Clinical and anatomical heterogeneity in autistic spectrum disorder: a structural MRI study

2009 ◽  
Vol 40 (7) ◽  
pp. 1171-1181 ◽  
Author(s):  
F. Toal ◽  
E. M. Daly ◽  
L. Page ◽  
Q. Deeley ◽  
B. Hallahan ◽  
...  

BackgroundAutistic spectrum disorder (ASD) is characterized by stereotyped/obsessional behaviours and social and communicative deficits. However, there is significant variability in the clinical phenotype; for example, people with autism exhibit language delay whereas those with Asperger syndrome do not. It remains unclear whether localized differences in brain anatomy are associated with variation in the clinical phenotype.MethodWe used voxel-based morphometry (VBM) to investigate brain anatomy in adults with ASD. We included 65 adults diagnosed with ASD (39 with Asperger syndrome and 26 with autism) and 33 controls who did not differ significantly in age or gender.ResultsVBM revealed that subjects with ASD had a significant reduction in grey-matter volume of medial temporal, fusiform and cerebellar regions, and in white matter of the brainstem and cerebellar regions. Furthermore, within the subjects with ASD, brain anatomy varied with clinical phenotype. Those with autism demonstrated an increase in grey matter in frontal and temporal lobe regions that was not present in those with Asperger syndrome.ConclusionsAdults with ASD have significant differences from controls in the anatomy of brain regions implicated in behaviours characterizing the disorder, and this differs according to clinical subtype.

2007 ◽  
Vol 191 (3) ◽  
pp. 224-228 ◽  
Author(s):  
Michaelc. Craig ◽  
Shahid H. Zaman ◽  
Eileen M. Daly ◽  
William J. Cutter ◽  
Dene M. W. Robertson ◽  
...  

BackgroundOur understanding of anatomical differences in people with autistic-spectrum disorder, is based on mixed-gender or male samples.AimsTo study regional grey-matter and white-matter differences in the brains of women with autistic-spectrum disorder.MethodWe compared the brain anatomy of 14 adult women with autistic-spectrum disorder with 19 controls using volumetric magnetic resonance imaging and voxel-based morphometry Results Women with autistic-spectrum disorder had a smaller density bilaterally of grey matter in the frontotemporal cortices and limbic system, and of white matter in the temporal lobes (anterior) and pons. In contrast, they had a larger white-matter density bilaterally in regions of the association and projection fibres of the frontal, parietal, posterior temporal and occipital lobes, in the commissural fibres of the corpus callosum (splenium) and cerebellum (anterior lobe). Further, we found a negative relationship between reduced grey-matter density in right limbic regions and social communication ability.ConclusionsWomen with autistic-spectrum disorder have significant differences in brain anatomy from controls, in brain regions previously reported as abnormal in adult men with the disorder. Some anatomical differences may be related to clinical symptoms.


2021 ◽  
Author(s):  
Hyeokmoon Kweon ◽  
Gokhan Aydogan ◽  
Alain Dagher ◽  
Danilo Bzdok ◽  
Christian C Ruff ◽  
...  

Recent studies report that socioeconomic status (SES) correlates with brain structure. Yet, such findings are variable and little is known about underlying causes. We present a well-powered voxel-based analysis of grey matter volume (GMV) across levels of SES, finding many small SES effects widely distributed across the brain, including cortical, subcortical and cerebellar regions. We also construct a polygenic index of SES to control for the additive effects of common genetic variation related to SES, which attenuates observed SES-GMV relations, to different degrees in different areas. Remaining variance, which may be attributable to environmental factors, is substantially accounted for by body mass index, a marker for lifestyle related to SES. In sum, SES affects multiple brain regions through measurable genetic and environmental effects.


NeuroImage ◽  
2001 ◽  
Vol 13 (6) ◽  
pp. 1097
Author(s):  
N. Schmitz ◽  
G. McAlonan ◽  
E.M. Daly ◽  
C.J. Moore ◽  
A. Simmons ◽  
...  

2018 ◽  
Vol 15 (2) ◽  
pp. 99
Author(s):  
Oktafian Farhan ◽  
Agus Subekti

Autisme merupakan disabilitas perkembangan yang dialami sepanjang hidup penderita Autistic Spectrum Disorder (ASD). Semakin cepat ditangani, semakin besar kemungkinan anak akan kembali normal. Untuk alasan ini, diperlukan metode baru yang dapat membantu orang tua dengan cepat mengenali gejala autisme pada anak-anak mereka. Dalam studi sebelumnya yang dilakukan oleh Fadi Fayez Tabhtah, suatu data set dihasilkan untuk mendeteksi apakah seorang anak memiliki autisme atau tidak. Tetapi penelitiannya hanya menghasilkan data set, ia tidak memeriksa lebih lanjut dimana algoritma cocok untuk data set yang telah dihasilkan. Atribut data set ternyata memiliki nilai yang salah, yang mengundang pertanyaan tentang keakurasian data. Dalam penelitian ini peneliti menggunakan metode CRISP-DM dan menguji keakuratan data set penelitian sebelumnya menggunakan algoritma C.45. Selanjutnya, aplikasi WEKA menggunakan pemilihan fitur dan pengaruh dari nilai yang salah untuk setiap atribut dan menemukan atribut yang paling signifikan. Atribut-atribut ini kemudian diuji dengan algoritma C.45 sehingga model prediksi dari data set diperoleh. Atribut A6 dari perhitungan pohon keputusan tidak muncul sama sekali sebagai cabang. Sebuah model baru diperoleh di mana atribut A6 dihilangkan, sehingga ketika diukur oleh algoritma C.45, nilai akurasi yang lebih baik diperoleh. Hasil model baru kemudian diuji pada data kuesioner baru, yang menghasilkan prediksi yang tepat.


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