The rise of large, publicly shared functional magnetic resonance imaging (fMRI) data sets in human neuroscience has focused on acquiring either a few hours of data on many individuals (‘wide’ fMRI) or many hours of data on a few individuals (‘deep’ fMRI). In this opinion article, we highlight an emerging approach within deep fMRI, which we refer to as ‘intensive’ fMRI: one that strives for extensive sampling of cognitive phenomena to support computational modeling and detailed investigation of brain function at the single voxel level. We discuss the fundamental principles, trade-offs, and practical considerations of intensive fMRI. We also emphasize that intensive fMRI does not simply mean collecting more data: it requires careful design of experiments to enable a rich hypothesis space, optimizing data quality, and strategically curating public resources to maximize community impact.

Recognizing faces regardless of their viewpoint is critical for social interactions. Traditional theories hold that view-selective early visual representations gradually become tolerant to viewpoint changes along the ventral visual hierarchy. Newer theories, based on single-neuron monkey electrophysiological recordings, suggest a three-stage architecture including an intermediate face-selective patch abruptly achieving invariance to mirror-symmetric face views. Human studies combining neuroimaging and multivariate pattern analysis (MVPA) have provided convergent evidence of view selectivity in early visual areas. However, contradictory conclusions have been reached concerning the existence in humans of a mirror-symmetric representation like that observed in macaques. We believe these contradictions arise from low-level stimulus confounds and data analysis choices. To probe for low-level confounds, we analyzed images from two face databases. Analyses of image luminance and contrast revealed biases across face views described by even polynomials—i.e., mirror-symmetric. To explain major trends across neuroimaging studies, we constructed a network model incorporating three constraints: cortical magnification, convergent feedforward projections, and interhemispheric connections. Given the identified low-level biases, we show that a gradual increase of interhemispheric connections across network-layers is sufficient to replicate view-tuning in early processing stages and mirror-symmetry in later stages. Data analysis decisions—pattern dissimilarity measure and data recentering—accounted for the inconsistent observation of mirror-symmetry across prior studies. Pattern analyses of human fMRI data (of either sex) revealed biases compatible with our model. The model provides a unifying explanation of MVPA studies of viewpoint selectivity and suggests observations of mirror-symmetry originate from ineffectively normalized signal imbalances across different face views.

In the ‘double-drift’ illusion, local motion within a window moving in the periphery of the visual field alters the window’s perceived path. The illusion is strong even when the eyes track a target whose motion matches the window so that the stimulus remains stable on the retina. This implies that the illusion involves the integration of retinal signals with non-retinal eye-movement signals. To identify where in the brain this integration occurs, we measured BOLD fMRI responses in visual cortex while subjects experienced the double-drift illusion. We then used a combination of univariate and multivariate decoding analyses to identify (1) which brain areas were sensitive to the illusion and (2) whether these brain areas contained information about the illusory stimulus trajectory. We identified a number of cortical areas that responded more strongly during the illusion than a control condition that was matched for low-level stimulus properties. Only in area hMT+ was it possible to decode the illusory trajectory. We additionally performed a number of important controls that rule out possible low-level confounds. Concurrent eye tracking confirmed that subjects accurately tracked the moving target; we were unable to decode the illusion trajectory using eye position measurements recorded during fMRI scanning, ruling out explanations based on differences in oculomotor behavior. Our results provide evidence for a perceptual representation in human visual cortex that incorporates extraretinal information.

A primary goal of neuroimaging is to relate fMRI measurements to neural tuning properties. Over the years, increasingly complex models, such as deep neural networks, have been proposed, attempting to extract as much information as possible from fMRI data. A complementary approach consists of modeling the neural system and using those models to fit the fMRI data. This approach is driven by insights into what the sensory system computes, rather than engineering an analysis pipeline that extracts information from fMRI data. Canonical models such as the steerable pyramid and Gabor filter banks have been applied to the visual cortex and have yielded important insights into the function and organization of both primary and higher order sensory brain regions. In this chapter, we describe the elements of the most commonly used image-computable models for visual neuroscience and discuss recent work applying these models to fMRI data. Finally, we discuss future potential extensions of the current models to other stimulus dimensions, modalities, and brain systems.

Similar to a camera aperture, pupil size adjusts to the surrounding luminance. Unlike a camera, pupil size is additionally modulated both by stimulus properties and by cognitive processes, including attention and arousal, though the interdependence of these factors is unclear. We hypothesized that different stimulus properties interact to jointly modulate pupil size while remaining independent from the impact of arousal. We measured pupil responses from human observers to equiluminant stimuli during a demanding rapid serial visual presentation (RSVP) task at fixation and tested how response amplitude depends on contrast, spatial frequency, and reward level. We found that under constant luminance, unattended stimuli evoke responses that are separable from changes caused by general arousal or attention. We further uncovered a double-dissociation between task-related responses and stimulus-evoked responses, suggesting that different sources of pupil size modulation are independent of one another. Our results shed light on neural pathways underlying pupillary response.

Primary sensory regions are believed to instantiate stable neural representations, yet a number of recent rodent studies suggest instead that representations drift over time. To test whether sensory representations are stable in human visual cortex, we analyzed a large longitudinal dataset of fMRI responses to images of natural scenes. We fit the fMRI responses using an image-computable encoding model and tested how well the model generalized across sessions. We found systematic changes in model fits that exhibited cumulative drift over many months. Convergent analyses pinpoint changes in neural responsivity as the source of the drift, while population-level representational dissimilarities between visual stimuli were unchanged. These observations suggest that downstream cortical areas may read-out a stable representation, even as representations within V1 exhibit drift.

Emotional expressions are an evolutionarily conserved means of social communication essential for social interactions. It is important to understand how anxious individuals perceive their social environments, including emotional expressions, especially with the rising prevalence of anxiety during the COVID-19 pandemic. Anxiety is often associated with an attentional bias for threat-related stimuli, such as angry faces. Yet the mechanisms by which anxiety enhances or impairs two key components of spatial attention—attentional capture and attentional disengagement—to emotional expressions are still unclear. Moreover, positive valence is often ignored in studies of threat-related attention and anxiety, despite the high occurrence of happy faces during everyday social interaction. Here, we investigated the relationship between anxiety, emotional valence, and spatial attention in 574 participants across two preregistered studies (data collected in 2021 and 2022; Experiment 1: n = 154, 54.5% male, Mage = 43.5 years; Experiment 2: n = 420, 58% male, Mage = 36.46 years). We found that happy faces capture attention more quickly than angry faces during the visual search experiment and found delayed disengagement from both angry and happy faces over neutral faces during the spatial cueing experiment. We also show that anxiety has a distinct impact on both attentional capture and disengagement of emotional faces. Together, our findings highlight the role of positively valenced stimuli in attracting and holding attention and suggest that anxiety is a critical factor in modulating spatial attention to emotional stimuli.

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.

Viewing faces that are perceived as emotionally expressive evokes enhanced neural responses in multiple brain regions, a phenomenon thought to depend critically on the amygdala. This emotion-related modulation is evident even in primary visual cortex (V1), providing a potential neural substrate by which emotionally salient stimuli can affect perception. How does emotional valence information, computed in the amygdala, reach V1? Here we use high-resolution functional MRI to investigate the layer profile and retinotopic distribution of neural activity specific to emotional facial expressions. Across three experiments, human participants viewed centrally presented face stimuli varying in emotional expression and performed a gender judgment task. We found that facial valence sensitivity was evident only in superficial cortical layers and was not restricted to the retinotopic location of the stimuli, consistent with diffuse feedback-like projections from the amygdala. Together, our results provide a feedback mechanism by which the amygdala directly modulates activity at the earliest stage of visual processing.

Neural responses throughout the visual cortex encode stimulus location in a retinotopic (i.e., eye-centered) reference frame, and memory for stimulus position is most precise in retinal coordinates. Yet visual perception is spatiotopic: objects are perceived as stationary, even though eye movements cause frequent displacement of their location on the retina. Previous studies found that, after a single saccade, memory of retinotopic locations is more accurate than memory of spatiotopic locations. However, it is not known whether various aspects of natural viewing affect the retinotopic reference frame advantage. We found that the retinotopic advantage may in part depend on a retinal afterimage, which can be effectively nullified through backwards masking. Moreover, in the presence of natural scenes, spatiotopic memory is more accurate than retinotopic memory, but only when subjects are provided sufficient time to process the scene before the eye movement. Our results demonstrate that retinotopic memory is not always more accurate than spatiotopic memory and that the fidelity of memory traces in both reference frames are sensitive to the presence of contextual cues.

Damage to the primary visual cortex (V1) causes homonymous visual-field loss long considered intractable. Multiple studies now show that perceptual training can restore visual functions in chronic cortically-induced blindness (CB). A popular hypothesis is that training can harness residual visual functions by recruiting intact extrageniculostriate pathways. Training may also induce plastic changes within spared regions of the damaged V1. Here, we link changes in luminance detection sensitivity with retinotopic fMRI activity before and after visual discrimination training in eleven patients with chronic, stroke-induced CB. We show that spared V1 activity representing perimetrically-blind locations prior to training predicts the amount of training-induced recovery of luminance detection sensitivity. Additionally, training results in an enlargement of population receptive fields in perilesional V1, which increases blind-field coverage and may support further recovery with subsequent training. These findings uncover fundamental changes in perilesional V1 cortex underlying training-induced restoration of conscious luminance detection sensitivity in CB. In humans, stroke damage to V1 causes large visual field defects. Spared V1 activity prior to training predicts the amount of training-induced recovery in luminance detection sensitivity. Moreover, visual training changes population receptive field properties within residual V1 circuits.

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.

The human ability to imagine motor actions without executing them (i.e., motor imagery) is crucial to a number of cognitive functions, including motor planning and learning, and has been shown to improve response times and accuracy of subsequent motor actions [1, 2]. Although these behavioral findings suggest the possibility that imagined movements directly influence primary motor cortex (M1), how this might occur remains unknown [3]. Here, we use a non-blood-oxygen-level-dependent (BOLD) method for collecting fMRI data, called vascular space occupancy (VASO) [4, 5], to measure neural activations across cortical laminae in M1 while participants either tapped their thumb and forefinger together or simply imagined doing so. We report that, whereas executed movements (i.e., finger tapping) evoked neural responses in both the superficial layers of M1 that receive cortical input and the deep layers of M1 that send output to the spinal cord to support movement, imagined movements evoked responses in superficial cortical layers only. Furthermore, we found that finger tapping preceded by both imagined and executed movements showed a reduced response in the superficial layers (repetition suppression) coupled with a heightened response in the deep layers (repetition enhancement). Taken together, our results provide evidence for a mechanism whereby imagined movements can directly affect motor performance and might explain how neural repetition effects lead to improvements in behavior (e.g., repetition priming).

The brain exhibits widespread endogenous responses in the absence of visual stimuli, even at the earliest stages of visual cortical processing. Such responses have been studied in monkeys using optical imaging with a limited field of view over visual cortex. Here, we used functional MRI (fMRI) in human participants to study the link between arousal and endogenous responses in visual cortex. The response that we observed was tightly entrained to task timing, was spatially extensive, and was independent of visual stimulation. We found that this response follows dynamics similar to that of pupil size and heart rate, suggesting that task-related activity is related to arousal. Finally, we found that higher reward increased response amplitude while decreasing its trial-to-trial variability (i.e., the noise). Computational simulations suggest that increased temporal precision underlies both of these observations. Our findings are consistent with optical imaging studies in monkeys and support the notion that arousal increases precision of neural activity.

How do endogenous (voluntary) and exogenous (involuntary) attention modulate activity in visual cortex? Using ROI-based fMRI analysis, we measured fMRI activity for valid and invalid trials (target at cued/un-cued location, respectively), pre- or post-cueing endogenous or exogenous attention, while participants performed the same orientation discrimination task. We found stronger modulation in contralateral than ipsilateral visual regions, and higher activity in valid- than invalid-trials. For endogenous attention, modulation of stimulus-evoked activity due to a pre-cue increased along the visual hierarchy, but was constant due to a post-cue. For exogenous attention, modulation of stimulus-evoked activity due to a pre-cue was constant along the visual hierarchy, but was not modulated due to a post-cue. These findings reveal that endogenous and exogenous attention distinctly modulate activity in visuo-occipital areas during orienting and reorienting; endogenous attention facilitates both the encoding and the readout of visual information whereas exogenous attention only facilitates the encoding of information.

A key challenge in human neuroscience is to gain information about patterns of neural activity using indirect measures. Multivariate pattern analysis methods testing for generalization of information across subjects have been used to support inferences regarding neural coding. One critical assumption of an important class of such methods is that anatomical normalization is suited to align spatially-structured neural patterns across individual brains. We asked whether anatomical normalization is suited for this purpose. If not, what sources of information are such across-subject cross-validated analyses likely to reveal? To investigate these questions, we implemented two-layered feedforward randomly-connected networks. A key feature of these simulations was a gain-field with a spatial structure shared across networks. To investigate whether total-signal imbalances across conditions—e.g. differences in overall activity— affect the observed pattern of results, we manipulated the energy-profile of images conforming to a pre-specified correlation structure. To investigate whether the level of granularity of the data also influences results, we manipulated the density of connections between network layers. Simulations showed that anatomical normalization is unsuited to align neural representations. Pattern similarity-relationships were explained by the observed total-signal imbalances across conditions. Further, we observed that deceptively complex representational structures emerge from arbitrary analysis choices, such as whether the data are mean-subtracted during preprocessing. These simulations also led to testable predictions regarding the distribution of low-level features in images used in recent fMRI studies that relied on leave-one-subject-out pattern analyses. Image analyses broadly confirmed these predictions. Finally, hyperalignment emerged as a principled alternative to test across-subject generalization of spatially-structured information. We illustrate cases in which hyperalignment proved successful, as well as cases in which it only partially recovered the latent correlation structure in the pattern of responses. Our results highlight the need for robust, high-resolution measurements from individual subjects. We also offer a way forward for across-subject analyses. We suggest ways to inform hyperalignment results with estimates of the strength of the signal associated with each condition. Such information can usefully constrain ensuing inferences regarding latent representational structures as well as population tuning dimensions.

Studies of visual temporal frequency preference typically examine frequencies under 20 Hz and measure local activity to evaluate the sensitivity of different cortical areas to variations in temporal frequencies. Most of these studies have not attempted to map preferred temporal frequency within and across visual areas, nor have they explored in detail, stimuli at gamma frequency, which recent research suggests may have potential clinical utility. In this study, we address this gap by using functional magnetic resonance imaging (fMRI) to measure response to flickering visual stimuli varying in frequency from 1 to 40 Hz. We apply stimulation in both a block design to examine task response and a steady-state design to examine functional connectivity. We observed distinct activation patterns between 1 Hz and 40 Hz stimuli. We also found that the correlation between medial thalamus and visual cortex was modulated by the temporal frequency. The modulation functions and tuned frequencies are different for the visual activity and thalamo-visual correlations. Using both fMRI activity and connectivity measurements, we show evidence for a temporal frequency specific organization across the human visual system.

Neural selectivity to orientation is one of the simplest and most thoroughly-studied cortical sensory features. Here, we show that a large body of research that purported to measure orientation tuning may have in fact been inadvertently measuring sensitivity to second-order changes in luminance, a phenomenon we term ‘vignetting’. Using a computational model of neural responses in primary visual cortex (V1), we demonstrate the impact of vignetting on simulated V1 responses. We then used the model to generate a set of predictions, which we confirmed with functional MRI experiments in human observers. Our results demonstrate that stimulus vignetting can wholly determine the orientation selectivity of responses in visual cortex measured at a macroscopic scale, and suggest a reinterpretation of a well-established literature on orientation processing in visual cortex.

The temporo-parietal junction (TPJ) has been associated with various cognitive and social functions, and is critical for attentional reorienting. Attention affects early visual processing. Neuroimaging studies dealing with such processes have thus far concentrated on striate and extrastriate areas. Here, we investigated whether attention orienting or reorienting modulate activity in visually driven TPJ subregions. For each observer we identified 3 visually responsive subregions within TPJ: 2 bilateral (vTPJant and vTPJpost) and 1 right lateralized (vTPJcent). Cortical activity in these subregions was measured using fMRI while observers performed a 2-alternative forced-choice orientation discrimination task. Covert spatial endogenous (voluntary) or exogenous (involuntary) attention was manipulated using either a central or a peripheral cue with task, stimuli and observers constant. Both endogenous and exogenous attention increased activity for invalidly cued trials in right vTPJpost; only endogenous attention increased activity for invalidly cued trials in left vTPJpost and in right vTPJcent; and neither type of attention modulated either right or left vTPJant. These results demonstrate that vTPJpost and vTPJcent mediate the reorientation of covert attention to task relevant stimuli, thus playing a critical role in visual attention. These findings reveal a differential reorienting cortical response after observers’ attention has been oriented to a given location voluntarily or involuntarily.

Functional magnetic resonance imaging (fMRI) studies have relied on multivariate analysis methods to decode visual motion direction from measurements of cortical activity. Above-chance decoding has been commonly used to infer the motion-selective response properties of the underlying neural populations. Moreover, patterns of reliable response biases across voxels that underlie decoding have been interpreted to reflect maps of functional architecture. Using fMRI, we identified a direction-selective response bias in human visual cortex that: (1) predicted motion-decoding accuracy; (2) depended on the shape of the stimulus aperture rather than the absolute direction of motion, such that response amplitudes gradually decreased with distance from the stimulus aperture edge corresponding to motion origin; and 3) was present in V1, V2, V3, but not evident in MT+, explaining the higher motion-decoding accuracies reported previously in early visual cortex. These results demonstrate that fMRI-based motion decoding has little or no dependence on the underlying functional organization of motion selectivity.

Microsaccade rate during fixation is modulated by the presentation of a visual stimulus. When the stimulus is an endogenous attention cue, the ensuing microsaccades tend to be directed toward the cue. This finding has been taken as evidence that microsaccades index the locus of spatial attention. But the vast majority of microsaccades that subjects make are not triggered by visual stimuli. Under natural viewing conditions, spontaneous microsaccades occur frequently (2-3 Hz), even in the absence of a stimulus or a task. While spontaneous microsaccades may depend on low-level visual demands, such as retinal fatigue, image fading, or fixation shifts, it is unknown whether their occurrence corresponds to changes in the attentional state. We developed a protocol to measure whether spontaneous microsaccades reflect shifts in spatial attention. Human subjects fixated a cross while microsaccades were detected from streaming eye-position data. Detection of a microsaccade triggered the appearance of a peripheral ring of grating patches, which were followed by an arrow (a postcue) indicating one of them as the target. The target was either congruent or incongruent (opposite) with respect to the direction of the microsaccade (which preceded the stimulus). Subjects reported the tilt of the target (clockwise or counterclockwise relative to vertical). We found that accuracy was higher for congruent than for incongruent trials. We conclude that the direction of spontaneous microsaccades is inherently linked to shifts in spatial attention.

To locate visual objects, the brain combines information about retinal location and direction of gaze. Studies in monkeys have demonstrated that eye position modulates the gain of visual signals with “gain fields,” so that single neurons represent both retinotopic location and eye position. We wished to know whether eye position and retinotopic stimulus location are both represented in human visual cortex. Using functional magnetic resonance imaging, we measured separately for each of several different gaze positions cortical responses to stimuli that varied periodically in retinal locus. Visually evoked responses were periodic following the periodic retinotopic stimulation. Only the response amplitudes depended on eye position; response phases were indistinguishable across eye positions. We used multivoxel pattern analysis to decode eye position from the spatial pattern of response amplitudes. The decoder reliably discriminated eye position in five of the early visual cortical areas by taking advantage of a spatially heterogeneous eye position-dependent modulation of cortical activity. We conclude that responses in retinotopically organized visual cortical areas are modulated by gain fields qualitatively similar to those previously observed neurophysiologically.

Multivariate decoding analyses are widely applied to functional magnetic resonance imaging (fMRI) data, but there is controversy over their interpretation. Orientation decoding in primary visual cortex (V1) reflects coarse-scale biases, including an over-representation of radial orientations. But fMRI responses to clockwise and counter-clockwise spirals can also be decoded. Because these stimuli are matched for radial orientation, while differing in local orientation, it has been argued that fine-scale columnar selectivity for orientation contributes to orientation decoding. We measured fMRI responses in human V1 to both oriented gratings and spirals. Responses to oriented gratings exhibited a complex topography, including a radial bias that was most pronounced in the peripheral representation, and a near-vertical bias that was most pronounced near the foveal representation. Responses to clockwise and counter-clockwise spirals also exhibited coarse-scale organization, at the scale of entire visual quadrants. The preference of each voxel for clockwise or counter-clockwise spirals was predicted from the preferences of that voxel for orientation and spatial position (i.e., within the retinotopic map). Our results demonstrate a bias for local stimulus orientation that has a coarse spatial scale, is robust across stimulus classes (spirals and gratings), and suffices to explain decoding from fMRI responses in V1.

The representation of orientation in primary visual cortex (V1) has been examined at a fine spatial scale corresponding to the columnar architecture. We present functional magnetic resonance imaging (fMRI) measurements providing evidence for a topographic map of orientation preference in human V1 at a much coarser scale, in register with the angular-position component of the retinotopic map of V1. This coarse-scale orientation map provides a parsimonious explanation for why multivariate pattern analysis methods succeed in decoding stimulus orientation from fMRI measurements, challenging the widely held assumption that decoding results reflect sampling of spatial irregularities in the fine-scale columnar architecture. Decoding stimulus attributes and cognitive states from fMRI measurements has proven useful for a number of applications, but our results demonstrate that the interpretation cannot assume decoding reflects or exploits columnar organization.

We experience the visual world as phenomenally invariant to eye position, but almost all cortical maps of visual space in monkeys use a retinotopic reference frame, that is, the cortical representation of a point in the visual world is different across eye positions. It was recently reported that human cortical area MT (unlike monkey MT) represents stimuli in a reference frame linked to the position of stimuli in space, a “spatiotopic” reference frame. We used visuotopic mapping with blood oxygen level-dependent functional magnetic resonance imaging signals to define 12 human visual cortical areas, and then determined whether the reference frame in each area was spatiotopic or retinotopic. We found that all 12 areas, including MT, represented stimuli in a retinotopic reference frame. Although there were patches of cortex in and around these visual areas that were ostensibly spatiotopic, none of these patches exhibited reliable stimulus-evoked responses. We conclude that the early, visuotopically organized visual cortical areas in the human brain (like their counterparts in the monkey brain) represent stimuli in a retinotopic reference frame.

With each eye movement, stationary objects in the world change position on the retina, yet we perceive the world as stable. Spatial updating, or remapping, is one neural mechanism by which the brain compensates for shifts in the retinal image caused by voluntary eye movements. Remapping of a visual representation is believed to arise from a widespread neural circuit including parietal and frontal cortex. The current experiment tests the hypothesis that extrastriate visual areas in human cortex have access to remapped spatial information. We tested this hypothesis using functional magnetic resonance imaging (fMRI). We first identified the borders of several occipital lobe visual areas using standard retinotopic techniques. We then tested subjects while they performed a single-step saccade task analogous to the task used in neurophysiological studies in monkeys, and two conditions that control for visual and motor effects. We analyzed the fMRI time series data with a nonlinear, fully Bayesian hierarchical statistical model. We identified remapping as activity in the single-step task that could not be attributed to purely visual or oculomotor effects. The strength of remapping was roughly monotonic with position in the visual hierarchy: remapped responses were largest in areas V3A and hV4 and smallest in V1 and V2. These results demonstrate that updated visual representations are present in cortical areas that are directly linked to visual perception.

Vision is an active process. We do not see the world directly; rather, we construct a representation of it from sensory inputs in combination with internal, nonvisual signals. In the case of spatial perception, our representation of the visual scene must take into account our own movements. This allows us to perceive the world as stationary despite the constant eye movements that produce new images on the retina. How is this perceptual stability achieved? Our central hypothesis is that a corollary discharge of the eye movement command updates, or remaps, an internal representation when the eyes move. In support of this hypothesis, the authors review evidence that parietal cortex and extrastriate visual areas in both monkeys and humans participate in spatial updating. These findings shed new light on the neural circuitry involved in producing a stable and coherent perception of visual space.

Following Benjamini and Hochberg [2], the False Discovery Rate has emerged as a viable alternative to strong control of Type I error in multiple testing problems such as those which arise in functional neuroimaging. This paper reports on new methods for false discovery control that can usefully be applied to functional neuroimaging data, especially for thresholding statistical maps. The methods are based on controlling the unobserved False Discovery Proportion (FOP) the number of false rejections divided by the number of rejections simultaneously over all thresholds. From this, one can design thresholding procedures to control the False Discovery Rate and other features of the false discovery process, including the probability that FDP exceeds a speci£ed level or the expected proportion of false regions. We give two variants on these procedures, one for unsmoothed data and one for smoothed data based on random £eld models. We illustrate the methods using data from a visual remapping study.

Cognitive and brain maturational changes continue throughout late childhood and adolescence. During this time, increasing cognitive control over behavior enhances the voluntary suppression of reflexive/impulsive response tendencies. Recently, with the advent of functional MRI, it has become possible to characterize changes in brain activity during cognitive development. In order to investigate the cognitive and brain maturation subserving the ability to voluntarily suppress context-inappropriate behavior, we tested 8–30 year olds in an oculomotor response–suppression task. Behavioral results indicated that adult-like ability to inhibit prepotent responses matured gradually through childhood and adolescence. Functional MRI results indicated that brain activation in frontal, parietal, striatal, and thalamic regions increased progressively from childhood to adulthood. Prefrontal cortex was more active in adolescents than in children or adults; adults demonstrated greater activation in the lateral cerebellum than younger subjects. These results suggest that efficient top-down modulation of reflexive acts may not be fully developed until adulthood and provide evidence that maturation of function across widely distributed brain regions lays the groundwork for enhanced voluntary control of behavior during cognitive development.

We used functional magnetic resonance imaging (fMRI) to investigate cortical activation during the performance of three oculomotor tasks that impose increasing levels of cognitive demand. (1) In a visually guided saccade (VGS) task, subjects made saccades to flashed targets. (2) In a compatible task, subjects made leftward and rightward saccades in response to foveal presentation of the uppercase words “LEFT” or “RIGHT.” (3) In a mixed task, subjects made rightward saccades in response to the lowercase word “left” and leftward saccades in response to the lowercase word “right” on incompatible trials (60%). The remaining 40% of trials required compatible responses to uppercase words. The VGS and compatible tasks, when compared to fixation, activated the three cortical eye fields: the supplementary eye field (SEF), the frontal eye field (FEF), and the parietal eye field (PEF). The mixed task, when compared to the compatible task, activated three additional cortical regions proximate to the three eye fields: (1) rostral to the SEF in medial frontal cortex; (2) rostral to the FEF in dorsolateral prefrontal cortex (DLPFC); (3) rostral and lateral to the PEF in posterior parietal cortex. These areas may contribute to the suppression of prepotent responses and in holding novel visuomotor associations in working memory.

OBJECTIVE: Neuroimaging studies have demonstrated reduced prefrontal cortical blood flow and metabolism in depression, but the neurobehavioral significance of these observations is not yet established. METHOD: The Wisconsin Card Sorting Test, a widely used neuropsychological index of prefrontal cortical function, was administered to 79 patients with major depression who had been unmedicated for at least 28 days, to 47 patients with schizophrenia who had never received antipsychotic medication, and to 61 healthy comparison subjects. RESULTS: Depressed patients demonstrated significant deficits on multiple Wisconsin Card Sorting Test measures compared with healthy individuals. These deficits were correlated with the severity of depression and were less severe than those demonstrated by patients with schizophrenia. CONCLUSIONS: These results provide neuropsychological evidence for significant prefrontal cortical dysfunction in depression.