695 research outputs found
CBMAT: a MATLAB toolbox for data preparation and post hoc analyses in neuroimaging meta-analyses
Activation Likelihood Estimation meta-analysis of brain correlates of placebo analgesia in human experimental pain
Autism Spectrum Disorder Diagnosis Using Sparse Graph Embedding of Morphological Brain Networks
Exploring the selective gray matter profile of autism spectrum disorder through Bayes Factor Modeling
INTRODUCTION: Despite decades of brain MRI research demonstrating atypical neuroanatomical substrate in patients with autism spectrum disorder (ASD), it remains unclear whether and to what extent disorder-selective neuroanatomical abnormalities occur in this spectrum. This, and the fact that multiple brain disorders report a common neuroanatomical substrate, makes transference and the application of neuroimaging findings into the clinical setting an open challenge. OBJECTIVES: To investigate the selective neuroanatomical alteration profile of the ASD brain, we employed a meta-analytic, data-driven, and reverse inference-based approach (i.e.; Bayes fACtor mOdeliNg). METHODS: Eligible voxel-based morphometry data were extracted by a standardized search on BrainMap and MEDLINE databases (849 published experiments, 131 brain disorders, 22747 clinical subjects, 16572 x-y-z coordinates). Two distinct datasets were generated: the ASD dataset, composed of ASD-related data; and the non-ASD dataset, composed of all other clinical conditions data. Starting from the two unthresholded activation likelihood estimation (ALE) maps, the calculus of the Bayes fACtor mOdeliNg was performed. This allowed us to obtain posterior probability distributions on the evidence of brain alteration specificity in ASD. RESULTS: We revealed both cortical and cerebellar areas of neuroanatomical alteration selectivity in ASD. Eight clusters showed a selectivity value ≥ 90%, namely the bilateral precuneus, the right inferior occipital gyrus, left lobule IX, left Crus II, right Crus I, and the right lobule VIIIA (Fig. 1). CONCLUSIONS: The identification of this neuroanatomical pattern provides new insights into the complex pathophysiology of ASD, opening attractive prospects for future neuroimaging-based interventions. DISCLOSURE: No significant relationships
One-Dimensional ZnO/Gold Junction for Simultaneous and Versatile Multisensing Measurements
The sensing capabilities of zinc oxide nano/micro-structures have been widely investigated and these structures are frequently used in the fabrication of cutting-edge sensors. However, to date, little attention has been paid to the multi-sensing abilities of this material. In this work, we present an efficient multisensor based on a single zinc oxide microwire/gold junction. The device is able to detect in real time three different stimuli, UV-VIS light, temperature and pH variations. This is thanks to three properties of zinc oxide its photoconductive response, pyroelectricity and surface functionalization with amino-propyl groups, respectively. The three stimuli can be detected either simultaneously or in a sequence/random order. A specific mathematical tool was also developed, together with a design of experiments (DoE), to predict the performances of the sensor. Our micro-device allows reliable and versatile real-time measurements of UV-VIS light, temperature and pH variations. Therefore, it shows great potential for use in the field of sensing for living cell cultures
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