Anila M. D’Mello

The cerebellum is one of the most consistent sites of abnormality in autism spectrum disorder (ASD) and cerebellar damage is associated with an increased risk of ASD symptoms, suggesting that cerebellar dysfunction may play a crucial role in the etiology of ASD. The cerebellum forms multiple closed-loop circuits with cerebral cortical regions that underpin movement, language, and social processing. Through these circuits, cerebellar dysfunction could impact the core ASD symptoms of social and communication deficits and repetitive and stereotyped behaviors. The emerging topography of sensorimotor, cognitive, and affective subregions in the cerebellum provides a new framework for interpreting the significance of regional cerebellar findings in ASD and their relationship to broader cerebro-cerebellar circuits. Further, recent research supports the idea that the integrity of cerebro-cerebellar loops might be important for early cortical development; disruptions in specific cerebro-cerebellar loops in ASD might impede the specialization of cortical regions involved in motor control, language, and social interaction, leading to impairments in these domains. Consistent with this concept, structural, and functional differences in sensorimotor regions of the cerebellum and sensorimotor cerebro-cerebellar circuits are associated with deficits in motor control and increased repetitive and stereotyped behaviors in ASD. Further, communication and social impairments are associated with atypical activation and structure in cerebro-cerebellar loops underpinning language and social cognition. Finally, there is converging evidence from structural, functional, and connectivity neuroimaging studies that cerebellar right Crus I/II abnormalities are related to more severe ASD impairments in all domains. We propose that cerebellar abnormalities may disrupt optimization of both structure and function in specific cerebro-cerebellar circuits in ASD.

Neuroanatomical differences in the cerebellum are among the most consistent findings in autism spectrum disorder (ASD), but little is known about the relationship between cerebellar dysfunction and core ASD symptoms. The newly-emerging existence of cerebellar sensorimotor and cognitive subregions provides a new framework for interpreting the functional significance of cerebellar findings in ASD. Here we use two complementary analyses - whole-brain voxel-based morphometry (VBM) and the SUIT cerebellar atlas - to investigate cerebellar regional gray matter (GM) and volumetric lobular measurements in 35 children with ASD and 35 typically-developing (TD) children (mean age 10.4 ± 1.6 years; range 8-13 years). To examine the relationships between cerebellar structure and core ASD symptoms, correlations were calculated between scores on the Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview (ADI) and the VBM and volumetric data. Both VBM and the SUIT analyses revealed reduced GM in ASD children in cerebellar lobule VII (Crus I/II). The degree of regional and lobular gray matter reductions in different cerebellar subregions correlated with the severity of symptoms in social interaction, communication, and repetitive behaviors. Structural differences and behavioral correlations converged on right cerebellar Crus I/II, a region which shows structural and functional connectivity with fronto-parietal and default mode networks. These results emphasize the importance of the location within the cerebellum to the potential functional impact of structural differences in ASD, and suggest that GM differences in cerebellar right Crus I/II are associated with the core ASD profile.

Autism spectrum disorder (ASD) is characterized by challenges in social communication and the presence of repetitive behaviors or restricted interests. Notably, males are four times as likely as females to be diagnosed with autism. Despite efforts to increase representation and characterization of autistic females, research studies consistently enroll small samples of females, or exclude females altogether. Importantly, researchers often rely on standardized measures to confirm diagnosis prior to enrollment in research studies. We retrospectively analyzed the effects of one such measure (Autism Diagnostic Observation Schedule, ADOS) on research inclusion/exclusion rates by sex in autistic adults, all of whom had a preexisting community diagnosis of autism (n = 145, 95 male, 50 female). Using the ADOS as a confirmatory diagnostic measure resulted in the exclusion of autistic females at a rate over 2.5 times higher than that of autistic males. We compared sex ratios in our sample to those in other large, publically available datasets that rely either on community diagnosis (6 datasets, total n = 42,209) or standardized assessments (2 datasets, total n = 214) to determine eligibility of participants for research. Reliance on community diagnosis rather than confirmatory diagnostic assessments resulted in significantly more equal sex ratios. These results provide evidence for a "leaky" recruitment-to-research pipeline for females in autism research. LAY SUMMARY: Despite efforts to increase the representation of autistic females in research, studies consistently enroll small samples of females or exclude females altogether. We find that despite making up almost 50% of the initially recruited sample based upon self-report of community diagnosis, autistic females are disproportonately excluded from research participation as a result of commonly used autism diagnostic measures. In our sample, and several other publically available datasets, reliance on community diagnosis resulted in significantly more equal sex ratios.

It has been proposed that the cerebellum acquires internal models of mental processes that enable prediction, allowing for the optimization of behavior. In language, semantic prediction speeds speech production and comprehension. Right cerebellar lobules VI and VII (including Crus I/II) are engaged during a variety of language processes and are functionally connected with cerebral cortical language networks. Further, right posterolateral cerebellar neuromodulation modifies behavior during predictive language processing. These data are consistent with a role for the cerebellum in semantic processing and semantic prediction. We combined transcranial direct current stimulation (tDCS) and fMRI to assess the behavioral and neural consequences of cerebellar tDCS during a sentence completion task. Task-based and resting-state fMRI data were acquired in healthy human adults ( n = 32; μ = 23.1 years) both before and after 20 min of 1.5 mA anodal ( n = 18) or sham ( n = 14) tDCS applied to the right posterolateral cerebellum. In the sentence completion task, the first four words of the sentence modulated the predictability of the final target word. In some sentences, the preceding context strongly predicted the target word, whereas other sentences were nonpredictive. Completion of predictive sentences increased activation in right Crus I/II of the cerebellum. Relative to sham tDCS, anodal tDCS increased activation in right Crus I/II during semantic prediction and enhanced resting-state functional connectivity between hubs of the reading/language networks. These results are consistent with a role for the right posterolateral cerebellum beyond motor aspects of language, and suggest that cerebellar internal models of linguistic stimuli support semantic prediction. SIGNIFICANCE STATEMENT Cerebellar involvement in language tasks and language networks is now well established, yet the specific cerebellar contribution to language processing remains unclear. It is thought that the cerebellum acquires internal models of mental processes that enable prediction, allowing for the optimization of behavior. Here we combined neuroimaging and neuromodulation to provide evidence that the cerebellum is specifically involved in semantic prediction during sentence processing. We found that activation within right Crus I/II was enhanced when semantic predictions were made, and we show that modulation of this region with transcranial direct current stimulation alters both activation patterns and functional connectivity within whole-brain language networks. For the first time, these data show that cerebellar neuromodulation impacts activation patterns specifically during predictive language processing.