Quantitative morphologic classification of layer 5 neurons from mouse primary visual cortex

A cellular mechanism contributing to pain-induced analgesia

ABSTRACT

The anterior cingulate cortex (ACC) plays a crucial role in the perception of pain. It is consistently activated by noxious stimuli and its hyperactivity in chronic pain indicates plasticity in the local neuronal network. However, the way persistent pain effects and modifies different neuronal cell types in the ACC and how this contributes to sensory sensitization is not completely understood. This study confirms the existence of 2 primary subtypes of pyramidal neurons in layer 5 of the rostral, agranular ACC, which we could classify as intratelencephalic (IT) and cortico-subcortical (SC) projecting neurons, similar to other cortical brain areas. Through retrograde labeling, whole-cell patch-clamp recording, and morphological analysis, we thoroughly characterized their different electrophysiological and morphological properties. When examining the effects of peripheral inflammatory pain on these neuronal subtypes, we observed time-dependent plastic changes in excitability. During the acute phase, both subtypes exhibited reduced excitability, which normalized to pre-inflammatory levels after day 7. Daily conditioning with nociceptive stimuli during this period induced an increase in excitability specifically in SC neurons, which was correlated with a decrease in mechanical sensitization. Subsequent inhibition of the activity of SC neurons projecting to the periaqueductal gray with in vivo chemogenetics, resulted in reinstatement of the hypersensitivity. Accordingly, it was sufficient to enhance the excitability of these neurons chemogenetically in the inflammatory pain condition to induce hypoalgesia. These findings suggest a cell type-specific effect on the descending control of nociception and a cellular mechanism for pain-induced analgesia. Furthermore, increased excitability in this neuronal population is hypoalgesic rather than hyperalgesic.

Cell-type-specific cholinergic control of granular retrosplenial cortex with implications for angular velocity coding across brain states

Cholinergic receptor activation enables the persistent firing of cortical pyramidal neurons, providing a key cellular basis for theories of spatial navigation involving working memory, path integration, and head direction encoding. The granular retrosplenial cortex (RSG) is important for spatially-guided behaviors, but how acetylcholine impacts RSG neurons is unknown. Here, we show that a transcriptomically, morphologically, and biophysically distinct RSG cell-type - the low-rheobase (LR) neuron - has a very distinct expression profile of cholinergic muscarinic receptors compared to all other neighboring excitatory neuronal subtypes. LR neurons do not fire persistently in response to cholinergic agonists, in stark contrast to all other principal neuronal subtypes examined within the RSG and across midline cortex. This lack of persistence allows LR neuron models to rapidly compute angular head velocity (AHV), independent of cholinergic changes seen during navigation. Thus, LR neurons can consistently compute AHV across brain states, highlighting the specialized RSG neural codes supporting navigation.

Polymer Physics-Based Classification of Neurons

Recognizing that diverse morphologies of neurons are reminiscent of structures of branched polymers, we put forward a principled and systematic way of classifying neurons that employs the ideas of polymer physics. In particular, we use 3D coordinates of individual neurons, which are accessible in recent neuron reconstruction datasets from electron microscope images. We numerically calculate the form factor, F(q), a Fourier transform of the distance distribution of particles comprising an object of interest, which is routinely measured in scattering experiments to quantitatively characterize the structure of materials. For a polymer-like object consisting of n monomers spanning over a length scale of r, F(q) scales with the wavenumber [Formula: see text] as [Formula: see text] at an intermediate range of q, where [Formula: see text] is the fractal dimension or the inverse scaling exponent ([Formula: see text]) characterizing the geometrical feature ([Formula: see text]) of the object. F(q) can be used to describe a neuron morphology in terms of its size ([Formula: see text]) and the extent of branching quantified by [Formula: see text]. By defining the distance between F(q)s as a measure of similarity between two neuronal morphologies, we tackle the neuron classification problem. In comparison with other existing classification methods for neuronal morphologies, our F(q)-based classification rests solely on 3D coordinates of neurons with no prior knowledge of morphological features. When applied to publicly available neuron datasets from three different organisms, our method not only complements other methods but also offers a physical picture of how the dendritic and axonal branches of an individual neuron fill the space of dense neural networks inside the brain.

Translaminar recurrence from layer 5 suppresses superficial cortical layers

Information flow in the sensory cortex has been described as a predominantly feedforward sequence with deep layers as the output structure. Although recurrent excitatory projections from layer 5 (L5) to superficial L2/3 have been identified by anatomical and physiological studies, their functional impact on sensory processing remains unclear. Here, we use layer-selective optogenetic manipulations in the primary auditory cortex to demonstrate that feedback inputs from L5 suppress the activity of superficial layers regardless of the arousal level, contrary to the prediction from their excitatory connectivity. This suppressive effect is predominantly mediated by translaminar circuitry through intratelencephalic neurons, with an additional contribution of subcortical projections by pyramidal tract neurons. Furthermore, L5 activation sharpened tone-evoked responses of superficial layers in both frequency and time domains, indicating its impact on cortical spectro-temporal integration. Together, our findings establish a translaminar inhibitory recurrence from deep layers that sharpens feature selectivity in superficial cortical layers.

Sensory Experience as a Regulator of Structural Plasticity in the Developing Whisker-to-Barrel System

Cellular structures provide the physical foundation for the functionality of the nervous system, and their developmental trajectory can be influenced by the characteristics of the external environment that an organism interacts with. Historical and recent works have determined that sensory experiences, particularly during developmental critical periods, are crucial for information processing in the brain, which in turn profoundly influence neuronal and non-neuronal cortical structures that subsequently impact the animals' behavioral and cognitive outputs. In this review, we focus on how altering sensory experience influences normal/healthy development of the central nervous system, particularly focusing on the cerebral cortex using the rodent whisker-to-barrel system as an illustrative model. A better understanding of structural plasticity, encompassing multiple aspects such as neuronal, glial, and extra-cellular domains, provides a more integrative view allowing for a deeper appreciation of how all aspects of the brain work together as a whole.

A community-based transcriptomics classification and nomenclature of neocortical cell types

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

Portrait of visual cortical circuits for generating neural oscillation dynamics

The mouse primary visual cortex (V1) has emerged as a classical system to study neural circuit mechanisms underlying visual function and plasticity. A variety of efferent-afferent neuronal connections exists within the V1 and between the V1 and higher visual cortical areas or thalamic nuclei, indicating that the V1 system is more than a mere receiver in information processing. Sensory representations in the V1 are dynamically correlated with neural activity oscillations that are distributed across different cortical layers in an input-dependent manner. Circuits consisting of excitatory pyramidal cells (PCs) and inhibitory interneurons (INs) are the basis for generating neural oscillations. In general, INs are clustered with their adjacent PCs to form specific microcircuits that gate or filter the neural information. The interaction between these two cell populations has to be coordinated within a local circuit in order to preserve neural coding schemes and maintain excitation-inhibition (E-I) balance. Phasic alternations of the E-I balance can dynamically regulate temporal rhythms of neural oscillation. Accumulating experimental evidence suggests that the two major sub-types of INs, parvalbumin-expressing (PV⁺) cells and somatostatin-expressing (SOM⁺) INs, are active in controlling slow and fast oscillations, respectively, in the mouse V1. The review summarizes recent experimental findings on elucidating cellular or circuitry mechanisms for the generation of neural oscillations with distinct rhythms in either developing or matured mouse V1, mainly focusing on visual relaying circuits and distinct local inhibitory circuits.

Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex

Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques. NEW & NOTEWORTHY In vivo patch-clamp is the gold standard for intracellular recordings, but it is a very manual and highly skilled technique. The robot in this work demonstrates the most automated in vivo patch-clamp experiment to date, by enabling production of multiple, serial intracellular recordings without human intervention. The robot automates pipette filling, wire threading, pipette positioning, neuron hunting, break-in, delivering sensory stimulus, and recording quality control, enabling in vivo cell-type characterization.

Olfactory deficit is associated with mitral cell dysfunction in the olfactory bulb of P301S tau transgenic mice

Neurofibrillary tangles consisting of hyperphosphorylated tau (P-tau) are the neuropathological hallmark of Alzheimer's disease (AD), and olfaction disorder is an early symptom of AD. However, the link between P-tau aggregation and olfaction disorder remains unclear. In this study, the expression of P-tau in the olfactory bulb (OB), particularly in the mitral cell layer (MCL), external plexiform layer (EPL), and granule cell layer (GCL), of AD patients was found to be significantly higher than that in the OB of normal aging subjects, which suggested that these layers in the OB were susceptible to P-tau. The P301S tau transgenic mice (P301S mice) exhibit AD-like features, which can be characterized by olfactory dysfunction that precedes cognitive disorder. Importantly, the excessive P-tau expression in the OB of P301S mice, particularly in MCs, was associated with MC loss at 9 months of age, and decreased MC firing activities started to be observed at 2 months of age. Our results revealed that MCs might contribute to olfactory dysfunction in P301S mice. Furthermore, we described an aberrant dendro-dendritic synaptic structure between granule cells (GCs) and MCs and abnormal gamma oscillations in the EPL of the OB, and these findings indicated that P-tau might disrupt the regulation of MCs by GCs in P301S mice starting at 5 months of age. These data showed that the reduction in the MC firing frequency at 2 months of age might not be caused by GC suppression. Based on these findings, we speculated that MCs are a putative target for the treatment of P-tau-induced early olfactory dysfunction, and thus, an exploration of the specific causes and mechanisms of MC functional changes in P301S mice is crucial.

Modifications of the axon initial segment during the hibernation of the Syrian hamster

Mammalian hibernation is a natural process in which the brain undergoes profound adaptive changes that appear to protect the brain from extreme hypoxia and hypothermia. In addition to a virtual cessation of neural and metabolic activity, these changes include a decrease in adult neurogenesis; the retraction of neuronal dendritic trees; changes in dendritic spines and synaptic connections; fragmentation of the Golgi apparatus; and the phosphorylation of the microtubule-associated protein tau. Furthermore, alterations of microglial cells also occur in torpor. Importantly, all of these changes are rapidly and fully reversed when the animals arouse from torpor state, with no apparent brain damage occurring. Thus, hibernating animals are excellent natural models to study different aspects of brain plasticity. The axon initial segment (AIS) is critical for the initiation of action potentials in neurons and is an efficient site for the regulation of neural activity. This specialized structure-characterized by the expression of different types of ion channels and adhesion, scaffolding and cytoskeleton proteins-is subjected to morpho-functional plastic changes upon variations in neural activity or in pathological conditions. Here, we used immunocytochemistry and 3D confocal microscopy reconstruction techniques to measure the possible morphological differences in the AIS of neocortical (layers II-III and V) and hippocampal (CA1) neurons during the hibernation of the Syrian hamster. Our results indicate that the general integrity of the AIS is resistant to the ischemia/hypoxia conditions that are characteristic of the torpor phase of hibernation. In addition, the length of the AIS significantly increased in all the regions studied-by about 16-20% in torpor animals compared to controls, suggesting the existence of compensatory mechanisms in response to a decrease in neuronal activity during the torpor phase of hibernation. Furthermore, in double-labeling experiment, we found that the AIS in layer V of torpid animals was longer in neurons expressing phospho-tau than in those not labeled for phospho-tau. This suggests that AIS plastic changes were more marked in phospho-tau accumulating neurons. Overall, the results further emphasize that mammalian hibernation is a good physiological model to study AIS plasticity mechanisms in non-pathological conditions.

Mining Big Neuron Morphological Data

The advent of automatic tracing and reconstruction technology has led to a surge in the number of neurons 3D reconstruction data and consequently the neuromorphology research. However, the lack of machine-driven annotation schema to automatically detect the types of the neurons based on their morphology still hinders the development of this branch of science. Neuromorphology is important because of the interplay between the shape and functionality of neurons and the far-reaching impact on the diagnostics and therapeutics in neurological disorders. This survey paper provides a comprehensive research in the field of automatic neurons classification and presents the existing challenges, methods, tools, and future directions for automatic neuromorphology analytics. We summarize the major automatic techniques applicable in the field and propose a systematic data processing pipeline for automatic neuron classification, covering data capturing, preprocessing, analyzing, classification, and retrieval. Various techniques and algorithms in machine learning are illustrated and compared to the same dataset to facilitate ongoing research in the field.

Asynchronous suppression of visual cortex during absence seizures in stargazer mice

Absence epilepsy is a common childhood disorder featuring frequent cortical spike-wave seizures with a loss of awareness and behavior. Using the calcium indicator GCaMP6 with in vivo 2-photon cellular microscopy and simultaneous electrocorticography, we examined the collective activity profiles of individual neurons and surrounding neuropil across all layers in V1 during spike-wave seizure activity over prolonged periods in stargazer mice. We show that most (~80%) neurons in all cortical layers reduce their activity during seizures, whereas a smaller pool activates or remains neutral. Unexpectedly, ictal participation of identified single-unit activity is not fixed, but fluctuates on a flexible time scale from seizure to seizure. Pairwise correlation analysis of calcium activity reveals a surprising lack of synchrony among neurons and neuropil patches in all layers during seizures. Our results demonstrate asynchronous suppression of visual cortex during absence seizures, with potential implications for understanding cortical network function during EEG states of reduced awareness.

Absence epilepsy is associated with frequent generalized spike-wave seizures and loss of awareness. Here the authors use 2-photon calcium imaging of primary visual cortex in a genetic mouse model of absence epilepsy and find that cortical neurons are less active and more loosely coupled to the seizure EEG signature than previously believed.

Basal tree complexity shapes functional pathways in the prefrontal cortex

While the morphology of basal dendritic trees in cortical pyramidal neurons varies, the functional implications of this diversity are just starting to emerge. In layer 5 pyramidal neurons of the prefrontal cortex, for example, increased basal tree complexity determines the recruitment of these neurons into functional circuits. Here, we use a modeling approach to investigate whether and how the morphology of the basal tree mediates the functional output of neurons. We implemented 57 basal tree morphologies of layer 5 prefrontal pyramidal neurons of the rat and identified morphological types that were characterized by different response features, forming distinct functional types. These types were robust to a wide range of manipulations (distribution of active ionic mechanisms, NMDA conductance, somatic and apical tree morphology, or the number of activated synapses) and supported different temporal coding schemes at both the single neuron and the microcircuit level. We predict that the basal tree morphological diversity among neurons of the same class mediates their segregation into distinct functional pathways. Extension of our approach/findings to other cortical areas and/or layers or under pathological conditions may provide a generalized role of the basal trees for neuronal function.NEW & NOTEWORTHY Our results suggest that the segregation of neurons to different functional types based on their basal tree morphology is in large part independent of the distribution of active ionic mechanisms, NMDA conductance, somatic and apical tree morphology, and the number of activated synapses; different functional types support distinct temporal coding schemes. This can be exploited to create networks with diverse coding characteristics, thus contributing to the functional heterogeneity within the same layer and area.

Laminar Localization and Projection-Specific Properties of Presubicular Neurons Targeting the Lateral Mammillary Nucleus, Thalamus, or Medial Entorhinal Cortex

The presubiculum (PrS) is part of an interconnected network of distributed brain regions where individual neurons signal the animals heading direction. PrS sends axons to medial entorhinal cortex (MEC), it is reciprocally connected with anterior thalamic nuclei (ATNs), and it sends feedback projections to the lateral mammillary nucleus (LMN), involved in generating the head direction signal. The intrinsic properties of projecting neurons will influence the pathway-specific transmission of activity. Here, we used projection-specific labeling of presubicular neurons to identify MEC-, LMN-, and ATN-projecting neurons in mice. MEC-projecting neurons located in superficial layers II/III were mostly regular spiking pyramidal neurons, and we also identified a Martinotti-type GABAergic neuron. The cell bodies of LMN-projecting neurons were located in a well-delimited area in the middle portion of the PrS, which corresponds to layer IV. The physiology of LMN projecting, pyramidal neurons stood out with a tendency to fire in bursts of action potentials (APs) with rapid onset. These properties may be uniquely adapted to reliably transmit visual landmark information with short latency to upstream LMN. Neurons projecting to ATN were located in layers V/VI, and they were mostly regular spiking pyramidal neurons. Unsupervised cluster analysis of intrinsic properties suggested distinct physiological features for the different categories of projection neurons, with some similarities between MEC- and ATN-projecting neurons. Projection-specific subpopulations may serve separate functions in the PrS and may be engaged differently in transmitting head direction related information.

AII amacrine cells: quantitative reconstruction and morphometric analysis of electrophysiologically identified cells in live rat retinal slices imaged with multi-photon excitation microscopy

AII amacrine cells have been found in all mammalian retinas examined and play an important role for visual processing under both scotopic and photopic conditions. Whereas ultrastructural investigations have provided a detailed understanding of synaptic connectivity, there is little information available with respect to quantitative properties and variation of cellular morphology. Here, we performed whole-cell recordings from AII amacrine cells in rat retinal slices and filled the cells with fluorescent dyes. Multi-photon excitation microscopy was used to acquire image stacks and after deconvolution, we performed quantitative morphological reconstruction by computer-aided manual tracing. We reconstructed and performed morphometric analysis on 43 AII amacrine cells, with a focus on branching pattern, dendritic lengths and diameters, surface area, and number and distribution of dendritic varicosities. Compared to previous descriptions, the most surprising result was the considerable extent of branching, with the maximum branch order ranging from approximately 10-40. We found that AII amacrine cells conform to a recently described general structural design principle for neural arbors, where arbor density decreases proportionally to increasing territory size. We confirmed and quantified the bi-stratified morphology of AII amacrine cells by analyzing the arborizations as a function of retinal localization or with Sholl spheres. Principal component and cluster analysis revealed no evidence for morphological subtypes of AII amacrines. These results establish a database of morphometric properties important for studies of development, regeneration, degeneration, and disease processes, as well as a workflow compatible with compartmental modeling.

Prolonged corticosterone exposure induces dendritic spine remodeling and attrition in the rat medial prefrontal cortex

The stress-responsive hypothalamo-pituitary-adrenal (HPA) axis plays a central role in promoting adaptations acutely, whereas adverse effects on physiology and behavior following chronic challenges may result from overactivity of this system. Elevations in glucocorticoids, the end-products of HPA activation, play roles in adaptive and maladaptive processes by targeting cognate receptors throughout neurons in limbic cortical networks to alter synaptic functioning. Because previous work has shown that chronic stress leads to functionally relevant regressive alterations in dendritic spine shape and number in pyramidal neurons in the medial prefrontal cortex (mPFC), this study examines the capacity of sustained increases in circulating corticosterone (B) alone to alter dendritic spine morphology and density in this region. Subcutaneous B pellets were implanted in rats to provide continuous exposure to levels approximating the circadian mean or peak of the steroid for 1, 2, or 3 weeks. Pyramidal neurons in the prelimbic area of the mPFC were selected for intracellular fluorescent dye filling, followed by high-resolution three-dimensional imaging and analysis of dendritic arborization and spine morphometry. Two or more weeks of B exposure decreased dendritic spine volume in the mPFC, whereas higher dose exposure of the steroid resulted in apical dendritic retraction and spine loss in the same cell population, with thin spine subtypes showing the greatest degree of attrition. Finally, these structural alterations were noted to persist following a 3-week washout period and corresponding restoration of circadian HPA rhythmicity. These studies suggest that prolonged disruptions in adrenocortical functioning may be sufficient to induce enduring regressive structural and functional alterations in the mPFC. J. Comp. Neurol. 524:3729-3746, 2016. © 2016 Wiley Periodicals, Inc.

Morphological Neuron Classification Using Machine Learning

Classification and quantitative characterization of neuronal morphologies from histological neuronal reconstruction is challenging since it is still unclear how to delineate a neuronal cell class and which are the best features to define them by. The morphological neuron characterization represents a primary source to address anatomical comparisons, morphometric analysis of cells, or brain modeling. The objectives of this paper are (i) to develop and integrate a pipeline that goes from morphological feature extraction to classification and (ii) to assess and compare the accuracy of machine learning algorithms to classify neuron morphologies. The algorithms were trained on 430 digitally reconstructed neurons subjectively classified into layers and/or m-types using young and/or adult development state population of the somatosensory cortex in rats. For supervised algorithms, linear discriminant analysis provided better classification results in comparison with others. For unsupervised algorithms, the affinity propagation and the Ward algorithms provided slightly better results.

Mixed functional microarchitectures for orientation selectivity in the mouse primary visual cortex

A minicolumn is the smallest anatomical module in the cortical architecture, but it is still in debate whether it serves as functional units for cortical processing. In the rodent primary visual cortex (V1), neurons with different preferred orientations are mixed horizontally in a salt and pepper manner, but vertical functional organization was not examined. In this study, we found that neurons with similar orientation preference are weakly but significantly clustered vertically in a short length and horizontally in the scale of a minicolumn. Interestingly, the vertical clustering is found only in a part of minicolumns, and others are composed of neurons with a variety of orientation preferences. Thus, the mouse V1 is a mixture of vertical clusters of neurons with various degrees of orientation similarity, which may be the compromise between the brain size and keeping the vertical clusters of similarly tuned neurons at least in a subset of clusters.

Primary visual cortical neurons display mostly a salt and pepper arrangement of orientation preferences along the horizontal cortical axis. Here the authors show that a significant subset of minicolumns, one-cell wide arrays of cells arranged along the vertical axis, show similar orientation tuning preferences.

Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function

Cortical layer 5 (L5) pyramidal neurons integrate inputs from many sources and distribute outputs to cortical and subcortical structures. Previous studies demonstrate two L5 pyramid types: cortico-cortical (CC) and cortico-subcortical (CS). We characterize connectivity and function of these cell types in mouse primary visual cortex and reveal a new subtype. Unlike previously described L5 CC and CS neurons, this new subtype does not project to striatum [cortico-cortical, non-striatal (CC-NS)] and has distinct morphology, physiology, and visual responses. Monosynaptic rabies tracing reveals that CC neurons preferentially receive input from higher visual areas, while CS neurons receive more input from structures implicated in top-down modulation of brain states. CS neurons are also more direction-selective and prefer faster stimuli than CC neurons. These differences suggest distinct roles as specialized output channels, with CS neurons integrating information and generating responses more relevant to movement control and CC neurons being more important in visual perception.

Layer 4 pyramidal neurons exhibit robust dendritic spine plasticity in vivo after input deprivation

Pyramidal neurons in layers 2/3 and 5 of primary somatosensory cortex (S1) exhibit somewhat modest synaptic plasticity after whisker input deprivation. Whether neurons involved at earlier steps of sensory processing show more or less plasticity has not yet been examined. Here, we used longitudinal in vivo two-photon microscopy to investigate dendritic spine dynamics in apical tufts of GFP-expressing layer 4 (L4) pyramidal neurons of the vibrissal (barrel) S1 after unilateral whisker trimming. First, we characterize the molecular, anatomical, and electrophysiological properties of identified L4 neurons in Ebf2-Cre transgenic mice. Next, we show that input deprivation results in a substantial (∼50%) increase in the rate of dendritic spine loss, acutely (4-8 d) after whisker trimming. This robust synaptic plasticity in L4 suggests that primary thalamic recipient pyramidal neurons in S1 may be particularly sensitive to changes in sensory experience. Ebf2-Cre mice thus provide a useful tool for future assessment of initial steps of sensory processing in S1.

Genotype-specific effects of Mecp2 loss-of-function on morphology of Layer V pyramidal neurons in heterozygous female Rett syndrome model mice

Rett syndrome (RTT) is a progressive neurological disorder primarily caused by mutations in the X-linked gene methyl-CpG-binding protein 2 (MECP2). The heterozygous female brain consists of mosaic of neurons containing both wild-type MeCP2 (MeCP2+) and mutant MeCP2 (MeCP2-). Three-dimensional morphological analysis was performed on individually genotyped layer V pyramidal neurons in the primary motor cortex of heterozygous (Mecp2(+/-) ) and wild-type (Mecp2(+/+) ) female mice ( > 6 mo.) from the Mecp2(tm1.1Jae) line. Comparing basal dendrite morphology, soma and nuclear size of MeCP2+ to MeCP2- neurons reveals a significant cell autonomous, genotype specific effect of Mecp2. MeCP2- neurons have 15% less total basal dendritic length, predominantly in the region 70-130 μm from the cell body and on average three fewer branch points, specifically loss in the second and third branch orders. Soma and nuclear areas of neurons of mice were analyzed across a range of ages (5-21 mo.) and X-chromosome inactivation (XCI) ratios (12-56%). On average, MeCP2- somata and nuclei were 15 and 13% smaller than MeCP2+ neurons respectively. In most respects branching morphology of neurons in wild-type brains (MeCP2 WT) was not distinguishable from MeCP2+ but somata and nuclei of MeCP2 WT neurons were larger than those of MeCP2+ neurons. These data reveal cell autonomous effects of Mecp2 mutation on dendritic morphology, but also suggest non-cell autonomous effects with respect to cell size. MeCP2+ and MeCP2- neuron sizes were not correlated with age, but were correlated with XCI ratio. Unexpectedly the MeCP2- neurons were smallest in brains where the XCI ratio was highly skewed toward MeCP2+, i.e., wild-type. This raises the possibility of cell non-autonomous effects that act through mechanisms other than globally secreted factors; perhaps competition for synaptic connections influences cell size and morphology in the genotypically mosaic brain of RTT model mice.

Electrophysiological properties of genetically identified subtypes of layer 5 neocortical pyramidal neurons: Ca²⁺ dependence and differential modulation by norepinephrine

We studied neocortical pyramidal neurons from two lines of bacterial artificial chromosome mice (etv1 and glt; Gene Expression Nervous System Atlas: GENSAT project), each of which expresses enhanced green fluorescent protein (EGFP) in a different subpopulation of layer 5 pyramidal neurons. In barrel cortex, etv1 and glt pyramidal cells were previously reported to differ in terms of their laminar distribution, morphology, thalamic inputs, cellular targets, and receptive field size. In this study, we measured the laminar distribution of etv1 and glt cells. On average, glt cells were located more deeply; however, the distributions of etv1 and glt cells extensively overlap in layer 5. To test whether these two cell types differed in electrophysiological properties that influence firing behavior, we prepared acute brain slices from 2-4-wk-old mice, where EGFP-positive cells in somatosensory cortex were identified under epifluorescence and then studied using whole cell current- or voltage-clamp recordings. We studied the details of action potential parameters and repetitive firing, characterized by the larger slow afterhyperpolarizations (AHPs) in etv1 neurons and larger medium AHPs (mAHPS) in glt cells, and compared currents underlying the mAHP and slow AHP (sAHP) in etv1 and glt neurons. Etv1 cells exhibited lower dV/dt for spike polarization and repolarization and reduced direct current (DC) gain (lower f-I slope) for repetitive firing than glt cells. Most importantly, we found that 1) differences in the expression of Ca(2+)-dependent K(+) conductances (small-conductance calcium-activated potassium channels and sAHP channels) determine major functional differences between etv1 and glt cells, and 2) there is differential modulation of etv1 and glt neurons by norepinephrine.

Classifying GABAergic interneurons with semi-supervised projected model-based clustering

OBJECTIVES

A recently introduced pragmatic scheme promises to be a useful catalog of interneuron names. We sought to automatically classify digitally reconstructed interneuronal morphologies according to this scheme. Simultaneously, we sought to discover possible subtypes of these types that might emerge during automatic classification (clustering). We also investigated which morphometric properties were most relevant for this classification.

MATERIALS AND METHODS

A set of 118 digitally reconstructed interneuronal morphologies classified into the common basket (CB), horse-tail (HT), large basket (LB), and Martinotti (MA) interneuron types by 42 of the world's leading neuroscientists, quantified by five simple morphometric properties of the axon and four of the dendrites. We labeled each neuron with the type most commonly assigned to it by the experts. We then removed this class information for each type separately, and applied semi-supervised clustering to those cells (keeping the others' cluster membership fixed), to assess separation from other types and look for the formation of new groups (subtypes). We performed this same experiment unlabeling the cells of two types at a time, and of half the cells of a single type at a time. The clustering model is a finite mixture of Gaussians which we adapted for the estimation of local (per-cluster) feature relevance. We performed the described experiments on three different subsets of the data, formed according to how many experts agreed on type membership: at least 18 experts (the full data set), at least 21 (73 neurons), and at least 26 (47 neurons).

RESULTS

Interneurons with more reliable type labels were classified more accurately. We classified HT cells with 100% accuracy, MA cells with 73% accuracy, and CB and LB cells with 56% and 58% accuracy, respectively. We identified three subtypes of the MA type, one subtype of CB and LB types each, and no subtypes of HT (it was a single, homogeneous type). We got maximum (adapted) Silhouette width and ARI values of 1, 0.83, 0.79, and 0.42, when unlabeling the HT, CB, LB, and MA types, respectively, confirming the quality of the formed cluster solutions. The subtypes identified when unlabeling a single type also emerged when unlabeling two types at a time, confirming their validity. Axonal morphometric properties were more relevant that dendritic ones, with the axonal polar histogram length in the [π, 2π) angle interval being particularly useful.

CONCLUSIONS

The applied semi-supervised clustering method can accurately discriminate among CB, HT, LB, and MA interneuron types while discovering potential subtypes, and is therefore useful for neuronal classification. The discovery of potential subtypes suggests that some of these types are more heterogeneous that previously thought. Finally, axonal variables seem to be more relevant than dendritic ones for distinguishing among the CB, HT, LB, and MA interneuron types.

Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty

Interneuron classification is an important and long-debated topic in neuroscience. A recent study provided a data set of digitally reconstructed interneurons classified by 42 leading neuroscientists according to a pragmatic classification scheme composed of five categorical variables, namely, of the interneuron type and four features of axonal morphology. From this data set we now learned a model which can classify interneurons, on the basis of their axonal morphometric parameters, into these five descriptive variables simultaneously. Because of differences in opinion among the neuroscientists, especially regarding neuronal type, for many interneurons we lacked a unique, agreed-upon classification, which we could use to guide model learning. Instead, we guided model learning with a probability distribution over the neuronal type and the axonal features, obtained, for each interneuron, from the neuroscientists' classification choices. We conveniently encoded such probability distributions with Bayesian networks, calling them label Bayesian networks (LBNs), and developed a method to predict them. This method predicts an LBN by forming a probabilistic consensus among the LBNs of the interneurons most similar to the one being classified. We used 18 axonal morphometric parameters as predictor variables, 13 of which we introduce in this paper as quantitative counterparts to the categorical axonal features. We were able to accurately predict interneuronal LBNs. Furthermore, when extracting crisp (i.e., non-probabilistic) predictions from the predicted LBNs, our method outperformed related work on interneuron classification. Our results indicate that our method is adequate for multi-dimensional classification of interneurons with probabilistic labels. Moreover, the introduced morphometric parameters are good predictors of interneuron type and the four features of axonal morphology and thus may serve as objective counterparts to the subjective, categorical axonal features.

Anatomy of hierarchy: feedforward and feedback pathways in macaque visual cortex

The laminar location of the cell bodies and terminals of interareal connections determines the hierarchical structural organization of the cortex and has been intensively studied. However, we still have only a rudimentary understanding of the connectional principles of feedforward (FF) and feedback (FB) pathways. Quantitative analysis of retrograde tracers was used to extend the notion that the laminar distribution of neurons interconnecting visual areas provides an index of hierarchical distance (percentage of supragranular labeled neurons [SLN]). We show that: 1) SLN values constrain models of cortical hierarchy, revealing previously unsuspected areal relations; 2) SLN reflects the operation of a combinatorial distance rule acting differentially on sets of connections between areas; 3) Supragranular layers contain highly segregated bottom-up and top-down streams, both of which exhibit point-to-point connectivity. This contrasts with the infragranular layers, which contain diffuse bottom-up and top-down streams; 4) Cell filling of the parent neurons of FF and FB pathways provides further evidence of compartmentalization; 5) FF pathways have higher weights, cross fewer hierarchical levels, and are less numerous than FB pathways. Taken together, the present results suggest that cortical hierarchies are built from supra- and infragranular counterstreams. This compartmentalized dual counterstream organization allows point-to-point connectivity in both bottom-up and top-down directions.

A comparison of manual neuronal reconstruction from biocytin histology or 2-photon imaging: morphometry and computer modeling

Accurate 3D reconstruction of neurons is vital for applications linking anatomy and physiology. Reconstructions are typically created using Neurolucida after biocytin histology (BH). An alternative inexpensive and fast method is to use freeware such as Neuromantic to reconstruct from fluorescence imaging (FI) stacks acquired using 2-photon laser-scanning microscopy during physiological recording. We compare these two methods with respect to morphometry, cell classification, and multicompartmental modeling in the NEURON simulation environment. Quantitative morphological analysis of the same cells reconstructed using both methods reveals that whilst biocytin reconstructions facilitate tracing of more distal collaterals, both methods are comparable in representing the overall morphology: automated clustering of reconstructions from both methods successfully separates neocortical basket cells from pyramidal cells but not BH from FI reconstructions. BH reconstructions suffer more from tissue shrinkage and compression artifacts than FI reconstructions do. FI reconstructions, on the other hand, consistently have larger process diameters. Consequently, significant differences in NEURON modeling of excitatory post-synaptic potential (EPSP) forward propagation are seen between the two methods, with FI reconstructions exhibiting smaller depolarizations. Simulated action potential backpropagation (bAP), however, is indistinguishable between reconstructions obtained with the two methods. In our hands, BH reconstructions are necessary for NEURON modeling and detailed morphological tracing, and thus remain state of the art, although they are more labor intensive, more expensive, and suffer from a higher failure rate due to the occasional poor outcome of histological processing. However, for a subset of anatomical applications such as cell type identification, FI reconstructions are superior, because of indistinguishable classification performance with greater ease of use, essentially 100% success rate, and lower cost.

Preserved excitatory-inhibitory balance of cortical synaptic inputs following deprived eye stimulation after a saturating period of monocular deprivation in rats

Monocular deprivation (MD) during development leads to a dramatic loss of responsiveness through the deprived eye in primary visual cortical neurons, and to degraded spatial vision (amblyopia) in all species tested so far, including rodents. Such loss of responsiveness is accompanied since the beginning by a decreased excitatory drive from the thalamo-cortical inputs. However, in the thalamorecipient layer 4, inhibitory interneurons are initially unaffected by MD and their synapses onto pyramidal cells potentiate. It remains controversial whether ocular dominance plasticity similarly or differentially affects the excitatory and inhibitory synaptic conductances driven by visual stimulation of the deprived eye and impinging onto visual cortical pyramids, after a saturating period of MD. To address this issue, we isolated visually-driven excitatory and inhibitory conductances by in vivo whole-cell recordings from layer 4 regular-spiking neurons in the primary visual cortex (V1) of juvenile rats. We found that a saturating period of MD comparably reduced visually-driven excitatory and inhibitory conductances driven by visual stimulation of the deprived eye. Also, the excitatory and inhibitory conductances underlying the synaptic responses driven by the ipsilateral, left open eye were similarly potentiated compared to controls. Multiunit recordings in layer 4 followed by spike sorting indicated that the suprathreshold loss of responsiveness and the MD-driven ocular preference shifts were similar for narrow spiking, putative inhibitory neurons and broad spiking, putative excitatory neurons. Thus, by the time the plastic response has reached a plateau, inhibitory circuits adjust to preserve the normal balance between excitation and inhibition in the cortical network of the main thalamorecipient layer.

Cortical regulation of dopaminergic neurons: role of the midbrain superior colliculus

Dopaminergic (DA) neurons respond to stimuli in a wide range of modalities, although the origin of the afferent sensory signals has only recently begun to emerge. In the case of vision, an important source of short-latency sensory information seems to be the midbrain superior colliculus (SC). However, longer-latency responses have been identified that are less compatible with the primitive perceptual capacities of the colliculus. Rather, they seem more in keeping with the processing capabilities of the cortex. Given that there are robust projections from the cortex to the SC, we examined whether cortical information could reach DA neurons via a relay in the colliculus. The somatosensory barrel cortex was stimulated electrically in the anesthetized rat with either single pulses or pulse trains. Although single pulses produced small phasic activations in the colliculus, they did not elicit responses in the majority of DA neurons. However, after disinhibitory intracollicular injections of the GABA_A antagonist bicuculline, collicular responses were substantially enhanced and previously unresponsive DA neurons now exhibited phasic excitations or inhibitions. Pulse trains applied to the cortex led to phasic changes (excitations to inhibitions) in the activity of DA neurons at baseline. These were blocked or attenuated by intracollicular administration of the GABA_A agonist muscimol. Taken together, the results indicate that the cortex can communicate with DA neurons via a relay in the SC. As a consequence, DA neuronal activity reflecting the unexpected occurrence of salient events and that signaling more complex stimulus properties may have a common origin.

Functional morphometric analysis in cellular behaviors: shape and size matter

Cellular morphogenesis in response to biophysical and topographical cues provides insights into cytoskeletal status, biointerface communications, and phenotypic adaptations in an incessant signaling feedback that governs cellular fate. Morphometric characterization is an important element in the study of the dynamic cellular behaviors, in their interactive response to environmental influence exerted by culture system. They collectively serve to reflect cellular proliferation, migration, and differentiation, which may serve as prognostic indices for clinical and pathological diagnosis. Various parameters are proposed to categorize morphological adaptations in relation to cellular function. In this review, the underlying principles, assumptions, and limitations of morphological characterizations are discussed. The significance, challenges, and implications of quantitative morphometric characterization of cell shapes and sizes in determining cellular functions are discussed.

Coding and decoding with dendrites

Since the discovery of complex, voltage dependent mechanisms in the dendrites of multiple neuron types, great effort has been devoted in search of a direct link between dendritic properties and specific neuronal functions. Over the last few years, new experimental techniques have allowed the visualization and probing of dendritic anatomy, plasticity and integrative schemes with unprecedented detail. This vast amount of information has caused a paradigm shift in the study of memory, one of the most important pursuits in Neuroscience, and calls for the development of novel theories and models that will unify the available data according to some basic principles. Traditional models of memory considered neural cells as the fundamental processing units in the brain. Recent studies however are proposing new theories in which memory is not only formed by modifying the synaptic connections between neurons, but also by modifications of intrinsic and anatomical dendritic properties as well as fine tuning of the wiring diagram. In this review paper we present previous studies along with recent findings from our group that support a key role of dendrites in information processing, including the encoding and decoding of new memories, both at the single cell and the network level.

Odor enrichment sculpts the abundance of olfactory bulb mitral cells

Mitral cells are the primary output cell from the olfactory bulb conveying olfactory sensory information to higher cortical areas. Gene-targeted deletion of the Shaker potassium channel Kv1.3 alters voltage-dependence and inactivation kinetics of mitral cell current properties, which contribute to the "Super-smeller" phenotype observed in Kv1.3-null mice. The goal of the current study was to determine if morphology and density are influenced by mitral cell excitability, olfactory environment, and stage of development. Wildtype (WT) and Kv1.3-null (KO) mice were exposed to a single odorant (peppermint or citralva) for 30 days. Under unstimulated conditions, postnatal day 20 KO mice had more mitral cells than their WT counterparts, but no difference in cell size. Odor-enrichment with peppermint, an olfactory and trigeminal stimulus, decreased the number of mitral cells in three month and one year old mice of both genotypes. Mitral cell density was most sensitive to odor-stimulation in three month WT mice. Enrichment at the same age with citralva, a purely olfactory stimulus, decreased cell density regardless of genotype. There were no significant changes in cell body shape in response to citralva exposure, but the cell area was greater in WT mice and selectively greater in the ventral region of the OB in KO mice. This suggests that trigeminal or olfactory stimulation may modify mitral cell area and density while not impacting cell body shape. Mitral cell density can therefore be modulated by the voltage and sensory environment to alter information processing or olfactory perception.

Digital morphometry of rat cerebellar climbing fibers reveals distinct branch and bouton types

Cerebellar climbing fibers (CFs) provide powerful excitatory input to Purkinje cells (PCs), which represent the sole output of the cerebellar cortex. Recent discoveries suggest that CFs have information-rich signaling properties important for cerebellar function, beyond eliciting the well known all-or-none PC complex spike. CF morphology has not been quantitatively analyzed at the same level of detail as its biophysical properties. Because morphology can greatly influence function, including the capacity for information processing, it is important to understand CF branching structure in detail, as well as its variability across and within arbors. We have digitally reconstructed 68 rat CFs labeled using biotinylated dextran amine injected into the inferior olive and comprehensively quantified their morphology. CF structure was considerably diverse even within the same anatomical regions. Distinctly identifiable primary, tendril, and distal branches could be operationally differentiated by the relative size of the subtrees at their initial bifurcations. Additionally, primary branches were more directed toward the cortical surface and had fewer and less pronounced synaptic boutons, suggesting they prioritize efficient and reliable signal propagation. Tendril and distal branches were spatially segregated and bouton dense, indicating specialization in signal transmission. Furthermore, CFs systematically targeted molecular layer interneuron cell bodies, especially at terminal boutons, potentially instantiating feedforward inhibition on PCs. This study offers the most detailed and comprehensive characterization of CF morphology to date. The reconstruction files and metadata are publicly distributed at NeuroMorpho.org.

A biophysical signature of network affiliation and sensory processing in mitral cells

One defining characteristic of the mammalian brain is its neuronal diversity. For a given region, substructure, layer or even cell type, variability in neuronal morphology and connectivity persists. Although it is well known that such cellular properties vary considerably according to neuronal type, the substantial biophysical diversity of neurons of the same morphological class is typically averaged out and ignored. Here we show that the amplitude of hyperpolarization-evoked sag of membrane potential recorded in olfactory bulb mitral cells is an emergent, homotypic property of local networks and sensory information processing. Simultaneous whole-cell recordings from pairs of cells show that the amount of hyperpolarization-evoked sag potential and current (Ih) is stereotypic for mitral cells belonging to the same glomerular circuit. This is corroborated by a mosaic, glomerulus-based pattern of expression of the HCN2 (hyperpolarization-activated cyclic nucleotide-gated channel 2) subunit of the Ih channel. Furthermore, inter-glomerular differences in both membrane potential sag and HCN2 protein are diminished when sensory input to glomeruli is genetically and globally altered so that only one type of odorant receptor is universally expressed. Population diversity in this intrinsic property therefore reflects differential expression between local mitral cell networks processing distinct odour-related information.

Orientation specificity of contrast adaptation in mouse primary visual cortex

Contrast adaptation is a commonly studied phenomenon in vision, where prolonged exposure to spatial contrast alters perceived stimulus contrast and produces characteristic shifts in the contrast response functions of primary visual cortex neurons in cats and primates. In this study we investigated contrast adaptation in mouse primary visual cortex with two goals in mind. First, we sought to establish a quantitative description of contrast adaptation in an animal model, where genetic tools are more readily applicable to this phenomenon. Second, the orientation specificity of contrast adaptation was studied to comparatively assess the possible role of local cortical networks in contrast adaptation. In cats and primates, predictable differences in visual processing across the cortical surface are thought to be caused by inhomogeneous local network membership that arises from the pinwheel organization of orientation columns. Because mice lack this pinwheel organization, we predicted that local cortical networks would have access to a broad spectrum of orientation signals, and contrast adaptation in mice would not be specific to the recorded cell's preferred orientation. We found that most mouse V1 neurons showed contrast adaptation that was robust regardless of whether the adapting stimulus matched the cell's preferred orientation or was orthogonal to it.

Principal component and cluster analysis of layer V pyramidal cells in visual and non-visual cortical areas projecting to the primary visual cortex of the mouse

The long-distance corticocortical connections between visual and nonvisual sensory areas that arise from pyramidal neurons located within layer V can be considered as a subpopulation of feedback connections. The purpose of the present study is to determine if layer V pyramidal neurons from visual and nonvisual sensory cortical areas that project onto the visual cortex (V1) constitute a homogeneous population of cells. Additionally, we ask whether dendritic arborization relates to the target, the sensory modality, the hierarchical level, or laterality of the source cortical area. Complete 3D reconstructions of dendritic arbors of retrogradely labeled layer V pyramidal neurons were performed for neurons of the primary auditory (A1) and somatosensory (S1) cortices and from the lateral (V2L) and medial (V2M) parts of the secondary visual cortices of both hemispheres. The morphological parameters extracted from these reconstructions were subjected to principal component analysis (PCA) and cluster analysis. The PCA showed that neurons are distributed within a continuous range of morphologies and do not form discrete groups. Nevertheless, the cluster analysis defines neuronal groups that share similar features. Each cortical area includes neurons belonging to several clusters. We suggest that layer V feedback connections within a single cortical area comprise several cell types.

MeCP2 mutation results in compartment-specific reductions in dendritic branching and spine density in layer 5 motor cortical neurons of YFP-H mice

Rett Syndrome (RTT) is a neurodevelopmental disorder predominantly caused by mutations in the X-linked gene MECP2. A primary feature of the syndrome is the impaired maturation and maintenance of excitatory synapses in the central nervous system (CNS). Different RTT mouse models have shown that particular Mecp2 mutations have highly variable effects on neuronal architecture. Distinguishing MeCP2 mutant cellular phenotypes therefore demands analysis of specific mutations in well-defined neuronal subpopulations. We examined a transgenically labeled subset of cortical neurons in YFP-H mice crossed with the Mecp2(tm1.1Jae) mutant line. YFP(+) Layer 5 pyramidal neurons in the motor cortex of wildtype and hemizygous mutant male mice were examined for differences in dendrite morphology and spine density. Total basal dendritic length was decreased by 18.6% due to both shorter dendrites and reduced branching proximal to the soma. Tangential dendrite lengths in the apical tuft were reduced by up to 26.6%. Spine density was reduced by 47.4% in the apical tuft and 54.5% in secondary apical dendrites, but remained unaffected in primary apical and proximal basal dendrites. We also found that MeCP2 mutation reduced the number of YFP(+) cells in YFP-H mice by up to 72% in various cortical regions without affecting the intensity of YFP expression in individual cells. Our results support the view that the effects of MeCP2 mutation are highly context-dependent and cannot be generalized across mutation types and cell populations.

Getting drowsy? Alert/nonalert transitions and visual thalamocortical network dynamics

The effects of different EEG brain states on spontaneous firing of cortical populations are not well understood. Such state shifts may occur frequently under natural conditions, and baseline firing patterns can impact neural coding (e.g., signal-to-noise ratios, sparseness of coding). Here, we examine the effects of spontaneous transitions from alert to nonalert awake EEG states in the rabbit visual cortex (5 s before and after the state-shifts). In layer 4, we examined putative spiny neurons and fast-spike GABAergic interneurons; in layer 5, we examined corticotectal neurons. We also examined the behavior of retinotopically aligned dorsal lateral geniculate nucleus (LGNd) neurons, usually recorded simultaneously with the above cortical populations. Despite markedly reduced firing and sharply increased bursting in the LGNd neurons following the transition to the nonalert state, little change occurred in the spiny neurons of layer 4. However, fast-spike neurons of layer 4 showed a paradoxical increase in firing rates as thalamic drive decreased in the nonalert state, even though some of these cells received potent monosynaptic input from the same LGNd neurons whose rates were reduced. The firing rates of corticotectal neurons of layer 5, similarly to spiny cells of layer 4, were not state-dependent, but these cells did become more bursty in the nonalert state, as did the fast-spike cells. These results show that spontaneous firing rates of midlayer spiny populations are remarkably conserved following the shift from alert to nonalert states, despite marked reductions in excitatory thalamic drive and increased activity in local fast-spike inhibitory interneurons.

Regular spiking and intrinsic bursting pyramidal cells show orthogonal forms of experience-dependent plasticity in layer V of barrel cortex

Most functional plasticity studies in the cortex have focused on layers (L) II/III and IV, whereas relatively little is known of LV. Structural measurements of dendritic spines in vivo suggest some specialization among LV cell subtypes. We therefore studied experience-dependent plasticity in the barrel cortex using intracellular recordings to distinguish regular spiking (RS) and intrinsic bursting (IB) subtypes. Postsynaptic potentials and suprathreshold responses in vivo revealed a remarkable dichotomy in RS and IB cell plasticity; spared whisker potentiation occurred in IB but not RS cells while deprived whisker depression occurred in RS but not IB cells. Similar RS/IB differences were found in the LII/III to V connections in brain slices. Modeling studies showed that subthreshold changes predicted the suprathreshold changes. These studies demonstrate the major functional partition of plasticity within a single cortical layer and reveal the LII/III to LV connection as a major excitatory locus of cortical plasticity.

Layer- and cell-type-specific subthreshold and suprathreshold effects of long-term monocular deprivation in rat visual cortex

Connectivity and dendritic properties are determinants of plasticity that are layer and cell-type specific in the neocortex. However, the impact of experience-dependent plasticity at the level of synaptic inputs and spike outputs remains unclear along vertical cortical microcircuits. Here I compared subthreshold and suprathreshold sensitivity to prolonged monocular deprivation (MD) in rat binocular visual cortex in layer 4 and layer 2/3 pyramids (4Ps and 2/3Ps) and in thick-tufted and nontufted layer 5 pyramids (5TPs and 5NPs), which innervate different extracortical targets. In normal rats, 5TPs and 2/3Ps are the most binocular in terms of synaptic inputs, and 5NPs are the least. Spike responses of all 5TPs were highly binocular, whereas those of 2/3Ps were dominated by either the contralateral or ipsilateral eye. MD dramatically shifted the ocular preference of 2/3Ps and 4Ps, mostly by depressing deprived-eye inputs. Plasticity was profoundly different in layer 5. The subthreshold ocular preference shift was sevenfold smaller in 5TPs because of smaller depression of deprived inputs combined with a generalized loss of responsiveness, and was undetectable in 5NPs. Despite their modest ocular dominance change, spike responses of 5TPs consistently lost their typically high binocularity during MD. The comparison of MD effects on 2/3Ps and 5TPs, the main affected output cells of vertical microcircuits, indicated that subthreshold plasticity is not uniquely determined by the initial degree of input binocularity. The data raise the question of whether 5TPs are driven solely by 2/3Ps during MD. The different suprathreshold plasticity of the two cell populations could underlie distinct functional deficits in amblyopia.

Morphology of superior colliculus- and middle temporal area-projecting neurons in primate primary visual cortex

Layers 5 and 6 of primate primary visual cortex (V1) harbor morphologically diverse cell groups that have corticocortical and corticosubcortical projections. Layer 6 middle temporal area (MT)-projecting neurons are particularly interesting, as they are the only deep-layer cortical neurons that provide both corticocortical feedforward inputs (to area MT) and corticosubcortical feedback projections (to superior colliculus [SC]) (Fries et al. [1985] Exp Brain Res 58:613-616). However, due to limitations in anatomical tracing techniques, little is known about the detailed morphologies of these cells. We therefore applied a genetically modified rabies virus as a retrograde tracer to fill the dendrites of projection neurons with green fluorescent protein (GFP) (Wickersham et al. [2007] Nat Methods 4:47-49). We injected virus into SC or area MT of macaque monkeys and examined labeled cells in V1. Two-thirds of labeled neurons following SC injections were found in layer 5, consisting of "tall-tufted" and "nontufted" cells; the remaining cells were layer 6 "nontufted." Area MT injections labeled neurons in layers 4B and 6, as previously described (Shipp and Zeki [1989] Eur J Neurosci 1:309-332). The layer 6 neurons projecting to MT were remarkably similar to the layer 6 SC-projecting neurons. In contrast to the dense and focused dendritic arbors of layer 5 "tall-tufted" pyramids, all "nontufted" cells had sparse, but unusually long basal dendrites. The nontufted cells closely resemble Meynert cells (le Gros Clark [1942] J Anat 76:369-376; Winfield et al. [1983] Proc R Soc Lond B Biol Sci 217:129-139), but the full in vivo reconstructions presented here show that their basal dendrites can extend much further (up to 1.2 mm) and are less asymmetric than inferred from Golgi reconstructions.

Comparison between supervised and unsupervised classifications of neuronal cell types: a case study

In the study of neural circuits, it becomes essential to discern the different neuronal cell types that build the circuit. Traditionally, neuronal cell types have been classified using qualitative descriptors. More recently, several attempts have been made to classify neurons quantitatively, using unsupervised clustering methods. While useful, these algorithms do not take advantage of previous information known to the investigator, which could improve the classification task. For neocortical GABAergic interneurons, the problem to discern among different cell types is particularly difficult and better methods are needed to perform objective classifications. Here we explore the use of supervised classification algorithms to classify neurons based on their morphological features, using a database of 128 pyramidal cells and 199 interneurons from mouse neocortex. To evaluate the performance of different algorithms we used, as a “benchmark,” the test to automatically distinguish between pyramidal cells and interneurons, defining “ground truth” by the presence or absence of an apical dendrite. We compared hierarchical clustering with a battery of different supervised classification algorithms, finding that supervised classifications outperformed hierarchical clustering. In addition, the selection of subsets of distinguishing features enhanced the classification accuracy for both sets of algorithms. The analysis of selected variables indicates that dendritic features were most useful to distinguish pyramidal cells from interneurons when compared with somatic and axonal morphological variables. We conclude that supervised classification algorithms are better matched to the general problem of distinguishing neuronal cell types when some information on these cell groups, in our case being pyramidal or interneuron, is known a priori. As a spin-off of this methodological study, we provide several methods to automatically distinguish neocortical pyramidal cells from interneurons, based on their morphologies. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 71: 71–82, 2011

Loss of visually driven synaptic responses in layer 4 regular-spiking neurons of rat visual cortex in absence of competing inputs

Monocular deprivation (MD) during development shifts the ocular preference of primary visual cortex (V1) neurons by depressing closed-eye responses and potentiating open-eye responses. As these 2 processes are temporally and mechanistically distinct, we tested whether loss of responsiveness occurs also in absence of competing inputs. We thus compared the effects of long-term MD in layer 4 regular-spiking pyramidal neurons (L4Ns) of binocular and monocular V1 (bV1 and mV1) with whole-cell recordings. In bV1, input depression was larger than potentiation, and the ocular dominance shift was larger for spike outputs. MD-but not retinal inactivation with tetrodotoxin-caused a comparable loss of synaptic and spike responsiveness in mV1, which is innervated only by the deprived eye. Conversely, brief MD depressed synaptic responses only in bV1. MD-driven depression in mV1 was accompanied by a proportional reduction of visual thalamic inputs, as assessed upon pharmacological silencing of intracortical transmission. Finally, sub- and suprathreshold responsiveness was similarly degraded in L4Ns of bV1 upon complete deprivation of patterned vision through a binocular deprivation period of comparable length. Thus, loss of synaptic inputs from the deprived eye occurs also in absence of competition in the main thalamorecipient lamina, albeit at a slower pace.

Descending projections from extrastriate visual cortex modulate responses of cells in primary auditory cortex

Primary sensory cortical responses are modulated by the presence or expectation of related sensory information in other modalities, but the sources of multimodal information and the cellular locus of this integration are unclear. We investigated the modulation of neural responses in the murine primary auditory cortical area Au1 by extrastriate visual cortex (V2). Projections from V2 to Au1 terminated in a classical descending/modulatory pattern, with highest density in layers 1, 2, 5, and 6. In brain slices, whole-cell recordings revealed long latency responses to stimulation in V2L that could modulate responses to subsequent white matter (WM) stimuli at latencies of 5-20 ms. Calcium responses imaged in Au1 cell populations showed that preceding WM with V2L stimulation modulated WM responses, with both summation and suppression observed. Modulation of WM responses was most evident for near-threshold WM stimuli. These data indicate that corticocortical projections from V2 contribute to multimodal integration in primary auditory cortex.

Cell-type specific properties of pyramidal neurons in neocortex underlying a layout that is modifiable depending on the cortical area

To understand sensory representation in cortex, it is crucial to identify its constituent cellular components based on cell-type-specific criteria. With the identification of cell types, an important question can be addressed: to what degree does the cellular properties of neurons depend on cortical location? We tested this question using pyramidal neurons in layer 5 (L5) because of their role in providing major cortical output to subcortical targets. Recently developed transgenic mice with cell-type-specific enhanced green fluorescent protein labeling of neuronal subtypes allow reliable identification of 2 cortical cell types in L5 throughout the entire neocortex. A comprehensive investigation of anatomical and functional properties of these 2 cell types in visual and somatosensory cortex demonstrates that, with important exceptions, most properties appear to be cell-type-specific rather than dependent on cortical area. This result suggests that although cortical output neurons share a basic layout throughout the sensory cortex, fine differences in properties are tuned to the cortical area in which neurons reside.

Morphological heterogeneity of layer VI neurons in mouse barrel cortex

Understanding the basic neuronal building blocks of the neocortex is a necessary first step toward comprehending the composition of cortical circuits. Neocortical layer VI is the most morphologically diverse layer and plays a pivotal role in gating information to the cortex via its feedback connection to the thalamus and other ipsilateral and callosal corticocortical connections. The heterogeneity of function within this layer is presumably linked to its varied morphological composition. However, so far, very few studies have attempted to define cell classes in this layer using unbiased quantitative methodologies. Utilizing the Golgi staining technique along with the Neurolucida software, we recontructed 222 cortical neurons from layer VI of mouse barrel cortex. Morphological analyses were performed by quantifying somatic and dendritic parameters, and, by using principal component and cluster analyses, we quantitatively categorized neurons into six distinct morphological groups. Additional systematic replication on a separate population of neurons yielded similar results, demonstrating the consistency and reliability of our categorization methodology. Subsequent post hoc analyses of dendritic parameters supported our neuronal classification scheme. Characterizing neuronal elements with unbiased quantitative techniques provides a framework for better understanding structure-function relationships within neocortical circuits in general.