Figure - available from: Journal of Autism and Developmental Disorders
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Face-processing performance compared to standardized IQ scores for all participants and for male and female participants.
Face-processing deficits, while not required for the diagnosis of autism spectrum disorder (ASD), have been associated with impaired social skills—a core feature of ASD; however, the strength and prevalence of this relationship remains unclear. Across 445 participants from the NIMH Data Archive, we examined the relationship between Benton Face Reco...
... One example of this is face recognition impairment . As many as 40% of individuals with ASD have impaired or altered face-processing ability [67,68] which significantly affects the development of social skills . However, traditional correlational neuroimaging investigations studying participants with ASD have provided variable and contradictory results regarding which brain region or network is responsible for this difficulty [67,. ...
A wide variety of model systems and experimental techniques can provide insight into the structure and function of the human brain in typical development and in neurodevelopmental disorders. Unfortunately, this work, whether based on manipulation of animal models or observational and correlational methods in humans, has a high attrition rate in translating scientific discovery into practicable treatments and therapies for neurodevelopmental disorders. With new computational and neuromodulatory approaches to interrogating brain networks, opportunities exist for “bedside-to bedside-translation” with a potentially shorter path to therapeutic options. Specifically, methods like lesion network mapping can identify brain networks involved in the generation of complex symptomatology, both from acute onset lesion-related symptoms and from focal developmental anomalies. Traditional neuroimaging can examine the generalizability of these findings to idiopathic populations, while non-invasive neuromodulation techniques such as transcranial magnetic stimulation provide the ability to do targeted activation or inhibition of these specific brain regions and networks. In parallel, real-time functional MRI neurofeedback also allow for endogenous neuromodulation of specific targets that may be out of reach for transcranial exogenous methods. Discovery of novel neuroanatomical circuits for transdiagnostic symptoms and neuroimaging-based endophenotypes may now be feasible for neurodevelopmental disorders using data from cohorts with focal brain anomalies. These novel circuits, after validation in large-scale highly characterized research cohorts and tested prospectively using noninvasive neuromodulation and neurofeedback techniques, may represent a new pathway for symptom-based targeted therapy.
Event-related potential (ERP) sensitivity to faces is predominantly characterized by an N170 peak that has greater amplitude and shorter latency when elicited by human faces than images of other objects. We developed a computational model of visual ERP generation to study this phenomenon which consisted of a convolutional neural network (CNN) connected to a recurrent neural network (RNN). We used open-access data to develop the model, generated synthetic images for simulating experiments, then collected additional data to validate predictions of these simulations. For modeling, visual stimuli presented during ERP experiments were represented as sequences of images (time x pixels). These were provided as inputs to the model. The CNN transformed these inputs into sequences of vectors that were passed to the RNN. The ERP waveforms evoked by visual stimuli were provided to the RNN as labels for supervised learning. The whole model was trained end-to-end using data from the open-access dataset to reproduce ERP waveforms evoked by visual events. Cross-validation model outputs strongly correlated with open-access (r = 0.98) and validation study data (r = 0.78). Open-access and validation study data correlated similarly (r = 0.81). Some aspects of model behavior were consistent with neural recordings while others were not, suggesting promising albeit limited capacity for modeling the neurophysiology of face-sensitive ERP generation.
Objective: Tuberous Sclerosis Complex (TSC) is associated with focal brain "tubers" and a high incidence of autism spectrum disorder (ASD). The location of brain tubers associated with autism may provide insight into the neuroanatomical substrate of ASD symptoms. Methods: We delineated tuber locations for 115 TSC participants with ASD (n = 31) and without ASD (n = 84) from the Tuberous Sclerosis Complex Autism Center of Excellence Research Network. We tested for associations between ASD diagnosis and tuber burden within the whole brain, specific lobes, and at eight regions of interest derived from the ASD neuroimaging literature including the anterior cingulate, orbitofrontal and posterior parietal cortices, the inferior frontal and fusiform gyri, the superior temporal sulcus, the amygdala, and the supplemental motor area. Next, we performed an unbiased data-driven voxel-wise lesion symptom mapping (VLSM) analysis. Finally, we calculated the risk of ASD associated with positive findings from the above analyses. Results: There were no significant ASD-related differences in tuber burden across the whole-brain, within specific lobes, or within a priori regions derived from the ASD literature. However, using VLSM analysis we found that tubers involving the right fusiform face area (FFA) were associated with a 3.7-fold increased risk of developing ASD. Interpretation: While TSC is a rare cause of ASD, there is a strong association between tuber involvement of the right FFA and ASD diagnosis. This highlights a potentially causative mechanism for developing autism in TSC that may guide research into ASD symptoms more generally. This article is protected by copyright. All rights reserved.