NeuroImage
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It has been suggested that within the frontal cortex there is a lateral to medial shift in the control of action, with the lateral premotor area (PMA) involved in externally specified actions and the medial supplementary motor areas (SMA) involved in internally specified actions. Recent brain imaging studies demonstrate, however, that the control of externally and internally specified actions may involve more complex and overlapping networks involving not only the PMA and the SMA, but also the pre-SMA and the lateral prefrontal cortex (PFC). The aim of the present study was to determine whether these frontal regions are differentially involved in the production of verbal responses, when they are externally specified and when they are internally specified. ⋯ The magnitude of the activity in the PFC (Brodmann area 45), the left PMAv and the pre-SMA increased for word generation, suggesting that each of these three regions plays a role in internally specified action selection. This confirms previous reports concerning the participation of the pre-SMA in verbal response selection. The pattern of activity in PMAv suggests participation in both externally and internally specified verbal actions.
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Even simple perceptual decisions are influenced by the emotional content of a stimulus. Recent neuroimaging studies provide evidence about the neural mechanisms of perceptual decision making on emotional stimuli. However, the effect of individual differences in cognitive processing of emotions on perceptual decision making remains poorly understood. ⋯ Conversely, individuals with poor ability in this domain showed greater coupling of dACC with the amygdala. Our data indicate that individual differences in the ability to identify and communicate one's emotional state are reflected by altered effective connectivity of the dACC with prefrontal and limbic regions. Thus, we provide neurophysiological evidence for a theoretical model that posits that a discommunication between limbic areas and the neocortex impairs cognitive processing of emotions.
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This work investigated the role of cognitive control functions in selective attention when task-relevant and -irrelevant stimuli come from different sensory modalities. We parametrically manipulated the load of an attentive tracking task and investigated its effect on irrelevant acoustic change-related processing. While subjects were performing the visual attentive tracking task, event-related potentials (ERPs) were recorded for frequent standard tones and rare deviant tones presented as auditory distractors. ⋯ The amplitude of the MMN, which indexes the early detection of irregular changes, increased with increasing attentional load, whereas the subsequent P3a component, which indicates the involuntary orienting of attention to deviants, was significant only in the lowest load condition. These findings suggest that active exclusion of the early detection process of irrelevant acoustic changes depends on available resources of cognitive control, whereas the late involuntary orienting of attention to deviants can be passively suppressed by high demand on central attentional resources. The present study thus reveals opposing visual attentional load effects at different temporal and functional stages in the rejection of deviant auditory distractors and provides a new perspective on the resolution of the long-standing early versus late attention selection debate.
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Bootstrap is an empirical non-parametric statistical technique based on data resampling that has been used to quantify uncertainties of diffusion tensor MRI (DTI) parameters, useful in tractography and in assessing DTI methods. The current bootstrap method (repetition bootstrap) used for DTI analysis performs resampling within the data sharing common diffusion gradients, requiring multiple acquisitions for each diffusion gradient. Recently, wild bootstrap was proposed that can be applied without multiple acquisitions. ⋯ The performances of these bootstrap approaches were compared in terms of bias, variance, and overall error of bootstrap-estimated standard error by Monte Carlo simulation. We demonstrate that residual bootstrap has smaller biases and overall errors, which enables estimation of uncertainties with higher accuracy. Understanding the properties of these bootstrap procedures will help us to choose the optimal approach for estimating uncertainties that can benefit hypothesis testing based on DTI parameters, probabilistic fiber tracking, and optimizing DTI methods.