keyword
https://read.qxmd.com/read/33088275/neurocognitive-mechanisms-underlying-social-atypicalities-in-autism-weak-amygdala-s-emotional-modulation-hypothesis
#1
Wataru Sato, Shota Uono, Takanori Kochiyama
Autism spectrum disorder (ASD) is a neurodevelopmental condition associated with atypicalities in social interaction. Although psychological and neuroimaging studies have revealed divergent impairments in psychological processes (e.g., emotion and perception) and neural activity (e.g., amygdala, superior temporal sulcus, and inferior frontal gyrus) related to the processing of social stimuli, it remains difficult to integrate these findings. In an effort to resolve this issue, we review our psychological and functional magnetic resonance imaging (fMRI) findings and present a hypothetical neurocognitive model...
2020: Frontiers in Psychiatry
https://read.qxmd.com/read/33086634/a-three-stage-teacher-student-neural-networks-and-sequential-feed-forward-selection-based-feature-selection-approach-for-the-classification-of-autism-spectrum-disorder
#2
Naseer Ahmed Khan, Samer Abdulateef Waheeb, Atif Riaz, Xuequn Shang
Autism disorder, generally known as Autism Spectrum Disorder (ASD) is a brain disorder characterized by lack of communication skills, social aloofness and repetitions in the actions in the patients, which is affecting millions of the people across the globe. Accurate identification of autistic patients is considered a challenging task in the domain of brain disorder science. To address this problem, we have proposed a three-stage feature selection approach for the classification of ASD on the preprocessed Autism Brain Imaging Data Exchange (ABIDE) rs-fMRI Dataset...
October 19, 2020: Brain Sciences
https://read.qxmd.com/read/33074746/diagnosis-of-autism-spectrum-disorder-based-on-functional-brain-networks-with-deep-learning
#3
Wutao Yin, Sakib Mostafa, Fang-Xiang Wu
Autism spectrum disorder (ASD) is a neurological and developmental disorder. Traditional diagnosis of ASD is typically performed through the observation of behaviors and interview of a patient. However, these diagnosis methods are time-consuming and can be misleading sometimes. Integrating machine learning algorithms with neuroimages, a diagnosis method, can possibly be established to detect ASD subjects from typical control subjects. In this study, we develop deep learning methods for diagnosis of ASD from functional brain networks constructed with brain functional magnetic resonance imaging (fMRI) data...
October 19, 2020: Journal of Computational Biology
https://read.qxmd.com/read/33072887/disrupted-eye-gaze-perception-as-a-biobehavioral-marker-of-social-dysfunction-an-rdoc-investigation
#4
Ivy F Tso, Carly A Lasagna, Kate D Fitzgerald, Costanza Colombi, Chandra Sripada, Scott J Peltier, Timothy D Johnson, Katharine N Thakkar
Social dysfunction is an intractable problem in a wide spectrum of psychiatric illnesses, undermining patients' capacities for employment, independent living, and maintaining meaningful relationships. Identifying common markers of social impairment across disorders and understanding their mechanisms are prerequisites to developing targeted neurobiological treatments that can be applied productively across diagnoses and illness stages to improve functional outcome. This project focuses on eye gaze perception, the ability to accurately and efficiently discriminate others' gaze direction, as a potential biomarker of social functioning that cuts across psychiatric diagnoses...
2020: Journal of Psychiatry and Brain Science
https://read.qxmd.com/read/33018595/metaheuristic-spatial-transformation-mst-for-accurate-detection-of-attention-deficit-hyperactivity-disorder-adhd-using-rs-fmri
#5
Abhay M S Aradhya, Suresh Sundaram, Mahardhika Pratama
Accurate detection of neuro-psychological disorders such as Attention Deficit Hyperactivity Disorder (ADHD) using resting state functional Magnetic Resonance Imaging (rs-fMRI) is challenging due to high dimensionality of input features, low inter-class separability, small sample size and high intra-class variability. For automatic diagnosis of ADHD and autism, spatial transformation methods have gained significance and have achieved improved classification performance. However, they are not reliable due to lack of generalization in dataset like ADHD with high variance and small sample size...
July 2020: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://read.qxmd.com/read/33016005/frontoparietal-network-in-executive-functioning-in-autism-spectrum-disorder
#6
Kaitlyn E May, Rajesh K Kana
Higher cognitive functions in autism spectrum disorder (ASD) are characterized by impairments in executive functions (EF). While some research attributes this to an overreliance of the prefrontal cortex (PFC), others demonstrate poor recruitment of the PFC in individuals with ASD. In order to assess the emerging consensus across neuroimaging studies of EF in ASD, the current study used a coordinate-based activation likelihood estimation (ALE) analysis of 16 functional magnetic resonance imaging (fMRI) studies, resulting in a meta-analysis of data from 739 participants (356 ASD, 383 typically developing [TD] individuals) ranging from 7 to 52 years of age...
October 5, 2020: Autism Research: Official Journal of the International Society for Autism Research
https://read.qxmd.com/read/32961402/neuromark-an-automated-and-adaptive-ica-based-pipeline-to-identify-reproducible-fmri-markers-of-brain-disorders
#7
Yuhui Du, Zening Fu, Jing Sui, Shuang Gao, Ying Xing, Dongdong Lin, Mustafa Salman, Anees Abrol, Md Abdur Rahaman, Jiayu Chen, L Elliot Hong, Peter Kochunov, Elizabeth A Osuch, Vince D Calhoun
Many mental illnesses share overlapping or similar clinical symptoms, confounding the diagnosis. It is important to systematically characterize the degree to which unique and similar changing patterns are reflective of brain disorders. Increasing sharing initiatives on neuroimaging data have provided unprecedented opportunities to study brain disorders. However, it is still an open question on replicating and translating findings across studies. Standardized approaches for capturing reproducible and comparable imaging markers are greatly needed...
August 11, 2020: NeuroImage: Clinical
https://read.qxmd.com/read/32949710/dynamic-time-warping-outperforms-pearson-correlation-in-detecting-atypical-functional-connectivity-in-autism-spectrum-disorders
#8
A C Linke, L E Mash, C H Fong, M K Kinnear, J S Kohli, M Wilkinson, R Tung, R J Jao Keehn, R A Carper, I Fishman, R-A Müller
Resting state fMRI (rsfMRI) is frequently used to study brain function, including in clinical populations. Similarity of blood-oxygen-level-dependent (BOLD) fluctuations during rsfMRI between brain regions is thought to reflect intrinsic functional connectivity (FC), potentially due to history of coactivation. To quantify similarity, studies have almost exclusively relied on Pearson correlation, which assumes linearity and can therefore underestimate FC if the hemodynamic response function differs regionally or there is BOLD signal lag between timeseries...
September 16, 2020: NeuroImage
https://read.qxmd.com/read/32935455/reduced-language-lateralization-in-autism-and-the-broader-autism-phenotype-as-assessed-with-robust-individual-subjects-analyses
#9
Olessia Jouravlev, Alexander J E Kell, Zachary Mineroff, Amanda J Haskins, Dima Ayyash, Nancy Kanwisher, Evelina Fedorenko
One of the few replicated functional brain differences between individuals with autism spectrum disorders (ASD) and neurotypical (NT) controls is reduced language lateralization. However, most prior reports relied on comparisons of group-level activation maps or functional markers that had not been validated at the individual-subject level, and/or used tasks that do not isolate language processing from other cognitive processes, complicating interpretation. Furthermore, few prior studies have examined functional responses in other brain networks, as needed to determine the spatial selectivity of the effect...
September 15, 2020: Autism Research: Official Journal of the International Society for Autism Research
https://read.qxmd.com/read/32891039/evoked-and-intrinsic-brain-network-dynamics-in-children-with-autism-spectrum-disorder
#10
Lauren Kupis, Celia Romero, Bryce Dirks, Stephanie Hoang, Meaghan V Parladé, Amy L Beaumont, Sandra M Cardona, Michael Alessandri, Catie Chang, Jason S Nomi, Lucina Q Uddin
OBJECTIVE: Brain dynamics underlie flexible cognition and behavior, yet little is known regarding this relationship in autism spectrum disorder (ASD). We examined time-varying changes in functional co-activation patterns (CAPs) across rest and task-evoked brain states to characterize differences between children with ASD and typically developing (TD) children and identify relationships with severity of social behaviors and restricted and repetitive behaviors. METHOD: 17 children with ASD and 27 TD children ages 7-12 completed a resting-state fMRI scan and four runs of a non-cued attention switching task...
August 25, 2020: NeuroImage: Clinical
https://read.qxmd.com/read/32885115/effects-of-spatial-smoothing-on-group-level-differences-in-functional-brain-networks
#11
Ana María Triana, Enrico Glerean, Jari Saramäki, Onerva Korhonen
Brain connectivity with functional magnetic resonance imaging (fMRI) is a popular approach for detecting differences between healthy and clinical populations. Before creating a functional brain network, the fMRI time series must undergo several preprocessing steps to control for artifacts and to improve data quality. However, preprocessing may affect the results in an undesirable way. Spatial smoothing, for example, is known to alter functional network structure. Yet, its effects on group-level network differences remain unknown...
2020: Network Neuroscience
https://read.qxmd.com/read/32863321/imaging-the-neural-circuit-basis-of-social-behavior-insights-from-mouse-and-human-studies
#12
Isamu Miura, Eric T N Overton, Nobuhiro Nakai, Takakazu Kawamata, Masaaki Sato, Toru Takumi
Social behavior includes a variety of behaviors that are expressed between two or more individuals. In humans, impairment of social function (i.e., social behavior and social cognition) is seen in neurodevelopmental and neurological disorders including autism spectrum disorders (ASDs) and stroke, respectively. In basic neuroscience research, fluorescence monitoring of neural activity, such as immediate early gene (IEG)-mediated whole-brain mapping, fiber photometry, and calcium imaging using a miniaturized head-mounted microscope or a two-photon microscope, and non-fluorescence imaging such as functional magnetic resonance imaging (fMRI) are increasingly used to measure the activity of many neurons and multiple brain areas in animals during social behavior...
September 15, 2020: Neurologia Medico-chirurgica
https://read.qxmd.com/read/32848528/the-potential-of-functional-near-infrared-spectroscopy-based-neurofeedback-a-systematic-review-and-recommendations-for-best-practice
#13
Simon H Kohl, David M A Mehler, Michael Lührs, Robert T Thibault, Kerstin Konrad, Bettina Sorger
Background: The effects of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI)-neurofeedback on brain activation and behaviors have been studied extensively in the past. More recently, researchers have begun to investigate the effects of functional near-infrared spectroscopy-based neurofeedback (fNIRS-neurofeedback). FNIRS is a functional neuroimaging technique based on brain hemodynamics, which is easy to use, portable, inexpensive, and has reduced sensitivity to movement artifacts...
2020: Frontiers in Neuroscience
https://read.qxmd.com/read/32793004/calcium-imaging-in-drug-discovery-for-psychiatric-disorders
#14
REVIEW
Saurav Seshadri, Daniel J Hoeppner, Katsunori Tajinda
The past 5 years have seen a sharp increase in the number of studies using calcium imaging in behaving rodents. These studies have helped identify important roles for individual cells, brain regions, and circuits in some of the core behavioral phenotypes of psychiatric disorders, such as schizophrenia and autism, and have characterized network dysfunction in well-established models of these disorders. Since rescuing clinically relevant behavioral deficits in disease model mice remains a foundation of preclinical CNS research, these studies have the potential to inform new therapeutic approaches targeting specific cell types or projections, or perhaps most importantly, the network-level context in which neurons function...
2020: Frontiers in Psychiatry
https://read.qxmd.com/read/32791440/classification-of-adhd-with-fmri-data-and-multi-objective-optimization
#15
Lizhen Shao, Yang You, Haipeng Du, Dongmei Fu
BACKGROUND AND OBJECTIVE: Dataset imbalance is an important problem in neuroimaging. Imbalanced datasets would cause the performance degradation of a classifier by utilizing imbalanced learning, which tends to overfocus on the majority class. In this paper, we consider an imbalanced neuroimaging classification problem, namely, classification of attention deficit hyperactivity disorder (ADHD) using resting-state functional magnetic resonance imaging. METHODS: We propose a multi-objective classification scheme based on support vector machine (SVM)...
August 7, 2020: Computer Methods and Programs in Biomedicine
https://read.qxmd.com/read/32762276/a-preliminary-study-of-atypical-cortical-change-ability-of-dynamic-whole-brain-functional-connectivity-in-autism-spectrum-disorder
#16
Bo Chen
OBJECTIVES: Designing new objectively diagnostic methods of autism spectrum disorder (ASD) are burning questions. Dynamic functional connectivity (DFC) methodology based on fMRI data are an effective lever to investigate changeability evolution of signal synchronization in macroscopic neural activity patterns. METHODS: Embracing the network dynamics concepts, this paper introduces changeability index ([Formula: see text]-score)which is focused on time-varying aspects of FCs, and develops a new framework for researching the roots of ASD brains at resting states in holism significance...
August 18, 2020: International Journal of Neuroscience
https://read.qxmd.com/read/32750917/single-volume-image-generator-and-deep-learning-based-asd-classification
#17
Md Rishad Ahmed, Yuan Zhang, Yi Liu, Hongen Liao
Autism spectrum disorder (ASD) is an intricate neuropsychiatric brain disorder characterized by social deficits and repetitive behaviors. Deep learning approaches have been applied in clinical or behavioral identification of ASD; most erstwhile models are inadequate in their capacity to exploit the data richness. On the other hand, classification techniques often solely rely on region-based summary and/or functional connectivity analysis of functional magnetic resonance imaging (fMRI). Besides, biomedical data modeling to analyze big data related to ASD is still perplexing due to its complexity and heterogeneity...
May 29, 2020: IEEE Journal of Biomedical and Health Informatics
https://read.qxmd.com/read/32746967/intrinsic-excitation-inhibition-imbalance-affects-medial-prefrontal-cortex-differently-in-autistic-men-versus-women
#18
Stavros Trakoshis, Pablo Martínez-Cañada, Federico Rocchi, Carola Canella, Wonsang You, Bhismadev Chakrabarti, Amber Nv Ruigrok, Edward T Bullmore, John Suckling, Marija Markicevic, Valerio Zerbi, Anthony J Bailey, Simon Baron-Cohen, Patrick F Bolton, Edward T Bullmore, Sarah Carrington, Marco Catani, Bhismadev Chakrabarti, Michael C Craig, Eileen M Daly, Sean Cl Deoni, Christine Ecker, Francesca Happé, Julian Henty, Peter Jezzard, Patrick Johnston, Derek K Jones, Meng-Chuan Lai, Michael V Lombardo, Anya Madden, Diane Mullins, Clodagh M Murphy, Declan Gm Murphy, Greg Pasco, Amber Nv Ruigrok, Susan A Sadek, Debbie Spain, Rose Stewart, John Suckling, Sally J Wheelwright, Steven C Williams, Simon Baron-Cohen, Alessandro Gozzi, Meng-Chuan Lai, Stefano Panzeri, Michael V Lombardo
Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio...
August 4, 2020: ELife
https://read.qxmd.com/read/32739707/the-role-of-the-mtg-in-negative-emotional-processing-in-young-adults-with-autistic-like-traits-a-fmri-task-study
#19
Yaxu Yu, Xiaoqin Wang, Junyi Yang, Jiang Qiu
BACKGROUND: Few previous studies explored negative emotion processing in autistic-like traits people using task-based fMRI. In this study, we applied task fMRI to determine the relationship between negative emotion processing and social skill within autistic-like traits people. aimed to find which brain areas specificity play a key role in emotional processing. METHODS: 106 of Chinese individuals measured with AQ. Then applied emotion regulation task to explore the difference in brain activation and functional connectivity in individuals with autistic traits...
July 14, 2020: Journal of Affective Disorders
https://read.qxmd.com/read/32730918/diagnostic-classification-of-autism-using-resting-state-fmri-data-improves-with-full-correlation-functional-brain-connectivity-compared-to-partial-correlation
#20
Jac Fredo Agastinose Ronicko, John Thomas, Prasanth Thangavel, Vineetha Koneru, Georg Langs, Justin Dauwels
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disability with altered connectivity in brain networks. NEW METHOD: In this study, brain connections in Resting-state functional Magnetic Resonance Imaging (Rs-fMRI) of ASD and Typical Developing (TD) are analyzed by partial and full correlation methods such as Gaussian Graphical Least Absolute Shrinkage and Selection Operator (GLASSO), Max-Det Matrix Completion (MDMC), and Pearson Correlation Co-Efficient (PCCE)...
July 27, 2020: Journal of Neuroscience Methods
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