Response sub-additivity and variability quenching in visual cortex.

Sub-additivity and variability are ubiquitous response motifs in the primary visual cortex (V1). Response sub-additivity enables the construction of useful interpretations of the visual environment, whereas response variability indicates the factors that limit the precision with which the brain can do this. There is increasing evidence that experimental manipulations that elicit response sub-additivity often also quench response variability. Here, we provide an overview of these phenomena and suggest that they may have common origins. We discuss empirical findings and recent model-based insights into the functional operations, computational objectives and circuit mechanisms underlying V1 activity. These different modelling approaches all predict that response sub-additivity and variability quenching often co-occur. The phenomenology of these two response motifs, as well as many of the insights obtained about them in V1, generalize to other cortical areas. Thus, the connection between response sub-additivity and variability quenching may be a canonical motif across the cortex.

Mammals Achieve Common Neural Coverage of Visual Scenes Using Distinct Sampling Behaviors.

Most vertebrates use head and eye movements to quickly change gaze orientation and sample different portions of the environment with periods of stable fixation. Visual information must be integrated across fixations to construct a complete perspective of the visual environment. In concert with this sampling strategy, neurons adapt to unchanging input to conserve energy and ensure that only novel information from each fixation is processed. We demonstrate how adaptation recovery times and saccade properties interact and thus shape spatiotemporal tradeoffs observed in the motor and visual systems of mice, cats, marmosets, macaques, and humans. These tradeoffs predict that in order to achieve similar visual coverage over time, animals with smaller receptive field sizes require faster saccade rates. Indeed, we find comparable sampling of the visual environment by neuronal populations across mammals when integrating measurements of saccadic behavior with receptive field sizes and V1 neuronal density. We propose that these mammals share a common statistically driven strategy of maintaining coverage of their visual environment over time calibrated to their respective visual system characteristics.

Interactions between saccades and smooth pursuit eye movements in marmosets.

Animals use a combination of eye movements to track moving objects. These different eye movements need to be coordinated for successful tracking, requiring interactions between the systems involved. Here, we study the interaction between the saccadic and smooth pursuit eye movement systems in marmosets. Using a single target pursuit task, we show that saccades cause an enhancement in pursuit following a saccade. Using a two-target pursuit task, we show that this enhancement in pursuit is selective towards the motion of the target selected by the saccade, irrespective of any biases in pursuit prior to the saccade. These experiments highlight the similarities in the functioning of saccadic and smooth pursuit eye movement systems across primates. SIGNIFICANCE STATEMENT: We study the coordination between the smooth-pursuit and saccadic eye movement systems in marmosets using single and multiple object motions. We find that saccade to a target increases pursuit velocity towards the target. If multiple objects are visible, saccade choice makes pursuit more selective towards the saccade target. Our results show that coordination between different eye movement systems to successfully track moving objects is similar between marmosets and primates.

Primate neocortex performs balanced sensory amplification.

The sensory cortex amplifies relevant features of external stimuli. This sensitivity and selectivity arise through the transformation of inputs by cortical circuitry. We characterize the circuit mechanisms and dynamics of cortical amplification by making large-scale simultaneous measurements of single cells in awake primates and testing computational models. By comparing network activity in both driven and spontaneous states with models, we identify the circuit as operating in a regime of non-normal balanced amplification. Incoming inputs are strongly but transiently amplified by strong recurrent feedback from the disruption of excitatory-inhibitory balance in the network. Strong inhibition rapidly quenches responses, thereby permitting the tracking of time-varying stimuli.

Exact analysis of the subthreshold variability for conductance-based neuronal models with synchronous synaptic inputs.

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects post-spiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime only yields realistic subthreshold variability (voltage variance ≅ 4-9mV 2 ) when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.

Exact analysis of the subthreshold variability for conductance-based neuronal models with synchronous synaptic inputs.

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects post-spiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime only yields realistic subthreshold variability (voltage variance ≃4-9mV2) when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.

Ocular following Eye Movements in Marmosets Follow Complex Motion Trajectories.

Ocular following eye movements help stabilize images on the retina and offer a window to study motion interpretation by visual circuits. We use these ocular following eye movements to study motion integration behavior in the marmosets. We characterize ocular following responses in the marmosets using different moving stimuli such as dot patterns, gratings, and plaids. Marmosets track motion along different directions and exhibit spatial frequency and speed sensitivity, which closely matches the sensitivity reported in neurons from their motion-selective area MT. Marmosets are also able to track the integrated motion of plaids, with tracking direction consistent with an intersection of constraints model of motion integration. Marmoset ocular following responses are similar to responses in macaques and humans with certain species-specific differences in peak sensitivities. Such motion-sensitive eye movement behavior in combination with direct access to cortical circuitry makes the marmoset model well suited to study the neural basis of motion integration.

Mammals achieve common neural coverage of visual scenes using distinct sampling behaviors.

Most vertebrates use head and eye movements to quickly change gaze orientation and sample different portions of the environment with periods of stable fixation. Visual information must be integrated across several fixations to construct a more complete perspective of the visual environment. In concert with this sampling strategy, neurons adapt to unchanging input to conserve energy and ensure that only novel information from each fixation is processed. We demonstrate how adaptation recovery times and saccade properties interact, and thus shape spatiotemporal tradeoffs observed in the motor and visual systems of different species. These tradeoffs predict that in order to achieve similar visual coverage over time, animals with smaller receptive field sizes require faster saccade rates. Indeed, we find comparable sampling of the visual environment by neuronal populations across mammals when integrating measurements of saccadic behavior with receptive field sizes and V1 neuronal density. We propose that these mammals share a common statistically driven strategy of maintaining coverage of their visual environment over time calibrated to their respective visual system characteristics.

Feedforward mechanisms of cross-orientation interactions in mouse V1.

Sensory neurons are modulated by context. For example, in mouse primary visual cortex (V1), neuronal responses to the preferred orientation are modulated by the presence of superimposed orientations ("plaids"). The effects of this modulation are diverse; some neurons are suppressed, while others have larger responses to a plaid than its components. We investigated whether this diversity could be explained by a unified circuit mechanism. We report that this masking is maintained during suppression of cortical activity, arguing against cortical mechanisms. Instead, the heterogeneity of plaid responses is explained by an interaction between stimulus geometry and orientation tuning. Highly selective neurons are uniformly suppressed by plaids, whereas the effects in weakly selective neurons depend on the spatial configuration of the stimulus, transitioning systematically between suppression and facilitation. Thus, the diverse responses emerge as a consequence of the spatial structure of feedforward inputs, with no need to invoke cortical interactions.

Natural binocular depth discrimination behavior in mice explained by visual cortical activity.

In mice and other mammals, forebrain neurons integrate right and left eye information to generate a three-dimensional representation of the visual environment. Neurons in the visual cortex of mice are sensitive to binocular disparity,1-3 yet it is unclear whether that sensitivity is linked to the perception of depth.4-8 We developed a natural task based on the classic visual cliff and pole descent tasks to estimate the psychophysical range of mouse depth discrimination.5,9 Mice with binocular vision descended to a near (shallow) surface more often when surrounding far (deep) surfaces were progressively more distant. Occlusion of one eye severely impaired their ability to target the near surface. We quantified the distance at which animals make their decisions to estimate the binocular image displacement of the checkerboard pattern on the near and far surfaces. Then, we assayed the disparity sensitivity of large populations of binocular neurons in primary visual cortex (V1) using two-photon microscopy2 and quantitatively compared this information available in V1 to their behavioral sensitivity. Disparity information in V1 matches the behavioral performance over the range of depths examined and was resistant to changes in binocular alignment. These findings reveal that mice naturally use stereoscopic cues to guide their behavior and indicate a neural basis for this depth discrimination task.

On the Rotations of the Cranial Spheres.

We integrate information from multiple sensory modalities and from ongoing plans to construct a perception of the world. In this issue of Neuron, Bouvier et al. (2020) and Guitchounts et al. (2020) examine the detailed circuitry that supports a flexible integration of head and visual signals in rodent primary visual cortex.

Interocular velocity cues elicit vergence eye movements in mice.

We stabilize the dynamic visual world on our retina by moving our eyes in response to motion signals. Coordinated movements between the two eyes are characterized as version when both eyes move in the same direction and vergence when the two eyes move in opposite directions. Vergence eye movements are necessary to track objects in three dimensions. In primates they can be elicited by intraocular differences in either spatial signals (disparity) or velocity, requiring the integration of left and right eye inputs. Whether mice are capable of similar behaviors is not known. To address this issue, we measured vergence eye movements in mice using a stereoscopic stimulus known to elicit vergence eye movements in primates. We found that mice also exhibit vergence eye movements, although at a low gain and that the primary driver of these vergence eye movements is interocular motion. Spatial disparity cues alone are ineffective. We also found that the vergence eye movements we observed in mice were robust to silencing visual cortex and to manipulations that disrupt the normal development of binocularity in visual cortex. A sublinear combination of motor commands driven by monocular signals is sufficient to account for our results.NEW & NOTEWORTHY The visual system integrates signals from the left and right eye to generate a representation of the world in depth. The binocular integration of signals may be observed from the coordinated vergence eye movements elicited by object motion in depth. We explored the circuits and signals responsible for these vergence eye movements in rodent and find these vergence eye movements are generated by a comparison of the motion and not spatial visual signals.

Voltage-Gated Intrinsic Conductances Shape the Input-Output Relationship of Cortical Neurons in Behaving Primate V1.

Neurons are input-output (I/O) devices-they receive synaptic inputs from other neurons, integrate those inputs with their intrinsic properties, and generate action potentials as outputs. To understand this fundamental process, we studied the interaction between synaptic inputs and intrinsic properties using whole-cell recordings from V1 neurons of awake, fixating macaque monkeys. Our measurements during spontaneous activity and visual stimulation reveal an intrinsic voltage-gated conductance that profoundly alters the integrative properties and visual responses of cortical neurons. This voltage-gated conductance increases neuronal gain and selectivity with subthreshold depolarization and linearizes the relationship between synaptic input and neural output. This intrinsic conductance is found in layer 2/3 V1 neurons of awake macaques, anesthetized mice, and acute brain slices. These results demonstrate that intrinsic conductances play an essential role in shaping the I/O relationship of cortical neurons and must be taken into account in future models of cortical computations.

Multiple Timescales Account for Adaptive Responses across Sensory Cortices.

Sensory systems encounter remarkably diverse stimuli in the external environment. Natural stimuli exhibit timescales and amplitudes of variation that span a wide range. Mechanisms of adaptation, a ubiquitous feature of sensory systems, allow for the accommodation of this range of scales. Are there common rules of adaptation across different sensory modalities? We measured the membrane potential responses of individual neurons in the visual, somatosensory, and auditory cortices of male and female mice to discrete, punctate stimuli delivered at a wide range of fixed and nonfixed frequencies. We find that the adaptive profile of the response is largely preserved across these three areas, exhibiting attenuation and responses to the cessation of stimulation, which are signatures of response to changes in stimulus statistics. We demonstrate that these adaptive responses can emerge from a simple model based on the integration of fixed filters operating over multiple time scales.SIGNIFICANCE STATEMENT Our recent sensations affect our current expectations and perceptions of the environment. Neural correlates of this process exist throughout the brain and are loosely termed adaptation. Adaptive processes have been described across sensory cortices, but direct comparisons of these processes have not been possible because paradigms have been tailored specifically for each modality. We developed a common stimulus set that was used to characterize adaptation in somatosensory, visual, and auditory cortex. We describe here the similarities and differences in adaptation across these cortical areas and demonstrate that adaptive responses may emerge from a set of static filters that operate over a broad range of timescales.

Mice Discriminate Stereoscopic Surfaces Without Fixating in Depth.

Stereopsis is a ubiquitous feature of primate mammalian vision, but little is known about if and how rodents such as mice use stereoscopic vision. We used random dot stereograms to test for stereopsis in male and female mice, and they were able to discriminate near from far surfaces over a range of disparities, with diminishing performance for small and large binocular disparities. Based on two-photon measurements of disparity tuning, the range of disparities represented in the visual cortex aligns with the behavior and covers a broad range of disparities. When we examined their binocular eye movements, we found that, unlike primates, mice did not systematically vary relative eye positions or use vergence eye movements when presented with different disparities. Nonetheless, the representation of disparity tuning was wide enough to capture stereoscopic information over a range of potential vergence angles. Although mice share fundamental characteristics of stereoscopic vision with primates and carnivores, their lack of disparity-dependent vergence eye movements and wide neuronal representation suggests that they may use a distinct strategy for stereopsis.SIGNIFICANCE STATEMENT Binocular vision allows us to derive depth information by comparing right and left eye information. We characterized binocular integration in mice because tools exist in these animals to dissect the underlying neural circuitry for binocular vision. Using random dot stereograms, we find that behavior and disparity tuning in the visual cortex share fundamental characteristics with primates, but we did not observe any evidence of disparity-dependent changes in vergence angle. We propose that mice use a distinct strategy of stereopsis compared with primates by using a broad range of disparities to encode depth over a large field of view and to compensate for nonstereoscopic changes in vergence angle that arise during natural behavior.

Synaptic Basis for Contrast-Dependent Shifts in Functional Identity in Mouse V1.

A central transformation that occurs within mammalian visual cortex is the change from linear, polarity-sensitive responses to nonlinear, polarity-insensitive responses. These neurons are classically labelled as either simple or complex, respectively, on the basis of their response linearity (Skottun et al., 1991). While the difference between cell classes is clear when the stimulus strength is high, reducing stimulus strength diminishes the differences between the cell types and causes some complex cells to respond as simple cells (Crowder et al., 2007; van Kleef et al., 2010; Hietanen et al., 2013). To understand the synaptic basis for this shift in behavior, we used in vivo whole-cell recordings while systematically shifting stimulus contrast. We find systematic shifts in the degree of complex cell responses in mouse primary visual cortex (V1) at the subthreshold level, demonstrating that synaptic inputs change in concert with the shifts in response linearity and that the change in response linearity is not simply due to the threshold nonlinearity. These shifts are consistent with a visual cortex model in which the recurrent amplification acts as a critical component in the generation of complex cell responses (Chance et al., 1999).

Functional Access to Neuron Subclasses in Rodent and Primate Forebrain.

Viral vectors enable foreign proteins to be expressed in brains of non-genetic species, including non-human primates. However, viruses targeting specific neuron classes have proved elusive. Here we describe viral promoters and strategies for accessing GABAergic interneurons and their molecularly defined subsets in the rodent and primate. Using a set intersection approach, which relies on two co-active promoters, we can restrict heterologous protein expression to cortical and hippocampal somatostatin-positive and parvalbumin-positive interneurons. With an orthogonal set difference method, we can enrich for subclasses of neuropeptide-Y-positive GABAergic interneurons by effectively subtracting the expression pattern of one promoter from that of another. These methods harness the complexity of gene expression patterns in the brain and significantly expand the number of genetically tractable neuron classes across mammals.

Natural image and receptive field statistics predict saccade sizes.

Humans and other primates sample the visual environment using saccadic eye movements that shift a high-resolution fovea toward regions of interest to create a clear perception of a scene across fixations. Many mammals, however, like mice, lack a fovea, which raises the question of why they make saccades. Here we describe and test the hypothesis that saccades are matched to natural scene statistics and to the receptive field sizes and adaptive properties of neural populations. Specifically, we determined the minimum amplitude of saccades in natural scenes necessary to provide uncorrelated inputs to model neural populations. This analysis predicts the distributions of observed saccade sizes during passive viewing for nonhuman primates, cats, and mice. Furthermore, disrupting the development of receptive field properties by monocular deprivation changed saccade sizes consistent with this hypothesis. Therefore, natural-scene statistics and the neural representation of natural images appear to be critical factors guiding saccadic eye movements.

Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex.

The connectivity principles underlying the emergence of orientation selectivity in primary visual cortex (V1) of mammals lacking an orientation map (such as rodents and lagomorphs) are poorly understood. We present a computational model in which random connectivity gives rise to orientation selectivity that matches experimental observations. The model predicts that mouse V1 neurons should exhibit intricate receptive fields in the two-dimensional frequency domain, causing a shift in orientation preferences with spatial frequency. We find evidence for these features in mouse V1 using calcium imaging and intracellular whole-cell recordings.