Unveiling critical ADHD biomarkers in limbic system and cerebellum using a binary hypothesis testing approach

Ying Chen; Lele Wang; Zhixin Li; Yibin Tang; Zhan Huan; Ying Chen; Lele Wang; Zhixin Li; Yibin Tang; Zhan Huan

doi:10.3934/mbe.2024256

Mathematical Biosciences and Engineering

2024, Volume 21, Issue 4: 5803-5825. doi: 10.3934/mbe.2024256

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Research article

Unveiling critical ADHD biomarkers in limbic system and cerebellum using a binary hypothesis testing approach

1.
School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213159, China
2.
College of Information Science and Engineering, Hohai University, Changzhou 213200, China

Academic Editor: Giuseppe Ciaburro

Received: 30 December 2023 Revised: 13 March 2024 Accepted: 11 April 2024 Published: 28 April 2024

Attention deficit hyperactivity disorder (ADHD) is a common childhood developmental disorder. In recent years, pattern recognition methods have been increasingly applied to neuroimaging studies of ADHD. However, these methods often suffer from limited accuracy and interpretability, impeding their contribution to the identification of ADHD-related biomarkers. To address these limitations, we applied the amplitude of low-frequency fluctuation (ALFF) results for the limbic system and cerebellar network as input data and conducted a binary hypothesis testing framework for ADHD biomarker detection. Our study on the ADHD-200 dataset at multiple sites resulted in an average classification accuracy of 93%, indicating strong discriminative power of the input brain regions between the ADHD and control groups. Moreover, our approach identified critical brain regions, including the thalamus, hippocampal gyrus, and cerebellum Crus 2, as biomarkers. Overall, this investigation uncovered potential ADHD biomarkers in the limbic system and cerebellar network through the use of ALFF realizing highly credible results, which can provide new insights for ADHD diagnosis and treatment.
- ADHD,
- binary hypothesis,
- biomarker detection,
- limbic system,
- cerebellum
Citation: Ying Chen, Lele Wang, Zhixin Li, Yibin Tang, Zhan Huan. Unveiling critical ADHD biomarkers in limbic system and cerebellum using a binary hypothesis testing approach[J]. Mathematical Biosciences and Engineering, 2024, 21(4): 5803-5825. doi: 10.3934/mbe.2024256

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Abstract

Attention deficit hyperactivity disorder (ADHD) is a common childhood developmental disorder. In recent years, pattern recognition methods have been increasingly applied to neuroimaging studies of ADHD. However, these methods often suffer from limited accuracy and interpretability, impeding their contribution to the identification of ADHD-related biomarkers. To address these limitations, we applied the amplitude of low-frequency fluctuation (ALFF) results for the limbic system and cerebellar network as input data and conducted a binary hypothesis testing framework for ADHD biomarker detection. Our study on the ADHD-200 dataset at multiple sites resulted in an average classification accuracy of 93%, indicating strong discriminative power of the input brain regions between the ADHD and control groups. Moreover, our approach identified critical brain regions, including the thalamus, hippocampal gyrus, and cerebellum Crus 2, as biomarkers. Overall, this investigation uncovered potential ADHD biomarkers in the limbic system and cerebellar network through the use of ALFF realizing highly credible results, which can provide new insights for ADHD diagnosis and treatment.

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