16 research outputs found

    Rebuttal to Hasan and Pedraza in comments and controversies: "Improving the reliability of manual and automated methods for hippocampal and amygdala volume measurements"

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    Here we address the critiques offered by Hasan and Pedraza to our recently published manuscript comparing the performance of two automated segmentation programs, FSL/FIRST and FreeSurfer (Morey R, Petty C, Xu Y, Pannu Hayes J, Wagner H, Lewis D, LaBar K, Styner M, McCarthy G. (2009): A comparison of automated segmentation and manual tracing for quantifying of hippocampal and amygdala volumes. Neuroimage 45:855-866). We provide an assessment and discussion of their specific critiques. Hasan and Pedraza bring up some important points concerning our omission of sample demographic features and inclusion of left and right hemisphere volumes as independent measures in correlational analyses. We present additional data on demographic attributes of our sample and correlations analyzed separately on left and right hemispheres of the amygdala and hippocampus. While their commentary aids the reader to more critically asses our study, it falls short of substantiating that our omissions ought to lead readers to significantly revise their interpretations. Further research will help to disentangle the advantages and limitations of the various freely-available automated segmentation software packages

    Interactions Between Emotion and Cognition: A Neurobiological Perspective

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    Dynamic Aspects of Face Processing in Humans

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    In this chapter, we will focus on the role of motion in identity and expression recognition in human, and its developmental and neurophysiological aspects. Based on results from literature, we make it clear that there is some form of characteristic facial information that is only available over time, and that it plays an important role in the recognition of identity, expression, speech, and gender; and that the addition of dynamic information improves the recognizability of expressions and identity, and can compensate for the loss of static information. Moreover, at least several different types of motion seem to exist, they play different roles, and a simple rigid/nonrigid dichotomy is neither sufficient nor appropriate to describe these motions. Additional research is necessary to determine what the dynamic features for face processing are
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