scholarly journals Rest-fMRI Based Comparison Study between Autism Spectrum Disorder and Typically Control Using Graph Frequency Bands

2021 ◽  
Author(s):  
Alireza Talesh Jafadideh ◽  
Babak Mohammadzadeh Asl
Keyword(s):  
Autism Spectrum Disorder ◽  
Signal Processing ◽  
Default Mode Network ◽  
High Frequency ◽  
Low Frequency ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Default Mode ◽  
Frequency Bands ◽  
The Brain

AbstractGraph signal processing is a subset of signal processing enabling the analysis of functional magnetic resonance imaging (fMRI) data in brain topological domain. One of the most important and highly interested tool of GSP is graph Fourier transform (GFT) by which brain signals can be analyzed in different graph frequency bands. In this paper, the resting-state fMRI (rfMRI) data is analyzed using GFT tool in order to discover new knowledge about the autism spectrum disorder (ASD) and find features discriminating between ASD and typically control (TC) subjects. For ASD group, the signal concentration in both low and high frequency bands is decreased by increasing the age in most of the brain well-known networks. The ASD in comparison to TC shows less intention for changing the signal concentration level when the level is very low or very high. In graph low frequency band, increasing the age is along with increasing the segregation and integration of brain ROIs respectively for ASD and TC. Also, in this band, the brain ROIs integration of ASD is more than TC. By increasing the age, the auditory network of ASD subjects shows increasing segregation and integration in graph low and high frequency bands, respectively. The reduced segregation of default mode network in ASD is happened in graph middle and higher frequency bands. The functional connectivity analysis between low and high frequency signals shows that some of the high frequency ROIs have connections with all low frequency ROIs so that the most of these connections are dramatically and significantly different between ASD and TC. By analyzing the local vertex frequency spectrum (LVFS) of ASD and TC at different states, it is seen these groups show contradictory behaviors with respect to each other in brain default mode network in two states. The results of different scenarios at different graph frequency bands demonstrate that using functional and structural data together can provide powerful tool for recognizing the ASD or even other brain disorders.

scholarly journals Default mode network modulation by mentalizing in young adults with autism spectrum disorder or schizophrenia

2020 ◽  
Vol 27 ◽  
pp. 102343 ◽  
Author(s):  
Christopher J. Hyatt ◽  
Vince D. Calhoun ◽  
Brian Pittman ◽  
Silvia Corbera ◽  
Morris D. Bell ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Young Adults ◽  
Default Mode Network ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Adults With Autism ◽  
Default Mode ◽  
Young Adults With Autism

scholarly journals Default mode network in young male adults with autism spectrum disorder: Relationship with autism spectrum traits

2014 ◽  
Vol 94 (2) ◽  
pp. 212 ◽  
Author(s):  
Miinyoung Jung ◽  
Hirotaka Kosaka ◽  
Daisuke Saito ◽  
Makoto Ishitobi ◽  
Toshio Munesue ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Default Mode Network ◽  
Young Male ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Adults With Autism ◽  
Default Mode

scholarly journals Hypo- and hyper-connectivity in default mode network related to social impairment in tweens with autism spectrum disorder

2016 ◽  
Author(s):  
Wilma Matthysen ◽  
Daniele Marinazzo ◽  
Roma Siugzdaite
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Social Communication ◽  
Resting State ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Connectivity Pattern ◽  
Resting State Networks ◽  
Default Mode

Background. Autism spectrum disorder is a neurodevelopmental disorder, marked by impairment in social communication and restricted, repetitive patterns of behavior, interests, or activities. Accumulating data suggests that alterations in functional connectivity might contribute to these deficits. Whereas functional connectivity in resting state fMRI is expressed by several resting-state networks, for this study we examined several of them, but our particular interest was in the default mode network (DMN), given its age dependent alteration of functional connectivity and its relation to social communication. Methods. Since the studies investigating young children (6-8 years) with autism have found hypo-connectivity in DMN and studies on adolescents (12-16 years old) with autism have found hyper-connectivity in the DMN, we were interested in connectivity pattern during the age of 8 to 12, so we investigated the role of altered intrinsic connectivity in 16 children (mean age 9.75 ±1.6 years) with autism spectrum disorder compared to 16 typically developing controls in the DMN and other resting-state networks. Results. Results show that, compared to controls, the group with autism spectrum disorder showed signs of both hypo- and hyper-connectivity in different regions of the resting-state networks related to social communication. Conclusion. That suggests that transition period from childhood to adolescence carries the complexity of functional connectivity from both age groups. Regions that showed differences in functional connectivity were discussed in relation to social communication difficulties.

scholarly journals Altered resting perfusion and functional connectivity of default mode network in youth with autism spectrum disorder

2015 ◽  
Vol 5 (9) ◽  
Author(s):  
Kay Jann ◽  
Leanna M. Hernandez ◽  
Devora Beck‐Pancer ◽  
Rosemary McCarron ◽  
Robert X. Smith ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Default Mode

Beta-adrenergic antagonism modulates functional connectivity in the default mode network of individuals with and without autism spectrum disorder

2016 ◽  
Vol 11 (5) ◽  
pp. 1278-1289 ◽  
Author(s):  
John P. Hegarty ◽  
Bradley J. Ferguson ◽  
Rachel M. Zamzow ◽  
Landon J. Rohowetz ◽  
Jeffrey D. Johnson ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Beta Adrenergic ◽  
Default Mode

scholarly journals Alterations in Social Brain Network Topology at Rest in Children With Autism Spectrum Disorder

2022 ◽  
Author(s):  
Narae Yoon ◽  
Youngmin Huh ◽  
Hyekyoung Lee ◽  
Johanna Inhyang Kim ◽  
Jung Lee ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Network Topology ◽  
Default Mode Network ◽  
Autism Spectrum ◽  
Brain Network ◽  
Preschool Age ◽  
Spectrum Disorder ◽  
Typical Development ◽  
Default Mode

Abstract BackgroundUnderconnectivity in the resting brain is not consistent in autism spectrum disorder (ASD). However, it is known that the default mode network is mainly decreased in childhood ASD. This study investigated the brain network topology as the changes in the connection strength and network efficiency in childhood ASD, including the early developmental stages.MethodsIn this study, 31 ASD children aged 2–11 years were compared with 31 age and sex-matched children showing typical development. We explored the functional connectivity based on graph filtration by assessing the single linkage distance and global and nodal efficiencies using resting-state functional magnetic resonance imaging. The relationship between functional connectivity and clinical scores was also analyzed.ResultsUnderconnectivities within the posterior default mode network subregions and between the inferior parietal lobule and inferior frontal/superior temporal regions were observed in the ASD group. These areas significantly correlated with the clinical phenotypes. The global, local, and nodal network efficiencies were lower in children with ASD than in those with typical development. In the preschool-age children (2–6 years) with ASD, the anterior-posterior connectivity of the default mode network and cerebellar connectivity were reduced.ConclusionsThe observed topological reorganization, underconnectivity, and disrupted efficiency in the default mode network subregions and social function-related regions could be significant biomarkers of childhood ASD.

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