 reported avalanches in local field potential recordings from organotypic cultures and acute slices of rat somatosensory cortex. How the cortex intrinsically organizes signals remains unknown. A current hypothesis was proposed by the condensed matter physicists Bak, Tang, and Wiesenfeld2 when they conjectured that if neuronal avalanche activity followed inverse power law distributions, then brain activity may be set around phase transitions within self-organized signals. We asked if we would observe self-organized signals in an isolated slice of our data driven detailed simulation of the mouse primary motor cortex? If we did, would we observe avalanches with power-law distributions in size and duration and what would they look like? Our results demonstrate that a brief unstructured stimulus (100ms, 57μA current) to a small subset of neurons (about 181 of more than 10,000) in a simulated mouse primary motor cortex slice results in self-organized and self-sustained avalanches with power-law size and duration distributions and values similar to those reported from in vivo and in vitro experiments. We observed 4 cross-layer and cross-neuron population patterns, 3 of which displayed a dominant rhythmic component. Avalanches were each composed of one or more of the 4 population patterns.

Circuits and mechanisms for TMS-induced corticospinal waves: Connecting sensitivity analysis to the network graph

Transcranial magnetic stimulation (TMS) is a non-invasive, FDA-cleared treatment for neuropsychiatric disorders with broad potential for new applications, but the neural circuits that are engaged during TMS are still poorly understood. Recordings of neural activity from the corticospinal tract provide a direct readout of the response of motor cortex to TMS, and therefore a new opportunity to model neural circuit dynamics. The study goal was to use epidural recordings from the cervical spine of human subjects to develop a computational model of a motor cortical macrocolumn through which the mechanisms underlying the response to TMS, including direct and indirect waves, could be investigated. An in-depth sensitivity analysis was conducted to identify important pathways, and machine learning was used to identify common circuit features among these pathways. Sensitivity analysis identified neuron types that preferentially contributed to single corticospinal waves. Single wave preference could be predicted using the average connection probability of all possible paths between the activated neuron type and L5 pyramidal tract neurons (PTNs). For these activations, the total conduction delay of the shortest path to L5 PTNs determined the latency of the corticospinal wave. Finally, there were multiple neuron type activations that could preferentially modulate a particular corticospinal wave. The results support the hypothesis that different pathways of circuit activation contribute to different corticospinal waves with participation of both excitatory and inhibitory neurons. Moreover, activation of both afferents to the motor cortex as well as specific neuron types within the motor cortex initiated different I-waves, and the results were interpreted to propose the cortical origins of afferents that may give rise to certain I-waves. The methodology provides a workflow for performing computationally tractable sensitivity analyses on complex models and relating the results to the network structure to both identify and understand mechanisms underlying the response to acute stimulation.

A new map of the rat isocortex and proisocortex: cytoarchitecture and M2 receptor distribution patterns

Neurotransmitters and their receptors are key molecules in information transfer between neurons, thus enabling inter-areal communication. Therefore, multimodal atlases integrating the brain's cyto- and receptor architecture constitute crucial tools to understand the relationship between its structural and functional segregation. Cholinergic muscarinic M2 receptors have been shown to be an evolutionarily conserved molecular marker of primary sensory areas in the mammalian brain. To complement existing rodent atlases, we applied a silver cell body staining and quantitative in vitro receptor autoradiographic visualization of M2 receptors to alternating sections throughout the entire brain of five adult male Wistar rats (three sectioned coronally, one horizontally, one sagittally). Histological sections and autoradiographs were scanned at a spatial resolution of 1 µm and 20 µm per pixel, respectively, and files were stored as 8 bit images. We used these high-resolution datasets to create an atlas of the entire rat brain, including the olfactory bulb, cerebellum and brainstem. We describe the cyto- and M2 receptor architectonic features of 48 distinct iso- and proisocortical areas across the rat forebrain and provide their mean M2 receptor density. The ensuing parcellation scheme, which is discussed in the framework of existing comprehensive atlasses, includes the novel subdivision of mediomedial secondary visual area Oc2MM into anterior (Oc2MMa) and posterior (Oc2MMp) parts, and of lateral visual area Oc2L into rostrolateral (Oc2Lr), intermediate dorsolateral (Oc2Lid), intermediate ventrolateral (Oc2Liv) and caudolateral (Oc2Lc) secondary visual areas. The M2 receptor densities and the comprehensive map of iso-and proisocortical areas constitute useful tools for future computational and neuroscientific studies.

Hierarchical Gradients of Encoded Spatial and Sensory Information in the Neocortex Are Attenuated by Dorsal Hippocampal Lesions

During navigation, the neocortex actively integrates learned spatial context with current sensory experience to guide behaviors. However, the relative encoding of spatial and sensorimotor information among cortical cells, and whether hippocampal feedback continues to modify these properties after learning, remains poorly understood. Thus, two-photon microscopy of male and female Thy1-GCaMP6s mice was used to longitudinally image neurons spanning superficial retrosplenial cortex and layers II-Va of primary and secondary motor cortices before and after bilateral dorsal hippocampal lesions. During behavior on a familiar cued treadmill, the locations of two obstacles were interchanged to decouple place-tuning from cue-tuning among position-correlated cells with fields at those locations. Subpopulations of place and cue cells each formed interareal gradients such that higher-level cortical regions exhibited higher fractions of place cells, whereas lower-level regions exhibited higher fractions of cue cells. Position-correlated cells in the motor cortex also formed translaminar gradients; more superficial cells were more likely to exhibit fields and were more sparsely and precisely tuned than deeper cells. After dorsal hippocampal lesions, a neural representation of the learned environment persisted, but retrosplenial cortex exhibited significantly increased cue-tuning, and, in motor cortices, both position-correlated cell recruitment and population activity at the unstable obstacle locations became more homogeneously elevated across laminae. Altogether, these results support that the hippocampus continues to modulate cortical responses in familiar environments, and the relative impact of descending feedback obeys hierarchical interareal and interlaminar gradients opposite to the flow of ascending sensory inputs.

Where Do Core Thalamocortical Axons Terminate in Mammalian Neocortex When There Is No Cytoarchitecturally Distinct Layer 4?

Although the mammalian cerebral cortex is most often described as a hexalaminar structure, there are cortical areas (primary motor cortex) and species (elephants, cetaceans, and hippopotami), where a cytoarchitecturally indistinct, or absent, layer 4 is noted. Thalamocortical projections from the core, or first order, thalamic system terminate primarily in layers 4/inner 3. We explored the termination sites of core thalamocortical projections in cortical areas and in species where there is no cytoarchitecturally distinct layer 4 using the immunolocalization of vesicular glutamate transporter 2, a known marker of core thalamocortical axon terminals, in 31 mammal species spanning the eutherian radiation. Several variations from the canonical cortical column outline of layer 4 and core thalamocortical inputs were noted. In shrews/microchiropterans, layer 4 was present, but many core thalamocortical projections terminated in layer 1 in addition to layers 4 and inner 3. In primate primary visual cortex, the sublaminated layer 4 was associated with a specialized core thalamocortical projection pattern. In primate primary motor cortex, no cytoarchitecturally distinct layer 4 was evident and the core thalamocortical projections terminated throughout layer 3. In the African elephant, cetaceans, and river hippopotamus, no cytoarchitecturally distinct layer 4 was observed and core thalamocortical projections terminated primarily in inner layer 3 and less densely in outer layer 3. These findings are contextualized in terms of cortical processing, perception, and the evolutionary trajectory leading to an indistinct or absent cortical layer 4.

Decreased cellular excitability of pyramidal tract neurons in primary motor cortex leads to paradoxically increased network activity in simulated parkinsonian motor cortex

Decreased excitability of pyramidal tract neurons in layer 5B (PT5B) of primary motor cortex (M1) has recently been shown in a dopamine-depleted mouse model of parkinsonism. We hypothesized that decreased PT5B neuron excitability would substantially disrupt oscillatory and non-oscillatory firing patterns of neurons in layer 5 (L5) of primary motor cortex (M1). To test this hypothesis, we performed computer simulations using a previously validated computer model of mouse M1. Inclusion of the experimentally identified parkinsonism-associated decrease of PT5B excitability into our computational model produced a paradoxical increase in rest-state PT5B firing rate, as well as an increase in beta-band oscillatory power in local field potential (LFP). In the movement-state, PT5B population firing and LFP showed reduced beta and increased high-beta, low-gamma activity of 20-35 Hz in the parkinsonian, but not in control condition. The appearance of beta-band oscillations in parkinsonism would be expected to disrupt normal M1 motor output and contribute to motor activity deficits seen in patients with Parkinson's disease (PD).

Circuits in the motor cortex explain oscillatory responses to transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a popular method used to investigate brain function. Stimulation over the motor cortex evokes muscle contractions known as motor evoked potentials (MEPs) and also high-frequency volleys of electrical activity measured in the cervical spinal cord. The physiological mechanisms of these experimentally derived responses remain unclear, but it is thought that the connections between circuits of excitatory and inhibitory neurons play a vital role. Using a spiking neural network model of the motor cortex, we explained the generation of waves of activity, so called 'I-waves', following cortical stimulation. The model reproduces a number of experimentally known responses including direction of TMS, increased inhibition, and changes in strength. Using populations of thousands of neurons in a model of cortical circuitry we showed that the cortex generated transient oscillatory responses without any tuning, and that neuron parameters such as refractory period and delays influenced the pattern and timing of those oscillations. By comparing our network with simpler, previously proposed circuits, we explored the contributions of specific connections and found that recurrent inhibitory connections are vital in producing later waves that significantly impact the production of motor evoked potentials in downstream muscles (Thickbroom, 2011). This model builds on previous work to increase our understanding of how complex circuitry of the cortex is involved in the generation of I-waves.

From active affordance to active inference: vertical integration of cognition in the cerebral cortex through dual subcortical control systems

In previous papers, we proposed that the dorsal attention system's top-down control is regulated by the dorsal division of the limbic system, providing a feedforward or impulsive form of control generating expectancies during active inference. In contrast, we proposed that the ventral attention system is regulated by the ventral limbic division, regulating feedback constraints and error-correction for active inference within the neocortical hierarchy. Here, we propose that these forms of cognitive control reflect vertical integration of subcortical arousal control systems that evolved for specific forms of behavior control. The feedforward impetus to action is regulated by phasic arousal, mediated by lemnothalamic projections from the reticular activating system of the lower brainstem, and then elaborated by the hippocampus and dorsal limbic division. In contrast, feedback constraint-based on environmental requirements-is regulated by the tonic activation furnished by collothalamic projections from the midbrain arousal control centers, and then sustained and elaborated by the amygdala, basal ganglia, and ventral limbic division. In an evolutionary-developmental analysis, understanding these differing forms of active affordance-for arousal and motor control within the subcortical vertebrate neuraxis-may help explain the evolution of active inference regulating the cognition of expectancy and error-correction within the mammalian 6-layered neocortex.

Betz cells of the primary motor cortex

Betz cells, named in honor of Volodymyr Betz (1834-1894), who described them as "giant pyramids" in the primary motor cortex of primates and other mammalian species, are layer V extratelencephalic projection (ETP) neurons that directly innervate α-motoneurons of the brainstem and spinal cord. Despite their large volume and circumferential dendritic architecture, to date, no single molecular criterion has been established that unequivocally distinguishes adult Betz cells from other layer V ETP neurons. In primates, transcriptional signatures suggest the presence of at least two ETP neuron clusters that contain mature Betz cells; these are characterized by an abundance of axon guidance and oxidative phosphorylation transcripts. How neurodevelopmental programs drive the distinct positional and morphological features of Betz cells in humans remains unknown. Betz cells display a distinct biphasic firing pattern involving early cessation of firing followed by delayed sustained acceleration in spike frequency and magnitude. Few cell type-specific transcripts and electrophysiological characteristics are conserved between rodent layer V ETP neurons of the motor cortex and primate Betz cells. This has implications for the modeling of disorders that affect the motor cortex in humans, such as amyotrophic lateral sclerosis (ALS). Perhaps vulnerability to ALS is linked to the evolution of neural networks for fine motor control reflected in the distinct morphomolecular architecture of the human motor cortex, including Betz cells. Here, we discuss histological, molecular, and functional data concerning the position of Betz cells in the emerging taxonomy of neurons across diverse species and their role in neurological disorders.

Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics

We developed a detailed model of macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus, utilizing the NEURON simulator and NetPyNE tool. The A1 model simulates a cortical column with over 12,000 neurons and 25 million synapses, incorporating data on cell-type-specific neuron densities, morphology, and connectivity across six cortical layers. It is reciprocally connected to the MGB thalamus, which includes interneurons and core and matrix-layer-specific projections to A1. The model simulates multiscale measures, including physiological firing rates, local field potentials (LFPs), current source densities (CSDs), and electroencephalography (EEG) signals. Laminar CSD patterns, during spontaneous activity and in response to broadband noise stimulus trains, mirror experimental findings. Physiological oscillations emerge spontaneously across frequency bands comparable to those recorded in vivo. We elucidate population-specific contributions to observed oscillation events and relate them to firing and presynaptic input patterns. The model offers a quantitative theoretical framework to integrate and interpret experimental data and predict its underlying cellular and circuit mechanisms.

Cortical circuit dynamics underlying motor skill learning: from rodents to humans

Motor learning is crucial for the survival of many animals. Acquiring a new motor skill involves complex alterations in both local neural circuits in many brain regions and long-range connections between them. Such changes can be observed anatomically and functionally. The primary motor cortex (M1) integrates information from diverse brain regions and plays a pivotal role in the acquisition and refinement of new motor skills. In this review, we discuss how motor learning affects the M1 at synaptic, cellular, and circuit levels. Wherever applicable, we attempt to relate and compare findings in humans, non-human primates, and rodents. Understanding the underlying principles shared by different species will deepen our understanding of the neurobiological and computational basis of motor learning.

Transcriptomic cytoarchitecture reveals principles of human neocortex organization

Variation in cytoarchitecture is the basis for the histological definition of cortical areas. We used single cell transcriptomics and performed cellular characterization of the human cortex to better understand cortical areal specialization. Single-nucleus RNA-sequencing of 8 areas spanning cortical structural variation showed a highly consistent cellular makeup for 24 cell subclasses. However, proportions of excitatory neuron subclasses varied substantially, likely reflecting differences in connectivity across primary sensorimotor and association cortices. Laminar organization of astrocytes and oligodendrocytes also differed across areas. Primary visual cortex showed characteristic organization with major changes in the excitatory to inhibitory neuron ratio, expansion of layer 4 excitatory neurons, and specialized inhibitory neurons. These results lay the groundwork for a refined cellular and molecular characterization of human cortical cytoarchitecture and areal specialization.

Spatial atlas of the mouse central nervous system at molecular resolution

Spatially charting molecular cell types at single-cell resolution across the 3D volume is critical for illustrating the molecular basis of brain anatomy and functions. Single-cell RNA sequencing has profiled molecular cell types in the mouse brain1,2, but cannot capture their spatial organization. Here we used an in situ sequencing method, STARmap PLUS3,4, to profile 1,022 genes in 3D at a voxel size of 194 × 194 × 345 nm3, mapping 1.09 million high-quality cells across the adult mouse brain and spinal cord. We developed computational pipelines to segment, cluster and annotate 230 molecular cell types by single-cell gene expression and 106 molecular tissue regions by spatial niche gene expression. Joint analysis of molecular cell types and molecular tissue regions enabled a systematic molecular spatial cell-type nomenclature and identification of tissue architectures that were undefined in established brain anatomy. To create a transcriptome-wide spatial atlas, we integrated STARmap PLUS measurements with a published single-cell RNA-sequencing atlas1, imputing single-cell expression profiles of 11,844 genes. Finally, we delineated viral tropisms of a brain-wide transgene delivery tool, AAV-PHP.eB5,6. Together, this annotated dataset provides a single-cell resource that integrates the molecular spatial atlas, brain anatomy and the accessibility to genetic manipulation of the mammalian central nervous system.

Whole-Brain Evaluation of Cortical Microconnectomes

The brain is an organ that functions as a network of many elements connected in a nonuniform manner. In the brain, the neocortex is evolutionarily newest and is thought to be primarily responsible for the high intelligence of mammals. In the mature mammalian brain, all cortical regions are expected to have some degree of homology, but have some variations of local circuits to achieve specific functions performed by individual regions. However, few cellular-level studies have examined how the networks within different cortical regions differ. This study aimed to find rules for systematic changes of connectivity (microconnectomes) across 16 different cortical region groups. We also observed unknown trends in basic parameters in vitro such as firing rate and layer thickness across brain regions. Results revealed that the frontal group shows unique characteristics such as dense active neurons, thick cortex, and strong connections with deeper layers. This suggests the frontal side of the cortex is inherently capable of driving, even in isolation and that frontal nodes provide the driving force generating a global pattern of spontaneous synchronous activity, such as the default mode network. This finding provides a new hypothesis explaining why disruption in the frontal region causes a large impact on mental health.

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.

The covariance environment defines cellular niches for spatial inference

The tsunami of new multiplexed spatial profiling technologies has opened a range of computational challenges focused on leveraging these powerful data for biological discovery. A key challenge underlying computation is a suitable representation for features of cellular niches. Here, we develop the covariance environment (COVET), a representation that can capture the rich, continuous multivariate nature of cellular niches by capturing the gene-gene covariate structure across cells in the niche, which can reflect the cell-cell communication between them. We define a principled optimal transport-based distance metric between COVET niches and develop a computationally efficient approximation to this metric that can scale to millions of cells. Using COVET to encode spatial context, we develop environmental variational inference (ENVI), a conditional variational autoencoder that jointly embeds spatial and single-cell RNA-seq data into a latent space. Two distinct decoders either impute gene expression across spatial modality, or project spatial information onto dissociated single-cell data. We show that ENVI is not only superior in the imputation of gene expression but is also able to infer spatial context to disassociated single-cell genomics data.

When do bursts matter in the primary motor cortex? Investigating changes in the intermittencies of beta rhythms associated with movement states

Brain activity exhibits significant temporal structure that is not well captured in the power spectrum. Recently, attention has shifted to characterising the properties of intermittencies in rhythmic neural activity (i.e. bursts), yet the mechanisms that regulate them are unknown. Here, we present evidence from electrocorticography recordings made over the motor cortex to show that the statistics of bursts, such as duration or amplitude, in the beta frequency (14-30 Hz) band, significantly aid the classification of motor states such as rest, movement preparation, execution, and imagery. These features reflect nonlinearities not detectable in the power spectrum, with states increasing in nonlinearity from movement execution to preparation to rest. Further, we show using a computational model of the cortical microcircuit, constrained to account for burst features, that modulations of laminar specific inhibitory interneurons are responsible for the temporal organisation of activity. Finally, we show that the temporal characteristics of spontaneous activity can be used to infer the balance of cortical integration between incoming sensory information and endogenous activity. Critically, we contribute to the understanding of how transient brain rhythms may underwrite cortical processing, which in turn, could inform novel approaches for brain state classification, and modulation with novel brain-computer interfaces.

Generalized extinction of fear memory depends on co-allocation of synaptic plasticity in dendrites

Memories can be modified by new experience in a specific or generalized manner. Changes in synaptic connections are crucial for memory storage, but it remains unknown how synaptic changes associated with different memories are distributed within neuronal circuits and how such distributions affect specific or generalized modification by novel experience. Here we show that fear conditioning with two different auditory stimuli (CS) and footshocks (US) induces dendritic spine elimination mainly on different dendritic branches of layer 5 pyramidal neurons in the mouse motor cortex. Subsequent fear extinction causes CS-specific spine formation and extinction of freezing behavior. In contrast, spine elimination induced by fear conditioning with >2 different CS-USs often co-exists on the same dendritic branches. Fear extinction induces CS-nonspecific spine formation and generalized fear extinction. Moreover, activation of somatostatin-expressing interneurons increases the occurrence of spine elimination induced by different CS-USs on the same dendritic branches and facilitates the generalization of fear extinction. These findings suggest that specific or generalized modification of existing memories by new experience depends on whether synaptic changes induced by previous experiences are segregated or co-exist at the level of individual dendritic branches.

Morphological Features of Human Dendritic Spines

Dendritic spine features in human neurons follow the up-to-date knowledge presented in the previous chapters of this book. Human dendrites are notable for their heterogeneity in branching patterns and spatial distribution. These data relate to circuits and specialized functions. Spines enhance neuronal connectivity, modulate and integrate synaptic inputs, and provide additional plastic functions to microcircuits and large-scale networks. Spines present a continuum of shapes and sizes, whose number and distribution along the dendritic length are diverse in neurons and different areas. Indeed, human neurons vary from aspiny or "relatively aspiny" cells to neurons covered with a high density of intermingled pleomorphic spines on very long dendrites. In this chapter, we discuss the phylogenetic and ontogenetic development of human spines and describe the heterogeneous features of human spiny neurons along the spinal cord, brainstem, cerebellum, thalamus, basal ganglia, amygdala, hippocampal regions, and neocortical areas. Three-dimensional reconstructions of Golgi-impregnated dendritic spines and data from fluorescence microscopy are reviewed with ultrastructural findings to address the complex possibilities for synaptic processing and integration in humans. Pathological changes are also presented, for example, in Alzheimer's disease and schizophrenia. Basic morphological data can be linked to current techniques, and perspectives in this research field include the characterization of spines in human neurons with specific transcriptome features, molecular classification of cellular diversity, and electrophysiological identification of coexisting subpopulations of cells. These data would enlighten how cellular attributes determine neuron type-specific connectivity and brain wiring for our diverse aptitudes and behavior.

Neuronal-spiking-based closed-loop stimulation during cortical ON- and OFF-states in freely moving mice

The slow oscillation is a central neuronal dynamic during sleep, and is generated by alternating periods of high and low neuronal activity (ON- and OFF-states). Mounting evidence causally links the slow oscillation to sleep's functions, and it has recently become possible to manipulate the slow oscillation non-invasively and phase-specifically. These developments represent promising clinical avenues, but they also highlight the importance of improving our understanding of how ON/OFF-states affect incoming stimuli and what role they play in neuronal plasticity. Most studies using closed-loop stimulation rely on the electroencephalogram and local field potential signals, which reflect neuronal ON- and OFF-states only indirectly. Here we develop an online detection algorithm based on spiking activity recorded from laminar arrays in mouse motor cortex. We find that online detection of ON- and OFF-states reflects specific phases of spontaneous local field potential slow oscillation. Our neuronal-spiking-based closed-loop procedure offers a novel opportunity for testing the functional role of slow oscillation in sleep-related restorative processes and neural plasticity.

Distinct local and brain-wide networks are activated by optogenetic stimulation of neurons specific to each layer of motor cortex

Primary motor cortex (M1) consists of a stack of interconnected but distinct layers (L1-L6) which affect motor control through large-scale networks. However, the brain-wide functional influence of each layer is poorly understood. We sought to expand our knowledge of these layers' circuitry by combining Cre-driver mouse lines, optogenetics, fMRI, and electrophysiology. Neuronal activities initiated in Drd3 neurons (within L2/3) were mainly confined within M1, while stimulation of Scnn1a, Rbp4, and Ntsr1 neurons (within L4, L5, and L6, respectively) evoked distinct responses in M1 and motor-related subcortical regions, including striatum and motor thalamus. We also found that fMRI responses from targeted stimulations correlated with both local field potentials (LFPs) and spike changes. This study represents a step forward in our understanding of how different layers of primary motor cortex are embedded in brain-wide circuitry.

Evaluation of advances in cortical development using model systems

Compared with that of even the closest primates, the human cortex displays a high degree of specialization and expansion that largely emerges developmentally. Although decades of research in the mouse and other model systems has revealed core tenets of cortical development that are well preserved across mammalian species, small deviations in transcription factor expression, novel cell types in primates and/or humans, and unique cortical architecture distinguish the human cortex. Importantly, many of the genes and signaling pathways thought to drive human-specific cortical expansion also leave the brain vulnerable to disease, as the misregulation of these factors is highly correlated with neurodevelopmental and neuropsychiatric disorders. However, creating a comprehensive understanding of human-specific cognition and disease remains challenging. Here, we review key stages of cortical development and highlight known or possible differences between model systems and the developing human brain. By identifying the developmental trajectories that may facilitate uniquely human traits, we highlight open questions in need of approaches to examine these processes in a human context and reveal translatable insights into human developmental disorders.

The brain of the tree pangolin (Manis tricuspis). IX. The pallial telencephalon

A cyto‐, myelo‐, and chemoarchitectonic analysis of the pallial telencephalon of the tree pangolin is provided. As certain portions of the pallial telencephalon have been described previously (olfactory pallium, hippocampal formation, and amygdaloid complex), we focus on the claustrum and endopiriform nuclear complex, the white matter and white matter interstitial cells, and the areal organization of the cerebral cortex. Our analysis indicates that the organization of the pallial telencephalon of the tree pangolin is similar to that observed in many other mammals, and specifically quite similar to the closely related carnivores. The claustrum of the tree pangolin exhibits a combination of insular and laminar architecture, while the endopiriform nuclear complex contains three nuclei, both reminiscent of observations made in other mammals. The population of white matter interstitial cells resembles that observed in other mammals, while a distinct laminated organization of the intracortical white matter was revealed with parvalbumin immunostaining. The cerebral cortex of the tree pangolin presented with indistinct laminar boundaries as well as pyramidalization of the neurons in both layers 2 and 4. All cortical regions typically found in mammals were present, with the cortical areas within these regions often corresponding to what has been reported in carnivores. Given the similarity of the organization of the pallial telencephalon of the tree pangolin to that observed in other mammals, especially carnivores, it would be reasonable to assume that the neural processing afforded the tree pangolin by these structures does not differ dramatically to that of other mammals.

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.

Genetic Deficiency of p53 Leads to Structural, Functional, and Synaptic Deficits in Primary Somatosensory Cortical Neurons of Adult Mice

The tumor suppressor p53 plays a crucial role in embryonic neuron development and neurite growth, and its involvement in neuronal homeostasis has been proposed. To better understand how the lack of the p53 gene function affects neuronal activity, spine development, and plasticity, we examined the electrophysiological and morphological properties of layer 5 (L5) pyramidal neurons in the primary somatosensory cortex barrel field (S1BF) by using in vitro whole-cell patch clamp and in vivo two-photon imaging techniques in p53 knockout (KO) mice. We found that the spiking frequency, excitatory inputs, and sag ratio were decreased in L5 pyramidal neurons of p53KO mice. In addition, both in vitro and in vivo morphological analyses demonstrated that dendritic spine density in the apical tuft is decreased in L5 pyramidal neurons of p53KO mice. Furthermore, chronic imaging showed that p53 deletion decreased dendritic spine turnover in steady-state conditions, and prevented the increase in spine turnover associated with whisker stimulation seen in wildtype mice. In addition, the sensitivity of whisker-dependent texture discrimination was impaired in p53KO mice compared with wildtype controls. Together, these results suggest that p53 plays an important role in regulating synaptic plasticity by reducing neuronal excitability and the number of excitatory synapses in S1BF.

Abnormalities in Cortical GABAergic Interneurons of the Primary Motor Cortex Caused by Lis1 (Pafah1b1) Mutation Produce a Non-drastic Functional Phenotype

LIS1 (PAFAH1B1) plays a major role in the developing cerebral cortex, and haploinsufficient mutations cause human lissencephaly type 1. We have studied morphological and functional properties of the cerebral cortex of mutant mice harboring a deletion in the first exon of the mouse Lis1 (Pafah1b1) gene, which encodes for the LisH domain. The Lis1/sLis1 animals had an overall unaltered cortical structure but showed an abnormal distribution of cortical GABAergic interneurons (those expressing calbindin, calretinin, or parvalbumin), which mainly accumulated in the deep neocortical layers. Interestingly, the study of the oscillatory activity revealed an apparent inability of the cortical circuits to produce correct activity patterns. Moreover, the fast spiking (FS) inhibitory GABAergic interneurons exhibited several abnormalities regarding the size of the action potentials, the threshold for spike firing, the time course of the action potential after-hyperpolarization (AHP), the firing frequency, and the frequency and peak amplitude of spontaneous excitatory postsynaptic currents (sEPSC’s). These morphological and functional alterations in the cortical inhibitory system characterize the Lis1/sLis1 mouse as a model of mild lissencephaly, showing a phenotype less drastic than the typical phenotype attributed to classical lissencephaly. Therefore, the results described in the present manuscript corroborate the idea that mutations in some regions of the Lis1 gene can produce phenotypes more similar to those typically described in schizophrenic and autistic patients and animal models.

Pum2 and TDP-43 refine area-specific cytoarchitecture post-mitotically and modulate translation of Sox5, Bcl11b, and Rorb mRNAs in developing mouse neocortex

In the neocortex, functionally distinct areas process specific types of information. Area identity is established by morphogens and transcriptional master regulators, but downstream mechanisms driving area-specific neuronal specification remain unclear. Here, we reveal a role for RNA-binding proteins in defining area-specific cytoarchitecture. Mice lacking Pum2 or overexpressing human TDP-43 show apparent ‘motorization’ of layers IV and V of primary somatosensory cortex (S1), characterized by dramatic expansion of cells co-expressing Sox5 and Bcl11b/Ctip2, a hallmark of subcerebral projection neurons, at the expense of cells expressing the layer IV neuronal marker Rorβ. Moreover, retrograde labeling experiments with cholera toxin B in Pum2; Emx1-Cre and TDP43^A315T mice revealed a corresponding increase in subcerebral connectivity of these neurons in S1. Intriguingly, other key features of somatosensory area identity are largely preserved, suggesting that Pum2 and TDP-43 may function in a downstream program, rather than controlling area identity per se. Transfection of primary neurons and in utero electroporation (IUE) suggest cell-autonomous and post-mitotic modulation of Sox5, Bcl11b/Ctip2, and Rorβ levels. Mechanistically, we find that Pum2 and TDP-43 directly interact with and affect the translation of mRNAs encoding Sox5, Bcl11b/Ctip2, and Rorβ. In contrast, effects on the levels of these mRNAs were not detectable in qRT-PCR or single-molecule fluorescent in situ hybridization assays, and we also did not detect effects on their splicing or polyadenylation patterns. Our results support the notion that post-transcriptional regulatory programs involving translational regulation and mediated by Pum2 and TDP-43 contribute to elaboration of area-specific neuronal identity and connectivity in the neocortex.

Dopaminergic modulation of primary motor cortex: From cellular and synaptic mechanisms underlying motor learning to cognitive symptoms in Parkinson's disease

The primary motor cortex (M1) is crucial for movement execution, especially dexterous ones, but also for cognitive functions like motor learning. The acquisition of motor skills to execute dexterous movements requires dopamine-dependent and -independent plasticity mechanisms within M1. In addition to the basal ganglia, M1 is disturbed in Parkinson's disease (PD). However, little is known about how the lack of dopamine (DA), characteristic of PD, directly or indirectly impacts M1 circuitry. Here we review data from studies of PD patients and the substantial research in non-human primate and rodent models of DA depletion. These models enable us to understand the importance of DA in M1 physiology at the behavioral, network, cellular, and synaptic levels. We first summarize M1 functions and neuronal populations in mammals. We then look at the origin of M1 DA and the cellular location of its receptors and explore the impact of DA loss on M1 physiology, motor, and executive functions. Finally, we discuss how PD treatments impact M1 functions.

MultiMAP: dimensionality reduction and integration of multimodal data

Multimodal data is rapidly growing in many fields of science and engineering, including single-cell biology. We introduce MultiMAP, a novel algorithm for dimensionality reduction and integration. MultiMAP can integrate any number of datasets, leverages features not present in all datasets, is not restricted to a linear mapping, allows the user to specify the influence of each dataset, and is extremely scalable to large datasets. We apply MultiMAP to single-cell transcriptomics, chromatin accessibility, methylation, and spatial data and show that it outperforms current approaches. On a new thymus dataset, we use MultiMAP to integrate cells along a temporal trajectory. This enables quantitative comparison of transcription factor expression and binding site accessibility over the course of T cell differentiation, revealing patterns of expression versus binding site opening kinetics.

Cortical Cartography: Mapping Arealization Using Single-Cell Omics Technology

The cerebral cortex derives its cognitive power from a modular network of specialized areas processing a multitude of information. The assembly and organization of these regions is vital for human behavior and perception, as evidenced by the prevalence of area-specific phenotypes that manifest in neurodevelopmental and psychiatric disorders. Generations of scientists have examined the architecture of the human cortex, but efforts to capture the gene networks which drive arealization have been hampered by the lack of tractable models of human neurodevelopment. Advancements in "omics" technologies, imaging, and computational power have enabled exciting breakthroughs into the molecular and structural characteristics of cortical areas, including transcriptomic, epigenomic, metabolomic, and proteomic profiles of mammalian models. Here we review the single-omics atlases that have shaped our current understanding of cortical areas, and their potential to fuel a new era of multi-omic single-cell endeavors to interrogate both the developing and adult human cortex.

Comparative cellular analysis of motor cortex in human, marmoset and mouse

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

Morphological diversity of single neurons in molecularly defined cell types

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits.

A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1-3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas-containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities-is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

Phenotypic variation of transcriptomic cell types in mouse motor cortex

Cortical neurons exhibit extreme diversity in gene expression as well as in morphological and electrophysiological properties1,2. Most existing neural taxonomies are based on either transcriptomic3,4 or morpho-electric5,6 criteria, as it has been technically challenging to study both aspects of neuronal diversity in the same set of cells7. Here we used Patch-seq8 to combine patch-clamp recording, biocytin staining, and single-cell RNA sequencing of more than 1,300 neurons in adult mouse primary motor cortex, providing a morpho-electric annotation of almost all transcriptomically defined neural cell types. We found that, although broad families of transcriptomic types (those expressing Vip, Pvalb, Sst and so on) had distinct and essentially non-overlapping morpho-electric phenotypes, individual transcriptomic types within the same family were not well separated in the morpho-electric space. Instead, there was a continuum of variability in morphology and electrophysiology, with neighbouring transcriptomic cell types showing similar morpho-electric features, often without clear boundaries between them. Our results suggest that neuronal types in the neocortex do not always form discrete entities. Instead, neurons form a hierarchy that consists of distinct non-overlapping branches at the level of families, but can form continuous and correlated transcriptomic and morpho-electrical landscapes within families.

Spatially resolved cell atlas of the mouse primary motor cortex by MERFISH

A mammalian brain is composed of numerous cell types organized in an intricate manner to form functional neural circuits. Single-cell RNA sequencing allows systematic identification of cell types based on their gene expression profiles and has revealed many distinct cell populations in the brain1,2. Single-cell epigenomic profiling3,4 further provides information on gene-regulatory signatures of different cell types. Understanding how different cell types contribute to brain function, however, requires knowledge of their spatial organization and connectivity, which is not preserved in sequencing-based methods that involve cell dissociation. Here we used a single-cell transcriptome-imaging method, multiplexed error-robust fluorescence in situ hybridization (MERFISH)5, to generate a molecularly defined and spatially resolved cell atlas of the mouse primary motor cortex. We profiled approximately 300,000 cells in the mouse primary motor cortex and its adjacent areas, identified 95 neuronal and non-neuronal cell clusters, and revealed a complex spatial map in which not only excitatory but also most inhibitory neuronal clusters adopted laminar organizations. Intratelencephalic neurons formed a largely continuous gradient along the cortical depth axis, in which the gene expression of individual cells correlated with their cortical depths. Furthermore, we integrated MERFISH with retrograde labelling to probe projection targets of neurons of the mouse primary motor cortex and found that their cortical projections formed a complex network in which individual neuronal clusters project to multiple target regions and individual target regions receive inputs from multiple neuronal clusters.

A multimodal cell census and atlas of the mammalian primary motor cortex

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization^1-5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

A multimodal cell census and atlas of the mammalian primary motor cortex

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1-5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

Thalamus and claustrum control parallel layer 1 circuits in retrosplenial cortex

The granular retrosplenial cortex (RSG) is critical for both spatial and non-spatial behaviors, but the underlying neural codes remain poorly understood. Here, we use optogenetic circuit mapping in mice to reveal a double dissociation that allows parallel circuits in superficial RSG to process disparate inputs. The anterior thalamus and dorsal subiculum, sources of spatial information, strongly and selectively recruit small low-rheobase (LR) pyramidal cells in RSG. In contrast, neighboring regular-spiking (RS) cells are preferentially controlled by claustral and anterior cingulate inputs, sources of mostly non-spatial information. Precise sublaminar axonal and dendritic arborization within RSG layer 1, in particular, permits this parallel processing. Observed thalamocortical synaptic dynamics enable computational models of LR neurons to compute the speed of head rotation, despite receiving head direction inputs that do not explicitly encode speed. Thus, parallel input streams identify a distinct principal neuronal subtype ideally positioned to support spatial orientation computations in the RSG.

Comparative Ultrastructural Analysis of Thalamocortical Innervation of the Primary Motor Cortex and Supplementary Motor Area in Control and MPTP-Treated Parkinsonian Monkeys

The synaptic organization of thalamic inputs to motor cortices remains poorly understood in primates. Thus, we compared the regional and synaptic connections of vGluT2-positive thalamocortical glutamatergic terminals in the supplementary motor area (SMA) and the primary motor cortex (M1) between control and MPTP-treated parkinsonian monkeys. In controls, vGluT2-containing fibers and terminal-like profiles invaded layer II-III and Vb of M1 and SMA. A significant reduction of vGluT2 labeling was found in layer Vb, but not in layer II-III, of parkinsonian animals, suggesting a potential thalamic denervation of deep cortical layers in parkinsonism. There was a significant difference in the pattern of synaptic connectivity in layers II-III, but not in layer Vb, between M1 and SMA of control monkeys. However, this difference was abolished in parkinsonian animals. No major difference was found in the proportion of perforated versus macular post-synaptic densities at thalamocortical synapses between control and parkinsonian monkeys in both cortical regions, except for a slight increase in the prevalence of perforated axo-dendritic synapses in the SMA of parkinsonian monkeys. Our findings suggest that disruption of the thalamic innervation of M1 and SMA may underlie pathophysiological changes of the motor thalamocortical loop in the state of parkinsonism.

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.

The impact of (ab)normal maternal environment on cortical development

The cortex in the mammalian brain is the most complex brain region that integrates sensory information and coordinates motor and cognitive processes. To perform such functions, the cortex contains multiple subtypes of neurons that are generated during embryogenesis. Newly born neurons migrate to their proper location in the cortex, grow axons and dendrites, and form neuronal circuits. These developmental processes in the fetal brain are regulated to a large extent by a great variety of factors derived from the mother - starting from simple nutrients as building blocks and ending with hormones. Thus, when the normal maternal environment is disturbed due to maternal infection, stress, malnutrition, or toxic substances, it might have a profound impact on cortical development and the offspring can develop a variety of neurodevelopmental disorders. Here we first describe the major developmental processes which generate neuronal diversity in the cortex. We then review our knowledge of how most common maternal insults affect cortical development, perturb neuronal circuits, and lead to neurodevelopmental disorders. We further present a concept of selective vulnerability of cortical neuronal subtypes to maternal-derived insults, where the vulnerability of cortical neurons and their progenitors to an insult depends on the time (developmental period), place (location in the developing brain), and type (unique features of a cell type and an insult). Finally, we provide evidence for the existence of selective vulnerability during cortical development and identify the most vulnerable neuronal types, stages of differentiation, and developmental time for major maternal-derived insults.

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.

Multiscale modeling of cortical gradients: The role of mesoscale circuits for linking macro- and microscale gradients of cortical organization and hierarchical information processing

The gradient concept in neuroscience describes systematic and continuous progressions of features of cortical organization across the entire cortex. Recent multimodal studies revealed a macroscale gradient from primary sensory to transmodal association areas which is linked to increasing representational abstraction along the cortical hierarchy, and which is paralleled by microscale gradients of cytoarchitecture and gene expression profiles. Convergent or divergent evidence from these multimodal studies is then used to support inferences about the existence of one common or multiple scale-specific gradients of hierarchical information processing. This paper evaluates the validity of such inferences within the framework of multiscale modeling. In branches of physics and biology where multiscale modeling techniques are used, the simple averaging of microscale details can introduce errors in macroscale modeling if it ignores structures at the intermediate mesoscales of organization which affect system behavior. Conversely, information about mesoscale structures can be used to determine which microscale details are actually relevant to macroscale behavior. In this paper, I similarly argue that multiscale modeling of cortical gradients needs to take organization of mesoscale circuits into account if it affects the structure-function relation that the models describe. Information about these circuits provides crucial evidence for evaluating inferences from micro- and macroscale data to the role of cortical gradients in hierarchical information processing. My application of the multiscale modeling framework reveals that the gradient concept tracks multiple overlapping progressions of cortical properties, rather than one overall gradient of hierarchical information processing. I support this argument by proposing a mesoscale gradient of connectivity which describes architectural differences between granular and agranular circuits, and which helps us better understand the relation between neural connectivity and hierarchical information processing.

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

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

Structural dynamics and stability of corticocortical and thalamocortical axon terminals during motor learning

Synaptic plasticity is the cellular basis of learning and memory. When animals learn a novel motor skill, synaptic modifications are induced in the primary motor cortex (M1), and new postsynaptic dendritic spines relevant to motor memory are formed in the early stage of learning. However, it is poorly understood how presynaptic axonal boutons are formed, eliminated, and maintained during motor learning, and whether long-range corticocortical and thalamocortical axonal boutons show distinct structural changes during learning. In this study, we conducted two-photon imaging of presynaptic boutons of long-range axons in layer 1 (L1) of the mouse M1 during the 7-day learning of an accelerating rotarod task. The training-period-averaged rate of formation of boutons on axons projecting from the secondary motor cortical area increased, while the average rate of elimination of those from the motor thalamus (thalamic boutons) decreased. In particular, the elimination rate of thalamic boutons during days 4-7 was lower than that in untrained mice, and the fraction of pre-existing thalamic boutons that survived until day 7 was higher than that in untrained mice. Our results suggest that the late stabilization of thalamic boutons in M1 contributes to motor skill learning.