Jiangang Liu

Detecting faces in pure noise images: a functional MRI study on top-down perception.

To assess the nature of top-down perceptual processes without contamination from bottom-up input, this functional MRI study investigated face detection in pure noise images. Greater activation was revealed for face versus nonface responses in the fusiform face area, but not in the occipital face area. Across participants, positive correlations were found for the degree of greater face-detection activation between the fusiform face area and bilateral inferior frontal gyri, suggesting a top-down pathway generating perceptual expectations. In contrast, the medial frontal, parietal, supplementary motor, parahippocampal, and striatal areas produced negative correlations between degrees of greater face-detection activation and behavioral responses, suggesting a possible role for these areas in selecting and executing appropriate responses that are based on the top-down expectations.

The other face of the other-race effect: An fMRI investigation of the other-race face categorization advantage

The present study was the first to use the functional magnetic resonance imaging (fMRI) methodology to investigate the neural correlates of race categorization of own- and other-race faces. We found that Chinese participants categorized the race of Caucasian faces more accurately and faster than that of Chinese faces, replicating the robust effect of the other-race categorization advantage. Regions of interest (ROI) analyses revealed greater neural activations when participants were categorizing own-race faces than other-race faces in the bilateral ventral occipito-temporal cortex (VOT) such as the fusiform face areas (FFAs) and the occipital face areas (OFAs). Within the left FFA, there was also a significant negative correlation between the behavioral difference of own- and other-race face categorization accuracy and the activation difference between categorizing own- and other-race faces. Whole brain analyses showed that categorizing own-race faces induced greater activations in the right medial frontal cortex (MFC) and right inferior frontal gyrus (IFG) than categorizing other-race faces. Psychophysiological interaction (PPI) analyses revealed that the frontal cortical regions interacted more strongly with the posterior VOT during the categorization of own-race faces than that of other-race faces. Overall, our findings suggest that relative to the categorization of other-race faces, more cortical resources are engaged during the categorization of own-race faces with which we have a higher level of processing expertise. This increased involvement of cortical neural sources perhaps serves to provide more in-depth processing of own-race faces (such as individuation), which in turn paradoxically results in the behavioral other-race categorization advantage.

Effective connectivities of cortical regions for top-down face processing: A Dynamic Causal Modeling study

To study top-down face processing, the present study used an experimental paradigm in which participants detected non-existent faces in pure noise images. Conventional BOLD signal analysis identified three regions involved in this illusory face detection. These regions included the left orbitofrontal cortex (OFC) in addition to the right fusiform face area (FFA) and right occipital face area (OFA), both of which were previously known to be involved in both top-down and bottom-up processing of faces. We used Dynamic Causal Modeling (DCM) and Bayesian model selection to further analyze the data, revealing both intrinsic and modulatory effective connectivities among these three cortical regions. Specifically, our results support the claim that the orbitofrontal cortex plays a crucial role in the top-down processing of faces by regulating the activities of the occipital face area, and the occipital face area in turn detects the illusory face features in the visual stimuli and then provides this information to the fusiform face area for further analysis.

Neural correlates of second-order verbal deception: a functional near-infrared spectroscopy (fNIRS) study.

The present study focused on neural correlates underlying second-order deception. In first-order deception, the recipient of deception is unaware of the deceivers deceptive intention. However, during second-order deception, the recipient is fully aware of the deceivers deceptive intention and thus the deceiver needs to use both lies and truths to deceive the recipient. Using the functional near-infrared spectroscopy (fNIRS) methodology and a naturalistic interactive game, we found that second-order deception elicited significantly greater [oxy-Hb] changes in the prefrontal cortex (the right superior frontal gyrus (SFG), BA6) than the non-deceptive control condition. This finding suggests that second-order deception, like first-order deception, engages specifically the cortical regions associated with the planning of complex actions and goal processing. We also found that lying to deceive produced greater neural activities in the right middle frontal gyrus than truth-telling to deceive. This suggests that although both actions serve deceptive purposes, making a false statement contradicting the true state of affairs still requires more executive control and thus greater neural responses in the cortical regions associated with this function. In addition, we found that the successful deception produced greater neural activities in a broad area of the prefrontal frontal cortex than failure to deceive, indicating the involvement of the cortical reward system during second-order deception. Further, failure of truth-telling to deceive produced greater neural responses in the right SFG than failure of lying to deceive. The present findings taken together suggest that second-order deception engages both the cortical executive and reward systems.

Intrinsically organized network for word processing during the resting state.

Neural mechanisms underlying word processing have been extensively studied. It has been revealed that when individuals are engaged in active word processing, a complex network of cortical regions is activated. However, it is entirely unknown whether the word-processing regions are intrinsically organized without any explicit processing tasks during the resting state. The present study investigated the intrinsic functional connectivity between word-processing regions during the resting state with the use of fMRI methodology. The low-frequency fluctuations were observed between the left middle fusiform gyrus and a number of cortical regions. They included the left angular gyrus, left supramarginal gyrus, bilateral pars opercularis, and left pars triangularis of the inferior frontal gyrus, which have been implicated in phonological and semantic processing. Additionally, the activations were also observed in the bilateral superior parietal lobule and dorsal lateral prefrontal cortex, which have been suggested to provide top-down monitoring on the visual-spatial processing of words. The findings of our study indicate an intrinsically organized network during the resting state that likely prepares the visual system to anticipate the highly probable word input for ready and effective processing.

Neural Correlates of Top-Down Letter Processing.

This fMRI study investigated top-down letter processing with an illusory letter detection task. Participants responded whether one of a number of different possible letters was present in a very noisy image. After initial training that became increasingly difficult, they continued to detect letters even though the images consisted of pure noise, which eliminated contamination from strong bottom-up input. For illusory letter detection, greater fMRI activation was observed in several cortical regions. These regions included the precuneus, an area generally involved in top-down processing of objects, and the left superior parietal lobule, an area previously identified with the processing of valid letter and word stimuli. In addition, top-down letter detection also activated the left inferior frontal gyrus, an area that may be involved in the integration of general top-down processing and letter-specific bottom-up processing. These findings suggest that these regions may play a significant role in top-down as well as bottom-up processing of letters and words, and are likely to have reciprocal functional connections to more posterior regions in the word and letter processing network.

Resting state neural networks for visual Chinese word processing in Chinese adults and children.

This study examined the resting state neural networks for visual Chinese word processing in Chinese children and adults. Both the functional connectivity (FC) and amplitude of low frequency fluctuation (ALFF) approaches were used to analyze the fMRI data collected when Chinese participants were not engaged in any specific explicit tasks. We correlated time series extracted from the visual word form area (VWFA) with those in other regions in the brain. We also performed ALFF analysis in the resting state FC networks. The FC results revealed that, regarding the functionally connected brain regions, there exist similar intrinsically organized resting state networks for visual Chinese word processing in adults and children, suggesting that such networks may already be functional after 3-4 years of informal exposure to reading plus 3-4 years formal schooling. The ALFF results revealed that children appear to recruit more neural resources than adults in generally reading-irrelevant brain regions. Differences between child and adult ALFF results suggest that childrens intrinsic word processing network during the resting state, though similar in functional connectivity, is still undergoing development. Further exposure to visual words and experience with reading are needed for children to develop a mature intrinsic network for word processing. The developmental course of the intrinsically organized word processing network may parallel that of the explicit word processing network.

A Dynamic Causal Modeling Analysis of the Effective Connectivities Underlying Top-Down Letter Processing.

The present study employed dynamic causal modeling to investigate the effective functional connectivity between regions of the neural network involved in top-down letter processing. We used an illusory letter detection paradigm in which participants detected letters while viewing pure noise images. When participants detected letters, the response of the right middle occipital gyrus (MOG) in the visual cortex was enhanced by increased feed-backward connectivity from the left inferior frontal gyrus (IFG). In addition, illusory letter detection increased feed-forward connectivity from the right MOG to the left inferior parietal lobules. Originating in the left IFG, this top-down letter processing network may facilitate the detection of letters by activating letter processing areas within the visual cortex. This activation in turns may highlight the visual features of letters and send letter information to activate the associated phonological representations in the identified parietal region.

A weighted-RV method to detect fine-scale functional connectivity during resting state.

During the resting state, in the absence of external stimuli or goal-directed mental tasks, some functionally related discrete regions of the brain show complex low-frequency fluctuations in the blood oxygenation level dependent signal. Here we developed a novel ROI-based multivariate statistical framework to obtain the fine-grained patterns of functionally specialized brain networks in the resting state. Under this framework, the weighted-RV method is proposed and used to detect the spatial fine-scale patterns of functional connectivity. This approach overcomes several major problems of the traditional resting-state data analysis methods such as Pearson correlation and linear regression analysis. By using simulation and real fMRI experiment, we have found that the weighted-RV method is shown to be more sensitive in detecting the fine-scale based low-frequency connectivity even at a very low functional contrast-to-noise ratio (CNR), and this method can achieve much better performance in mapping the fine-grained patterns of functionally specialized brain networks compared to the traditional methods.

Development of Effective Connectivity during Own- and Other-Race Face Processing: A Granger Causality Analysis

Numerous developmental studies have suggested that other-race effect (ORE) in face recognition emerges as early as in infancy and develops steadily throughout childhood. However, there is very limited research on the neural mechanisms underlying this developmental ORE. The present study used Granger causality analysis (GCA) to examine the development of childrens cortical networks in processing own- and other-race faces. Children were between 3 and 13 years. An old-new paradigm was used to assess their own- and other-race face recognition with ETG-4000 (Hitachi Medical Co., Japan) acquiring functional near infrared spectroscopy (fNIRS) data. After preprocessing, for each participant and under each face condition, we obtained the causal map by calculating the weights of causal relations between the time courses of [oxy-Hb] of each pair of channels using GCA. To investigate further the differential causal connectivity for own-race faces and other-race faces at the group level, a repeated measure analysis of variance (ANOVA) was performed on the GCA weights for each pair of channels with the face race task (own-race face vs. other-race face) as the within-subject variable and the age as a between-subject factor (continuous variable). We found an age-related increase in functional connectivity, paralleling a similar age-related improvement in behavioral face processing ability. More importantly, we found that the significant differences in neural functional connectivity between the recognition of own-race faces and that of other-race faces were modulated by age. Thus, like the behavioral ORE, the neural ORE emerges early and undergoes a protracted developmental course.