On the Spectrum

Chapter 5
Age- and sex-related associations with time spent in dynamic states
Next, we explored how dynamic connectivity properties such as mean dwell time (MDT) and
fraction of time spent in dynamic states (FT) change as functions of age and sex (Figure 5).
Here, for each of the dynamic FNC states, we computed the MDT (how long an individual
spends in a given state on average) and FT (total time spent in a given state). The equations
for MDT and FT are given in the online method section. We found that older children showed
higher MDT and FT in the globally modularized dFNC state, or State-1. Conversely, younger
subjects showed higher MDT and FT in the globally disconnected state, or State-2. We also
investigated the sex-related differences in MDT and FT in the dynamic states. We found that
in the disconnected state (State-2), boys showed higher FT, whereas in DMN-modularized
state (State-3), girls showed higher MDT and FT. The other two dynamic states, the globally
modularized state (State-1) and the globally hyperconnected state (State-4) showed trendlevel
sex effects, where boys showed higher MDT and FT compared to girls in States-1 and -4.
Characterization of dynamic connectopathy (chronnectopathy) in autistic traits and
children with ASD
In addition to characterizing static and dynamic FNCs in typical development, we also studied
the chronnectopathy, or disruption of the typical dynamic connectivity patterns, in children
with autistic traits. We assessed autistic traits using the Social Responsiveness Scale (SRS)
(Constantino, Davis, Todd, Schindler, Gross et al. 2003) in a subset of children (n=560). For
static connectivity, one component pair (the left supplementary motor area, i.e. SMA, and the
right supramarginal gyrus, i.e. SmG), showed an association with autistic traits. Specifically,
children with more autistic traits showed weaker static FNC. Interestingly, for dFNC State-3,
children with more autistic traits showed higher connectivity in three component pairs (right
insula and left superior frontal gyrus, right SmG and left precuneus i.e. preC, and right insula
and left preC) and lower connectivity in two component pairs (right-insula and right SmG, and
left SMA and right SmG). Next, we assessed how MDT and FT vary with respect to autistic trait
scores (Figure 6). In the globally disconnected state (State-2), autistic traits showed a positive
association with MDT. In the DMN-modularized state (State-3), autistic traits were negatively
associated with MDT. Thus, children with high levels of autistic traits spent more time in
the globally disconnected state (State-2) and children with lower levels spent more time in
the DMN-modularized state (State-3). Results remained highly consistent when models were
additionally adjusted for non-verbal IQ. A similar pattern of effects was observed at the severe
end of the spectrum, when 22 children with clinical ASD were compared to 88 age, sex and
IQ matched controls (Figure S6). Further, in order to assess whether the above-mentioned
associations are a core feature of the trait-continuum or if effects were driven by the most
severely affected children, sensitivity analyses were run. In these sensitivity analyses, children
with clinical ASD or an autistic traits score above the screening threshold were excluded, and
results remained consistent (Figure S7).
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