Polyneuronal innervation of spiny stellate neurons in cat visual cortex

Network resonance and the auditory steady state response

The auditory steady state response (ASSR) arises when periodic sounds evoke stable responses in auditory networks that reflect the acoustic characteristics of the stimuli, such as the amplitude of the sound envelope. Larger for some stimulus rates than others, the ASSR in the human electroencephalogram (EEG) is notably maximal for sounds modulated in amplitude at 40 Hz. To investigate the local circuit underpinnings of the large ASSR to 40 Hz amplitude-modulated (AM) sounds, we acquired skull EEG and local field potential (LFP) recordings from primary auditory cortex (A1) in the rat during the presentation of 20, 30, 40, 50, and 80 Hz AM tones. 40 Hz AM tones elicited the largest ASSR from the EEG acquired above auditory cortex and the LFP acquired from each cortical layer in A1. The large ASSR in the EEG to 40 Hz AM tones was not due to larger instantaneous amplitude of the signals or to greater phase alignment of the LFP across the cortical layers. Instead, it resulted from decreased latency variability (or enhanced temporal consistency) of the 40 Hz response. Statistical models indicate the EEG signal was best predicted by LFPs in either the most superficial or deep cortical layers, suggesting deep layer coordinators of the ASSR. Overall, our results indicate that the recruitment of non-uniform but more temporally consistent responses across A1 layers underlie the larger ASSR to amplitude-modulated tones at 40 Hz.

Variation and convergence in the morpho-functional properties of the mammalian neocortex

Man's natural inclination to classify and hierarchize the living world has prompted neurophysiologists to explore possible differences in brain organisation between mammals, with the aim of understanding the diversity of their behavioural repertoires. But what really distinguishes the human brain from that of a platypus, an opossum or a rodent? In this review, we compare the structural and electrical properties of neocortical neurons in the main mammalian radiations and examine their impact on the functioning of the networks they form. We discuss variations in overall brain size, number of neurons, length of their dendritic trees and density of spines, acknowledging their increase in humans as in most large-brained species. Our comparative analysis also highlights a remarkable consistency, particularly pronounced in marsupial and placental mammals, in the cell typology, intrinsic and synaptic electrical properties of pyramidal neuron subtypes, and in their organisation into functional circuits. These shared cellular and network characteristics contribute to the emergence of strikingly similar large-scale physiological and pathological brain dynamics across a wide range of species. These findings support the existence of a core set of neural principles and processes conserved throughout mammalian evolution, from which a number of species-specific adaptations appear, likely allowing distinct functional needs to be met in a variety of environmental contexts.

Multisensory-inspired modeling and neural correlates for two key binocular interactions

Most binocular vision models assume that the two eyes sum incompletely. However, some facilitatory cortical neurons fire for only one eye, but amplify their firing rates if both eyes are stimulated. These 'binocular gate' neurons closely resemble subthreshold multisensory neurons. Binocular amplification for binocular gate neurons follows a power law, with a compressive exponent. Unexpectedly, this rule also applies to facilitatory true binocular neurons; although driven by either eye, binocular neurons are well modeled as gated amplifiers of their strongest monocular response, if both eyes are stimulated. Psychophysical data follows the same power law as the neural data, with a similar exponent; binocular contrast sensitivity can be modeled as a gated amplification of the more sensitive eye. These results resemble gated amplification phenomena in multisensory integration, and other non-driving modulatory interactions that affect sensory processing. Models of incomplete summation seem unnecessary for V1 facilitatory neurons or contrast sensitivity. However, binocular combination of clearly visible monocular stimuli follows Schrödinger's nonlinear magnitude-weighted average. We find that putatively suppressive binocular neurons closely follow Schrödinger's equation. Similar suppressive multisensory neurons are well documented but seldom studied. Facilitatory binocular neurons and mildly suppressive binocular neurons are likely neural correlates of binocular sensitivity and binocular appearance respectively.

Nanoscale analysis of functionally diverse glutamatergic synapses in the neocortex reveals input and layer-specific organization

Discovery of synaptic nanostructures suggests a molecular logic for the flexibility of synaptic function. We still have little understanding of how functionally diverse synapses in the brain organize their nanoarchitecture due to challenges associated with super-resolution imaging in complex brain tissue. Here, we characterized single-domain camelid nanobodies for the 3D quantitative multiplex imaging of synaptic nano-organization in 6 µm brain cryosections using STED nanoscopy. We focused on thalamocortical (TC) and corticocortical (CC) synapses along the apical-basal axis of layer 5 pyramidal neurons as models of functionally diverse glutamatergic synapses in the brain. Spines receiving TC input were larger than CC spines in all layers examined. However, TC synapses on apical and basal dendrites conformed to different organizational principles. TC afferents on apical dendrites frequently contacted spines with multiple aligned PSD-95/Bassoon nanomodules, which are larger. TC spines on basal dendrites contained mostly one aligned PSD-95/Bassoon nanocluster. However, PSD-95 nanoclusters were larger and scaled with spine volume. The nano-organization of CC synapses did not change across cortical layers. These results highlight striking nanoscale diversity of functionally distinct glutamatergic synapses, relying on afferent input and sub-cellular localization of individual synaptic connections.

Mapping thalamic innervation to individual L2/3 pyramidal neurons and modeling their 'readout' of visual input

The thalamus is the main gateway for sensory information from the periphery to the mammalian cerebral cortex. A major conundrum has been the discrepancy between the thalamus's central role as the primary feedforward projection system into the neocortex and the sparseness of thalamocortical synapses. Here we use new methods, combining genetic tools and scalable tissue expansion microscopy for whole-cell synaptic mapping, revealing the number, density and size of thalamic versus cortical excitatory synapses onto individual layer 2/3 (L2/3) pyramidal cells (PCs) of the mouse primary visual cortex. We find that thalamic inputs are not only sparse, but remarkably heterogeneous in number and density across individual dendrites and neurons. Most surprising, despite their sparseness, thalamic synapses onto L2/3 PCs are smaller than their cortical counterparts. Incorporating these findings into fine-scale, anatomically faithful biophysical models of L2/3 PCs reveals how individual neurons with sparse and weak thalamocortical synapses, embedded in small heterogeneous neuronal ensembles, may reliably 'read out' visually driven thalamic input.

A model for the development of binocular congruence in primary visual cortex

Neurons in primary visual cortex are selective for stimulus orientation, and a neuron's preferred orientation changes little when the stimulus is switched from one eye to the other. It has recently been shown that monocular orientation preferences are uncorrelated before eye opening; how, then, do they become aligned during visual experience? We aimed to provide a model for this acquired congruence. Our model, which simulates the cat's visual system, comprises multiple on-centre and off-centre channels from both eyes converging onto neurons in primary visual cortex; development proceeds in two phases via Hebbian plasticity in the geniculocortical synapse. First, cortical drive comes from waves of activity drifting across each retina. The result is orientation tuning that differs between the two eyes. The second phase begins with eye opening: at each visual field location, on-centre cortical inputs from one eye can cancel off-centre inputs from the other eye. Synaptic plasticity reduces the destructive interference by up-regulating inputs from one eye at the expense of its fellow, resulting in binocular congruence of orientation tuning. We also show that orthogonal orientation preferences at the end of the first phase result in ocular dominance, suggesting that ocular dominance is a by-product of binocular congruence.

A binocular synaptic network supports interocular response alignment in visual cortical neurons

In visual cortex, signals from the two eyes merge to form a coherent binocular representation. Here we investigate the synaptic interactions underlying the binocular representation of stimulus orientation in ferret visual cortex with in vivo calcium imaging of layer 2/3 neurons and their dendritic spines. Individual neurons with aligned somatic responses received a mixture of monocular and binocular synaptic inputs. Surprisingly, monocular pathways alone could not account for somatic alignment because ipsilateral monocular inputs poorly matched somatic preference. Binocular inputs exhibited different degrees of interocular alignment, and those with a high degree of alignment (congruent) had greater selectivity and somatic specificity. While congruent inputs were similar to others in measures of strength, simulations show that the number of active congruent inputs predicts aligned somatic output. Our study suggests that coherent binocular responses derive from connectivity biases that support functional amplification of aligned signals within a heterogeneous binocular intracortical network.

Attention separates sensory and motor signals in the mouse visual cortex

Visually guided behaviors depend on the activity of cortical networks receiving visual inputs and transforming these signals to guide appropriate actions. However, non-retinal inputs, carrying motor signals as well as cognitive and attentional modulatory signals, also activate these cortical regions. How these networks integrate coincident signals ensuring reliable visual behaviors is poorly understood. In this study, we observe neural responses in the dorsal-parietal cortex of mice during a visual discrimination task driven by visual stimuli and movements. We find that visual and motor signals interact according to two mechanisms: divisive normalization and separation of responses. Interactions are contextually modulated by the animal's state of sustained attention, which amplifies visual and motor signals and increases their discriminability in a low-dimensional space of neural activations. These findings reveal computational principles operating in dorsal-parietal networks that enable separation of incoming signals for reliable visually guided behaviors during interactions with the environment.

How Cortical Circuits Implement Cortical Computations: Mouse Visual Cortex as a Model

The mouse, as a model organism to study the brain, gives us unprecedented experimental access to the mammalian cerebral cortex. By determining the cortex's cellular composition, revealing the interaction between its different components, and systematically perturbing these components, we are obtaining mechanistic insight into some of the most basic properties of cortical function. In this review, we describe recent advances in our understanding of how circuits of cortical neurons implement computations, as revealed by the study of mouse primary visual cortex. Further, we discuss how studying the mouse has broadened our understanding of the range of computations performed by visual cortex. Finally, we address how future approaches will fulfill the promise of the mouse in elucidating fundamental operations of cortex.

An ultrastructural connectomic analysis of a higher-order thalamocortical circuit in the mouse

Many studies exist of thalamocortical synapses in primary sensory cortex, but much less in known about higher-order thalamocortical projections to higher-order cortical areas. We begin to address this gap using genetic labeling combined with large volume serial electron microscopy (i.e., "connectomics") to study the projection from the thalamic posterior medial nucleus to the secondary somatosensory cortex in a mouse. We injected into this thalamic nucleus a cocktail combining a cre-expressing virus and one expressing cre-dependent ascorbate peroxidase that provides an electron dense cytoplasmic label. This "intersectional" viral approach specifically labeled thalamocortical axons and synapses, free of retrograde labeling, in all layers of cortex. Labeled thalamocortical synapses represented 14% of all synapses in the cortical volume, consistent with previous estimates of first-order thalamocortical inputs. We found that labeled thalamocortical terminals, relative to unlabeled ones: were larger, were more likely to contain a mitochondrion, more frequently targeted spiny dendrites and avoided aspiny dendrites, and often innervated larger spines with spine apparatuses, among other differences. Furthermore, labeled terminals were more prevalent in layers 2/3 and synaptic differences between labeled and unlabeled terminals were greatest in layers 2/3. The laminar differences reported here contrast with reports of first-order thalamocortical connections in primary sensory cortices where, for example, labeled terminals were larger in layer 4 than layers 2/3 (Viaene et al., 2011a). These data offer the first glimpse of higher-order thalamocortical synaptic ultrastructure and point to the need for more analyses, as such connectivity likely represents a majority of thalamocortical circuitry.

Recurrent network dynamics shape direction selectivity in primary auditory cortex

Detecting the direction of frequency modulation (FM) is essential for vocal communication in both animals and humans. Direction-selective firing of neurons in the primary auditory cortex (A1) has been classically attributed to temporal offsets between feedforward excitatory and inhibitory inputs. However, it remains unclear how cortical recurrent circuitry contributes to this computation. Here, we used two-photon calcium imaging and whole-cell recordings in awake mice to demonstrate that direction selectivity is not caused by temporal offsets between synaptic currents, but by an asymmetry in total synaptic charge between preferred and non-preferred directions. Inactivation of cortical somatostatin-expressing interneurons (SOM cells) reduced direction selectivity, revealing its cortical contribution. Our theoretical models showed that charge asymmetry arises due to broad spatial topography of SOM cell-mediated inhibition which regulates signal amplification in strongly recurrent circuitry. Together, our findings reveal a major contribution of recurrent network dynamics in shaping cortical tuning to behaviorally relevant complex sounds.

A Model for the Origin of Motion Direction Selectivity in Visual Cortex

Motion perception is a vital part of our sensory repertoire in that it contributes to navigation, awareness of moving objects, and communication. Motion sense in carnivores and primates originates with primary visual cortical neurons selective for motion direction. More than 60 years after the discovery of these neurons, there is still no consensus on the mechanism underlying direction selectivity. This paper describes a model of the cat's visual system in which direction selectivity results from the well-documented orientation selectivity of inhibitory neurons: inhomogeneities in the orientation preference map for inhibitory neurons leads to spatially asymmetric inhibition, and thus to direction selectivity. Stimulation of the model with a drifting grating shows that direction selectivity results from the relative timing of excitatory and inhibitory inputs to a neuron. Using a stationary contrast-reversing grating reveals that the inhibitory input is spatially displaced in the preferred direction relative to the excitatory input, and that this asymmetry leads to the timing difference. More generally, the model yields physiologically realistic estimates of the direction selectivity index, and it reproduces the critical finding with contrast-reversing gratings that response phase advances with grating spatial phase. It is concluded that a model based on intracortical inhibition can account well for the known properties of direction selectivity in carnivores and primates.SIGNIFICANCE STATEMENT Motion perception is vital for navigation, communication, and the awareness of moving objects. Motion sense depends on cortical neurons that are selective for motion direction, and this paper describes a model for the physiological mechanism underlying cortical direction selectivity. The essence of the model is that intracortical inhibition of a direction-selective cell is spatially inhomogeneous and therefore depends on whether a stimulus generates inhibition before or after reaching the cell's receptive field: the response is weaker in the former than in the latter case. If the model is correct, it will contribute to the understanding of motion processing in carnivores and primates.

Complementary Inhibitory Weight Profiles Emerge from Plasticity and Allow Flexible Switching of Receptive Fields

Cortical areas comprise multiple types of inhibitory interneurons, with stereotypical connectivity motifs that may follow specific plasticity rules. Yet, their combined effect on postsynaptic dynamics has been largely unexplored. Here, we analyze the response of a single postsynaptic model neuron receiving tuned excitatory connections alongside inhibition from two plastic populations. Synapses from each inhibitory population change according to distinct plasticity rules. We tested different combinations of three rules: Hebbian, anti-Hebbian, and homeostatic scaling. Depending on the inhibitory plasticity rule, synapses become unspecific (flat), anticorrelated to, or correlated with excitatory synapses. Crucially, the neuron's receptive field (i.e., its response to presynaptic stimuli) depends on the modulatory state of inhibition. When both inhibitory populations are active, inhibition balances excitation, resulting in uncorrelated postsynaptic responses regardless of the inhibitory tuning profiles. Modulating the activity of a given inhibitory population produces strong correlations to either preferred or nonpreferred inputs, in line with recent experimental findings that show dramatic context-dependent changes of neurons' receptive fields. We thus confirm that a neuron's receptive field does not follow directly from the weight profiles of its presynaptic afferents. Our results show how plasticity rules in various cell types can interact to shape cortical circuit motifs and their dynamics.SIGNIFICANCE STATEMENT Neurons in sensory areas of the cortex are known to respond to specific features of a given input (e.g., specific sound frequencies), but recent experimental studies show that such responses (i.e., their receptive fields) depend on context. Inspired by the cortical connectivity, we built models of excitatory and inhibitory inputs onto a single neuron, to study how receptive fields may change on short and long time scales. We show how various synaptic plasticity rules allow for the emergence of diverse connectivity profiles and, moreover, how their dynamic interaction creates a mechanism by which postsynaptic responses can quickly change. Our work emphasizes multiple roles of inhibition in cortical processing and provides a first mechanistic model for flexible receptive fields.

Cortical Presynaptic Boutons Progressively Engulf Spinules as They Mature

Despite decades of discussion in the neuroanatomical literature, the role of the synaptic "spinule" in synaptic development and function remains elusive. Canonically, spinules are finger-like projections that emerge from postsynaptic spines and can become enveloped by presynaptic boutons. When a presynaptic bouton encapsulates a spinule in this manner, the membrane apposition between the spinule and surrounding bouton can be significantly larger than the membrane interface at the synaptic active zone. Hence, spinules may represent a mechanism for extrasynaptic neuronal communication and/or may function as structural "anchors" that increase the stability of cortical synapses. Yet despite their potential to impact synaptic function, we have little information on the percentages of developing and adult cortical bouton populations that contain spinules, the percentages of these cortical spinule-bearing boutons (SBBs) that contain spinules from distinct neuronal/glial origins, or whether the onset of activity or cortical plasticity are correlated with increased prevalence of cortical SBBs. Here, we employed 2D and 3D electron microscopy to determine the prevalence of spinules in excitatory presynaptic boutons at key developmental time points in the primary visual cortex (V1) of female and male ferrets. We find that the prevalence of SBBs in V1 increases across postnatal development, such that ∼25% of excitatory boutons in late adolescent ferret V1 contain spinules. In addition, we find that a majority of spinules within SBBs at later developmental time points emerge from postsynaptic spines and adjacent boutons/axons, suggesting that synaptic spinules may enhance synaptic stability and allow for axo-axonal communication in mature sensory cortex.

An Attempt at a Unified Theory of the Neocortical Microcircuit in Sensory Cortex

The neocortex performs a wide range of functions, including working memory, sensory perception, and motor planning. Despite this diversity in function, evidence suggests that the neocortex is made up of repeating subunits ("macrocolumns"), each of which is largely identical in circuitry. As such, the specific computations performed by these macrocolumns are of great interest to neuroscientists and AI researchers. Leading theories of this microcircuit include models of predictive coding, hierarchical temporal memory (HTM), and Adaptive Resonance Theory (ART). However, these models have not yet explained: (1) how microcircuits learn sequences input with delay (i.e., working memory); (2) how networks of columns coordinate processing on precise timescales; or (3) how top-down attention modulates sensory processing. I provide a theory of the neocortical microcircuit that extends prior models in all three ways. Additionally, this theory provides a novel working memory circuit that extends prior models to support simultaneous multi-item storage without disrupting ongoing sensory processing. I then use this theory to explain the functional origin of a diverse set of experimental findings, such as cortical oscillations.

Ultrastructural heterogeneity of layer 4 excitatory synaptic boutons in the adult human temporal lobe neocortex

Synapses are fundamental building blocks controlling and modulating the ‘behavior’ of brain networks. How their structural composition, most notably their quantitative morphology underlie their computational properties remains rather unclear, particularly in humans. Here, excitatory synaptic boutons (SBs) in layer 4 (L4) of the temporal lobe neocortex (TLN) were quantitatively investigated. Biopsies from epilepsy surgery were used for fine-scale and tomographic electron microscopy (EM) to generate 3D-reconstructions of SBs. Particularly, the size of active zones (AZs) and that of the three functionally defined pools of synaptic vesicles (SVs) were quantified. SBs were comparatively small (~2.50 μm²), with a single AZ (~0.13 µm²); preferentially established on spines. SBs had a total pool of ~1800 SVs with strikingly large readily releasable (~20), recycling (~80) and resting pools (~850). Thus, human L4 SBs may act as ‘amplifiers’ of signals from the sensory periphery, integrate, synchronize and modulate intra- and extracortical synaptic activity.

Dense connectomic reconstruction in layer 4 of the somatosensory cortex

The dense circuit structure of mammalian cerebral cortex is still unknown. With developments in three-dimensional electron microscopy, the imaging of sizable volumes of neuropil has become possible, but dense reconstruction of connectomes is the limiting step. We reconstructed a volume of ~500,000 cubic micrometers from layer 4 of mouse barrel cortex, ~300 times larger than previous dense reconstructions from the mammalian cerebral cortex. The connectomic data allowed the extraction of inhibitory and excitatory neuron subtypes that were not predictable from geometric information. We quantified connectomic imprints consistent with Hebbian synaptic weight adaptation, which yielded upper bounds for the fraction of the circuit consistent with saturated long-term potentiation. These data establish an approach for the locally dense connectomic phenotyping of neuronal circuitry in the mammalian cortex.

Feedforward Thalamocortical Connectivity Preserves Stimulus Timing Information in Sensory Pathways

Reliable timing of cortical spikes in response to visual events is crucial in representing visual inputs to the brain. Spikes in the primary visual cortex (V1) need to occur at the same time within a repeated visual stimulus. Two classical mechanisms are employed by the cortex to enhance reliable timing. First, cortical neurons respond reliably to a restricted set of stimuli through their preference for certain patterns of membrane potential due to their intrinsic properties. Second, intracortical networking of excitatory and inhibitory neurons induces lateral inhibition that, through the timing and strength of IPSCs and EPSCs, produces sparse and reliably timed cortical neuron spike trains to be transmitted downstream. Here, we describe a third mechanism that, through preferential thalamocortical synaptic connectivity, enhances the trial-to-trial timing precision of cortical spikes in the presence of spike train variability within each trial that is introduced between LGN neurons in the retino-thalamic pathway. Applying experimentally recorded LGN spike trains from the anesthetized cat to a detailed model of a spiny stellate V1 neuron, we found that output spike timing precision improved with increasing numbers of convergent LGN inputs. The improvement was consistent with the predicted proportionality of [Formula: see text] for n LGN source neurons. We also found connectivity configurations that maximize reliability and that generate V1 cell output spike trains quantitatively similar to the experimental recordings. Our findings suggest a general principle, namely intra-trial variability among converging inputs, that increases stimulus response precision and is widely applicable to synaptically connected spiking neurons.SIGNIFICANCE STATEMENT The early visual pathway of the cat is favorable for studying the effects of trial-to-trial variability of synaptic inputs and intra-trial variability of thalamocortical connectivity on information transmission into the visual cortex. We have used a detailed model to show that there are preferred combinations of the number of thalamic afferents and the number of synapses per afferent that maximize the output reliability and spike-timing precision of cortical neurons. This provides additional insights into how synchrony in thalamic spike trains can reduce trial-to-trial variability to produce highly reliable reporting of sensory events to the cortex. The same principles may apply to other converging pathways where temporally jittered spike trains can reliably drive the downstream neuron and improve temporal precision.

Locations in the Neocortex: A Theory of Sensorimotor Object Recognition Using Cortical Grid Cells

The neocortex is capable of anticipating the sensory results of movement but the neural mechanisms are poorly understood. In the entorhinal cortex, grid cells represent the location of an animal in its environment, and this location is updated through movement and path integration. In this paper, we propose that sensory neocortex incorporates movement using grid cell-like neurons that represent the location of sensors on an object. We describe a two-layer neural network model that uses cortical grid cells and path integration to robustly learn and recognize objects through movement and predict sensory stimuli after movement. A layer of cells consisting of several grid cell-like modules represents a location in the reference frame of a specific object. Another layer of cells which processes sensory input receives this location input as context and uses it to encode the sensory input in the object's reference frame. Sensory input causes the network to invoke previously learned locations that are consistent with the input, and motor input causes the network to update those locations. Simulations show that the model can learn hundreds of objects even when object features alone are insufficient for disambiguation. We discuss the relationship of the model to cortical circuitry and suggest that the reciprocal connections between layers 4 and 6 fit the requirements of the model. We propose that the subgranular layers of cortical columns employ grid cell-like mechanisms to represent object specific locations that are updated through movement.

Binocular Modulation of Monocular V1 Neurons

In humans and other primates, sensory signals from each eye remain separated until they arrive in the primary visual cortex (V1), but their exact meeting point is unknown. In V1, some neurons respond to stimulation of only one eye (monocular neurons), while most neurons respond to stimulation of either eye (binocular neurons). The main input layers of V1 contain most of the monocular neurons while binocular neurons dominate the layers above and below. This observation has given rise to the idea that the two eyes' signals remain separate until they converge outside V1's input layers. Here, we show that, despite responding to only one eye, monocular neurons in all layers, including the input layers, of V1 discriminate between stimulation of their driving eye alone and stimulation of both eyes. Some monocular V1 neurons' responses were significantly enhanced, or facilitated, when both eyes were stimulated. Binocular facilitation within V1's input layers tended to occur at the onset of the visual response, which could be explained by converging thalamocortical inputs. However, most V1 monocular neurons were significantly reduced, or suppressed, to binocular stimulation. In contrast to facilitation, binocular suppression occurred several milliseconds following the onset of the visual response, suggesting that the bulk of binocular modulation involves cortical inhibition. These findings, combined, suggest that binocular signals arise at an earlier processing stage than previously appreciated, as even so-called monocular neurons in V1's input layers encode what is shown to both eyes.

Major Feedforward Thalamic Input Into Layer 4C of Primary Visual Cortex in Primate

One of the underlying principles of how mammalian circuits are constructed is the relative influence of feedforward to recurrent synaptic drive. It has been dogma in sensory systems that the thalamic feedforward input is relatively weak and that there is a large amplification of the input signal by recurrent feedback. Here we show that in trichromatic primates there is a major feedforward input to layer 4C of primary visual cortex. Using a combination of 3D-electron-microscopy and 3D-confocal imaging of thalamic boutons we found that the average feedforward contribution was about 20% of the total excitatory input in the parvocellular (P) pathway, about 3 times the currently accepted values for primates. In the magnocellular (M) pathway it was around 15%, nearly twice the currently accepted values. New methods showed the total synaptic and cell densities were as much as 150% of currently accepted values. The new estimates of contributions of feedforward synaptic inputs into visual cortex call for a major revision of the design of the canonical cortical circuit.

Sensory experience inversely regulates feedforward and feedback excitation-inhibition ratio in rodent visual cortex

Brief (2-3d) monocular deprivation (MD) during the critical period induces a profound loss of responsiveness within binocular (V1b) and monocular (V1m) regions of rodent primary visual cortex. This has largely been ascribed to long-term depression (LTD) at thalamocortical synapses, while a contribution from intracortical inhibition has been controversial. Here we used optogenetics to isolate and measure feedforward thalamocortical and feedback intracortical excitation-inhibition (E-I) ratios following brief MD. Despite depression at thalamocortical synapses, thalamocortical E-I ratio was unaffected in V1b and shifted toward excitation in V1m, indicating that thalamocortical excitation was not effectively reduced. In contrast, feedback intracortical E-I ratio was shifted toward inhibition in V1m, and a computational model demonstrated that these opposing shifts produced an overall suppression of layer 4 excitability. Thus, feedforward and feedback E-I ratios can be independently tuned by visual experience, and enhanced feedback inhibition is the primary driving force behind loss of visual responsiveness.

Anti-correlated cortical networks arise from spontaneous neuronal dynamics at slow timescales

In the highly interconnected architectures of the cerebral cortex, recurrent intracortical loops disproportionately outnumber thalamo-cortical inputs. These networks are also capable of generating neuronal activity without feedforward sensory drive. It is unknown, however, what spatiotemporal patterns may be solely attributed to intrinsic connections of the local cortical network. Using high-density microelectrode arrays, here we show that in the isolated, primary somatosensory cortex of mice, neuronal firing fluctuates on timescales from milliseconds to tens of seconds. Slower firing fluctuations reveal two spatially distinct neuronal ensembles, which correspond to superficial and deeper layers. These ensembles are anti-correlated: when one fires more, the other fires less and vice versa. This interplay is clearest at timescales of several seconds and is therefore consistent with shifts between active sensing and anticipatory behavioral states in mice.

Inhibition in Simple Cell Receptive Fields Is Broad and OFF-Subregion Biased

Inhibition in thalamorecipient layer 4 simple cells of primary visual cortex is believed to play important roles in establishing visual response properties and integrating visual inputs across their receptive fields (RFs). Simple cell RFs are characterized by nonoverlapping, spatially restricted subregions in which visual stimuli can either increase or decrease the firing rate of the cell, depending on contrast. Inhibition is believed to be triggered exclusively from visual stimulation of individual RF subregions. However, this view is at odds with the known anatomy of layer 4 interneurons in visual cortex and differs from recent findings in mouse visual cortex. Here we show with in vivo intracellular recordings in cats that while excitation is restricted to RF subregions, inhibition spans the width of simple cell RFs. Consequently, excitatory stimuli within a subregion concomitantly drive excitation and inhibition. Furthermore, we found that the distribution of inhibition across the RF is stronger toward OFF subregions. This inhibitory OFF-subregion bias has a functional consequence on spatial integration of inputs across the RF. A model based on the known anatomy of layer 4 demonstrates that the known proportion and connectivity of inhibitory neurons in layer 4 of primary visual cortex is sufficient to explain broad inhibition with an OFF-subregion bias while generating a variety of phase relations, including antiphase, between excitation and inhibition in response to drifting gratings.SIGNIFICANCE STATEMENT The wiring of excitatory and inhibitory neurons in cortical circuits is key to determining the response properties in sensory cortex. In the visual cortex, the first cells that receive visual input are simple cells in layer 4. The underlying circuitry responsible for the response properties of simple cells is not yet known. In this study, we challenge a long-held view concerning the pattern of inhibitory input and provide results that agree with current known anatomy. We show here that inhibition is evoked broadly across the receptive fields of simple cells, and we identify a surprising bias in inhibition within the receptive field. Our findings represent a step toward a unified view of inhibition across different species and sensory systems.

Feedforward Approximations to Dynamic Recurrent Network Architectures

Recurrent neural network architectures can have useful computational properties, with complex temporal dynamics and input-sensitive attractor states. However, evaluation of recurrent dynamic architectures requires solving systems of differential equations, and the number of evaluations required to determine their response to a given input can vary with the input or can be indeterminate altogether in the case of oscillations or instability. In feedforward networks, by contrast, only a single pass through the network is needed to determine the response to a given input. Modern machine learning systems are designed to operate efficiently on feedforward architectures. We hypothesized that two-layer feedforward architectures with simple, deterministic dynamics could approximate the responses of single-layer recurrent network architectures. By identifying the fixed-point responses of a given recurrent network, we trained two-layer networks to directly approximate the fixed-point response to a given input. These feedforward networks then embodied useful computations, including competitive interactions, information transformations, and noise rejection. Our approach was able to find useful approximations to recurrent networks, which can then be evaluated in linear and deterministic time complexity.

Cornu Ammonis Regions-Antecedents of Cortical Layers?

Studying neocortex and hippocampus in parallel, we are struck by the similarities. All three to four layered allocortices and the six layered mammalian neocortex arise in the pallium. All receive and integrate multiple cortical and subcortical inputs, provide multiple outputs and include an array of neuronal classes. During development, each cell positions itself to sample appropriate local and distant inputs and to innervate appropriate targets. Simpler cortices had already solved the need to transform multiple coincident inputs into serviceable outputs before neocortex appeared in mammals. Why then do phylogenetically more recent cortices need multiple pyramidal cell layers? A simple answer is that more neurones can compute more complex functions. The dentate gyrus and hippocampal CA regions-which might be seen as hippocampal antecedents of neocortical layers-lie side by side, albeit around a tight bend. Were the millions of cells of rat neocortex arranged in like fashion, the surface area of the CA pyramidal cell layers would be some 40 times larger. Even if evolution had managed to fold this immense sheet into the space available, the distances between neurones that needed to be synaptically connected would be huge and to maintain the speed of information transfer, massive, myelinated fiber tracts would be needed. How much more practical to stack the "cells that fire and wire together" into narrow columns, while retaining the mechanisms underlying the extraordinary precision with which circuits form. This demonstrably efficient arrangement presents us with challenges, however, not the least being to categorize the baffling array of neuronal subtypes in each of five "pyramidal layers." If we imagine the puzzle posed by this bewildering jumble of apical dendrites, basal dendrites and axons, from many different pyramidal and interneuronal classes, that is encountered by a late-arriving interneurone insinuating itself into a functional circuit, we can perhaps begin to understand why definitive classification, covering every aspect of each neurone's structure and function, is such a challenge. Here, we summarize and compare the development of these two cortices, the properties of their neurones, the circuits they form and the ordered, unidirectional flow of information from one hippocampal region, or one neocortical layer, to another.

Diverse Representations of Olfactory Information in Centrifugal Feedback Projections

Although feedback or centrifugal projections from higher processing centers of the brain to peripheral regions have long been known to play essential functional roles, the anatomical organization of these connections remains largely unknown. Using a virus-based retrograde labeling strategy and 3D whole-brain reconstruction methods, we mapped the spatial organization of centrifugal projections from two olfactory cortical areas, the anterior olfactory nucleus (AON) and the piriform cortex, to the granule cell layer of the main olfactory bulb in the mouse. Both regions are major recipients of information from the bulb and are the largest sources of feedback to the bulb, collectively constituting circuits essential for olfactory coding and olfactory behavior. We found that, although ipsilateral inputs from the AON were uniformly distributed, feedback from the contralateral AON had a strong ventral bias. In addition, we observed that centrifugally projecting neurons were spatially clustered in the piriform cortex, in contrast to the distributed feedforward axonal inputs that these cells receive from the principal neurons of the bulb. Therefore, information carried from the bulb to higher processing structures by anatomically stereotypic projections is likely relayed back to the bulb by organizationally distinct feedback projections that may reflect different coding strategies and therefore different functional roles.

SIGNIFICANCE STATEMENT

Principles of anatomical organization, sometimes instantiated as "maps" in the mammalian brain, have provided key insights into the structure and function of circuits in sensory systems. Generally, these characterizations focus on projections from early sensory processing areas to higher processing structures despite considerable evidence that feedback or centrifugal projections often constitute major conduits of information flow. Our results identify structure in the organization of centrifugal feedback projections to the olfactory bulb that is fundamentally different from the organization of feedforward circuits. Our study suggests that understanding computations performed in the olfactory bulb, and more generally in the olfactory system, requires understanding interactions between feedforward and feedback "maps" both structurally and functionally.

Focal Local Field Potential Signature of the Single-Axon Monosynaptic Thalamocortical Connection

A resurgence has taken place in recent years in the use of the extracellularly recorded local field potential (LFP) to investigate neural network activity. To probe monosynaptic thalamic activation of cortical postsynaptic target cells, so called spike-trigger-averaged LFP (stLFP) signatures have been measured. In these experiments, the cortical LFP is measured by multielectrodes covering several cortical lamina and averaged on spontaneous spikes of thalamocortical (TC) cells. Using a well established forward-modeling scheme, we investigated the biophysical origin of this stLFP signature with simultaneous synaptic activation of cortical layer-4 neurons, mimicking the effect of a single afferent spike from a single TC neuron. Constrained by previously measured intracellular responses of the main postsynaptic target cell types and with biologically plausible assumptions regarding the spatial distribution of thalamic synaptic inputs into layer 4, the model predicted characteristic contributions to monosynaptic stLFP signatures both for the regular-spiking (RS) excitatory neurons and the fast-spiking (FS) inhibitory interneurons. In particular, the FS cells generated stLFP signatures of shorter temporal duration than the RS cells. Added together, a sum of the stLFP signatures of these two principal synaptic targets of TC cells were observed to resemble experimentally measured stLFP signatures. Outside the volume targeted by TC afferents, the resulting postsynaptic LFP signals were found to be sharply attenuated. This implies that such stLFP signatures provide a very local measure of TC synaptic activation, and that newly developed inverse current-source density (CSD)-estimation methods are needed for precise assessment of the underlying spatiotemporal CSD profiles.SIGNIFICANCE STATEMENT Despite its long history and prevalent use, the proper interpretation of the extracellularly recorded local field potential (LFP) is still not fully established. Here we investigate by biophysical modeling the origin of the focal LFP signature of the single-axon monosynaptic thalamocortical connection as measured by spike-trigger-averaging of cortical LFPs on spontaneous spikes of thalamocortical neurons. We find that this LFP signature is well accounted for by a model assuming thalamic projections to two cortical layer-4 cell populations: one excitatory (putatively regular-spiking cells) and one inhibitory (putatively fast-spiking cells). The LFP signature is observed to decay sharply outside the cortical region receiving the thalamocortical projection, implying that it indeed provides a very local measure of thalamocortical synaptic activation.

Opposing Effects of Maternal Hypo- and Hyperthyroidism on the Stability of Thalamocortical Synapses in the Visual Cortex of Adult Offspring

Insufficient or excessive thyroid hormone (TH) levels during fetal development can cause long-term neurological and cognitive problems. Studies in animal models of perinatal hypo- and hyperthyroidism suggest that these problems may be a consequence of the formation of maladaptive circuitry in the cerebral cortex, which can persist into adulthood. Here we used mouse models of maternal hypo- and hyperthyroidism to investigate the long-term effects of altering thyroxine (T4) levels during pregnancy (corresponding to embryonic days 6.5-18.5) on thalamocortical (TC) axon dynamics in adult offspring. Because perinatal hypothyroidism has been linked to visual processing deficits in humans, we performed chronic two-photon imaging of TC axons and boutons in primary visual cortex (V1). We found that a decrease or increase in maternal serum T4 levels was associated with atypical steady-state dynamics of TC axons and boutons in V1 of adult offspring. Hypothyroid offspring exhibited axonal branch and bouton dynamics indicative of an abnormal increase in TC connectivity, whereas changes in hyperthyroid offspring were indicative of an abnormal decrease in TC connectivity. Collectively, our data suggest that alterations to prenatal T4 levels can cause long-term synaptic instability in TC circuits, which could impair early stages of visual processing.

An Ultrastructural Study of the Thalamic Input to Layer 4 of Primary Motor and Primary Somatosensory Cortex in the Mouse

The traditional classification of primary motor cortex (M1) as an agranular area has been challenged recently when a functional layer 4 (L4) was reported in M1. L4 is the principal target for thalamic input in sensory areas, which raises the question of how thalamocortical synapses formed in M1 in the mouse compare with those in neighboring sensory cortex (S1). We identified thalamic boutons by their immunoreactivity for the vesicular glutamate transporter 2 (VGluT2) and performed unbiased disector counts from electron micrographs. We discovered that the thalamus contributed proportionately only half as many synapses to the local circuitry of L4 in M1 compared with S1. Furthermore, thalamic boutons in M1 targeted spiny dendrites exclusively, whereas ∼9% of synapses were formed with dendrites of smooth neurons in S1. VGluT2⁺ boutons in M1 were smaller and formed fewer synapses per bouton on average (1.3 vs 2.1) than those in S1, but VGluT2⁺ synapses in M1 were larger than in S1 (median postsynaptic density areas of 0.064 μm² vs 0.042 μm²). In M1 and S1, thalamic synapses formed only a small fraction (12.1% and 17.2%, respectively) of all of the asymmetric synapses in L4. The functional role of the thalamic input to L4 in M1 has largely been neglected, but our data suggest that, as in S1, the thalamic input is amplified by the recurrent excitatory connections of the L4 circuits. The lack of direct thalamic input to inhibitory neurons in M1 may indicate temporal differences in the inhibitory gating in L4 of M1 versus S1.SIGNIFICANCE STATEMENT Classical interpretations of the function of primary motor cortex (M1) emphasize its lack of the granular layer 4 (L4) typical of sensory cortices. However, we show here that, like sensory cortex (S1), mouse M1 also has the canonical circuit motif of a core thalamic input to the middle cortical layer and that thalamocortical synapses form a small fraction (M1: 12%; S1: 17%) of all asymmetric synapses in L4 of both areas. Amplification of thalamic input by recurrent local circuits is thus likely to be a significant mechanism in both areas. Unlike M1, where thalamocortical boutons typically form a single synapse, thalamocortical boutons in S1 usually formed multiple synapses, which means they can be identified with high probability in the electron microscope without specific labeling.

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

To uncover the functional topography of layer 6 neurons, optical imaging was combined with three-dimensional neuronal reconstruction. Apical dendrite morphology of 23 neurons revealed three distinct types. Type Aa possessed a short apical dendrite with many oblique branches, Type Ab was characterized by a short and less branched apical dendrite, whereas Type B had a long apical dendrite with tufts in layer 2. Each type had a similar number of boutons, yet their spatial distribution differed from each other in both radial and horizontal extent. Boutons of Type Aa and Ab were almost restricted to the column of the parent soma with a laminar preference to layer 4 and 5/6, respectively. Only Type B contributed to long horizontal connections (up to 1.5 mm) mostly in deep layers. For all types, bouton distribution on orientation map showed an almost equal occurrence at iso- (52.6 ± 18.8 %) and non-iso-orientation (oblique, 27.7 ± 14.9 % and cross-orientation 19.7 ± 10.9 %) sites. Spatial convergence of axons of nearby layer 6 spiny neurons depended on soma separation of the parent cells, but only weakly on orientation preference, contrary to orientation dependence of converging axons of layer 4 spiny cells. The results show that layer 6 connections have only a weak dependence on orientation preference compared with those of layers 2/3 (Buzás et al., J Comp Neurol 499:861–881, 2006) and 4 (Karube and Kisvárday, Cereb Cortex 21:1443–1458, 2011).

Thalamus plays a central role in ongoing cortical functioning

Several challenges to current views of thalamocortical processing are offered here. Glutamatergic pathways in thalamus and cortex are divided into two distinct classes: driver and modulator. We suggest that driver inputs are the main conduits of information and that modulator inputs modify how driver inputs are processed. Different driver sources reveal two types of thalamic relays: first order relays receive subcortical driver input (for example, retinal input to the lateral geniculate nucleus), whereas higher order relays (for example, pulvinar) receive driver input from layer 5 of cortex and participate in cortico-thalamo-cortical (or transthalamic) circuits. These transthalamic circuits represent an unappreciated aspect of cortical functioning, which I discuss here. Direct corticocortical connections are often paralleled by transthalamic ones. Furthermore, driver inputs to thalamus, both first and higher order, typically arrive via branching axons, and the transthalamic branch often innervates subcortical motor centers, leading to the suggestion that these inputs to thalamus serve as efference copies.

Morphometric analysis of feedforward pathways from the primary somatosensory area (S1) of rats

We used biotinylated dextran amine (BDA) to anterogradely label individual axons projecting from primary somatosensory cortex (S1) to four different cortical areas in rats. A major goal was to determine whether axon terminals in these target areas shared morphometric similarities based on the shape of individual terminal arbors and the density of two bouton types: en passant (Bp) and terminaux (Bt). Evidence from tridimensional reconstructions of isolated axon terminal fragments (n=111) did support a degree of morphological heterogeneity establishing two broad groups of axon terminals. Morphological parameters associated with the complexity of terminal arbors and the proportion of beaded Bp vs stalked Bt were found to differ significantly in these two groups following a discriminant function statistical analysis across axon fragments. Interestingly, both groups occurred in all four target areas, possibly consistent with a commonality of presynaptic processing of tactile information. These findings lay the ground for additional work aiming to investigate synaptic function at the single bouton level and see how this might be associated with emerging properties in postsynaptic targets.

Morphological Substrates for Parallel Streams of Corticogeniculate Feedback Originating in Both V1 and V2 of the Macaque Monkey

Corticothalamic circuits are essential for reciprocal information exchange between the thalamus and cerebral cortex. Nevertheless, the role of corticothalamic circuits in sensory processing remains a mystery. In the visual system, afferents from retina to the lateral geniculate nucleus (LGN) and from LGN to primary visual cortex (V1) are organized into functionally distinct parallel processing streams. Physiological evidence suggests corticogeniculate feedback may be organized into parallel streams; however, little is known about the diversity of corticogeniculate neurons, their local computations, or the structure-function relationship among corticogeniculate neurons. We used a virus-mediated approach to label and reconstruct the complete dendritic and local axonal arbors of identified corticogeniculate neurons in the macaque monkey. Our results reveal morphological substrates for parallel streams of corticogeniculate feedback based on distinct classes of neurons in V1 and V2. These results support the hypothesis that distinct populations of feedback neurons provide independent and unique information to the LGN.

In vivo models of cortical acquired epilepsy

The neocortex is the site of origin of several forms of acquired epilepsy. Here we provide a brief review of experimental models that were recently developed to study neocortical epileptogenesis as well as some major results obtained with these methods. Most of neocortical seizures appear to be nocturnal and it is known that neuronal activities reveal high levels of synchrony during slow-wave sleep. Therefore, we start the review with a description of mechanisms of neuronal synchronization and major forms of synchronized normal and pathological activities. Then, we describe three experimental models of seizures and epileptogenesis: ketamine-xylazine anesthesia as feline seizure triggered factor, cortical undercut as cortical penetrating wound model and neocortical kindling. Besides specific technical details describing these models we also provide major features of pathological brain activities recorded during epileptogenesis and seizures. The most common feature of all models of neocortical epileptogenesis is the increased duration of network silent states that up-regulates neuronal excitability and eventually leads to epilepsy.

Visual Receptive Field Properties of Neurons in the Mouse Lateral Geniculate Nucleus

The lateral geniculate nucleus (LGN) is increasingly regarded as a "smart-gating" operator for processing visual information. Therefore, characterizing the response properties of LGN neurons will enable us to better understand how neurons encode and transfer visual signals. Efforts have been devoted to study its anatomical and functional features, and recent advances have highlighted the existence in rodents of complex features such as direction/orientation selectivity. However, unlike well-researched higher-order mammals such as primates, the full array of response characteristics vis-à-vis its morphological features have remained relatively unexplored in the mouse LGN. To address the issue, we recorded from mouse LGN neurons using multisite-electrode-arrays (MEAs) and analysed their discharge patterns in relation to their location under a series of visual stimulation paradigms. Several response properties paralleled results from earlier studies in the field and these include centre-surround organization, size of receptive field, spontaneous firing rate and linearity of spatial summation. However, our results also revealed "high-pass" and "low-pass" features in the temporal frequency tuning of some cells, and greater average contrast gain than reported by earlier studies. In addition, a small proportion of cells had direction/orientation selectivity. Both "high-pass" and "low-pass" cells, as well as direction and orientation selective cells, were found only in small numbers, supporting the notion that these properties emerge in the cortex. ON- and OFF-cells showed distinct contrast sensitivity and temporal frequency tuning properties, suggesting parallel projections from the retina. Incorporating a novel histological technique, we created a 3-D LGN volume model explicitly capturing the morphological features of mouse LGN and localising individual cells into anterior/middle/posterior LGN. Based on this categorization, we show that the ON/OFF, DS/OS and linear response properties are not regionally restricted. Our study confirms earlier findings of spatial pattern selectivity in the LGN, and builds on it to demonstrate that relatively elaborate features are computed early in the visual pathway.

Contrast invariance of orientation tuning in cat primary visual cortex neurons depends on stimulus size

KEY POINTS

The process of orientation tuning is an important and well-characterized feature of neurons in primary visual cortex. The combination of ascending and descending circuits involved is not only relevant to understanding visual processing but the function of neocortex in general. The classic feed-forward model of orientation tuning predicts a broadening effect due to increasing contrast; yet, experimental results consistently report contrast invariance. We show here that contrast invariance actually depends on stimulus size such that large stimuli extending beyond the neuron's receptive field engage circuits that promote invariance, whereas optimally sized, smaller stimuli result in contrast variance that is more in line with the classical orientation tuning model. These results illustrate the importance of optimizing stimulus parameters to best reflect the sensory pathways under study and provide new clues about different circuits that may be involved in variant and invariant response properties.

ABSTRACT

Selective response to stimulus orientation is a key feature of neurons in primary visual cortex, yet the underlying mechanisms generating orientation tuning are not fully understood. The combination of feed-forward and cortical mechanisms involved is not only relevant to understanding visual processing but the function of neocortex in general. The classic feed-forward model predicts that orientation tuning should broaden considerably with increasing contrast; however, experimental results consistently report contrast invariance. We show here, in primary visual cortex of anaesthetized cats under neuromuscular blockade, that contrast invariance occurs when visual stimuli are large enough to include the extraclassical surround (ECS), which is likely to involve circuits of suppression that may not be entirely feed-forward in origin. On the other hand, when stimulus size is optimized to the classical receptive field of each neuron, the population average shows a statistically significant 40% increase in tuning width at high contrast, demonstrating that contrast variance of orientation tuning can occur. Conversely, our results also suggest that the phenomenon of contrast invariance relies in part on the presence of the ECS. Moreover, these results illustrate the importance of optimizing stimulus parameters to best reflect the neural pathways under study.

Target-specific properties of thalamocortical synapses onto layer 4 of mouse primary visual cortex

In primary sensory cortices, thalamocortical (TC) inputs can directly activate excitatory and inhibitory neurons. In vivo experiments in the main input layer (L4) of primary visual cortex (V1) have shown that excitatory and inhibitory neurons have different tuning properties. The different functional properties may arise from distinct intrinsic properties of L4 neurons, but could also depend on cell type-specific properties of the synaptic inputs from the lateral geniculate nucleus of the thalamus (LGN) onto L4 neurons. While anatomical studies identified LGN inputs onto both excitatory and inhibitory neurons in V1, their synaptic properties have not been investigated. Here we used an optogenetic approach to selectively activate LGN terminal fields in acute coronal slices containing V1, and recorded monosynaptic currents from excitatory and inhibitory neurons in L4. LGN afferents made monosynaptic connections with pyramidal (Pyr) and fast-spiking (FS) neurons. TC EPSCs on FS neurons were larger and showed steeper short-term depression in response to repetitive stimulation than those on Pyr neurons. LGN inputs onto Pyr and FS neurons also differed in postsynaptic receptor composition and organization of presynaptic release sites. Together, our results demonstrate that LGN input onto L4 neurons in mouse V1 have target-specific presynaptic and postsynaptic properties. Distinct mechanisms of activation of feedforward excitatory and inhibitory neurons in the main input layer of V1 are likely to endow neurons with different response properties to incoming visual stimuli.

Neural cell adhesion molecule NrCAM regulates Semaphorin 3F-induced dendritic spine remodeling

Neuron-glial related cell adhesion molecule (NrCAM) is a regulator of axon growth and repellent guidance, and has been implicated in autism spectrum disorders. Here a novel postsynaptic role for NrCAM in Semaphorin3F (Sema3F)-induced dendritic spine remodeling was identified in pyramidal neurons of the primary visual cortex (V1). NrCAM localized to dendritic spines of star pyramidal cells in postnatal V1, where it was coexpressed with Sema3F. NrCAM deletion in mice resulted in elevated spine densities on apical dendrites of star pyramidal cells at both postnatal and adult stages, and electron microscopy revealed increased numbers of asymmetric synapses in layer 4 of V1. Whole-cell recordings in cortical slices from NrCAM-null mice revealed increased frequency of mEPSCs in star pyramidal neurons. Recombinant Sema3F-Fc protein induced spine retraction on apical dendrites of wild-type, but not NrCAM-null cortical neurons in culture, while re-expression of NrCAM rescued the spine retraction response. NrCAM formed a complex in brain with Sema3F receptor subunits Neuropilin-2 (Npn-2) and PlexinA3 (PlexA3) through an Npn-2-binding sequence (TARNER) in the extracellular Ig1 domain. A trans heterozygous genetic interaction test demonstrated that Sema3F and NrCAM pathways interacted in vivo to regulate spine density in star pyramidal neurons. These findings reveal NrCAM as a novel postnatal regulator of dendritic spine density in cortical pyramidal neurons, and an integral component of the Sema3F receptor complex. The results implicate NrCAM as a contributor to excitatory/inhibitory balance in neocortical circuits.

Physiology and Impact of Horizontal Connections in Rat Neocortex

Cortical information processing at the cellular level has predominantly been studied in local networks, which are dominated by strong vertical connectivity between layers. However, recent studies suggest that the bulk of axons targeting pyramidal neurons most likely originate from outside this local range, emphasizing the importance of horizontal connections. We mapped a subset of these connections to L5B pyramidal neurons in rat somatosensory cortex with photostimulation, identifying intact projections up to a lateral distance of 2 mm. Our estimates of the spatial distribution of cells presynaptic to L5B pyramids support the idea that the majority is located outside the local volume. The synaptic physiology of horizontal connections does not differ markedly from that of local connections, whereas the layer and cell-type-dependent pattern of innervation does. Apart from L2/3, L6A provides a strong source of horizontal connections. Implementing our data into a spiking neuronal network model shows that more horizontal connections promote robust asynchronous ongoing activity states and reduce noise correlations in stimulus-induced activity.

Very-long-range disynaptic V1 connections through layer 6 pyramidal neurons revealed by transneuronal tracing with rabies virus

Neurons in primary visual cortex (V1) integrate across the representation of the visual field through networks of long-range projecting pyramidal neurons. These projections, which originate from within V1 and through feedback from higher visual areas, are likely to play a key role in such visual processes as low contrast facilitation and extraclassical surround suppression. The extent of the visual field representation covered by feedback is generally much larger than that covered through monosynaptic horizontal connections within V1, and, although it may be possible that multisynaptic horizontal connections across V1 could also lead to more widespread spatial integration, nothing is known regarding such circuits. In this study, we used injections of the CVS-11 strain of rabies virus to examine disynaptic long-range horizontal connections within macaque monkey V1. Injections were made around the representation of 5° eccentricity in the lower visual field. Along the opercular surface of V1, we found that the majority of connected neurons extended up to 8 mm in most layers, consistent with twice the typically reported distances of monosynaptic connections. In addition, mainly in layer 6, a steady presence of connected neurons within V1 was observed up to 16 mm away. A relatively high percentage of these connected neurons had large-diameter somata characteristic of Meynert cells, which are known to project as far as 8 mm individually. Several neurons, predominantly in layer 6, were also found deep within the calcarine sulcus, reaching as far as 20° of eccentricity, based on estimates, and extending well into the upper visual field representation. Thus, our anatomical results provide evidence for a wide-ranging disynaptic circuit within V1, mediated largely through layer 6, that accounts for integration across a large region of the visual field.

Layer 6 corticothalamic neurons activate a cortical output layer, layer 5a

Layer 6 corticothalamic neurons are thought to modulate incoming sensory information via their intracortical axons targeting the major thalamorecipient layer of the neocortex, layer 4, and via their long-range feedback projections to primary sensory thalamic nuclei. However, anatomical reconstructions of individual layer 6 corticothalamic (L6 CT) neurons include examples with axonal processes ramifying within layer 5, and the relative input of the overall population of L6 CT neurons to layers 4 and 5 is not well understood. We compared the synaptic impact of L6 CT cells on neurons in layers 4 and 5. We found that the axons of L6 CT neurons densely ramified within layer 5a in both visual and somatosensory cortices of the mouse. Optogenetic activation of corticothalamic neurons generated large EPSPs in pyramidal neurons in layer 5a. In contrast, excitatory neurons in layer 4 exhibited weak excitation or disynaptic inhibition. Fast-spiking parvalbumin-positive cells in both layer 5a and layer 4 were also strongly activated by L6 CT neurons. The overall effect of L6 CT activation was to suppress layer 4 while eliciting action potentials in layer 5a pyramidal neurons. Together, our data indicate that L6 CT neurons strongly activate an output layer of the cortex.

Structural determinants underlying the high efficacy of synaptic transmission and plasticity at synaptic boutons in layer 4 of the adult rat 'barrel cortex'

Excitatory layer 4 (L4) neurons in the 'barrel field' of the rat somatosensory cortex represent an important component in thalamocortical information processing. However, no detailed information exists concerning the quantitative geometry of synaptic boutons terminating on these neurons. Thus, L4 synaptic boutons were investigated using serial ultrathin sections and subsequent quantitative 3D reconstructions. In particular, parameters representing structural correlates of synaptic transmission and plasticity such as the number, size and distribution of pre- and postsynaptic densities forming the active zone (AZ) and of the three functionally defined pools of synaptic vesicles were analyzed. L4 synaptic boutons varied substantially in shape and size; the majority had a single, but large AZ with opposing pre- and postsynaptic densities that matched perfectly in size and position. More than a third of the examined boutons showed perforations of the postsynaptic density. Synaptic boutons contained on average a total pool of 561 ± 108 vesicles, with ~5% constituting the putative readily releasable, ~23% the recycling, and the remainder the reserve pool. These pools are comparably larger than other characterized central synapses. Synaptic complexes were surrounded by a dense network of fine astrocytic processes that reached as far as the synaptic cleft, thus regulating the temporal and spatial glutamate concentration, and thereby shaping the unitary EPSP amplitude. In summary, the geometry and size of AZs, the comparably large readily releasable and recycling pools, together with the tight astrocytic ensheathment, may explain and contribute to the high release probability, efficacy and modulation of synaptic transmission at excitatory L4 synaptic boutons. Moreover, the structural variability as indicated by the geometry of L4 synaptic boutons, the presence of mitochondria and the size and shape of the AZs strongly suggest that synaptic reliability, strength and plasticity is governed and modulated individually at excitatory L4 synaptic boutons.

The impact of cortical deafferentation on the neocortical slow oscillation

Slow oscillation is the main brain rhythm observed during deep sleep in mammals. Although several studies have demonstrated its neocortical origin, the extent of the thalamic contribution is still a matter of discussion. Using electrophysiological recordings in vivo on cats and computational modeling, we found that the local thalamic inactivation or the complete isolation of the neocortical slabs maintained within the brain dramatically reduced the expression of slow and fast oscillations in affected cortical areas. The slow oscillation began to recover 12 h after thalamic inactivation. The slow oscillation, but not faster activities, nearly recovered after 30 h and persisted for weeks in the isolated slabs. We also observed an increase of the membrane potential fluctuations recorded in vivo several hours after thalamic inactivation. Mimicking this enhancement in a network computational model with an increased postsynaptic activity of long-range intracortical afferents or scaling K(+) leak current, but not several other Na(+) and K(+) intrinsic currents was sufficient for recovering the slow oscillation. We conclude that, in the intact brain, the thalamus contributes to the generation of cortical active states of the slow oscillation and mediates its large-scale synchronization. Our study also suggests that the deafferentation-induced alterations of the sleep slow oscillation can be counteracted by compensatory intracortical mechanisms and that the sleep slow oscillation is a fundamental and intrinsic state of the neocortex.