Responses In Human Visual Cortex Research Articles

The role of awareness in shaping responses in human visual cortex

The visual cortex contains information about stimuli even when they are not consciously perceived. However, it remains unknown whether the visual system integrates local features into global objects without awareness. Here, we tested this by measuring brain activity in human observers viewing fragmented shapes that were either visible or rendered invisible by fast counterphase flicker. We then projected measured neural responses to these stimuli back into visual space. Visible stimuli caused robust responses reflecting the positions of their component fragments. Their neural representations also strongly resembled one another regardless of local features. By contrast, representations of invisible stimuli differed from one another and, crucially, also from visible stimuli. Our results demonstrate that even the early visual cortex encodes unconscious visual information differently from conscious information, presumably by only encoding local features. This could explain previous conflicting behavioural findings on unconscious visual processing.

Representational Geometries Reveal Differential Effects of Response Correlations on Population Codes in Neurophysiology and Functional Magnetic Resonance Imaging.

Two sensory neurons usually display trial-by-trial spike-count correlations given the repeated representations of a stimulus. The effects of such response correlations on population-level sensory coding have been the focal contention in computational neuroscience over the past few years. In the meantime, multivariate pattern analysis (MVPA) has become the leading analysis approach in functional magnetic resonance imaging (fMRI), but the effects of response correlations among voxel populations remain underexplored. Here, instead of conventional MVPA analysis, we calculate linear Fisher information of population responses in human visual cortex (five males, one female) and hypothetically remove response correlations between voxels. We found that voxelwise response correlations generally enhance stimulus information, a result standing in stark contrast to the detrimental effects of response correlations reported in empirical neurophysiological studies. By voxel-encoding modeling, we further show that these two seemingly opposite effects actually can coexist within the primate visual system. Furthermore, we use principal component analysis to decompose stimulus information in population responses onto different principal dimensions in a high-dimensional representational space. Interestingly, response correlations simultaneously reduce and enhance information on higher- and lower-variance principal dimensions, respectively. The relative strength of the two antagonistic effects within the same computational framework produces the apparent discrepancy in the effects of response correlations in neuronal and voxel populations. Our results suggest that multivariate fMRI data contain rich statistical structures that are directly related to sensory information representation, and the general computational framework to analyze neuronal and voxel population responses can be applied in many types of neural measurements.SIGNIFICANCE STATEMENT Despite the vast research interest in the effect of spike-count noise correlations on population codes in neurophysiology, it remains unclear how the response correlations between voxels influence MVPA in human imaging. We used an information-theoretic approach and showed that unlike the detrimental effects of response correlations reported in neurophysiology, voxelwise response correlations generally improve sensory coding. We conducted a series of in-depth analyses and demonstrated that neuronal and voxel response correlations can coexist within the visual system and share some common computational mechanisms. These results shed new light on how the population codes of sensory information can be evaluated via different neural measurements.

Delayed divisive normalization predicts temporal dynamics of neural responses in human visual cortex

Delayed divisive normalization predicts temporal dynamics of neural responses in human visual cortex

Cortical mechanisms of visual brightness.

SUMMARYThe primary visual cortex signals the onset of light and dark stimuli with ON and OFF cortical pathways. Here, we demonstrate that both pathways generate similar response increments to large homogeneous surfaces and their response average increases with surface brightness. We show that, in cat visual cortex, response dominance from ON or OFF pathways is bimodally distributed when stimuli are smaller than one receptive field center but unimodally distributed when they are larger. Moreover, whereas small bright stimuli drive opposite responses from ON and OFF pathways (increased versus suppressed activity), large bright surfaces drive similar response increments. We show that this size-brightness relation emerges because strong illumination increases the size of light surfaces in nature and both ON and OFF cortical neurons receive input from ON thalamic pathways. We conclude that visual scenes are perceived as brighter when the average response increments from ON and OFF cortical pathways become stronger.

Temporal Dynamics of Neural Responses in Human Visual Cortex.

Neural responses to visual stimuli exhibit complex temporal dynamics, including subadditive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic recordings from patients presented with stimuli that varied in duration, interstimulus interval (ISI) and contrast. Aggregating data across patients from both sexes yielded 98 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several nonlinear features. Peak response amplitude saturates with high contrast and longer stimulus durations, the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs, and response latency decreases with increasing contrast. These features are accurately captured by a computational model composed of a small set of canonical neuronal operations, that is, linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast- and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex and demonstrate that a simple model captures these dynamics at millisecond resolution.SIGNIFICANCE STATEMENT Sensory inputs and neural responses change continuously over time. It is especially challenging to understand a system that has both dynamic inputs and outputs. Here, we use a computational modeling approach that specifies computations to convert a time-varying input stimulus to a neural response time course, and we use this to predict neural activity measured in the human visual cortex. We show that this computational model predicts a wide variety of complex neural response shapes, which we induced experimentally by manipulating the duration, repetition, and contrast of visual stimuli. By comparing data and model predictions, we uncover systematic properties of temporal dynamics of neural signals, allowing us to better understand how the brain processes dynamic sensory information.

Signals from Single-Opponent Cortical Cells in the Human cVEP.

We used the chromatic visual evoked potential (cVEP) to study responses in human visual cortex evoked by equiluminant color stimuli for 6 male and 11 female observers. Large-area, colored squares were used to stimulate Single-Opponent cells preferentially, and fine color-checkerboard stimuli were used to activate Double-Opponent responses preferentially. Stimuli were modulated along the following two directions in color space: (1) the cardinal direction, L-M or M-L of DKL (Derrington, Krauskopf, and Lennie) space; and (2) the line from the white point to the color of the Red LED in the display screen, which was approximately intermediate between the L-M and -S directions in DKL space in cone-contrast coordinates. The amplitudes of cVEPs to large squares were smaller than those to checkerboards, and the latency of the cVEP response to squares was significantly less than the checkerboard latency. The latency of cVEP responses to the squares varied little with cone-contrast unlike the steep reduction of latency with cone-contrast observed in responses to color checkerboard patterns. The dynamic differences between cVEPs to squares and checkerboards support the hypothesis that a distinct neuronal mechanism responded to squares: Single-Opponent cells. Response amplitude, latency, and transientness-and their dependence on cone-contrast-were similar in the responses in the L-M and Red color directions. The similarity supports the hypothesis that the Single-Opponent signals in the cVEP come from a distinct population of cells that receives subtractive inputs from L and M cones, either L-M or M-L.SIGNIFICANCE STATEMENT This article is about characterizing the visual behavior of a distinct population of neurons in the human visual cortex, the Single-Opponent color cells. Based on single-cell results in the visual cortex of macaque monkeys, we used large uniformly colored stimuli to isolate the responses of Single-Opponent cells in the chromatic visual evoked potential (cVEP) recorded on the scalp of human observers. VEP signals recorded under conditions believed to reveal Single-Opponent responses are small and transient. Their time course is relatively unaffected by cone-contrast, and they are relatively insensitive to stimulus modulation of short wavelength-sensitive S cones. Because Single-Opponent cells convey signals that can be used to judge the color of scene illumination, knowing their visual properties is important for understanding color vision.

Voxel-wise binocular energy models for binocular disparity decoding

Binocular disparity is a powerful cue for depth perception in three-dimensional (3D) space. Some neurophysiological studies proposed the binocular phase-shift and position-shift energy models to predict the responses of individual disparity-tuned neurons in cats and macaques. By far, it is unclear how to use binocular energy models to characterize the voxels’ responses in human visual cortex. In this study, we introduced the binocular energy models to the functional magnetic resonance imaging study and constructed the position-shift receptive-field model (Position-RFM) and the phase-shift receptive-field model (Phase-RFM) to predict voxel responses to disparity and to identify novel disparity levels from voxel responses. The results revealed that Phase-RFM outperformed Position-RFM in fitting the voxel responses for all the visual regions. Moreover, the novel disparity levels can be better identified from voxel’s responses in visual regions by Phase-RFM than Position-RFM. The findings may suggest that Phase-RFM can better encode the responses of disparity-tuned neuron populations than Position-RFM for human visual regions.

Voxel-Wise Linearity Analysis of Increments and Decrements in BOLD Responses in Human Visual Cortex Using a Contrast Adaptation Paradigm.

The linearity of BOLD responses is a fundamental presumption in most analysis procedures for BOLD fMRI studies. Previous studies have examined the linearity of BOLD signal increments, but less is known about the linearity of BOLD signal decrements. The present study assessed the linearity of both BOLD signal increments and decrements in the human primary visual cortex using a contrast adaptation paradigm. Results showed that both BOLD signal increments and decrements kept linearity to long stimuli (e.g., 3 s, 6 s), yet, deviated from linearity to transient stimuli (e.g., 1 s). Furthermore, a voxel-wise analysis showed that the deviation patterns were different for BOLD signal increments and decrements: while the BOLD signal increments demonstrated a consistent overestimation pattern, the patterns for BOLD signal decrements varied from overestimation to underestimation. Our results suggested that corrections to deviations from linearity of transient responses should consider the different effects of BOLD signal increments and decrements.

A multiplicity of color-responsive cortical mechanisms revealed by the dynamics of cVEPs

Our results connect higher-order color mechanisms deduced from psychophysics with the known diversity of populations of double-opponent, color-responsive cells in V1. We used the chromatic visual evoked potential, the cVEP, to study responses in human visual cortex to equiluminant color patterns. Stimuli were modulated along three directions in color space: the cardinal directions, L-M and S, and along the line in color space from the white point to the color of the Red LED in the display screen (the Red direction). The Red direction is roughly intermediate between L-M and S in DKL space in cone-contrast coordinates. While cVEP response amplitude, latency, and width--and their dependences on cone contrast-- were similar in the L-M and Red directions, the Transientness of the Red response was significantly greater than for responses to stimuli in the L-M direction and in the S direction. This difference in response dynamics supports the concept that there are multiple, distinct neuronal populations, so-called higher- order color mechanisms, for color perception within human V1 cortex.

History Modulates Early Sensory Processing of Salient Distractors.

To find important objects, we must focus on our goals, ignore distractions, and take our changing environment into account. This is formalized in models of visual search whereby goal-driven, stimulus-driven, and history-driven factors are integrated into a priority map that guides attention. Stimulus history robustly influences where attention is allocated even when the physical stimulus is the same: when a salient distractor is repeated over time, it captures attention less effectively. A key open question is how we come to ignore salient distractors when they are repeated. Goal-driven accounts propose that we use an active, expectation-driven mechanism to attenuate the distractor signal (e.g., predictive coding), whereas stimulus-driven accounts propose that the distractor signal is attenuated because of passive changes to neural activity and inter-item competition (e.g., adaptation). To test these competing accounts, we measured item-specific fMRI responses in human visual cortex during a visual search task where trial history was manipulated (colors unpredictably switched or were repeated). Consistent with a stimulus-driven account of history-based distractor suppression, we found that repeated singleton distractors were suppressed starting in V1, and distractor suppression did not increase in later visual areas. In contrast, we observed signatures of goal-driven target enhancement that were absent in V1, increased across visual areas, and were not modulated by stimulus history. Our data suggest that stimulus history does not alter goal-driven expectations, but rather modulates canonically stimulus-driven sensory responses to contribute to a temporally integrated representation of priority.SIGNIFICANCE STATEMENT Visual search refers to our ability to find what we are looking for in a cluttered visual world (e.g., finding your keys). To perform visual search, we must integrate information about our goals (e.g., "find the red keychain"), the environment (e.g., salient items capture your attention), and changes to the environment (i.e., stimulus history). Although stimulus history impacts behavior, the neural mechanisms that mediate history-driven effects remain debated. Here, we leveraged fMRI and multivariate analysis techniques to measure history-driven changes to the neural representation of items during visual search. We found that stimulus history influenced the representation of a salient "pop-out" distractor starting in V1, suggesting that stimulus history operates via modulations of early sensory processing rather than goal-driven expectations.

Modeling the temporal dynamics of neural responses in human visual cortex

Cortical responses to visual stimuli exhibit complex temporal dynamics, including sub-additive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. Multiple computational models have been proposed to account for these dynamics in several measurement domains, including single-cell recordings, psychophysics, and fMRI. It is challenging to compare these models because there are differences in model form, test stimuli, and instrument. Here we present a new dataset that is well-suited to compare models of neural temporal dynamics. The dataset is from electrocorticographic (ECoG) recordings of human visual cortex, which measures cortical neural population responses with high spatial and temporal precision. The stimuli were large, static contrast patterns and varied systematically in contrast, duration, and inter-stimulus interval (ISI). Time-varying broadband responses were computed using the power envelope of the band-pass filtered voltage time course (50-170 Hz) recorded from a total of 126 electrodes in ten epilepsy patients, covering earlier (V1-V4) and higher-order (LO, TO, IPS) retinotopic maps. In all visual regions, the ECoG broadband responses show several non-linear features: peak response amplitude saturates with high contrast and long stimulus durations; response latency decreases with increasing contrast; and the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs. These features were well predicted by a computational model (Zhou, Benson, Kay and Winawer, 2019) comprised of a small set of canonical neuronal operations: linear filtering, rectification, exponentiation, and a delayed divisive gain control. These results demonstrate that a simple computational model comprised of canonical neuronal computations captures a wide range of temporal and contrast-dependent neuronal dynamics at millisecond resolution. Finally, we present a software repository that implements models of temporal dynamics in a modular fashion, enabling the comparison of many models fit to the same data and analyzed with the same methods.

Layer-specific modulation of visual responses in human visual cortex by emotional faces

Layer-specific modulation of visual responses in human visual cortex by emotional faces

Intracranial recordings reveal unique shape and timing of responses in human visual cortex during illusory visual events

During binocular rivalry, perception spontaneously changes without any alteration to the visual stimulus. What neural events bring about this illusion that a constant stimulus is changing? We recorded from intracranial electrodes placed on the occipital and posterior temporal cortex of two patients with epilepsy while they experienced illusory changes of a face-house binocular-rivalry stimulus or observed a control stimulus that physically changed. We performed within-patient comparisons of broadband high-frequency responses, focusing on single epochs recorded along the ventral processing stream. We found transient face- and house-selective responses localized to the same electrodes for illusory and physical changes, but the temporal characteristics of these responses markedly differed. In comparison with physical changes, responses to illusory changes were longer lasting, in particular exhibiting a characteristic slow rise. Furthermore, the temporal order of responses across the visual hierarchy was reversed for illusory as compared to physical changes: for illusory changes, higher order fusiform and parahippocampal regions responded before lower order occipital regions. Our tentative interpretation of these findings is that two stages underlie the initiation of illusory changes: a destabilization stage in which activity associated with the impending change gradually accumulates across the visual hierarchy, ultimately graduating in a top-down cascade of activity that may stabilize the new perceptual interpretation of the stimulus.

Intracranial Recordings Reveal Unique Shape and Timing of Responses in Human Visual Cortex during Illusory Visual Events

During binocular rivalry, perception spontaneously changes without any alteration to the visual stimulus. What neural events bring about this illusion that a constant stimulus is changing? We recorded from intracranial electrodes placed on the occipital and posterior temporal cortex of two patients with epilepsy while they experienced illusory changes of a face-house binocular-rivalry stimulus or observed a control stimulus that physically changed. We performed within-patient comparisons of broadband high-frequency responses, focusing on single epochs recorded along the ventral processing stream. We found transient face- and house-selective responses localized to the same electrodes for illusory and physical changes, but the temporal characteristics of these responses markedly differed. In comparison with physical changes, responses to illusory changes were longer lasting, in particular exhibiting a characteristic slow rise. Furthermore, the temporal order of responses across the visual hierarchy was reversed for illusory as compared to physical changes: for illusory changes, higher order fusiform and parahippocampal regions responded before lower order occipital regions. Our tentative interpretation of these findings is that two stages underlie the initiation of illusory changes: a destabilization stage in which activity associated with the impending change gradually accumulates across the visual hierarchy, ultimately graduating in a top-down cascade of activity that may stabilize the new perceptual interpretation of the stimulus.

Cortical suppression in human primary visual cortex predicts individual differences in illusory tilt perception.

Neural responses to visual stimuli are modulated by spatial and temporal context. For example, in primary visual cortex (V1), responses to an oriented target stimulus will be suppressed when embedded within an oriented surround stimulus. This suppression is orientation-specific, with the largest suppression observed when stimuli in the neuron's classical receptive field and surround are of similar orientation. In human psychological experiments, the tilt illusion and tilt aftereffect demonstrate an effect of context on perceived orientation of a target stimulus. Similar to the neurophysiological data, the strength of these effects is modulated by the orientation difference between the target stimulus and context. It has been hypothesized that the neural mechanism underlying both the tilt illusion and tilt aftereffect involves orientation-tuned inhibition in V1. However, to date there is no direct evidence linking human perception of these illusions with measurements of inhibition from human visual cortex. Here, we measured context-induced suppression of neural responses in human visual cortex using functional magnetic resonance imaging (fMRI). In the same participants, we also measured magnitudes of their tilt illusion and tilt aftereffect. Our data revealed a significant relationship between the magnitude of neural suppression in V1 and size of the tilt illusion and tilt aftereffect. That is, participants who showed stronger blood oxygenation level dependent (BOLD) suppression in V1 also perceived stronger shifts in illusory tilt. This agreement between perception and neural responses in human V1 suggests a shared inhibitory mechanism that mediates both spatial and temporal effects of context in human perception.

A non-invasive, quantitative study of broadband spectral responses in human visual cortex.

Currently, non-invasive methods for studying the human brain do not routinely and reliably measure spike-rate-dependent signals, independent of responses such as hemodynamic coupling (fMRI) and subthreshold neuronal synchrony (oscillations and event-related potentials). In contrast, invasive methods—microelectrode recordings and electrocorticography (ECoG)—have recently measured broadband power elevation in field potentials (~50–200 Hz) as a proxy for locally averaged spike rates. Here, we sought to detect and quantify stimulus-related broadband responses using magnetoencephalography (MEG). Extracranial measurements like MEG and EEG have multiple global noise sources and relatively low signal-to-noise ratios; moreover high frequency artifacts from eye movements can be confounded with stimulus design and mistaken for signals originating from brain activity. For these reasons, we developed an automated denoising technique that helps reveal the broadband signal of interest. Subjects viewed 12-Hz contrast-reversing patterns in the left, right, or bilateral visual field. Sensor time series were separated into evoked (12-Hz amplitude) and broadband components (60–150 Hz). In all subjects, denoised broadband responses were reliably measured in sensors over occipital cortex, even in trials without microsaccades. The broadband pattern was stimulus-dependent, with greater power contralateral to the stimulus. Because we obtain reliable broadband estimates with short experiments (~20 minutes), and with sufficient signal-to-noise to distinguish responses to different stimuli, we conclude that MEG broadband signals, denoised with our method, offer a practical, non-invasive means for characterizing spike-rate-dependent neural activity for addressing scientific questions about human brain function.

Population receptive field (pRF) measurements of chromatic responses in human visual cortex using fMRI

The spatial sensitivity of the human visual system depends on stimulus color: achromatic gratings can be resolved at relatively high spatial frequencies while sensitivity to isoluminant color contrast tends to be more low-pass. Models of early spatial vision often assume that the receptive field size of pattern-sensitive neurons is correlated with their spatial frequency sensitivity - larger receptive fields are typically associated with lower optimal spatial frequency. A strong prediction of this model is that neurons coding isoluminant chromatic patterns should have, on average, a larger receptive field size than neurons sensitive to achromatic patterns. Here, we test this assumption using functional magnetic resonance imaging (fMRI). We show that while spatial frequency sensitivity depends on chromaticity in the manner predicted by behavioral measurements, population receptive field (pRF) size measurements show no such dependency. At any given eccentricity, the mean pRF size for neuronal populations driven by luminance, opponent red/green and S-cone isolating contrast, are identical. Changes in pRF size (for example, an increase with eccentricity and visual area hierarchy) are also identical across the three chromatic conditions. These results suggest that fMRI measurements of receptive field size and spatial resolution can be decoupled under some circumstances - potentially reflecting a fundamental dissociation between these parameters at the level of neuronal populations.

Temporal windows in psychophysical discrimination and in neural responses in human visual cortex

Temporal windows in psychophysical discrimination and in neural responses in human visual cortex

Human Visual Cortex Responses to Rapid Cone and Melanopsin-Directed Flicker.

The retina contains cone photoreceptors and ganglion cells that contain the photopigment melanopsin. Cones provide brightness and color signals to visual cortex. Melanopsin influences circadian rhythm and the pupil, but its contribution to cortex and perception is less clear. We measured the response of human visual cortex with fMRI using spectral modulations tailored to stimulate the cones and melanopsin separately. We found that cortical responses to cone signals vary systematically across visual areas. Differences in temporal sensitivity for achromatic, red-green, and blue-yellow stimuli generally reflect the known perceptual properties of vision. We found that melanopsin signals do not produce a measurable response in visual cortex at temporal frequencies between 0.5 and 64 Hz at daytime light levels.

Orientation-tuned surround suppression improves computational models of human visual cortex

In recent years, population receptive field models fit to fMRI data have been used to characterize responses in human visual cortex (Dumoulin and Wandell, 2008, Neuroimage). Initial population receptive field models represented stimuli as binary contrast masks, but recent models have incorporated a larger range of visual computations in order to predict responses directly from the image pixels. The model-based approach summarizes diverse findings from visual neuroscience and elucidates the visual computations performed in each area. FMRI has the particular advantage of enabling quick and effective exploration of computational properties throughout the entire visual system. A recent two-stage cascade model was shown to account for much of the observed variance of BOLD responses in early visual areas in response to a wide range of band-limited grayscale images (Kay et al. 2013, PLoS CB). However, the existing model still exhibits certain systematic failures. Response amplitudes to contrast patterns with a single orientation are systematically overpredicted, while amplitudes to contrast patterns with extended curved edges are systematically underpredicted. Here we asked whether updating the model to reflect additional findings about the visual response properties of neurons could improve model performance. Physiology, psychophysics, and theory support the hypothesis that neuronal responses are suppressed by an orientation-tuned surround (Schwartz and Simoncelli, 2001, Nature Neuroscience; Cavanaugh, Bair, and Movshon, 2002, Journal of Neurophysiology). We revisited data from Kay et al. and implemented an additional computation: a spatially extended, orientation-tuned divisive normalization step. The updated model produced systematically better predictions in V1/V2/V3, without introducing additional parameters or degrees of freedom. These results show steady progress in building increasingly accurate models of the computations performed in the human visual pathways. Meeting abstract presented at VSS 2015