Dynamics of tuning in the Fourier domain

Local organization of spatial frequency tuning dynamics in the cat visual areas 17 and 18

Spatial frequency (SF) is a prominent feature to which most neurons in cat areas 17 and 18 (area 17/18) exhibit tuning selectivity. Previous studies have shown that neurons with similar SF tunings are locally clustered into SF preference domains. However, the functional organization of SF tuning remains not fully understood. Neurons in these areas show a variety of SF tuning dynamics; however, it is unknown how neurons with diverse dynamics are locally organized to form the population dynamics of the domains. The laminar organization of SF dynamics is also unknown, knowledge of which may be useful for determining how SF tuning dynamics of cat area 17/18 neurons arise in cortical circuits. To address these issues, we recorded the activities of multiple neurons in the cat area 17/18 using microelectrode arrays and characterized the time courses of the SF tunings of these neurons by a subspace reverse correlation. A wide range of SF dynamics was already present in the input layer, suggesting that intracortical mechanisms contribute to generating SF dynamics inside this layer but do not further shape it outside this layer. Local neuronal pools with similar SF tunings contained diverse SF dynamics. The average preferred SF of a pool similarly increased with response time. Moreover, the range of single-neuron preferred SFs in a pool tended to increase with time. Our results suggest that, in the presence of organized tuning diversity within an SF domain, the cortical SF organization remains stable during response time in cat area 17/18.NEW & NOTEWORTHY In cat area 17/18, we found that a local pool of neurons with similar spatial frequency (SF) tunings shows diverse but organized dynamics. Our results suggest that, in the presence of organized tuning diversity within an SF domain, the cortical SF organization remains stable over response time in these areas. Laminar analysis suggests that intracortical mechanisms contribute to generating SF dynamics inside the input layer but do not further shape it outside this layer.

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.

Local tuning biases in mouse primary visual cortex

Neurons in primary visual cortex are selective to the orientation and spatial frequency of sinusoidal gratings. In the classic model of cortical organization, a population of neurons responding to the same region of the visual field but tuned to all possible feature combinations provides a detailed representation of the local image. Such a functional module is assumed to be replicated across primary visual cortex to provide a uniform representation of the image across the entire visual field. In contrast, it has been hypothesized that the tiling properties of ON- and OFF-center receptive fields in the retina, largely mirrored in the geniculate, may constrain cortical tuning at each location in the visual field. This model predicts the existence of local biases in tuning that vary across the visual field and would prevent the cortex from developing a uniform, modular representation as postulated by the classic model. Here, we confirm the existence of local tuning biases in the primary visual cortex of the mouse, lending support to the notion that cortical tuning may be constrained by signals from the periphery. NEW & NOTEWORTHY Populations of cortical neurons responding to the same part of the visual field are shown to have similar tuning. Such local biases are consistent with the hypothesis that cortical tuning, in mouse primary visual cortex, is constrained by signals from the periphery.

Active learning of cortical connectivity from two-photon imaging data

Understanding how groups of neurons interact within a network is a fundamental question in system neuroscience. Instead of passively observing the ongoing activity of a network, we can typically perturb its activity, either by external sensory stimulation or directly via techniques such as two-photon optogenetics. A natural question is how to use such perturbations to identify the connectivity of the network efficiently. Here we introduce a method to infer sparse connectivity graphs from in-vivo, two-photon imaging of population activity in response to external stimuli. A novel aspect of the work is the introduction of a recommended distribution, incrementally learned from the data, to optimally refine the inferred network. Unlike existing system identification techniques, this “active learning” method automatically focuses its attention on key undiscovered areas of the network, instead of targeting global uncertainty indicators like parameter variance. We show how active learning leads to faster inference while, at the same time, provides confidence intervals for the network parameters. We present simulations on artificial small-world networks to validate the methods and apply the method to real data. Analysis of frequency of motifs recovered show that cortical networks are consistent with a small-world topology model.

Cluster-based analysis improves predictive validity of spike-triggered receptive field estimates

Spectrotemporal receptive field (STRF) characterization is a central goal of auditory physiology. STRFs are often approximated by the spike-triggered average (STA), which reflects the average stimulus preceding a spike. In many cases, the raw STA is subjected to a threshold defined by gain values expected by chance. However, such correction methods have not been universally adopted, and the consequences of specific gain-thresholding approaches have not been investigated systematically. Here, we evaluate two classes of statistical correction techniques, using the resulting STRF estimates to predict responses to a novel validation stimulus. The first, more traditional technique eliminated STRF pixels (time-frequency bins) with gain values expected by chance. This correction method yielded significant increases in prediction accuracy, including when the threshold setting was optimized for each unit. The second technique was a two-step thresholding procedure wherein clusters of contiguous pixels surviving an initial gain threshold were then subjected to a cluster mass threshold based on summed pixel values. This approach significantly improved upon even the best gain-thresholding techniques. Additional analyses suggested that allowing threshold settings to vary independently for excitatory and inhibitory subfields of the STRF resulted in only marginal additional gains, at best. In summary, augmenting reverse correlation techniques with principled statistical correction choices increased prediction accuracy by over 80% for multi-unit STRFs and by over 40% for single-unit STRFs, furthering the interpretational relevance of the recovered spectrotemporal filters for auditory systems analysis.

Enhanced Spatial Resolution During Locomotion and Heightened Attention in Mouse Primary Visual Cortex

We do not fully understand how behavioral state modulates the processing and transmission of sensory signals. Here, we studied the cortical representation of the retinal image in mice that spontaneously switched between a state of rest and a constricted pupil, and one of active locomotion and a dilated pupil, indicative of heightened attention. We measured the selectivity of neurons in primary visual cortex for orientation and spatial frequency, as well as their response gain, in these two behavioral states. Consistent with prior studies, we found that preferred orientation and spatial frequency remained invariant across states, whereas response gain increased during locomotion relative to rest. Surprisingly, relative gain, defined as the ratio between the gain during locomotion and the gain during rest, was not uniform across the population. Cells tuned to high spatial frequencies showed larger relative gain compared with those tuned to lower spatial frequencies. The preferential enhancement of high-spatial-frequency information was also reflected in our ability to decode the stimulus from population activity. Finally, we show that changes in gain originate from shifts in the operating point of neurons along a spiking nonlinearity as a function of behavioral state. Differences in the relative gain experienced by neurons with high and low spatial frequencies are due to corresponding differences in how these cells shift their operating points between behavioral states.

SIGNIFICANCE STATEMENT

How behavioral state modulates the processing and transmission of sensory signals remains poorly understood. Here, we show that the mean firing rate and neuronal gain increase during locomotion as a result in a shift of the operating point of neurons. We define relative gain as the ratio between the gain of neurons during locomotion and rest. Interestingly, relative gain is higher in cells with preferences for higher spatial frequencies than those with low-spatial-frequency selectivity. This means that, during a state of locomotion and heightened attention, the population activity in primary visual cortex can support better spatial acuity, a phenomenon that parallels the improved spatial resolution observed in human subjects during the allocation of spatial attention.

Spatiotemporal Filter for Visual Motion Integration from Pursuit Eye Movements in Humans and Monkeys

Despite the enduring interest in motion integration, a direct measure of the space-time filter that the brain imposes on a visual scene has been elusive. This is perhaps because of the challenge of estimating a 3D function from perceptual reports in psychophysical tasks. We take a different approach. We exploit the close connection between visual motion estimates and smooth pursuit eye movements to measure stimulus-response correlations across space and time, computing the linear space-time filter for global motion direction in humans and monkeys. Although derived from eye movements, we find that the filter predicts perceptual motion estimates quite well. To distinguish visual from motor contributions to the temporal duration of the pursuit motion filter, we recorded single-unit responses in the monkey middle temporal cortical area (MT). We find that pursuit response delays are consistent with the distribution of cortical neuron latencies and that temporal motion integration for pursuit is consistent with a short integration MT subpopulation. Remarkably, the visual system appears to preferentially weight motion signals across a narrow range of foveal eccentricities rather than uniformly over the whole visual field, with a transiently enhanced contribution from locations along the direction of motion. We find that the visual system is most sensitive to motion falling at approximately one-third the radius of the stimulus aperture. Hypothesizing that the visual drive for pursuit is related to the filtered motion energy in a motion stimulus, we compare measured and predicted eye acceleration across several other target forms.SIGNIFICANCE STATEMENT A compact model of the spatial and temporal processing underlying global motion perception has been elusive. We used visually driven smooth eye movements to find the 3D space-time function that best predicts both eye movements and perception of translating dot patterns. We found that the visual system does not appear to use all available motion signals uniformly, but rather weights motion preferentially in a narrow band at approximately one-third the radius of the stimulus. Although not universal, the filter predicts responses to other types of stimuli, demonstrating a remarkable degree of generalization that may lead to a deeper understanding of visual motion processing.

Spatial clustering of tuning in mouse primary visual cortex

The primary visual cortex of higher mammals is organized into two-dimensional maps, where the preference of cells for stimulus parameters is arranged regularly on the cortical surface. In contrast, the preference of neurons in the rodent appears to be arranged randomly, in what is termed a salt-and-pepper map. Here we revisited the spatial organization of receptive fields in mouse primary visual cortex by measuring the tuning of pyramidal neurons in the joint orientation and spatial frequency domain. We found that the similarity of tuning decreases as a function of cortical distance, revealing a weak but statistically significant spatial clustering. Clustering was also observed across different cortical depths, consistent with a columnar organization. Thus, the mouse visual cortex is not strictly a salt-and-pepper map. At least on a local scale, it resembles a degraded version of the organization seen in higher mammals, hinting at a possible common origin.

The preference of cells in mouse primary visual cortex are thought to be randomly distributed in a salt-and-pepper map, in contrast to the smooth cortical maps observed in higher mammals. Here the authors show that excitatory cells in mouse primary visual cortex are spatially clustered, resembling a degraded version of the organization seen in higher mammals.

Neural mechanisms of coarse-to-fine discrimination in the visual cortex

Vision is a dynamic process that refines the spatial scale of analysis over time, as evidenced by a progressive improvement in the ability to detect and discriminate finer details. To understand coarse-to-fine discrimination, we studied the dynamics of spatial frequency (SF) response using reverse correlation in the primary visual cortex (V1) of the primate. In a majority of V1 cells studied, preferred SF either increased monotonically with time (group 1) or changed nonmonotonically, with an initial increase followed by a decrease (group 2). Monotonic shift in preferred SF occurred with or without an early suppression at low SFs. Late suppression at high SFs always accompanied nonmonotonic SF dynamics. Bayesian analysis showed that SF discrimination performance and best discriminable SF frequencies changed with time in different ways in the two groups of neurons. In group 1 neurons, SF discrimination performance peaked on both left and right flanks of the SF tuning curve at about the same time. In group 2 neurons, peak discrimination occurred on the right flank (high SFs) later than on the left flank (low SFs). Group 2 neurons were also better discriminators of high SFs. We examined the relationship between the time at which SF discrimination performance peaked on either flank of the SF tuning curve and the corresponding best discriminable SFs in both neuronal groups. This analysis showed that the population best discriminable SF increased with time in V1. These results suggest neural mechanisms for coarse-to-fine discrimination behavior and that this process originates in V1 or earlier.

Joint tuning for direction of motion and binocular disparity in macaque MT is largely separable

Neurons in sensory cortical areas are tuned to multiple dimensions, or features, of their sensory space. Understanding how single neurons represent multiple features is of great interest for determining the informative dimensions of the neurons' response, the decoding algorithms appropriate for extracting this information from the neuronal population, and for determining where specific transformations occur along the visual hierarchy. Despite the established role of cortical area MT in judgments of motion and depth, it is not known how individual neurons jointly encode the two dimensions. We investigated the joint tuning of individual MT neurons for two visual features: direction of motion and binocular disparity, an important depth cue. We found that a separable, multiplicative combination of tuning for the two features can account for more than 90% of the variance in the joint tuning function for over 91% of MT neurons. These results suggest 1) that each feature can be read out independently from MT by simply averaging across the population without regard to the other feature and 2) that the inseparable representations seen in subsequent areas, such as MST, must be computed beyond MT. Intriguingly, we found that the remaining nonseparable component of the joint tuning function often manifested as small but systematic changes in the neurons' preferences for one feature as the other one was varied. We believe this reflects the local columnar organization of tuning for direction and binocular disparity in MT, indicating that joint tuning may provide a new tool with which to probe functional architecture.

Receptive-field subfields of V2 neurons in macaque monkeys are adult-like near birth

Infant primates can discriminate texture-defined form despite their relatively low visual acuity. The neuronal mechanisms underlying this remarkable visual capacity of infants have not been studied in nonhuman primates. Since many V2 neurons in adult monkeys can extract the local features in complex stimuli that are required for form vision, we used two-dimensional dynamic noise stimuli and local spectral reverse correlation to measure whether the spatial map of receptive-field subfields in individual V2 neurons is sufficiently mature near birth to capture local features. As in adults, most V2 neurons in 4-week-old monkeys showed a relatively high degree of homogeneity in the spatial matrix of facilitatory subfields. However, ∼25% of V2 neurons had the subfield map where the neighboring facilitatory subfields substantially differed in their preferred orientations and spatial frequencies. Over 80% of V2 neurons in both infants and adults had "tuned" suppressive profiles in their subfield maps that could alter the tuning properties of facilitatory profiles. The differences in the preferred orientations between facilitatory and suppressive profiles were relatively large but extended over a broad range. Response immaturities in infants were mild; the overall strength of facilitatory subfield responses was lower than that in adults, and the optimal correlation delay ("latency") was longer in 4-week-old infants. These results suggest that as early as 4 weeks of age, the spatial receptive-field structure of V2 neurons is as complex as in adults and the ability of V2 neurons to compare local features of neighboring stimulus elements is nearly adult like.

Local circuit inhibition in the cerebral cortex as the source of gain control and untuned suppression

Theoretical considerations have led to the concept that the cerebral cortex is operating in a balanced state in which synaptic excitation is approximately balanced by synaptic inhibition from the local cortical circuit. This paper is about the functional consequences of the balanced state in sensory cortex. One consequence is gain control: there is experimental evidence and theoretical support for the idea that local circuit inhibition acts as a local automatic gain control throughout the cortex. Second, inhibition increases cortical feature selectivity: many studies of different sensory cortical areas have reported that suppressive mechanisms contribute to feature selectivity. Synaptic inhibition from the local microcircuit should be untuned (or broadly tuned) for stimulus features because of the microarchitecture of the cortical microcircuit. Untuned inhibition probably is the source of Untuned Suppression that enhances feature selectivity. We studied inhibition's function in our experiments, guided by a neuronal network model, on orientation selectivity in the primary visual cortex, V1, of the Macaque monkey. Our results revealed that Untuned Suppression, generated by local circuit inhibition, is crucial for the generation of highly orientation-selective cells in V1 cortex.

Contributions of excitation and suppression in shaping spatial frequency selectivity of V1 neurons as revealed by binocular measurements

Neurons in the early visual cortex are generally highly sensitive to stimuli presented to the two eyes. However, the majority of studies on spatial and temporal aspects of neural responses were based on monocular measurements. To study neurons under more natural, i.e., binocular, conditions, we presented sinusoidal gratings of a variety of spatial frequencies (SF) dichoptically in rapid sequential flashes and analyzed the data using a binocular reverse correlation technique for neurons in cat area 17. The resulting set of data represents a frequency-domain binocular receptive field from which detailed selectivities, both monocular and binocular, could be obtained. Consistent with previous studies, the responses could generally be explained by linear summation of inputs from the two eyes. Suppressive responses were also observed and were delayed typically by 5–15 ms relative to excitatory responses. However, we have found more diverse nature of suppressive responses than those reported previously. The optimal suppressive frequency could be either higher or lower than that of the excitatory responses. The bandwidth of SF tuning of the suppressive responses was usually broader than that of the excitatory responses. Cells with lower optimal SFs for suppression tended to show high optimal SFs and sharp tuning curves. The dynamic shift of optimal SF from low to high SF was accompanied by suppression with earlier onset and higher peak SF or later onset and lower peak SF than excitation. These results suggest that the suppression plays an essential role in generating the temporal dynamics of SF selectivity.

Dynamics of spatial frequency tuning in mouse visual cortex

Neuronal spatial frequency tuning in primary visual cortex (V1) substantially changes over time. In both primates and cats, a shift of the neuron's preferred spatial frequency has been observed from low frequencies early in the response to higher frequencies later in the response. In most cases, this shift is accompanied by a decreased tuning bandwidth. Recently, the mouse has gained attention as a suitable animal model to study the basic mechanisms of visual information processing, demonstrating similarities in basic neuronal response properties between rodents and highly visual mammals. Here we report the results of extracellular single-unit recordings in the anesthetized mouse where we analyzed the dynamics of spatial frequency tuning in V1 and the lateromedial area LM within the lateral extrastriate area V2L. We used a reverse-correlation technique to demonstrate that, as in monkeys and cats, the preferred spatial frequency of mouse V1 neurons shifted from low to higher frequencies later in the response. However, this was not correlated with a clear selectivity increase or enhanced suppression of responses to low spatial frequencies. These results suggest that the neuronal connections responsible for the temporal shift in spatial frequency tuning may considerably differ between mice and monkeys.

Local sensitivity to stimulus orientation and spatial frequency within the receptive fields of neurons in visual area 2 of macaque monkeys

We used dynamic dense noise stimuli and local spectral reverse correlation methods to reveal the local sensitivities of neurons in visual area 2 (V2) of macaque monkeys to orientation and spatial frequency within their receptive fields. This minimized the potentially confounding assumptions that are inherent in stimulus selections. The majority of neurons exhibited a relatively high degree of homogeneity for the preferred orientations and spatial frequencies in the spatial matrix of facilitatory subfields. However, about 20% of all neurons showed maximum orientation differences between neighboring subfields that were greater than 25 deg. The neurons preferring horizontal or vertical orientations showed less inhomogeneity in space than the neurons preferring oblique orientations. Over 50% of all units also exhibited suppressive profiles, and those were more heterogeneous than facilitatory profiles. The preferred orientation and spatial frequency of suppressive profiles differed substantially from those of facilitatory profiles, and the neurons with suppressive subfields had greater orientation selectivity than those without suppressive subfields. The peak suppression occurred with longer delays than the peak facilitation. These results suggest that the receptive field profiles of the majority of V2 neurons reflect the orderly convergence of V1 inputs over space, but that a subset of V2 neurons exhibit more complex response profiles having both suppressive and facilitatory subfields. These V2 neurons with heterogeneous subfield profiles could play an important role in the initial processing of complex stimulus features.

Spatiotemporal frequency tuning dynamics of neurons in the owl visual wulst

The transformation of spatial (SF) and temporal frequency (TF) tuning functions from broad-band/low-pass to narrow band-pass profiles is one of the key emergent properties of neurons in the mammalian primary visual cortex (V1). The mechanisms underlying such transformation are still a matter of ongoing debate. With the aim of providing comparative insights into the issue, we analyzed various aspects of the spatiotemporal tuning dynamics of neurons in the visual wulst of four awake owls. The wulst is the avian telencephalic target of the retinothalamofugal pathway and, in owls, bears striking functional analogy with V1. Most neurons in our sample exhibited fast and large-magnitude adaptation to the visual stimuli with response latencies very similar to those reported for V1. Moreover, latency increased as a function of stimulus SF but not TF, which suggests that parvo- and magno-like geniculate inputs could be converging onto single wulst neurons. No net shifts in preferred SF or TF were observed along the initial second of stimulation, but bandwidth decreased roughly during the first 200 ms after response latency for both stimulus dimensions. For SF, this occurred exclusively as a consequence of low-frequency suppression, whereas suppression was observed both at the low- and high-frequency limbs of TF tuning curves. Overall these results indicate that SF and TF tuning curves in the wulst are shaped by both feedforward and intratelencephalic suppressive mechanisms, similarly to what seems to be the case in the mammalian striate cortex.

Correlation between spatial frequency and orientation selectivity in V1 cortex: implications of a network model

We addressed how spatial frequency and orientation selectivity coexist and co-vary in Macaque primary visual cortex (V1) by simulating cortical layer 4Cα of V1 with a large-scale network model and then comparing the model's behavior with a population of cells we recorded in layer 4Cα. We compared the distributions of orientation and spatial frequency selectivity, as well as the correlation between the two, in the model with what we observed in the 4Cα population. We found that (1) in the model, both spatial frequency and orientation selectivity of neuronal firing are greater and more diverse than the LGN inputs to model neurons; (2) orientation and spatial frequency selectivity co-vary in the model in a way very similar to what we observed in layer 4Cα neurons; (3) in the model, orientation and spatial frequency selectivity co-vary because of intra-cortical inhibition. The results suggest that cortical inhibition provides a common mechanism for selectivity in multiple dimensions.

Time course of cross-orientation suppression in the early visual cortex

Responses of a visual neuron to optimally oriented stimuli can be suppressed by a superposition of another grating with a different orientation. This effect is known as cross-orientation suppression. However, it is still not clear whether the effect is intracortical in origin or a reflection of subcortical processes. To address this issue, we measured spatiotemporal responses to a plaid pattern, a superposition of two gratings, as well as to individual component gratings (optimal and mask) using a subspace reverse-correlation method. Suppression for the plaid was evaluated by comparing the response to that for the optimal grating. For component stimuli, excitatory and negative responses were defined as responses more positive and negative, respectively, than that to a blank stimulus. The suppressive effect for plaids was observed in the vast majority of neurons. However, only approximately 30% of neurons showed the negative response to mask-only gratings. The magnitudes of negative responses to mask-only stimuli were correlated with the degree of suppression for plaid stimuli. Comparing the latencies, we found that the suppression for the plaids starts at about the same time or slightly later than the response onset for the optimal grating and reaches its maximum at about the same time as the peak latency for the mask-only grating. Based on these results, we propose that in addition to the suppressive effect originating at the subcortical stage, delayed suppressive signals derived from the intracortical networks act on the neuron to generate cross-orientation suppression.