NeuroImage
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Social connectedness theory posits that the brain processes social rejection as a threat to survival. Recent electrophysiological evidence suggests that midfrontal theta (4-8Hz) oscillations in the EEG provide a window on the processing of social rejection. Here we examined midfrontal theta dynamics (power and inter-trial phase synchrony) during the processing of social evaluative feedback. ⋯ Theta phase, however, differed from the FRN by also displaying stronger phase synchrony in response to rejection vs. acceptance feedback. Together, this study highlights distinct roles for midfrontal theta power and phase synchrony in response to social evaluative feedback. Our findings contribute to the literature by showing that midfrontal theta oscillatory power is sensitive to social rejection but only when peer rejection is unexpected, and this theta response is governed by a widely distributed neural network implicated in saliency detection and conflict monitoring.
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Facial expressions attract attention due to their motivational significance. Previous work focused on attentional biases towards threat-related, fearful faces, although healthy participants tend to avoid mild threat. Growing evidence suggests that neuronal gamma (>30Hz) and alpha-band activity (8-12Hz) play an important role in attentional selection, but it is unknown if such oscillatory activity is involved in the guidance of attention through facial expressions. ⋯ We observed an attentional cost of processing the face distractors, as reflected in lower task performance on targets with short stimulus onset asynchrony (SOA <150ms) between faces and targets. On the neuronal level, attentional orienting to face distractors led to enhanced gamma band activity in bilateral occipital and parietal regions, when fearful faces were presented in the same hemifield as targets, but only in short SOA trials. Our findings provide evidence that both top-down and bottom-up attentional biases are reflected in parieto-occipital gamma-band activity.
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Deep brain stimulation (DBS) of the subgenual cingulate gyrus (area CG25) is beneficial in treatment resistant depression. Though the mechanisms of action of Cg25 DBS remain largely unknown, it is commonly believed that Cg25 DBS modulates limbic activity of large networks to achieve thymic regulation of patients. To investigate how emotional attention is influenced by Cg25 DBS, we assessed behavioral and electroencephalographic (EEG) responses to an emotional Stroop task in 5 patients during ON and OFF stimulation conditions. ⋯ Here, using a simplified neural mass model that did not take explicitly into account the cytoarchitecture of the considered brain regions, we showed that the remote action of Cg25 DBS could be explained by a reduced top-down effective connectivity of the amygdalo-temporo-polar complex. Overall, our results thus indicate that Cg25 DBS during the emotional Stroop task causes a decrease of top-down limbic influence on the ventral visual stream itself, rather than a modulation of prefrontal cognitive processes only. Tuning down limbic excitability in relation to sensory processing might be one of the biological mechanisms through which Cg25 DBS produces positive clinical outcome in the treatment of resistant depression.
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Multicenter Study
Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data.
Machine learning approaches have been widely used for the identification of neuropathology from neuroimaging data. However, these approaches require large samples and suffer from the challenges associated with multi-site, multi-protocol data. We propose a novel approach to address these challenges, and demonstrate its usefulness with the Autism Brain Imaging Data Exchange (ABIDE) database. ⋯ The proposed approach consists of two main stages: a domain adaptation stage using partial least squares regression to maximize the consistency of imaging data across sites; and a learning stage combining support vector regression for regional prediction of severity with elastic-net penalized linear regression for integrating regional predictions into a whole-brain severity prediction. The proposed method performed markedly better than simpler alternatives, better with multi-site than single-site data, and resulted in a considerably higher cross-validated correlation score than has previously been reported in the literature for multi-site data. This demonstration of the utility of the proposed approach for detecting structural brain abnormalities in ASD from the multi-site, multi-protocol ABIDE dataset indicates the potential of designing machine learning methods to meet the challenges of agglomerative data.
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Comparative Study
Diffusion kurtosis metrics as biomarkers of microstructural development: A comparative study of a group of children and a group of adults.
The most common modality of diffusion MRI used in the ageing and development studies is diffusion tensor imaging (DTI) providing two key measures, fractional anisotropy and mean diffusivity. Here, we investigated diffusional changes occurring between childhood (average age 10.3 years) and mitddle adult age (average age 54.3 years) with the help of diffusion kurtosis imaging (DKI), a recent novel extension of DTI that provides additional metrics quantifying non-Gaussianity of water diffusion in brain tissue. We performed voxelwise statistical between-group comparison of diffusion tensor and kurtosis tensor metrics using two methods, namely, the tract-based spatial statistics (TBSS) and the atlas-based regional data analysis. ⋯ The largest changes of this parameter (interpreted as reflecting the lowest level of maturation by the age of children group) were observed in the association fibres, cingulum (gyrus) and cingulum (hippocampus) followed by superior longitudinal fasciculus and inferior longitudinal fasciculus. The smallest changes were observed in the commissural fibres, forceps major and forceps minor. In conclusion, our data suggest that DKI is sensitive to developmental changes in local microstructure and environment, and is particularly powerful to unravel developmental differences in major association fibres, such as the cingulum and superior longitudinal fasciculus.