AIMC Topic: Brain

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Neural xenografts contribute to long-term recovery in stroke via molecular graft-host crosstalk.

Nature communications
Stroke remains a leading cause of disability due to the brain's limited ability to regenerate damaged neural circuits. Here, we show that local transplantation of iPSC-derived neural progenitor cells (NPCs) improves brain repair and long-term functio...

Advantages of fully automated AI-enhanced algorithm (5D CNS+™) for generating a fetal neurosonogram in clinical routine.

Journal of perinatal medicine
OBJECTIVES: The objective was to demonstrate superiority of a fully vs. semi-automated approach (5D CNS+™) and to verify operators could handle and benefit from a fully automated rendering volumetric datasets to generate a complete fetal neurosonogra...

Multimodal MRI analysis selecting key brain features for machine learning based classification of diabetic neuropathic pain and phenotypes.

Journal of the neurological sciences
Cerebral alterations are associated with diabetic peripheral neuropathy (DPN) and neuropathic pain, including reductions in brain volumes, cortical thickness, sulcus depth, and alterations in metabolites and functional connectivity. This study combin...

Quercetagetin alleviates ischemic stroke injury by preserving macrophage/microglia homeostasis via inhibiting ACP5.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: The proinflammatory response triggered by macrophages/microglia plays a crucial role in the prognosis of acute ischemic stroke (AIS). Identifying novel targets to regulate the homeostasis of these cells is essential. Developing therapeuti...

Diffusion MRI of the prenatal fetal brain: a methodological scoping review.

NeuroImage
BACKGROUND: Fetal diffusion-weighted Magnetic Resonance Imaging (dMRI) represents a promising modality for the assessment of white matter fiber organization, microstructure and development during pregnancy. Over the past two decades, research using t...

Reinforcement learning at the interface of artificial intelligence and cognitive science.

Neuroscience
Reinforcement learning (RL) is a computational framework that models how agents learn from trial and error to make sequential decisions. Rooted in behavioural psychology, RL has become central to artificial intelligence and is increasingly applied in...

Brain stimulation preferentially influences long-range projections.

Science advances
Advances in brain stimulation have made it possible to target smaller and smaller regions for electromagnetic stimulation, in the hopes of producing increasingly focal neural effects. However, the brain is extensively interconnected, and the neurons ...

EEG Connectivity is an Objective Signature of Reduced Consciousness and Sleep Depth.

Brain topography
Different levels of reduced consciousness characterise human sleep stages at the behavioural level. On electroencephalography (EEG), the identification of sleep stages predominantly relies on localised oscillatory power within distinct frequency band...

Enhanced electrophysiological recordings in acute brain slices, spheroids, and organoids using 3D high-density multielectrode arrays.

PloS one
Recent advances in three-dimensional (3D) biological brain models in vitro and ex vivo are creating new opportunities to understand the complexity of neural networks but pose the technological challenge of obtaining high-throughput recordings of elec...