Shruti Japee

Visual awareness and the detection of fearful faces.

A commonly held view is that emotional stimuli are processed independently of awareness. Here, the authors parametrically varied the duration of a fearful face target stimulus that was backward masked by a neutral face. The authors evaluated awareness by characterizing behavioral performance using receiver operating characteristic curves from signal detection theory. Their main finding was that no universal objective awareness threshold exists for fear perception. Although several subjects displayed a behavioral pattern consistent with previous reports (i.e., targets masked at 33 ms), a considerable percentage of their subjects (64%) were capable of reliably detecting 33-ms targets. Their findings suggest that considerable information is available even in briefly presented stimuli (possibly as short as 17 ms) to support masked fear detection.

SUMA: an interface for surface-based intra- and inter-subject analysis with AFNI

Surface-based brain imaging analysis is increasingly being used for detailed analysis of the topology of brain activation patterns and changes in cerebral gray matter. Here we present SUMA, a new interface for visualizing and performing surface-based brain imaging analysis that is tightly coupled to AFNI - a volume-based brain imaging analysis suite. The interactive part of SUMA is used for rapid and interactive surface and data visualization, access and manipulations with direct link to the volumetric data rendered in AFNI. The batch-mode part of SUMA allows for surface based operations such as geometry and data smoothing, surface to volume domain mapping in both directions and node-based statistical and computational tools. We also present methods for mapping low resolution functional data onto the cortical surface while preserving the topological information present in the volumetric data and detail an efficient procedure for performing cross-subject, surface-based analysis with minimal interpolation of the functional data.

Activations in visual and attention-related areas predict and correlate with the degree of perceptual learning.

Repeated experience with a visual stimulus can result in improved perception of the stimulus, i.e., perceptual learning. To understand the underlying neural mechanisms of this process, we used functional magnetic resonance imaging to track brain activations during the course of training on a contrast discrimination task. Based on their ability to improve on the task within a single scan session, subjects were separated into two groups: “learners” and “nonlearners.” As learning progressed, learners showed progressively reduced activation in both visual cortex, including Brodmanns areas 18 and 19 and the fusiform gyrus, and several cortical regions associated with the attentional network, namely, the intraparietal sulcus (IPS), frontal eye field (FEF), and supplementary eye field. Among learners, the decrease in brain activations in these regions was highly correlated with the magnitude of performance improvement. Unlike learners, nonlearners showed no changes in brain activations during training. Learners showed stronger activation than nonlearners during the initial period of training in all these brain regions, indicating that one could predict from the initial activation level who would learn and who would not. In addition, over the course of training, the functional connectivity between IPS and FEF in the right hemisphere with early visual areas was stronger for learners than nonlearners. We speculate that sharpened tuning of neuronal representations may cause reduced activation in visual cortex during perceptual learning and that attention may facilitate this process through an interaction of attention-related and visual cortical regions.

A role of right middle frontal gyrus in reorienting of attention: a case study.

The right middle fontal gyrus (MFG) has been proposed to be a site of convergence of the dorsal and ventral attention networks, by serving as a circuit-breaker to interrupt ongoing endogenous attentional processes in the dorsal network and reorient attention to an exogenous stimulus. Here, we probed the contribution of the right MFG to both endogenous and exogenous attention by comparing performance on an orientation discrimination task of a patient with a right MFG resection and a group of healthy controls. On endogenously cued trials, participants were shown a central cue that predicted with 90% accuracy the location of a subsequent peri-threshold Gabor patch stimulus. On exogenously cued trials, a cue appeared briefly at one of two peripheral locations, followed by a variable inter-stimulus interval (ISI; range 0–700 ms) and a Gabor patch in the same or opposite location as the cue. Behavioral data showed that for endogenous, and short ISI exogenous trials, valid cues facilitated responses compared to invalid cues, for both the patient and controls. However, at long ISIs, the patient exhibited difficulty in reverting to top-down attentional control, once the facilitatory effect of the exogenous cue had dissipated. When explicitly cued during long ISIs to attend to both stimulus locations, the patient was able to engage successfully in top-down control. This result indicates that the right MFG may play an important role in reorienting attention from exogenous to endogenous attentional control. Resting state fMRI data revealed that the right superior parietal lobule and right orbitofrontal cortex, showed significantly higher correlations with a left MFG seed region (a region tightly coupled with the right MFG in controls) in the patient relative to controls. We hypothesize that this paradoxical increase in cortical coupling represents a compensatory mechanism in the patient to offset the loss of function of the resected tissue in right prefrontal cortex.

Attentional control during the transient updating of cue information

The goal of the present study was to investigate the neural correlates of top-down control of switching behavior in humans and to contrast them to those observed during switching behavior guided by bottom-up mechanisms. In the main experimental condition (color-cue), which was guided by top-down control, a central cue indicated the color of a peripheral grating on which the subject performed an orientation judgment. For switch trials, the color of the cue on the current trial was different from the color on the previous trial. For non-switch trials, the color of the cue on the current trial was the same as the color in the preceding trial. During a control condition (pop-out), which was guided by bottom-up saliency, the target grating was defined by color contrast; again both switch and non-switch trials occurred. We observed stronger evoked responses during the color-cue task relative to the pop-out task in the inferior parietal lobule (IPL), frontal eye field (FEF), middle frontal gyrus (MFG), and inferior frontal gyrus (IFG). The contrast of switch vs. non-switch trials revealed activations in regions that were engaged when there was a change in the identity of the target. Collectively, switch trials evoked stronger responses relative to non-switch trials in fronto-parietal regions that appeared to be left lateralized, including left intraparietal sulcus (IPS) and left MFG/IFG. Task by trial type interactions (switch>non-switch during color-cue relative to pop-out) were observed in several fronto-parietal regions, including IPS, FEF, MFG and IFG, in addition to regions in visual cortex. Our findings suggest that, within the fronto-parietal attentional network, the IPS and MFG/IFG appear to be most heavily involved in attentive cue updating. Furthermore, several visual regions engaged by oriented gratings were strongly affected by cue updating, raising the possibility that they were the recipient of top-down signals that were generated when cue information was updated.

Individual Differences in Valence Modulation of Face-Selective M170 Response

Magnetoencephalography was used to examine the effect of individual differences on the temporal dynamics of emotional face processing by grouping subjects based on their ability to detect masked valence-laden stimuli. Receiver operating characteristic curves and a nonparametric sensitivity measure were used to categorize subjects into those that could and could not reliably detect briefly presented fearful faces that were backward-masked by neutral faces. Results showed that, in a cluster of face-responsive sensors, the strength of the M170 response was modulated by valence only when subjects could reliably detect the masked fearful faces. Source localization of the M170 peak using synthetic aperture magnetometry identified sources in face processing areas such as right middle occipital gyrus and left fusiform gyrus that showed the valence effect for those target durations at which subjects were sensitive to the fearful stimulus. Subjects who were better able to detect fearful faces also showed higher trait anxiety levels. These results suggest that individual differences between subjects, such as trait anxiety levels and sensitivity to fearful stimuli, may be an important factor to consider when studying emotion processing.

Fearful face detection sensitivity in healthy adults correlates with anxiety-related traits.

Threatening faces have a privileged status in the brain, which can be reflected in a processing advantage. However, this effect varies among individuals, even healthy adults. For example, one recent study showed that fearful face detection sensitivity correlated with trait anxiety in healthy adults (S. Japee, L. Crocker, F. Carver, L. Pessoa, & L. G. Ungerleider, 2009. Individual differences in valence modulation of face-selective M170 response. Emotion, 9, 59-69). Here, we expanded on those findings by investigating whether intersubject variability in fearful face detection is also associated with state anxiety, as well as more broadly with other traits related to anxiety. To measure fearful face detection sensitivity, we used a masked face paradigm where the target face was presented for only 33 ms and was immediately followed by a neutral face mask. Subjects then rated their confidence in detecting either fear or no fear in the target face. Fearful face detection sensitivity was calculated for each subject using signal detection theory. Replicating previous results, we found a significant positive correlation between trait anxiety and fearful face detection sensitivity. However, this behavioral advantage did not correlate with state anxiety. We also found that fearful face detection sensitivity correlated with other personality measures, including neuroticism and harm avoidance. Our data suggest that fearful face detection sensitivity varies parametrically across the healthy population, is associated broadly with personality traits related to anxiety, but remains largely unaffected by situational fluctuations in anxiety. These results underscore the important contribution of anxiety-related personality traits to threat processing in healthy adults.

Face-selective regions differ in their ability to classify facial expressions

Recognition of facial expressions is crucial for effective social interactions. Yet, the extent to which the various face-selective regions in the human brain classify different facial expressions remains unclear. We used functional magnetic resonance imaging (fMRI) and support vector machine pattern classification analysis to determine how well face-selective brain regions are able to decode different categories of facial expression. Subjects participated in a slow event-related fMRI experiment in which they were shown 32 face pictures, portraying four different expressions: neutral, fearful, angry, and happy and belonging to eight different identities. Our results showed that only the amygdala and the posterior superior temporal sulcus (STS) were able to accurately discriminate between these expressions, albeit in different ways: the amygdala discriminated fearful faces from non-fearful faces, whereas STS discriminated neutral from emotional (fearful, angry and happy) faces. In contrast to these findings on the classification of emotional expression, only the fusiform face area (FFA) and anterior inferior temporal cortex (aIT) could discriminate among the various facial identities. Further, the amygdala and STS were better than FFA and aIT at classifying expression, while FFA and aIT were better than the amygdala and STS at classifying identity. Taken together, our findings indicate that the decoding of facial emotion and facial identity occurs in different neural substrates: the amygdala and STS for the former and FFA and aIT for the latter.

A Normalization Framework for Emotional Attention

The normalization model of attention proposes that attention can affect performance by response- or contrast-gain changes, depending on the size of the stimulus and attention field. Here, we manipulated the attention field by emotional valence, negative faces versus positive faces, while holding stimulus size constant in a spatial cueing task. We observed changes in the cueing effect consonant with changes in response gain for negative faces and contrast gain for positive faces. Neuroimaging experiments confirmed that subjects’ attention fields were narrowed for negative faces and broadened for positive faces. Importantly, across subjects, the self-reported emotional strength of negative faces and positive faces correlated, respectively, both with response- and contrast-gain changes and with primary visual cortex (V1) narrowed and broadened attention fields. Effective connectivity analysis showed that the emotional valence-dependent attention field was closely associated with feedback from the dorsolateral prefrontal cortex (DLPFC) to V1. These findings indicate a crucial involvement of DLPFC in the normalization processes of emotional attention.

The superior temporal sulcus is causally connected to the amygdala: A combined TBS-fMRI study.

Nonhuman primate neuroanatomical studies have identified a cortical pathway from the superior temporal sulcus (STS) projecting into dorsal subregions of the amygdala, but whether this same pathway exists in humans is unknown. Here, we addressed this question by combining theta burst transcranial magnetic stimulation (TBS) with fMRI to test the prediction that the STS and amygdala are functionally connected during face perception. Human participants (N = 17) were scanned, over two sessions, while viewing 3 s video clips of moving faces, bodies, and objects. During these sessions, TBS was delivered over the face-selective right posterior STS (rpSTS) or over the vertex control site. A region-of-interest analysis revealed results consistent with our hypothesis. Namely, TBS delivered over the rpSTS reduced the neural response to faces (but not to bodies or objects) in the rpSTS, right anterior STS (raSTS), and right amygdala, compared with TBS delivered over the vertex. By contrast, TBS delivered over the rpSTS did not significantly reduce the neural response to faces in the right fusiform face area or right occipital face area. This pattern of results is consistent with the existence of a cortico-amygdala pathway in humans for processing face information projecting from the rpSTS, via the raSTS, into the amygdala. This conclusion is consistent with nonhuman primate neuroanatomy and with existing face perception models. SIGNIFICANCE STATEMENT Neuroimaging studies have identified multiple face-selective regions in the brain, but the functional connections between these regions are unknown. In the present study, participants were scanned with fMRI while viewing movie clips of faces, bodies, and objects before and after transient disruption of the face-selective right posterior superior temporal sulcus (rpSTS). Results showed that TBS disruption reduced the neural response to faces, but not to bodies or objects, in the rpSTS, right anterior STS (raSTS), and right amygdala. These results are consistent with the existence of a cortico-amygdala pathway in humans for processing face information projecting from the rpSTS, via the raSTS, into the amygdala. This conclusion is consistent with nonhuman primate neuroanatomy and with existing face perception models.