A Perspective on Cortical Layering and Layer-Spanning Neuronal Elements

Cellular psychology: relating cognition to context-sensitive pyramidal cells

'Cellular psychology' is a new field of inquiry that studies dendritic mechanisms for adapting mental events to the current context, thus increasing their coherence, flexibility, effectiveness, and comprehensibility. Apical dendrites of neocortical pyramidal cells have a crucial role in cognition - those dendrites receive input from diverse sources, including feedback, and can amplify the cell's feedforward transmission if relevant in that context. Specialized subsets of inhibitory interneurons regulate this cooperative context-sensitive processing by increasing or decreasing amplification. Apical input has different effects on cellular output depending on whether we are awake, deeply asleep, or dreaming. Furthermore, wakeful thought and imagery may depend on apical input. High-resolution neuroimaging in humans supports and complements evidence on these cellular mechanisms from other mammals.

The vertebrate retina: a window into the evolution of computation in the brain

Animal brains are probably the most complex computational machines on our planet, and like everything in biology, they are the product of evolution. Advances in developmental and palaeobiology have been expanding our general understanding of how nervous systems can change at a molecular and structural level. However, how these changes translate into altered function - that is, into 'computation' - remains comparatively sparsely explored. What, concretely, does it mean for neuronal computation when neurons change their morphology and connectivity, when new neurons appear or old ones disappear, or when transmitter systems are slowly modified over many generations? And how does evolution use these many possible knobs and dials to constantly tune computation to give rise to the amazing diversity in animal behaviours we see today? Addressing these major gaps of understanding benefits from choosing a suitable model system. Here, I present the vertebrate retina as one perhaps unusually promising candidate. The retina is ancient and displays highly conserved core organisational principles across the entire vertebrate lineage, alongside a myriad of adjustments across extant species that were shaped by the history of their visual ecology. Moreover, the computational logic of the retina is readily interrogated experimentally, and our existing understanding of retinal circuits in a handful of species can serve as an anchor when exploring the visual circuit adaptations across the entire vertebrate tree of life, from fish deep in the aphotic zone of the oceans to eagles soaring high up in the sky.

Large-scale deep tissue voltage imaging with targeted-illumination confocal microscopy

Voltage imaging with cellular specificity has been made possible by advances in genetically encoded voltage indicators. However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines the signal-to-noise ratio and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating while also maximizing signal detection efficiency. The resulting benefits in signal-to-noise ratio and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different genetically encoded voltage indicator classes.

Dysfunctions of cellular context-sensitivity in neurodevelopmental learning disabilities

Pyramidal neurons have a pivotal role in the cognitive capabilities of neocortex. Though they have been predominantly modeled as integrate-and-fire point processors, many of them have another point of input integration in their apical dendrites that is central to mechanisms endowing them with the sensitivity to context that underlies basic cognitive capabilities. Here we review evidence implicating impairments of those mechanisms in three major neurodevelopmental disabilities, fragile X, Down syndrome, and fetal alcohol spectrum disorders. Multiple dysfunctions of the mechanisms by which pyramidal cells are sensitive to context are found to be implicated in all three syndromes. Further deciphering of these cellular mechanisms would lead to the understanding of and therapies for learning disabilities beyond any that are currently available.

Spatial Dissection of the Distinct Cellular Responses to Normal Aging and Alzheimer's Disease in Human Prefrontal Cortex at Single-Nucleus Resolution

Aging significantly elevates the risk for Alzheimer's disease (AD), contributing to the accumulation of AD pathologies, such as amyloid-β (Aβ), inflammation, and oxidative stress. The human prefrontal cortex (PFC) is highly vulnerable to the impacts of both aging and AD. Unveiling and understanding the molecular alterations in PFC associated with normal aging (NA) and AD is essential for elucidating the mechanisms of AD progression and developing novel therapeutics for this devastating disease. In this study, for the first time, we employed a cutting-edge spatial transcriptome platform, STOmics® SpaTial Enhanced Resolution Omics-sequencing (Stereo-seq), to generate the first comprehensive, subcellular resolution spatial transcriptome atlas of the human PFC from six AD cases at various neuropathological stages and six age, sex, and ethnicity matched controls. Our analyses revealed distinct transcriptional alterations across six neocortex layers, highlighted the AD-associated disruptions in laminar architecture, and identified changes in layer-to-layer interactions as AD progresses. Further, throughout the progression from NA to various stages of AD, we discovered specific genes that were significantly upregulated in neurons experiencing high stress and in nearby non-neuronal cells, compared to cells distant from the source of stress. Notably, the cell-cell interactions between the neurons under the high stress and adjacent glial cells that promote Aβ clearance and neuroprotection were diminished in AD in response to stressors compared to NA. Through cell-type specific gene co-expression analysis, we identified three modules in excitatory and inhibitory neurons associated with neuronal protection, protein dephosphorylation, and negative regulation of Aβ plaque formation. These modules negatively correlated with AD progression, indicating a reduced capacity for toxic substance clearance in AD subject samples. Moreover, we have discovered a novel transcription factor, ZNF460, that regulates all three modules, establishing it as a potential new therapeutic target for AD. Overall, utilizing the latest spatial transcriptome platform, our study developed the first transcriptome-wide atlas with subcellular resolution for assessing the molecular alterations in the human PFC due to AD. This atlas sheds light on the potential mechanisms underlying the progression from NA to AD.

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

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

An Agent-Based Model to Reproduce the Boolean Logic Behaviour of Neuronal Self-Organised Communities through Pulse Delay Modulation and Generation of Logic Gates

The human brain is arguably the most complex "machine" to ever exist. Its detailed functioning is yet to be fully understood, let alone modelled. Neurological processes have logical signal-processing and biophysical aspects, and both affect the brain's structure, functioning and adaptation. Mathematical approaches based on both information and graph theory have been extensively used in an attempt to approximate its biological functioning, along with Artificial Intelligence frameworks inspired by its logical functioning. In this article, an approach to model some aspects of the brain learning and signal processing is presented, mimicking the metastability and backpropagation found in the real brain while also accounting for neuroplasticity. Several simulations are carried out with this model to demonstrate how dynamic neuroplasticity, neural inhibition and neuron migration can reshape the brain's logical connectivity to synchronise signal processing and obtain certain target latencies. This work showcases the importance of dynamic logical and biophysical remodelling in brain plasticity. Combining mathematical (agents, graph theory, topology and backpropagation) and biomedical ingredients (metastability, neuroplasticity and migration), these preliminary results prove complex brain phenomena can be reproduced-under pertinent simplifications-via affordable computations, which can be construed as a starting point for more ambitiously accurate simulations.

Cortical depth profiles in primary visual cortex for illusory and imaginary experiences

Visual illusions and mental imagery are non-physical sensory experiences that involve cortical feedback processing in the primary visual cortex. Using laminar functional magnetic resonance imaging (fMRI) in two studies, we investigate if information about these internal experiences is visible in the activation patterns of different layers of primary visual cortex (V1). We find that imagery content is decodable mainly from deep layers of V1, whereas seemingly 'real' illusory content is decodable mainly from superficial layers. Furthermore, illusory content shares information with perceptual content, whilst imagery content does not generalise to illusory or perceptual information. Together, our results suggest that illusions and imagery, which differ immensely in their subjective experiences, also involve partially distinct early visual microcircuits. However, overlapping microcircuit recruitment might emerge based on the nuanced nature of subjective conscious experience.

Cellular and laminar architecture: A short history and commentary

The feedforward/feedback classification, as originally stated in relation to early visual areas in the macaque monkey, has had a significant influence on ideas of laminar interactions, area reciprocity, and cortical hierarchical organization. In some contrast with this macroscale "laminar connectomics," a more cellular approach to cortical connections, as briefly surveyed here, points to a still underappreciated heterogeneity of neuronal subtypes and complex microcircuitries. From the perspective of heterogeneities, the question of how brain regions interact and influence each other quickly leads to discussions about concurrent hierarchical and nonhierarchical cortical features, brain organization as a multiscale system forming nested groups and hierarchies, connectomes annotated by multiple biological attributes, and interleaved and overlapping scales of organization.

Layer 1 of somatosensory cortex: an important site for input to a tiny cortical compartment

Neocortical layer 1 has been proposed to be at the center for top-down and bottom-up integration. It is a locus for interactions between long-range inputs, layer 1 interneurons, and apical tuft dendrites of pyramidal neurons. While input to layer 1 has been studied intensively, the level and effect of input to this layer has still not been completely characterized. Here we examined the input to layer 1 of mouse somatosensory cortex with retrograde tracing and optogenetics. Our assays reveal that local input to layer 1 is predominantly from layers 2/3 and 5 pyramidal neurons and interneurons, and that subtypes of local layers 5 and 6b neurons project to layer 1 with different probabilities. Long-range input from sensory-motor cortices to layer 1 of somatosensory cortex arose predominantly from layers 2/3 neurons. Our optogenetic experiments showed that intra-telencephalic layer 5 pyramidal neurons drive layer 1 interneurons but have no effect locally on layer 5 apical tuft dendrites. Dual retrograde tracing revealed that a fraction of local and long-range neurons was both presynaptic to layer 5 neurons and projected to layer 1. Our work highlights the prominent role of local inputs to layer 1 and shows the potential for complex interactions between long-range and local inputs, which are both in position to modify the output of somatosensory cortex.

Neuronal connected burst cascades bridge macroscale adaptive signatures across arousal states

The human brain displays a rich repertoire of states that emerge from the microscopic interactions of cortical and subcortical neurons. Difficulties inherent within large-scale simultaneous neuronal recording limit our ability to link biophysical processes at the microscale to emergent macroscopic brain states. Here we introduce a microscale biophysical network model of layer-5 pyramidal neurons that display graded coarse-sampled dynamics matching those observed in macroscale electrophysiological recordings from macaques and humans. We invert our model to identify the neuronal spike and burst dynamics that differentiate unconscious, dreaming, and awake arousal states and provide insights into their functional signatures. We further show that neuromodulatory arousal can mediate different modes of neuronal dynamics around a low-dimensional energy landscape, which in turn changes the response of the model to external stimuli. Our results highlight the promise of multiscale modelling to bridge theories of consciousness across spatiotemporal scales.

Different roles of response covariability and its attentional modulation in the sensory cortex and posterior parietal cortex

The covariability of neural responses in the neuron population is highly relevant to the information encoding. Cognitive processes, such as attention, are found to modulate the covariability in the visual cortex to improve information encoding, suggesting the computational advantage of covariability modulation in the neural system. However, is the covariability modulation a general mechanism for enhanced information encoding throughout the information processing pathway, or only adopted in certain processing stages, depending on the property of neural representation? Here, with ultrahigh-field MRI, we examined the covariability, which was estimated by noise correlation, in different attention states in the early visual cortex and posterior parietal cortex (PPC) of the human brain, and its relationship to the quality of information encoding. Our results showed that while attention decreased the covariability to improve the stimulus encoding in the early visual cortex, covariability modulation was not observed in the PPC, where covariability had little impact on information encoding. Further, attention promoted the information flow between the early visual cortex and PPC, with an apparent emphasis on a flow from high- to low-dimensional representations, suggesting the existence of a reduction in the dimensionality of neural representation from the early visual cortex to PPC. Finally, the neural response patterns in the PPC could predict the amplitudes of covariability change in the early visual cortex, indicating a top-down control from the PPC to early visual cortex. Our findings reveal the specific roles of the sensory cortex and PPC during attentional modulation of covariability, determined by the complexity and fidelity of the neural representation in each cortical region.

Canonical circuit computations for computer vision

Advanced computer vision mechanisms have been inspired by neuroscientific findings. However, with the focus on improving benchmark achievements, technical solutions have been shaped by application and engineering constraints. This includes the training of neural networks which led to the development of feature detectors optimally suited to the application domain. However, the limitations of such approaches motivate the need to identify computational principles, or motifs, in biological vision that can enable further foundational advances in machine vision. We propose to utilize structural and functional principles of neural systems that have been largely overlooked. They potentially provide new inspirations for computer vision mechanisms and models. Recurrent feedforward, lateral, and feedback interactions characterize general principles underlying processing in mammals. We derive a formal specification of core computational motifs that utilize these principles. These are combined to define model mechanisms for visual shape and motion processing. We demonstrate how such a framework can be adopted to run on neuromorphic brain-inspired hardware platforms and can be extended to automatically adapt to environment statistics. We argue that the identified principles and their formalization inspires sophisticated computational mechanisms with improved explanatory scope. These and other elaborated, biologically inspired models can be employed to design computer vision solutions for different tasks and they can be used to advance neural network architectures of learning.

Mediation of the association between disadvantaged neighborhoods and cortical microstructure by body mass index

BACKGROUND

Living in a disadvantaged neighborhood is associated with worse health outcomes, including brain health, yet the underlying biological mechanisms are incompletely understood. We investigated the relationship between neighborhood disadvantage and cortical microstructure, assessed as the T1-weighted/T2-weighted ratio (T1w/T2w) on magnetic resonance imaging, and the potential mediating roles of body mass index (BMI) and stress, as well as the relationship between trans-fatty acid intake and cortical microstructure.

METHODS

Participants comprised 92 adults (27 men; 65 women) who underwent neuroimaging and provided residential address information. Neighborhood disadvantage was assessed as the 2020 California State area deprivation index (ADI). The T1w/T2w ratio was calculated at four cortical ribbon levels (deep, lower-middle, upper-middle, and superficial). Perceived stress and BMI were assessed as potential mediating factors. Dietary data was collected in 81 participants.

RESULTS

Here, we show that worse ADI is positively correlated with BMI (r = 0.27, p = .01) and perceived stress (r = 0.22, p = .04); decreased T1w/T2w ratio in middle/deep cortex in supramarginal, temporal, and primary motor regions (p < .001); and increased T1w/T2w ratio in superficial cortex in medial prefrontal and cingulate regions (p < .001). Increased BMI partially mediates the relationship between worse ADI and observed T1w/T2w ratio increases (p = .02). Further, trans-fatty acid intake (high in fried fast foods and obesogenic) is correlated with these T1w/T2w ratio increases (p = .03).

CONCLUSIONS

Obesogenic aspects of neighborhood disadvantage, including poor dietary quality, may disrupt information processing flexibility in regions involved in reward, emotion regulation, and cognition. These data further suggest ramifications of living in a disadvantaged neighborhood on brain health.

Ultra-High Field Imaging of Human Visual Cognition

Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e., submillimeter resolution) tool that allows us to probe laminar and columnar circuits, distinguish bottom-up versus top-down pathways, and map small subcortical areas. We review recent work demonstrating that UHF fMRI provides a robust methodology for imaging the brain across cortical depths and columns that provides insights into the brain's organization and functions at unprecedented spatial resolution, advancing our understanding of the fine-scale computations and interareal communication that support visual cognition.

Large-scale deep tissue voltage imaging with targeted illumination confocal microscopy

Voltage imaging with cellular specificity has been made possible by the tremendous advances in genetically encoded voltage indicators (GEVIs). However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines signal-to-noise ratio (SNR) and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating, while also maximizing signal detection efficiency. The resulting benefits in SNR and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different GEVI classes.

Could theropod dinosaurs have evolved to a human level of intelligence?

Noting that some theropod dinosaurs had large brains, large grasping hands, and likely binocular vision, paleontologist Dale Russell suggested that a branch of these dinosaurs might have evolved to a human intelligence level, had dinosaurs not become extinct. I offer reasons why the likely pallial organization in dinosaurs would have made this improbable, based on four assumptions. First, it is assumed that achieving human intelligence requires evolving an equivalent of the about 200 functionally specialized cortical areas characteristic of humans. Second, it is assumed that dinosaurs had an avian nuclear type of pallial organization, in contrast to the mammalian cortical organization. Third, it is assumed that the interactions between the different neuron types making up an information processing unit within pallium are critical to its role in analyzing information. Finally, it is assumed that increasing axonal length between the neuron sets carrying out this operation impairs its efficacy. Based on these assumptions, I present two main reasons why dinosaur pallium might have been unable to add the equivalent of 200 efficiently functioning cortical areas. First, a nuclear pattern of pallial organization would require increasing distances between the neuron groups corresponding to the separate layers of any given mammalian cortical area, as more sets of nuclei equivalent to a cortical area are interposed between the existing sets, increasing axon length and thereby impairing processing efficiency. Second, because of its nuclear organization, dinosaur pallium could not reduce axon length by folding to bring adjacent areas closer together, as occurs in cerebral cortex.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Mediating role of obesity on the association between disadvantaged neighborhoods and intracortical myelination

We investigated the relationship between neighborhood disadvantage (area deprivation index [ADI]) and intracortical myelination (T1-weighted/T2-weighted ratio at deep to superficial cortical levels), and the potential mediating role of the body mass index (BMI) and perceived stress in 92 adults. Worse ADI was correlated with increased BMI and perceived stress (p's<.05). Non-rotated partial least squares analysis revealed associations between worse ADI and decreased myelination in middle/deep cortex in supramarginal, temporal, and primary motor regions and increased myelination in superficial cortex in medial prefrontal and cingulate regions (p<.001); thus, neighborhood disadvantage may influence the flexibility of information processing involved in reward, emotion regulation, and cognition. Structural equation modelling revealed increased BMI as partially mediating the relationship between worse ADI and observed myelination increases (p=.02). Further, trans-fatty acid intake was correlated with observed myelination increases (p=.03), suggesting the importance of dietary quality. These data further suggest ramifications of neighborhood disadvantage on brain health.

Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity

This review focuses on cytoarchitectonics and receptor architectonics as biological correlates of function and connectivity. It introduces the 3-dimensional cytoarchitectonic probabilistic maps of cortical areas and nuclei of the Julich-Brain Atlas, available at EBRAINS, to study structure-function relationships. The maps are linked to the BigBrain as microanatomical reference model and template space. The siibra software tool suite enables programmatic access to the maps and to receptor architectonic data that are anchored to brain areas. Such cellular and molecular data are tools for studying magnetic resonance connectivity including modeling and simulation. At the end, we highlight perspectives of the Julich-Brain as well as methodological considerations. Thus, microstructural maps as part of a multimodal atlas help elucidate the biological correlates of large-scale networks and brain function with a high level of anatomical detail, which provides a basis to study brains of patients with psychiatric disorders.

Synapses, predictions, and prediction errors: A neocortical computational study of MDD using the temporal memory algorithm of HTM

INTRODUCTION

Synapses and spines play a significant role in major depressive disorder (MDD) pathophysiology, recently highlighted by the rapid antidepressant effect of ketamine and psilocybin. According to the Bayesian brain and interoception perspectives, MDD is formalized as being stuck in affective states constantly predicting negative energy balance. To understand how spines and synapses relate to the predictive function of the neocortex and thus to symptoms, we used the temporal memory (TM), an unsupervised machine-learning algorithm. TM models a single neocortical layer, learns in real-time, and extracts and predicts temporal sequences. TM exhibits neocortical biological features such as sparse firing and continuous online learning using local Hebbian-learning rules.

METHODS

We trained a TM model on random sequences of upper-case alphabetical letters, representing sequences of affective states. To model depression, we progressively destroyed synapses in the TM model and examined how that affected the predictive capacity of the network. We found that the number of predictions decreased non-linearly.

RESULTS

Destroying 50% of the synapses slightly reduced the number of predictions, followed by a marked drop with further destruction. However, reducing the synapses by 25% distinctly dropped the confidence in the predictions. Therefore, even though the network was making accurate predictions, the network was no longer confident about these predictions.

DISCUSSION

These findings explain how interoceptive cortices could be stuck in limited affective states with high prediction error. Connecting ketamine and psilocybin's proposed mechanism of action to depression pathophysiology, the growth of new synapses would allow representing more futuristic predictions with higher confidence. To our knowledge, this is the first study to use the TM model to connect changes happening at synaptic levels to the Bayesian formulation of psychiatric symptomatology. Linking neurobiological abnormalities to symptoms will allow us to understand the mechanisms of treatments and possibly, develop new ones.

Are the Anterior and Mid-Cingulate Cortices Distinct in Rodents?

The prefrontal cortex (PFC) is involved in cognitive control, emotional regulation, and motivation. In this Perspective article, we discuss the nomenclature of the subdivisions of the medial prefrontal cortex (mPFC), since the anatomical definitions of the PFC subregions have been confusing. Although the mid-cingulate cortex (MCC) and anterior cingulate cortex (ACC) have distinct features in humans and non-human primates, it is unclear whether these regions serve different functions in rodents. Accurate mapping of the cingulate cortex in rodents is important to allow comparisons between species. A proposed change in the nomenclature of the rodent cingulate cortex to anterior cingulate cortex (aCg) and mid-cingulate cortex (mCg) is presented based on our data. We show evidence for distinct cortico-cortical projections from the aCg and mCg to the PrL. The aCg→PrL neurons were abundant in layer VI, while the mCg→PrL neurons were mainly distributed in layer V. In addition, a sex difference was detected in the aCg, with males having a higher proportion of layer V neurons projecting to the PrL than females. Based on this laminar distribution and considering that layer V and VI send efferent projections to different brain areas such as the brain stem, amygdala, and thalamus, we propose that aCg and mCg need to be considered separate entities for future rodent studies. This new definition will put into perspective the role of rodent cingulate cortex in diverse aspects of cognition and facilitate interspecies comparisons in cingulate cortex research.

VIP-Expressing GABAergic Neurons: Disinhibitory vs. Inhibitory Motif and Its Role in Communication Across Neocortical Areas

GABAergic neurons play a crucial role in shaping cortical activity. Even though GABAergic neurons constitute a small fraction of cortical neurons, their peculiar morphology and functional properties make them an intriguing and challenging task to study. Here, we review the basic anatomical features, the circuit properties, and the possible role in the relevant behavioral task of a subclass of GABAergic neurons that express vasoactive intestinal polypeptide (VIP). These studies were performed using transgenic mice in which the VIP-expressing neurons can be recognized using fluorescent proteins and optogenetic manipulation to control (or regulate) their electrical activity. Cortical VIP-expressing neurons are more abundant in superficial cortical layers than other cortical layers, where they are mainly studied. Optogenetic and paired recordings performed in ex vivo cortical preparations show that VIP-expressing neurons mainly exert their inhibitory effect onto somatostatin-expressing (SOM) inhibitory neurons, leading to a disinhibitory effect onto excitatory pyramidal neurons. However, this subclass of GABAergic neurons also releases neurotransmitters onto other GABAergic and non-GABAergic neurons, suggesting other possible circuit roles than a disinhibitory effect. The heterogeneity of VIP-expressing neurons also suggests their involvement and recruitment during different functions via the inhibition/disinhibition of GABAergic and non-GABAergic neurons locally and distally, depending on the specific local circuit in which they are embedded, with potential effects on the behavioral states of the animal. Although VIP-expressing neurons represent only a tiny fraction of GABAergic inhibitory neurons in the cortex, these neurons’ selective activation/inactivation could produce a relevant behavioral effect in the animal. Regardless of the increasing finding and discoveries on this subclass of GABAergic neurons, there is still a lot of missing information, and more studies should be done to unveil their role at the circuit and behavior level in different cortical layers and across different neocortical areas.

Current findings and perspectives on aberrant neural oscillations in schizophrenia

There is now consistent evidence that neural oscillation at low- and high-frequencies constitute an important aspect of the pathophysiology of schizophrenia. Specifically, impaired rhythmic activity may underlie the deficit to generate coherent cognition and behavior, leading to the characteristic symptoms of psychosis and cognitive deficits. Importantly, the generating mechanisms of neural oscillations are relatively well-understood and thus enable the targeted search for the underlying circuit impairments and novel treatment targets. In the following review, we will summarize and assess the evidence for aberrant rhythmic activity in schizophrenia through evaluating studies that have utilized Electro/Magnetoencephalography to examine neural oscillations during sensory and cognitive tasks as well as during resting-state measurements. These data will be linked to current evidence from post-mortem, neuroimaging, genetics, and animal models that have implicated deficits in GABAergic interneurons and glutamatergic neurotransmission in oscillatory deficits in schizophrenia. Finally, we will highlight methodological and analytical challenges as well as provide recommendations for future research.

Apical amplification-a cellular mechanism of conscious perception?

We present a theoretical view of the cellular foundations for network-level processes involved in producing our conscious experience. Inputs to apical synapses in layer 1 of a large subset of neocortical cells are summed at an integration zone near the top of their apical trunk. These inputs come from diverse sources and provide a context within which the transmission of information abstracted from sensory input to their basal and perisomatic synapses can be amplified when relevant. We argue that apical amplification enables conscious perceptual experience and makes it more flexible, and thus more adaptive, by being sensitive to context. Apical amplification provides a possible mechanism for recurrent processing theory that avoids strong loops. It makes the broadcasting hypothesized by global neuronal workspace theories feasible while preserving the distinct contributions of the individual cells receiving the broadcast. It also provides mechanisms that contribute to the holistic aspects of integrated information theory. As apical amplification is highly dependent on cholinergic, aminergic, and other neuromodulators, it relates the specific contents of conscious experience to global mental states and to fluctuations in arousal when awake. We conclude that apical dendrites provide a cellular mechanism for the context-sensitive selective amplification that is a cardinal prerequisite of conscious perception.

Advances in resting state fMRI acquisitions for functional connectomics

Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

Cortical layer-specific modulation of neuronal activity after sensory deprivation due to spinal cord injury

Abstract

Cortical areas have the capacity of large‐scale reorganization following sensory deafferentation. However, it remains unclear whether this phenomenon is a unique process that homogeneously affects the entire deprived cortical region or whether it is susceptible to changes depending on neuronal networks across distinct cortical layers. Here, we studied how the local circuitry within each layer of the deafferented cortex forms the basis for neuroplastic changes after immediate thoracic spinal cord injury (SCI) in anaesthetized rats. In vivo electrophysiological recordings from deafferented hindlimb somatosensory cortex showed that SCI induces layer‐specific changes mediating evoked and spontaneous activity. In supragranular layer 2/3, SCI increased gamma oscillations and the ability of these neurons to initiate up‐states during spontaneous activity, suggesting an altered corticocortical network and/or intrinsic properties that may serve to maintain the excitability of the cortical column after deafferentation. On the other hand, SCI enhanced the infragranular layers’ ability to integrate evoked sensory inputs leading to increased and faster neuronal responses. Delayed evoked response onsets were also observed in layer 5/6, suggesting alterations in thalamocortical connectivity. Altogether, our data indicate that SCI immediately modifies the local circuitry within the deafferented cortex allowing supragranular layers to better integrate spontaneous corticocortical information, thus modifying column excitability, and infragranular layers to better integrate evoked sensory inputs to preserve subcortical outputs. These layer‐specific neuronal changes may guide the long‐term alterations in neuronal excitability and plasticity associated with the rearrangements of somatosensory networks and the appearance of central sensory pathologies usually associated with spinal cord injury.

Key points

Sensory stimulation of forelimb produces cortical evoked responses in the somatosensory hindlimb cortex in a layer‐dependent manner.

Spinal cord injury favours the input statistics of corticocortical connections between intact and deafferented cortices.

After spinal cord injury supragranular layers exhibit better integration of spontaneous corticocortical information while infragranular layers exhibit better integration of evoked sensory stimulation.

Cortical reorganization is a layer‐specific phenomenon.

Topographical and laminar distribution of audiovisual processing within human planum temporale

The brain is capable of integrating signals from multiple sensory modalities. Such multisensory integration can occur in areas that are commonly considered unisensory, such as planum temporale (PT) representing the auditory association cortex. However, the roles of different afferents (feedforward vs. feedback) to PT in multisensory processing are not well understood. Our study aims to understand that by examining laminar activity patterns in different topographical subfields of human PT under unimodal and multisensory stimuli. To this end, we adopted an advanced mesoscopic (sub-millimeter) fMRI methodology at 7 T by acquiring BOLD (blood-oxygen-level-dependent contrast, which has higher sensitivity) and VAPER (integrated blood volume and perfusion contrast, which has superior laminar specificity) signal concurrently, and performed all analyses in native fMRI space benefiting from an identical acquisition between functional and anatomical images. We found a division of function between visual and auditory processing in PT and distinct feedback mechanisms in different subareas. Specifically, anterior PT was activated more by auditory inputs and received feedback modulation in superficial layers. This feedback depended on task performance and likely arose from top-down influences from higher-order multimodal areas. In contrast, posterior PT was preferentially activated by visual inputs and received visual feedback in both superficial and deep layers, which is likely projected directly from the early visual cortex. Together, these findings provide novel insights into the mechanism of multisensory interaction in human PT at the mesoscopic spatial scale.

Linking cortical circuit models to human cognition with laminar fMRI

Laboratory animal research has provided significant knowledge into the function of cortical circuits at the laminar level, which has yet to be fully leveraged towards insights about human brain function on a similar spatiotemporal scale. The use of functional magnetic resonance imaging (fMRI) in conjunction with neural models provides new opportunities to gain important insights from current knowledge. During the last five years, human studies have demonstrated the value of high-resolution fMRI to study laminar-specific activity in the human brain. This is mostly performed at ultra-high-field strengths (≥ 7 T) and is known as laminar fMRI. Advancements in laminar fMRI are beginning to open new possibilities for studying questions in basic cognitive neuroscience. In this paper, we first review recent methodological advances in laminar fMRI and describe recent human laminar fMRI studies. Then, we discuss how the use of laminar fMRI can help bridge the gap between cortical circuit models and human cognition.

Creative Destruction: A Basic Computational Model of Cortical Layer Formation

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

Mechanism of action of a diterpene alkaloid hypaconitine on cytotoxicity and inhibitory effect of BAPTA-AM in HCN-2 neuronal cells

Hypaconitine, a neuromuscular blocker, is a diterpene alkaloid found in the root of Aconitum carmichaelii. Although hypaconitine was shown to affect various physiological responses in neurological models, the effect of hypaconitine on cell viability and the mechanism of its action of Ca2+ handling is elusive in cortical neurons. This study examined whether hypaconitine altered viability and Ca2+ signalling in HCN-2 neuronal cell lines. Cell viability was measured by the cell proliferation reagent (WST-1). Cytosolic Ca2+ concentrations [Ca2+ ]i was measured by the Ca2+ -sensitive fluorescent dye fura-2. In HCN-2 cells, hypaconitine (10-50 μmol/L) induced cytotoxicity and [Ca2+ ]i rises in a concentration-dependent manner. Removal of extracellular Ca2+ partially reduced the hypaconitine's effect on [Ca2+ ]i rises. Furthermore, chelation of cytosolic Ca2+ with BAPTA-AM reduced hypaconitine's cytotoxicity. In Ca2+ -containing medium, hypaconitine-induced Ca2+ entry was inhibited by modulators (2-APB and SKF96365) of store-operated Ca2+ channels and a protein kinase C (PKC) inhibitor (GF109203X). Hypaconitine induced Mn2+ influx indirectly suggesting that hypaconitine evoked Ca2+ entry. In Ca2+ -free medium, treatment with the endoplasmic reticulum Ca2+ pump inhibitor thapsigargin abolished hypaconitine-induced [Ca2+ ]i rises. Conversely, treatment with hypaconitine inhibited thapsigargin-induced [Ca2+ ]i rises. However, inhibition of phospholipase C (PLC) with U73122 did not inhibit hypaconitine-induced [Ca2+ ]i rises. Together, hypaconitine caused cytotoxicity that was linked to preceding [Ca2+ ]i rises by Ca2+ influx via store-operated Ca2+ entry involved PKC regulation and evoking PLC-independent Ca2+ release from the endoplasmic reticulum. Because BAPTA-AM loading only partially reversed hypaconitine-induced cell death, it suggests that hypaconitine induced a second Ca2+ -independent cytotoxicity in HCN-2 cells.

Challenges in Modeling Human Neural Circuit Formation via Brain Organoid Technology

Human brain organoids are three-dimensional self-organizing tissues induced from pluripotent cells that recapitulate some aspects of early development and some of the early structure of the human brain in vitro. Brain organoids consist of neural lineage cells, such as neural stem/precursor cells, neurons, astrocytes and oligodendrocytes. Additionally, brain organoids contain fluid-filled ventricle-like structures surrounded by a ventricular/subventricular (VZ/SVZ) zone-like layer of neural stem cells (NSCs). These NSCs give rise to neurons, which form multiple outer layers. Since these structures resemble some aspects of structural arrangements in the developing human brain, organoid technology has attracted great interest in the research fields of human brain development and disease modeling. Developmental brain disorders have been intensely studied through the use of human brain organoids. Relatively early steps in human brain development, such as differentiation and migration, have also been studied. However, research on neural circuit formation with brain organoids has just recently began. In this review, we summarize the current challenges in studying neural circuit formation with organoids and discuss future perspectives.

Advances in 3D neural, vascular and neurovascular models for drug testing and regenerative medicine

Clinical trials continue to fall short regarding drugs to effectively treat brain-affecting diseases. Although there are many causes of these shortcomings, the most relevant are the inability of most therapeutic agents to cross the blood-brain barrier (BBB) and the failure to translate effects from animal models to patients. In this review, we analyze the most recent developments in BBB, neural, and neurovascular models, analyzing their impact on the drug development process by considering their quantitative and phenotypical characterization. We offer a perspective of the state-of-the-art of the models that could revolutionize the pharmaceutical industry.

Layer-specific serotonergic induction of long-term depression in the prefrontal cortex of rats

Layer 2/3 pyramidal neurons (L2/3 PyNs) of the cortex extend their basal dendrites near the soma and as apical dendritic tufts in layer 1, which mainly receive feedforward and feedback inputs, respectively. It is suggested that neuromodulators such as serotonin and acetylcholine may regulate the information flow between brain structures depending on the brain state. However, little is known about the dendritic compartment-specific induction of synaptic transmission in single PyNs. Here, we studied layer-specific serotonergic and cholinergic induction of long-term synaptic plasticity in L2/3 PyNs of the agranular insular cortex, a lateral component of the orbitofrontal cortex. Using FM1-43 dye unloading, we verified that local electrical stimulation to layers 1 (L1) and 3 (L3) activated axon terminals mostly located in L1 and perisomatic area (L2/3). Independent and AMPA receptor-mediated excitatory postsynaptic potential was evoked by local electrical stimulation of either L1 or L3. Application of serotonin (5-HT, 10 μM) induced activity-dependent long-term depression (LTD) in L2/3 but not in L1 inputs. LTD induced by 5-HT was blocked by the 5-HT₂ receptor antagonist ketanserin, an NMDA receptor antagonist and by intracellular Ca²⁺ chelation. The 5-HT₂ receptor agonist α-me-5-HT mimicked the LTD induced by 5-HT. However, the application of carbachol induced muscarinic receptor-dependent LTD in both inputs. The differential layer-specific induction of LTD by neuromodulators might play an important role in information processing mechanism of the prefrontal cortex.

The laminar pattern of resting state in human cerebral cortex

Resting state functional Magnetic Resonance Imaging (RS-fMRI) provides the means to measure neuronal activity. One of the most commonly used methods to explore the RS-fMRI signal is the Probabilistic Independent Component Analysis (PICA). PICA allows to depict brain functional connectivity (FC) networks. Yet most of the IC maps obtained with this method do not represent any particular FC network. Consequently, those IC maps are classified as artifacts or noise of an unknown source. We hypothesized that the unexplained RS-fMRI signal patterns that are picked up by the PICA can be related to the differences in oxygen metabolism and blood flow in cortical layers. This study aimed at (1) providing preliminary evidence to the effects of laminar organization of neocortex on the RS-fMRI signal, and (2) evaluating the application of laminar maps to aid the classification of IC maps. We created laminar maps 1-4 that depict relative cortical thickness of layers IV and VI. Our data show that the RS-fMRI signal is significantly related to the relative thickness of the cortical layer VI but not layer IV. Importantly, the laminar maps 1-4 overlap with four separate IC maps. Thus, the laminar maps 1-4 improve classification and interpretation of the IC maps. Moreover, the laminar maps 1-4 may be considered as FC networks that are the bridging piece between particular cognitive functions. Together, these data provide preliminary evidence to the fundamental questions about the role of cortical layering in the RS-fMRI signal and brain FC networks.

Systematic modelling of the development of laminar projection origins in the cerebral cortex: Interactions of spatio-temporal patterns of neurogenesis and cellular heterogeneity

The architectonic type principle conceptualizes structural connections between brain areas in terms of the relative architectonic differentiation of connected areas. It has previously been shown that spatio-temporal interactions between the time and place of neurogenesis could underlie multiple features of empirical mammalian connectomes, such as projection existence and the distribution of projection strengths. However, so far no mechanistic explanation for the emergence of typically observed laminar patterns of projection origins and terminations has been tested. Here, we expand an in silico model of the developing cortical sheet to explore which factors could potentially constrain the development of laminar projection patterns. We show that manipulations which rely solely on spatio-temporal interactions, namely the relative density of laminar compartments, a delay in the neurogenesis of infragranular layers relative to layer 1, and a delay in the neurogenesis of supragranular layers relative to infragranular layers, do not result in the striking correlation between supragranular contribution to projections and the relative differentiation of areas that is typically observed in the mammalian cortex. In contrast, we find that if we introduce systematic variation in cell-intrinsic properties, coupling them with architectonic differentiation, the resulting laminar projection patterns closely mirror the empirically observed patterns. We also find that the spatio-temporal interactions posited to occur during neurogenesis are necessary for the formation of the characteristic laminar patterns. Hence, our results indicate that the specification of the laminar patterns of projection origins may result from systematic variation in a number of cell-intrinsic properties, superimposed on the previously identified spatio-temporal interactions which are sufficient for the emergence of the architectonic type principle on the level of inter-areal connectivity in silico.

Recurrent Processing Drives Perceptual Plasticity

Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high-field (7T) functional imaging at sub-millimeter resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. We demonstrate that learning alters orientation-specific representations in superficial rather than middle or deeper V1 layers, consistent with recurrent plasticity mechanisms via horizontal connections. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro-circuits of experience-dependent plasticity.

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Discrimination training alters orientation representations in superficial V1 layers

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Orientation-specific V1 plasticity is independent of task context

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Discrimination training alters orientation representations in middle IPS layers

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Learning enhances feedforward connectivity from visual to parietal cortex

Cellular Mechanisms of Conscious Processing

Recent breakthroughs in neurobiology indicate that the time is ripe to understand how cellular-level mechanisms are related to conscious experience. Here, we highlight the biophysical properties of pyramidal cells, which allow them to act as gates that control the evolution of global activation patterns. In conscious states, this cellular mechanism enables complex sustained dynamics within the thalamocortical system, whereas during unconscious states, such signal propagation is prohibited. We suggest that the hallmark of conscious processing is the flexible integration of bottom-up and top-down data streams at the cellular level. This cellular integration mechanism provides the foundation for Dendritic Information Theory, a novel neurobiological theory of consciousness.

Perinatal exposure of rats to the HIV drug efavirenz affects medial prefrontal cortex cytoarchitecture

Efavirenz (EFV) is used for antiretroviral treatment of HIV infection, and successfully inhibits viral replication and mother-to-child transmission of HIV during pregnancy and childbirth. Unfortunately, the drug induces neuropsychiatric symptoms such as anxiety and depressed mood and potentially affects cognitive performance. EFV acts on, among others, the serotonin transporter and serotonin receptors that are expressed in the developing brain. Yet, how perinatal EFV exposure affects brain cytoarchitecture remains unclear. Here, we exposed pregnant and lactating rats to EFV, and examined in the medial prefrontal cortex (mPFC) of their adult offspring the effects of the maternal EFV exposure on cortical architecture. We observed a significant decrease in the number of cells, mainly mature neurons, in the infra/prelimbic and cingulate cortices of adult offspring. Next, we found an altered cortical cytoarchitecture characterized by a significant reduction in deep- and superficial-layer cells. This was accompanied by a sharp increase in programmed cell death, as we identified a significantly higher number of cleaved Caspase-3-positive cells. Finally, the serotonergic and dopaminergic innervation of the mPFC subdomains was increased. Thus, the perinatal exposure to EFV provoked in the mPFC of adult offspring cell death, significant changes in cytoarchitecture, and disturbances in serotonergic and dopaminergic innervation. Our results are important in the light of EFV treatment of HIV-positive pregnant women, and its effect on brain development and cognitive behavior.

Perspective on the Multiple Pathways to Changing Brain States

In this review article, we highlight several disparate ideas that are linked to changes in brain state (i.e., sleep to arousal, Down to Up, synchronized to de-synchronized). In any discussion of the brain state, we propose that the cortical pyramidal neuron has a central position. EEG recordings, which typically assess brain state, predominantly reflect the activity of cortical pyramidal neurons. This means that the dominant rhythmic activity that characterizes a particular brain state ultimately has to manifest globally across the pyramidal neuron population. During state transitions, it is the long-range connectivity of these neurons that broadcast the resultant changes in activity to many subcortical targets. Structures like the thalamus, brainstem/hypothalamic neuromodulatory systems, and respiratory systems can also strongly influence brain state, and for many decades we have been uncovering bidirectional pathways that link these structures to state changes in the cerebral cortex. More recently, movement and active behaviors have emerged as powerful drivers of state changes. Each of these systems involve different circuits distributed across the brain. Yet, for a system-wide change in brain state, there must be a collaboration between these circuits that reflects and perhaps triggers the transition between brain states. As we expand our understanding of how brain state changes, our current challenge is to understand how these diverse sets of circuits and pathways interact to produce the changes observed in cortical pyramidal neurons.

Long-term beneficial effects of hematopoietic growth factors on brain repair in the chronic phase of severe traumatic brain injury

Severe traumatic brain injury (TBI) is the major cause of long-term, even life-long disability and cognitive impairments in young adults. The lack of therapeutic approaches to improve recovery in the chronic phase of severe TBI is a big challenge to the medical research field. Using a single severe TBI model in young adult mice, this study examined the restorative efficacy of two hematopoietic growth factors, stem cell factor (SCF) and granulocyte colony-stimulating factor (G-CSF), on brain repair in the chronic phase of TBI. SCF and G-CSF alone or combination (SCF + G-CSF) treatment was administered at 3 months post-TBI. Functional recovery was evaluated by neurobehavioral tests during the period of 21 weeks after treatment. Neuropathology was examined 22 weeks after treatment. We observed that severe TBI caused persistent impairments in spatial learning/memory and somatosensory-motor function, long-term and widespread neuropathology, including dendritic reduction, decrease and overgrowth of axons, over-generated excitatory synapses, and demyelination in the cortex, hippocampus and striatum. SCF, G-CSF, and SCF + G-CSF treatments ameliorated severe TBI-induced widespread neuropathology. SCF + G-CSF treatment showed superior efficacy in improving long-term functional outcome, enhancing neural plasticity, rebalancing neural structure networks disturbed by severe TBI, and promoting remyelination. These novel findings demonstrate the therapeutic potential of SCF and G-CSF in enhancing recovery in the chronic phase of severe TBI .

The Reeler Mouse: A Translational Model of Human Neurological Conditions, or Simply a Good Tool for Better Understanding Neurodevelopment?

The first description of the Reeler mutation in mouse dates to more than fifty years ago, and later, its causative gene (reln) was discovered in mouse, and its human orthologue (RELN) was demonstrated to be causative of lissencephaly 2 (LIS2) and about 20% of the cases of autosomal-dominant lateral temporal epilepsy (ADLTE). In both human and mice, the gene encodes for a glycoprotein referred to as reelin (Reln) that plays a primary function in neuronal migration during development and synaptic stabilization in adulthood. Besides LIS2 and ADLTE, RELN and/or other genes coding for the proteins of the Reln intracellular cascade have been associated substantially to other conditions such as spinocerebellar ataxia type 7 and 37, VLDLR-associated cerebellar hypoplasia, PAFAH1B1-associated lissencephaly, autism, and schizophrenia. According to their modalities of inheritances and with significant differences among each other, these neuropsychiatric disorders can be modeled in the homozygous (reln^−/−) or heterozygous (reln^+/−) Reeler mouse. The worth of these mice as translational models is discussed, with focus on their construct and face validity. Description of face validity, i.e., the resemblance of phenotypes between the two species, centers onto the histological, neurochemical, and functional observations in the cerebral cortex, hippocampus, and cerebellum of Reeler mice and their human counterparts.

Scene Representations Conveyed by Cortical Feedback to Early Visual Cortex Can Be Described by Line Drawings

Human behavior is dependent on the ability of neuronal circuits to predict the outside world. Neuronal circuits in early visual areas make these predictions based on internal models that are delivered via non-feedforward connections. Despite our extensive knowledge of the feedforward sensory features that drive cortical neurons, we have a limited grasp on the structure of the brain's internal models. Progress in neuroscience therefore depends on our ability to replicate the models that the brain creates internally. Here we record human fMRI data while presenting partially occluded visual scenes. Visual occlusion allows us to experimentally control sensory input to subregions of visual cortex while internal models continue to influence activity in these regions. Because the observed activity is dependent on internal models, but not on sensory input, we have the opportunity to map visual features conveyed by the brain's internal models. Our results show that activity related to internal models in early visual cortex are more related to scene-specific features than to categorical or depth features. We further demonstrate that behavioral line drawings provide a good description of internal model structure representing scene-specific features. These findings extend our understanding of internal models, showing that line drawings provide a window into our brains' internal models of vision.

SIGNIFICANCE STATEMENT We find that fMRI activity patterns corresponding to occluded visual information in early visual cortex fill in scene-specific features. Line drawings of the missing scene information correlate with our recorded activity patterns, and thus to internal models. Despite our extensive knowledge of the sensory features that drive cortical neurons, we have a limited grasp on the structure of our brains' internal models. These results therefore constitute an advance to the field of neuroscience by extending our knowledge about the models that our brains construct to efficiently represent and predict the world. Moreover, they link a behavioral measure to these internal models, which play an active role in many components of human behavior, including visual predictions, action planning, and decision making.

Cracking the Function of Layers in the Sensory Cortex

Understanding how cortical activity generates sensory perceptions requires a detailed dissection of the function of cortical layers. Despite our relatively extensive knowledge of their anatomy and wiring, we have a limited grasp of what each layer contributes to cortical computation. We need to develop a theory of cortical function that is rooted solidly in each layer's component cell types and fine circuit architecture and produces predictions that can be validated by specific perturbations. Here we briefly review the progress toward such a theory and suggest an experimental road map toward this goal. We discuss new methods for the all-optical interrogation of cortical layers, for correlating in vivo function with precise identification of transcriptional cell type, and for mapping local and long-range activity in vivo with synaptic resolution. The new technologies that can crack the function of cortical layers are finally on the immediate horizon.

Myelin and Modeling: Bootstrapping Cortical Microcircuits

Histological studies of myelin-stained sectioned cadaver brain and in vivo myelin-weighted magnetic resonance imaging (MRI) show that the cerebral cortex is organized into cortical areas with generally well-defined boundaries, which have consistent internal patterns of myelination. The process of myelination is largely driven by neural experience, in which the axonal passage of action potentials stimulates neighboring oligodendrocytes to perform their task. This bootstrapping process, such that the traffic of action potentials facilitates increased traffic, suggests the hypothesis that the specific pattern of myelination (myeloarchitecture) in each cortical area reveals the principal cortical microcircuits required for the function of that area. If this idea is correct, the observable sequential maturation of specific brain areas can provide evidence for models of the stages of cognitive development.