Geometric and functional organization of cortical circuits

Overabundant endocannabinoids in neurons are detrimental to cognitive function

2-Arachidonoylglycerol (2-AG) is the most prevalent endocannabinoid involved in maintaining brain homeostasis. Previous studies have demonstrated that inactivating monoacylglycerol lipase (MAGL), the primary enzyme responsible for degrading 2-AG in the brain, alleviates neuropathology and prevents synaptic and cognitive decline in animal models of neurodegenerative diseases. However, we show that selectively inhibiting 2-AG metabolism in neurons impairs cognitive function in mice. This cognitive impairment appears to result from decreased expression of synaptic proteins and synapse numbers, impaired long-term synaptic plasticity and cortical circuit functional connectivity, and diminished neurogenesis. Interestingly, the synaptic and cognitive deficits induced by neuronal MAGL inactivation can be counterbalanced by inhibiting astrocytic 2-AG metabolism. Transcriptomic analyses reveal that inhibiting neuronal 2-AG degradation leads to widespread changes in expression of genes associated with synaptic function. These findings suggest that crosstalk in 2-AG signaling between astrocytes and neurons is crucial for maintaining synaptic and cognitive functions and that excessive 2-AG in neurons alone is detrimental to cognitive function.

Parallel Synapses with Transmission Nonlinearities Enhance Neuronal Classification Capacity

Cortical neurons often establish multiple synaptic contacts with the same postsynaptic neuron. To avoid functional redundancy of these parallel synapses, it is crucial that each synapse exhibits distinct computational properties. Here we model the current to the soma contributed by each synapse as a sigmoidal transmission function of its presynaptic input, with learnable parameters such as amplitude, slope, and threshold. We evaluate the classification capacity of a neuron equipped with such nonlinear parallel synapses, and show that with a small number of parallel synapses per axon, it substantially exceeds that of the Perceptron. Furthermore, the number of correctly classified data points can increase superlinearly as the number of presynaptic axons grows. When training with an unrestricted number of parallel synapses, our model neuron can effectively implement an arbitrary aggregate transmission function for each axon, constrained only by monotonicity. Nevertheless, successful learning in the model neuron often requires only a small number of parallel synapses. We also apply these parallel synapses in a feedforward neural network trained to classify MNIST images, and show that they can increase the test accuracy. This demonstrates that multiple nonlinear synapses per input axon can substantially enhance a neuron's computational power.

From pixels to connections: exploring in vitro neuron reconstruction software for network graph generation

Digital reconstruction has been instrumental in deciphering how in vitro neuron architecture shapes information flow. Emerging approaches reconstruct neural systems as networks with the aim of understanding their organization through graph theory. Computational tools dedicated to this objective build models of nodes and edges based on key cellular features such as somata, axons, and dendrites. Fully automatic implementations of these tools are readily available, but they may also be purpose-built from specialized algorithms in the form of multi-step pipelines. Here we review software tools informing the construction of network models, spanning from noise reduction and segmentation to full network reconstruction. The scope and core specifications of each tool are explicitly defined to assist bench scientists in selecting the most suitable option for their microscopy dataset. Existing tools provide a foundation for complete network reconstruction, however more progress is needed in establishing morphological bases for directed/weighted connectivity and in software validation.

How spatial omics approaches can be used to map the biological impacts of stress in psychiatric disorders: a perspective, overview and technical guide

Exposure to significant levels of stress and trauma throughout life is a leading risk factor for the development of major psychiatric disorders. Despite this, we do not have a comprehensive understanding of the mechanisms that explain how stress raises psychiatric disorder risk. Stress in humans is complex and produces variable molecular outcomes depending on the stress type, timing, and duration. Deciphering how stress increases disorder risk has consequently been challenging to address with the traditional single-target experimental approaches primarily utilized to date. Importantly, the molecular processes that occur following stress are not fully understood but are needed to find novel treatment targets. Sequencing-based omics technologies, allowing for an unbiased investigation of physiological changes induced by stress, are rapidly accelerating our knowledge of the molecular sequelae of stress at a single-cell resolution. Spatial multi-omics technologies are now also emerging, allowing for simultaneous analysis of functional molecular layers, from epigenome to proteome, with anatomical context. The technology has immense potential to transform our understanding of how disorders develop, which we believe will significantly propel our understanding of how specific risk factors, such as stress, contribute to disease course. Here, we provide our perspective of how we believe these technologies will transform our understanding of the neurobiology of stress, and also provided a technical guide to assist molecular psychiatry and stress researchers who wish to implement spatial omics approaches in their own research. Finally, we identify potential future directions using multi-omics technology in stress research.

Neuronal functional connectivity is impaired in a layer dependent manner near the chronically implanted microelectrodes

Objective

This study aims to reveal longitudinal changes in functional network connectivity within and across different brain structures near the chronically implanted microelectrode. While it is well established that the foreign-body response (FBR) contributes to the gradual decline of the signals recorded from brain implants over time, how does the FBR impact affect the functional stability of neural circuits near implanted Brain-Computer Interfaces (BCIs) remains unknown. This research aims to illuminate how the chronic FBR can alter local neural circuit function and the implications for BCI decoders.

Approach

This study utilized multisite Michigan-style microelectrodes that span all cortical layers and the hippocampal CA1 region to collect spontaneous and visually-evoked electrophysiological activity. Alterations in neuronal activity near the microelectrode were tested assessing cross-frequency synchronization of LFP and spike entrainment to LFP oscillatory activity throughout 16 weeks after microelectrode implantation.

Main Results

The study found that cortical layer 4, the input-receiving layer, maintained activity over the implantation time. However, layers 2/3 rapidly experienced severe impairment, leading to a loss of proper intralaminar connectivity in the downstream output layers 5/6. Furthermore, the impairment of interlaminar connectivity near the microelectrode was unidirectional, showing decreased connectivity from Layers 2/3 to Layers 5/6 but not the reverse direction. In the hippocampus, CA1 neurons gradually became unable to properly entrain to the surrounding LFP oscillations.

Significance

This study provides a detailed characterization of network connectivity dysfunction over long-term microelectrode implantation periods. This new knowledge could contribute to the development of targeted therapeutic strategies aimed at improving the health of the tissue surrounding brain implants and potentially inform engineering of adaptive decoders as the FBR progresses. Our study's understanding of the dynamic changes in the functional network over time opens the door to developing interventions for improving the long-term stability and performance of intracortical microelectrodes.

Cyclic structure with cellular precision in a vertebrate sensorimotor neural circuit

Neuronal wiring diagrams reconstructed by electron microscopy1,2,3,4,5 pose new questions about the organization of nervous systems following the time-honored tradition of cross-species comparisons.6,7 The C. elegans connectome has been conceptualized as a sensorimotor circuit that is approximately feedforward,8,9,10,11 starting from sensory neurons proceeding to interneurons and ending with motor neurons. Overrepresentation of a 3-cell motif often known as the "feedforward loop" has provided further evidence for feedforwardness.10,12 Here, we contrast with another sensorimotor wiring diagram that was recently reconstructed from a larval zebrafish brainstem.13 We show that the 3-cycle, another 3-cell motif, is highly overrepresented in the oculomotor module of this wiring diagram. This is a first for any neuronal wiring diagram reconstructed by electron microscopy, whether invertebrate12,14 or mammalian.15,16,17 The 3-cycle of cells is "aligned" with a 3-cycle of neuronal groups in a stochastic block model (SBM)18 of the oculomotor module. However, the cellular cycles exhibit more specificity than can be explained by the group cycles-recurrence to the same neuron is surprisingly common. Cyclic structure could be relevant for theories of oculomotor function that depend on recurrent connectivity. The cyclic structure coexists with the classic vestibulo-ocular reflex arc for horizontal eye movements,19 and could be relevant for recurrent network models of temporal integration by the oculomotor system.20,21.

Single-neuron analysis of dendrites and axons reveals the network organization in mouse prefrontal cortex

The structures of dendrites and axons form the basis for the connectivity of neural network, but their precise relationship at single-neuron level remains unclear. Here we report the complete dendrite and axon morphology of nearly 2,000 neurons in mouse prefrontal cortex (PFC). We identified morphological variations of somata, dendrites and axons across laminar layers and PFC subregions and the general rules of somatodendritic scaling with cytoarchitecture. We uncovered 24 morphologically distinguishable dendrite subtypes in 1,515 pyramidal projection neurons and 405 atypical pyramidal projection neurons and spiny stellate neurons with unique axon projection patterns. Furthermore, correspondence analysis among dendrites, local axons and long-range axons revealed coherent morphological changes associated with electrophysiological phenotypes. Finally, integrative dendrite-axon analysis uncovered the organization of potential intra-column, inter-hemispheric and inter-column connectivity among projection neuron types in PFC. Together, our study provides a comprehensive structural repertoire for the reconstruction and analysis of PFC neural network.

Correlated Somatosensory Input in Parvalbumin/Pyramidal Cells in Mouse Motor Cortex

In mammalian cortex, feedforward excitatory connections recruit feedforward inhibition. This is often carried by parvalbumin (PV+) interneurons, which may densely connect to local pyramidal (Pyr) neurons. Whether this inhibition affects all local excitatory cells indiscriminately or is targeted to specific subnetworks is unknown. Here, we test how feedforward inhibition is recruited by using two-channel circuit mapping to excite cortical and thalamic inputs to PV+ interneurons and Pyr neurons to mouse primary vibrissal motor cortex (M1). Single Pyr and PV+ neurons receive input from both cortex and thalamus. Connected pairs of PV+ interneurons and excitatory Pyr neurons receive correlated cortical and thalamic inputs. While PV+ interneurons are more likely to form local connections to Pyr neurons, Pyr neurons are much more likely to form reciprocal connections with PV+ interneurons that inhibit them. This suggests that Pyr and PV ensembles may be organized based on their local and long-range connections, an organization that supports the idea of local subnetworks for signal transduction and processing. Excitatory inputs to M1 can thus target inhibitory networks in a specific pattern which permits recruitment of feedforward inhibition to specific subnetworks within the cortical column.

Evaluating spatial and network properties of NMDA-dependent neuronal connectivity in mixed cortical cultures

A technique combining fluorescence imaging with Ca2+ indicators and single-cell laser scanning photostimulation of caged glutamate (LSPS) allowed identification of functional connections between individual neurons in mixed cultures of rat neocortical cells as well as observation of synchronous spontaneous activity among neurons. LSPS performed on large numbers of neurons yielded maps of functional connections between neurons and allowed calculation of neuronal network parameters. LSPS also provided an indirect measure of excitability of neurons targeted for photostimulation. By repeating LSPS sessions with the same neurons, stability of connections and change in the number and strength of connections were also determined. Experiments were conducted in the presence of bicuculline to study in detail the properties of excitatory neurotransmission. The AMPA receptor inhibitor, 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX), abolished synchronous neuronal activity but had no effect on connections mapped by LSPS. In contrast, the NMDA receptor inhibitor, 2-Amino-5-phosphono-pentanoic acid (APV), dramatically decreased the number of functional connections between neurons while also affecting synchronous spontaneous activity. Functional connections were also decreased by increasing extracellular Mg2+ concentration. These data demonstrated that LSPS mapping interrogates NMDA receptor-dependent connectivity between neurons in the network. In addition, a GluN2A-specific inhibitor, NVP-AAM077, decreased the number and strength of connections between neurons as well as neuron excitability. Conversely, the GluN2A-specific positive modulator, GNE-0723, increased these same properties. These data showed that LSPS can be used to directly study perturbations in the properties of NMDA receptor-dependent connectivity in neuronal networks. This approach should be applicable in a wide variety of in vitro and in vivo experimental preparations.

Orientation and direction tuning align with dendritic morphology and spatial connectivity in mouse visual cortex

The functional properties of neocortical pyramidal cells (PCs), such as direction and orientation selectivity in visual cortex, predominantly derive from their excitatory and inhibitory inputs. For layer 2/3 (L2/3) PCs, the detailed relationship between their functional properties and how they sample and integrate information across cortical space is not fully understood. Here, we study this relationship by combining functional in vivo two-photon calcium imaging, in vitro functional circuit mapping, and dendritic reconstruction of the same L2/3 PCs in mouse visual cortex. Our work reveals direct correlations between dendritic morphology and functional input connectivity and the orientation as well as direction tuning of L2/3 PCs. First, the apical dendritic tree is elongated along the postsynaptic preferred orientation, considering the representation of visual space in the cortex as determined by its retinotopic organization. Additionally, sharply orientation-tuned cells show a less complex apical tree compared with broadly tuned cells. Second, in direction-selective L2/3 PCs, the spatial distribution of presynaptic partners is offset from the soma opposite to the preferred direction. Importantly, although the presynaptic excitatory and inhibitory input distributions spatially overlap on average, the excitatory input distribution is spatially skewed along the preferred direction, in contrast to the inhibitory distribution. Finally, the degree of asymmetry is positively correlated with the direction selectivity of the postsynaptic L2/3 PC. These results show that the dendritic architecture and the spatial arrangement of excitatory and inhibitory presynaptic cells of L2/3 PCs play important roles in shaping their orientation and direction tuning.

Synaptic connectivity to L2/3 of primary visual cortex measured by two-photon optogenetic stimulation

Understanding cortical microcircuits requires thorough measurement of physiological properties of synaptic connections formed within and between diverse subclasses of neurons. Towards this goal, we combined spatially precise optogenetic stimulation with multicellular recording to deeply characterize intralaminar and translaminar monosynaptic connections to supragranular (L2/3) neurons in the mouse visual cortex. The reliability and specificity of multiphoton optogenetic stimulation were measured across multiple Cre lines, and measurements of connectivity were verified by comparison to paired recordings and targeted patching of optically identified presynaptic cells. With a focus on translaminar pathways, excitatory and inhibitory synaptic connections from genetically defined presynaptic populations were characterized by their relative abundance, spatial profiles, strength, and short-term dynamics. Consistent with the canonical cortical microcircuit, layer 4 excitatory neurons and interneurons within L2/3 represented the most common sources of input to L2/3 pyramidal cells. More surprisingly, we also observed strong excitatory connections from layer 5 intratelencephalic neurons and potent translaminar inhibition from multiple interneuron subclasses. The hybrid approach revealed convergence to and divergence from excitatory and inhibitory neurons within and across cortical layers. Divergent excitatory connections often spanned hundreds of microns of horizontal space. In contrast, divergent inhibitory connections were more frequently measured from postsynaptic targets near each other.

A Kalirin missense mutation enhances dendritic RhoA signaling and leads to regression of cortical dendritic arbors across development

Normally, dendritic size is established prior to adolescence and then remains relatively constant into adulthood due to a homeostatic balance between growth and retraction pathways. However, schizophrenia is characterized by accelerated reductions of cerebral cortex gray matter volume and onset of clinical symptoms during adolescence, with reductions in layer 3 pyramidal neuron dendritic length, complexity, and spine density identified in multiple cortical regions postmortem. Nogo receptor 1 (NGR1) activation of the GTPase RhoA is a major pathway restricting dendritic growth in the cerebral cortex. We show that the NGR1 pathway is stimulated by OMGp and requires the Rho guanine nucleotide exchange factor Kalirin-9 (KAL9). Using a genetically encoded RhoA sensor, we demonstrate that a naturally occurring missense mutation in Kalrn, KAL-PT, that was identified in a schizophrenia cohort, confers enhanced RhoA activitation in neuronal dendrites compared to wild-type KAL. In mice containing this missense mutation at the endogenous locus, there is an adolescent-onset reduction in dendritic length and complexity of layer 3 pyramidal neurons in the primary auditory cortex. Spine density per unit length of dendrite is unaffected. Early adult mice with these structural deficits exhibited impaired detection of short gap durations. These findings provide a neuropsychiatric model of disease capturing how a mild genetic vulnerability may interact with normal developmental processes such that pathology only emerges around adolescence. This interplay between genetic susceptibility and normal adolescent development, both of which possess inherent individual variability, may contribute to heterogeneity seen in phenotypes in human neuropsychiatric disease.

Cross-Streams Through the Ventral Posteromedial Thalamic Nucleus to Convey Vibrissal Information

Whisker detection is crucial to adapt to the environment for some animals, but how the nervous system processes and integrates whisker information is still an open question. It is well-known that two main parallel pathways through Ventral posteromedial thalamic nucleus (VPM) ascend to the barrel cortex, and classical theory suggests that the cross-talk from trigeminal nucleus interpolaris (Sp5i) to principal nucleus (Pr5) between the main parallel pathways contributes to the multi-whisker integration in barrel columns. Moreover, some studies suggest there are other cross-streams between the parallel pathways. To confirm their existence, in this study we used a dual-viral labeling strategy and high-resolution, large-volume light imaging to get the complete morphology of individual VPM neurons and trace their projections. We found some new thalamocortical projections from the ventral lateral part of VPM (VPMvl) to barrel columns. In addition, the retrograde-viral labeling and imaging results showed there were the large trigeminothalamic projections from Sp5i to the dorsomedial section of VPM (VPMdm). Our results reveal new cross-streams between the parallel pathways through VPM, which may involve the execution of multi-whisker integration in barrel columns.

Mechanisms Underlying Target Selectivity for Cell Types and Subcellular Domains in Developing Neocortical Circuits

The cerebral cortex contains numerous neuronal cell types, distinguished by their molecular identity as well as their electrophysiological and morphological properties. Cortical function is reliant on stereotyped patterns of synaptic connectivity and synaptic function among these neuron types, but how these patterns are established during development remains poorly understood. Selective targeting not only of different cell types but also of distinct postsynaptic neuronal domains occurs in many brain circuits and is directed by multiple mechanisms. These mechanisms include the regulation of axonal and dendritic guidance and fine-scale morphogenesis of pre- and postsynaptic processes, lineage relationships, activity dependent mechanisms and intercellular molecular determinants such as transmembrane and secreted molecules, many of which have also been implicated in neurodevelopmental disorders. However, many studies of synaptic targeting have focused on circuits in which neuronal processes target different lamina, such that cell-type-biased connectivity may be confounded with mechanisms of laminar specificity. In the cerebral cortex, each cortical layer contains cell bodies and processes from intermingled neuronal cell types, an arrangement that presents a challenge for the development of target-selective synapse formation. Here, we address progress and future directions in the study of cell-type-biased synaptic targeting in the cerebral cortex. We highlight challenges to identifying developmental mechanisms generating stereotyped patterns of intracortical connectivity, recent developments in uncovering the determinants of synaptic target selection during cortical synapse formation, and current gaps in the understanding of cortical synapse specificity.

The cell adhesion molecule Sdk1 shapes assembly of a retinal circuit that detects localized edges

Nearly 50 different mouse retinal ganglion cell (RGC) types sample the visual scene for distinct features. RGC feature selectivity arises from their synapses with a specific subset of amacrine (AC) and bipolar cell (BC) types, but how RGC dendrites arborize and collect input from these specific subsets remains poorly understood. Here we examine the hypothesis that RGCs employ molecular recognition systems to meet this challenge. By combining calcium imaging and type-specific histological stains, we define a family of circuits that express the recognition molecule Sidekick-1 (Sdk1), which include a novel RGC type (S1-RGC) that responds to local edges. Genetic and physiological studies revealed that Sdk1 loss selectively disrupts S1-RGC visual responses, which result from a loss of excitatory and inhibitory inputs and selective dendritic deficits on this neuron. We conclude that Sdk1 shapes dendrite growth and wiring to help S1-RGCs become feature selective.

MAP2 is differentially phosphorylated in schizophrenia, altering its function

Schizophrenia (Sz) is a highly polygenic disorder, with common, rare, and structural variants each contributing only a small fraction of overall disease risk. Thus, there is a need to identify downstream points of convergence that can be targeted with therapeutics. Reduction of microtubule-associated protein 2 (MAP2) immunoreactivity (MAP2-IR) is present in individuals with Sz, despite no change in MAP2 protein levels. MAP2 is phosphorylated downstream of multiple receptors and kinases identified as Sz risk genes, altering its immunoreactivity and function. Using an unbiased phosphoproteomics approach, we quantified 18 MAP2 phosphopeptides, 9 of which were significantly altered in Sz subjects. Network analysis grouped MAP2 phosphopeptides into three modules, each with a distinct relationship to dendritic spine loss, synaptic protein levels, and clinical function in Sz subjects. We then investigated the most hyperphosphorylated site in Sz, phosphoserine1782 (pS1782). Computational modeling predicted phosphorylation of S1782 reduces binding of MAP2 to microtubules, which was confirmed experimentally. We generated a transgenic mouse containing a phosphomimetic mutation at S1782 (S1782E) and found reductions in basilar dendritic length and complexity along with reduced spine density. Because only a limited number of MAP2 interacting proteins have been previously identified, we combined co-immunoprecipitation with mass spectrometry to characterize the MAP2 interactome in mouse brain. The MAP2 interactome was enriched for proteins involved in protein translation. These associations were shown to be functional as overexpression of wild type and phosphomimetic MAP2 reduced protein synthesis in vitro. Finally, we found that Sz subjects with low MAP2-IR had reductions in the levels of synaptic proteins relative to nonpsychiatric control (NPC) subjects and to Sz subjects with normal and MAP2-IR, and this same pattern was recapitulated in S1782E mice. These findings suggest a new conceptual framework for Sz-that a large proportion of individuals have a "MAP2opathy"-in which MAP function is altered by phosphorylation, leading to impairments of neuronal structure, synaptic protein synthesis, and function.

Stimulus Feature-Specific Control of Layer 2/3 Subthreshold Whisker Responses by Layer 4 in the Mouse Primary Somatosensory Cortex

In the barrel field of the rodent primary somatosensory cortex (S1bf), excitatory cells in layer 2/3 (L2/3) display sparse firing but reliable subthreshold response during whisker stimulation. Subthreshold responses encode specific features of the sensory stimulus, for example, the direction of whisker deflection. According to the canonical model for the flow of sensory information across cortical layers, activity in L2/3 is driven by layer 4 (L4). However, L2/3 cells receive excitatory inputs from other regions, raising the possibility that L4 partially drives L2/3 during whisker stimulation. To test this hypothesis, we combined patch-clamp recordings from L2/3 pyramidal neurons in S1bf with selective optogenetic inhibition of L4 during passive whisker stimulation in both anesthetized and awake head-restrained mice. We found that L4 optogenetic inhibition did not abolish the subthreshold whisker-evoked response nor it affected spontaneous membrane potential fluctuations of L2/3 neurons. However, L4 optogenetic inhibition decreased L2/3 subthreshold responses to whisker deflections in the preferred direction, and it increased L2/3 responses to stimuli in the nonpreferred direction, leading to a change in the direction tuning. Our results contribute to reveal the circuit mechanisms underlying the processing of sensory information in the rodent S1bf.

Neuron tracing and quantitative analyses of dendritic architecture reveal symmetrical three-way-junctions and phenotypes of git-1 in C. elegans

Complex dendritic trees are a distinctive feature of neurons. Alterations to dendritic morphology are associated with developmental, behavioral and neurodegenerative changes. The highly-arborized PVD neuron of C. elegans serves as a model to study dendritic patterning; however, quantitative, objective and automated analyses of PVD morphology are missing. Here, we present a method for neuronal feature extraction, based on deep-learning and fitting algorithms. The extracted neuronal architecture is represented by a database of structural elements for abstracted analysis. We obtain excellent automatic tracing of PVD trees and uncover that dendritic junctions are unevenly distributed. Surprisingly, these junctions are three-way-symmetrical on average, while dendritic processes are arranged orthogonally. We quantify the effect of mutation in git-1, a regulator of dendritic spine formation, on PVD morphology and discover a localized reduction in junctions. Our findings shed new light on PVD architecture, demonstrating the effectiveness of our objective analyses of dendritic morphology and suggest molecular control mechanisms.

Spatially structured inhibition defined by polarized parvalbumin interneuron axons promotes head direction tuning

In cortical microcircuits, it is generally assumed that fast-spiking parvalbumin interneurons mediate dense and nonselective inhibition. Some reports indicate sparse and structured inhibitory connectivity, but the computational relevance and the underlying spatial organization remain unresolved. In the rat superficial presubiculum, we find that inhibition by fast-spiking interneurons is organized in the form of a dominant super-reciprocal microcircuit motif where multiple pyramidal cells recurrently inhibit each other via a single interneuron. Multineuron recordings and subsequent 3D reconstructions and analysis further show that this nonrandom connectivity arises from an asymmetric, polarized morphology of fast-spiking interneuron axons, which individually cover different directions in the same volume. Network simulations assuming topographically organized input demonstrate that such polarized inhibition can improve head direction tuning of pyramidal cells in comparison to a "blanket of inhibition." We propose that structured inhibition based on asymmetrical axons is an overarching spatial connectivity principle for tailored computation across brain regions.

Spine dynamics in the brain, mental disorders and artificial neural networks

In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements: they also embody algorithms that implement the brain's ability to learn from experience and cope with new challenges. Importantly, they exhibit structural dynamics that depend on activity, excitatory input and inhibitory input (synaptic plasticity or 'extrinsic' dynamics) and dynamics independent of activity ('intrinsic' dynamics), both of which are subject to neuromodulatory influences and reinforcers such as dopamine. Here we succinctly review extrinsic and intrinsic dynamics, compare these with parallels in machine learning where they exist, describe the importance of intrinsic dynamics for memory management and adaptation, and speculate on how disruption of extrinsic and intrinsic dynamics may give rise to mental disorders. Throughout, we also highlight algorithmic features of spine dynamics that may be relevant to future artificial intelligence developments.

Structure and function of a neocortical synapse

In 1986, electron microscopy was used to reconstruct by hand the entire nervous system of a roundworm, the nematode Caenorhabditis elegans¹. Since this landmark study, high-throughput electron-microscopic techniques have enabled reconstructions of much larger mammalian brain circuits at synaptic resolution^2,3. Nevertheless, it remains unknown how the structure of a synapse relates to its physiological transmission strength-a key limitation for inferring brain function from neuronal wiring diagrams. Here we combine slice electrophysiology of synaptically connected pyramidal neurons in the mouse somatosensory cortex with correlated light microscopy and high-resolution electron microscopy of all putative synaptic contacts between the recorded neurons. We find a linear relationship between synapse size and strength, providing the missing link in assigning physiological weights to synapses reconstructed from electron microscopy. Quantal analysis also reveals that synapses contain at least 2.7 neurotransmitter-release sites on average. This challenges existing release models and provides further evidence that neocortical synapses operate with multivesicular release^4-6, suggesting that they are more complex computational devices than thought, and therefore expanding the computational power of the canonical cortical microcircuitry.

Multiple timescales of neural dynamics and integration of task-relevant signals across cortex

A long-lasting challenge in neuroscience has been to find a set of principles that could be used to organize the brain into distinct areas with specific functions. Recent studies have proposed the orderly progression in the time constants of neural dynamics as an organizational principle of cortical computations. However, relationships between these timescales and their dependence on response properties of individual neurons are unknown, making it impossible to determine how mechanisms underlying such a computational principle are related to other aspects of neural processing. Here, we developed a comprehensive method to simultaneously estimate multiple timescales in neuronal dynamics and integration of task-relevant signals along with selectivity to those signals. By applying our method to neural and behavioral data during a dynamic decision-making task, we found that most neurons exhibited multiple timescales in their response, which consistently increased from parietal to prefrontal and cingulate cortex. While predicting rates of behavioral adjustments, these timescales were not correlated across individual neurons in any cortical area, resulting in independent parallel hierarchies of timescales. Additionally, none of these timescales depended on selectivity to task-relevant signals. Our results not only suggest the existence of multiple canonical mechanisms for increasing timescales of neural dynamics across cortex but also point to additional mechanisms that allow decorrelation of these timescales to enable more flexibility.

Spatiotemporal constraints on optogenetic inactivation in cortical circuits

Optogenetics allows manipulations of genetically and spatially defined neuronal populations with excellent temporal control. However, neurons are coupled with other neurons over multiple length scales, and the effects of localized manipulations thus spread beyond the targeted neurons. We benchmarked several optogenetic methods to inactivate small regions of neocortex. Optogenetic excitation of GABAergic neurons produced more effective inactivation than light-gated ion pumps. Transgenic mice expressing the light-dependent chloride channel GtACR1 produced the most potent inactivation. Generally, inactivation spread substantially beyond the photostimulation light, caused by strong coupling between cortical neurons. Over some range of light intensity, optogenetic excitation of inhibitory neurons reduced activity in these neurons, together with pyramidal neurons, a signature of inhibition-stabilized neural networks ('paradoxical effect'). The offset of optogenetic inactivation was followed by rebound excitation in a light dose-dependent manner, limiting temporal resolution. Our data offer guidance for the design of in vivo optogenetics experiments.

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.

Self-organization of modular network architecture by activity-dependent neuronal migration and outgrowth

The spatial distribution of neurons and activity-dependent neurite outgrowth shape long-range interaction, recurrent local connectivity and the modularity in neuronal networks. We investigated how this mesoscale architecture develops by interaction of neurite outgrowth, cell migration and activity in cultured networks of rat cortical neurons and show that simple rules can explain variations of network modularity. In contrast to theoretical studies on activity-dependent outgrowth but consistent with predictions for modular networks, spontaneous activity and the rate of synchronized bursts increased with clustering, whereas peak firing rates in bursts increased in highly interconnected homogeneous networks. As Ca²⁺ influx increased exponentially with increasing network recruitment during bursts, its modulation was highly correlated to peak firing rates. During network maturation, long-term estimates of Ca²⁺ influx showed convergence, even for highly different mesoscale architectures, neurite extent, connectivity, modularity and average activity levels, indicating homeostatic regulation towards a common set-point of Ca²⁺ influx.

Circuit asymmetries underlie functional lateralization in the mouse auditory cortex

The left hemisphere's dominance in processing social communication has been known for over a century, but the mechanisms underlying this lateralized cortical function are poorly understood. Here, we compare the structure, function, and development of each auditory cortex (ACx) in the mouse to look for specializations that may underlie lateralization. Using Fos brain volume imaging, we found greater activation in the left ACx in response to vocalizations, while the right ACx responded more to frequency sweeps. In vivo recordings identified hemispheric differences in spectrotemporal selectivity, reinforcing their functional differences. We then compared the synaptic connectivity within each hemisphere and discovered lateralized circuit-motifs that are hearing experience-dependent. Our results suggest a specialist role for the left ACx, focused on facilitating the detection of specific vocalization features, while the right ACx is a generalist with the ability to integrate spectrotemporal features more broadly.

Fundamental bounds on learning performance in neural circuits

How does the size of a neural circuit influence its learning performance? Larger brains tend to be found in species with higher cognitive function and learning ability. Intuitively, we expect the learning capacity of a neural circuit to grow with the number of neurons and synapses. We show how adding apparently redundant neurons and connections to a network can make a task more learnable. Consequently, large neural circuits can either devote connectivity to generating complex behaviors or exploit this connectivity to achieve faster and more precise learning of simpler behaviors. However, we show that in a biologically relevant setting where synapses introduce an unavoidable amount of noise, there is an optimal size of network for a given task. Above the optimal network size, the addition of neurons and synaptic connections starts to impede learning performance. This suggests that the size of brain circuits may be constrained by the need to learn efficiently with unreliable synapses and provides a hypothesis for why some neurological learning deficits are associated with hyperconnectivity. Our analysis is independent of specific learning rules and uncovers fundamental relationships between learning rate, task performance, network size, and intrinsic noise in neural circuits.

Positional Strategies for Connection Specificity and Synaptic Organization in Spinal Sensory-Motor Circuits

Proprioceptive sensory axons in the spinal cord form selective connections with motor neuron partners, but the strategies that confer such selectivity remain uncertain. We show that muscle-specific sensory axons project to motor neurons along topographically organized angular trajectories and that motor pools exhibit diverse dendritic arbors. On the basis of spatial constraints on axo-dendritic interactions, we propose positional strategies that can account for sensory-motor connectivity and synaptic organization. These strategies rely on two patterning principles. First, the degree of axo-dendritic overlap reduces the number of potential post-synaptic partners. Second, a close correlation between the small angle of axo-dendritic approach and the formation of synaptic clusters imposes specificity of connections when sensory axons intersect multiple motor pools with overlapping dendritic arbors. Our study identifies positional strategies with prominent roles in the organization of spinal sensory-motor circuits.

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Morphological Diversity Strongly Constrains Synaptic Connectivity and Plasticity

Synaptic connectivity between neurons is naturally constrained by the anatomical overlap of neuronal arbors, the space on the axon available for synapses, and by physiological mechanisms that form synapses at a subset of potential synapse locations. What is not known is how these constraints impact emergent connectivity in a circuit with diverse morphologies. We investigated the role of morphological diversity within and across neuronal types on emergent connectivity in a model of neocortical microcircuitry. We found that the average overlap between the dendritic and axonal arbors of different types of neurons determines neuron-type specific patterns of distance-dependent connectivity, severely constraining the space of possible connectomes. However, higher order connectivity motifs depend on the diverse branching patterns of individual arbors of neurons belonging to the same type. Morphological diversity across neuronal types, therefore, imposes a specific structure on first order connectivity, and morphological diversity within neuronal types imposes a higher order structure of connectivity. We estimate that the morphological constraints resulting from diversity within and across neuron types together lead to a 10-fold reduction of the entropy of possible connectivity configurations, revealing an upper bound on the space explored by structural plasticity.

Studies of cortical connectivity using optical circuit mapping methods

An important consideration when probing the function of any neuron is to uncover the source of synaptic input onto the cell, its intrinsic physiology and efferent targets. Over the years, electrophysiological approaches have generated considerable insight into these properties in a variety of cortical neuronal subtypes and circuits. However, as researchers explore neuronal function in greater detail, they are increasingly turning to optical techniques to bridge the gap between local network interactions and behaviour. The application of optical methods has increased dramatically over the past decade, spurred on by the optogenetic revolution. In this review, we provide an account of recent innovations, providing researchers with a primer detailing circuit mapping strategies in the cerebral cortex. We will focus on technical aspects of performing neurotransmitter uncaging and channelrhodopsin-assisted circuit mapping, with the aim of identifying common pitfalls that can negatively influence the collection of reliable data.

Somatosensory maps

Somatosensory areas containing topographic maps of the body surface are a major feature of parietal cortex. In primates, parietal cortex contains four somatosensory areas, each with its own map, with the primary cutaneous map in area 3b. Rodents have at least three parietal somatosensory areas. Maps are not isomorphic to the body surface, but magnify behaviorally important skin regions, which include the hands and face in primates, and the whiskers in rodents. Within each map, intracortical circuits process tactile information, mediate spatial integration, and support active sensation. Maps may also contain fine-scale representations of touch submodalities, or direction of tactile motion. Functional representations are more overlapping than suggested by textbook depictions of map topography. The whisker map in rodent somatosensory cortex is a canonic system for studying cortical microcircuits, sensory coding, and map plasticity. Somatosensory maps are plastic throughout life in response to altered use or injury. This chapter reviews basic principles and recent findings in primate, human, and rodent somatosensory maps.

Circuits in the rodent brainstem that control whisking in concert with other orofacial motor actions

The world view of rodents is largely determined by sensation on two length scales. One is within the animal's peri-personal space; sensorimotor control on this scale involves active movements of the nose, tongue, head, and vibrissa, along with sniffing to determine olfactory clues. The second scale involves the detection of more distant space through vision and audition; these detection processes also impact repositioning of the head, eyes, and ears. Here we focus on orofacial motor actions, primarily vibrissa-based touch but including nose twitching, head bobbing, and licking, that control sensation at short, peri-personal distances. The orofacial nuclei for control of the motor plants, as well as primary and secondary sensory nuclei associated with these motor actions, lie within the hindbrain. The current data support three themes: First, the position of the sensors is determined by the summation of two drive signals, i.e., a fast rhythmic component and an evolving orienting component. Second, the rhythmic component is coordinated across all orofacial motor actions and is phase-locked to sniffing as the animal explores. Reverse engineering reveals that the preBötzinger inspiratory complex provides the reset to the relevant premotor oscillators. Third, direct feedback from somatosensory trigeminal nuclei can rapidly alter motion of the sensors. This feedback is disynaptic and can be tuned by high-level inputs. A holistic model for the coordination of orofacial motor actions into behaviors will encompass feedback pathways through the midbrain and forebrain, as well as hindbrain areas.

Altered Synapse Stability in the Early Stages of Tauopathy

Synapse loss is a key feature of dementia, but it is unclear whether synaptic dysfunction precedes degenerative phases of the disease. Here, we show that even before any decrease in synapse density, there is abnormal turnover of cortical axonal boutons and dendritic spines in a mouse model of tauopathy-associated dementia. Strikingly, tauopathy drives a mismatch in synapse turnover; postsynaptic spines turn over more rapidly, whereas presynaptic boutons are stabilized. This imbalance between pre- and post-synaptic stability coincides with reduced synaptically driven neuronal activity in pre-degenerative stages of the disease.

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Density of cortical axonal boutons and dendritic spines is reduced early in tauopathy

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Abnormalities in synaptic stability and size exist before decreases in synapse density

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Turnover of dendritic spines is elevated, whereas presynaptic boutons are stabilized

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Neuronal activity is reduced at stages associated with mismatched synaptic turnover

Multi-scale account of the network structure of macaque visual cortex

Cortical network structure has been extensively characterized at the level of local circuits and in terms of long-range connectivity, but seldom in a manner that integrates both of these scales. Furthermore, while the connectivity of cortex is known to be related to its architecture, this knowledge has not been used to derive a comprehensive cortical connectivity map. In this study, we integrate data on cortical architecture and axonal tracing data into a consistent multi-scale framework of the structure of one hemisphere of macaque vision-related cortex. The connectivity model predicts the connection probability between any two neurons based on their types and locations within areas and layers. Our analysis reveals regularities of cortical structure. We confirm that cortical thickness decays with cell density. A gradual reduction in neuron density together with the relative constancy of the volume density of synapses across cortical areas yields denser connectivity in visual areas more remote from sensory inputs and of lower structural differentiation. Further, we find a systematic relation between laminar patterns on source and target sides of cortical projections, extending previous findings from combined anterograde and retrograde tracing experiments. Going beyond the classical schemes, we statistically assign synapses to target neurons based on anatomical reconstructions, which suggests that layer 4 neurons receive substantial feedback input. Our derived connectivity exhibits a community structure that corresponds more closely with known functional groupings than previous connectivity maps and identifies layer-specific directional differences in cortico-cortical pathways. The resulting network can form the basis for studies relating structure to neural dynamics in mammalian cortex at multiple scales.

Circuit changes in motor cortex during motor skill learning

Motor cortex is important for motor skill learning, particularly the dexterous skills necessary for our favorite sports and careers. We are especially interested in understanding how plasticity in motor cortex contributes to skill learning. Although human studies have been helpful in understanding the importance of motor cortex in learning skilled tasks, animal models are necessary for achieving a detailed understanding of the circuitry underlying these behaviors and the changes that occur during training. We review data from these models to try to identify sites of plasticity in motor cortex, focusing on rodents asa model system. Rodent neocortex contains well-differentiated motor and sensory regions, as well as neurons expressing similar genetic markers to many of the same circuit components in human cortex. Furthermore, rodents have circuit mapping tools for labeling, targeting, and manipulating these cell types as circuit nodes. Crucially, the projection from rodent primary somatosensory cortex to primary motor cortex is a well-studied corticocortical projection and a model of sensorimotor integration. We first summarize some of the descending pathways involved in making dexterous movements, including reaching. We then describe local and long-range circuitry in mouse motor cortex, summarizing structural and functional changes associated with motor skill acquisition. We then address which specific connections might be responsible for plasticity. For insight into the range of plasticity mechanisms employed by cortex, we review plasticity in sensory systems. The similarities and differences between motor cortex plasticity and critical periods of plasticity in sensory systems are discussed.

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.

Weighing the Evidence in Peters' Rule: Does Neuronal Morphology Predict Connectivity?

Although the importance of network connectivity is increasingly recognized, identifying synapses remains challenging relative to the routine characterization of neuronal morphology. Thus, researchers frequently employ axon-dendrite colocations as proxies of potential connections. This putative equivalence, commonly referred to as Peters' rule, has been recently studied at multiple levels and scales, fueling passionate debates regarding its validity. Our critical literature review identifies three conceptually distinct but often confused applications: inferring neuron type circuitry, predicting synaptic contacts among individual cells, and estimating synapse numbers within neuron pairs. Paradoxically, at the originally proposed cell-type level, Peters' rule remains largely untested. Leveraging Hippocampome.org, we validate and refine the relationship between axonal-dendritic colocations and synaptic circuits, clarifying the interpretation of existing and forthcoming data.

Connectomic Analysis of Brain Networks: Novel Techniques and Future Directions

Brain networks, localized or brain-wide, exist only at the cellular level, i.e., between specific pre- and post-synaptic neurons, which are connected through functionally diverse synapses located at specific points of their cell membranes. "Connectomics" is the emerging subfield of neuroanatomy explicitly aimed at elucidating the wiring of brain networks with cellular resolution and a quantified accuracy. Such data are indispensable for realistic modeling of brain circuitry and function. A connectomic analysis, therefore, needs to identify and measure the soma, dendrites, axonal path, and branching patterns together with the synapses and gap junctions of the neurons involved in any given brain circuit or network. However, because of the submicron caliber, 3D complexity, and high packing density of most such structures, as well as the fact that axons frequently extend over long distances to make synapses in remote brain regions, creating connectomic maps is technically challenging and requires multi-scale approaches, Such approaches involve the combination of the most sensitive cell labeling and analysis methods available, as well as the development of new ones able to resolve individual cells and synapses with increasing high-throughput. In this review, we provide an overview of recently introduced high-resolution methods, which researchers wanting to enter the field of connectomics may consider. It includes several molecular labeling tools, some of which specifically label synapses, and covers a number of novel imaging tools such as brain clearing protocols and microscopy approaches. Apart from describing the tools, we also provide an assessment of their qualities. The criteria we use assess the qualities that tools need in order to contribute to deciphering the key levels of circuit organization. We conclude with a brief future outlook for neuroanatomic research, computational methods, and network modeling, where we also point out several outstanding issues like structure-function relations and the complexity of neural models.

Astrocyte morphology is confined by cortical functional boundaries in mammals ranging from mice to human

Cortical blood flow can be modulated by local activity across a range of species; from barrel-specific blood flow in the rodent somatosensory cortex to the human cortex, where BOLD-fMRI reveals numerous functional borders. However, it appears that the distribution of blood capillaries largely ignores these functional boundaries. Here we report that, by contrast, astrocytes, a major player in blood-flow control, show a striking morphological sensitivity to functional borders. Specifically, we show that astrocyte processes are structurally confined by barrel boundaries in the mouse, by the border of primary auditory cortex in the rat and by layers IIIa/b and Cytochrome Oxidase (CO)-blobs boundaries in the human primary visual cortex. Thus, astrocytes which are critical elements in neuro-hemodynamic coupling show a significant anatomical segregation along functional boundaries across different mammalian species. These results may open a new anatomical marker for delineating functional borders across species, including post-mortem human brains.

DOI:http://dx.doi.org/10.7554/eLife.15915.001

The brain is subdivided into many specialized regions that each has distinct roles. A key aim of brain research is to define the boundaries of these areas. Researchers have attempted to map the transitions between brain regions by identifying changes in the properties and activity of neurons (the cells that transmit information around the brain). However, these approaches cannot be used in some circumstances, such as when studying the living human brain, where only non-invasive experimental techniques can be used.

Cells other than neurons are also present in the brain. Astrocytes (a sub-type of glia cells) are support cells that have an extensive array of branches that project from each astrocyte’s cell body, often giving it a characteristic star shape. Now, using high-magnification light microscopy, Eliam et al. show that the branches of individual astrocytes tend to avoid crossing the borders of brain regions with different roles. These changes in crossing densities define measurable boundaries between such subdivisions.

These density-change boundaries formed by the astrocytes are present in multiple species – mouse, rat and human – and in multiple systems: touch, auditory and visual. This discovery could provide a new window into the functional organization of the brain. It may also offer insights into how the brain optimizes its blood-flow control across different subregions.

The results of this study raise an additional question: is the confinement of astrocytes to single regions of the brain shaped by experience or is it present from birth? Exposing animals to different sensory experiences at different developmental stages will hopefully shed further light on this phenomenon.

DOI:http://dx.doi.org/10.7554/eLife.15915.002

Stereotyped spatial patterns of functional synaptic connectivity in the cerebellar cortex

Motor coordination is supported by an array of highly organized heterogeneous modules in the cerebellum. How incoming sensorimotor information is channeled and communicated between these anatomical modules is still poorly understood. In this study, we used transgenic mice expressing GFP in specific subsets of Purkinje cells that allowed us to target a given set of cerebellar modules. Combining in vitro recordings and photostimulation, we identified stereotyped patterns of functional synaptic organization between the granule cell layer and its main targets, the Purkinje cells, Golgi cells and molecular layer interneurons. Each type of connection displayed position-specific patterns of granule cell synaptic inputs that do not strictly match with anatomical boundaries but connect distant cortical modules. Although these patterns can be adjusted by activity-dependent processes, they were found to be consistent and predictable between animals. Our results highlight the operational rules underlying communication between modules in the cerebellar cortex.

Optogenetic Approaches for Mesoscopic Brain Mapping

Recent advances in identifying genetically unique neuronal proteins has revolutionized the study of brain circuitry. Researchers are now able to insert specific light-sensitive proteins (opsins) into a wide range of specific cell types via viral injections or by breeding transgenic mice. These opsins enable the activation, inhibition, or modulation of neuronal activity with millisecond control within distinct brain regions defined by genetic markers. Here we present a useful guide to implement this technique into any lab. We first review the materials needed and practical considerations and provide in-depth instructions for acute surgeries in mice. We conclude with all-optical mapping techniques for simultaneous recording and manipulation of population activity of many neurons in vivo by combining arbitrary point optogenetic stimulation and regional voltage-sensitive dye imaging. It is our intent to make these methods available to anyone wishing to use them.

Principles of connectivity among morphologically defined cell types in adult neocortex

Since the work of Ramón y Cajal in the late 19th and early 20th centuries, neuroscientists have speculated that a complete understanding of neuronal cell types and their connections is key to explaining complex brain functions. However, a complete census of the constituent cell types and their wiring diagram in mature neocortex remains elusive. By combining octuple whole-cell recordings with an optimized avidin-biotin-peroxidase staining technique, we carried out a morphological and electrophysiological census of neuronal types in layers 1, 2/3, and 5 of mature neocortex and mapped the connectivity between more than 11,000 pairs of identified neurons. We categorized 15 types of interneurons, and each exhibited a characteristic pattern of connectivity with other interneuron types and pyramidal cells. The essential connectivity structure of the neocortical microcircuit could be captured by only a few connectivity motifs.

Nogo Receptor Signaling Restricts Adult Neural Plasticity by Limiting Synaptic AMPA Receptor Delivery

Experience-dependent plasticity is limited in the adult brain, and its molecular and cellular mechanisms are poorly understood. Removal of the myelin-inhibiting signaling protein, Nogo receptor (NgR1), restores adult neural plasticity. Here we found that, in NgR1-deficient mice, whisker experience-driven synaptic α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) insertion in the barrel cortex, which is normally complete by 2 weeks after birth, lasts into adulthood. In vivo live imaging by two-photon microscopy revealed more AMPAR on the surface of spines in the adult barrel cortex of NgR1-deficient than on those of wild-type (WT) mice. Furthermore, we observed that whisker stimulation produced new spines in the adult barrel cortex of mutant but not WT mice, and that the newly synthesized spines contained surface AMPAR. These results suggest that Nogo signaling limits plasticity by restricting synaptic AMPAR delivery in coordination with anatomical plasticity.

An algorithm to predict the connectome of neural microcircuits

Experimentally mapping synaptic connections, in terms of the numbers and locations of their synapses and estimating connection probabilities, is still not a tractable task, even for small volumes of tissue. In fact, the six layers of the neocortex contain thousands of unique types of synaptic connections between the many different types of neurons, of which only a handful have been characterized experimentally. Here we present a theoretical framework and a data-driven algorithmic strategy to digitally reconstruct the complete synaptic connectivity between the different types of neurons in a small well-defined volume of tissue—the micro-scale connectome of a neural microcircuit. By enforcing a set of established principles of synaptic connectivity, and leveraging interdependencies between fundamental properties of neural microcircuits to constrain the reconstructed connectivity, the algorithm yields three parameters per connection type that predict the anatomy of all types of biologically viable synaptic connections. The predictions reproduce a spectrum of experimental data on synaptic connectivity not used by the algorithm. We conclude that an algorithmic approach to the connectome can serve as a tool to accelerate experimental mapping, indicating the minimal dataset required to make useful predictions, identifying the datasets required to improve their accuracy, testing the feasibility of experimental measurements, and making it possible to test hypotheses of synaptic connectivity.

Cortical Composition Hierarchy Driven by Spine Proportion Economical Maximization or Wire Volume Minimization

The structure and quantitative composition of the cerebral cortex are interrelated with its computational capacity. Empirical data analyzed here indicate a certain hierarchy in local cortical composition. Specifically, neural wire, i.e., axons and dendrites take each about 1/3 of cortical space, spines and glia/astrocytes occupy each about (1/3)², and capillaries around (1/3)⁴. Moreover, data analysis across species reveals that these fractions are roughly brain size independent, which suggests that they could be in some sense optimal and thus important for brain function. Is there any principle that sets them in this invariant way? This study first builds a model of local circuit in which neural wire, spines, astrocytes, and capillaries are mutually coupled elements and are treated within a single mathematical framework. Next, various forms of wire minimization rule (wire length, surface area, volume, or conduction delays) are analyzed, of which, only minimization of wire volume provides realistic results that are very close to the empirical cortical fractions. As an alternative, a new principle called “spine economy maximization” is proposed and investigated, which is associated with maximization of spine proportion in the cortex per spine size that yields equally good but more robust results. Additionally, a combination of wire cost and spine economy notions is considered as a meta-principle, and it is found that this proposition gives only marginally better results than either pure wire volume minimization or pure spine economy maximization, but only if spine economy component dominates. However, such a combined meta-principle yields much better results than the constraints related solely to minimization of wire length, wire surface area, and conduction delays. Interestingly, the type of spine size distribution also plays a role, and better agreement with the data is achieved for distributions with long tails. In sum, these results suggest that for the efficiency of local circuits wire volume may be more primary variable than wire length or temporal delays, and moreover, the new spine economy principle may be important for brain evolutionary design in a broader context.

Cerebral cortex is an outer layer of the brain in mammals, and it plays a critical part in various cognitive processes such as learning, memory, attention, language, and consciousness. The cerebral cortex contains a number of neuroanatomical parameters whose values are essentially conserved across species and brain sizes, which suggests that these particular parameters are somehow important for brain efficient functioning. This study shows that the fractional volumes of five major cortical components both neuronal and non-neuronal (axons, dendrites, spines, glia/astrocytes, capillaries) are also approximately conserved across mammals, and neural wire (axons and dendrites) occupies the most of cortical space. Moreover, the fractional volumes form a special hierarchy of dependencies, being approximately equal to integer powers of 1/3. Is there any evolutionary principle of cortical organization that would explain these properties? This study finds that there are two different theoretical principles that can provide answers: one standard related to minimization of neural wire fractional volume, and a new proposition associated with economical maximization of spine content. However, the latter principle produces more robust results, which suggests that spine economical maximization is potentially an alternative to the more common “wire minimization” in explaining the cortical layout. Therefore, the current study can become an important contribution to our understanding (or debating) of the main factors influencing the evolution of local cortical circuits in the brain.

DOP-2 D2-Like Receptor Regulates UNC-7 Innexins to Attenuate Recurrent Sensory Motor Neurons during C. elegans Copulation

Neuromodulation of self-amplifying circuits directs context-dependent behavioral executions. Although recurrent networks are found throughout the Caenorhabditis elegans connectome, few reports describe the mechanisms that regulate reciprocal neural activity during complex behavior. We used C. elegans male copulation to dissect how a goal-oriented motor behavior is regulated by recurrently wired sensory-motor neurons. As the male tail presses against the hermaphrodite's vulva, cholinergic and glutamatergic reciprocal innervations of post cloaca sensilla (PCS) neurons (PCA, PCB, and PCC), hook neurons (HOA, HOB), and their postsynaptic sex muscles execute rhythmic copulatory spicule thrusts. These repetitive spicule movements continue until the male shifts off the vulva or genital penetration is accomplished. However, the signaling mechanism that temporally and spatially restricts repetitive intromission attempts to vulva cues was unclear. Here, we report that confinement of spicule insertion attempts to the vulva is facilitated by D2-like receptor modulation of gap-junctions between PCB and the hook sensillum. We isolated a missense mutation in the UNC-7(L) gap-junction isoform, which perturbs DOP-2 signaling in the PCB neuron and its electrical partner, HOA. The glutamate-gated chloride channel AVR-14 is expressed in HOA. Our analysis of the unc-7 mutant allele indicates that when DOP-2 promotes UNC-7 electrical communication, AVR-14-mediated inhibitory signals pass from HOA to PCB. As a consequence, PCB is less receptive to be stimulated by its recurrent synaptic partner, PCA. Behavioral observations suggest that dopamine neuromodulation of UNC-7 ensures attenuation of recursive intromission attempts when the male disengages or is dislodged from the hermaphrodite genitalia.

SIGNIFICANCE STATEMENT

Using C. elegans male copulation as a model, we found that the neurotransmitter dopamine stimulates D2-like receptors in two sensory circuits to terminate futile behavioral loops. The D2-like receptors promote inhibitory electrical junction activity between a chemosensory and a mechanosensory circuit. Therefore, both systems are attenuated and the animal ceases the recursive behavior.

Sidekick 2 directs formation of a retinal circuit that detects differential motion

In the mammalian retina, processes of approximately 70 types of interneurons form specific synapses on roughly 30 types of retinal ganglion cells (RGCs) in a neuropil called the inner plexiform layer. Each RGC type extracts salient features from visual input, which are sent deeper into the brain for further processing. The specificity and stereotypy of synapses formed in the inner plexiform layer account for the feature-detecting ability of RGCs. Here we analyse the development and function of synapses on one mouse RGC type, called the W3B-RGC. These cells have the remarkable property of responding when the timing of the movement of a small object differs from that of the background, but not when they coincide. Such cells, known as local edge detectors or object motion sensors, can distinguish moving objects from a visual scene that is also moving. We show that W3B-RGCs receive strong and selective input from an unusual excitatory amacrine cell type known as VG3-AC (vesicular glutamate transporter 3). Both W3B-RGCs and VG3-ACs express the immunoglobulin superfamily recognition molecule sidekick 2 (Sdk2), and both loss- and gain-of-function studies indicate that Sdk2-dependent homophilic interactions are necessary for the selectivity of the connection. The Sdk2-specified synapse is essential for visual responses of W3B-RGCs: whereas bipolar cells relay visual input directly to most RGCs, the W3B-RGCs receive much of their input indirectly, via the VG3-ACs. This non-canonical circuit introduces a delay into the pathway from photoreceptors in the centre of the receptive field to W3B-RGCs, which could improve their ability to judge the synchrony of local and global motion.