The authors have declared that no competing interest exist.
Conceived and designed the experiments: EJM PM JPO YSC. Performed the experiments: EJM AA SH JH SD. Analyzed the data: YSC JPO. Wrote the paper: YSC JPO EJM PM AA SH JH SD.
¶ These authors are co-first authors on this work.
Over 90% of children with Autism Spectrum Disorders (ASD) demonstrate atypical sensory behaviors. In fact, hyper- or hyporeactivity to sensory input or unusual interest in sensory aspects of the environment is now included in the DSM-5 diagnostic criteria. However, there are children with sensory processing differences who do not meet an ASD diagnosis but do show atypical sensory behaviors to the same or greater degree as ASD children. We previously demonstrated that children with Sensory Processing Disorders (SPD) have impaired white matter microstructure, and that this white matter microstructural pathology correlates with atypical sensory behavior. In this study, we use diffusion tensor imaging (DTI) fiber tractography to evaluate the structural connectivity of specific white matter tracts in boys with ASD (n = 15) and boys with SPD (n = 16), relative to typically developing children (n = 23). We define white matter tracts using probabilistic streamline tractography and assess the strength of tract connectivity using mean fractional anisotropy. Both the SPD and ASD cohorts demonstrate decreased connectivity relative to controls in parieto-occipital tracts involved in sensory perception and multisensory integration. However, the ASD group alone shows impaired connectivity, relative to controls, in temporal tracts thought to subserve social-emotional processing. In addition to these group difference analyses, we take a dimensional approach to assessing the relationship between white matter connectivity and participant function. These correlational analyses reveal significant associations of white matter connectivity with auditory processing, working memory, social skills, and inattention across our three study groups. These findings help elucidate the roles of specific neural circuits in neurodevelopmental disorders, and begin to explore the dimensional relationship between critical cognitive functions and structural connectivity across affected and unaffected children.
The human brain is a sensory processor. Its core function is to perceive, integrate, interpret, and then facilitate the appropriate coordinated response to the visual, tactile, auditory, olfactory, and proprioceptive information present in the world around us. Thus it comes as no surprise that inaccurate or imprecise sensory processing and multisensory integration (MSI) can lead to impaired intellectual and social development
Autism spectrum disorders (ASD) have traditionally been characterized by impaired communication, social interaction, and behavioral flexibility
In comparison to DTI studies of ASD, investigation of structural connectivity in children with isolated SPD is in its infancy. We recently reported that, although children with SPD do not exhibit morphological abnormalities from structural MR imaging, they have strikingly decreased white matter microstructural integrity, especially in posterior cerebral regions
In this study, we examine white matter tracts that we hypothesize will be atypical in children with SPD or ASD subjects relative to typically developing children (TDC). Based upon our previous work on white matter microstructure in SPD
The Institutional Review Board (IRB) at the University of California in San Francisco approved this study (UCSF IRB Protocol #: 10-01940). Subjects were recruited from the UCSF Autism and Neurodevelopment Program clinical sites and research database, and from local online parent board listings. Informed consent was obtained from the parents or legal guardians, with the assent of all participants.
Sixteen right-handed males with SPD, fifteen males with ASD (12 right-handed, 1 left-handed, 2 ambidextrous), and 23 right-handed male TDC, all between 8 and 12 years of age, were prospectively enrolled under our IRB protocol.
Voxel-based analysis of the DTI data from the 16 SPD subjects and the 23 TDC using tract-based spatial statistics (TBSS) to investigate white matter microstructure was previously reported in
All subjects were assessed with the Wechsler Intelligence Scale for Children-Fourth Edition
TDC Mean ± Std | ASD Mean ± Std | Pval | SPD Mean ± Std | Pval | |
PRI | 113.5±13.5 | 101.6±14.1 | 115.8±11.5 | 0.576 | |
VCI | 119.2±12.7 | 101.6±20.5 | 117.4±12.8 | 0.660 | |
WMI | 108.4±10.9 | 99.6±17.7 | 0.111 | 104.4±12.8 | 0.320 |
PSI | 101.3±13.6 | 87.4±11.1 | 97.1±12.9 | 0.334 |
PRIs, VCIs, WMIs and PSIs for each cohort, with p values from two-tailed t-tests for differences between TDCs and each patient cohort (statistically significant p values of less than 0,05 are indicated in boldface).
All subjects were evaluated with the Sensory Profile
Inclusion in the SPD group required a community based Occupational Therapy diagnosis of Sensory Processing Disorder plus a score in the definite difference (DD) range, defined as greater than two standard deviations from the mean, of either the total or the auditory processing score of the Sensory Profile. Five of the SPD subjects scored in the DD range for total score alone, four scored in the DD range for the auditory processing score alone, and seven scored in the DD range for both the total and auditory score. Two ASD subjects scored in the DD range for the total score alone, one ASD subject scored in the DD range for the auditory score alone, and seven of the ASD subjects scored in the DD range for both the total and auditory score. The sensory profile was not obtained for one ASD individual. All of the controls scored in the normal range (
TDC Mean ±Std | ASD Mean ±Std | SPD Mean ±Std | |
Auditory | 33.6±3.5 | *24.4±5.9 | *22.7±4.9 |
Tactile | 83.3±5.8 | 72.4±8.6 | *62.9+8.8 |
Visual | 41.2±3.0 | 35.6±6.3 | 32.3±7.1 |
Inattention | 28.7±3.6 | *20.3±4.4 | *17.8±5.3 |
Total | 172.3±11.0 | *135.1±18.2 | *128.5±15.8 |
Multisensory | 31.3±3.1 | 23.7±4.5 | 22.2±3.7 |
Asterisks indicate mean scores that fall within the definite difference range. None of the mean scores fell in the probable difference range.
All subjects were evaluated with the Social Communication Questionnaire (SCQ), a parent report ASD screening instrument
Three of the SPD cohort scored above 15 on the SCQ and were further evaluated with the ADI-R and ADOS. One SPD participant scored above the ASD cutoff on the current diagnosis scoring of the ADOS but did not meet criteria on the ADI-R. Another SPD individual met criteria on the ADI-R but not the ADOS. Neither was considered to meet clinical criteria when evaluated by a cognitive behavioral child neurologist with expertise in autism and neurodevelopment (EJM). The third SPD participant who scored above 15 on the SCQ met neither the ADI-R nor ADOS cut-off. A supplementary analysis was performed, excluding these three SPD subjects from the study cohort (
On the inattention/distractibility factor of the Sensory Profile, eleven of the 16 SPD subjects scored in the definite difference range, four in the probable difference range, and one in the typical range. Of the 15 ASD subjects, seven scored in the definite difference range, five scored in the probable difference range, two scored in the typical range, and one was not administered the Sensory Profile. Of the 23 TDC, none scored in the definite difference range, three in the probable difference range, and twenty in the typical range. Atypical inattention/distractibility scores on the Sensory Profile do not necessarily indicate that individuals would meet clinical criteria for an attention deficit (hyperactivity) disorder (ADHD) diagnosis. Formal ADHD evaluations were not conducted as part of this study.
Three of 16 SPD boys were born prematurely, one at 32 weeks gestation and two at 34 weeks gestation. One of the 23 typically developing children was born prematurely, at 33 weeks gestation. These four subjects were found to be in the middle of the distribution for global FA and mean FA extracted from clusters of significantly affected voxels using TBSS for their respective groups, and therefore they were not considered to be outliers
MR imaging was performed on a 3T Tim Trio scanner (Siemens, Erlangen, Germany) using a 12-channel head coil. Structural MR imaging of the brain was performed with an axial 3D magnetization prepared rapid acquisition gradient-echo (MP-RAGE) T1-weighted sequence (TE = 2.98 ms, TR = 2300 ms, TI = 900 ms, flip angle of 9°) with a 256 mm field of view (FOV), and 160 1.0 mm contiguous partitions at a 256×256 matrix. Whole-brain DTI was performed with a multislice 2D single-shot twice-refocused spin-echo echo-planar sequence with 64 diffusion-encoding directions, diffusion-weighting strength of b = 2000 s/mm2, iPAT reduction factor of 2, TE/TR = 109/8000 ms, averages = 1, interleaved 2.2 mm axial slices with no gap, and in-plane resolution of 2.2×2.2 mm with a 100×100 matrix and FOV of 220 mm. An additional volume was acquired with no diffusion weighting (b = 0 s/mm2). The total DTI acquisition time was 8.67 min.
The diffusion-weighted images were corrected for motion and eddy currents using FMRIB’s Linear Image Registration Tool (FLIRT;
The FSL bedpostx tool was used for HARDI reconstruction of the diffusion data, modeling multiple fiber orientations per voxel, and thereby accounting for crossing fibers
White matter tract | Seed mask | Waypoint and termination mask | Exclusion mask |
Fusiform - amygdala | Fusiform gyrus | Amygdala | All other gm regions |
Fusiform - hippocampus | Fusiform gyrus | Hippocampus | All other gm regions |
Uncinate fasciculus (UF) | Orbitofrontal cortex* | Entorhinal cortex + temporal pole | All other gm regions |
Inferior longitudinal fasciculus (ILF) | Pericalcarine cortex | Inferior temporal cortex | Thalamus + all other cortical regions |
Inferior frontooccipital fasciculus (IFOF) | Lingual gyrus | Orbitofrontal cortex* | Thalamus + all other cortical regions |
The Freesurfer seed, waypoint, termination, and exclusion masks used in fiber tractography to delineate examined temporal tracts. *Orbitofrontal cortex was created by summing the medial orbitofrontal cortex and lateral orbitofrontal cortex.
White matter tract | Seed mask | Waypoint and termination mask | Exclusion mask |
Optic radiation | Pericalcarine cortex | Eroded thalamus | All other cortical regions |
Dorsal visual stream | Pericalcarine cortex | Inferior parietal cortex | Thalamus |
Splenium of the corpus callosum | Left lateral occipital cortex | Right lateral occipital cortex* | All other cortical regions |
Posterior corona radiata (PCR) (occipital) | All occipital regions | Cerebral peduncle | All other cortical regions |
Posterior corona radiata (PCR) (parietal) | All parietal regions | Cerebral peduncle | All other cortical regions |
The Freesurfer seed, waypoint, termination, and exclusion masks used in fiber tractography to delineate examined parieto-occipital tracts. *For the tract through the splenium of the corpus callosum, a callosal waypoint mask was also used.
White matter tract | Seed mask | Waypoint and termination mask | Exclusion mask |
Anterior thalamic radiation(ATR) (medial orbitofrontal cortex) | Medial orbitofrontal cortex | Eroded thalamus | All other gm regions |
Anterior thalamic radiation(ATR) (rostral middle frontal cortex) | Rostral middle frontal cortex | Eroded thalamus | All other gm regions |
Genu of the corpus callosum(medial orbitofrontal cortex) | Left medial orbitofrontal cortex | Right medial orbitofrontal cortex | All other cortical regions |
Genu of the corpus callosum(rostral middle frontal cortex) | Left rostral middle frontal cortex | Right rostral middle frontal cortex | All other cortical regions |
Anterior corona radiata (ACR) | All frontal regions | Cerebral peduncle | All other cortical regions |
The Freesurfer seed, waypoint, termination, and exclusion masks used in fiber tractography to delineate examined frontal tracts. *For the tracts through the genu of the corpus callosum, a callosal waypoint mask was also used.
Subsequent to performance of probabilistic streamline fiber tractography, tract masks for every tract described in
White matter connectivity was calculated as the average FA value within the delineated tract of interest. This measurement has been shown to be highly reproducible in cross-sectional
Representative examples of each of the 15 delineated tracts are displayed in
Green masks represent frontal tracts, blue masks represent parietal-occipital tracts, and orange masks represent temporal tracts. The tracts are superimposed upon the T1 image, registered to diffusion space and with decreased opacity, of the representative subject.
For each tract, decreases in FA were separately assessed for the SPD and ASD cohorts relative to controls using one-tailed permutation tests (n = 10,000) (adapted from
Pearson’s correlations of FA in the 15 examined tracts with the VCI, PRI, WMI, PSI, the social component of the SCQ, and the five subtests of the SP (auditory, visual, tactile, inattention, multisensory integration) were investigated dimensionally across all individuals. Statistical significance was assessed at p<0.05 with FDR correction across all 15 tracts. For tracts and cognitive/behavioral metrics demonstrating significant associations across groups, post-hoc correlational analyses were conducted for the unilateral tract FA (left and right hemisphere independently) across groups, as well as unilateral and bilateral tract FA (left and right combined) for each cohort (TDC, SPD, and ASD) independently.
Crossbars correspond to group averages. Green asterisks depict significant group differences between ASD and TDC subjects, and red asterisks depict significant group differences between SPD and TDC subjects, FDR corrected at p<0.05.
Crossbars correspond to group averages. Green asterisks depict significant group differences between ASD and TDC subjects, and red asterisks depict significant group differences between SPD and TDC subjects, FDR corrected at p<0.05.
Crossbars correspond to group averages. Green asterisks depict significant group differences between ASD and TDC subjects, and red asterisks depict significant group differences between SPD and TDC subjects, FDR corrected at p<0.05.
Tract | TDC mean FA±SD | ASD mean FA±SD | P-val | SPD mean FA±SD | P-val |
0.3693±0.0182 | 0.3546±0.0177 | 0.3738±0.0203 | 0.2298 | ||
0.3587±0.0146 | 0.3469±0.0156 | 0.3558±0.016 | 0.282 | ||
0.3429±0.0156 | 0.3375±0.0137 | 0.118 | 0.3388±0.0099 | 0.1886 | |
0.4114±0.0147 | 0.4008±0.0192 | 0.4028±0.0164 | 0.0468 | ||
0.3956±0.0171 | 0.3844±0.0156 | 0.3893±0.0128 | 0.11 | ||
0.4095±0.0113 | 0.4029±0.0127 | 0.0516 | 0.4032±0.0175 | 0.0814 | |
0.4155±0.0147 | 0.4052±0.0179 | 0.4009±0.0156 | |||
0.4658±0.0161 | 0.4589±0.0167 | 0.1012 | 0.4517±0.0238 | ||
0.4194±0.0123 | 0.4093±0.0161 | 0.4085±0.019 | |||
0.4182±0.0093 | 0.4142±0.0168 | 0.1338 | 0.4124±0.0178 | 0.1018 | |
0.4182±0.0091 | 0.4259±0.0146 | 0.0508 | 0.4136±0.0156 | 0.1236 | |
0.3623±0.0137 | 0.3627±0.0137 | 0.4984 | 0.3581±0.014 | 0.1694 | |
0.3530±0.0111 | 0.3532±0.0143 | 0.3616 | 0.3457±0.0105 | 0.0238 | |
0.4361±0.0224 | 0.4338±0.0179 | 0.3666 | 0.4296±0.0218 | 0.1916 | |
0.4105±0.0196 | 0.4078±0.0208 | 0.4306 | 0.4008±0.0204 | 0.0674 |
The mean and standard deviation of FA within each tract for each group, with associated p values for group differences of the TDC cohort with either the SPD cohort or the ASD cohort. Bolded p values represent significant group differences at p<0.05, FDR corrected.
Significantly impaired connectivity (lower FA) was detected for the ASD cohort alone relative to the TDC cohort in the fusiform-amygdala and fusiform-hippocampus tracts, the inferior fronto-occipital fasciculi (IFOF), and the inferior longitudinal fasciculi (ILF) (p<0.05, FDR corrected). The SPD cohort showed no significant differences in these tracts relative to the TDC cohort. There was no significant difference in connectivity of the uncinate fasciculi of either the ASD or SPD cohorts relative to the controls.
The SPD group alone showed significantly decreased connectivity in the splenium of the corpus callosum relative to the TDC cohort. Both the SPD and the ASD group showed reduced connectivity relative to controls in the dorsal visual stream and the posterior corona radiata (occipital portion) (all results with p<0.05, FDR corrected).
Neither the SPD nor ASD groups demonstrated significant differences in the optic radiations (pericalcarine – thalamus PTR) or parietal PCR relative to TDC; however, there were strong trends toward lower connectivity of the optic radiations in both the ASD and SPD groups relative to TDC.
Connectivity in the frontal tracts was not significantly decreased for either the SPD or ASD cohorts, although the SPD group showed trends towards decreased connectivity for all measured frontal tracts.
Homologous white matter tracts of the left and right cerebral hemispheres were combined for purposes of consolidation and improved statistical power. However, group differences were also computed unilaterally for each tract. In all cases, the results from bilateral tracts shown here agree with trends or statistically significant group differences from the component unilateral tracts, with no appreciable hemispheric asymmetries found.
PRI was significantly lower in the ASD cohort compared to the TDC subjects, thus group differences in connectivity were computed while controlling for PRI scores. After controlling for PRI and including FDR correction, connectivity for the ASD cohort was no longer significantly lower in the IFOF or ILF, but still demonstrated decreased FA in the fusiform -amygdala and fusiform –hippocampus tracts. The results for the SPD subjects were unchanged when controlling for PRI, as expected since these subjects did not demonstrate differences in PRI relative to TDC.
Significant combined-group correlations were found between WMI and the bilateral optic radiations (r = 0.41, p = 0.003) as well as the bilateral PCR (occipital) (r = 0.49, p<0.001) (
The two bilateral tracts demonstrating significant associations between FA and WMI after FDR correction are displayed. Optic radiation: r = 0.41, p = 0.003. PCR (occipital): r = 0.49, p<0.001. Results of unilateral and individual group correlations are displayed in
r - bilateral | r - left | r - right | ||||
PTR (optic radiation) | ||||||
All | 0.41 | 0.36 | 0.32 | |||
TDC | −0.08 | − |
||||
ASD | 0.54 | |||||
SPD | 0.62 | 0.35 | 0.73 | |||
PCR (occipital) | ||||||
All | 0.49 | 0.50 | 0.32 | |||
TDC | 0.22 | 0.39 | −0.07 | |||
ASD | 0.46 | 0.40 | 0.30 | |||
SPD | 0.67 | 0.68 | 0.56 |
The bilateral tracts demonstrating significant combined-group associations with WMI are displayed. Correlation coefficients and p values are displayed for these tracts, along with combined group unilateral associations, individual group bilateral associations, and individual group unilateral associations.
Significant combined-group correlations were found between the social component of the SCQ and the bilateral fusiform - amygdala (r = −0.44, p = 0.001) as well as the bilateral fusiform-hippocampus (r = −0.39, p = 0.004) (
The two bilateral tracts demonstrating significant associations between FA and the social component of the SCQ after FDR correction are displayed. Fusiform-amygdala: r = −0.44, p<0.001. Fusiform-hippocampus: r = −0.39, p = 0.004. Results of unilateral and individual group correlations are displayed in
r - bilateral | r - left | r - right | ||||
Fusiform-amygdala | ||||||
All | −0.44 | −0.27 | −0.37 | |||
TDC | −0.39 | −0.18 | −0.29 | |||
ASD | −0.40 | −0.34 | −0.18 | |||
SPD | −0.32 | 0.03 | −0.50 | |||
Fusiform-hippocampus | ||||||
All | −0.39 | −0.25 | −0.40 | |||
TDC | −0.14 | −0.11 | −0.15 | |||
ASD | −0.25 | −0.22 | −0.12 | |||
SPD | −0.27 | −0.01 | −0.47 |
The bilateral tracts demonstrating significant combined-group associations with the social component of the SCQ are displayed. Correlation coefficients and p values are displayed for these tracts, along with combined group unilateral associations, individual group bilateral associations, and individual group unilateral associations.
Significant combined-group correlations were found between the inattention measures of the Sensory Profile and the dorsal visual stream (r = 0.38, p = 0.006) as well as the bilateral PCR (occipital) (r = 0.46, p = 0.001) (
The two bilateral tracts demonstrating significant associations between FA and the inattention measure of the Sensory Profile after FDR correction are displayed. Dorsal visual stream: r = 0.38, p = 0.006. PCR (occipital): r = 0.46, p<0.001. Results of unilateral and individual group correlations are displayed in
r - bilateral | r - left | r - right | ||||
Dorsal Visual Stream | ||||||
All | 0.38 | 0.34 | 0.27 | |||
TDC | −0.16 | −0.09 | −0.19 | |||
ASD | 0.37 | 0.04 | 0.37 | |||
SPD | 0.25 | 0.05 | 0.40 | |||
PCR (occipital) | ||||||
All | 0.46 | 0.37 | 0.41 | |||
TDC | 0.00 | 0.06 | −0.05 | |||
ASD | 0.63 | 0.44 | 0.63 | |||
SPD | 0.41 | 0.19 | 0.54 |
The bilateral tracts demonstrating significant combined-group associations with the inattention measure of the Sensory Profile are displayed. Correlation coefficients and p values are displayed for these tracts, along with combined group unilateral associations, individual group bilateral associations, and individual group unilateral associations.
Significant combined-group correlations were found between the auditory factor of the Sensory Profile and the bilateral PCR (occipital) (r = 0.42, p = 0.004) (
The bilateral tract demonstrating significant associations between FA and the auditory measure of the Sensory Profile after FDR correction are displayed. PCR (occipital): r = 0.42, p = 0.002. Results of unilateral and individual group correlations are displayed in
r - bilateral | r - left | r - right | ||||
PCR (occipital) | ||||||
All | 0.42 | 0.33 | 0.37 | |||
TDC | −0.33 | −0.20 | −0.27 | |||
ASD | 0.60 | 0.38 | 0.62 | |||
SPD | 0.41 | 0.20 | 0.49 |
The bilateral tracts demonstrating significant combined-group associations with the inattention measure of the Sensory Profile are displayed. Correlation coefficients and p values are displayed for these tracts, along with combined group unilateral associations, individual group bilateral associations, and individual group unilateral associations.
The combined groups did not demonstrate significant correlations between FA in the 15 investigated tracts and PRI, VCI, or the other subscores of the Sensory Profile after correction for multiple comparisons.
Some tracts demonstrated a significant fraction of shared voxels.
Color intensity corresponds to the subject average of the fraction of the voxels of the tracts on the vertical axis that are contained within the tracts on the horizontal axis. Tracts that are more than one-third contained in any other tract are indicated by an asterisk on the vertical axis.
This study is the first to investigate white matter connectivity of both children with SPD and children with ASD relative to typically developing children. Diffusion MR fiber tracking was employed for the hypothesis-driven identification of specific white matter tracts. The results suggest both overlapping and divergent white matter microstructural pathology affecting the two clinical cohorts, with tracts traditionally associated with social emotional processing being significantly affected for the ASD cohort relative to TDC, but relatively unaffected in SPD. While both the ASD and the SPD participants demonstrate white matter pathology in the sensory processing regions of the dorsal visual stream and the posterior corona radiata, only the SPD cohort demonstrates statistically significant differences in the splenium of the corpus callosum relative to the TDC cohort. These findings extend previous research using DTI in autism cohorts to include concurrent analysis of children that exhibit sensory processing differences, but not the language and social deficits that characterize a full ASD diagnosis.
While the most extensive white matter alterations in the SPD subjects are observed in the parieto-occipital tracts, which subserve auditory, tactile, and visual perception and integration, this cohort demonstrates trends towards decreased connectivity compared to TDC in most measured tracts. It is also worth specific comment that, while both the SPD and ASD cohorts were affected in these fundamental sensory processing tracts, the FA in all but one of these tracts trended lower for the SPD subjects relative to the ASD subjects. This difference may reflect the prominence of abnormal sensory related behaviors, which is an inclusion criterion for SPD group membership, whereas, in general, children with ASD are primarily characterized by profound social communication deficits. In this sample, 65% of children with ASD scored in the definite difference (DD) range (>2 standard deviations from the mean) on the Sensory Profile Total Score and 57% were in the DD range for the Auditory Processing Score. While many children with ASD have auditory, tactile and visuomotor processing challenges, these deficits are not as ubiquitous as in our SPD cohort. Our findings further suggest that sensory-based behavioral deficits in both groups may be predicated on atypical conduction of information from unimodal to multimodal integration regions as well as inefficient transfer of information between hemispheres via the corpus callosum for the SPD group.
Perhaps the most striking finding is that, relative to the control group, the ASD cohort shows reduced structural connectivity in the fusiform gyrus connections to the amygdala and hippocampus, whereas children with SPD do not. These white matter pathways are thought to facilitate facial emotional processing, a core feature of autism and the domain of clinical divergence for ASD versus SPD
There are however additional farther reaching implications for fusiform connectivity disruptions with regard to language development. A theoretical model of audiovisual affective speech perception begins with input to primary auditory and visual cortex
In addition to the fusiform connections, our ASD group was found to have reduced FA in the ILF and the IFOF. This is in line with previous reports, although there is considerable variability in the literature, likely resulting from group heterogeneity in terms of symptom variability, severity, and age of cohort
As can be seen from the group comparison figures, while there are clear and statistically significant group differences, there is also considerable overlap in the measurements from tracts across all three groups: ASD, SPD, and TDC. This highlights the importance of a new direction for cognitive and behavioral research based on the investigation of abilities as a continuous measure across children rather than split by exceedingly broad and overlapping clinical labels, a concept which has been formalized in the Research Domain Criteria (RDoC) Project
There are important limitations to note for this study, which should motivate further investigation. First, we have not determined an optimal method for characterizing the sensory subtypes and distinguishing between hypo- or hyper-sensory sensitivity, nor do we have sufficient power in this study for sensory subtype group analysis. We and many sensorimotor based researchers are working to develop a phenotyping tool that maps to specific white matter tracts, and we hope to identify and characterize separate constructs of sensory deficits in larger cohorts going forward. Second, tract overlap exists in our results. A significant portion of the amygdala-fusiform tract is contained within the hippocampal-fusiform tract. In addition, the ILF is partially contained within the dorsal visual stream and the PTR is partially contained within the PCR. Despite these spatial overlaps, the group difference results are not identical between overlapping tracts and provide separately valuable information about structural connectivity in these subjects. Additional connectivity analysis, both structural and functional, will shed additional light on specific regional contributions to the neural underpinnings of sensory and emotional processing differences. Our investigation is also limited in generalizability, as all of the subjects were boys between the ages of 8 and 12 years in an effort to limit developmental confounds in this small sample. The PRI scores of the ASD cohort were significantly lower than that of the SPD and TDC cohorts; however, the most important group differences in structural connectivity between ASD and controls remained statistically significant after regressing out the effect of PRI. Further research is therefore needed to determine whether these findings generalize to other ages, genders, and intellectual abilities.
Future research will include investigation of functional connectivity using resting state fMRI and magnetoencephalography (MEG). The ROIs used to determine structural connectivity in this study can be used to assess differences in functional connectivity between these same regions, with functional coupling hypothesized to be reduced where decreased structural connectivity was found in this work. While prior studies have found relationships between functional connectivity and white matter volume in ASD
We hope that by utilizing larger sample sizes and direct assessment of auditory, tactile, visuomotor processing, we will be able to gain a deeper understanding of how neural circuitry differences map to clinically relevant challenges for individual children. The ultimate goal of this and future work is to guide personalized treatments ranging from behavioral interventions and targeted psychopharmacology to cognitive training using child-friendly video game platforms.
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We are grateful to our participants and their families for their time and support.