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fMRI Autism

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https://www.readbyqxmd.com/read/29736781/combination-of-rs-fmri-and-smri-data-to-discriminate-autism-spectrum-disorders-in-young-children-using-deep-belief-network
#1
Maryam Akhavan Aghdam, Arash Sharifi, Mir Mohsen Pedram
In recent years, the use of advanced magnetic resonance (MR) imaging methods such as functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) has recorded a great increase in neuropsychiatric disorders. Deep learning is a branch of machine learning that is increasingly being used for applications of medical image analysis such as computer-aided diagnosis. In a bid to classify and represent learning tasks, this study utilized one of the most powerful deep learning algorithms (deep belief network (DBN)) for the combination of data from Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) datasets...
May 7, 2018: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/29718384/neural-substrates-for-moral-judgments-of-psychological-versus-physical-harm
#2
Lily Tsoi, James A Dungan, Aleksandr Chakroff, Liane L Young
While we may think about harm as primarily being about physical injury, harm can also take the form of negative psychological impact. Using functional magnetic resonance imaging (fMRI), we examined the extent to which moral judgments of physical and psychological harms are processed similarly, focusing on brain regions implicated in mental state reasoning or theory of mind, a key cognitive process for moral judgment. First, univariate analyses reveal item-specific features that lead to greater recruitment of theory of mind regions for psychological harm versus physical harm...
April 28, 2018: Social Cognitive and Affective Neuroscience
https://www.readbyqxmd.com/read/29683406/influence-of-anxiety-and-alexithymia-on-brain-activations-associated-with-the-perception-of-others-pain-in-autism
#3
Amandine Lassalle, Nicole R Zürcher, Carlo A Porro, Francesca Benuzzi, Loyse Hippolyte, Eric Lemonnier, Jakob Åsberg Johnels, Nouchine Hadjikhani
The circumstances under which empathy is altered in ASD remain unclear, as previous studies did not systematically find differences in brain activation between ASD and controls in empathy-eliciting paradigms, and did not always monitor whether differences were primarily due to ASD "per se", or to conditions overlapping with ASD, such as alexithymia and anxiety. Here, we collected fMRI data from 47 participants (22 ASD) viewing pictures depicting hands and feet of unknown others in painful, disgusting, or neutral situations...
April 23, 2018: Social Neuroscience
https://www.readbyqxmd.com/read/29682095/brain-responses-underlying-anthropomorphism-agency-and-social-attribution-in-autism-spectrum-disorder
#4
Carla J Ammons, Constance F Doss, David Bala, Rajesh K Kana
Background: Theory of Mind (ToM), the ability to attribute mental states to oneself and others, is frequently impaired in Autism Spectrum Disorder (ASD) and may result from altered activation of social brain regions. Conversely, Typically Developing (TD) individuals overextend ToM and show a strong tendency to anthropomorphize and interpret biological motion in the environment. Less is known about how the degree of anthropomorphism influences intentional attribution and engagement of the social brain in ASD...
2018: Open Neuroimaging Journal
https://www.readbyqxmd.com/read/29667272/different-brain-networks-underlying-intelligence-in-autism-spectrum-disorders
#5
Emmanuel Peng Kiat Pua, Charles B Malpas, Stephen C Bowden, Marc L Seal
There has been sustained clinical and cognitive neuroscience research interest in how network correlates of brain-behavior relationships might be altered in Autism Spectrum Disorders (ASD) and other neurodevelopmental disorders. As previous work has mostly focused on adults, the nature of whole-brain connectivity networks underlying intelligence in pediatric cohorts with abnormal neurodevelopment requires further investigation. We used network-based statistics (NBS) to examine the association between resting-state functional Magnetic Resonance Imaging (fMRI) connectivity and fluid intelligence ability in male children (n = 50) with Autism Spectrum Disorders (ASD; M = 10...
April 17, 2018: Human Brain Mapping
https://www.readbyqxmd.com/read/29664902/a-general-prediction-model-for-the-detection-of-adhd-and-autism-using-structural-and-functional-mri
#6
Bhaskar Sen, Neil C Borle, Russell Greiner, Matthew R G Brown
This work presents a novel method for learning a model that can diagnose Attention Deficit Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional connectivity features obtained from 3-dimensional structural magnetic resonance imaging (MRI) and 4-dimensional resting-state functional magnetic resonance imaging (fMRI) scans of subjects. We explore a series of three learners: (1) The LeFMS learner first extracts features from the structural MRI images using the texture-based filters produced by a sparse autoencoder...
2018: PloS One
https://www.readbyqxmd.com/read/29657509/a-tensor-statistical-model-for-quantifying-dynamic-functional-connectivity
#7
Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Guorong Wu
Functional connectivity (FC) has been widely investigated in many imaging-based neuroscience and clinical studies. Since functional Magnetic Resonance Image (MRI) signal is just an indirect reflection of brain activity, it is difficult to accurately quantify the FC strength only based on signal correlation. To address this limitation, we propose a learning-based tensor model to derive high sensitivity and specificity connectome biomarkers at the individual level from resting-state fMRI images. First, we propose a learning-based approach to estimate the intrinsic functional connectivity...
June 2017: Information Processing in Medical Imaging: Proceedings of the ... Conference
https://www.readbyqxmd.com/read/29656107/statistical-testing-and-power-analysis-for-brain-wide-association-study
#8
Weikang Gong, Lin Wan, Wenlian Lu, Liang Ma, Fan Cheng, Wei Cheng, Stefan Grünewald, Jianfeng Feng
The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking...
April 5, 2018: Medical Image Analysis
https://www.readbyqxmd.com/read/29628271/functional-network-abnormalities-consistent-with-behavioral-profile-in-autism-spectrum-disorder
#9
René Besseling, Rolf Lamerichs, Britt Michels, Stephan Heunis, Anton de Louw, Anton Tijhuis, Jan Bergmans, Bert Aldenkamp
Autism spectrum disorder (ASD) is a neurodevelopmental disorder in which the severity of symptoms varies over subjects. The iCAPs model (innovation-driven co-activation patterns) is a recently developed spatio-temporal model to describe fMRI data. In this study, the iCAPs model was employed to find functional imaging biomarkers for ASD in resting-state fMRI data. MRI data from 125 ASD patients and 243 healthy controls was selected from the online ABIDE data repository. Following standard fMRI preprocessing steps, the iCAP patterns were fitted to the data to obtain network time series...
February 21, 2018: Psychiatry Research
https://www.readbyqxmd.com/read/29610102/bayesian-multiresolution-variable-selection-for-ultra-high-dimensional-neuroimaging-data
#10
Yize Zhao, Jian Kang, Qi Long
Ultra-high dimensional variable selection has become increasingly important in analysis of neuroimaging data. For example, in the Autism Brain Imaging Data Exchange (ABIDE) study, neuroscientists are interested in identifying important biomarkers for early detection of the autism spectrum disorder (ASD) using high resolution brain images that include hundreds of thousands voxels. However, most existing methods are not feasible for solving this problem due to their extensive computational costs. In this work, we propose a novel multiresolution variable selection procedure under a Bayesian probit regression framework...
March 2018: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/29587625/the-effects-of-intranasal-oxytocin-on-reward-circuitry-responses-in-children-with-autism-spectrum-disorder
#11
R K Greene, M Spanos, C Alderman, E Walsh, J Bizzell, M G Mosner, J L Kinard, G D Stuber, T Chandrasekhar, L C Politte, L Sikich, G S Dichter
BACKGROUND: Intranasal oxytocin (OT) has been shown to improve social communication functioning of individuals with autism spectrum disorder (ASD) and, thus, has received considerable interest as a potential ASD therapeutic agent. Although preclinical research indicates that OT modulates the functional output of the mesocorticolimbic dopamine system that processes rewards, no clinical brain imaging study to date has examined the effects of OT on this system using a reward processing paradigm...
March 27, 2018: Journal of Neurodevelopmental Disorders
https://www.readbyqxmd.com/read/29556179/characterization-of-noise-signatures-of-involuntary-head-motion-in-the-autism-brain-imaging-data-exchange-repository
#12
Carla Caballero, Sejal Mistry, Joe Vero, Elizabeth B Torres
The variability inherently present in biophysical data is partly contributed by disparate sampling resolutions across instrumentations. This poses a potential problem for statistical inference using pooled data in open access repositories. Such repositories combine data collected from multiple research sites using variable sampling resolutions. One example is the Autism Brain Imaging Data Exchange repository containing thousands of imaging and demographic records from participants in the spectrum of autism and age-matched neurotypical controls...
2018: Frontiers in Integrative Neuroscience
https://www.readbyqxmd.com/read/29554540/cortical-responses-to-dynamic-emotional-facial-expressions-generalize-across-stimuli-and-are-sensitive-to-task-relevance-in-adults-with-and-without-autism
#13
Dorit Kliemann, Hilary Richardson, Stefano Anzellotti, Dima Ayyash, Amanda J Haskins, John D E Gabrieli, Rebecca R Saxe
Individuals with Autism Spectrum Disorders (ASD) report difficulties extracting meaningful information from dynamic and complex social cues, like facial expressions. The nature and mechanisms of these difficulties remain unclear. Here we tested whether that difficulty can be traced to the pattern of activity in "social brain" regions, when viewing dynamic facial expressions. In two studies, adult participants (male and female) watched brief videos of a range of positive and negative facial expressions, while undergoing functional magnetic resonance imaging (Study 1: ASD n = 16, control n = 21; Study 2: ASD n = 22, control n = 30)...
February 21, 2018: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/29541439/network-specific-sex-differentiation-of-intrinsic-brain-function-in-males-with-autism
#14
Dorothea L Floris, Meng-Chuan Lai, Tanmay Nath, Michael P Milham, Adriana Di Martino
Background: The male predominance in the prevalence of autism spectrum disorder (ASD) has motivated research on sex differentiation in ASD. Multiple sources of evidence have suggested a neurophenotypic convergence of ASD-related characteristics and typical sex differences. Two existing, albeit competing, models provide predictions on such neurophenotypic convergence. These two models are testable with neuroimaging. Specifically, the Extreme Male Brain (EMB) model predicts that ASD is associated with enhanced brain maleness in both males and females with ASD (i...
2018: Molecular Autism
https://www.readbyqxmd.com/read/29487793/differences-in-atypical-resting-state-effective-connectivity-distinguish-autism-from-schizophrenia
#15
Dana Mastrovito, Catherine Hanson, Stephen Jose Hanson
Autism and schizophrenia share overlapping genetic etiology, common changes in brain structure and common cognitive deficits. A number of studies using resting state fMRI have shown that machine learning algorithms can distinguish between healthy controls and individuals diagnosed with either autism spectrum disorder or schizophrenia. However, it has not yet been determined whether machine learning algorithms can be used to distinguish between the two disorders. Using a linear support vector machine, we identify features that are most diagnostic for each disorder and successfully use them to classify an independent cohort of subjects...
2018: NeuroImage: Clinical
https://www.readbyqxmd.com/read/29487516/perceived-gaze-direction-modulates-neural-processing-of-prosocial-decision-making
#16
Delin Sun, Robin Shao, Zhaoxin Wang, Tatia M C Lee
Gaze direction is a common social cue implying potential interpersonal interaction. However, little is known about the neural processing of social decision making influenced by perceived gaze direction. Here, we employed functional magnetic resonance imaging (fMRI) method to investigate 27 females when they were engaging in an economic exchange game task during which photos of direct or averted eye gaze were shown. We found that, when averted but not direct gaze was presented, prosocial vs. selfish choices were associated with stronger activations in the right superior temporal gyrus (STG) as well as larger functional couplings between right STG and the posterior cingulate cortex (PCC)...
2018: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/29484255/brain-resting-state-networks-in-adolescents-with-high-functioning-autism-analysis-of-spatial-connectivity-and-temporal-neurodynamics
#17
Antoine Bernas, Evelien M Barendse, Albert P Aldenkamp, Walter H Backes, Paul A M Hofman, Marc P H Hendriks, Roy P C Kessels, Frans M J Willems, Peter H N de With, Svitlana Zinger, Jacobus F A Jansen
Introduction: Autism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using functional magnetic resonance imaging (fMRI). Even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic, or resting-state, connectivity. Global default connectivity in individuals with autism versus controls is not well characterized, especially for a high-functioning young population...
February 2018: Brain and Behavior
https://www.readbyqxmd.com/read/29483346/the-functional-highly-sensitive-brain-a-review-of-the-brain-circuits-underlying-sensory-processing-sensitivity-and-seemingly-related-disorders
#18
REVIEW
Bianca Acevedo, Elaine Aron, Sarah Pospos, Dana Jessen
During the past decade, research on the biological basis of sensory processing sensitivity (SPS)-a genetically based trait associated with greater sensitivity and responsivity to environmental and social stimuli-has burgeoned. As researchers try to characterize this trait, it is still unclear how SPS is distinct from seemingly related clinical disorders that have overlapping symptoms, such as sensitivity to the environment and hyper-responsiveness to incoming stimuli. Thus, in this review, we compare the neural regions implicated in SPS with those found in fMRI studies of-Autism Spectrum Disorder (ASD), Schizophrenia (SZ) and Post-Traumatic Stress Disorder (PTSD) to elucidate the neural markers and cardinal features of SPS versus these seemingly related clinical disorders...
April 19, 2018: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
https://www.readbyqxmd.com/read/29467790/classification-of-autism-spectrum-disorder-using-random-support-vector-machine-cluster
#19
Xia-An Bi, Yang Wang, Qing Shu, Qi Sun, Qian Xu
Autism spectrum disorder (ASD) is mainly reflected in the communication and language barriers, difficulties in social communication, and it is a kind of neurological developmental disorder. Most researches have used the machine learning method to classify patients and normal controls, among which support vector machines (SVM) are widely employed. But the classification accuracy of SVM is usually low, due to the usage of a single SVM as classifier. Thus, we used multiple SVMs to classify ASD patients and typical controls (TC)...
2018: Frontiers in Genetics
https://www.readbyqxmd.com/read/29455363/predicting-autism-spectrum-disorder-using-domain-adaptive-cross-site-evaluation
#20
Runa Bhaumik, Ashish Pradhan, Soptik Das, Dulal K Bhaumik
The advances in neuroimaging methods reveal that resting-state functional fMRI (rs-fMRI) connectivity measures can be potential diagnostic biomarkers for autism spectrum disorder (ASD). Recent data sharing projects help us replicating the robustness of these biomarkers in different acquisition conditions or preprocessing steps across larger numbers of individuals or sites. It is necessary to validate the previous results by using data from multiple sites by diminishing the site variations. We investigated partial least square regression (PLS), a domain adaptive method to adjust the effects of multicenter acquisition...
February 17, 2018: Neuroinformatics
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