Functional and Anatomical Growth Charts of the Cerebellum from Infancy to Young Adulthood

1250 

Abstract Submission 

Aikaterina Manoli^1,2,3,4, Neville Magielse^5,6,1, Felix Hoffstaedter^7,6, Nilsu Saglam¹, Lorenz Ahle¹, Ceyda Yalcin¹, Hidir Arslan¹, Charlotte Grosse Wiesmann¹, Jörn Diedrichsen^8,9,10, Sofie Valk^1,3,6

¹Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ²International Max Planck Research School on Cognitive Neuroimaging, Leipzig, Germany, ³Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany, ⁴Faculty of Medicine, Leipzig University, Leipzig, Germany, ⁵INM-7, Research Center Jülich, Jülich, NRW, ⁶Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany, ⁷Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, NRW, ⁸The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada, ⁹Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Ontario, Canada, ¹⁰Department of Computer Science, University of Western Ontario, London, Ontario, Canada

Aikaterina Manoli  
Max Planck Institute for Human Cognitive and Brain Sciences|International Max Planck Research School on Cognitive Neuroimaging|Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich|Faculty of Medicine, Leipzig University
Leipzig, Germany|Leipzig, Germany|Jülich, Germany|Leipzig, Germany

Neville Magielse  
INM-7, Research Center Jülich|Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf|Max Planck Institute for Human Cognitive and Brain Sciences
Jülich, NRW|Düsseldorf, Germany|Leipzig, Germany

Felix Hoffstaedter  
Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich|Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf
Jülich, NRW|Düsseldorf, Germany

Nilsu Saglam  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany

Lorenz Ahle  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany

Ceyda Yalcin  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany

Hidir Arslan  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany

Charlotte Grosse Wiesmann  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany

Jörn Diedrichsen  
The Brain and Mind Institute, University of Western Ontario|Department of Statistical and Actuarial Sciences, University of Western Ontario|Department of Computer Science, University of Western Ontario
London, Ontario, Canada|London, Ontario, Canada|London, Ontario, Canada

Sofie Valk  
Max Planck Institute for Human Cognitive and Brain Sciences|Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich|Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf
Leipzig, Germany|Jülich, Germany|Düsseldorf, Germany

Apart from its role in motor processing, the cerebellum is involved in a wide range of cognitive functions, extending its relevance for clinical conditions. Accumulating evidence from paediatric populations suggests that early-life cerebellar abnormalities are linked to neurocognitive deficits in autism and schizophrenia (Olson et al., 2023). Despite these periods being closely linked to the development of neuropsychiatric disorders, a normative framework of cerebellar development is currently lacking. Here, we constructed normative models of cerebellar volumetric growth from infancy to adulthood, by focusing on both anatomical and functional cerebellar parcellations.

We leveraged open structural (T1-weighted) MRI data from the Baby Connectome Project (BCP; Howell et al., 2019) and the Lifespan Human Connectome Project in Development (HCP-D; Somerville et al., 2018) (N_total=993; age range: 0.5-22 years). Infant scans (< 2 years) were preprocessed with iBEAT (Dai et al., 2013), a toolbox optimized for infant brain processing and extraction. Child and adolescent scans (> 2 years) were processed with the standard HCP minimal preprocessing pipelines (Glasser et al., 2013). We obtained native-space anatomical volumes using ACAPULCO (Han et al., 2020), a convolutional neural network-based algorithm that segments the cerebellum into 28 lobules. For functional models, we used an atlas of 10 cerebellar regions spanning cognitive, affective and motor domains (King et al., 2019). We extracted functional parcel volumes by resampling the MNI-space atlas to each subject's native space with trilinear interpolation. Manual correction of anatomical and functional parcel masks was employed to account for over- or under-inclusion of cerebellar boundaries. We constructed anatomical and functional growth models using hierarchical Bayesian regression (HBR), which allowed us to control for sex and scanner site variability by specifying them as batch effects (Gaiser et al., 2023). We generated linear and 3rd-order b-spline models of cerebellar growth across age for each parcel, after splitting the dataset into a training (80%) and test set (20%). Inference was performed with Markov chain Monte Carlo methods (4 chains with 2000 samples). Finally, linear and b-spline model performance was compared via leave-one-out cross-validation.

We found divergent effects of age on cerebellar volumes within anatomical (Fig. 1A) and functional parcels (Fig. 1B). Anterior anatomical parcels (lobules I–VI) demonstrated larger age-related effects (i.e., steeper growth trajectories) compared to posterior parcels (lobules VII–IX). Contrarily, all functional parcels demonstrated consistent volumetric increases across age. Lastly, models stratified by sex revealed steeper growth trajectories for males compared to females, with females also demonstrating patterns of slight volumetric decrease across development in anatomical parcels.

We found differences in normative trajectories between anatomical and functional cerebellar parcellations. Functional regions, involved in distinct cognitive processes, demonstrated consistent volumetric growth, which could reflect improvement in cognitive tasks across age. By contrast, anatomical regions showed a posterior-anterior gradient, in which anterior volumes increased more steeply than posterior volumes. This can be interpreted in light of the lack of convergence between functional and anatomical boundaries in the cerebellum (King et al., 2019). Anterior anatomical regions, uniformly involved in motor functions, demonstrate consistent growth across development. Conversely, the size of posterior anatomical regions encompasses a mosaic of functional subregions, which span several anatomical boundaries. This highlights a greater relevance of functional maps of the cerebellum for early-life diagnosis of neurodevelopmental disorders, based on deviations from normative trajectories related to specific cognitive functions.

Early life, Adolescence, Aging ¹

Normal Brain Development: Fetus to Adolescence ²

Bayesian Modeling

Segmentation and Parcellation

Anatomy and Functional Systems

Cerebellum

Cognition

Development

Modeling

MRI

NORMAL HUMAN

Open Data

PEDIATRIC

Segmentation

STRUCTURAL MRI