Invited Session IV: Studies of the visual cortex with sub-millimeter resolution: Toward an all-optical bi-directional interrogation of topographic population codes in primate cortex.

The representation of visual stimuli in primate V1 is widely distributed and topographic. This raises the possibility that in some visual tasks, downstream areas that decode V1 signals in order to mediate perception could combine V1 signals at a relevant topographic scale-e.g., at the scale of orientation columns. If this were the case, then the fundamental unit of information would be individual columns rather than single neurons, and to account for the subject's behavior in a perceptual task, it would be necessary and sufficient to consider the summed activity of the thousands of neurons within each column. In this presentation I will discuss our initial attempts to test this topographic-code hypothesis using our optical-genetic toolbox for "reading" and "writing" neural population codes at the spatial scales of topographic maps in V1 of behaving macaques.

Similar masking effects of natural backgrounds on detection performances in humans, macaques, and macaque-V1 population responses.

Visual systems evolve to process the stimuli that arise in the organism's natural environment, and hence, to fully understand the neural computations in the visual system, it is important to measure behavioral and neural responses to natural visual stimuli. Here, we measured psychometric and neurometric functions in the macaque monkey for detection of a windowed sine-wave target in uniform backgrounds and in natural backgrounds of various contrasts. The neurometric functions were obtained by near-optimal decoding of voltage-sensitive-dye-imaging (VSDI) responses at the retinotopic scale in primary visual cortex (V1). The results were compared with previous human psychophysical measurements made under the same conditions. We found that human and macaque behavioral thresholds followed the generalized Weber's law as function of contrast, and that both the slopes and the intercepts of the threshold as a function of background contrast match each other up to a single scale factor. We also found that the neurometric thresholds followed the generalized Weber's law with slopes and intercepts matching the behavioral slopes and intercepts up to a single scale factor. We conclude that human and macaque ability to detect targets in natural backgrounds are affected in the same way by background contrast, that these effects are consistent with population decoding at the retinotopic scale by down-stream circuits, and that the macaque monkey is an appropriate animal model for gaining an understanding of the neural mechanisms in humans for detecting targets in natural backgrounds. Finally, we discuss limitations of the current study and potential next steps.NEW & NOTEWORTHY We measured macaque detection performance in natural images and compared their performance to the detection sensitivity of neurophysiological responses recorded in the primary visual cortex (V1), and to the performance of human subjects. We found that 1) human and macaque behavioral performances are in quantitative agreement and 2) are consistent with near-optimal decoding of V1 population responses.

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.

Nonlinear Lateral Interactions in V1 Population Responses Explained by a Contrast Gain Control Model.

How do cortical responses to local image elements combine to form a spatial pattern of population activity in primate V1? Here, we used voltage-sensitive dye imaging, which measures summed membrane potential activity, to examine the rules that govern lateral interactions between the representations of two small local-oriented elements in macaque (Macaca mulatta) V1. We find strong subadditive and mostly orientation-independent interactions for nearby elements [2-4 mm interelement cortical distance (IED)] that gradually become linear at larger separations (>6 mm IED). These results are consistent with a population gain control model describing nonlinear V1 population responses to single oriented elements. However, because of the membrane potential-to-spiking accelerating nonlinearity, the model predicts supra-additive lateral interactions of spiking responses for intermediate separations at a range of locations between the two elements, consistent with some prior facilitatory effects observed in electrophysiology and psychophysics. Overall, our results suggest that population-level lateral interactions in V1 are primarily explained by a simple orientation-independent contrast gain control mechanism.SIGNIFICANCE STATEMENT Interactions between representations of simple visual elements such as oriented edges in primary visual cortex (V1) are thought to contribute to our ability to easily integrate contours and segment surfaces, but the mechanisms that govern these interactions are primarily unknown. Our study provides novel evidence that lateral interactions at the population level are governed by a simple contrast gain-control mechanism, and we show how this divisive gain-control mechanism can give rise to apparently facilitatory spiking responses.

Long-range traveling waves of activity triggered by local dichoptic stimulation in V1 of behaving monkeys.

Traveling waves of cortical activity, in which local stimulation triggers lateral spread of activity to distal locations, have been hypothesized to play an important role in cortical function. However, there is conflicting physiological evidence for the existence of spreading traveling waves of neural activity triggered locally. Dichoptic stimulation, in which the two eyes view dissimilar monocular patterns, can lead to dynamic wave-like fluctuations in visual perception and therefore, provides a promising means for identifying and studying cortical traveling waves. Here, we used voltage-sensitive dye imaging to test for the existence of traveling waves of activity in the primary visual cortex of awake, fixating monkeys viewing dichoptic stimuli. We find clear traveling waves that are initiated by brief, localized contrast increments in one of the monocular patterns and then, propagate at speeds of ∼ 30 mm/s. These results demonstrate that under an appropriate visual context, circuitry in visual cortex in alert animals is capable of supporting long-range traveling waves triggered by local stimulation.

Disparate nonlinear neural dynamics measured with different techniques in macaque and human V1.

Diverse neuro-imaging techniques measure different aspects of neural responses with distinct spatial and temporal resolutions. Relating measured neural responses across different methods has been challenging. Here, we take a step towards overcoming this challenge, by comparing the nonlinearity of neural dynamics measured across methods. We used widefield voltage-sensitive dye imaging (VSDI) to measure neural population responses in macaque V1 to visual stimuli with a wide range of temporal waveforms. We found that stimulus-evoked VSDI responses are surprisingly near-additive in time. These results are qualitatively different from the strong sub-additive dynamics previously measured using fMRI and electrocorticography (ECoG) in human visual cortex with a similar set of stimuli. To test whether this discrepancy is specific to VSDI-a signal dominated by subthreshold neural activity, we repeated our measurements using widefield imaging of a genetically encoded calcium indicator (GcaMP6f)-a signal dominated by spiking activity, and found that GCaMP signals in macaque V1 are also near-additive. Therefore, the discrepancies in the extent of sub-additivity between the macaque and the human measurements are unlikely due to differences between sub- and supra-threshold neural responses. Finally, we use a simple yet flexible delayed normalization model to capture these different dynamics across measurements (with different model parameters). The model can potentially generalize to a broader set of stimuli, which aligns with previous suggestion that dynamic gain-control is a canonical computation contributing to neural processing in the brain.

Neural correlates of perceptual similarity masking in primate V1.

Visual detection is a fundamental natural task. Detection becomes more challenging as the similarity between the target and the background in which it is embedded increases, a phenomenon termed 'similarity masking'. To test the hypothesis that V1 contributes to similarity masking, we used voltage sensitive dye imaging (VSDI) to measure V1 population responses while macaque monkeys performed a detection task under varying levels of target-background similarity. Paradoxically, we find that during an initial transient phase, V1 responses to the target are enhanced, rather than suppressed, by target-background similarity. This effect reverses in the second phase of the response, so that in this phase V1 signals are positively correlated with the behavioral effect of similarity. Finally, we show that a simple model with delayed divisive normalization can qualitatively account for our findings. Overall, our results support the hypothesis that a nonlinear gain control mechanism in V1 contributes to perceptual similarity masking.

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 postspiking 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 yields realistic subthreshold variability (voltage variance ≃4-9 mV2) only 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.

Mesoscopic calcium imaging in a head-unrestrained male non-human primate using a lensless microscope.

Mesoscopic calcium imaging enables studies of cell-type specific neural activity over large areas. A growing body of literature suggests that neural activity can be different when animals are free to move compared to when they are restrained. Unfortunately, existing systems for imaging calcium dynamics over large areas in non-human primates (NHPs) are table-top devices that require restraint of the animal's head. Here, we demonstrate an imaging device capable of imaging mesoscale calcium activity in a head-unrestrained male non-human primate. We successfully miniaturize our system by replacing lenses with an optical mask and computational algorithms. The resulting lensless microscope can fit comfortably on an NHP, allowing its head to move freely while imaging. We are able to measure orientation columns maps over a 20 mm2 field-of-view in a head-unrestrained macaque. Our work establishes mesoscopic imaging using a lensless microscope as a powerful approach for studying neural activity under more naturalistic conditions.

NEURAL CORRELATES OF PERCEPTUAL SIMILARITY MASKING IN PRIMATE V1.

Visual detection is a fundamental natural task. Detection becomes more challenging as the similarity between the target and the background in which it is embedded increases, a phenomenon termed "similarity masking". To test the hypothesis that V1 contributes to similarity masking, we used voltage sensitive dye imaging (VSDI) to measure V1 population responses while macaque monkeys performed a detection task under varying levels of target-background similarity. Paradoxically, we find that during an initial transient phase, V1 responses to the target are enhanced, rather than suppressed, by target-background similarity. This effect reverses in the second phase of the response, so that in this phase V1 signals are positively correlated with the behavioral effect of similarity. Finally, we show that a simple model with delayed divisive normalization can qualitatively account for our findings. Overall, our results support the hypothesis that a nonlinear gain control mechanism in V1 contributes to perceptual similarity masking.

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.

Uniform spatial spread of population activity in primate parafoveal V1.

What are the shape and size of the region in primate V1 that processes information from a single point in visual space? This region, a fundamental property termed cortical point image (CPI) (McIlwain 1986), represents the minimal population of V1 neurons that can be activated by a visual stimulus and therefore has important implications for population coding in the cortex. Previous indirect attempts to measure the CPI in macaque V1 using sparse microelectrode recordings resulted in conflicting findings. Whereas some early studies suggested that CPI size is constant throughout V1 (e.g., Hubel and Wiesel 1974), others have reported large changes in CPI size in parafoveal V1 (e.g., Van Essen et al. 1984). To resolve this controversy, we used voltage-sensitive dye imaging in V1 of fixating monkeys to directly measure the subthreshold CPI and several related properties across a range of parafoveal eccentricities. We found that despite large changes in other properties of the retinotopic map, the subthreshold CPI is approximately constant and extends over ∼6 × 8 mm(2). This large and invariant CPI ensures a uniform representation of each point in visual space, with a complete representation of all visual features in V1, as originally proposed by Hubel and Wiesel (1974). In addition, we found several novel and unexpected asymmetries and anisotropies in the shapes of the CPI and the population receptive field. These results expand our understanding of the representation of visual space in V1 and are likely to be relevant for the representations of stimuli in other sensory cortical areas.

The relationship between voltage-sensitive dye imaging signals and spiking activity of neural populations in primate V1.

Voltage-sensitive dye imaging (VSDI) is a powerful technique for measuring neural population responses from a large cortical region simultaneously with millisecond temporal resolution and columnar spatial resolution. However, the relationship between the average VSDI signal and the average spiking activity of neural populations is largely unknown. To better understand this relationship, we compared visual responses measured from V1 of behaving monkeys using VSDI and single-unit electrophysiology. We found large and systematic differences between position and orientation tuning properties obtained with these two techniques. We then determined that a simple computational model could explain these tuning differences. This model, together with our experimental results, allowed us to estimate the quantitative relationship between the average VSDI signal and local spiking activity. We found that this relationship is similar to the previously reported nonlinear relationship between average membrane potential and spike rate in single V1 neurons, suggesting that VSDI signals are dominated by subthreshold synaptic activity. This model, together with the VSDI measured maps for spatial position (retinotopy) and orientation, also allowed us to estimate the spatial integration area over which neural responses contribute to the VSDI signal at a given location. We found that the VSDI-integration area is consistent with a Gaussian envelope with a space constant of ∼230 µm. Finally, we show how this model and estimated parameters can be used to predict the pattern of population responses at the level of spiking activity from VSDI responses.

Similar neural and perceptual masking effects of low-power optogenetic stimulation in primate V1.

Can direct stimulation of primate V1 substitute for a visual stimulus and mimic its perceptual effect? To address this question, we developed an optical-genetic toolkit to 'read' neural population responses using widefield calcium imaging, while simultaneously using optogenetics to 'write' neural responses into V1 of behaving macaques. We focused on the phenomenon of visual masking, where detection of a dim target is significantly reduced by a co-localized medium-brightness mask (Cornsweet and Pinsker, 1965; Whittle and Swanston, 1974). Using our toolkit, we tested whether V1 optogenetic stimulation can recapitulate the perceptual masking effect of a visual mask. We find that, similar to a visual mask, low-power optostimulation can significantly reduce visual detection sensitivity, that a sublinear interaction between visual- and optogenetic-evoked V1 responses could account for this perceptual effect, and that these neural and behavioral effects are spatially selective. Our toolkit and results open the door for further exploration of perceptual substitutions by direct stimulation of sensory cortex.

Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface.

Calcium imaging is a powerful tool for recording from large populations of neurons in vivo. Imaging in rhesus macaque motor cortex can enable the discovery of fundamental principles of motor cortical function and can inform the design of next generation brain-computer interfaces (BCIs). Surface two-photon imaging, however, cannot presently access somatic calcium signals of neurons from all layers of macaque motor cortex due to photon scattering. Here, we demonstrate an implant and imaging system capable of chronic, motion-stabilized two-photon imaging of neuronal calcium signals from macaques engaged in a motor task. By imaging apical dendrites, we achieved optical access to large populations of deep and superficial cortical neurons across dorsal premotor (PMd) and gyral primary motor (M1) cortices. Dendritic signals from individual neurons displayed tuning for different directions of arm movement. Combining several technical advances, we developed an optical BCI (oBCI) driven by these dendritic signalswhich successfully decoded movement direction online. By fusing two-photon functional imaging with CLARITY volumetric imaging, we verified that many imaged dendrites which contributed to oBCI decoding originated from layer 5 output neurons, including a putative Betz cell. This approach establishes new opportunities for studying motor control and designing BCIs via two photon imaging.

Optimal decoding of correlated neural population responses in the primate visual cortex.

Even the simplest environmental stimuli elicit responses in large populations of neurons in early sensory cortical areas. How these distributed responses are read out by subsequent processing stages to mediate behavior remains unknown. Here we used voltage-sensitive dye imaging to measure directly population responses in the primary visual cortex (V1) of monkeys performing a demanding visual detection task. We then evaluated the ability of different decoding rules to detect the target from the measured neural responses. We found that small visual targets elicit widespread responses in V1, and that response variability at distant sites is highly correlated. These correlations render most previously proposed decoding rules inefficient relative to one that uses spatially antagonistic center-surround summation. This optimal decoder consistently outperformed the monkey in the detection task, demonstrating the sensitivity of our techniques. Overall, our results suggest an unexpected role for inhibitory mechanisms in efficient decoding of neural population responses.

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.

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.

Linking neuronal and behavioral performance in a reaction-time visual detection task.

Perceptual decisions are likely to be based on signals that are provided by populations of neurons in early sensory cortical areas. How these neural responses are combined across neurons and over time to mediate behavior is unknown. To study the link between neural responses and perceptual decisions, we recorded the activity of single units (SU) and multiple units (MU) in the primary visual cortex (V1) of monkeys while they performed a reaction-time visual detection task. We then determined how well the target could be detected from these neural signals. We found that, on average, the detection sensitivities supported by SU and MU in V1 are comparable with the detection sensitivity of the monkey even when considering neural responses during brief temporal intervals (median duration, 137 ms) that ended shortly before the monkey's reaction time. However, we observed systematic differences between the overall shape of the neurometric functions and the monkey's psychometric functions. We also examined the quantitative relationship between SU and MU activity and found that MU responses are consistent with the sum of the responses of multiple SU, most of which have low stimulus selectivity. Finally, we found weak but significant trial-to-trial covariations between V1 activity and behavioral choices, demonstrating for the first time that choice probability can be observed at the earliest stages of cortical sensory processing. Together, these results suggest that the activity of a large population of V1 neurons is combined suboptimally by subsequent processing stages to mediate behavioral performance in visual detection tasks.