On the Spectrum

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From Chronnectivity To Chronnectopathy: Connectivity Dynamics of Typical Development Figure S5. 5 Summary metrics from the four dynamic connectivity states in relation to age and sex after excluding subjects with higher levels of behavioral problems. For age associations, positive beta coefficient (β) indicates older children spend more time in that particular state whereas negative beta coefficient Figure (β) indicates S5. Summary younger children metrics spend from more the four time dynamic in a particular connectivity state. For states sex in analyses, relation positive to age beta coefficient (β) indicates girls spend more time in the state relative to boys, and negative beta and coefficient sex after (β) indicates excluding that boys subjects spend with more time higher in the levels state of relative behavioral to girls. Bar problems. graphs indicate For age the associations, unstandardized positive beta coefficients beta coefficient (β) with standard (β) indicates error (S.E.) older from children regression spend models, more and time Asterisks in that (*) indicate the results survived the false discovery rate (FDR) multiple comparison correction threshold particular of pFDR = 0.05. state The whereas rendering negative brain maps beta are coefficient showing modularized (β) indicates positive younger (red) and children negative spend (blue) connectivity for the corresponding dynamic states. more time in a particular state. For sex analyses, positive beta coefficient (β) indicates girls spend more time in the state relative to boys, and negative beta coefficient (β) indicates that boys spend more time in the state relative to girls. Bar graphs indicate the unstandardized beta coefficients (β) with standard error (S.E.) from regression models, and Asterisks (*) indicate the results survived the false discovery rate (FDR) multiple 1256
Chapter 5 3.2 Case-control study for autism We also designed a case-control study for subjects with autism spectrum disorder (ASD) and autistic traits, where we had age, sex and IQ matched 88 healthy subjects and 22 subjects with autistic traits and ASD. We assessed the difference in dynamic FNC states between healthy control (HC) and autistic traits and ASD groups (Figure S6). Note that, these results are showing group differences between HC and ASD in state-1 and state-4, two of the dynamic states that did not capture any SRS effects (effects of autistic trait) in terms of mean dwell time (MDT) and fraction of time (FT) for the original analyses with 774 subjects. Figure S6. The medians of cluster centroids by state for HC (top) and ASD (middle) along with the count of subjects that had at least one window in each state are shown. The bottom row shows the FDR-corrected (indicate p < 0.05) results of two-sample t-test performed across subject median dFNC maps by state. Figure S6. The medians of cluster centroids by state for HC (top) and ASD (middle) 3.3 along Sensitivity with the count analysis of subjects based on that autistic had at trait least and one autism window in each state are shown. The We bottom also row performed shows the a sensitivity FDR-corrected analysis (indicate to evaluate p < 0.05) the effects results of SRS two-sample scores on t-test summary measures performed of across the dynamic subject median states dFNC (MT maps and FT). by state. We removed the subjects who are diagnosed with ASD, as well as the subjects with SRS scores above the screening cut-off. Using this subset 3.3 Sensitivity of the subjects analysis (after based exclusion, autistic number trait and of subjects=528), autism we performed the analyses for SRS score effects on MDT and FT (Figure S7). The SRS sensitivity analysis did not reveal We also performed a sensitivity analysis to evaluate the effects of SRS scores on any FDR-corrected effect of autistic traits. However, the direction of the effects remained the same summary as the measures original of analysis the dynamic (with states 774 subjects). (MDT and FT). We removed the subjects who are diagnosed with ASD, as well as the subjects with SRS scores above the screening 126 cutoff. Using this subset of the subjects (after exclusion, number of subjects=528), we
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On the Spectrum the neurobiology of
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ISBN: 978-94-6233-336-9 © Laura Bl
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PROMOTIECOMMISSIE Promotoren Overig
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MANUSCRIPTS THAT FORM THE BASIS OF
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Chapter 1 10
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Chapter 1 Cuthbert, Garvey, Heinsse
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Chapter 1 folding of the brain into
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Chapter 1 beneficial for treatment
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Chapter 1 REFERENCES Achenbach, T.
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Chapter 1 Sonuga-Barke, E. J. S.
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IPart I: The neurobiology of autist
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Chapter 2 ABSTRACT Objective: Recen
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Chapter 2 Hardan 2010) and right pa
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Chapter 2 Statistical analysis To i
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Chapter 2 Gyrification Six regions
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Chapter 2 The association remained
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Chapter 2 Table 4. Autistic traits
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Chapter 2 While we found widespread
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Chapter 2 REFERENCES Amaral, D. G.,
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Chapter 2 Wallace, G. L., P. Shaw,
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Chapter 2 South-West of the Netherl
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Chapter 2 Supplementary Figure 1. F
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Chapter 2 Supplementary Figure 3. G
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Chapter 2 Supplementary Figure 5. C
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Chapter 2 Supplementary Table 1. No
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Chapter 2 Supplementary Table 3. Ca
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3 A Prospective Study of Fetal Head
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A Prospective Study of Fetal Head G
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Chapter 7 Table 3 Cortical thicknes
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Chapter 7 Our finding was suggestiv
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Chapter 7 Using empirically defined
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Chapter 7 Fischl, B. and A. M. Dale
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Chapter 7 Supplement Table 1 Brain
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IIIPart III
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Chapter 8 190
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Chapter 8 stable relationships, and
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Chapter 8 gyrification changes in p
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Chapter 8 genetic or environmental
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Chapter 8 diseases, according to th
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Chapter 8 ability may be even more
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Chapter 8 symptoms could be more sp
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Chapter 8 association of maternal v
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Chapter 8 REFERENCES Abrahams, B. S
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Chapter 8 Goddard, M. N., S. van Ri
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Chapter 8 Sebat, J., B. Lakshmi, D.
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SSummary Samenvatting
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Summary SUMMARY Despite evidence fr
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Summary along a continuum were used
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Samenvatting SAMENVATTING Genetisch
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Samenvatting jonge kinderen die zic
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Addendum Mous SE, Schoemaker NK, Bl
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Addendum Zoeken in andere databases
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Addendum School of Women’s and In
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Addendum Graag wil ik Dr. Marion Sm
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Addendum hebben. Dank in het bijzon
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On the Spectrum

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