Joint representations of color and form in mouse visual cortex described by random pooling from rods and cones.

Spatial transitions in color can aid any visual perception task, and its neural representation, the "integration of color and form," is thought to begin at primary visual cortex (V1). Integration of color and form is untested in mouse V1, yet studies show that the ventral retina provides the necessary substrate from green-sensitive rods and ultraviolet-sensitive cones. Here, we used two-photon imaging in V1 to measure spatial frequency (SF) tuning along four axes of rod and cone contrast space, including luminance and color. We first reveal that V1's sensitivity to color is similar to luminance, yet average SF tuning is significantly shifted lowpass for color. Next, guided by linear models, we used SF tuning along all four color axes to estimate the proportion of neurons that fall into classic models of color opponency, i.e., "single-," "double-," and "non-opponent." Few neurons (∼6%) fit the criteria for double opponency, which are uniquely tuned for chromatic borders. Most of the population can be described as a unimodal distribution ranging from strongly single-opponent to non-opponent. Consistent with recent studies of the rodent and primate retina, our V1 data are well-described by a simple model in which ON and OFF channels to V1 sample the photoreceptor mosaic randomly. Finally, an analysis comparing color opponency to preferred orientation and retinotopy further validates rods, and not cone M-opsin, as opponent with cone S-opsin in the upper visual field.NEW & NOTEWORTHY This study is the first to show that mouse V1 is highly sensitive to UV-green color contrast. Furthermore, it provides a detailed characterization of "color opponency," which is the putative neural basis for color perception. Finally, using an extremely simple yet novel random wiring model, we account for our observations.

Primary visual cortex straightens natural video trajectories.

Many sensory-driven behaviors rely on predictions about future states of the environment. Visual input typically evolves along complex temporal trajectories that are difficult to extrapolate. We test the hypothesis that spatial processing mechanisms in the early visual system facilitate prediction by constructing neural representations that follow straighter temporal trajectories. We recorded V1 population activity in anesthetized macaques while presenting static frames taken from brief video clips, and developed a procedure to measure the curvature of the associated neural population trajectory. We found that V1 populations straighten naturally occurring image sequences, but entangle artificial sequences that contain unnatural temporal transformations. We show that these effects arise in part from computational mechanisms that underlie the stimulus selectivity of V1 cells. Together, our findings reveal that the early visual system uses a set of specialized computations to build representations that can support prediction in the natural environment.

Maps of cone opsin input to mouse V1 and higher visual areas.

Studies in the mouse retina have characterized the spatial distribution of an anisotropic ganglion cell and photoreceptor mosaic, which provides a solid foundation to study how the cortex pools from afferent parallel color channels. In particular, the mouse's retinal mosaic exhibits a gradient of wavelength sensitivity along its dorsoventral axis. Cones at the ventral extreme mainly express S opsin, which is sensitive to ultraviolet (UV) wavelengths. Then, moving toward the retina's dorsal extreme, there is a transition to M-opsin dominance. Here, we tested the hypothesis that the retina's opsin gradient is recapitulated in cortical visual areas as a functional map of wavelength sensitivity. We first identified visual areas in each mouse by mapping retinotopy with intrinsic signal imaging (ISI). Next, we measured ISI responses to stimuli along different directions of the S- and M-color plane to quantify the magnitude of S and M input to each location of the retinotopic maps in five visual cortical areas (V1, AL, LM, PM, and RL). The results illustrate a significant change in the S:M-opsin input ratio along the axis of vertical retinotopy that is consistent with the gradient along the dorsoventral axis of the retina. In particular, V1 populations encoding the upper visual field responded to S-opsin contrast with 6.1-fold greater amplitude than to M-opsin contrast. V1 neurons encoding lower fields responded with 4.6-fold greater amplitude to M- than S-opsin contrast. The maps in V1 and higher visual areas (HVAs) underscore the significance of a wavelength sensitivity gradient for guiding the mouse's behavior.NEW & NOTEWORTHY Two elements of this study are particularly novel. For one, it is the first to quantify cone inputs to mouse visual cortex; we have measured cone input in five visual areas. Next, it is the first study to identify a feature map in the mouse visual cortex that is based on well-characterized anisotropy of cones in the retina; we have identified maps of opsin selectivity in five visual areas.

Automated identification of mouse visual areas with intrinsic signal imaging.

Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (∼1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (∼2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.

Efficient Receptive Field Tiling in Primate V1.

The primary visual cortex (V1) encodes a diverse set of visual features, including orientation, ocular dominance (OD), and spatial frequency (SF), whose joint organization must be precisely structured to optimize coverage within the retinotopic map. Prior experiments have only identified efficient coverage based on orthogonal maps. Here we used two-photon calcium imaging to reveal an alternative arrangement for OD and SF maps in macaque V1; their gradients run parallel but with unique spatial periods, whereby low-SF regions coincide with monocular regions. Next we mapped receptive fields and found surprisingly precise micro-retinotopy that yields a smaller point-image and requires more efficient inter-map geometry, thus underscoring the significance of map relationships. While smooth retinotopy is constraining, studies suggest that it improves both wiring economy and the V1 population code read downstream. Altogether, these data indicate that connectivity within V1 is finely tuned and precise at the level of individual neurons.

Topography and areal organization of mouse visual cortex.

To guide future experiments aimed at understanding the mouse visual system, it is essential that we have a solid handle on the global topography of visual cortical areas. Ideally, the method used to measure cortical topography is objective, robust, and simple enough to guide subsequent targeting of visual areas in each subject. We developed an automated method that uses retinotopic maps of mouse visual cortex obtained with intrinsic signal imaging (Schuett et al., 2002; Kalatsky and Stryker, 2003; Marshel et al., 2011) and applies an algorithm to automatically identify cortical regions that satisfy a set of quantifiable criteria for what constitutes a visual area. This approach facilitated detailed parcellation of mouse visual cortex, delineating nine known areas (primary visual cortex, lateromedial area, anterolateral area, rostrolateral area, anteromedial area, posteromedial area, laterointermediate area, posterior area, and postrhinal area), and revealing two additional areas that have not been previously described as visuotopically mapped in mice (laterolateral anterior area and medial area). Using the topographic maps and defined area boundaries from each animal, we characterized several features of map organization, including variability in area position, area size, visual field coverage, and cortical magnification. We demonstrate that higher areas in mice often have representations that are incomplete or biased toward particular regions of visual space, suggestive of specializations for processing specific types of information about the environment. This work provides a comprehensive description of mouse visuotopic organization and describes essential tools for accurate functional localization of visual areas.

Building maps from maps in primary visual cortex.

Neurons in the visual system respond to more complex and holistic features at each new stage of processing. Often, these features are organized into continuous maps. Could there be a fundamental link between continuous maps and functional hierarchies? Here, we review recent studies regarding V1 maps providing some of the most noteworthy advances in our understanding of how and why maps exist. In particular, we focus on the common theme that some maps are inherited from the input of parallel pathways, which are then intimately linked to the emergence of new functional properties and their corresponding maps. These results on V1 maps may prove to be a unifying framework for hierarchical representations in the visual cortex.

Contrast dependence and differential contributions from somatostatin- and parvalbumin-expressing neurons to spatial integration in mouse V1.

A characteristic feature in the primary visual cortex is that visual responses are suppressed as a stimulus extends beyond the classical receptive field. Here, we examined the role of inhibitory neurons expressing somatostatin (SOM⁺) or parvalbumin (PV⁺) on surround suppression and preferred receptive field size. We recorded multichannel extracellular activity in V1 of transgenic mice expressing channelrhodopsin in SOM⁺ neurons or PV⁺ neurons. Preferred size and surround suppression were measured using drifting square-wave gratings of varying radii and at two contrasts. Consistent with findings in primates, we found that the preferred size was larger for lower contrasts across all cortical depths, whereas the suppression index (SI) showed a trend to decrease with contrast. We then examined the effect of these metrics on units that were suppressed by photoactivation of either SOM⁺ or PV⁺ neurons. When activating SOM⁺ neurons, we found a significant increase in SI at cortical depths >400 µm, whereas activating PV⁺ neurons caused a trend toward lower SIs regardless of cortical depth. Conversely, activating PV⁺ neurons significantly increased preferred size across all cortical depths, similar to lowering contrast, whereas activating SOM⁺ neurons had no systematic effect on preferred size across all depths. These data suggest that SOM⁺ and PV⁺ neurons contribute differently to spatial integration. Our findings are compatible with the notion that SOM⁺ neurons mediate surround suppression, particularly in deeper cortex, whereas PV⁺ activation decreases the drive of the input to cortex and therefore resembles the effects on spatial integration of lowering contrast.

Orthogonal micro-organization of orientation and spatial frequency in primate primary visual cortex.

Orientation and spatial frequency tuning are highly salient properties of neurons in primary visual cortex (V1). The combined organization of these particular tuning properties in the cortical space will strongly shape the V1 population response to different visual inputs, yet it is poorly understood. In this study, we used two-photon imaging in macaque monkey V1 to demonstrate the three-dimensional cell-by-cell layout of both spatial frequency and orientation tuning. We first found that spatial frequency tuning was organized into highly structured maps that remained consistent across the depth of layer II/III, similarly to orientation tuning. Next, we found that orientation and spatial frequency maps were intimately related at the fine spatial scale observed with two-photon imaging. Not only did the map gradients tend notably toward orthogonality, but they also co-varied negatively from cell to cell at the spatial scale of cortical columns.

Anterior-posterior direction opponency in the superficial mouse lateral geniculate nucleus.

We show functional-anatomical organization of motion direction in mouse dorsal lateral geniculate nucleus (dLGN) using two-photon calcium imaging of dense populations in thalamus. Surprisingly, the superficial 75 µm region contains anterior and posterior direction-selective neurons (DSLGNs) intermingled with nondirection-selective neurons, while upward- and downward-selective neurons are nearly absent. Unexpectedly, the remaining neurons encode both anterior and posterior directions, forming horizontal motion-axis selectivity. A model of random wiring consistent with these results makes quantitative predictions about the connectivity of direction-selective retinal ganglion cell (DSRGC) inputs to the superficial dLGN. DSLGNs are more sharply tuned than DSRGCs. These results suggest that dLGN maintains and sharpens retinal direction selectivity and integrates opposing DSRGC subtypes in a functional-anatomical region, perhaps forming a feature representation for horizontal-axis motion, contrary to dLGN being a simple relay. Furthermore, they support recent conjecture that cortical direction and orientation selectivity emerge in part from a previously undescribed motion-selective retinogeniculate pathway.

Traveling waves in visual cortex.

Electrode recordings and imaging studies have revealed that localized visual stimuli elicit waves of activity that travel across primary visual cortex. Traveling waves are present also during spontaneous activity, but they can be greatly reduced by widespread and intensive visual stimulation. In this Review, we summarize the evidence in favor of these traveling waves. We suggest that their substrate may lie in long-range horizontal connections and that their functional role may involve the integration of information over large regions of space.

Robustness of traveling waves in ongoing activity of visual cortex.

Numerous studies have revealed traveling waves of activity in sensory cortex, both following sensory stimulation and during ongoing activity. We contributed to this body of work by measuring the spike-triggered average of the local field potential (stLFP) at multiple concurrent locations (Nauhaus et al., 2009) in the visual cortex of anesthetized cats and macaques. We found the stLFP to be progressively delayed at increasing distances from the site of the triggering spikes, and interpreted this as a traveling wave of depolarization originating from that site. Our results were criticized, however, on two grounds. First, a study using the same recording techniques in the visual cortex of awake macaques reported an apparent lack of traveling waves, and proposed that traveling waves could arise artifactually from excessive filtering of the field potentials (Ray and Maunsell, 2011). Second, the interpretability of the stLFP was questioned (Kenneth Miller, personal communication), as the stLFP must reflect not only interactions between spike trains and field potentials, but also correlations within and across the spike trains. Here, we show that our data and interpretation are not imperiled by these criticisms. We reanalyzed our field potentials to remove any possible artifact due to filtering and to discount the effects of correlations within and across the triggering spike trains. In both cases, we found that the traveling waves were still present. In fact, closer inspection of Ray and Maunsell's (2011) data from awake cortex shows that they do agree with ours, as they contain clear evidence for traveling waves.

Nonlinearity of two-photon Ca2+ imaging yields distorted measurements of tuning for V1 neuronal populations.

We studied the relative accuracy of drifting gratings and noise stimuli for functionally characterizing neural populations using two-photon calcium imaging. Calcium imaging has the potential to distort measurements due to nonlinearity in the conversion from spikes to observed fluorescence. We demonstrate a dramatic impact of fluorescence saturation on functional measurements in ferret V1 by showing that responses to drifting gratings strongly violate contrast invariance of orientation tuning, a fundamental property of the spike rates. The observed relationship is consistent with saturation that clips the high-contrast tuning curve peaks by ∼40%. The nonlinearity was also apparent in mouse V1 responses to drifting gratings, but not as strong as in the ferret. Contrast invariance holds, however, for tuning curves measured with a randomized grating stimulus. This finding is consistent with prior work showing that the linear portion of a linear-nonlinear system can be recovered with reverse correlation. Furthermore, we demonstrate that a noise stimulus is more effective at keeping spike rates in the linear operating regime of a saturating nonlinearity, which both maximizes signal-to-noise ratios and simplifies the recovery of fast spike dynamics from slow calcium transients. Finally, we uncover spatiotemporal receptive fields by removing the nonlinearity and slow calcium transient from a model of fluorescence generation, which allowed us to observe dynamic sharpening of orientation tuning. We conclude that for two-photon recordings it is imperative that one considers the nonlinear distortion when designing stimuli and interpreting results, especially in sensory areas, species, or cell types with high firing rates.

Functional specialization of seven mouse visual cortical areas.

To establish the mouse as a genetically tractable model for high-order visual processing, we characterized fine-scale retinotopic organization of visual cortex and determined functional specialization of layer 2/3 neuronal populations in seven retinotopically identified areas. Each area contains a distinct visuotopic representation and encodes a unique combination of spatiotemporal features. Areas LM, AL, RL, and AM prefer up to three times faster temporal frequencies and significantly lower spatial frequencies than V1, while V1 and PM prefer high spatial and low temporal frequencies. LI prefers both high spatial and temporal frequencies. All extrastriate areas except LI increase orientation selectivity compared to V1, and three areas are significantly more direction selective (AL, RL, and AM). Specific combinations of spatiotemporal representations further distinguish areas. These results reveal that mouse higher visual areas are functionally distinct, and separate groups of areas may be specialized for motion-related versus pattern-related computations, perhaps forming pathways analogous to dorsal and ventral streams in other species.

Local origin of field potentials in visual cortex.

The local field potential (LFP) is increasingly used to measure the combined activity of neurons within a region of tissue. Yet, available estimates of the size of this region are highly disparate, ranging from several hundred microns to a few millimeters. To measure the size of this region directly, we used a combination of multielectrode recordings and optical imaging. We determined the orientation selectivity of stimulus-evoked LFP signals in primary visual cortex and were able to predict it on the basis of the surrounding map of orientation preference. The results show that > 95% of the LFP signal originates within 250 microm of the recording electrode. This quantitative estimate indicates that LFPs are more local than often recognized and provides a guide to the interpretation of the increasing number of studies that rest on LFP recordings.

Stimulus contrast modulates functional connectivity in visual cortex.

Neurons in visual cortex are linked by an extensive network of lateral connections. To study the effect of these connections on neural responses, we recorded spikes and local field potentials (LFPs) from multi-electrode arrays that were implanted in monkey and cat primary visual cortex. Spikes at each location generated outward traveling LFP waves. When the visual stimulus was absent or had low contrast, these LFP waves had large amplitudes and traveled over long distances. Their effect was strong: LFP traces at any site could be predicted by the superposition of waves that were evoked by spiking in a approximately 1.5-mm radius. As stimulus contrast increased, both the magnitude and the distance traveled by the waves progressively decreased. We conclude that the relative weight of feedforward and lateral inputs in visual cortex is not fixed, but rather depends on stimulus contrast. Lateral connections dominate at low contrast, when spatial integration of signals is perhaps most beneficial.

Neuronal selectivity and local map structure in visual cortex.

The organization of primary visual cortex (V1) into functional maps makes individual cells operate in a variety of contexts. For instance, some neurons lie in regions of fairly homogeneous orientation preference (iso-orientation domains), while others lie in regions with a variety of preferences (e.g., pinwheel centers). We asked whether this diversity in local map structure correlates with the degree of selectivity of spike responses. We used a combination of imaging and electrophysiology to reveal that neurons in regions of homogeneous orientation preference have much sharper tuning. Moreover, in both monkeys and cats, a common principle links the structure of the orientation map, on the spatial scale of dendritic integration, to the degree of selectivity of individual cells. We conclude that neural computation is not invariant across the cortical surface. This finding must factor into future theories of receptive field wiring and map development.

Precise alignment of micromachined electrode arrays with V1 functional maps.

Recent theoretical models of primary visual cortex predict a relationship between receptive field properties and the location of the neuron within the orientation maps. Testing these predictions requires the development of new methods that allow the recording of single units at various locations across the orientation map. Here we present a novel technique for the precise alignment of functional maps and array recordings. Our strategy consists of first measuring the orientation maps in V1 using intrinsic optical imaging. A micromachined electrode array is subsequently implanted in the same patch of cortex for electrophysiological recordings, including the measurement of orientation tuning curves. The location of the array within the map is obtained by finding the position that maximizes the agreement between the preferred orientations measured electrically and optically. Experimental results of the alignment procedure from two implementations in monkey V1 are presented. The estimated accuracy of the procedure is evaluated using computer simulations. The methodology should prove useful in studying how signals from the local neighborhood of a neuron, thought to provide a dominant feedback signal, shape the receptive field properties in V1.