Mapping spatial frequency preferences across human primary visual cortex

Preferred spatial frequency covaries with cortical magnification in human primary visual cortex

Primary visual cortex (V1) has played a key role in understanding the organization of cerebral cortex. Both structural and functional properties vary sharply throughout the human V1 map. Despite large variation, underlying constancies computed from the covariation pattern of V1 properties have been proposed. Such constancies would imply that V1 is composed of multiple identical units whose visual properties differ only due to differences in their inputs. To test this, we used fMRI to investigate how V1 cortical magnification and preferred spatial frequency covary across eccentricity and polar angle, and across individual observers (n=40). The two properties correlated across individuals, such that those with higher overall cortical magnification (i.e., larger V1 maps) had higher preferred spatial frequency (integrated across the map). Although correlated, the two properties were not proportional, and hence their ratio (mm of cortex per stimulus cycle) was not constant. Cortical magnification and preferred spatial frequency were strongly correlated across eccentricity and across polar angle, however their relation differed between these dimensions: they were proportional across eccentricity but not polar angle. The constant ratio of cortical magnification to preferred spatial frequency across eccentricity suggests a shared underlying cause of variation in the two properties, e.g., the gradient of retinal ganglion cell density across eccentricity. In contrast, the deviation from proportionality around polar angle implies that cortical variation differs from that in retina along this dimension. Thus, a constancy hypothesis is supported for one of the two spatial dimensions of V1, highlighting the importance of examining the full 2D-map, in multiple individuals, to understand how V1 is organized.

Traveling waves in the human visual cortex: An MEG-EEG model-based approach

Brain oscillations might be traveling waves propagating in cortex. Studying their propagation within single cortical areas has mostly been restricted to invasive measurements. Their investigation in healthy humans, however, requires non-invasive recordings, such as MEG or EEG. Identifying traveling waves with these techniques is challenging because source summation, volume conduction, and low signal-to-noise ratios make it difficult to localize cortical activity from sensor responses. The difficulty is compounded by the lack of a known ground truth in traveling wave experiments. Rather than source-localizing cortical responses from sensor activity, we developed a two-part model-based neuroimaging approach: (1) The putative neural sources of a propagating oscillation were modeled within primary visual cortex (V1) via retinotopic mapping from functional MRI recordings (encoding model); and (2) the modeled sources were projected onto MEG and EEG sensors to predict the resulting signal using a biophysical head model. We tested our model by comparing its predictions against the MEG-EEG signal obtained when participants viewed visual stimuli designed to elicit either fovea-to-periphery or periphery-to-fovea traveling waves or standing waves in V1, in which ground truth cortical waves could be reasonably assumed. Correlations on within-sensor phase and amplitude relations between predicted and measured data revealed good model performance. Crucially, the model predicted sensor data more accurately when the input to the model was a traveling wave going in the stimulus direction compared to when the input was a standing wave, or a traveling wave in a different direction. Furthermore, model accuracy peaked at the spatial and temporal frequency parameters of the visual stimulation. Together, our model successfully recovers traveling wave properties in cortex when they are induced by traveling waves in stimuli. This provides a sound basis for using MEG-EEG to study endogenous traveling waves in cortex and test hypotheses related with their role in cognition.

Color and Spatial Frequency Provide Functional Signatures of Retinotopic Visual Areas

Primate vision relies on retinotopically organized cortical parcels defined by representations of hemifield (upper vs lower visual field), eccentricity (fovea vs periphery), and area (V1, V2, V3, V4). Here we test for functional signatures of these organizing principles. We used functional magnetic resonance imaging to measure responses to gratings varying in spatial frequency, color, and saturation across retinotopically defined parcels in two macaque monkeys, and we developed a Sparse Supervised Embedding (SSE) analysis to identify stimulus features that best distinguish cortical parcels from each other. Constraining the SSE model to distinguish just eccentricity representations of the voxels revealed the expected variation of spatial frequency and S-cone modulation with eccentricity. Constraining the model according to the dorsal/ventral location and retinotopic area of each voxel provided unexpected functional signatures, which we investigated further with standard univariate analyses. Posterior parcels (V1) were distinguished from anterior parcels (V4) by differential responses to chromatic and luminance contrast, especially of low-spatial-frequency gratings. Meanwhile, ventral parcels were distinguished from dorsal parcels by differential responses to chromatic and luminance contrast, especially of colors that modulate all three cone types. The dorsal/ventral asymmetry not only resembled differences between candidate dorsal and ventral subdivisions of human V4 but also extended to include all retinotopic visual areas, starting in V1 and increasing from V1 to V4. The results provide insight into the functional roles of different retinotopic areas and demonstrate the utility of SSE as a data-driven tool for generating hypotheses about cortical function and behavior.

A bias in transsaccadic perception of spatial frequency changes

Visual processing differs between the foveal and peripheral visual field. These differences can lead to different appearances of objects in the periphery and the fovea, posing a challenge to perception across saccades. Differences in the appearance of visual features between the peripheral and foveal visual field may bias change discrimination across saccades. Previously it has been reported that spatial frequency (SF) appears higher in the periphery compared to the fovea (Davis et al., 1987). In this study, we investigated the visual appearance of SF before and after a saccade and the discrimination of SF changes during saccades. In addition, we tested the contributions of pre- and postsaccadic information to change discrimination performance. In the first experiment, we found no differences in the appearance of SF before and after a saccade. However, participants showed a clear bias to report SF increases. Interestingly, a 200-ms postsaccadic blank improved the precision of the responses but did not affect the bias. In the second experiment, participants showed lower thresholds for SF increases than for decreases, suggesting that the bias in the first experiment was not just a response bias. Finally, we asked participants to discriminate the SF of stimuli presented before a saccade. Thresholds in the presaccadic discrimination task were lower than in the change discrimination task, suggesting that transsaccadic change discrimination is not merely limited by presaccadic discrimination in the periphery. The change direction bias might stem from more effective masking or overwriting of the presaccadic stimulus by the postsaccadic low SF stimulus.

Auditory and Visual Gratings Elicit Distinct Gamma Responses

Sensory stimulation is often accompanied by fluctuations at high frequencies (>30 Hz) in brain signals. These could be "narrowband" oscillations in the gamma band (30-70 Hz) or nonoscillatory "broadband" high-gamma (70-150 Hz) activity. Narrowband gamma oscillations, which are induced by presenting some visual stimuli such as gratings and have been shown to weaken with healthy aging and the onset of Alzheimer's disease, hold promise as potential biomarkers. However, since delivering visual stimuli is cumbersome as it requires head stabilization for eye tracking, an equivalent auditory paradigm could be useful. Although simple auditory stimuli have been shown to produce high-gamma activity, whether specific auditory stimuli can also produce narrowband gamma oscillations is unknown. We tested whether auditory ripple stimuli, which are considered an analog to visual gratings, could elicit narrowband oscillations in auditory areas. We recorded 64-channel electroencephalogram from male and female (18 each) subjects while they either fixated on the monitor while passively viewing static visual gratings or listened to stationary and moving ripples, played using loudspeakers, with their eyes open or closed. We found that while visual gratings induced narrowband gamma oscillations with suppression in the alpha band (8-12 Hz), auditory ripples did not produce narrowband gamma but instead elicited very strong broadband high-gamma response and suppression in the beta band (14-26 Hz). Even though we used equivalent stimuli in both modalities, our findings indicate that the underlying neuronal circuitry may not share ubiquitous strategies for stimulus processing.

Normalization by orientation-tuned surround in human V1-V3

An influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a multi-stage computation. The first stage is linear filtering. The second stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of the linear filters in quadrature phase. The third stage is normalization, in which a local population of complex cells mutually inhibit one another. Because the population includes cells tuned to a range of orientations and spatial frequencies, the result is that the responses are effectively normalized by the local stimulus contrast. Here, using evidence from human functional MRI, we show that the classical model fails to account for the relative responses to two classes of stimuli: straight, parallel, band-passed contours (gratings), and curved, band-passed contours (snakes). The snakes elicit fMRI responses that are about twice as large as the gratings, yet a traditional divisive normalization model predicts responses that are about the same. Motivated by these observations and others from the literature, we implement a divisive normalization model in which cells matched in orientation tuning ("tuned normalization") preferentially inhibit each other. We first show that this model accounts for differential responses to these two classes of stimuli. We then show that the model successfully generalizes to other band-pass textures, both in V1 and in extrastriate cortex (V2 and V3). We conclude that even in primary visual cortex, complex features of images such as the degree of heterogeneity, can have large effects on neural responses.

Expectation Cues and False Percepts Generate Stimulus-Specific Activity in Distinct Layers of the Early Visual Cortex

Perception has been proposed to result from the integration of feedforward sensory signals with internally generated feedback signals. Feedback signals are believed to play an important role in driving false percepts, that is, seeing things that are not actually there. Feedforward and feedback influences on perception can be studied using layer-specific fMRI, which we used here to interrogate neural activity underlying high-confidence false percepts while healthy human participants (N = 25, male and female) performed a perceptual orientation discrimination task. Auditory cues implicitly signaled the most likely upcoming orientation (referred to here as expectations). These expectations induced orientation-specific templates in the deep and superficial layers of V2, without affecting perception. In contrast, the orientation of falsely perceived stimuli with high confidence was reflected in the middle input layers of V2, suggesting a feedforward signal contributing to false percepts. The prevalence of high-confidence false percepts was related to everyday hallucination severity in a separate online sample (N = 100), suggesting a possible link with abnormal perceptual experiences. These results reveal a potential feedforward mechanism underlying false percepts, reflected by spontaneous stimulus-like activity in the input layers of the visual cortex, independent of top-down signals reflecting cued orientations.SIGNIFICANCE STATEMENT False percepts have been suggested to arise through excessive feedback signals. However, feedforward contributions to false percepts have remained largely understudied. Laminar fMRI has been shown to be useful in distinguishing feedforward from feedback activity as it allows the imaging of different cortical layers. In the present study we demonstrate that although cued orientations are encoded in the feedback layers of the visual cortex, the content of the false percepts are encoded in the feedforward layers and did not rely on these cued orientations. This shows that false percepts can in principle emerge from random feedforward signals in the visual cortex, with possible implications for disorders hallmarked by hallucinations like schizophrenia and Parkinson's disease.

Featural representation and internal noise underlie the eccentricity effect in contrast sensitivity

Human visual performance for basic visual dimensions (e.g., contrast sensitivity and acuity) peaks at the fovea and decreases with eccentricity. The eccentricity effect is related to the larger surface area of the visual cortex corresponding to the fovea, but it is unknown if differential feature tuning contributes to this eccentricity effect. Here, we investigated two system-level computations underlying the eccentricity effect: featural representation (tuning) and internal noise. Observers (both sexes) detected a Gabor embedded in filtered white noise which appeared at the fovea or one of four perifoveal locations. We used psychophysical reverse correlation to estimate the weights assigned by the visual system to a range of orientations and spatial frequencies (SFs) in noisy stimuli, which are conventionally interpreted as perceptual sensitivity to the corresponding features. We found higher sensitivity to task-relevant orientations and SFs at the fovea than the perifovea, and no difference in selectivity for either orientation or SF. Concurrently, we measured response consistency using a double-pass method, which allowed us to infer the level of internal noise by implementing a noisy observer model. We found lower internal noise at the fovea than perifovea. Finally, individual variability in contrast sensitivity correlated with sensitivity to and selectivity for task-relevant features as well as with internal noise. Moreover, the behavioral eccentricity effect mainly reflects the foveal advantage in orientation sensitivity compared to other computations. These findings suggest that the eccentricity effect stems from a better representation of task-relevant features and lower internal noise at the fovea than at the perifovea.

Polar angle asymmetries in visual perception and neural architecture

Human visual performance changes with visual field location. It is best at the center of gaze and declines with eccentricity, and also varies markedly with polar angle. These perceptual polar angle asymmetries are linked to asymmetries in the organization of the visual system. We review and integrate research quantifying how performance changes with visual field location and how this relates to neural organization at multiple stages of the visual system. We first briefly review how performance varies with eccentricity and the neural foundations of this effect. We then focus on perceptual polar angle asymmetries and their neural foundations. Characterizing perceptual and neural variations across and around the visual field contributes to our understanding of how the brain translates visual signals into neural representations which form the basis of visual perception.

Differences in visual stimulation between reading and walking and implications for myopia development

Visual input plays an important role in the development of myopia (nearsightedness), a visual disorder that blurs vision at far distances. The risk of myopia progression increases with the time spent reading and decreases with outdoor activity for reasons that remain poorly understood. To investigate the stimulus parameters driving this disorder, we compared the visual input to the retina of humans performing two tasks associated with different risks of myopia progression, reading and walking. Human subjects performed the two tasks while wearing glasses with cameras and sensors that recorded visual scenes and visuomotor activity. When compared with walking, reading black text in white background reduced spatiotemporal contrast in central vision and increased it in peripheral vision, leading to a pronounced reduction in the ratio of central/peripheral strength of visual stimulation. It also made the luminance distribution heavily skewed toward negative dark contrast in central vision and positive light contrast in peripheral vision, decreasing the central/peripheral stimulation ratio of ON visual pathways. It also decreased fixation distance, blink rate, pupil size, and head-eye coordination reflexes dominated by ON pathways. Taken together with previous work, these results support the hypothesis that reading drives myopia progression by understimulating ON visual pathways.

Natural scene sampling reveals reliable coarse-scale orientation tuning in human V1

Orientation selectivity in primate visual cortex is organized into cortical columns. Since cortical columns are at a finer spatial scale than the sampling resolution of standard BOLD fMRI measurements, analysis approaches have been proposed to peer past these spatial resolution limitations. It was recently found that these methods are predominantly sensitive to stimulus vignetting - a form of selectivity arising from an interaction of the oriented stimulus with the aperture edge. Beyond vignetting, it is not clear whether orientation-selective neural responses are detectable in BOLD measurements. Here, we leverage a dataset of visual cortical responses measured using high-field 7T fMRI. Fitting these responses using image-computable models, we compensate for vignetting and nonetheless find reliable tuning for orientation. Results further reveal a coarse-scale map of orientation preference that may constitute the neural basis for known perceptual anisotropies. These findings settle a long-standing debate in human neuroscience, and provide insights into functional organization principles of visual cortex.

Linking individual differences in human primary visual cortex to contrast sensitivity around the visual field

A central question in neuroscience is how the organization of cortical maps relates to perception, for which human primary visual cortex (V1) is an ideal model system. V1 nonuniformly samples the retinal image, with greater cortical magnification (surface area per degree of visual field) at the fovea than periphery and at the horizontal than vertical meridian. Moreover, the size and cortical magnification of V1 varies greatly across individuals. Here, we used fMRI and psychophysics in the same observers to quantify individual differences in V1 cortical magnification and contrast sensitivity at the four polar angle meridians. Across observers, the overall size of V1 and localized cortical magnification positively correlated with contrast sensitivity. Moreover, greater cortical magnification and higher contrast sensitivity at the horizontal than the vertical meridian were strongly correlated. These data reveal a link between cortical anatomy and visual perception at the level of individual observer and stimulus location.