Table 2.

Dimensional Studies Using Functional Connectivity Data

Study	Data Source	n	Age, Years, Mean ± SD or Range	Male, %	Algorithm/Approach	Features	Validation	Symptoms/Phenotypes Predicted	Highlights
(27)	ABIDE, ADHD-200	ABIDE: 122 autism, 230 NT^a ADHD-200: 77 ADHD, 35 NT	6–24	71%^b	CPM (linear regression)	FC from 268 × 268 ROIs (Shen atlas) (148)	Internal (split half, leave-one-out CV); leave-one-site-out CV; external validation in independent sample	SRS, ADOS, ADHD-RS	SRS, ADOS predictive network models were largely distinct; SRS model generalized to predict inattention in a separate ADHD sample
(54)	Lab-specific	58 autism^c	Not specified for dim. analyses	Not specified for dim. analyses	Linear regression	16 FC	Internal (leave-one-out CV)	ADOS, ADI-R	Functional connections identified as correctly classifying autism vs. NT status generalized to predict the communication domain of ADOS
(78)	ABIDE	103 autism	20.8 ± 8.1	100%	SVR	First score of principal connectivity gradient, stepwise connectivity maps	Internal (5-fold CV); leave-one-site-out CV	ADOS	Prediction of ADOS total and social cognition; DMN and primary visual areas highly represented in predictive models
(86)	ABIDE, LEAP	232 autism^d	14.8 ± 6.5	74%	CCA	FC from 415 × 415 ROIs [Schaefer atlas (149) 1 subcortical atlas]	Leave-one-site-out CV	Various autism, social abilities scales	Multiple canonical variates predictive of left-out-site; connections within and between somatomotor, DMN, attention, visual networks implicated in models
(87)	Lab-specific	31 autism	17.9 ± 3.4	100%	Ridge regression	FC from DMN, SN, FPN networks (Power atlas) (140)	Internal (leave-one-out CV)	SRS, ABAS	Prediction of change in SRS and ABAS scores and prediction of time 2 SRS scores ~ 3 years after scanning
(88)	ABIDE	85 autism 191 NT	8–13	66%	CPM (linear regression)	FC from 268 × 268 ROIs (Shen atlas) (148)	Internal (leave-one-out, split-half CV); site 1 to site 2 prediction	BRIEF	Complex, brain-wide model with many edges in somatomotor, visual, and cerebellar areas; also edges in DMN and temporal lobe
(89)	ABIDE	82 autism	7–12	100%	Lasso regression	FC from 227 × 227 ROIs (Power atlas) (140)	Internal (leave-one-out CV)	ADOS	Separate predictive brain networks predicting communication and social interaction phenotypes can be merged to predict social affect scores

ABAS, Adaptive Behavior Assessment System; ABIDE, Autism Brain Imaging Data Exchange; ADHD, attention-deficit/hyperactivity disorder; ADHD-RS, ADHD Rating Scale; ADI-R, Autism Diagnostic Interview–Revised; ADOS, Autism Diagnostic Observation Schedule; BRIEF, Behavior Rating Inventory of Executive Function; CCA, canonical correlation analysis; CPM, connectome-based predictive modeling; CV, cross-validation; dFC, dynamic functional connectivity; dim., dimension; DMN, default mode network; FC, functional connectivity; FPN, frontoparietal network; LEAP, European Autism Interventions Multicenter Study for Developing New Medications Longitudinal European Autism Project; NT, neurotypical; ROI, region of interest; SN, salience network; SRS, Social Responsiveness Scale; SVR, support vector regression.

Here, we report sample size used for most of the SRS analyses (SRS total scores as well as the following subscales: communication, motivation, and mannerisms). The sample size was n = 180 NT and 80 autism for predicting SRS cognition and awareness subscales and n = 79 autism and n = 58 autism for predicting ADOS modules 3 and 4, respectively.

Across SRS analyses, ~70% of the sample was male; in ADOS analyses, ~85% of the sample was male. Sex was not reported in the ADHD-200 sample.

We report the sample size used in the ADOS dimensional prediction analyses. A total of 27 participants with autism were used in the ADI-R dimensional prediction analyses.

A total of 125 individuals with autism and 78 control subjects from the LEAP cohort were used in Short Sensory Profile subscales analyses; demographics were roughly similar to the rest of the sample.