Astrocyte coverage of excitatory synapses correlates to measures of synapse structure and function in ferret primary visual cortex.

Most excitatory synapses in the mammalian brain are contacted or ensheathed by astrocyte processes, forming tripartite synapses. Astrocytes are thought to be critical regulators of the structural and functional dynamics of synapses. While the degree of synaptic coverage by astrocytes is known to vary across brain regions and animal species, the reason for and implications of this variability remains unknown. Further, how astrocyte coverage of synapses relates to in vivo functional properties of individual synapses has not been investigated. Here, we characterized astrocyte coverage of synapses of pyramidal neurons in the ferret visual cortex and, using correlative light and electron microscopy, examined their relationship to synaptic strength and sensory-evoked Ca2+ activity. Nearly, all synapses were contacted by astrocytes, and most were contacted along the axon-spine interface. Structurally, we found that the degree of synaptic astrocyte coverage directly scaled with synapse size and postsynaptic density complexity. Functionally, we found that the amount of astrocyte coverage scaled with how selectively a synapse responds to a particular visual stimulus and, at least for the largest synapses, scaled with the reliability of visual stimuli to evoke postsynaptic Ca2+ events. Our study shows astrocyte coverage is highly correlated with structural metrics of synaptic strength of excitatory synapses in the visual cortex and demonstrates a previously unknown relationship between astrocyte coverage and reliable sensory activation.

Mirrored might: A vision for inhibition.

In this issue of Neuron, Znamenskiy et al.1 unveil functional connection specificity between PV+ inhibitory interneurons and excitatory pyramidal neurons in mouse visual cortex, providing a circuit mechanism for stable amplification of cortical subpopulations.

Efficient Decoding of Large-Scale Neural Population Responses With Gaussian-Process Multiclass Regression.

Neural decoding methods provide a powerful tool for quantifying the information content of neural population codes and the limits imposed by correlations in neural activity. However, standard decoding methods are prone to overfitting and scale poorly to high-dimensional settings. Here, we introduce a novel decoding method to overcome these limitations. Our approach, the gaussian process multiclass decoder (GPMD), is well suited to decoding a continuous low-dimensional variable from high-dimensional population activity and provides a platform for assessing the importance of correlations in neural population codes. The GPMD is a multinomial logistic regression model with a gaussian process prior over the decoding weights. The prior includes hyperparameters that govern the smoothness of each neuron's decoding weights, allowing automatic pruning of uninformative neurons during inference. We provide a variational inference method for fitting the GPMD to data, which scales to hundreds or thousands of neurons and performs well even in data sets with more neurons than trials. We apply the GPMD to recordings from primary visual cortex in three species: monkey, ferret, and mouse. Our decoder achieves state-of-the-art accuracy on all three data sets and substantially outperforms independent Bayesian decoding, showing that knowledge of the correlation structure is essential for optimal decoding in all three species.

Postsynaptic mitochondria are positioned to support functional diversity of dendritic spines.

Postsynaptic mitochondria are critical for the development, plasticity, and maintenance of synaptic inputs. However, their relationship to synaptic structure and functional activity is unknown. We examined a correlative dataset from ferret visual cortex with in vivo two-photon calcium imaging of dendritic spines during visual stimulation and electron microscopy reconstructions of spine ultrastructure, investigating mitochondrial abundance near functionally and structurally characterized spines. Surprisingly, we found no correlation to structural measures of synaptic strength. Instead, we found that mitochondria are positioned near spines with orientation preferences that are dissimilar to the somatic preference. Additionally, we found that mitochondria are positioned near groups of spines with heterogeneous orientation preferences. For a subset of spines with a mitochondrion in the head or neck, synapses were larger and exhibited greater selectivity to visual stimuli than those without a mitochondrion. Our data suggest mitochondria are not necessarily positioned to support the energy needs of strong spines, but rather support the structurally and functionally diverse inputs innervating the basal dendrites of cortical neurons.

Astrocyte coverage of excitatory synapses correlates to measures of synapse structure and function in primary visual cortex.

Most excitatory synapses in the mammalian brain are contacted by astrocytes, forming the tripartite synapse. This interface is thought to be critical for glutamate turnover and structural or functional dynamics of synapses. While the degree of synaptic contact of astrocytes is known to vary across brain regions and animal species, the implications of this variability remain unknown. Furthermore, precisely how astrocyte coverage of synapses relates to in vivo functional properties of individual dendritic spines has yet to be investigated. Here, we characterized perisynaptic astrocyte processes (PAPs) contacting synapses of pyramidal neurons of the ferret visual cortex and, using correlative light and electron microscopy, examined their relationship to synaptic strength and to sensory-evoked Ca2+ activity. Nearly all synapses were contacted by PAPs, and most were contacted along the axon-spine interface (ASI). Structurally, we found that the degree of PAP coverage scaled with synapse size and complexity. Functionally, we found that PAP coverage scaled with the selectivity of Ca2+ responses of individual synapses to visual stimuli and, at least for the largest synapses, scaled with the reliability of visual stimuli to evoke postsynaptic Ca2+ events. Our study shows astrocyte coverage is highly correlated with structural properties of excitatory synapses in the visual cortex and implicates astrocytes as a contributor to reliable sensory activation.

Developmental emergence of sleep rhythms enables long-term memory in Drosophila.

In adulthood, sleep-wake rhythms are one of the most prominent behaviors under circadian control. However, during early life, sleep is spread across the 24-hour day. The mechanism through which sleep rhythms emerge, and consequent advantage conferred to a juvenile animal, is unknown. In the second-instar Drosophila larvae (L2), like in human infants, sleep is not under circadian control. We identify the precise developmental time point when the clock begins to regulate sleep in Drosophila, leading to emergence of sleep rhythms in early third-instars (L3). At this stage, a cellular connection forms between DN1a clock neurons and arousal-promoting Dh44 neurons, bringing arousal under clock control to drive emergence of circadian sleep. Last, we demonstrate that L3 but not L2 larvae exhibit long-term memory (LTM) of aversive cues and that this LTM depends upon deep sleep generated once sleep rhythms begin. We propose that the developmental emergence of circadian sleep enables more complex cognitive processes, including the onset of enduring memories.

Synaptic weights that correlate with presynaptic selectivity increase decoding performance.

The activity of neurons in the visual cortex is often characterized by tuning curves, which are thought to be shaped by Hebbian plasticity during development and sensory experience. This leads to the prediction that neural circuits should be organized such that neurons with similar functional preference are connected with stronger weights. In support of this idea, previous experimental and theoretical work have provided evidence for a model of the visual cortex characterized by such functional subnetworks. A recent experimental study, however, have found that the postsynaptic preferred stimulus was defined by the total number of spines activated by a given stimulus and independent of their individual strength. While this result might seem to contradict previous literature, there are many factors that define how a given synaptic input influences postsynaptic selectivity. Here, we designed a computational model in which postsynaptic functional preference is defined by the number of inputs activated by a given stimulus. Using a plasticity rule where synaptic weights tend to correlate with presynaptic selectivity, and is independent of functional-similarity between pre- and postsynaptic activity, we find that this model can be used to decode presented stimuli in a manner that is comparable to maximum likelihood inference.

Postsynaptic mitochondria are positioned to support functional diversity of dendritic spines.

Postsynaptic mitochondria are critical to the development, plasticity, and maintenance of synaptic inputs. However, their relationship to synaptic structure and functional activity is unknown. We examined a correlative dataset from ferret visual cortex with in vivo two-photon calcium imaging of dendritic spines during visual stimulation and electron microscopy (EM) reconstructions of spine ultrastructure, investigating mitochondrial abundance near functionally- and structurally-characterized spines. Surprisingly, we found no correlation to structural measures of synaptic strength. Instead, we found that mitochondria are positioned near spines with orientation preferences that are dissimilar to the somatic preference. Additionally, we found that mitochondria are positioned near groups of spines with heterogeneous orientation preferences. For a subset of spines with mitochondrion in the head or neck, synapses were larger and exhibited greater selectivity to visual stimuli than those without a mitochondrion. Our data suggest mitochondria are not necessarily positioned to support the energy needs of strong spines, but rather support the structurally and functionally diverse inputs innervating the basal dendrites of cortical neurons.

Unraveling Functional Diversity of Cortical Synaptic Architecture Through the Lens of Population Coding.

The synaptic inputs to single cortical neurons exhibit substantial diversity in their sensory-driven activity. What this diversity reflects is unclear, and appears counter-productive in generating selective somatic responses to specific stimuli. One possibility is that this diversity reflects the propagation of information from one neural population to another. To test this possibility, we bridge population coding theory with measurements of synaptic inputs recorded in vivo with two-photon calcium imaging. We construct a probabilistic decoder to estimate the stimulus orientation from the responses of a realistic, hypothetical input population of neurons to compare with synaptic inputs onto individual neurons of ferret primary visual cortex (V1) recorded with two-photon calcium imaging in vivo. We find that optimal decoding requires diverse input weights and provides a straightforward mapping from the decoder weights to excitatory synapses. Analytically derived weights for biologically realistic input populations closely matched the functional heterogeneity of dendritic spines imaged in vivo with two-photon calcium imaging. Our results indicate that synaptic diversity is a necessary component of information transmission and reframes studies of connectivity through the lens of probabilistic population codes. These results suggest that the mapping from synaptic inputs to somatic selectivity may not be directly interpretable without considering input covariance and highlights the importance of population codes in pursuit of the cortical connectome.

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.

Cortical response selectivity derives from strength in numbers of synapses.

Single neocortical neurons are driven by populations of excitatory inputs, which form the basis of neuronal selectivity to features of sensory input. Excitatory connections are thought to mature during development through activity-dependent Hebbian plasticity1, whereby similarity between presynaptic and postsynaptic activity selectively strengthens some synapses and weakens others2. Evidence in support of this process includes measurements of synaptic ultrastructure and in vitro and in vivo physiology and imaging studies3-8. These corroborating lines of evidence lead to the prediction that a small number of strong synaptic inputs drive neuronal selectivity, whereas weak synaptic inputs are less correlated with the somatic output and modulate activity overall6,7. Supporting evidence from cortical circuits, however, has been limited to measurements of neighbouring, connected cell pairs, raising the question of whether this prediction holds for a broad range of synapses converging onto cortical neurons. Here we measure the strengths of functionally characterized excitatory inputs contacting single pyramidal neurons in ferret primary visual cortex (V1) by combining in vivo two-photon synaptic imaging and post hoc electron microscopy. Using electron microscopy reconstruction of individual synapses as a metric of strength, we find no evidence that strong synapses have a predominant role in the selectivity of cortical neuron responses to visual stimuli. Instead, selectivity appears to arise from the total number of synapses activated by different stimuli. Moreover, spatial clustering of co-active inputs appears to be reserved for weaker synapses, enhancing the contribution of weak synapses to somatic responses. Our results challenge the role of Hebbian mechanisms in shaping neuronal selectivity in cortical circuits, and suggest that selectivity reflects the co-activation of large populations of presynaptic neurons with similar properties and a mixture of strengths.

Targeting Functionally Characterized Synaptic Architecture Using Inherent Fiducials and 3D Correlative Microscopy.

Brain circuits are highly interconnected three-dimensional structures fabricated from components ranging vastly in size; from cell bodies to individual synapses. While neuronal activity can be visualized with advanced light microscopy (LM) techniques, the resolution of electron microscopy (EM) is critical for identifying synaptic connections between neurons. Here, we combine these two techniques, affording the advantage of each and allowing for measurements to be made of the same neural features across imaging platforms. We established an EM-label-free workflow utilizing inherent structural features to correlate in vivo two-photon LM and volumetric scanning EM (SEM) in the ferret visual cortex. By optimizing the volume SEM sample preparation protocol, imaging with the OnPoint detector, and utilizing the focal charge compensation device during serial block-face imaging, we achieved sufficient resolution and signal-to-noise ratio to analyze synaptic ultrastructure for hundreds of synapses within sample volumes. Our novel workflow provides a reliable method for quantitatively characterizing synaptic ultrastructure in functionally imaged neurons, providing new insights into neuronal circuit organization.

Cortical synaptic architecture supports flexible sensory computations.

Establishing the fundamental principles that underlie the integration of excitatory and inhibitory presynaptic input populations is crucial to understanding how individual cortical neurons transform signals from peripheral receptors. Here we review recent studies using novel tools to examine the functional properties of excitatory synaptic inputs and the tuning of excitation and inhibition onto individual neurons. New evidence challenges existing synaptic connectivity rules and suggests a more complex functional synaptic architecture that supports a broad range of operations, enabling single neurons to encode multiple sensory features and flexibly shape their computations in the face of diverse sensory input.

In Vivo Imaging of the Coupling between Neuronal and CREB Activity in the Mouse Brain.

Sensory experiences cause long-term modifications of neuronal circuits by modulating activity-dependent transcription programs that are vital for regulation of long-term synaptic plasticity and memory. However, it has not been possible to precisely determine the interaction between neuronal activity patterns and transcription factor activity. Here we present a technique using two-photon fluorescence lifetime imaging (2pFLIM) with new FRET biosensors to chronically image in vivo signaling of CREB, an activity-dependent transcription factor important for synaptic plasticity, at single-cell resolution. Simultaneous imaging of the red-shifted CREB sensor and GCaMP permitted exploration of how experience shapes the interplay between CREB and neuronal activity in the neocortex of awake mice. Dark rearing increased the sensitivity of CREB activity to Ca2+ elevations and prolonged the duration of CREB activation to more than 24 h in the visual cortex. This technique will allow researchers to unravel the transcriptional dynamics underlying experience-dependent plasticity in the brain.

Functional Logic of Layer 2/3 Inhibitory Connectivity in the Ferret Visual Cortex.

Understanding how cortical inhibition shapes circuit function requires identifying the connectivity rules relating the response properties of inhibitory interneurons and their postsynaptic targets. Here we explore the orientation tuning of layer 2/3 inhibitory inputs in the ferret visual cortex using a combination of in vivo axon imaging, functional input mapping, and physiology. Inhibitory boutons exhibit robust orientation-tuned responses with preferences that can differ significantly from the cortical column in which they reside. Inhibitory input fields measured with patterned optogenetic stimulation and intracellular recordings revealed that these inputs originate from a wide range of orientation domains, inconsistent with a model of co-tuned inhibition and excitation. Intracellular synaptic conductance measurements confirm that individual neurons can depart from a co-tuned regime. Our results argue against a simple rule for the arrangement of inhibitory inputs supplied by layer 2/3 circuits and suggest that heterogeneity in presynaptic inhibitory networks contributes to neural response properties.

Author Correction: Stability, affinity, and chromatic variants of the glutamate sensor iGluSnFR.

The version of this paper originally published cited a preprint version of ref. 12 instead of the published version (Proc. Natl. Acad. Sci. USA 115, 5594-5599; 2018), which was available before this Nature Methods paper went to press. The reference information has been updated in the PDF and HTML versions of the article.

Publisher Correction: Stability, affinity, and chromatic variants of the glutamate sensor iGluSnFR.

In the version of this paper originally published, important figure labels in Fig. 3d were not visible. An image layer present in the authors' original figure that included two small dashed outlines and text labels indicating ROI 1 and ROI 2, as well as a scale bar and the name of the cell label, was erroneously altered during image processing. The figure has been corrected in the HTML and PDF versions of the paper.

Stability, affinity, and chromatic variants of the glutamate sensor iGluSnFR.

Single-wavelength fluorescent reporters allow visualization of specific neurotransmitters with high spatial and temporal resolution. We report variants of intensity-based glutamate-sensing fluorescent reporter (iGluSnFR) that are functionally brighter; detect submicromolar to millimolar amounts of glutamate; and have blue, cyan, green, or yellow emission profiles. These variants could be imaged in vivo in cases where original iGluSnFR was too dim, resolved glutamate transients in dendritic spines and axonal boutons, and allowed imaging at kilohertz rates.

Differential tuning of excitation and inhibition shapes direction selectivity in ferret visual cortex.

To encode specific sensory inputs, cortical neurons must generate selective responses for distinct stimulus features. In principle, a variety of factors can contribute to the response selectivity of a cortical neuron: the tuning and strength of excitatory1-3 and inhibitory synaptic inputs4-6, dendritic nonlinearities7-9 and spike threshold10,11. Here we use a combination of techniques including in vivo whole-cell recording, synaptic- and cellular-resolution in vivo two-photon calcium imaging, and GABA (γ-aminobutyric acid) neuron-selective optogenetic manipulation to dissect the factors that contribute to the direction-selective responses of layer 2/3 neurons in ferret visual cortex (V1). Two-photon calcium imaging of dendritic spines12,13 revealed that each neuron receives a mixture of excitatory synaptic inputs selective for the somatic preferred or null direction of motion. The relative number of preferred- and null-tuned excitatory inputs predicted a neuron's somatic direction preference, but failed to account for the degree of direction selectivity. By contrast, in vivo whole-cell patch-clamp recordings revealed a notable degree of direction selectivity in subthreshold responses that was significantly correlated with spiking direction selectivity. Subthreshold direction selectivity was predicted by the magnitude and variance of the response to the null direction of motion, and several lines of evidence, including conductance measurements, demonstrate that differential tuning of excitation and inhibition suppresses responses to the null direction of motion. Consistent with this idea, optogenetic inactivation of GABAergic neurons in layer 2/3 reduced direction selectivity by enhancing responses to the null direction. Furthermore, by optogenetically mapping connections of inhibitory neurons in layer 2/3 in vivo, we find that layer 2/3 inhibitory neurons make long-range, intercolumnar projections to excitatory neurons that prefer the opposite direction of motion. We conclude that intracortical inhibition exerts a major influence on the degree of direction selectivity in layer 2/3 of ferret V1 by suppressing responses to the null direction of motion.