AIMC Topic: Brain
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Deconvolution of cell types and states in spatial multiomics utilizing TACIT.
Nature communications
Apr 21, 2025
Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning increasingly plays a role, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in...
Artificial intelligence-powered four-fold upscaling of human brain synthetic metabolite maps.
The Journal of international medical research
Apr 21, 2025
ObjectiveCompared with anatomical magnetic resonance imaging modalities, metabolite images from magnetic resonance spectroscopic imaging often suffer from low quality and detail due to their larger voxel sizes. Conventional interpolation techniques a...
Uncertainty mapping and probabilistic tractography using Simulation-based Inference in diffusion MRI: A comparison with classical Bayes.
Medical image analysis
Apr 20, 2025
Simulation-Based Inference (SBI) has recently emerged as a powerful framework for Bayesian inference: Neural networks are trained on simulations from a forward model, and learn to rapidly estimate posterior distributions. We here present an SBI frame...
Tailored self-supervised pretraining improves brain MRI diagnostic models.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 17, 2025
Self-supervised learning has shown potential in enhancing deep learning methods, yet its application in brain magnetic resonance imaging (MRI) analysis remains underexplored. This study seeks to leverage large-scale, unlabeled public brain MRI datase...
Transcriptomic analyses of human brains with Alzheimer's disease identified dysregulated epilepsy-causing genes.
Epilepsy & behavior : E&B
Apr 17, 2025
BACKGROUND & OBJECTIVE: Alzheimer's Disease (AD) patients at multiple stages of disease progression have a high prevalence of seizures. However, whether AD and epilepsy share pathophysiological changes remains poorly defined. In this study, we levera...
From social effort to social behavior: An integrated neural model for social motivation.
Neuroscience and biobehavioral reviews
Apr 17, 2025
As humans rely on social groups for survival, social motivation is central to behavior and well-being. Here we define social motivation as the effort that initiates and directs behavior towards social outcomes, with the goal of satisfying our fundame...
Joint resting state and structural networks characterize pediatric bipolar patients compared to healthy controls: a multimodal fusion approach.
NeuroImage
Apr 17, 2025
Pediatric bipolar disorder (PBD) is a highly debilitating condition, characterized by alternating episodes of mania and depression, with intervening periods of remission. Limited information is available about the functional and structural abnormalit...
Deep learning-based EEG source imaging is robust under varying electrode configurations.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Apr 16, 2025
OBJECTIVES: Previous research has underscored the necessity of high-density EEG for accurate and reliable EEG source imaging (ESI) results with conventional ESI methods, limiting their utility in clinical settings with only low-density EEG available....
Assessment of AI-accelerated T2-weighted brain MRI, based on clinical ratings and image quality evaluation.
European journal of radiology
Apr 16, 2025
OBJECTIVE: To compare clinical ratings and signal-to-noise ratio (SNR) measures of a commercially available Deep Learning-based MRI reconstruction method (T2) against conventional T2- turbo spin echo brain MRI (T2).
Topology optimization of random memristors for input-aware dynamic SNN.
Science advances
Apr 16, 2025
Machine learning has advanced unprecedentedly, exemplified by GPT-4 and SORA. However, they cannot parallel human brains in efficiency and adaptability due to differences in signal representation, optimization, runtime reconfigurability, and hardware...
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