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1.
Cereb Cortex ; 34(13): 19-29, 2024 May 02.
Article in English | MEDLINE | ID: mdl-38696600

ABSTRACT

While fronto-posterior underconnectivity has often been reported in autism, it was shown that different contexts may modulate between-group differences in functional connectivity. Here, we assessed how different task paradigms modulate functional connectivity differences in a young autistic sample relative to typically developing children. Twenty-three autistic and 23 typically developing children aged 6 to 15 years underwent functional magnetic resonance imaging (fMRI) scanning while completing a reasoning task with visuospatial versus semantic content. We observed distinct connectivity patterns in autistic versus typical children as a function of task type (visuospatial vs. semantic) and problem complexity (visual matching vs. reasoning), despite similar performance. For semantic reasoning problems, there was no significant between-group differences in connectivity. However, during visuospatial reasoning problems, we observed occipital-occipital, occipital-temporal, and occipital-frontal over-connectivity in autistic children relative to typical children. Also, increasing the complexity of visuospatial problems resulted in increased functional connectivity between occipital, posterior (temporal), and anterior (frontal) brain regions in autistic participants, more so than in typical children. Our results add to several studies now demonstrating that the connectivity alterations in autistic relative to neurotypical individuals are much more complex than previously thought and depend on both task type and task complexity and their respective underlying cognitive processes.


Subject(s)
Autistic Disorder , Brain , Magnetic Resonance Imaging , Semantics , Humans , Child , Male , Adolescent , Female , Autistic Disorder/physiopathology , Autistic Disorder/diagnostic imaging , Autistic Disorder/psychology , Brain/diagnostic imaging , Brain/physiopathology , Brain Mapping , Space Perception/physiology , Neural Pathways/physiopathology , Neural Pathways/diagnostic imaging
2.
Cereb Cortex ; 33(14): 9186-9211, 2023 07 05.
Article in English | MEDLINE | ID: mdl-37317036

ABSTRACT

The neural underpinnings of enhanced locally oriented visual processing that are specific to autistics with a Wechsler's Block Design (BD) peak are largely unknown. Here, we investigated the brain correlates underlying visual segmentation associated with the well-established autistic superior visuospatial abilities in distinct subgroups using functional magnetic resonance imaging. This study included 31 male autistic adults (15 with (AUTp) and 16 without (AUTnp) a BD peak) and 28 male adults with typical development (TYP). Participants completed a computerized adapted BD task with models having low and high perceptual cohesiveness (PC). Despite similar behavioral performances, AUTp and AUTnp showed generally higher occipital activation compared with TYP participants. Compared with both AUTnp and TYP participants, the AUTp group showed enhanced task-related functional connectivity within posterior visuoperceptual regions and decreased functional connectivity between frontal and occipital-temporal regions. A diminished modulation in frontal and parietal regions in response to increased PC was also found in AUTp participants, suggesting heavier reliance on low-level processing of global figures. This study demonstrates that enhanced visual functioning is specific to a cognitive phenotypic subgroup of autistics with superior visuospatial abilities and reinforces the need to address autistic heterogeneity by good cognitive characterization of samples in future studies.


Subject(s)
Autistic Disorder , Adult , Humans , Male , Brain/diagnostic imaging , Visual Perception/physiology , Brain Mapping/methods , Occipital Lobe , Magnetic Resonance Imaging/methods
3.
Cereb Cortex ; 33(5): 1566-1580, 2023 02 20.
Article in English | MEDLINE | ID: mdl-35552620

ABSTRACT

BACKGROUND: Autism spectrum disorder (ASD) is a common neurodevelopmental diagnosis showing substantial phenotypic heterogeneity. A leading example can be found in verbal and nonverbal cognitive skills, which vary from elevated to impaired compared with neurotypical individuals. Moreover, deficits in verbal profiles often coexist with normal or superior performance in the nonverbal domain. METHODS: To study brain substrates underlying cognitive imbalance in ASD, we capitalized categorical and dimensional IQ profiling as well as multimodal neuroimaging. RESULTS: IQ analyses revealed a marked verbal to nonverbal IQ imbalance in ASD across 2 datasets (Dataset-1: 155 ASD, 151 controls; Dataset-2: 270 ASD, 490 controls). Neuroimaging analysis in Dataset-1 revealed a structure-function substrate of cognitive imbalance, characterized by atypical cortical thickening and altered functional integration of language networks alongside sensory and higher cognitive areas. CONCLUSION: Although verbal and nonverbal intelligence have been considered as specifiers unrelated to autism diagnosis, our results indicate that intelligence disparities are accentuated in ASD and reflected by a consistent structure-function substrate affecting multiple brain networks. Our findings motivate the incorporation of cognitive imbalances in future autism research, which may help to parse the phenotypic heterogeneity and inform intervention-oriented subtyping in ASD.


Subject(s)
Autism Spectrum Disorder , Autistic Disorder , Humans , Autistic Disorder/complications , Brain , Intelligence , Cognition
4.
Neuroimage ; 263: 119612, 2022 11.
Article in English | MEDLINE | ID: mdl-36070839

ABSTRACT

Multimodal magnetic resonance imaging (MRI) has accelerated human neuroscience by fostering the analysis of brain microstructure, geometry, function, and connectivity across multiple scales and in living brains. The richness and complexity of multimodal neuroimaging, however, demands processing methods to integrate information across modalities and to consolidate findings across different spatial scales. Here, we present micapipe, an open processing pipeline for multimodal MRI datasets. Based on BIDS-conform input data, micapipe can generate i) structural connectomes derived from diffusion tractography, ii) functional connectomes derived from resting-state signal correlations, iii) geodesic distance matrices that quantify cortico-cortical proximity, and iv) microstructural profile covariance matrices that assess inter-regional similarity in cortical myelin proxies. The above matrices can be automatically generated across established 18 cortical parcellations (100-1000 parcels), in addition to subcortical and cerebellar parcellations, allowing researchers to replicate findings easily across different spatial scales. Results are represented on three different surface spaces (native, conte69, fsaverage5), and outputs are BIDS-conform. Processed outputs can be quality controlled at the individual and group level. micapipe was tested on several datasets and is available at https://github.com/MICA-MNI/micapipe, documented at https://micapipe.readthedocs.io/, and containerized as a BIDS App http://bids-apps.neuroimaging.io/apps/. We hope that micapipe will foster robust and integrative studies of human brain microstructure, morphology, function, cand connectivity.


Subject(s)
Connectome , Electronic Data Processing , Neuroimaging , Software , Humans , Brain/diagnostic imaging , Brain/anatomy & histology , Connectome/methods , Diffusion Tensor Imaging , Magnetic Resonance Imaging/methods , Neuroimaging/methods , Software/standards , Electronic Data Processing/methods , Electronic Data Processing/standards
5.
J Autism Dev Disord ; 53(12): 4719-4730, 2023 Dec.
Article in English | MEDLINE | ID: mdl-36136200

ABSTRACT

In light of the known visuoperceptual strengths and altered language skills in autism, we investigated the impact of problem content (semantic/visuospatial) combined with complexity and presence of lures on fluid reasoning in 43 autistic and 41 typical children (6-13 years old). Increased complexity and presence of lures diminished performance, but less so as the children's age increased. Typical children were slightly more accurate overall, whereas autistic children were faster at solving complex visuospatial problems. Thus, reasoning could rely more extensively on visuospatial strategies in autistic versus typical children. A combined speed-accuracy measure revealed similar performance in both groups, suggesting a similar pace in fluid reasoning development. Visual presentation of conceptual information seems to suit the reasoning processes of autistic children.


Subject(s)
Autism Spectrum Disorder , Autistic Disorder , Humans , Child , Adolescent , Autistic Disorder/diagnosis , Semantics , Autism Spectrum Disorder/diagnosis , Problem Solving , Cognition
6.
Autism Res ; 15(1): 103-116, 2022 01.
Article in English | MEDLINE | ID: mdl-34704349

ABSTRACT

Intellectual assessment in preschool autistic children bears many challenges, particularly for those who have lower language and/or cognitive abilities. These challenges often result in underestimation of their potential or exclusion from research studies. Understanding how different instruments and definitions used to identify autistic preschool children with global developmental delay (GDD) affect sample composition is critical to advance research on this understudied clinical population. This study set out to examine the extent to which using different instruments to define GDD affects sample composition and whether different definitions affect resultant cognitive and adaptive profiles. Data from the Mullen Scales of Early Learning and the Vineland Adaptive Behavior Scales-Second Edition, a parent-report tool, were analyzed in a sample of 64 autistic and 73 neurotypical children (28-69 months). Our results highlight that cognitive assessment alone should not be used in clinical or research practices to infer a comorbid diagnosis of GDD, as it might lead to underestimating autistic children's potential. Instead, using both adaptive and cognitive levels as a stratification method to create subgroups of children with and without GDD might be a promising approach to adequately differentiate them, with less risk of underestimating them.


Subject(s)
Autism Spectrum Disorder , Autistic Disorder , Language Development Disorders , Aptitude , Autism Spectrum Disorder/complications , Child, Preschool , Cognition , Humans
7.
Neuroimage Clin ; 36: 103221, 2022.
Article in English | MEDLINE | ID: mdl-36228483

ABSTRACT

Enhanced visuospatial abilities characterize the cognitive profile of a subgroup of autistics. However, the neural correlates underlying such cognitive strengths are largely unknown. Using functional magnetic resonance imaging (fMRI), we investigated the neural underpinnings of superior visuospatial functioning in different autistic subgroups. Twenty-seven autistic adults, including 13 with a Wechsler's Block Design peak (AUTp) and 14 without (AUTnp), and 23 typically developed adults (TYP) performed a classic mental rotation task. As expected, AUTp participants were faster at the task compared to TYP. At the neural level, AUTp participants showed enhanced bilateral parietal and occipital activation, stronger occipito-parietal and fronto-occipital connectivity, and diminished fronto-parietal connectivity compared to TYP. On the other hand, AUTnp participants presented greater activation in right and anterior regions compared to AUTp. In addition, reduced connectivity between occipital and parietal regions was observed in AUTnp compared to AUTp and TYP participants. A greater reliance on posterior regions is typically reported in the autism literature. Our results suggest that this commonly reported finding may be specific to a subgroup of autistic individuals with enhanced visuospatial functioning. Moreover, this study demonstrated that increased occipito-frontal synchronization was associated with superior visuospatial abilities in autism. This finding contradicts the long-range under-connectivity hypothesis in autism. Finally, given the relationship between distinct cognitive profiles in autism and our observed differences in brain functioning, future studies should provide an adequate characterization of the autistic subgroups in their research. The main limitations are small sample sizes and the inclusion of male-only participants.


Subject(s)
Autistic Disorder , Adult , Humans , Male , Magnetic Resonance Imaging/methods , Space Perception/physiology , Visual Perception/physiology , Cognition , Brain , Brain Mapping
8.
J Exp Psychol Gen ; 151(3): 578-596, 2022 Mar.
Article in English | MEDLINE | ID: mdl-34582232

ABSTRACT

Autism is diagnosed according to atypical social-communication and repetitive behaviors. However, autistic individuals are also distinctive in the high variability of specific abilities such as learning. Having been characterized as experiencing great difficulty with learning, autistics have also been reported to learn spontaneously in exceptional ways. These contrasting accounts suggest that some situations may be better than others for learning in autism. We tested this possibility using a probabilistic category learning task with four learning situations differing either in feedback intensity or information presentation. Two learning situations compared high- versus low-intensity feedback, while two other learning situations without external feedback compared isolated sequentially presented information versus arrays of simultaneously presented information. We assessed the categorization and generalization performance of 54 autistic and 52 age-matched typical school-age children after they learned in different situations. We found that children in both groups were able to learn and generalize novel probabilistic categories in all four learning situations. However, across and within groups, autistic children were advantaged by simultaneously presented information while typical children were advantaged by high-intensity feedback when learning. These findings question some common aspects of autism interventions (e.g., frequent intense feedback, minimized simplified information), and underline the importance of improving our current understanding of how and when autistics learn optimally. (PsycInfo Database Record (c) 2022 APA, all rights reserved).


Subject(s)
Autism Spectrum Disorder , Autistic Disorder , Child , Cognition , Generalization, Psychological , Humans , Learning
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