Functional differentiation between cerebral and cerebellar white matter in word decoding and automaticity: a diffusion MRI study

The involvement of both the cerebrum and the cerebellum in reading processes has been acknowledged in previous research, yet their specific contributions remained unclear. In this study, we employed machine learning techniques and diffusion tensor imaging (DTI) to elucidate the respective roles of t...

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Published inCortex Vol. 190; pp. 131 - 145
Main Authors Wei, Yue, Ling, Li, Liu, Shi Kuang, Luo, Yue-Jia, Li, Hehui
Format Journal Article
LanguageEnglish
Published Italy Elsevier Ltd 01.09.2025
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Online AccessGet full text
ISSN0010-9452
1973-8102
1973-8102
DOI10.1016/j.cortex.2025.06.011

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Abstract The involvement of both the cerebrum and the cerebellum in reading processes has been acknowledged in previous research, yet their specific contributions remained unclear. In this study, we employed machine learning techniques and diffusion tensor imaging (DTI) to elucidate the respective roles of the cerebrum and the cerebellum in reading in adult readers (n = 109, 63 females, mean age = 21 years). We discovered that fractional anisotropy (FA) across the entire brain effectively differentiated good readers from those with poorer reading abilities. Furthermore, compared to the FA within the cerebellum, FA within the cerebrum demonstrated superior performance in identifying readers with better word decoding abilities. In contrast, compared to FA within the cerebellum, the model based on cerebro-cerebellar FA was more effective in distinguishing readers with varying levels of automaticity. These findings were validated through diverse methods, including brain-behavioral association analysis, support vector machine algorithms, and logistic regression. Our results provide evidence for a functional differentiation between the cerebrum and the cerebellum in word reading. Specifically, cerebral white matters are closely associated with word decoding abilities, whereas cerebro-cerebellar connections appear to play a role in supporting automatized skills.
AbstractList The involvement of both the cerebrum and the cerebellum in reading processes has been acknowledged in previous research, yet their specific contributions remained unclear. In this study, we employed machine learning techniques and diffusion tensor imaging (DTI) to elucidate the respective roles of the cerebrum and the cerebellum in reading in adult readers (n = 109, 63 females, mean age = 21 years). We discovered that fractional anisotropy (FA) across the entire brain effectively differentiated good readers from those with poorer reading abilities. Furthermore, compared to the FA within the cerebellum, FA within the cerebrum demonstrated superior performance in identifying readers with better word decoding abilities. In contrast, compared to FA within the cerebellum, the model based on cerebro-cerebellar FA was more effective in distinguishing readers with varying levels of automaticity. These findings were validated through diverse methods, including brain-behavioral association analysis, support vector machine algorithms, and logistic regression. Our results provide evidence for a functional differentiation between the cerebrum and the cerebellum in word reading. Specifically, cerebral white matters are closely associated with word decoding abilities, whereas cerebro-cerebellar connections appear to play a role in supporting automatized skills.
The involvement of both the cerebrum and the cerebellum in reading processes has been acknowledged in previous research, yet their specific contributions remained unclear. In this study, we employed machine learning techniques and diffusion tensor imaging (DTI) to elucidate the respective roles of the cerebrum and the cerebellum in reading in adult readers (n = 109, 63 females, mean age = 21 years). We discovered that fractional anisotropy (FA) across the entire brain effectively differentiated good readers from those with poorer reading abilities. Furthermore, compared to the FA within the cerebellum, FA within the cerebrum demonstrated superior performance in identifying readers with better word decoding abilities. In contrast, compared to FA within the cerebellum, the model based on cerebro-cerebellar FA was more effective in distinguishing readers with varying levels of automaticity. These findings were validated through diverse methods, including brain-behavioral association analysis, support vector machine algorithms, and logistic regression. Our results provide evidence for a functional differentiation between the cerebrum and the cerebellum in word reading. Specifically, cerebral white matters are closely associated with word decoding abilities, whereas cerebro-cerebellar connections appear to play a role in supporting automatized skills.The involvement of both the cerebrum and the cerebellum in reading processes has been acknowledged in previous research, yet their specific contributions remained unclear. In this study, we employed machine learning techniques and diffusion tensor imaging (DTI) to elucidate the respective roles of the cerebrum and the cerebellum in reading in adult readers (n = 109, 63 females, mean age = 21 years). We discovered that fractional anisotropy (FA) across the entire brain effectively differentiated good readers from those with poorer reading abilities. Furthermore, compared to the FA within the cerebellum, FA within the cerebrum demonstrated superior performance in identifying readers with better word decoding abilities. In contrast, compared to FA within the cerebellum, the model based on cerebro-cerebellar FA was more effective in distinguishing readers with varying levels of automaticity. These findings were validated through diverse methods, including brain-behavioral association analysis, support vector machine algorithms, and logistic regression. Our results provide evidence for a functional differentiation between the cerebrum and the cerebellum in word reading. Specifically, cerebral white matters are closely associated with word decoding abilities, whereas cerebro-cerebellar connections appear to play a role in supporting automatized skills.
Author Li, Hehui
Ling, Li
Luo, Yue-Jia
Liu, Shi Kuang
Wei, Yue
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Keywords Automaticity
The cerebellum
Functional differentiation
Word reading
The cerebrum
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Snippet The involvement of both the cerebrum and the cerebellum in reading processes has been acknowledged in previous research, yet their specific contributions...
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SubjectTerms Adolescent
Adult
Anisotropy
Automaticity
Cerebellum - diagnostic imaging
Cerebellum - physiology
Cerebrum - diagnostic imaging
Cerebrum - physiology
Diffusion Magnetic Resonance Imaging - methods
Diffusion Tensor Imaging - methods
Female
Functional differentiation
Humans
Machine Learning
Male
Reading
Support Vector Machine
The cerebellum
The cerebrum
White Matter - diagnostic imaging
White Matter - physiology
Word reading
Young Adult
Title Functional differentiation between cerebral and cerebellar white matter in word decoding and automaticity: a diffusion MRI study
URI https://dx.doi.org/10.1016/j.cortex.2025.06.011
https://www.ncbi.nlm.nih.gov/pubmed/40663890
https://www.proquest.com/docview/3230525443
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