Po-Jang Hsieh

New Method for fMRI Investigations of Language: Defining ROIs Functionally in Individual Subjects

Previous neuroimaging research has identified a number of brain regions sensitive to different aspects of linguistic processing, but precise functional characterization of these regions has proven challenging. We hypothesize that clearer functional specificity may emerge if candidate language-sensitive regions are identified functionally within each subject individually, a method that has revealed striking functional specificity in visual cortex but that has rarely been applied to neuroimaging studies of language. This method enables pooling of data from corresponding functional regions across subjects rather than from corresponding locations in stereotaxic space (which may differ functionally because of the anatomical variability across subjects). However, it is far from obvious a priori that this method will work as it requires that multiple stringent conditions be met. Specifically, candidate language-sensitive brain regions must be identifiable functionally within individual subjects in a short scan, must be replicable within subjects and have clear correspondence across subjects, and must manifest key signatures of language processing (e.g., a higher response to sentences than nonword strings, whether visual or auditory). We show here that this method does indeed work: we identify 13 candidate language-sensitive regions that meet these criteria, each present in >or=80% of subjects individually. The selectivity of these regions is stronger using our method than when standard group analyses are conducted on the same data, suggesting that the future application of this method may reveal clearer functional specificity than has been evident in prior neuroimaging research on language.

Pop-Out Without Awareness Unseen Feature Singletons Capture Attention Only When Top-Down Attention Is Available

Visual pop-out occurs when a unique visual target (e.g., a feature singleton) is present in a set of homogeneous distractors. However, the role of visual awareness in this process remains unclear. In the experiments reported here, we showed that even though subjects were not aware of a suppressed pop-out display, their subsequent performance on an orientation-discrimination task was significantly better at the pop-out location than at a control location. These results indicate that conscious visual awareness of a feature singleton is not necessary for it to attract attention. Furthermore, the subliminal pop-out effect disappeared when subjects diverted their attention toward a rapid sequential visual presentation task while presented with the same subliminal pop-out display. These results suggest that top-down attention is necessary for the subliminal pop-out effect and that the cognitive processes underlying attention and awareness are somewhat independent.

Pop-Out Without Awareness

Visual pop-out occurs when a unique visual target (e.g., a feature singleton) is present in a set of homogeneous distractors. However, the role of visual awareness in this process remains unclear. In the experiments reported here, we showed that even though subjects were not aware of a suppressed pop-out display, their subsequent performance on an orientation-discrimination task was significantly better at the pop-out location than at a control location. These results indicate that conscious visual awareness of a feature singleton is not necessary for it to attract attention. Furthermore, the subliminal pop-out effect disappeared when subjects diverted their attention toward a rapid sequential visual presentation task while presented with the same subliminal pop-out display. These results suggest that top-down attention is necessary for the subliminal pop-out effect and that the cognitive processes underlying attention and awareness are somewhat independent.

Microsaccade Rate Varies with Subjective Visibility during Motion-Induced Blindness

Motion-induced blindness (MIB) occurs when a dot embedded in a motion field subjectively vanishes. Here we report the first psychophysical data concerning effects of microsaccade/eyeblink rate upon perceptual switches during MIB. We find that the rate of microsaccades/eyeblink rises before and after perceptual transitions from not seeing to seeing the dot, and decreases before perceptual transitions from seeing it to not seeing it. In addition, event-related fMRI data reveal that, when a dot subjectively reappears during MIB, the blood oxygen-level dependent (BOLD) signal increases in V1v and V2v and decreases in contralateral hMT+. These BOLD signal changes observed upon perceptual state changes in MIB could be driven by the change of perceptual states and/or a confounding factor, such as the microsaccade/eyeblink rate.

The infinite regress illusion reveals faulty integration of local and global motion signals

We report a new visual illusion, where a global shape appears to continually move away from fixation, even though it remains a fixed distance from fixation. The illusion occurs because local motion signals within the object indicate motion away from fixation, and are incorrectly attributed by the visual system to the motion trajectory of the global object. A simple weighted vector summation of global and local motion signals, while a reasonable first approximation, cannot fully account for our data. We show that the faster the local motion signal, the more it biases judgments of global motion direction. We propose that local and global motion signals are summed non-linearly for this stimulus because as local motion speed increases, moving luminance blobs are visible for less time, affording less time to inhibit inappropriate component motion signals. This effect reveals the degree to which the visual system can incorrectly combine local and global motion signals belonging to a single object.

BOLD activation varies parametrically with corner angle throughout human retinotopic cortex

The Alternating Brightness Star (ABS) is an illusion that provides insight into the relationship between brightness perception and corner angle. Recent psychophysical studies of this illusion have shown that corner salience varies parametrically with corner angle, with sharp angles leading to strong illusory percepts and shallow angles leading to weak percepts. It is hypothesized that the illusory effects arise because of an interaction between surface corners and the shape of visual receptive fields: sharp surface corners may create hotspots of high local contrast due to processing by center–surround and other early receptive fields. If this hypothesis is correct, early visual neurons should respond powerfully to sharp corners and curved portions of surface edges. Indeed, the primary role of early visual neurons may be to localize the discontinuities along the edges of surfaces. If so, all early visual areas should show greater BOLD responses to sharp corners than to shallow corners. On the other hand, if corner processing is exclusively constrained to certain areas of the brain, only those specific areas will show greater responses to sharp vs shallow corners. To address this we explored the BOLD correlates of the ABS illusion in the human visual cortex using fMRI. We found that BOLD signal varies parametrically with corner angle throughout the visual cortex, offering the first neurophysiological correlates of the ABS illusion. This finding provides a neurophysiological basis for the previously reported psychophysical data that showed that corner salience varied parametrically with corner angle. We propose that all early visual areas localize discontinuities along the edges of surfaces, and that specific cortical corner-processing circuits further establish the specific nature of those discontinuities, such as their orientation.

Search for Patterns of Functional Specificity in the Brain: A Nonparametric Hierarchical Bayesian Model for Group fMRI Data

Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with previously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli.

Pre-stimulus pattern of activity in the fusiform face area predicts face percepts during binocular rivalry.

Visual input is ambiguous, yet conscious experience is unambiguous. In binocular rivalry the two eyes receive conflicting images, but only one of them is consciously perceived at a time. Here we search for the neural sites of the competitive interactions underlying this phenomenon by testing whether neural pattern activity occurring before stimulus presentation can predict the initial dominant percept in binocular rivalry and, if so, where in the brain such predictive activity is found. Subjects were scanned while viewing an image of a face in one eye and an image of a house in the other eye with anaglyph glasses. The rivalrous stimulus was presented briefly for each trial, and the subject indicated which of the two images he or she preferentially perceived. Our results show that BOLD fMRI multivariate pattern activity in the fusiform face area (FFA) before the stimulus is presented predicts which of the two images will be dominant, suggesting that higher extrastriate areas, such as the FFA, are not only correlated with, but may also be involved in determining the initial dominant percept in binocular rivalry. Furthermore, by examining pattern activity before and after trial onset, we found that pre-trial activity in the FFA for the rivalrous face trials is no more similar to the post-trial activity for the non-rivalrous face trials than to that for the non-rivalrous house trials, indicating a dissociation between neural pattern information, which predicts a given state of awareness, and mean responses, which reflect the state of awareness ultimately achieved.

“Brain-reading” of perceived colors reveals a feature mixing mechanism underlying perceptual filling-in in cortical area V1

Visual filling‐in occurs when a retinally stabilized object undergoes perceptual fading. As the term “filling‐in” implies, it is commonly believed that information about the apparently vanished object is lost and replaced solely by information arising from the surrounding background. Here we report multivoxel pattern analysis fMRI data that challenge this long‐held belief. When subjects view blue disks on a red background while fixating, the stimulus and background appear to turn a uniform purple upon perceptual fading, suggesting that a feature mixing mechanism may underlie color filling‐in. We find that ensemble fMRI signals in retinotopic visual areas reliably predict (i) which of three colors a subject reports seeing; (ii) whether a subject is in a perceptually filled‐in state or not; and (iii) furthermore, while subjects are in the perceptual state of filling‐in, the BOLD signal activation pattern in the sub‐areas of V1 corresponding to the location of the blue disks behaves as if subjects are in fact viewing a perceptually mixed color (purple), rather than the color of the disks (blue) or the color of the background (red). These results imply that the mechanism of filling‐in in stimuli in which figure and background surfaces are equated is a process of “feature mixing”, not “feature replacement”. These data indicate that feature mixing may involve cortical areas as early as V1. Hum Brain Mapp, 2010.

Data-driven functional clustering reveals dominance of face, place, and body selectivity in the ventral visual pathway

Regions selective for faces, places, and bodies feature prominently in the literature on the human ventral visual pathway. Are selectivities for these categories in fact the most robust response profiles in this pathway, or is their prominence an artifact of biased sampling of the hypothesis space in prior work? Here we use a data-driven structure discovery method that avoids the assumptions built into most prior work by 1) giving equal consideration to all possible response profiles over the conditions tested, 2) relaxing implicit anatomical constraints (that important functional profiles should manifest themselves in spatially contiguous voxels arising in similar locations across subjects), and 3) testing for dominant response profiles over images, rather than categories, thus enabling us to discover, rather than presume, the categories respected by the brain. Even with these assumptions relaxed, face, place, and body selectivity emerge as dominant in the ventral stream.