The occipitoparietal pathway of the macaque monkey: comparison of pyramidal cell morphology in layer III of functionally related cortical visual areas

Key morphological features of human pyramidal neurons

The basic building block of the cerebral cortex, the pyramidal cell, has been shown to be characterized by a markedly different dendritic structure among layers, cortical areas, and species. Functionally, differences in the structure of their dendrites and axons are critical in determining how neurons integrate information. However, within the human cortex, these neurons have not been quantified in detail. In the present work, we performed intracellular injections of Lucifer Yellow and 3D reconstructed over 200 pyramidal neurons, including apical and basal dendritic and local axonal arbors and dendritic spines, from human occipital primary visual area and associative temporal cortex. We found that human pyramidal neurons from temporal cortex were larger, displayed more complex apical and basal structural organization, and had more spines compared to those in primary sensory cortex. Moreover, these human neocortical neurons displayed specific shared and distinct characteristics in comparison to previously published human hippocampal pyramidal neurons. Additionally, we identified distinct morphological features in human neurons that set them apart from mouse neurons. Lastly, we observed certain consistent organizational patterns shared across species. This study emphasizes the existing diversity within pyramidal cell structures across different cortical areas and species, suggesting substantial species-specific variations in their computational properties.

Lamination, Borders, and Thalamic Projections of the Primary Visual Cortex in Human, Non-Human Primate, and Rodent Brains

The primary visual cortex (V1) is one of the most studied regions of the brain and is characterized by its specialized and laminated layer 4 in human and non-human primates. However, studies aiming to harmonize the definition of the cortical layers and borders of V1 across rodents and primates are very limited. This article attempts to identify and harmonize the molecular markers and connectional patterns that can consistently link corresponding cortical layers of V1 and borders across mammalian species and ages. V1 in primates has at least two additional and unique layers (L3b2 and L3c) and two sublayers of layer 4 (L4a and L4b) compared to rodent V1. In all species examined, layers 4 and 3b of V1 receive strong inputs from the (dorsal) lateral geniculate nucleus, and V1 is mostly surrounded by the secondary visual cortex except for one location where V1 directly abuts area prostriata. The borders of primate V1 can also be clearly identified at mid-gestational ages using gene markers. In rodents, a novel posteromedial extension of V1 is identified, which expresses V1 marker genes and receives strong inputs from the lateral geniculate nucleus. This V1 extension was labeled as the posterior retrosplenial cortex and medial secondary visual cortex in the literature and brain atlases. Layer 6 of the rodent and primate V1 originates corticothalamic projections to the lateral geniculate, lateral dorsal, and reticular thalamic nuclei and the lateroposterior-pulvinar complex with topographic organization. Finally, the direct geniculo-extrastriate (particularly the strong geniculo-prostriata) projections are probably major contributors to blindsight after V1 lesions. Taken together, compared to rodents, primates, and humans, V1 has at least two unique middle layers, while other layers are comparable across species and display conserved molecular markers and similar connections with the visual thalamus with only subtle differences.

The Primate Cortical LFP Exhibits Multiple Spectral and Temporal Gradients and Widespread Task-Dependence During Visual Short-Term Memory

Although cognitive functions are hypothesized to be mediated by synchronous neuronal interactions in multiple frequency bands among widely distributed cortical areas, we still lack a basic understanding of the distribution and task dependence of oscillatory activity across the cortical map. Here, we ask how the spectral and temporal properties of the local field potential (LFP) vary across the primate cerebral cortex, and how they are modulated during visual short-term memory. We measured the LFP from 55 cortical areas in two macaque monkeys while they performed a visual delayed match to sample task. Analysis of peak frequencies in the LFP power spectra reveals multiple discrete frequency bands between 3-80 Hz that differ between the two monkeys. The LFP power in each band, as well as the Sample Entropy, a measure of signal complexity, display distinct spatial gradients across the cortex, some of which correlate with reported spine counts in layer 3 pyramidal neurons. Cortical areas can be robustly decoded using a small number of spectral and temporal parameters, and significant task dependent increases and decreases in spectral power occur in all cortical areas. These findings reveal pronounced, widespread and spatially organized gradients in the spectral and temporal activity of cortical areas. Task-dependent changes in cortical activity are globally distributed, even for a simple cognitive task.

Deficits in neuronal architecture but not over-inhibition are main determinants of reduced neuronal network activity in a mouse model of overexpression of Dyrk1A

In this study, we investigated the impact of Dual specificity tyrosine-phosphorylation-regulated kinase 1A (Dyrk1A) overexpression, a gene associated with Down syndrome, on hippocampal neuronal deficits in mice. Our findings revealed that mice overexpressing Dyrk1A (TgDyrk1A; TG) exhibited impaired hippocampal recognition memory, disrupted excitation-inhibition balance, and deficits in long-term potentiation (LTP). Specifically, we observed layer-specific deficits in dendritic arborization of TG CA1 pyramidal neurons in the stratum radiatum. Through computational modeling, we determined that these alterations resulted in reduced storage capacity and compromised integration of inputs, with decreased high γ oscillations. Contrary to prevailing assumptions, our model suggests that deficits in neuronal architecture, rather than over-inhibition, primarily contribute to the reduced network. We explored the potential of environmental enrichment (EE) as a therapeutic intervention and found that it normalized the excitation-inhibition balance, restored LTP, and improved short-term recognition memory. Interestingly, we observed transient significant dendritic remodeling, leading to recovered high γ. However, these effects were not sustained after EE discontinuation. Based on our findings, we conclude that Dyrk1A overexpression-induced layer-specific neuromorphological disturbances impair the encoding of place and temporal context. These findings contribute to our understanding of the underlying mechanisms of Dyrk1A-related hippocampal deficits and highlight the challenges associated with long-term therapeutic interventions for cognitive impairments.

Gradients of neurotransmitter receptor expression in the macaque cortex

Dynamics and functions of neural circuits depend on interactions mediated by receptors. Therefore, a comprehensive map of receptor organization across cortical regions is needed. In this study, we used in vitro receptor autoradiography to measure the density of 14 neurotransmitter receptor types in 109 areas of macaque cortex. We integrated the receptor data with anatomical, genetic and functional connectivity data into a common cortical space. We uncovered a principal gradient of receptor expression per neuron. This aligns with the cortical hierarchy from sensory cortex to higher cognitive areas. A second gradient, driven by serotonin 5-HT1A receptors, peaks in the anterior cingulate, default mode and salience networks. We found a similar pattern of 5-HT1A expression in the human brain. Thus, the macaque may be a promising translational model of serotonergic processing and disorders. The receptor gradients may enable rapid, reliable information processing in sensory cortical areas and slow, flexible integration in higher cognitive areas.

Deficits in neuronal architecture but not over-inhibition are main determinants of reduced neuronal network activity in a mouse model of overexpression of Dyrk1A

Abnormal dendritic arbors, dendritic spine "dysgenesis" and excitation inhibition imbalance are main traits assumed to underlie impaired cognition and behavioral adaptation in intellectual disability. However, how these modifications actually contribute to functional properties of neuronal networks, such as signal integration or storage capacity is unknown. Here, we used a mouse model overexpressing Dyrk1A (Dual-specificity tyrosine [Y]-regulated kinase), one of the most relevant Down syndrome (DS) candidate genes, to gather quantitative data regarding hippocampal neuronal deficits produced by the overexpression of Dyrk1A in mice (TgDyrk1A; TG). TG mice showed impaired hippocampal recognition memory, altered excitation-inhibition balance and deficits in hippocampal CA1 LTP. We also detected for the first time that deficits in dendritic arborization in TG CA1 pyramidal neurons are layer-specific, with a reduction in the width of the stratum radiatum, the postsynaptic target site of CA3 excitatory neurons, but not in the stratum lacunosum-moleculare, which receives temporo-ammonic projections. To interrogate about the functional impact of layer-specific TG dendritic deficits we developed tailored computational multicompartmental models. Computational modelling revealed that neuronal microarchitecture alterations in TG mice lead to deficits in storage capacity, altered the integration of inputs from entorhinal cortex and hippocampal CA3 region onto CA1 pyramidal cells, important for coding place and temporal context and on connectivity and activity dynamics, with impaired the ability to reach high γ oscillations. Contrary to what is assumed in the field, the reduced network activity in TG is mainly contributed by the deficits in neuronal architecture and to a lesser extent by over-inhibition. Finally, given that therapies aimed at improving cognition have also been tested for their capability to recover dendritic spine deficits and excitation-inhibition imbalance, we also tested the short- and long-term changes produced by exposure to environmental enrichment (EE). Exposure to EE normalized the excitation inhibition imbalance and LTP, and had beneficial effects on short-term recognition memory. Importantly, it produced massive but transient dendritic remodeling of hippocampal CA1, that led to recovery of high γ oscillations, the main readout of synchronization of CA1 neurons, in our simulations. However, those effects where not stable and were lost after EE discontinuation. We conclude that layer-specific neuromorphological disturbances produced by Dyrk1A overexpression impair coding place and temporal context. Our results also suggest that treatments targeting structural plasticity, such as EE, even though hold promise towards improved treatment of intellectual disabilities, only produce temporary recovery, due to transient dendritic remodeling.

Optogenetic stimulation of the primary visual cortex drives activity in the visual association cortex

Developing optogenetic methods for research in non-human primates (NHP) is important for translational neuroscience and for delineating brain function with unprecedented specificity. Here we assess, in macaque monkeys, the selectivity by which optogenetic stimulation of the primary visual cortex (V1) drives the local laminar and widespread cortical connectivity related to visual perception. Towards this end, we transfected neurons with light-sensitive channelrhodopsin in dorsal V1. fMRI revealed that optogenetic stimulation of V1 using blue light at 40 Hz increased functional activity in the visual association cortex, including areas V2/V3, V4, motion-sensitive area MT and frontal eye fields, although nonspecific heating and eye movement contributions to this effect could not be ruled out. Neurophysiology and immunohistochemistry analyses confirmed optogenetic modulation of spiking activity and opsin expression with the strongest expression in layer 4-B in V1. Stimulating this pathway during a perceptual decision task effectively elicited a phosphene percept in the receptive field of the stimulated neurons in one monkey. Taken together, our findings demonstrate the great potential of optogenetic methods to drive the large-scale cortical circuits of the primate brain with high functional and spatial specificity.

The large numbers of minicolumns in the primary visual cortex of humans, chimpanzees and gorillas are related to high visual acuity

Minicolumns are thought to be a fundamental neural unit in the neocortex and their replication may have formed the basis of the rapid cortical expansion that occurred during primate evolution. We sought evidence of minicolumns in the primary visual cortex (V-1) of three great apes, three rodents and representatives from three other mammalian orders: Eulipotyphla (European hedgehog), Artiodactyla (domestic pig) and Carnivora (ferret). Minicolumns, identified by the presence of a long bundle of radial, myelinated fibers stretching from layer III to the white matter of silver-stained sections, were found in the human, chimpanzee, gorilla and guinea pig V-1. Shorter bundles confined to one or two layers were found in the other species but represent modules rather than minicolumns. The inter-bundle distance, and hence density of minicolumns, varied systematically both within a local area that might represent a hypercolumn but also across the whole visual field. The distance between all bundles had a similar range for human, chimpanzee, gorilla, ferret and guinea pig: most bundles were 20-45 μm apart. By contrast, the space between bundles was greater for the hedgehog and pig (20-140 μm). The mean density of minicolumns was greater in tangential sections of the gorilla and chimpanzee (1,243-1,287 bundles/mm2) than in human (314-422 bundles/mm2) or guinea pig (643 bundles/mm2). The minicolumnar bundles did not form a hexagonal lattice but were arranged in thin curving and branched bands separated by thicker bands of neuropil/somata. Estimates of the total number of modules/minicolumns within V-1 were strongly correlated with visual acuity.

Expression of actin- and oxidative phosphorylation-related transcripts across the cortical visuospatial working memory network in unaffected comparison and schizophrenia subjects

Visuospatial working memory (vsWM), which is impaired in schizophrenia (SZ), is mediated by a distributed cortical network. In one node of this network, the dorsolateral prefrontal cortex (DLPFC), altered expression of transcripts for actin assembly and mitochondrial oxidative phosphorylation (OXPHOS) have been reported in SZ. To understand the relationship between these processes, and the extent to which similar alterations are present in other regions of vsWM network in SZ, a subset of actin- (CDC42, BAIAP2, ARPC3, and ARPC4) and OXPHOS-related (ATP5H, COX4I1, COX7B, and NDUFB3) transcripts were quantified in DLPFC by RNA sequencing in 139 SZ and unaffected comparison (UC) subjects, and in DLPFC and three other regions of the cortical vsWM network by qPCR in 20 pairs of SZ and UC subjects. By RNA sequencing, levels of actin- and OXPHOS-related transcripts were significantly altered in SZ, and robustly correlated in both UC and SZ subject groups. By qPCR, cross-regional expression patterns of these transcripts in UC subjects were consistent with greater actin assembly in DLPFC and higher OXPHOS activity in primary visual cortex (V1). In SZ, CDC42 and ARPC4 levels were lower in all regions, BAIAP2 levels higher only in V1, and ARPC3 levels unaltered across regions. All OXPHOS-related transcript levels were lower in SZ, with the disease effect decreasing from posterior to anterior regions. The differential alterations in markers of actin assembly and energy production across regions of the cortical vsWM network in SZ suggest that each region may make specific contributions to vsWM impairments in the illness.

Topological Sholl descriptors for neuronal clustering and classification

Neuronal morphology is a fundamental factor influencing information processing within neurons and networks. Dendritic morphology in particular can widely vary among cell classes, brain regions, and animal species. Thus, accurate quantitative descriptions allowing classification of large sets of neurons is essential for their structural and functional characterization. Current robust and unbiased computational methods that characterize groups of neurons are scarce. In this work, we introduce a novel technique to study dendritic morphology, complementing and advancing many of the existing techniques. Our approach is to conceptualize the notion of a Sholl descriptor and associate, for each morphological feature, and to each neuron, a function of the radial distance from the soma, taking values in a metric space. Functional distances give rise to pseudo-metrics on sets of neurons which are then used to perform the two distinct tasks of clustering and classification. To illustrate the use of Sholl descriptors, four datasets were retrieved from the large public repository https://neuromorpho.org/ comprising neuronal reconstructions from different species and brain regions. Sholl descriptors were subsequently computed, and standard clustering methods enhanced with detection and metric learning algorithms were then used to objectively cluster and classify each dataset. Importantly, our descriptors outperformed conventional morphometric techniques (L-Measure metrics) in several of the tested datasets. Therefore, we offer a novel and effective approach to the analysis of diverse neuronal cell types, and provide a toolkit for researchers to cluster and classify neurons.

Common Microscale and Macroscale Principles of Connectivity in the Human Brain

The brain requires efficient information transfer between neurons and large-scale brain regions. Brain connectivity follows predictable organizational principles. At the cellular level, larger supragranular pyramidal neurons have larger, more branched dendritic trees, more synapses, and perform more complex computations; at the macroscale, region-to-region connections display a diverse architecture with highly connected hub areas facilitating complex information integration and computation. Here, we explore the hypothesis that the branching structure of large-scale region-to-region connectivity follows similar organizational principles as the neuronal scale. We examine microscale connectivity of basal dendritic trees of supragranular pyramidal neurons (300+) across 10 cortical areas in five human donor brains (1 male, 4 female). Dendritic complexity was quantified as the number of branch points, tree length, spine count, spine density, and overall branching complexity. High-resolution diffusion-weighted MRI was used to construct white matter trees of corticocortical wiring. Examining complexity of the resulting white matter trees using the same measures as for dendritic trees shows heteromodal association areas to have larger, more complex white matter trees than primary areas (p < 0.0001) and macroscale complexity to run in parallel with microscale measures, in terms of number of inputs (r = 0.677, p = 0.032), branch points (r = 0.797, p = 0.006), tree length (r = 0.664, p = 0.036), and branching complexity (r = 0.724, p = 0.018). Our findings support the integrative theory that brain connectivity follows similar principles of connectivity at neuronal and macroscale levels and provide a framework to study connectivity changes in brain conditions at multiple levels of organization.SIGNIFICANCE STATEMENT Within the human brain, cortical areas are involved in a wide range of processes, requiring different levels of information integration and local computation. At the cellular level, these regional differences reflect a predictable organizational principle with larger, more complexly branched supragranular pyramidal neurons in higher order regions. We hypothesized that the 3D branching structure of macroscale corticocortical connections follows the same organizational principles as the cellular scale. Comparing branching complexity of dendritic trees of supragranular pyramidal neurons and of MRI-based regional white matter trees of macroscale connectivity, we show that macroscale branching complexity is larger in higher order areas and that microscale and macroscale complexity go hand in hand. Our findings contribute to a multiscale integrative theory of brain connectivity.

Mechanisms of distributed working memory in a large-scale network of macaque neocortex

Neural activity underlying working memory is not a local phenomenon but distributed across multiple brain regions. To elucidate the circuit mechanism of such distributed activity, we developed an anatomically constrained computational model of large-scale macaque cortex. We found that mnemonic internal states may emerge from inter-areal reverberation, even in a regime where none of the isolated areas is capable of generating self-sustained activity. The mnemonic activity pattern along the cortical hierarchy indicates a transition in space, separating areas engaged in working memory and those which do not. A host of spatially distinct attractor states is found, potentially subserving various internal processes. The model yields testable predictions, including the idea of counterstream inhibitory bias, the role of prefrontal areas in controlling distributed attractors, and the resilience of distributed activity to lesions or inactivation. This work provides a theoretical framework for identifying large-scale brain mechanisms and computational principles of distributed cognitive processes.

Differential gene expression in layer 3 pyramidal neurons across 3 regions of the human cortical visual spatial working memory network

Visual spatial working memory (vsWM) is mediated by a distributed cortical network composed of multiple nodes, including primary visual (V1), posterior parietal (PPC), and dorsolateral prefrontal (DLPFC) cortices. Feedforward and feedback information is transferred among these nodes via projections furnished by pyramidal neurons (PNs) located primarily in cortical layer 3. Morphological and electrophysiological differences among layer 3 PNs across these nodes have been reported; however, the transcriptional signatures underlying these differences have not been examined in the human brain. Here we interrogated the transcriptomes of layer 3 PNs from 39 neurotypical human subjects across 3 critical nodes of the vsWM network. Over 8,000 differentially expressed genes were detected, with more than 6,000 transcriptional differences present between layer 3 PNs in V1 and those in PPC and DLPFC. Additionally, over 600 other genes differed in expression along the rostral-to-caudal hierarchy formed by these 3 nodes. Moreover, pathway analysis revealed enrichment of genes in V1 related to circadian rhythms and in DLPFC of genes involved in synaptic plasticity. Overall, these results show robust regional differences in the transcriptome of layer 3 PNs, which likely contribute to regional specialization in their morphological and physiological features and thus in their functional contributions to vsWM.

Putative neural consequences of captivity for elephants and cetaceans

The present review assesses the potential neural impact of impoverished, captive environments on large-brained mammals, with a focus on elephants and cetaceans. These species share several characteristics, including being large, wide-ranging, long-lived, cognitively sophisticated, highly social, and large-brained mammals. Although the impact of the captive environment on physical and behavioral health has been well-documented, relatively little attention has been paid to the brain itself. Here, we explore the potential neural consequences of living in captive environments, with a focus on three levels: (1) The effects of environmental impoverishment/enrichment on the brain, emphasizing the negative neural consequences of the captive/impoverished environment; (2) the neural consequences of stress on the brain, with an emphasis on corticolimbic structures; and (3) the neural underpinnings of stereotypies, often observed in captive animals, underscoring dysregulation of the basal ganglia and associated circuitry. To this end, we provide a substantive hypothesis about the negative impact of captivity on the brains of large mammals (e.g., cetaceans and elephants) and how these neural consequences are related to documented evidence for compromised physical and psychological well-being.

Nonlinear Dendritic Coincidence Detection for Supervised Learning

Cortical pyramidal neurons have a complex dendritic anatomy, whose function is an active research field. In particular, the segregation between its soma and the apical dendritic tree is believed to play an active role in processing feed-forward sensory information and top-down or feedback signals. In this work, we use a simple two-compartment model accounting for the nonlinear interactions between basal and apical input streams and show that standard unsupervised Hebbian learning rules in the basal compartment allow the neuron to align the feed-forward basal input with the top-down target signal received by the apical compartment. We show that this learning process, termed coincidence detection, is robust against strong distractions in the basal input space and demonstrate its effectiveness in a linear classification task.

Learning Invariant Object and Spatial View Representations in the Brain Using Slow Unsupervised Learning

First, neurophysiological evidence for the learning of invariant representations in the inferior temporal visual cortex is described. This includes object and face representations with invariance for position, size, lighting, view and morphological transforms in the temporal lobe visual cortex; global object motion in the cortex in the superior temporal sulcus; and spatial view representations in the hippocampus that are invariant with respect to eye position, head direction, and place. Second, computational mechanisms that enable the brain to learn these invariant representations are proposed. For the ventral visual system, one key adaptation is the use of information available in the statistics of the environment in slow unsupervised learning to learn transform-invariant representations of objects. This contrasts with deep supervised learning in artificial neural networks, which uses training with thousands of exemplars forced into different categories by neuronal teachers. Similar slow learning principles apply to the learning of global object motion in the dorsal visual system leading to the cortex in the superior temporal sulcus. The learning rule that has been explored in VisNet is an associative rule with a short-term memory trace. The feed-forward architecture has four stages, with convergence from stage to stage. This type of slow learning is implemented in the brain in hierarchically organized competitive neuronal networks with convergence from stage to stage, with only 4-5 stages in the hierarchy. Slow learning is also shown to help the learning of coordinate transforms using gain modulation in the dorsal visual system extending into the parietal cortex and retrosplenial cortex. Representations are learned that are in allocentric spatial view coordinates of locations in the world and that are independent of eye position, head direction, and the place where the individual is located. This enables hippocampal spatial view cells to use idiothetic, self-motion, signals for navigation when the view details are obscured for short periods.

Variation in Pyramidal Cell Morphology Across the Human Anterior Temporal Lobe

Pyramidal neurons are the most abundant and characteristic neuronal type in the cerebral cortex and their dendritic spines are the main postsynaptic elements of cortical excitatory synapses. Previous studies have shown that pyramidal cell structure differs across layers, cortical areas, and species. However, within the human cortex, the pyramidal dendritic morphology has been quantified in detail in relatively few cortical areas. In the present work, we performed intracellular injections of Lucifer Yellow at several distances from the temporal pole. We found regional differences in pyramidal cell morphology, which showed large inter-individual variability in most of the morphological variables measured. However, some values remained similar in all cases. The smallest and least complex cells in the most posterior temporal region showed the greatest dendritic spine density. Neurons in the temporal pole showed the greatest sizes with the highest number of spines. Layer V cells were larger, more complex, and had a greater number of dendritic spines than those in layer III. The present results suggest that, while some aspects of pyramidal structure are conserved, there are specific variations across cortical regions, and species.

Developmental Changes in Pyramidal Cell Morphology in Multiple Visual Cortical Areas Using Cluster Analysis

Neuronal morphology is characterized by salient features such as complex axonal and dendritic arbors. In the mammalian brain, variations in dendritic morphology among cell classes, brain regions, and animal species are thought to underlie known differences in neuronal function. In this work, we obtained a large dataset from http://neuromorpho.org/ comprising layer III pyramidal cells in different cortical areas of the ventral visual pathway (V1, V2, V4, TEO, and TE) of the macaque monkey at different developmental stages. We performed an in depth quantitative analysis of pyramidal cell morphology throughout development in an effort to determine which aspects mature early in development and which features require a protracted period of maturation. We were also interested in establishing if developmental changes in morphological features occur simultaneously or hierarchically in multiple visual cortical areas. We addressed these questions by performing principal component analysis (PCA) and hierarchical clustering analysis on relevant morphological features. Our analysis indicates that the maturation of pyramidal cell morphology is largely based on early development of topological features in most visual cortical areas. Moreover, the maturation of pyramidal cell morphology in V1, V2, V4, TEO, and TE is characterized by unique developmental trajectories.

Decline of Orientation and Direction Sensitivity in the Aging Population

While the aging population is growing, our knowledge regarding age-related deterioration of visual perception remains limited. In the present study, we investigated the effects of aging on orientation and direction sensitivity in a healthy population using a weighted up–down adaptive method to improve the efficiency and reliability of the task. A total of 57 healthy participants aged 22–72 years were included and divided into old and young groups. Raw experimental data were processed using a psychometric method to determine the differences between the two groups. In the orientation task, the threshold of the discrimination angle and bias (i.e., the difference between the perceived midpoint from the logistic function and the reference point) was increased, while the lapsing rate (i.e., 1—the maximum logistic function) did not significantly change in the old group compared with the young group. In the motion direction task, the threshold, bias, and lapsing rate were significantly increased in the old group compared with the young group. These results suggest that the decreased ability of old participants in discrimination of stimulus orientation and motion direction could be related to the impaired function of visual cortex.

Visual response characteristics of neurons in the second visual area of marmosets

The physiological characteristics of the marmoset second visual area (V2) are poorly understood compared with those of the primary visual area (V1). In this study, we observed the physiological response characteristics of V2 neurons in four healthy adult marmosets using intracortical tungsten microelectrodes. We recorded 110 neurons in area V2, with receptive fields located between 8° and 15° eccentricity. Most (88.2%) of these neurons were orientation selective, with half-bandwidths typically ranging between 10° and 30°. A significant proportion of neurons (28.2%) with direction selectivity had a direction index greater than 0.5. The vast majority of V2 neurons had separable spatial frequency and temporal frequency curves and, according to this criterion, they were not speed selective. The basic functional response characteristics of neurons in area V2 resemble those found in area V1. Our findings show that area V2 together with V1 are important in primate visual processing, especially in locating objects in space and in detecting an object’s direction of motion. The methods used in this study were approved by the Monash University Animal Ethics Committee, Australia (MARP 2009-2011) in 2009.

Expression of Transcripts Selective for GABA Neuron Subpopulations across the Cortical Visuospatial Working Memory Network in the Healthy State and Schizophrenia

Visuospatial working memory (WM), which is impaired in schizophrenia, depends on a distributed network including visual, posterior parietal, and dorsolateral prefrontal cortical regions. Within each region, information processing is differentially regulated by subsets of γ-aminobutyric acid (GABA) neurons that express parvalbumin (PV), somatostatin (SST), or vasoactive intestinal peptide (VIP). In schizophrenia, WM impairments have been associated with alterations of PV and SST neurons in the dorsolateral prefrontal cortex. Here, we quantified transcripts selectively expressed in GABA neuron subsets across four cortical regions in the WM network from comparison and schizophrenia subjects. In comparison subjects, PV mRNA levels declined and SST mRNA levels increased from posterior to anterior regions, whereas VIP mRNA levels were comparable across regions except for the primary visual cortex (V1). In schizophrenia subjects, each transcript in PV and SST neurons exhibited similar alterations across all regions, whereas transcripts in VIP neurons were unaltered in any region except for V1. These findings suggest that the contribution of each GABA neuron subset to inhibitory regulation of local circuitry normally differs across cortical regions of the visuospatial WM network and that in schizophrenia alterations of PV and SST neurons are a shared feature across these regions, whereas VIP neurons are affected only in V1.

Cortical Afferents of Area 10 in Cebus Monkeys: Implications for the Evolution of the Frontal Pole

Area 10, located in the frontal pole, is a unique specialization of the primate cortex. We studied the cortical connections of area 10 in the New World Cebus monkey, using injections of retrograde tracers in different parts of this area. We found that injections throughout area 10 labeled neurons in a consistent set of areas in the dorsolateral, ventrolateral, orbital, and medial parts of the frontal cortex, superior temporal association cortex, and posterior cingulate/retrosplenial region. However, sites on the midline surface of area 10 received more substantial projections from the temporal lobe, including clear auditory connections, whereas those in more lateral parts received >90% of their afferents from other frontal areas. This difference in anatomical connectivity reflects functional connectivity findings in the human brain. The pattern of connections in Cebus is very similar to that observed in the Old World macaque monkey, despite >40 million years of evolutionary separation, but lacks some of the connections reported in the more closely related but smaller marmoset monkey. These findings suggest that the clearer segregation observed in the human frontal pole reflects regional differences already present in early simian primates, and that overall brain mass influences the pattern of cortico-cortical connectivity.

Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models

The cerebral cortex of primates encompasses multiple anatomically and physiologically distinct areas processing visual information. Areas V1, V2, and V5/MT are conserved across mammals and are central for visual behavior. To facilitate the generation of biologically accurate computational models of primate early visual processing, here we provide an overview of over 350 published studies of these three areas in the genus Macaca, whose visual system provides the closest model for human vision. The literature reports 14 anatomical connection types from the lateral geniculate nucleus of the thalamus to V1 having distinct layers of origin or termination, and 194 connection types between V1, V2, and V5, forming multiple parallel and interacting visual processing streams. Moreover, within V1, there are reports of 286 and 120 types of intrinsic excitatory and inhibitory connections, respectively. Physiologically, tuning of neuronal responses to 11 types of visual stimulus parameters has been consistently reported. Overall, the optimal spatial frequency (SF) of constituent neurons decreases with cortical hierarchy. Moreover, V5 neurons are distinct from neurons in other areas for their higher direction selectivity, higher contrast sensitivity, higher temporal frequency tuning, and wider SF bandwidth. We also discuss currently unavailable data that could be useful for biologically accurate models.

GABAergic and non-GABAergic subpopulations of Kv3.1b-expressing neurons in macaque V2 and MT: laminar distributions and proportion of total neuronal population

The Kv3.1b potassium channel subunit, which facilitates the fast-spiking phenotype characteristic of parvalbumin (PV)-expressing inhibitory interneurons, is also expressed by subpopulations of excitatory neurons in macaque cortex. We have previously shown that V1 neurons expressing Kv3.1b but not PV or GABA were largely concentrated within layers 4Cα and 4B of V1, suggesting laminar or pathway specificity. In the current study, the distribution and pattern of co-immunoreactivity of GABA, PV, and Kv3.1b across layers in extrastriate cortical areas V2 and MT of the macaque monkey were measured using the same triple immunofluorescence labeling, confocal microscopy, and partially automated cell-counting strategies used in V1. For comparison, densities of the overall cell and neuronal populations were also measured for each layer of V2 and MT using tissue sections immunofluorescence labeled for the pan-neuronal marker NeuN. GABAergic neurons accounted for 14% of the total neuronal population in V2 and 25% in MT. Neurons expressing Kv3.1b but neither GABA nor PV were present in both areas. This subpopulation was most prevalent in the lowest subcompartment of layer 3, comprising 5% of the total neuronal population in layer 3C of both areas, and 41% and 36% of all Kv3.1b+ neurons in this layer in V2 and MT, respectively. The prevalence and laminar distribution of this subpopulation were remarkably consistent between V2 and MT and showed a striking similarity to the patterns observed previously in V1, suggesting a common contribution to the cortical circuit across areas.

Changes in the Proportion of Inhibitory Interneuron Types from Sensory to Executive Areas of the Primate Neocortex: Implications for the Origins of Working Memory Representations

Neuronal spiking activity encoding working memory (WM) is robust in primate association cortices but weak or absent in early sensory cortices. This may be linked to changes in the proportion of neuronal types across areas that influence circuits' ability to generate recurrent excitation. We recorded neuronal activity from areas middle temporal (MT), medial superior temporal (MST), and the lateral prefrontal cortex (LPFC) of monkeys performing a WM task and classified neurons as narrow (NS) and broad spiking (BS). The ratio NS/BS decreased from MT > MST > LPFC. We analyzed the Allen Institute database of ex vivo mice/human intracellular recordings to interpret our data. Our analysis suggests that NS neurons correspond to parvalbumin (PV) or somatostatin (SST) interneurons while BS neurons are pyramidal (P) cells or vasoactive intestinal peptide (VIP) interneurons. We labeled neurons in monkey tissue sections of MT/MST and LPFC and found that the proportion of PV in cortical layers 2/3 decreased, while the proportion of CR cells increased from MT/MST to LPFC. Assuming that primate CR/CB/PV cells perform similar computations as mice VIP/SST/PV cells, our results suggest that changes in the proportion of CR and PV neurons in layers 2/3 cells may favor the emergence of activity encoding WM in association areas.

Volume Electron Microscopy Study of the Relationship Between Synapses and Astrocytes in the Developing Rat Somatosensory Cortex

In recent years, numerous studies have shown that astrocytes play an important role in neuronal processing of information. One of the most interesting findings is the existence of bidirectional interactions between neurons and astrocytes at synapses, which has given rise to the concept of “tripartite synapses” from a functional point of view. We used focused ion beam milling and scanning electron microscopy (FIB/SEM) to examine in 3D the relationship of synapses with astrocytes that were previously labeled by intracellular injections in the rat somatosensory cortex. We observed that a large number of synapses (32%) had no contact with astrocytic processes. The remaining synapses (68%) were in contact with astrocytic processes, either at the level of the synaptic cleft (44%) or with the pre- and/or post-synaptic elements (24%). Regarding synaptic morphology, larger synapses with more complex shapes were most frequently found within the population that had the synaptic cleft in contact with astrocytic processes. Furthermore, we observed that although synapses were randomly distributed in space, synapses that were free of astrocytic processes tended to form clusters. Overall, at least in the developing rat neocortex, the concept of tripartite synapse only seems to be applicable to a subset of synapses.

Retinotopic specializations of cortical and thalamic inputs to area MT

Retinotopic specializations in the ventral visual stream, especially foveal adaptations, provide primates with high-acuity vision in the central visual field. However, visual field specializations have not been studied in the dorsal visual stream, dedicated to processing visual motion and visually guided behaviors. To investigate this, we injected retrograde neuronal tracers occupying the whole visuotopic representation of the middle temporal (MT) visual area in marmoset monkeys and studied the distribution and morphology of the afferent primary visual cortex (V1) projections. Contrary to previous reports, we found a heterogeneous population of V1-MT projecting neurons distributed in layers 3C and 6. In layer 3C, spiny stellate neurons were distributed mainly in foveal representations, while pyramidal morphologies were characteristic of peripheral eccentricities. This primate adaptation of the V1 to MT pathway is arranged in a way that we had not previously understood, with abundant stellate projection neurons in the high-resolution foveal portions, suggesting rapid relay of motion information to visual area MT. We also describe that the medial portion of the inferior pulvinar (PIm), which is the main thalamic input to area MT, shows a retinotopic organization, likely reflecting the importance of this pathway during development and the establishment of area MT topography.

Distinct Properties of Layer 3 Pyramidal Neurons from Prefrontal and Parietal Areas of the Monkey Neocortex

In primates, working memory function depends on activity in a distributed network of cortical areas that display different patterns of delay task-related activity. These differences are correlated with, and might depend on, distinctive properties of the neurons located in each area. For example, layer 3 pyramidal neurons (L3PNs) differ significantly between primary visual and dorsolateral prefrontal (DLPFC) cortices. However, to what extent L3PNs differ between DLPFC and other association cortical areas is less clear. Hence, we compared the properties of L3PNs in monkey DLPFC versus posterior parietal cortex (PPC), a key node in the cortical working memory network. Using patch-clamp recordings and biocytin cell filling in acute brain slices, we assessed the physiology and morphology of L3PNs from monkey DLPFC and PPC. The L3PN transcriptome was studied using laser microdissection combined with DNA microarray or quantitative PCR. We found that in both DLPFC and PPC, L3PNs were divided into regular spiking (RS-L3PNs) and bursting (B-L3PNs) physiological subtypes. Whereas regional differences in single-cell excitability were modest, B-L3PNs were rare in PPC (RS-L3PN:B-L3PN, 94:6), but were abundant in DLPFC (50:50), showing greater physiological diversity. Moreover, DLPFC L3PNs display larger and more complex basal dendrites with higher dendritic spine density. Additionally, we found differential expression of hundreds of genes, suggesting a transcriptional basis for the differences in L3PN phenotype between DLPFC and PPC. These data show that the previously observed differences between DLPFC and PPC neuron activity during working memory tasks are associated with diversity in the cellular/molecular properties of L3PNs.SIGNIFICANCE STATEMENT In the human and nonhuman primate neocortex, layer 3 pyramidal neurons (L3PNs) differ significantly between dorsolateral prefrontal (DLPFC) and sensory areas. Hence, L3PN properties reflect, and may contribute to, a greater complexity of computations performed in DLPFC. However, across association cortical areas, L3PN properties are largely unexplored. We studied the physiology, dendrite morphology and transcriptome of L3PNs from macaque monkey DLPFC and posterior parietal cortex (PPC), two key nodes in the cortical working memory network. L3PNs from DLPFC had greater diversity of physiological properties and larger basal dendrites with higher spine density. Moreover, transcriptome analysis suggested a molecular basis for the differences in the physiological and morphological phenotypes of L3PNs from DLPFC and PPC.

Neuron density fundamentally relates to architecture and connectivity of the primate cerebral cortex

Studies of structural brain connectivity have revealed many intriguing features of complex cortical networks. To advance integrative theories of cortical organization, an understanding is required of how connectivity interrelates with other aspects of brain structure. Recent studies have suggested that interareal connectivity may be related to a variety of macroscopic as well as microscopic architectonic features of cortical areas. However, it is unclear how these features are inter-dependent and which of them most strongly and fundamentally relate to structural corticocortical connectivity. Here, we systematically investigated the relation of a range of microscopic and macroscopic architectonic features of cortical organization, namely layer III pyramidal cell soma cross section, dendritic synapse count, dendritic synapse density and dendritic tree size as well as area neuron density, to multiple properties of cortical connectivity, using a comprehensive, up-to-date structural connectome of the primate brain. Importantly, relationships were investigated by multi-variate analyses to account for the interrelations of features. Of all considered factors, the classical architectonic parameter of neuron density most strongly and consistently related to essential features of cortical connectivity (existence and laminar patterns of projections, area degree), and in conjoint analyses largely abolished effects of cellular morphological features. These results confirm neuron density as a central architectonic indicator of the primate cerebral cortex that is closely related to essential aspects of brain connectivity and is also highly indicative of further features of the architectonic organization of cortical areas, such as the considered cellular morphological measures. Our findings integrate several aspects of cortical micro- and macroscopic organization, with implications for cortical development and function.

Patterns of Dendritic Basal Field Orientation of Pyramidal Neurons in the Rat Somatosensory Cortex

The study of neuronal dendritic orientation is of interest because it is related to how neurons grow dendrites to establish the synaptic input that neurons receive. The dendritic orientations of neurons in the nervous system vary, ranging from rather heterogeneously distributed (asymmetric) to homogeneously distributed (symmetric) dendritic arbors. Here, we analyze the dendritic orientation of the basal dendrites of intracellularly labeled pyramidal neurons from horizontal sections of Layers II–VI of the hindlimb somatosensory (S1HL) cortex of 14-d-old (P14) rats. We used circular statistics and proposed two new graphical descriptive representations of the neuron. We found that the dendritic pattern of most neurons was asymmetric. Furthermore, we found that there is a mixture of different types of orientations within any given group of neurons in any cortical layer. In addition, we investigated whether dendritic orientation was related to the physical location within the brain with respect to the anterior, dorsal, posterior and ventral directions. Generally, there was a preference towards the anterior orientation. A comparison between layers revealed that the preference for the anterior orientation was more pronounced in neurons located in Layers II, III, IV, and Va than for the neurons located in Layers Vb and VI. The dorsal orientation was the least preferred orientation in all layers, except for Layers IV and Va, where the ventral orientation had the lowest preference. Therefore, the orientation of basal dendritic arbors of pyramidal cells is variable and asymmetric, although a majority has a single orientation with a preference for the anterior direction in P14 rats.

Auditory and Visual Motion Processing and Integration in the Primate Cerebral Cortex

The ability of animals to detect motion is critical for survival, and errors or even delays in motion perception may prove costly. In the natural world, moving objects in the visual field often produce concurrent sounds. Thus, it can highly advantageous to detect motion elicited from sensory signals of either modality, and to integrate them to produce more reliable motion perception. A great deal of progress has been made in understanding how visual motion perception is governed by the activity of single neurons in the primate cerebral cortex, but far less progress has been made in understanding both auditory motion and audiovisual motion integration. Here we, review the key cortical regions for motion processing, focussing on translational motion. We compare the representations of space and motion in the visual and auditory systems, and examine how single neurons in these two sensory systems encode the direction of motion. We also discuss the way in which humans integrate of audio and visual motion cues, and the regions of the cortex that may mediate this process.

Neuronal Distribution Across the Cerebral Cortex of the Marmoset Monkey (Callithrix jacchus)

Using stereological analysis of NeuN-stained sections, we investigated neuronal density and number of neurons per column throughout the marmoset cortex. Estimates of mean neuronal density encompassed a greater than 3-fold range, from >150 000 neurons/mm3 in the primary visual cortex to ~50 000 neurons/mm3 in the piriform complex. There was a trend for density to decrease from posterior to anterior cortex, but also local gradients, which resulted in a complex pattern; for example, in frontal, auditory, and somatosensory cortex neuronal density tended to increase towards anterior areas. Anterior cingulate, motor, premotor, insular, and ventral temporal areas were characterized by relatively low neuronal densities. Analysis across the depth of the cortex revealed greater laminar variation of neuronal density in occipital, parietal, and inferior temporal areas, in comparison with other regions. Moreover, differences between areas were more pronounced in the supragranular layers than in infragranular layers. Calculations of the number of neurons per unit column revealed a pattern that was distinct from that of neuronal density, including local peaks in the posterior parietal, superior temporal, precuneate, frontopolar, and temporopolar regions. These results suggest that neuronal distribution in adult cortex result from a complex interaction of developmental/ evolutionary determinants and functional requirements.

Selective Loss of Thin Spines in Area 7a of the Primate Intraparietal Sulcus Predicts Age-Related Working Memory Impairment

Brodmann area 7a of the parietal cortex is active during working memory tasks in humans and nonhuman primates, but the composition and density of dendritic spines in area 7a and their relevance both to working memory and cognitive aging remain unexplored. Aged monkeys have impaired working memory, and we have previously shown that this age-induced cognitive impairment is partially mediated by a loss of thin spines in prefrontal cortex area 46, a critical area for working memory. Because area 46 is reciprocally connected with area 7a of the parietal cortex and 7a mediates visual attention integration, we hypothesized that thin spine density in area 7a would correlate with working memory performance as well. To investigate the synaptic profile of area 7a and its relevance to working memory and cognitive aging, we investigated differences in spine type and density in layer III pyramidal cells of area 7a in young and aged, male and female rhesus macaques (Macaca mulatta) that were cognitively assessed using the delayed response test of working memory. Area 7a shows age-related loss of thin spines, and thin spine density positively correlates with delayed response performance in aged monkeys. In contrast, these cells show no age-related changes in dendritic length or branching. These changes mirror age-related changes in area 46 but are distinct from other neocortical regions, such as V1. These findings support our hypothesis that cognitive aging is driven primarily by synaptic changes, and more specifically by changes in thin spines, in key association areas.SIGNIFICANCE STATEMENT This study advances our understanding of cognitive aging by demonstrating the relevance of area 7a thin spines to working memory performance. This study is the first to look at cognitive aging in the intraparietal sulcus, and also the first to report spine or dendritic measures for area 7a in either young adult or aged nonhuman primates. These results contribute to the hypothesis that thin spines support working memory performance and confirm our prior observation that cognitive aging is driven by synaptic changes rather than changes in dendritic morphology or neuron death. Importantly, these data show that age-related working memory changes are not limited to disruptions of the prefrontal cortex but also include an association region heavily interconnected with prefrontal cortex.

Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography

Hierarchy provides a unifying principle for the macroscale organization of anatomical and functional properties across primate cortex, yet microscale bases of specialization across human cortex are poorly understood. Anatomical hierarchy is conventionally informed by invasive tract-tracing measurements, creating a need for a principled proxy measure in humans. Moreover, cortex exhibits marked interareal variation in gene expression, yet organizing principles of cortical transcription remain unclear. We hypothesized that specialization of cortical microcircuitry involves hierarchical gradients of gene expression. We found that a noninvasive neuroimaging measure-MRI-derived T1-weighted/T2-weighted (T1w/T2w) mapping-reliably indexes anatomical hierarchy, and it captures the dominant pattern of transcriptional variation across human cortex. We found hierarchical gradients in expression profiles of genes related to microcircuit function, consistent with monkey microanatomy, and implicated in neuropsychiatric disorders. Our findings identify a hierarchical axis linking cortical transcription and anatomy, along which gradients of microscale properties may contribute to the macroscale specialization of cortical function.

Controlling Complexity of Cerebral Cortex Simulations-I: CxSystem, a Flexible Cortical Simulation Framework

Simulation of the cerebral cortex requires a combination of extensive domain-specific knowledge and efficient software. However, when the complexity of the biological system is combined with that of the software, the likelihood of coding errors increases, which slows model adjustments. Moreover, few life scientists are familiar with software engineering and would benefit from simplicity in form of a high-level abstraction of the biological model. Our primary aim was to build a scalable cortical simulation framework for personal computers. We isolated an adjustable part of the domain-specific knowledge from the software. Next, we designed a framework that reads the model parameters from comma-separated value files and creates the necessary code for Brian2 model simulation. This separation allows rapid exploration of complex cortical circuits while decreasing the likelihood of coding errors and automatically using efficient hardware devices. Next, we tested the system on a simplified version of the neocortical microcircuit proposed by Markram and colleagues ( 2015 ). Our results indicate that the framework can efficiently perform simulations using Python, C <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>+</mml:mo><mml:mo>+</mml:mo></mml:mrow></mml:math> , and GPU devices. The most efficient device varied with computer hardware and the duration and scale of the simulated system. The speed of Brian2 was retained despite an overlying layer of software. However, the Python and C <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>+</mml:mo><mml:mo>+</mml:mo></mml:mrow></mml:math> devices inherited the single core limitation of Brian2. The CxSystem framework supports exploration of complex models on personal computers and thus has the potential to facilitate research on cortical networks and systems.

Parallel Development of Chromatin Patterns, Neuron Morphology, and Connections: Potential for Disruption in Autism

The phenotype of neurons and their connections depend on complex genetic and epigenetic processes that regulate the expression of genes in the nucleus during development and throughout life. Here we examined the distribution of nuclear chromatin patters in relation to the epigenetic landscape, phenotype and connections of neurons with a focus on the primate cerebral cortex. We show that nuclear patterns of chromatin in cortical neurons are related to neuron size and cortical connections. Moreover, we point to evidence that reveals an orderly sequence of events during development, linking chromatin and gene expression patterns, neuron morphology, function, and connections across cortical areas and layers. Based on this synthesis, we posit that systematic studies of changes in chromatin patterns and epigenetic marks across cortical areas will provide novel insights on the development and evolution of cortical networks, and their disruption in connectivity disorders of developmental origin, like autism. Achieving this requires embedding and interpreting genetic, transcriptional, and epigenetic studies within a framework that takes into consideration distinct types of neurons, local circuit interactions, and interareal pathways. These features vary systematically across cortical areas in parallel with laminar structure and are differentially affected in disorders. Finally, based on evidence that autism-associated genetic polymorphisms are especially prominent in excitatory neurons and connectivity disruption affects mostly limbic cortices, we employ this systematic approach to propose novel, targeted studies of projection neurons in limbic areas to elucidate the emergence and time-course of developmental disruptions in autism.

3D morphology-based clustering and simulation of human pyramidal cell dendritic spines

The dendritic spines of pyramidal neurons are the targets of most excitatory synapses in the cerebral cortex. They have a wide variety of morphologies, and their morphology appears to be critical from the functional point of view. To further characterize dendritic spine geometry, we used in this paper over 7,000 individually 3D reconstructed dendritic spines from human cortical pyramidal neurons to group dendritic spines using model-based clustering. This approach uncovered six separate groups of human dendritic spines. To better understand the differences between these groups, the discriminative characteristics of each group were identified as a set of rules. Model-based clustering was also useful for simulating accurate 3D virtual representations of spines that matched the morphological definitions of each cluster. This mathematical approach could provide a useful tool for theoretical predictions on the functional features of human pyramidal neurons based on the morphology of dendritic spines.

Dendritic spines of pyramidal neurons are the targets of most excitatory synapses in the cerebral cortex and their morphology appears to be critical from the functional point of view. Thus, characterizing this morphology is necessary to link structural and functional spine data and thus interpret and make them more meaningful. We have used a large database of more than 7,000 individually 3D reconstructed dendritic spines from human cortical pyramidal neurons that is first transformed into a set of 54 quantitative features characterizing spine geometry mathematically. The resulting data set is grouped into spine clusters based on a probabilistic model with Gaussian finite mixtures. We uncover six groups of spines whose discriminative characteristics are identified with machine learning methods as a set of rules. The clustering model allows us to simulate accurate spines from human pyramidal neurons to suggest new hypotheses of the functional organization of these cells.

Neural architecture: from cells to circuits

Circuit operations are determined jointly by the properties of the circuit elements and the properties of the connections among these elements. In the nervous system, neurons exhibit diverse morphologies and branching patterns, allowing rich compartmentalization within individual cells and complex synaptic interactions among groups of cells. In this review, we summarize work detailing how neuronal morphology impacts neural circuit function. In particular, we consider example neurons in the retina, cerebral cortex, and the stomatogastric ganglion of crustaceans. We also explore molecular coregulators of morphology and circuit function to begin bridging the gap between molecular and systems approaches. By identifying motifs in different systems, we move closer to understanding the structure-function relationships that are present in neural circuits.

Altered Gradients of Glutamate and Gamma-Aminobutyric Acid Transcripts in the Cortical Visuospatial Working Memory Network in Schizophrenia

BACKGROUND

Visuospatial working memory (vsWM), which is impaired in schizophrenia, requires information transfer across multiple nodes in the cerebral cortex, including visual, posterior parietal, and dorsolateral prefrontal regions. Information is conveyed across these regions via the excitatory projections of glutamatergic pyramidal neurons located in layer 3, whose activity is modulated by local inhibitory gamma-aminobutyric acidergic (GABAergic) neurons. Key properties of these neurons differ across these cortical regions. Consequently, in schizophrenia, alterations in the expression of gene products regulating these properties could disrupt vsWM function in different ways, depending on the region(s) affected.

METHODS

Here, we quantified the expression of markers of glutamate and GABA neurotransmission selectively in layer 3 of four cortical regions in the vsWM network from 20 matched pairs of schizophrenia and unaffected comparison subjects.

RESULTS

In comparison subjects, levels of glutamate transcripts tended to increase, whereas GABA transcript levels tended to decrease, from caudal to rostral, across cortical regions of the vsWM network. Composite measures across all transcripts revealed a significant effect of region, with the glutamate measure lowest in the primary visual cortex and highest in the dorsolateral prefrontal cortex, whereas the GABA measure showed the opposite pattern. In schizophrenia subjects, the expression levels of many of these transcripts were altered. However, this disease effect differed across regions, such that the caudal-to-rostral increase in the glutamate measure was blunted and the caudal-to-rostral decline in the GABA measure was enhanced in the illness.

CONCLUSIONS

Differential alterations in layer 3 glutamate and GABA neurotransmission across cortical regions may contribute to vsWM deficits in schizophrenia.

Non-invasive laminar inference with MEG: Comparison of methods and source inversion algorithms

Magnetoencephalography (MEG) is a direct measure of neuronal current flow; its anatomical resolution is therefore not constrained by physiology but rather by data quality and the models used to explain these data. Recent simulation work has shown that it is possible to distinguish between signals arising in the deep and superficial cortical laminae given accurate knowledge of these surfaces with respect to the MEG sensors. This previous work has focused around a single inversion scheme (multiple sparse priors) and a single global parametric fit metric (free energy). In this paper we use several different source inversion algorithms and both local and global, as well as parametric and non-parametric fit metrics in order to demonstrate the robustness of the discrimination between layers. We find that only algorithms with some sparsity constraint can successfully be used to make laminar discrimination. Importantly, local t-statistics, global cross-validation and free energy all provide robust and mutually corroborating metrics of fit. We show that discrimination accuracy is affected by patch size estimates, cortical surface features, and lead field strength, which suggests several possible future improvements to this technique. This study demonstrates the possibility of determining the laminar origin of MEG sensor activity, and thus directly testing theories of human cognition that involve laminar- and frequency-specific mechanisms. This possibility can now be achieved using recent developments in high precision MEG, most notably the use of subject-specific head-casts, which allow for significant increases in data quality and therefore anatomically precise MEG recordings.

Section

Analysis methods.

Classifications

Source localization: inverse problem; Source localization: other.

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Laminar inferences can be made with MEG using both local and global fit metrics.

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Source inversion algorithms with sparsity constraints performed best.

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Classification is affected by patch size estimates, anatomy, and lead field strength.

Age-related plasticity of the axon initial segment of cortical pyramidal cells in marmoset monkeys

Structural plasticity of the axon initial segment (AIS), the site of action potential initiation, is observed as part of the normal early development of the cortex, as well as in association with injury and disease. Here, we show that structural AIS plasticity also occurs with normal aging in adult marmosets. Immunohistochemical techniques were used to reveal the extent of the AIS of layer 2/3A pyramidal cells in 8 neocortical areas. We found that the AIS length varied significantly between areas in young adult (2-3 years old) marmosets, with neurons in frontal area 14C having the longest AIS, and those in the primary visual cortex the shortest. Similar interareal differences were observed in aged (12-14 year old) monkeys, but the AIS was significantly shortened in many areas, relative to the corresponding length in young adults. Shortening of the AIS is likely to represent a compensatory response to changes in the excitation-inhibition balance, associated with the loss of GABAergic interneurons in the aged cortex.

Area-Specific Features of Pyramidal Neurons-a Comparative Study in Mouse and Rhesus Monkey

A principal challenge of systems neuroscience is to understand the unique characteristics of cortical neurons and circuits that enable area- and species-specific sensory encoding, motor function, cognition, and behavior. To address this issue, we compared properties of layer 3 pyramidal neurons in 2 cortical areas that span a broad range of cortical function-primary sensory (V1), to cognitive (frontal)-in the mouse and the rhesus monkey. Hierarchical clustering and discriminant analyses of 15 physiological and 25 morphological variables revealed 2 fundamental principles. First, V1 and frontal neurons are remarkably similar with regard to nearly every property in the mouse, while the opposite is true in the monkey, with V1 and frontal neurons exhibiting significant differences in nearly every property assessed. Second, neurons within visual and frontal areas differ significantly between the mouse and the monkey. Neurons in mouse and monkey V1 are the same size, but differ in nearly every other way; mouse frontal cortical neurons are smaller than those in the monkey and also differ substantially with regard to most other properties. These findings have broad implications for understanding the differential contributions of heterogeneous neuronal types in construction of cortical microcircuitry in diverse brain areas and species.

Postnatal Development of Intrinsic Horizontal Axons in Macaque Inferior Temporal and Primary Visual Cortices

Two distinct areas along the ventral visual stream of monkeys, the primary visual (V1) and inferior temporal (TE) cortices, exhibit different projection patterns of intrinsic horizontal axons with patchy terminal fields in adult animals. The differences between the patches in these 2 areas may reflect differences in cortical representation and processing of visual information. We studied the postnatal development of patches by injecting an anterograde tracer into TE and V1 in monkeys of various ages. At 1 week of age, labeled patches with distribution patterns reminiscent of those in adults were already present in both areas. The labeling intensity of patches decayed exponentially with projection distance in monkeys of all ages in both areas, but this trend was far less evident in TE. The number and extent of patches gradually decreased with age in V1, but not in TE. In V1, axonal and bouton densities increased postnatally only in patches with short projection distances, whereas in TE this density change occurred in patches with various projection distances. Thus, patches with area-specific distribution patterns are formed early in life, and area-specific postnatal developmental processes shape the connectivity of patches into adulthood.

Postnatal Dendritic Growth and Spinogenesis of Layer-V Pyramidal Cells Differ between Visual, Inferotemporal, and Prefrontal Cortex of the Macaque Monkey

Pyramidal cells in the primate cerebral cortex, particularly those in layer III, exhibit regional variation in both the time course and magnitude of postnatal growth and pruning of dendrites and spines. Less is known about the development of pyramidal cell dendrites and spines in other cortical layers. Here we studied dendritic morphology of layer-V pyramidal cells in primary visual cortex (V1, sensory), cytoarchitectonic area TE in the inferotemporal cortex (sensory association), and granular prefrontal cortex (Walker's area 12, executive) of macaque monkeys at the ages of 2 days, 3 weeks, 3.5 months, and 4.5 years. We found that changes in the basal dendritic field area of pyramidal cells were different across the three areas. In V1, field size became smaller over time (largest at 2 days, half that size at 4.5 years), in TE it did not change, and in area 12 it became larger over time (smallest at 2 days, 1.5 times greater at 4.5 years). In V1 and TE, the total number of branch points in the basal dendritic trees was similar between 2 days and 4.5 years, while in area 12 the number was greater in the adult monkeys than in the younger ones. Spine density peaked at 3 weeks and declined in all areas by adulthood, with V1 exhibiting a faster decline than area TE or area 12. Estimates of the total number of spines in the dendritic trees revealed that following the onset of visual experience, pyramidal cells in V1 lose more spines than they grow, whereas those in TE and area 12 grow more spines than they lose during the same period. These data provide further evidence that the process of synaptic refinement in cortical pyramidal cells differs not only according to time, but also location within the cortex. Furthermore, given the previous finding that layer-III pyramidal cells in all these areas exhibit the highest density and total number of spines at 3.5 months, the current results indicate that pyramidal cells in layers III and V develop spines at different rates.

Pyramidal Neurons Are Not Generalizable Building Blocks of Cortical Networks

A key challenge in cortical neuroscience is to gain a comprehensive understanding of how pyramidal neuron heterogeneity across different areas and species underlies the functional specialization of individual neurons, networks, and areas. Comparative studies have been important in this endeavor, providing data relevant to the question of which of the many inherent properties of individual pyramidal neurons are necessary and sufficient for species-specific network and areal function. In this mini review, the importance of pyramidal neuron structural properties for signaling are outlined, followed by a summary of our recent work comparing the structural features of mouse (C57/BL6 strain) and rhesus monkey layer 3 (L3) pyramidal neurons in primary visual and frontal association cortices and their implications for neuronal and areal function. Based on these and other published data, L3 pyramidal neurons plausibly might be considered broadly “generalizable” from one area to another in the mouse neocortex due to their many similarities, but major differences in the properties of these neurons in diverse areas in the rhesus monkey neocortex rules this out in the primate. Further, fundamental differences in the dendritic topology of mouse and rhesus monkey pyramidal neurons highlight the implausibility of straightforward scaling and/or extrapolation from mouse to primate neurons and cortical networks.

Rat-strain dependent changes of dendritic and spine morphology in the hippocampus after cocaine self-administration

We previously showed that cocaine self-administration increases spine density in CA1 hippocampal neurons in Lewis (LEW) but not in Fischer 344 (F344) rats. Dendritic spine morphology is intimately related to its function. Thus, we conducted a 3D morphological analysis of CA1 dendrites and dendritic spines in these two strains of rats. Strain-specific differences were observed prior to cocaine self-administration: LEW rats had significantly larger dendritic diameters but lower spine density than the F344 strain. After cocaine self-administration, proximal dendritic volume, dendritic surface area and spine density were increased in LEW rats, where a higher percentage of larger spines were also observed. In addition, we found a strong positive correlation between dendritic volume and spine morphology, and a moderate correlation between dendritic volume and spine density in cocaine self-administered LEW rats, an effect that was not evident in any other condition. By contrast, after cocaine self-administration, F334 rats showed decreased spine head volumes. Our findings suggest that genetic differences could play a key role in the structural plasticity induced by cocaine in CA1 pyramidal neurons. These cocaine-induced alterations could be related to differences in the memory processing of drug reward cues that could potentially explain differential individual vulnerability to cocaine addiction.

Coupling between One-Dimensional Networks Reconciles Conflicting Dynamics in LIP and Reveals Its Recurrent Circuitry

Little is known about the internal circuitry of the primate lateral intraparietal area (LIP). During two versions of a delayed-saccade task, we found radically different network dynamics beneath similar population average firing patterns. When neurons are not influenced by stimuli outside their receptive fields (RFs), dynamics of the high-dimensional LIP network during slowly varying activity lie predominantly in one multi-neuronal dimension, as described previously. However, when activity is suppressed by stimuli outside the RF, slow LIP dynamics markedly deviate from a single dimension. The conflicting results can be reconciled if two LIP local networks, each underlying an RF location and dominated by a single multi-neuronal activity pattern, are suppressively coupled to each other. These results demonstrate the low dimensionality of slow LIP local dynamics, and suggest that LIP local networks encoding the attentional and movement priority of competing visual locations actively suppress one another.