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  • Neuroinformatics

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  • Authors: Pietrini, Pietro;
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Laricchiuta, Daniela; Greco, Francesca; Piras, Fabrizio; Cordella, Barbara; +6 Authors
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Authors: Foster, Jane A.; Lyte, Mark; Meyer, Emeran; Cryan, John F.;

    There is a growing appreciation of the importance of gut microbiota to health and disease. This has been driven by advances in sequencing technology and recent findings demonstrating the important role of microbiota in common health disorders such as obesity. Moreover, the potential role of gut microbiota in influencing brain function, behavior, and mental health has attracted the attention of neuroscientists and psychiatrists. At the 29th International College of Neuropsychopharmacology (CINP) World Congress held in Vancouver, Canada, in June 2014, a group of experts presented the symposium, “Gut microbiota and brain function: Relevance to psychiatric disorders” to review the latest findings in how gut microbiota may play a role in brain function, behavior, and disease. The symposium covered a broad range of topics, including gut microbiota and neuroendocrine function, the influence of gut microbiota on behavior, probiotics as regulators of brain and behavior, and imaging the gut-brain axis in humans. This report provides an overview of these presentations.

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    Authors: Withers, James;

    This thesis presents a method for the segmentation of dual-channel structural magnetic resonance imaging (MRI) volumes of the human brain into four tissue classes. The state-of-the-art FSL FAST segmentation software (Zhang et al., 2001) is in widespread clinical use, and so it is considered a benchmark. A significant proportion of FAST’s errors has been shown to be localised to cortical sulci and blood vessels; this issue has driven the developments in this thesis, rather than any particular clinical demand. The original theme lies in preserving and even restoring these thin structures, poorly resolved in typical clinical MRI. Bright plate-shaped sulci and dark tubular vessels are best contrasted from the other tissues using the T2- and PD-weighted data, respectively. A contrasting tube detector algorithm (based on Frangi et al., 1998) was adapted to detect both structures, with smoothing (based on Westin and Knutsson, 2006) of an intermediate tensor representation to ensure smoothness and fuller coverage of the maps. The segmentation strategy required the MRI volumes to be upscaled to an artificial high resolution where a small partial volume label set would be valid and the segmentation process would be simplified. A resolution enhancement process (based on Salvado et al., 2006) was significantly modified to smooth homogeneous regions and sharpen their boundaries in dual-channel data. In addition, it was able to preserve the mapped thin structures’ intensities or restore them to pure tissue values. Finally, the segmentation phase employed a relaxation-based labelling optimisation process (based on Li et al., 1997) to improve accuracy, rather than more efficient greedy methods which are typically used. The thin structure location prior maps and the resolution-enhanced data also helped improve the labelling accuracy, particularly around sulci and vessels. Testing was performed on the aged LBC1936 clinical dataset and on younger brain volumes acquired at the SHEFC Brain Imaging Centre (Western General Hospital, Edinburgh, UK), as well as the BrainWeb phantom. Overall, the proposed methods rivalled and often improved segmentation accuracy compared to FAST, where the ground truth was produced by a radiologist using software designed for this project. The performance in pathological and atrophied brain volumes, and the differences with the original segmentation algorithm on which it was based (van Leemput et al., 2003), were also examined. Among the suggestions for future development include a soft labelling consensus formation framework to mitigate rater bias in the ground truth, and contour-based models of the brain parenchyma to provide additional structural constraints.

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    Authors: Jancke, L.; Staiger, J.F.; Schlaug, G.; Huang, Y.; +1 Authors

    Using high-resolution in vivo magnetic resonance morphometry we measured forebrain volume (FBV), midsagittal size of the corpus callosum (CC) and four CC subareas in 120 young and healthy adults (49 women, 71 men). We found moderate linear and quadratic correlations, indicating that the CC and all CC subareas increase with FBV both in men and women (multiple r2 ranging from 0.10 to 0.28). Allometric equations revealed that these increases were less than proportional to FBV (r2 ranging from 0.02 to 0.30). Absolute CC measurements, as well as CC subareas relative to total CC or FBV (the latter measures termed the CC ratios), were further analyzed with regard to possible effects of handedness, gender, or handedness by gender interaction. Contrary to previous reports, left-handers did not show larger CC measurements compared to right-handers. The only apparent influence of gender was on the CC ratios, which were larger in women. However, smaller brains had larger CC ratios which were mainly independent of gender, a result of the less than proportional increase of callosal size with FBV. We suggest that the previously described gender differences in CC anatomy may be better explained by an underlying effect of brain size, with larger brains having relatively smaller callosa. This lends empirical support to the hypothesis that brain size may be an important factor influencing interhemispheric connectivity and lateralization

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    Authors: Naranjo Ornedo, Valeriana; Morales, Sandra; Legaz-Aparicio, A.; Larrey-Ruiz, J.; +2 Authors
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    Authors: Noemi Passarello; Francesca Greco; Fabrizio Piras; Barbara Cordella; +4 Authors

    Contemporary neurosciences have shown that emotion, thought and language involve the functioning of connected brain areas, which allow the recognition and expression of one���s own feelings. The present pilot study was aimed at investigating the link among verbal expression of emotional experiences (assessed through the Toronto Structured Interview for Alexithymia - TSIA), the capacity of emotional regulation (assessed by means of the Attachment Style Questionnaire, the Emotion Regulation Questionnaire, and the Coping Orientation to Problems Experiences), the linguistic structure and symbolic representation of narration (assessed through the Text Mining Analyses), and brain area structures (by means of a 3-T high-resolution structural Magnetic Resonance Imaging). To this aim, nine (males=5) healthy adult subjects were interviewed by means of the TSIA and scored on psychological questionnaires. The cortical and subcortical structural measures were also evaluated. TSIA transcripts were then analysed by using a cluster analysis and, subsequently, a correspondence analysis, and the values of lexical factors were correlated with cortical and subcortical structural measures as well as with TSIA and psychological scores. Overall, the reciprocal relationships among the measures of neurobiological structures, the capacity of identifying, describing and regulating emotions, and the ability of translating the emotional experiences into verbal forms, allowed to identify a complex pattern of biopsychosocial aspects, getting light on referential processes characterizing the verbally and not-verbally express emotions. Psychology Hub, Vol. 38 No. 2 (2021)

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    Authors: Singh, Vishwajeet; Miyapuram, K. P.; Bapi, Raju S.;

    Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cognitive state. We consider the inverse problem of detecting the cognitive state of a human subject based on the fMRI data. We have explored classification techniques such as Gaussian Naive Bayes, k-Nearest Neighbour and Support Vector Machines. In order to reduce the very high dimensional fMRI data, we have used three feature selection strategies. Discriminating features and activity based features were used to select features for the problem of identifying the instantaneous cognitive state given a single fMRI scan and correlation based features were used when fMRI data from a single time interval was given. A case study of visuo-motor sequence learning is presented. The set of cognitive states we are interested in detecting are whether the subject has learnt a sequence, and if the subject is paying attention only towards the position or towards both the color and position of the visual stimuli. We have successfully used correlation based features to detect position-color related cognitive states with 80% accuracy and the cognitive states related to learning with 62.5% accuracy.

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    Authors: Morin, Alain;

    In this presentation I use recent empirical evidence and theoretical analyses concerning the importance of language in consciousness. Preliminary clinical and neuropsychological data indicate that inner speech is deeply linked to self-awareness; also, four hypotheses concerning the crucial role inner speech plays in self-focus are presented. I conclude by proposing that genuine consciousness (i.e., self-awareness) is impossible without language.

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  • Authors: A Pascarella and F Pitolli;

    Understanding brain function from magneto-electroencephalographic (M/EEG) measurements requires advanced mathematical and signal processing tools. Although the analysis of M/EEG data at sensors level sheds light on important brain mechanisms, full exploitation of the information contained in such brain data could be achieved by reconstructing the active neural sources from M/EEG measurements. This involves solving an ill-posed and ill-conditioned inverse problem in which not only the identification of the most suitable inversion method [1, 2] but also the calibration of the regularization parameters is of paramount importance. Once time series representing brain activity are available, a next step is to develop tools to extract meaningful information that characterizes brain activity [3, 4], for example, when the subject under study is affected by diseases that impair brain function. The mini-symposium brings together researchers from various disciplines who have developed methodologies that are being successfully used for the analysis of the M/EEG data, the solution of the underlying inverse problem and in the definition of brain fingerprint. The purpose is not only to present the latest research results in this area but also to create a fruitful environment for the development of new ideas.

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  • Authors: Pietrini, Pietro;
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    Authors: Laricchiuta, Daniela; Greco, Francesca; Piras, Fabrizio; Cordella, Barbara; +6 Authors
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Archivio della ricer...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Authors: Foster, Jane A.; Lyte, Mark; Meyer, Emeran; Cryan, John F.;

    There is a growing appreciation of the importance of gut microbiota to health and disease. This has been driven by advances in sequencing technology and recent findings demonstrating the important role of microbiota in common health disorders such as obesity. Moreover, the potential role of gut microbiota in influencing brain function, behavior, and mental health has attracted the attention of neuroscientists and psychiatrists. At the 29th International College of Neuropsychopharmacology (CINP) World Congress held in Vancouver, Canada, in June 2014, a group of experts presented the symposium, “Gut microbiota and brain function: Relevance to psychiatric disorders” to review the latest findings in how gut microbiota may play a role in brain function, behavior, and disease. The symposium covered a broad range of topics, including gut microbiota and neuroendocrine function, the influence of gut microbiota on behavior, probiotics as regulators of brain and behavior, and imaging the gut-brain axis in humans. This report provides an overview of these presentations.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Withers, James;

    This thesis presents a method for the segmentation of dual-channel structural magnetic resonance imaging (MRI) volumes of the human brain into four tissue classes. The state-of-the-art FSL FAST segmentation software (Zhang et al., 2001) is in widespread clinical use, and so it is considered a benchmark. A significant proportion of FAST’s errors has been shown to be localised to cortical sulci and blood vessels; this issue has driven the developments in this thesis, rather than any particular clinical demand. The original theme lies in preserving and even restoring these thin structures, poorly resolved in typical clinical MRI. Bright plate-shaped sulci and dark tubular vessels are best contrasted from the other tissues using the T2- and PD-weighted data, respectively. A contrasting tube detector algorithm (based on Frangi et al., 1998) was adapted to detect both structures, with smoothing (based on Westin and Knutsson, 2006) of an intermediate tensor representation to ensure smoothness and fuller coverage of the maps. The segmentation strategy required the MRI volumes to be upscaled to an artificial high resolution where a small partial volume label set would be valid and the segmentation process would be simplified. A resolution enhancement process (based on Salvado et al., 2006) was significantly modified to smooth homogeneous regions and sharpen their boundaries in dual-channel data. In addition, it was able to preserve the mapped thin structures’ intensities or restore them to pure tissue values. Finally, the segmentation phase employed a relaxation-based labelling optimisation process (based on Li et al., 1997) to improve accuracy, rather than more efficient greedy methods which are typically used. The thin structure location prior maps and the resolution-enhanced data also helped improve the labelling accuracy, particularly around sulci and vessels. Testing was performed on the aged LBC1936 clinical dataset and on younger brain volumes acquired at the SHEFC Brain Imaging Centre (Western General Hospital, Edinburgh, UK), as well as the BrainWeb phantom. Overall, the proposed methods rivalled and often improved segmentation accuracy compared to FAST, where the ground truth was produced by a radiologist using software designed for this project. The performance in pathological and atrophied brain volumes, and the differences with the original segmentation algorithm on which it was based (van Leemput et al., 2003), were also examined. Among the suggestions for future development include a soft labelling consensus formation framework to mitigate rater bias in the ground truth, and contour-based models of the brain parenchyma to provide additional structural constraints.

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    Authors: Jancke, L.; Staiger, J.F.; Schlaug, G.; Huang, Y.; +1 Authors

    Using high-resolution in vivo magnetic resonance morphometry we measured forebrain volume (FBV), midsagittal size of the corpus callosum (CC) and four CC subareas in 120 young and healthy adults (49 women, 71 men). We found moderate linear and quadratic correlations, indicating that the CC and all CC subareas increase with FBV both in men and women (multiple r2 ranging from 0.10 to 0.28). Allometric equations revealed that these increases were less than proportional to FBV (r2 ranging from 0.02 to 0.30). Absolute CC measurements, as well as CC subareas relative to total CC or FBV (the latter measures termed the CC ratios), were further analyzed with regard to possible effects of handedness, gender, or handedness by gender interaction. Contrary to previous reports, left-handers did not show larger CC measurements compared to right-handers. The only apparent influence of gender was on the CC ratios, which were larger in women. However, smaller brains had larger CC ratios which were mainly independent of gender, a result of the less than proportional increase of callosal size with FBV. We suggest that the previously described gender differences in CC anatomy may be better explained by an underlying effect of brain size, with larger brains having relatively smaller callosa. This lends empirical support to the hypothesis that brain size may be an important factor influencing interhemispheric connectivity and lateralization

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    Authors: Naranjo Ornedo, Valeriana; Morales, Sandra; Legaz-Aparicio, A.; Larrey-Ruiz, J.; +2 Authors
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    Authors: Noemi Passarello; Francesca Greco; Fabrizio Piras; Barbara Cordella; +4 Authors

    Contemporary neurosciences have shown that emotion, thought and language involve the functioning of connected brain areas, which allow the recognition and expression of one���s own feelings. The present pilot study was aimed at investigating the link among verbal expression of emotional experiences (assessed through the Toronto Structured Interview for Alexithymia - TSIA), the capacity of emotional regulation (assessed by means of the Attachment Style Questionnaire, the Emotion Regulation Questionnaire, and the Coping Orientation to Problems Experiences), the linguistic structure and symbolic representation of narration (assessed through the Text Mining Analyses), and brain area structures (by means of a 3-T high-resolution structural Magnetic Resonance Imaging). To this aim, nine (males=5) healthy adult subjects were interviewed by means of the TSIA and scored on psychological questionnaires. The cortical and subcortical structural measures were also evaluated. TSIA transcripts were then analysed by using a cluster analysis and, subsequently, a correspondence analysis, and the values of lexical factors were correlated with cortical and subcortical structural measures as well as with TSIA and psychological scores. Overall, the reciprocal relationships among the measures of neurobiological structures, the capacity of identifying, describing and regulating emotions, and the ability of translating the emotional experiences into verbal forms, allowed to identify a complex pattern of biopsychosocial aspects, getting light on referential processes characterizing the verbally and not-verbally express emotions. Psychology Hub, Vol. 38 No. 2 (2021)

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