AdvanDNN: Deep Neural Network Analysis of Neuroimaging for Identifying Vulnerable Brain Regions in Autism Spectrum Disorder
- Title
- AdvanDNN: Deep Neural Network Analysis of Neuroimaging for Identifying Vulnerable Brain Regions in Autism Spectrum Disorder
- Creator
- Lamani M.R.; Julian Benadit P.; Guruprasad C.
- Description
- Exploring the neurological framework of autism spectrum disorder (ASD) presents a significant challenge due to its diverse manifestations and cognitive impacts. This study introduces an innovative deep learning approach, employing an advanced deep neural network (AdvanDNN) model to identify and analyze brain regions vulnerable to ASD. Utilizing the AAL116 brain atlas for anatomical standardization, our model processes a comprehensive set of neuroimaging data, including structural and functional MRI scans, to discern distinct neural patterns associated with ASD. The AdvanDNN model, with its robust deep learning architecture, was meticulously trained and validated, demonstrating a notable accuracy of 91.17% in distinguishing between ASD-affected individuals and controls. This marks an improvement over the state of the art, contributing a significant advance to the diagnostic processes. Notably, the model identified a pronounced anticorrelation in brain function between anterior and posterior regions, corroborating existing empirical evidence of disrupted connectivity within ASD neurology. The analysis further pinpointed critical regions, such as the prefrontal cortex, amygdala, and temporal lobes, that exhibit significant deviations from typical developmental patterns. These findings illustrate the potential of deep learning in enhancing early detection and providing pathways for intervention. The application of the AdvanDNN model offers a promising direction for personalized treatment strategies and underscores the value of precision medicine in addressing neurodevelopmental disorders. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
- Source
- Lecture Notes in Electrical Engineering, Vol-1247 LNEE, pp. 497-510.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- AAL116 atlas; AdvanDNN; Autism spectrum disorder; Brain connectivity; Deep learning; Neuroimaging analysis
- Coverage
- Lamani M.R., CHRIST (Deemed to Be University), Kanmanike, Kumbalgodu, Mysore Road, Karnataka, Bangalore, 560074, India; Julian Benadit P., CHRIST (Deemed to Be University), Kanmanike, Kumbalgodu, Mysore Road, Karnataka, Bangalore, 560074, India; Guruprasad C., Departmentof Psychiatry, Bangalore Medical College & Research Institute (BMCRI), Karnataka, Bangalore, 560002, India
- Rights
- Restricted Access
- Relation
- ISSN: 18761100; ISBN: 978-981976713-7
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Lamani M.R.; Julian Benadit P.; Guruprasad C., “AdvanDNN: Deep Neural Network Analysis of Neuroimaging for Identifying Vulnerable Brain Regions in Autism Spectrum Disorder,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19008.