AIMC Topic: Cerebellum

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Neural correlates of forward and backward walking in MS: insights from myelin water imaging.

Experimental brain research
Mobility impairments and increased fall risk are common in multiple sclerosis (MS), resulting from myelin degradation in motor pathways. While forward walking is a common mobility assessment, backward walking shows greater sensitivity in distinguishi...

Stimulus Contingency and Task Context Encoding within the Anterior Cingulate-Amygdala-Cerebellum Associative Learning Network.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Cerebellum (CB) interactions with forebrain systems contribute to learning cognitive and motor tasks, but the nature of these interactions is unknown. Trace eyeblink conditioning (EBC) is an excellent associative learning paradigm for examining inter...

Personalized MRI-based characterization of subcortical anomalies in Ataxia-Telangiectasia using deep-learning.

PloS one
BACKGROUND: Cerebellar atrophy is a known feature of ataxia-telangiectasia (A-T). However, basal ganglia dysfunction contributing to extrapyramidal movement disorders in A-T remains understudied.

Deep adversarial learning identifies ADHD-specific associations between apoptotic genes and white matter microstructure in frontal-striatum-cerebellum circuit.

Translational psychiatry
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by genetic predisposition and alterations in brain structural connectivity. While existing studies have established associations between genetic variants a...

Data-driven cognitive subtypes in major depressive disorder: Grey matter atrophy in the left fusiform gyrus and cerebellum.

Journal of affective disorders
BACKGROUND: This study aims to apply a semi-supervised machine learning approach for classifying major depressive disorder (MDD) patients into more homogeneous cognitive subtypes based on multidimensional cognitive profiles, and to perform multimodal...

Strategies to Decipher Neuron Identity from Extracellular Recordings in Behaving Nonhuman Primates.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Identification of the neuron type is critical when using extracellular recordings in awake, behaving animal subjects to understand computation in neural circuits. Yet, modern recording probes have limited power to resolve neuron identity. Here, we pr...

Specific Contribution of the Cerebellar Inferior Posterior Lobe to Motor Learning in Degenerative Cerebellar Ataxia.

Cerebellum (London, England)
BACKGROUND AND OBJECTIVE: Degenerative cerebellar ataxia, a group of progressive neurodegenerative disorders, is characterised by cerebellar atrophy and impaired motor learning. Using CerebNet, a deep learning algorithm for cerebellar segmentation, t...

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

BMJ mental health
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...

Linking cellular-level phenomena to brain architecture: the case of spiking cerebellar controllers.

Neural networks : the official journal of the International Neural Network Society
Linking cellular-level phenomena to brain architecture and behavior is a holy grail for theoretical and computational neuroscience. Advances in neuroinformatics have recently allowed scientists to embed spiking neural networks of the cerebellum with ...

Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning.

PLoS computational biology
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...