Two temporal channels in human V1 identified using fMRI

Rethinking simultaneous suppression in visual cortex via compressive spatiotemporal population receptive fields

When multiple visual stimuli are presented simultaneously in the receptive field, the neural response is suppressed compared to presenting the same stimuli sequentially. The prevailing hypothesis suggests that this suppression is due to competition among multiple stimuli for limited resources within receptive fields, governed by task demands. However, it is unknown how stimulus-driven computations may give rise to simultaneous suppression. Using fMRI, we find simultaneous suppression in single voxels, which varies with both stimulus size and timing, and progressively increases up the visual hierarchy. Using population receptive field (pRF) models, we find that compressive spatiotemporal summation rather than compressive spatial summation predicts simultaneous suppression, and that increased simultaneous suppression is linked to larger pRF sizes and stronger compressive nonlinearities. These results necessitate a rethinking of simultaneous suppression as the outcome of stimulus-driven compressive spatiotemporal computations within pRFs, and open new opportunities to study visual processing capacity across space and time.

Temporal dynamics of short-term neural adaptation across human visual cortex

Neural responses in visual cortex adapt to prolonged and repeated stimuli. While adaptation occurs across the visual cortex, it is unclear how adaptation patterns and computational mechanisms differ across the visual hierarchy. Here we characterize two signatures of short-term neural adaptation in time-varying intracranial electroencephalography (iEEG) data collected while participants viewed naturalistic image categories varying in duration and repetition interval. Ventral- and lateral-occipitotemporal cortex exhibit slower and prolonged adaptation to single stimuli and slower recovery from adaptation to repeated stimuli compared to V1-V3. For category-selective electrodes, recovery from adaptation is slower for preferred than non-preferred stimuli. To model neural adaptation we augment our delayed divisive normalization (DN) model by scaling the input strength as a function of stimulus category, enabling the model to accurately predict neural responses across multiple image categories. The model fits suggest that differences in adaptation patterns arise from slower normalization dynamics in higher visual areas interacting with differences in input strength resulting from category selectivity. Our results reveal systematic differences in temporal adaptation of neural population responses between lower and higher visual brain areas and show that a single computational model of history-dependent normalization dynamics, fit with area-specific parameters, accounts for these differences.

Rethinking simultaneous suppression in visual cortex via compressive spatiotemporal population receptive fields

When multiple visual stimuli are presented simultaneously in the receptive field, the neural response is suppressed compared to presenting the same stimuli sequentially. The prevailing hypothesis suggests that this suppression is due to competition among multiple stimuli for limited resources within receptive fields, governed by task demands. However, it is unknown how stimulus-driven computations may give rise to simultaneous suppression. Using fMRI, we find simultaneous suppression in single voxels, which varies with both stimulus size and timing, and progressively increases up the visual hierarchy. Using population receptive field (pRF) models, we find that compressive spatiotemporal summation rather than compressive spatial summation predicts simultaneous suppression, and that increased simultaneous suppression is linked to larger pRF sizes and stronger compressive nonlinearities. These results necessitate a rethinking of simultaneous suppression as the outcome of stimulus-driven compressive spatiotemporal computations within pRFs, and open new opportunities to study visual processing capacity across space and time.

Characterizing Spatiotemporal Population Receptive Fields in Human Visual Cortex with fMRI

The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time-varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants (both females and males). We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (1) from early to later areas within a visual stream, spatial and temporal windows of pRFs progressively increase in size and show greater compressive nonlinearities, (2) later visual areas show diverging spatial and temporal windows across streams, and (3) within early visual areas (V1-V3), both spatial and temporal windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses using fMRI.

What has vision science taught us about functional MRI?

In the domain of human neuroimaging, much attention has been paid to the question of whether and how the development of functional magnetic resonance imaging (fMRI) has advanced our scientific knowledge of the human brain. However, the opposite question is also important; how has our knowledge of the brain advanced our understanding of fMRI? Here, we discuss how and why scientific knowledge about the human and animal visual system has been used to answer fundamental questions about fMRI as a brain measurement tool and how these answers have contributed to scientific discoveries beyond vision science.

Luxotonic signals in human prefrontal cortex as a possible substrate for effects of light on mood and cognition

Studies with experimental animals have revealed a mood-regulating neural pathway linking intrinsically photosensitive retinal ganglion cells (ipRGCs) and the prefrontal cortex (PFC), involved in the pathophysiology of mood disorders. Since humans also have light-intensity-encoding ipRGCs, we asked whether a similar pathway exists in humans. Here, functional MRI was used to identify PFC regions and other areas exhibiting light-intensity-dependent signals. We report 26 human brain regions having activation that either monotonically decreases or monotonically increases with light intensity. Luxotonic-related activation occurred across the cerebral cortex, in diverse subcortical structures, and in the cerebellum, encompassing regions with functions related to visual image formation, motor control, cognition, and emotion. Light suppressed PFC activation, which monotonically decreased with increasing light intensity. The sustained time course of light-evoked PFC responses and their susceptibility to prior light exposure resembled those of ipRGCs. These findings offer a functional link between light exposure and PFC-mediated cognitive and affective phenomena.

The magnitude of the sound-induced flash illusion does not increase monotonically as a function of visual stimulus eccentricity

The sound-induced flash illusion (SIFI) occurs when a rapidly presented visual stimulus is accompanied by two auditory stimuli, creating the illusory percept of two visual stimuli. While much research has focused on how the temporal proximity of the audiovisual stimuli impacts susceptibility to the illusion, comparatively less research has focused on the impact of spatial manipulations. Here, we aimed to assess whether manipulating the eccentricity of visual flash stimuli altered the properties of the temporal binding window associated with the SIFI. Twenty participants were required to report whether they perceived one or two flashes that were concurrently presented with one or two beeps. Visual stimuli were presented at one of four different retinal eccentricities (2.5, 5, 7.5, or 10 degrees below fixation) and audiovisual stimuli were separated by one of eight stimulus-onset asynchronies. In keeping with previous findings, increasing stimulus-onset asynchrony between the auditory and visual stimuli led to a marked decrease in susceptibility to the illusion allowing us to estimate the width and amplitude of the temporal binding window. However, varying the eccentricity of the visual stimulus had no effect on either the width or the peak amplitude of the temporal binding window, with a similar pattern of results observed for both the “fission” and “fusion” variants of the illusion. Thus, spatial manipulations of the audiovisual stimuli used to elicit the SIFI appear to have a weaker effect on the integration of sensory signals than temporal manipulations, a finding which has implications for neuroanatomical models of multisensory integration.

Parallel processing in human visual cortex revealed through the influence of their neural responses on the visual evoked potential

The neural response in the human visual system is composed of magno-, parvo- and koniocellular input from the retina. Signal differences from functional imaging between health and individuals with a cognitive weakness are attributed to a dysfunction of a specific retinal input. Yet, anatomical interconnections within the human visual system obscure individual contribution to the neural response in V1. Deflections in the visual evoked potential (VEP) arise from an interaction between electric dipoles, their strength determined by the size of the neural population active during temporal - and spatial luminance contrast processing. To investigate interaction between these neural responses, we recorded the VEP over visual cortex of 14 healthy adults viewing four series of windmill patterns. Within a series, the relative area white in a pattern varied systematically. Between series, the number of sectors across which this area was distributed doubled. These patterns were viewed as pattern alternating and on-/off stimuli. P100/P1 amplitude increased linearly with the relative area white in the pattern, while N135/N1 and P240/P2 amplitude increased with the number of sectors of which the area white was distributed. The decreases P100 amplitude with increasing number of sectors is attributed to an interaction between electric dipoles located in granular and supragranular layers of V1. Differences between the VEP components obtained during a pattern reversing display and following pattern onset are accounted for by the transient and sustained nature of neural responses processing temporal - and spatial luminance contrast and ability of these responses to manifest in the VEP.

The relationship between transcription and eccentricity in human V1

Gene expression gradients radiating from regions of primary sensory cortices have recently been described and are thought to underlie the large-scale organization of the human cerebral cortex. However, the role of transcription in the functional layout of a single region within the adult brain has yet to be clarified, likely owing to the difficulty of identifying a brain region anatomically consistent enough across individuals with dense enough tissue sampling. Overcoming these hurdles in human primary visual cortex (V1), we show a relationship between differential gene expression and the cortical layout of eccentricity in human V1. Interestingly, these genes are unique from those previously identified that contribute to the positioning of cortical areas in the visual processing hierarchy. Enrichment analyses show that a subset of the identified genes encode for structures related to inhibitory interneurons, ion channels, as well as cellular projections, and are expressed more in foveal compared to peripheral portions of human V1. These findings predict that tissue density should be higher in foveal compared to peripheral V1. Using a histological pipeline, we validate this prediction using Nissl-stained sections of postmortem occipital cortex. We discuss these findings relative to previous studies in non-human primates, as well as in the context of an organizational pattern in which the adult human brain employs transcription gradients at multiple spatial scales: across the cerebral cortex, across areas within processing hierarchies, and within single cortical areas.

Population Models, Not Analyses, of Human Neuroscience Measurements

Selectivity for many basic properties of visual stimuli, such as orientation, is thought to be organized at the scale of cortical columns, making it difficult or impossible to measure directly with noninvasive human neuroscience measurement. However, computational analyses of neuroimaging data have shown that selectivity for orientation can be recovered by considering the pattern of response across a region of cortex. This suggests that computational analyses can reveal representation encoded at a finer spatial scale than is implied by the spatial resolution limits of measurement techniques. This potentially opens up the possibility to study a much wider range of neural phenomena that are otherwise inaccessible through noninvasive measurement. However, as we review in this article, a large body of evidence suggests an alternative hypothesis to this superresolution account: that orientation information is available at the spatial scale of cortical maps and thus easily measurable at the spatial resolution of standard techniques. In fact, a population model shows that this orientation information need not even come from single-unit selectivity for orientation tuning, but instead can result from population selectivity for spatial frequency. Thus, a categorical error of interpretation can result whereby orientation selectivity can be confused with spatial frequency selectivity. This is similarly problematic for the interpretation of results from numerous studies of more complex representations and cognitive functions that have built upon the computational techniques used to reveal stimulus orientation. We suggest in this review that these interpretational ambiguities can be avoided by treating computational analyses as models of the neural processes that give rise to measurement. Building upon the modeling tradition in vision science using considerations of whether population models meet a set of core criteria is important for creating the foundation for a cumulative and replicable approach to making valid inferences from human neuroscience measurements. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Depth-dependent functional MRI responses to chromatic and achromatic stimuli throughout V1 and V2

In the primate visual system, form (shape, location) and color information are processed in separate but interacting pathways. Recent access to high-resolution neuroimaging has facilitated the exploration of the structure of these pathways at the mesoscopic level in the human visual cortex. We used 7T fMRI to observe selective activation of the primary visual cortex to chromatic versus achromatic stimuli in five participants across two scanning sessions. Achromatic checkerboards with low spatial frequency and high temporal frequency targeted the color-insensitive magnocellular pathway. Chromatic checkerboards with higher spatial frequency and low temporal frequency targeted the color-selective parvocellular pathway. This work resulted in three main findings. First, responses driven by chromatic stimuli had a laminar profile biased towards superficial layers of V1, as compared to responses driven by achromatic stimuli. Second, we found stronger preference for chromatic stimuli in parafoveal V1 compared with peripheral V1. Finally, we found alternating, stimulus-selective bands stemming from the V1 border into V2 and V3. Similar alternating patterns have been previously found in both NHP and human extrastriate cortex. Together, our findings confirm the utility of fMRI for revealing details of mesoscopic neural architecture in human cortex.

Evidence for different spatiotemporal mechanisms using duration thresholds: An individual differences approach

The study of motion perception through classical psychophysical methods has suggested that independent spatiotemporal filters acting over specific locations in retinal images carry out early motion processing. On the other hand, individual differences approaches have been able to identify a structure of spatiotemporal filters too. In this same fashion-through an individual differences approach-the present study aims to uncover a structure of spatiotemporal frequency selective motion mechanisms. This is done, for the first time, using supra-threshold contrast stimuli in a motion direction discrimination task. Two experiments were performed measuring duration thresholds for drifting 2D Gabor gratings of 0.25, 0.5, 0.75, 1, 1.5, 2, 3 and 6 c/deg. They moved with a speed of 2 deg/sec, with Michelson contrasts of 0.1 or 0.9 (Experiment 1) or had a contrast of 0.9 drifting with a temporal frequency of 2 Hz or 8 Hz (Experiment 2). Principal component analyses uncover three factors in each of four conditions. When Varimax-rotated, these are seen to be selective to spatial frequencies lower than 0.5 c/deg, intermediate ones from 0.5 to 1-1.5 c/deg, and frequencies greater than 1-1.5 c/deg. Direct Oblimin rotations indicate that factors are moderately correlated. Further analyses show very slight differences in the correlational structures between contrast conditions (0.1 vs. 0.9), and no differences between temporal frequency conditions (2 Hz vs. 8 Hz). To conclude, the idea of a three-factor structure in motion processing for low, intermediate, and high spatial frequencies is supported.

Feedback contribution to surface motion perception in the human early visual cortex

Human visual surface perception has neural correlates in early visual cortex, but the role of feedback during surface segmentation in human early visual cortex remains unknown. Feedback projections preferentially enter superficial and deep anatomical layers, which provides a hypothesis for the cortical depth distribution of fMRI activity related to feedback. Using ultra-high field fMRI, we report a depth distribution of activation in line with feedback during the (illusory) perception of surface motion. Our results fit with a signal re-entering in superficial depths of V1, followed by a feedforward sweep of the re-entered information through V2 and V3. The magnitude and sign of the BOLD response strongly depended on the presence of texture in the background, and was additionally modulated by the presence of illusory motion perception compatible with feedback. In summary, the present study demonstrates the potential of depth-resolved fMRI in tackling biomechanical questions on perception.

Center-surround velocity-based segmentation: Speed, eccentricity, and timing of visual stimuli interact to determine interocular dominance

We used a novel method to capture the spatial dominance pattern of competing motion fields at rivalry onset. When rivaling velocities were different, the participants reported center-surround segmentation: The slower stimuli often dominated in the center while faster motion persisted along the borders. The size of the central static/slow field scaled with the stimulus size. The central dominance was time-locked to the static stimulus onset but was disrupted if the dynamic stimulus was presented later. We then used the same stimuli as masks in an interocular suppression paradigm. The local suppression strengths were probed with targets at different eccentricities. Consistent with the center-surround segmentation, target speed and location interacted with mask velocities. Specifically, suppression power of the slower masks was nonhomogenous with eccentricity, providing a potential explanation for center-surround velocity-based segmentation. This interaction of speed, eccentricity, and timing has implications for motion processing and interocular suppression. The influence of different masks on which target features get suppressed predicts that some "unconscious effects" are not generalizable across masks and, thus, need to be replicated under various masking conditions.

Predicting neuronal dynamics with a delayed gain control model

Visual neurons respond to static images with specific dynamics: neuronal responses sum sub-additively over time, reduce in amplitude with repeated or sustained stimuli (neuronal adaptation), and are slower at low stimulus contrast. Here, we propose a simple model that predicts these seemingly disparate response patterns observed in a diverse set of measurements-intracranial electrodes in patients, fMRI, and macaque single unit spiking. The model takes a time-varying contrast time course of a stimulus as input, and produces predicted neuronal dynamics as output. Model computation consists of linear filtering, expansive exponentiation, and a divisive gain control. The gain control signal relates to but is slower than the linear signal, and this delay is critical in giving rise to predictions matched to the observed dynamics. Our model is simpler than previously proposed related models, and fitting the model to intracranial EEG data uncovers two regularities across human visual field maps: estimated linear filters (temporal receptive fields) systematically differ across and within visual field maps, and later areas exhibit more rapid and substantial gain control. The model is further generalizable to account for dynamics of contrast-dependent spike rates in macaque V1, and amplitudes of fMRI BOLD in human V1.

Towards an intuitive communication-BCI: decoding visually imagined characters from the early visual cortex using high-field fMRI

Brain-computer interfaces aim to provide people with paralysis with the possibility to use their neural signals to control devices. For communication, most BCIs are based on the selection of letters from a (digital) letter board to spell words and sentences. Visual mental imagery of letters could offer a new, fast and intuitive way to spell in a BCI-communication solution. Here we provide a proof of concept for the decoding of visually imagined characters from the early visual cortex using 7 Tesla functional MRI. Sixteen healthy participants visually imagined three different characters for 3, 5 and 7 s in a slow event-related design. Using single-trial classification, we were able to decode the characters with an average accuracy of 54%, which is significantly above chance level (33%). Furthermore, the imagined characters were classifiable shortly after cue onset and remained classifiable with prolonged imagery. These properties, combined with the cortical location of the early visual cortex and its decodable activity, encourage further research on intracranial interfacing using surface electrodes to bring us closer to such a visual imagery based BCI communication solution.

Differential sustained and transient temporal processing across visual streams

How do high-level visual regions process the temporal aspects of our visual experience? While the temporal sensitivity of early visual cortex has been studied with fMRI in humans, temporal processing in high-level visual cortex is largely unknown. By modeling neural responses with millisecond precision in separate sustained and transient channels, and introducing a flexible encoding framework that captures differences in neural temporal integration time windows and response nonlinearities, we predict fMRI responses across visual cortex for stimuli ranging from 33 ms to 20 s. Using this innovative approach, we discovered that lateral category-selective regions respond to visual transients associated with stimulus onsets and offsets but not sustained visual information. Thus, lateral category-selective regions compute moment-to-moment visual transitions, but not stable features of the visual input. In contrast, ventral category-selective regions process both sustained and transient components of the visual input. Our model revealed that sustained channel responses to prolonged stimuli exhibit adaptation, whereas transient channel responses to stimulus offsets are surprisingly larger than for stimulus onsets. This large offset transient response may reflect a memory trace of the stimulus when it is no longer visible, whereas the onset transient response may reflect rapid processing of new items. Together, these findings reveal previously unconsidered, fundamental temporal mechanisms that distinguish visual streams in the human brain. Importantly, our results underscore the promise of modeling brain responses with millisecond precision to understand the underlying neural computations.

How does the brain encode the timing of our visual experience? Using functional magnetic resonance imaging (fMRI) and a generative temporal model with millisecond resolution, we discovered that visual regions in the lateral and ventral processing streams fundamentally differ in their temporal processing of the visual input. Regions in lateral temporal cortex process visual transients associated with the beginning and ending of the stimulus, but not its stable aspects. That is, lateral regions appear to compute moment-to-moment changes in the visual input. In contrast, regions in ventral temporal cortex process both stable and transient components of the visual input, even as the response to the former exhibits adaptation. Surprisingly, the model predicts that in ventral regions responses to stimulus endings are larger than beginnings. We suggest that ending responses may reflect a memory trace of the stimulus, when it is no longer visible, and the beginning responses may reflect processing of new inputs. Together, these findings (i) reveal a fundamental temporal mechanism that distinguishes visual streams and (ii) highlight both the importance and utility of modeling brain responses with millisecond precision to understand the temporal dynamics of neural computations in the human brain.

Eccentricity-dependent temporal contrast tuning in human visual cortex measured with fMRI

Cells in the peripheral retina tend to have higher contrast sensitivity and respond at higher flicker frequencies than those closer to the fovea. Although this predicts increased behavioural temporal contrast sensitivity in the peripheral visual field, this effect is rarely observed in psychophysical experiments. It is unknown how temporal contrast sensitivity is represented across eccentricity within cortical visual field maps and whether such sensitivities reflect the response properties of retinal cells or psychophysical sensitivities. Here, we used functional magnetic resonance imaging (fMRI) to measure contrast sensitivity profiles at four temporal frequencies in five retinotopically-defined visual areas. We also measured population receptive field (pRF) parameters (polar angle, eccentricity, and size) in the same areas. Overall contrast sensitivity, independent of pRF parameters, peaked at 10 Hz in all visual areas. In V1, V2, V3, and V3a, peripherally-tuned voxels had higher contrast sensitivity at a high temporal frequency (20 Hz), while hV4 more closely reflected behavioural sensitivity profiles. We conclude that our data reflect a cortical representation of the increased peripheral temporal contrast sensitivity that is already present in the retina and that this bias must be compensated later in the cortical visual pathway.

The functional neuroanatomy of face perception: from brain measurements to deep neural networks

A central goal in neuroscience is to understand how processing within the ventral visual stream enables rapid and robust perception and recognition. Recent neuroscientific discoveries have significantly advanced understanding of the function, structure and computations along the ventral visual stream that serve as the infrastructure supporting this behaviour. In parallel, significant advances in computational models, such as hierarchical deep neural networks (DNNs), have brought machine performance to a level that is commensurate with human performance. Here, we propose a new framework using the ventral face network as a model system to illustrate how increasing the neural accuracy of present DNNs may allow researchers to test the computational benefits of the functional architecture of the human brain. Thus, the review (i) considers specific neural implementational features of the ventral face network, (ii) describes similarities and differences between the functional architecture of the brain and DNNs, and (iii) provides a hypothesis for the computational value of implementational features within the brain that may improve DNN performance. Importantly, this new framework promotes the incorporation of neuroscientific findings into DNNs in order to test the computational benefits of fundamental organizational features of the visual system.

Encoding model of temporal processing in human visual cortex

How is temporal information processed in human visual cortex? Visual input is relayed to V1 through segregated transient and sustained channels in the retina and lateral geniculate nucleus (LGN). However, there is intense debate as to how sustained and transient temporal channels contribute to visual processing beyond V1. The prevailing view associates transient processing predominately with motion-sensitive regions and sustained processing with ventral stream regions, while the opposing view suggests that both temporal channels contribute to neural processing beyond V1. Using fMRI, we measured cortical responses to time-varying stimuli and then implemented a two temporal channel-encoding model to evaluate the contributions of each channel. Different from the general linear model of fMRI that predicts responses directly from the stimulus, the encoding approach first models neural responses to the stimulus from which fMRI responses are derived. This encoding approach not only predicts cortical responses to time-varying stimuli from milliseconds to seconds but also, reveals differential contributions of temporal channels across visual cortex. Consistent with the prevailing view, motion-sensitive regions and adjacent lateral occipitotemporal regions are dominated by transient responses. However, ventral occipitotemporal regions are driven by both sustained and transient channels, with transient responses exceeding the sustained. These findings propose a rethinking of temporal processing in the ventral stream and suggest that transient processing may contribute to rapid extraction of the content of the visual input. Importantly, our encoding approach has vast implications, because it can be applied with fMRI to decipher neural computations in millisecond resolution in any part of the brain.

Compressive Temporal Summation in Human Visual Cortex

Combining sensory inputs over space and time is fundamental to vision. Population receptive field models have been successful in characterizing spatial encoding throughout the human visual pathways. A parallel question, how visual areas in the human brain process information distributed over time, has received less attention. One challenge is that the most widely used neuroimaging method, fMRI, has coarse temporal resolution compared with the time-scale of neural dynamics. Here, via carefully controlled temporally modulated stimuli, we show that information about temporal processing can be readily derived from fMRI signal amplitudes in male and female subjects. We find that all visual areas exhibit subadditive summation, whereby responses to longer stimuli are less than the linear prediction from briefer stimuli. We also find fMRI evidence that the neural response to two stimuli is reduced for brief interstimulus intervals (indicating adaptation). These effects are more pronounced in visual areas anterior to V1-V3. Finally, we develop a general model that shows how these effects can be captured with two simple operations: temporal summation followed by a compressive nonlinearity. This model operates for arbitrary temporal stimulation patterns and provides a simple and interpretable set of computations that can be used to characterize neural response properties across the visual hierarchy. Importantly, compressive temporal summation directly parallels earlier findings of compressive spatial summation in visual cortex describing responses to stimuli distributed across space. This indicates that, for space and time, cortex uses a similar processing strategy to achieve higher-level and increasingly invariant representations of the visual world.SIGNIFICANCE STATEMENT Combining sensory inputs over time is fundamental to seeing. Two important temporal phenomena are summation, the accumulation of sensory inputs over time, and adaptation, a response reduction for repeated or sustained stimuli. We investigated these phenomena in the human visual system using fMRI. We built predictive models that operate on arbitrary temporal patterns of stimulation using two simple computations: temporal summation followed by a compressive nonlinearity. Our new temporal compressive summation model captures (1) subadditive temporal summation, and (2) adaptation. We show that the model accounts for systematic differences in these phenomena across visual areas. Finally, we show that for space and time, the visual system uses a similar strategy to achieve increasingly invariant representations of the visual world.

Oxygen Level and LFP in Task-Positive and Task-Negative Areas: Bridging BOLD fMRI and Electrophysiology

The human default mode network (DMN) shows decreased blood oxygen level dependent (BOLD) signals in response to a wide range of attention-demanding tasks. Our understanding of the specifics regarding the neural activity underlying these "task-negative" BOLD responses remains incomplete. We paired oxygen polarography, an electrode-based oxygen measurement technique, with standard electrophysiological recording to assess the relationship of oxygen and neural activity in task-negative posterior cingulate cortex (PCC), a hub of the DMN, and visually responsive task-positive area V3 in the awake macaque. In response to engaging visual stimulation, oxygen, LFP power, and multi-unit activity in PCC showed transient activation followed by sustained suppression. In V3, oxygen, LFP power, and multi-unit activity showed an initial phasic response to the stimulus followed by sustained activation. Oxygen responses were correlated with LFP power in both areas, although the apparent hemodynamic coupling between oxygen level and electrophysiology differed across areas. Our results suggest that oxygen responses reflect changes in LFP power and multi-unit activity and that either the coupling of neural activity to blood flow and metabolism differs between PCC and V3 or computing a linear transformation from a single LFP band to oxygen level does not capture the true physiological process.

Human cortical areas involved in perception of surface glossiness

Glossiness is the visual appearance of an object's surface as defined by its surface reflectance properties. Despite its ecological importance, little is known about the neural substrates underlying its perception. In this study, we performed the first human neuroimaging experiments that directly investigated where the processing of glossiness resides in the visual cortex. First, we investigated the cortical regions that were more activated by observing high glossiness compared with low glossiness, where the effects of simple luminance and luminance contrast were dissociated by controlling the illumination conditions (Experiment 1). As cortical regions that may be related to the processing of glossiness, V2, V3, hV4, VO-1, VO-2, collateral sulcus (CoS), LO-1, and V3A/B were identified, which also showed significant correlation with the perceived level of glossiness. This result is consistent with the recent monkey studies that identified selective neural response to glossiness in the ventral visual pathway, except for V3A/B in the dorsal visual pathway, whose involvement in the processing of glossiness could be specific to the human visual system. Second, we investigated the cortical regions that were modulated by selective attention to glossiness (Experiment 2). The visual areas that showed higher activation to attention to glossiness than that to either form or orientation were identified as right hV4, right VO-2, and right V3A/B, which were commonly identified in Experiment 1. The results indicate that these commonly identified visual areas in the human visual cortex may play important roles in glossiness perception.

On the 'visual' in 'audio-visual integration': a hypothesis concerning visual pathways

Crossmodal interaction conferring enhancement in sensory processing is nowadays widely accepted. Such benefit is often exemplified by neural response amplification reported in physiological studies conducted with animals, which parallel behavioural demonstrations of sound-driven improvement in visual tasks in humans. Yet, a good deal of controversy still surrounds the nature and interpretation of these human psychophysical studies. Here, we consider the interpretation of crossmodal enhancement findings under the light of the functional as well as anatomical specialization of magno- and parvocellular visual pathways, whose paramount relevance has been well established in visual research but often overlooked in crossmodal research. We contend that a more explicit consideration of this important visual division may resolve some current controversies and help optimize the design of future crossmodal research.

A BOLD signature of eyeblinks in the visual cortex

We are usually unaware of the brief but large illumination changes caused by blinks, presumably because of blink suppression mechanisms. In fMRI however, increase of the BOLD signal was reported in the visual cortex, e.g. during blocks of voluntary blinks (Bristow, Frith and Rees, 2005) or after spontaneous blinks recorded during the prolonged fixation of a static stimulus (Tse, Baumgartner and Greenlee, 2010). We tested whether such activation, possibly related to illumination changes, was also present during standard fMRI retinotopic and visual experiments and was large enough to contaminate the BOLD signal we are interested in. We monitored in a 3T scanner the eyeblinks of 14 subjects who observed three different types of visual stimuli, including periodic rotating wedges and contracting/expanding rings, event-related Mondrians and graphemes, while fixating. We performed event-related analyses on the set of detected spontaneous blinks. We observed large and widespread BOLD responses related to blinks in the visual cortex of every subject and whatever the visual stimulus. The magnitude of the modulation was comparable to visual stimulation. However, blink-related activations lay mostly in the anterior parts of retinotopic visual areas, coding the periphery of the visual field well beyond the extent of our stimuli. Blinks therefore represent an important source of BOLD variations in the visual cortex and a troublesome source of noise since any correlation, even weak, between the distribution of blinks and a tested protocol could trigger artifactual activities. However, the typical signature of blinks along the anterior calcarine and the parieto-occipital sulcus allows identifying, even in the absence of eyetracking, fMRI protocols possibly contaminated by a heterogeneous distribution of blinks.

Early suppressive mechanisms and the negative blood oxygenation level-dependent response in human visual cortex

Functional magnetic resonance imaging (fMRI) studies of early sensory cortex often measure stimulus-driven increases in the blood oxygenation level-dependent (BOLD) signal. However, these positive responses are frequently accompanied by reductions in the BOLD signal in adjacent regions of cortex. Although this negative BOLD response (NBR) is thought to result from neuronal suppression, the precise relationship between local activity, suppression, and perception remains unknown. By measuring BOLD signals in human primary visual cortex while varying the baseline contrast levels in the region affected by the NBR, we tested three physiologically plausible computational models of neuronal modulation that could explain this phenomenon: a subtractive model, a response gain model, and a contrast gain model. We also measured the ability of isoluminant contrast to generate an NBR. We show that the NBR can be modeled as a pathway-specific contrast gain modulation that is strongest outside the fovea. We found a similar spatial bias in a psychophysical study using identical stimuli, although these data indicated a response gain rather than a contrast gain mechanism. We reconcile these findings by proposing (1) that the NBR is associated with a long-range suppressive mechanism that hyperpolarizes a subset of magnocellularly driven neurons at the input to V1, (2) that this suppression is broadly tuned to match the spatial features of the mask region, and (3) that increasing the baseline contrast in the suppressed region drives all neurons in the input layer, reducing the relative contribution of the suppressing subpopulation in the fMRI signal.