AIMC Topic: Cerebellum

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Multivariate brain morphological patterns across mood disorders: key roles of frontotemporal and cerebellar areas.

BMJ mental health Jun 10, 2025
BACKGROUND: Differentiating major depressive disorder (MDD) from bipolar disorder (BD) remains a significant clinical challenge, as both disorders exhibit overlapping symptoms but require distinct treatment approaches. Advances in voxel-based morphom...
Humans Female Adult Male Magnetic Resonance Imaging Cerebellum Gray Matter Multivariate Analysis Middle Aged Depressive Disorder, Major Bipolar Disorder
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Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning.

PLoS computational biology Mar 17, 2025
Although the cerebellum is typically associated with supervised learning algorithms, it also exhibits extensive involvement in reward processing. In this study, we investigated the cerebellum's role in executing reinforcement learning algorithms, wit...
Algorithms Animals Male Mice Reinforcement, Psychology Supervised Machine Learning Computational Biology Purkinje Cells Cerebellum Models, Neurological Reward Mice, Inbred C57BL
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A deep learning strategy to identify cell types across species from high-density extracellular recordings.

Cell Feb 28, 2025
High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but fail to reveal cell type. Here, we develop a strategy to identify cell types from extracellular recordings in awake animals an...
Mice, Inbred C57BL Neurons Cerebellum Purkinje Cells Interneurons Optogenetics Deep Learning Mice Rats Animals Male
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DeepCERES: A deep learning method for cerebellar lobule segmentation using ultra-high resolution multimodal MRI.

NeuroImage Feb 6, 2025
This paper introduces a novel multimodal and high-resolution human brain cerebellum lobule segmentation method. Unlike current tools that operate at standard resolution (1 mm) or using mono-modal data, the proposed method improves cerebellum lobule s...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Female Adult Male Multimodal Imaging Cerebellum Neuroimaging Humans
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Prenatal Diagnostics Using Deep Learning: A Dual Approach to Plane Localization and Cerebellum Segmentation in Ultrasound Images.

Journal of clinical ultrasound : JCU Feb 3, 2025
OBJECTIVE: The fetal ultrasound examination is the significant task of mid-term pregnancy inspection and the accurate localization as well as the segmentation of the cerebellum is crucial for clinical diagnosis. This research focuses on developing de...
Humans Female Ultrasonography, Prenatal Deep Learning Neural Networks, Computer Cerebellum Pregnancy Neurodevelopmental Disorders
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A neuromechanics solution for adjustable robot compliance and accuracy.

Science robotics Jan 22, 2025
Robots have to adjust their motor behavior to changing environments and variable task requirements to successfully operate in the real world and physically interact with humans. Thus, robotics strives to enable a broad spectrum of adjustable motor be...
Muscle Contraction Biomechanical Phenomena Muscle, Skeletal Robotics Equipment Design Humans Torque Cerebellum Computer Simulation Viscosity
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Enhancing automatic sleep stage classification with cerebellar EEG and machine learning techniques.

Computers in biology and medicine Dec 10, 2024
Sleep disorders have become a significant health concern in modern society. To investigate and diagnose sleep disorders, sleep analysis has emerged as the primary research method. Conventional polysomnography primarily relies on cerebral electroencep...
Polysomnography Machine Learning Sleep Stages Signal Processing, Computer-Assisted Mice, Inbred C57BL Male Animals Electromyography Electroencephalography Mice Cerebellum
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Machine learning with multiple modalities of brain magnetic resonance imaging data to identify the presence of bipolar disorder.

Journal of affective disorders Sep 14, 2024
BACKGROUND: Bipolar disorder (BD) is a chronic psychiatric mood disorder that is solely diagnosed based on clinical symptoms. These symptoms often overlap with other psychiatric disorders. Efforts to use machine learning (ML) to create predictive mod...
Machine Learning Diffusion Magnetic Resonance Imaging Brain Female Adult Male Bipolar Disorder Humans Middle Aged Magnetic Resonance Imaging Case-Control Studies Cerebellum
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Convolutional Neural Network for Fully Automated Cerebellar Volumetry in Children in Comparison to Manual Segmentation and Developmental Trajectory of Cerebellar Volumes.

Cerebellum (London, England) Oct 13, 2023
The purpose of this study was to develop a fully automated and reliable volumetry of the cerebellum of children during infancy and childhood using deep learning algorithms in comparison to manual segmentation. In addition, the clinical usefulness of ...
Child Humans Image Processing, Computer-Assisted Neural Networks, Computer Deep Learning Magnetic Resonance Imaging Organ Size Male Retrospective Studies Adolescent Female Cerebellum Infant Child, Preschool Infant, Newborn
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CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation.

NeuroImage Oct 27, 2022
Quantifying the volume of the cerebellum and its lobes is of profound interest in various neurodegenerative and acquired diseases. Especially for the most common spinocerebellar ataxias (SCA), for which the first antisense oligonculeotide-base gene s...
Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Reproducibility of Results Cerebellum Deep Learning
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