scholarly journals Network component analysis reveals developmental trajectories of structural connectivity and specific alterations in autism spectrum disorder

2017 ◽  
Author(s):  
Gareth Ball ◽  
Richard Beare ◽  
Marc L. Seal

The structural organisation of the brain can be characterised as a hierarchical ensemble of segregated modules linked by densely interconnected hub regions that facilitate distributed functional interactions. Disturbances to this network may be an important marker of abnormal development. Recently, several neurodevelopmental disorders, including autism spectrum disorder (ASD), have been framed as disorders of connectivity but the full nature and timing of these disturbances remain unclear.In this study, we use non-negative matrix factorisation, a data-driven, multivariate approach, to model the structural network architecture of the brain as a set of superposed subnetworks, or network components.In an openly available dataset of 196 subjects scanned between 5 to 85 years we identify a set of robust and reliable subnetworks that develop in tandem with age and reflect both anatomically local and long-range, network hub connections. In a second experiment, we compare network components in a cohort of 51 high-functioning ASD adolescents to a group of age-matched controls. We identify a specific subnetwork representing an increase in local connection strength in the cingulate cortex in ASD (t=3.44, p<0.001).This work highlights possible long-term implications of alterations to the developmental trajectories of specific cortical subnetworks.

2020 ◽  
Vol 14 (2) ◽  
pp. 170-174
Author(s):  
Koichi Kawada ◽  
Nobuyuki Kuramoto ◽  
Seisuke Mimori

: Autism spectrum disorder (ASD) is a neurodevelopmental disease, and the number of patients has increased rapidly in recent years. The causes of ASD involve both genetic and environmental factors, but the details of causation have not yet been fully elucidated. Many reports have investigated genetic factors related to synapse formation, and alcohol and tobacco have been reported as environmental factors. This review focuses on endoplasmic reticulum stress and amino acid cycle abnormalities (particularly glutamine and glutamate) induced by many environmental factors. In the ASD model, since endoplasmic reticulum stress is high in the brain from before birth, it is clear that endoplasmic reticulum stress is involved in the development of ASD. On the other hand, one report states that excessive excitation of neurons is caused by the onset of ASD. The glutamine-glutamate cycle is performed between neurons and glial cells and controls the concentration of glutamate and GABA in the brain. These neurotransmitters are also known to control synapse formation and are important in constructing neural circuits. Theanine is a derivative of glutamine and a natural component of green tea. Theanine inhibits glutamine uptake in the glutamine-glutamate cycle via slc38a1 without affecting glutamate; therefore, we believe that theanine may prevent the onset of ASD by changing the balance of glutamine and glutamate in the brain.


Author(s):  
Emily Neuhaus

Autism spectrum disorder (ASD) is defined by deficits in social communication and interaction, and restricted and repetitive behaviors and interests. Although current diagnostic conceptualizations of ASD do not include emotional difficulties as core deficits, the disorder is associated with emotion dysregulation across the lifespan, with considerable implications for long-term psychological, social, and educational outcomes. The overarching goal of this chapter is to integrate existing knowledge of emotion dysregulation in ASD and identify areas for further investigation. The chapter reviews the prevalence and expressions of emotion dysregulation in ASD, discusses emerging theoretical models that frame emotion dysregulation as an inherent (rather than associated) feature of ASD, presents neurobiological findings and mechanisms related to emotion dysregulation in ASD, and identifies continuing controversies and resulting research priorities.


SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A11-A12
Author(s):  
Carolyn Jones ◽  
Randall Olson ◽  
Alex Chau ◽  
Peyton Wickham ◽  
Ryan Leriche ◽  
...  

Abstract Introduction Glutamate concentrations in the cortex fluctuate with the sleep wake cycle in both rodents and humans. Altered glutamatergic signaling, as well as the early life onset of sleep disturbances have been implicated in neurodevelopmental disorders such as autism spectrum disorder. In order to study how sleep modulates glutamate activity in brain regions relevant to social behavior and development, we disrupted sleep in the socially monogamous prairie vole (Microtus ochrogaster) rodent species and quantified markers of glutamate neurotransmission within the prefrontal cortex, an area of the brain responsible for advanced cognition and complex social behaviors. Methods Male and female prairie voles were sleep disrupted using an orbital shaker to deliver automated gentle cage agitation at continuous intervals. Sleep was measured using EEG/EMG signals and paired with real time glutamate concentrations in the prefrontal cortex using an amperometric glutamate biosensor. This same method of sleep disruption was applied early in development (postnatal days 14–21) and the long term effects on brain development were quantified by examining glutamatergic synapses in adulthood. Results Consistent with previous research in rats, glutamate concentration in the prefrontal cortex increased during periods of wake in the prairie vole. Sleep disruption using the orbital shaker method resulted in brief cortical arousals and reduced time in REM sleep. When applied during development, early life sleep disruption resulted in long-term changes in both pre- and post-synaptic components of glutamatergic synapses in the prairie vole prefrontal cortex including increased density of immature spines. Conclusion In the prairie vole rodent model, sleep disruption on an orbital shaker produces a sleep, behavioral, and neurological phenotype that mirrors aspects of autism spectrum disorder including altered features of excitatory neurotransmission within the prefrontal cortex. Studies using this method of sleep disruption combined with real time biosensors for excitatory neurotransmitters will enhance our understanding of modifiable risk factors, such as sleep, that contribute to the altered development of glutamatergic synapses in the brain and their relationship to social behavior. Support (if any) NSF #1926818, VA CDA #IK2 BX002712, Portland VA Research Foundation, NIH NHLBI 5T32HL083808-10, VA Merit Review #I01BX001643


2021 ◽  
Author(s):  
Pavithra Elumalai ◽  
Yasharth Yadav ◽  
Nitin Williams ◽  
Emil Saucan ◽  
Jürgen Jost ◽  
...  

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders that pose a significant global health burden. Measures from graph theory have been used to characterise ASD-related changes in resting-state fMRI functional connectivity networks (FCNs), but recently developed geometry-inspired measures have not been applied so far. In this study, we applied geometry-inspired graph Ricci curvatures to investigate ASD-related changes in resting-state fMRI FCNs. To do this, we applied Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and healthy controls (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We performed these comparisons at the brain-wide level as well as at the level of individual brain regions, and further, determined the behavioral relevance of region-specific differences with Neurosynth meta-analysis decoding. We found brain-wide ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures. For Forman-Ricci curvature, these differences were distributed across 83 of the 200 brain regions studied, and concentrated within the Default Mode, Somatomotor and Ventral Attention Network. Meta-analysis decoding identified the brain regions showing curvature differences as involved in social cognition, memory, language and movement. Notably, comparison with results from previous non-invasive stimulation (TMS/tDCS) experiments revealed that the set of brain regions showing curvature differences overlapped with the set of brain regions whose stimulation resulted in positive cognitive or behavioural outcomes in ASD patients. These results underscore the utility of geometry-inspired graph Ricci curvatures in characterising disease-related changes in ASD, and possibly, other neurodevelopmental disorders.


Author(s):  
Yael Dai ◽  
Inge-Marie Eigsti

This chapter reviews strengths and weaknesses in executive function (EF) domains, including inhibition, working memory, flexibility, fluency, and planning, in adolescents (age 13–19) with autism spectrum disorder (ASD). Given the dramatic developmental changes in the brain regions that support EF during the period of adolescence, it is critical to evaluate which EF abilities show a distinct profile during this period. As this chapter will demonstrate, youth with ASD show deficits across all domains of EF, particularly in complex tasks that include arbitrary instructions. We describe the fundamental measures for assessing skills in each domain and discuss limitations and future directions for research, as well as clinical implications of these findings for working with youth with ASD.


Author(s):  
Anna K. Prohl ◽  
◽  
Benoit Scherrer ◽  
Xavier Tomas-Fernandez ◽  
Peter E. Davis ◽  
...  

Abstract Background Autism spectrum disorder (ASD) is prevalent in tuberous sclerosis complex (TSC), occurring in approximately 50% of patients, and is hypothesized to be caused by disruption of neural circuits early in life. Tubers, or benign hamartomas distributed stochastically throughout the brain, are the most conspicuous of TSC neuropathology, but have not been consistently associated with ASD. Widespread neuropathology of the white matter, including deficits in myelination, neuronal migration, and axon formation, exist and may underlie ASD in TSC. We sought to identify the neural circuits associated with ASD in TSC by identifying white matter microstructural deficits in a prospectively recruited, longitudinally studied cohort of TSC infants. Methods TSC infants were recruited within their first year of life and longitudinally imaged at time of recruitment, 12 months of age, and at 24 months of age. Autism was diagnosed at 24 months of age with the ADOS-2. There were 108 subjects (62 TSC-ASD, 55% male; 46 TSC+ASD, 52% male) with at least one MRI and a 24-month ADOS, for a total of 187 MRI scans analyzed (109 TSC-ASD; 78 TSC+ASD). Diffusion tensor imaging properties of multiple white matter fiber bundles were sampled using a region of interest approach. Linear mixed effects modeling was performed to test the hypothesis that infants who develop ASD exhibit poor white matter microstructural integrity over the first 2 years of life compared to those who do not develop ASD. Results Subjects with TSC and ASD exhibited reduced fractional anisotropy in 9 of 17 white matter regions, sampled from the arcuate fasciculus, cingulum, corpus callosum, anterior limbs of the internal capsule, and the sagittal stratum, over the first 2 years of life compared to TSC subjects without ASD. Mean diffusivity trajectories did not differ between groups. Conclusions Underconnectivity across multiple white matter fiber bundles develops over the first 2 years of life in subjects with TSC and ASD. Future studies examining brain-behavior relationships are needed to determine how variation in the brain structure is associated with ASD symptoms.


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