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1.  Effective connectivities of cortical regions for top-down face processing: A Dynamic Causal Modeling study 
Brain research  2010;1340:40-51.
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.
doi:10.1016/j.brainres.2010.04.044
PMCID: PMC3724518  PMID: 20423709
Face processing; Top-down processing; Bottom-up processing; Dynamic Causal Modeling (DCM); Orbitofrontal cortex (OFC)
2.  Is Order the Defining Feature of Magnitude Representation? An ERP Study on Learning Numerical Magnitude and Spatial Order of Artificial Symbols 
PLoS ONE  2012;7(11):e49565.
Using an artificial-number learning paradigm and the ERP technique, the present study investigated neural mechanisms involved in the learning of magnitude and spatial order. 54 college students were divided into 2 groups matched in age, gender, and school major. One group was asked to learn the associations between magnitude (dot patterns) and the meaningless Gibson symbols, and the other group learned the associations between spatial order (horizontal positions on the screen) and the same set of symbols. Results revealed differentiated neural mechanisms underlying the learning processes of symbolic magnitude and spatial order. Compared to magnitude learning, spatial-order learning showed a later and reversed distance effect. Furthermore, an analysis of the order-priming effect showed that order was not inherent to the learning of magnitude. Results of this study showed a dissociation between magnitude and order, which supports the numerosity code hypothesis of mental representations of magnitude.
doi:10.1371/journal.pone.0049565
PMCID: PMC3501518  PMID: 23185363
3.  Distinct representations of subtraction and multiplication in the neural systems for numerosity and language 
Human brain mapping  2011;32(11):1932-1947.
It has been proposed that recent cultural inventions such as symbolic arithmetic recycle evolutionary older neural mechanisms. A central assumption of this hypothesis is that the degree to which a pre-existing mechanism is recycled depends upon the degree of similarity between its initial function and the novel task. To test this assumption, we investigated whether the brain region involved in magnitude comparison in the intraparietal sulcus (IPS), localized by a numerosity comparison task, is recruited to a greater degree by arithmetic problems that involve number comparison (single-digit subtractions) than by problems that involve retrieving facts from memory (single-digit multiplications). Our results confirmed that subtractions are associated with greater activity in the IPS than multiplications, whereas multiplications elicit greater activity than subtractions in regions involved in verbal processing including the middle temporal gyrus and inferior frontal gyrus that were localized by a phonological processing task. Pattern analyses further indicated that the neural mechanisms more active for subtraction than multiplication in the IPS overlap with those involved in numerosity comparison, and that the strength of this overlap predicts inter-individual performance in the subtraction task. These findings provide novel evidence that elementary arithmetic relies on the co-option of evolutionary older neural circuits.
doi:10.1002/hbm.21159
PMCID: PMC3117906  PMID: 21246667
multiplication; subtraction; numerosity; neural recycling; fMRI
4.  Neural Correlates of Top-Down Letter Processing 
Neuropsychologia  2009;48(2):636.
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.
doi:10.1016/j.neuropsychologia.2009.10.024
PMCID: PMC2814001  PMID: 19883666
word processing; letter processing; top-down processing; fMRI
5.  A distributed neural system for top-down face processing 
Neuroscience letters  2008;451(1):6-10.
Evidence suggests that the neural system associated with face processing is a distributed cortical network containing both bottom-up and top-down mechanisms. While bottom-up face processing has been the focus of many studies, the neural areas involved in the top-down face processing have not been extensively investigated due to difficulty in isolating top-down influences from the bottom-up response engendered by presentation of a face. In the present study, we used a novel experimental method to induce illusory face detection. This method allowed for directly examining the neural systems involved in top-down face processing while minimizing the influence of bottom-up perceptual input. A distributed cortical network of top-down face processing was identified by analyzing the functional connectivity patterns of the right fusiform face area (FFA). This distributed cortical network model for face processing includes both “core” and “extended” face processing areas. It also includes left anterior cingulate cortex (ACC), bilateral orbitofrontal cortex (OFC), left dorsolateral prefrontal cortex (DLPFC), left premotor cortex, and left inferior parietal cortex. These findings suggest that top-down face processing contains not only regions for analyzing the visual appearance of faces, but also those involved in processing low spatial frequency (LSF) information, decision making, and working memory.
doi:10.1016/j.neulet.2008.12.039
PMCID: PMC2634849  PMID: 19121364
top-down processing; psychophysiological interaction (PPI); distributed cortical network; fMRI; face processing

Results 1-5 (5)