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.

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.

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.

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.

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.

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.

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.

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.

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.

Sensory stimulation shifts visual cortex from synchronous to asynchronous states.

In the mammalian cerebral cortex, neural responses are highly variable during spontaneous activity and sensory stimulation. To explain this variability, the cortex of alert animals has been proposed to be in an asynchronous high-conductance state in which irregular spiking arises from the convergence of large numbers of uncorrelated excitatory and inhibitory inputs onto individual neurons. Signatures of this state are that a neuron's membrane potential (Vm) hovers just below spike threshold, and its aggregate synaptic input is nearly Gaussian, arising from many uncorrelated inputs. Alternatively, irregular spiking could arise from infrequent correlated input events that elicit large fluctuations in Vm (refs 5, 6). To distinguish between these hypotheses, we developed a technique to perform whole-cell Vm measurements from the cortex of behaving monkeys, focusing on primary visual cortex (V1) of monkeys performing a visual fixation task. Here we show that, contrary to the predictions of an asynchronous state, mean Vm during fixation was far from threshold (14 mV) and spiking was triggered by occasional large spontaneous fluctuations. Distributions of Vm values were skewed beyond that expected for a range of Gaussian input, but were consistent with synaptic input arising from infrequent correlated events. Furthermore, spontaneous fluctuations in Vm were correlated with the surrounding network activity, as reflected in simultaneously recorded nearby local field potential. Visual stimulation, however, led to responses more consistent with an asynchronous state: mean Vm approached threshold, fluctuations became more Gaussian, and correlations between single neurons and the surrounding network were disrupted. These observations show that sensory drive can shift a common cortical circuitry from a synchronous to an asynchronous state.

Binocular Disparity Selectivity Weakened after Monocular Deprivation in Mouse V1.

Experiences during the critical period sculpt the circuitry within the neocortex, leading to changes in the functional responses of sensory neurons. Monocular deprivation (MD) during the visual critical period causes shifts in ocular preference, or dominance, toward the open eye in primary visual cortex (V1) and disrupts the normal development of acuity. In carnivores and primates, MD also disrupts the emergence of binocular disparity selectivity, a cue resulting from integrating ocular inputs. This disruption may be a result of the increase in neurons driven exclusively by the open eye that follows deprivation or a result of a mismatch in the convergence of ocular inputs. To distinguish between these possibilities, we measured the ocular dominance (OD) and disparity selectivity of neurons from male and female mouse V1 following MD. Normal mouse V1 neurons are dominated by contralateral eye input and contralateral eye deprivation shifts mouse V1 neurons toward more balanced responses between the eyes. This shift toward binocularity, as assayed by OD, decreased disparity sensitivity. MD did not alter the initial maturation of binocularity, as disparity selectivity before the MD was indistinguishable from normal mature animals. Decreased disparity tuning was most pronounced in binocular and ipsilaterally biased neurons, which are the populations that have undergone the largest shifts in OD. In concert with the decline in disparity selectivity, we observed a shift toward lower spatial frequency selectivity for the ipsilateral eye following MD. These results suggest an emergence of novel synaptic inputs during MD that disrupt the representation of disparity selectivity.SIGNIFICANCE STATEMENT We demonstrate that monocular deprivation during the developmental critical period impairs binocular integration in mouse primary visual cortex. This impairment occurs despite an increase in the degree to which neurons become more binocular. We further demonstrate that our deprivation did not impair the maturation of disparity selectivity. Disparity selectivity has already reached a matured level before the monocular deprivation. The loss of disparity tuning is primarily observed in neurons dominated by the open eye, suggesting a link between altered inputs and loss of disparity sensitivity. These results suggest that new inputs following deprivation may not maintain the precise spatial relationship between the two eye inputs required for disparity selectivity.

Functional characterization and spatial clustering of visual cortical neurons in the predatory grasshopper mouse Onychomys arenicola.

Mammalian neocortical circuits are functionally organized such that the selectivity of individual neurons systematically shifts across the cortical surface, forming a continuous map. Maps of the sensory space exist in cortex, such as retinotopic maps in the visual system or tonotopic maps in the auditory system, but other functional response properties also may be similarly organized. For example, many carnivores and primates possess a map for orientation selectivity in primary visual cortex (V1), whereas mice, rabbits, and the gray squirrel lack orientation maps. In this report we show that a carnivorous rodent with predatory behaviors, the grasshopper mouse (Onychomys arenicola), lacks a canonical columnar organization of orientation preference in V1; however, neighboring neurons within 50 µm exhibit related tuning preference. Using a combination of two-photon microscopy and extracellular electrophysiology, we demonstrate that the functional organization of visual cortical neurons in the grasshopper mouse is largely the same as in the C57/BL6 laboratory mouse. We also find similarity in the selectivity for stimulus orientation, direction, and spatial frequency. Our results suggest that the properties of V1 neurons across rodent species are largely conserved.NEW & NOTEWORTHY Carnivores and primates possess a map for orientation selectivity in primary visual cortex (V1), whereas rodents and lagomorphs lack this organization. We examine, for the first time, V1 of a wild carnivorous rodent with predatory behaviors, the grasshopper mouse (Onychomys arenicola). We demonstrate the cellular organization of V1 in the grasshopper mouse is largely the same as the C57/BL6 laboratory mouse, suggesting that V1 neuron properties across rodent species are largely conserved.

Orientation selectivity in the visual cortex of the nine-banded armadillo.

Orientation selectivity in primary visual cortex (V1) has been proposed to reflect a canonical computation performed by the neocortical circuitry. Although orientation selectivity has been reported in all mammals examined to date, the degree of selectivity and the functional organization of selectivity vary across mammalian clades. The differences in degree of orientation selectivity are large, from reports in marsupials that only a small subset of neurons are selective to studies in carnivores, in which it is rare to find a neuron lacking selectivity. Furthermore, the functional organization in cortex varies in that the primate and carnivore V1 is characterized by an organization in which nearby neurons share orientation preference while other mammals such as rodents and lagomorphs either lack or have only extremely weak clustering. To gain insight into the evolutionary emergence of orientation selectivity, we examined the nine-banded armadillo, a species within the early placental clade Xenarthra. Here we use a combination of neuroimaging, histological, and electrophysiological methods to identify the retinofugal pathways, locate V1, and for the first time examine the functional properties of V1 neurons in the armadillo (Dasypus novemcinctus) V1. Individual neurons were strongly sensitive to the orientation and often the direction of drifting gratings. We uncovered a wide range of orientation preferences but found a bias for horizontal gratings. The presence of strong orientation selectivity in armadillos suggests that the circuitry responsible for this computation is common to all placental mammals.NEW & NOTEWORTHY The current study shows that armadillo primary visual cortex (V1) neurons share the signature properties of V1 neurons of primates, carnivorans, and rodents. Furthermore, these neurons exhibit a degree of selectivity for stimulus orientation and motion direction similar to that found in primate V1. Our findings in armadillo visual cortex suggest that the functional properties of V1 neurons emerged early in the mammalian lineage, near the time of the divergence of marsupials.

Functional characterization of spikelet activity in the primary visual cortex.

KEY POINTS: In vivo whole-cell patch-clamp recordings in cat visual cortex revealed small deflections in the membrane potential of neurons, termed spikelets. Spikelet statistics and functional properties suggest these deflections originate from a single, nearby cell. Spikelets shared a number sensory selectivities with the principal neuron including orientation selectivity, receptive field location and eye preference. Principal neurons and spikelets did not, however, generally share preferences for depth (binocular disparity). Cross-correlation of spikelet activity and membrane potential revealed direct effects on the membrane potential of some principal neurons, suggesting that these cells were synaptically coupled or received common input from the cortical network. Other spikelet-neuron pairs revealed indirect effects, likely to be the result of correlated network events. ABSTRACT: Intracellular recordings in the neocortex reveal not only the membrane potential of neurons, but small unipolar or bipolar deflections that are termed spikelets. Spikelets have been proposed to originate from various sources, including active dendritic mechanisms, gap junctions and extracellular signals. Here we examined the functional characteristics of spikelets measured in neurons from cat primary visual cortex in vivo. Spiking statistics and our functional characterization of spikelet activity indicate that spikelets originate from a separate, nearby cell. Spikelet kinetics and lack of a direct effect on spikelet activity from hyperpolarizing current injection suggest they do not arise from electrical coupling to the principal neuron being recorded. Spikelets exhibited matched orientation tuning preference and ocular dominance to the principal neuron. In contrast, binocular disparity preferences of spikelets and the principal neuron were unrelated. Finally, we examined the impact of spikelets on the principal neuron's membrane potential; we did observe some records for which spikelets were correlated with the membrane potential of the principal neuron, suggesting that these neurons were synaptically coupled or received common input from the cortical network.

Strabismus disrupts binocular synaptic integration in primary visual cortex.

Visual disruption early in development dramatically changes how primary visual cortex neurons integrate binocular inputs. The disruption is paradigmatic for investigating the synaptic basis of long-term changes in cortical function, because the primary visual cortex is the site of binocular convergence. The underlying alterations in circuitry by visual disruption remain poorly understood. Here we compare membrane potential responses, observed via whole-cell recordings in vivo, of primary visual cortex neurons in normal adult cats with those of cats in which strabismus was induced before the developmental critical period. In strabismic cats, we observed a dramatic shift in the ocular dominance distribution of simple cells, the first stage of visual cortical processing, toward responding to one eye instead of both, but not in complex cells, which receive inputs from simple cells. Both simple and complex cells no longer conveyed the binocular information needed for depth perception based on binocular cues. There was concomitant binocular suppression such that responses were weaker with binocular than with monocular stimulation. Our estimates of the excitatory and inhibitory input to single neurons indicate binocular suppression that was not evident in synaptic excitation, but arose de novo because of synaptic inhibition. Further constraints on circuit models of plasticity result from indications that the ratio of excitation to inhibition evoked by monocular stimulation decreased mainly for nonpreferred eye stimulation. Although we documented changes in synaptic input throughout primary visual cortex, a circuit model with plasticity at only thalamocortical synapses is sufficient to account for our observations.

Emergence of orientation selectivity in the Mammalian visual pathway.

Orientation selectivity is a property of mammalian primary visual cortex (V1) neurons, yet its emergence along the visual pathway varies across species. In carnivores and primates, elongated receptive fields first appear in V1, whereas in lagomorphs such receptive fields emerge earlier, in the retina. Here we examine the mouse visual pathway and reveal the existence of orientation selectivity in lateral geniculate nucleus (LGN) relay cells. Cortical inactivation does not reduce this orientation selectivity, indicating that cortical feedback is not its source. Orientation selectivity is similar for LGN relay cells spiking and subthreshold input to V1 neurons, suggesting that cortical orientation selectivity is inherited from the LGN in mouse. In contrast, orientation selectivity of cat LGN relay cells is small relative to subthreshold inputs onto V1 simple cells. Together, these differences show that although orientation selectivity exists in visual neurons of both rodents and carnivores, its emergence along the visual pathway, and thus its underlying neuronal circuitry, is fundamentally different.

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.

A retinal source of spatial contrast gain control.

Sensory cortex is able to encode a broad range of stimulus features despite a great variation in signal strength. In cat primary visual cortex (V1), for example, neurons are able to extract stimulus features like orientation or spatial configuration over a wide range of stimulus contrasts. The contrast-invariant spatial tuning found in V1 neuron responses has been modeled as a gain control mechanism, but at which stage of the visual pathway it emerges has remained unclear. Here we describe our findings that contrast-invariant spatial tuning occurs not only in the responses of lateral geniculate nucleus (LGN) relay cells but also in their afferent retinal input. Our evidence suggests that a similar contrast-invariant mechanism is found throughout the stages of the early visual pathway, and that the contrast-invariant spatial selectivity is evident in both retinal ganglion cell and LGN cell responses.