Axon topography of layer 6 spiny cells to orientation map in the primary visual cortex of the cat (area 18)

Towards a mesoscale physical modeling framework for stereotactic-EEG recordings

Objective.Stereotactic-electroencephalography (SEEG) and scalp EEG recordings can be modeled using mesoscale neural mass population models (NMMs). However, the relationship between those mathematical models and the physics of the measurements is unclear. In addition, it is challenging to represent SEEG data by combining NMMs and volume conductor models due to the intermediate spatial scale represented by these measurements.Approach.We provide a framework combining the multi-compartmental modeling formalism and a detailed geometrical model to simulate the transmembrane currents that appear in layer 3, 5 and 6 pyramidal cells due to a synaptic input. With this approach, it is possible to realistically simulate the current source density (CSD) depth profile inside a cortical patch due to inputs localized into a single cortical layer and the induced voltage measured by two SEEG contacts using a volume conductor model. Based on this approach, we built a framework to connect the activity of a NMM with a volume conductor model and we simulated an example of SEEG signal as a proof of concept.Main results.CSD depends strongly on the distribution of the synaptic inputs onto the different cortical layers and the equivalent current dipole strengths display substantial differences (of up to a factor of four in magnitude in our example). Thus, the inputs coming from different neural populations do not contribute equally to the electrophysiological recordings. A direct consequence of this is that the raw output of NMMs is not a good proxy for electrical recordings. We also show that the simplest CSD model that can accurately reproduce SEEG measurements can be constructed from discrete monopolar sources (one per cortical layer).Significance.Our results highlight the importance of including a physical model in NMMs to represent measurements. We provide a framework connecting microscale neuron models with the neural mass formalism and with physical models of the measurement process that can improve the accuracy of predicted electrophysiological recordings.

Form, synapses and orientation topography of a new cell type in layer 6 of the cat’s primary visual cortex

Here we report the morpho-functional features of a novel type of deep-layer neuron. The neuron was selected from a large pool of intracellularly labelled cells based on the large cell body, numerous spine-free dendrites with an overall interneuron morphology. However, the axon gave off long-range axons up to 2.8 mm from the parent soma in layers 5/6 before entering the white matter. The boutons were uniformly distributed along the axon without forming distinct clusters. Dendritic length, surface area and volume values were at least 3 times larger than any known cortical neuron types with the exception of giant pyramidal cells of layer 5. Electron microscopy of the boutons revealed that they targeted dendritic spines (78%) and less frequently dendritic shafts (22%). Nearly half of the postsynaptic dendrites were immunopositive to GABA. Superimposing the axonal field on the orientation map obtained with optical imaging showed a preponderance of boutons to cross-orientations (38%) and an equal representation of iso- and oblique orientations (31%). The results suggest an integrating role for the layer 6 stellate neuron which projects to a functionally broad range of neurons in the deep cortical layers and to other cortical and/or subcortical regions.

Revisiting horizontal connectivity rules in V1: from like-to-like towards like-to-all

Horizontal connections in the primary visual cortex of carnivores, ungulates and primates organize on a near-regular lattice. Given the similar length scale for the regularity found in cortical orientation maps, the currently accepted theoretical standpoint is that these maps are underpinned by a like-to-like connectivity rule: horizontal axons connect preferentially to neurons with similar preferred orientation. However, there is reason to doubt the rule's explanatory power, since a growing number of quantitative studies show that the like-to-like connectivity preference and bias mostly observed at short-range scale, are highly variable on a neuron-to-neuron level and depend on the origin of the presynaptic neuron. Despite the wide availability of published data, the accepted model of visual processing has never been revised. Here, we review three lines of independent evidence supporting a much-needed revision of the like-to-like connectivity rule, ranging from anatomy to population functional measures, computational models and to theoretical approaches. We advocate an alternative, distance-dependent connectivity rule that is consistent with new structural and functional evidence: from like-to-like bias at short horizontal distance to like-to-all at long horizontal distance. This generic rule accounts for the observed high heterogeneity in interactions between the orientation and retinotopic domains, that we argue is necessary to process non-trivial stimuli in a task-dependent manner.

Cortical Output Is Gated by Horizontally Projecting Neurons in the Deep Layers

Pyramidal tract neurons (PTs) represent the major output cell type of the mammalian neocortex. Here, we report the origins of the PTs’ ability to respond to a broad range of stimuli with onset latencies that rival or even precede those of their intracortical input neurons. We find that neurons with extensive horizontally projecting axons cluster around the deep-layer terminal fields of primary thalamocortical axons. The strategic location of these corticocortical neurons results in high convergence of thalamocortical inputs, which drive reliable sensory-evoked responses that precede those in other excitatory cell types. The resultant fast and horizontal stream of excitation provides PTs throughout the cortical area with input that acts to amplify additional inputs from thalamocortical and other intracortical populations. The fast onsets and broadly tuned characteristics of PT responses hence reflect a gating mechanism in the deep layers, which assures that sensory-evoked input can be reliably transformed into cortical output.

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Simulations predict in vivo responses for major output cell type of the neocortex

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Simulations reveal strategy how to test the origins of cortical output empirically

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Manipulations confirm that deep-layer corticocortical neurons gate cortical output

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Gating of cortical output originates from deep-layer thalamocortical input stratum

Altered social behavior in mice carrying a cortical Foxp2 deletion

Genetic disruptions of the forkhead box transcription factor FOXP2 in humans cause an autosomal-dominant speech and language disorder. While FOXP2 expression pattern are highly conserved, its role in specific brain areas for mammalian social behaviors remains largely unknown. Here we studied mice carrying a homozygous cortical Foxp2 deletion. The postnatal development and gross morphological architecture of mutant mice was indistinguishable from wildtype (WT) littermates. Unbiased behavioral profiling of adult mice revealed abnormalities in approach behavior towards conspecifics as well as in the reciprocal responses of WT interaction partners. Furthermore mutant mice showed alterations in acoustical parameters of ultrasonic vocalizations, which also differed in function of the social context. Cell type-specific gene expression profiling of cortical pyramidal neurons revealed aberrant regulation of genes involved in social behavior. In particular Foxp2 mutants showed the downregulation of Mint2 (Apba2), a gene involved in approach behavior in mice and autism spectrum disorder in humans. Taken together these data demonstrate that cortical Foxp2 is required for normal social behaviors in mice.

What do we know about laminar connectivity?

In this brief review, I attempt an overview of the main components of anatomical laminar-level connectivity. These are: extrinsic outputs, excitatory and inhibitory intrinsic connectivity, and intrinsic inputs. Supporting data are biased from the visual system of nonhuman primates (NHPs), but I have drawn as much as possible from a broader span in order to treat the important issue of area-specific variability. In a second part, I briefly discuss laminar connectivity in the context of network organization (feedforward/feedback cortical connections, and the major types of corticothalamic connections). I also point out anatomical issues in need of clarification, including more systematic, whole brain coverage of tracer injections; more data on anterogradely labeled terminations; more complete, area-specific quantitative data about projection neurons, and quantitative data on terminal density and convergence. Postsynaptic targets are largely unknown, but their identification is essential for understanding the finer analysis and principles of laminar patterns. Laminar resolution MRI offers a promising new tool for exploring laminar connectivity: it is potentially fast and macro-scale, and allows for repeated investigation under different stimulus conditions. Conversely, anatomical resolution, although detailed beyond the current level of MRI visualization, offers a rich trove for experimental design and interpretation of fMRI activation patterns.