Altered Temporospatial Variability of Dynamic Amplitude of Low-Frequency Fluctuation in Children with Autism Spectrum Disorder.
Sliding-window resting scans reveal moving, not just lower, brain-wave strength in autism, especially in the default-mode network.
01Research in Context
What this study did
The team scanned kids with and without autism while they lay still. They tracked how the strength of super-slow brain waves changed every few seconds.
The measure is called dynamic ALFF. It shows which areas turn up and down in a resting brain.
What they found
Kids with autism showed a unique time map of brain activity. The default-mode network, the day-dream circuit, had the clearest differences.
Stronger odd patterns in this network matched higher symptom scores.
How this fits with other research
Karavallil Achuthan et al. (2023) also looked at ALFF, but they saw less activity in autism. The new study adds the time lens, so the drop they saw is now seen as shifting, not simply low.
He et al. (2018) first showed the DMN is less flexible in young kids with autism. Guo et al. (2024) echo that point and tie the wobble size to day-to-day symptoms.
Lu et al. (2024) went further by splitting boys and girls. They found sex-only dynamic signatures in the ACC, reminding us that the broad picture may hide sub-groups.
Why it matters
You now have a cheap, task-free marker: resting DMN dynamic ALFF. If future kits give real-time numbers, you could chart symptom change without long tests. Until then, keep scans in mind when a child shows puzzling social swings—brain variability may be part of the story you share with parents.
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02At a glance
03Original abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder with altered brain activity. However, little is known about the integrated temporospatial variation of dynamic spontaneous brain activity in ASD. In the present study, resting-state functional magnetic resonance imaging data were analyzed for 105 ASD and 102 demographically-matched typically developmental controls (TC) children obtained from the Autism Brain Imaging Data Exchange database. Using the sliding-window approach, temporal, spatial, and temporospatial variability of dynamic amplitude of low-frequency fluctuation (tvALFF, svALFF, and tsvALFF) were calculated for each participant. Group-comparisons were further performed at global, network, and brain region levels to quantify differences between ASD and TC groups. The relationship between temporospatial dynamic amplitude of low-frequency fluctuation variation alterations and clinical symptoms of ASD was finally explored by a support vector regression model. Relative to TC, we found enhanced tvALFF in visual network (Vis), somatomotor network (SMT), and salience/ventral attention network (SVA) of ASD, and weakened tvALFF in dorsal attention network (DAN) of ASD. Besides, ASD showed decreased svALFF in Vis, SVA, and limbic network (Limbic), and increased svALFF in DAN and default mode network (DMN). Elevated tsvALFF was found in the Vis, SMT, and DMN of ASD. More importantly, the altered tsvALFF from the DMN can predict the symptom severity of ASD. These findings demonstrate altered temporospatial dynamics of the spontaneous brain activity in ASD and provide novel insights into the neural mechanism underlying ASD.
Journal of autism and developmental disorders, 2024 · doi:10.3389/fpsyt.2019.00680