AIMC Topic: Brain

Clear Filters Showing 381 to 390 of 4413 articles

Transcriptomic analyses of human brains with Alzheimer's disease identified dysregulated epilepsy-causing genes.

Epilepsy & behavior : E&B
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
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
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...

The GluN3-containing NMDA receptors.

Channels (Austin, Tex.)
N-methyl-D-aspartate receptors (NMDARs) are heterotetrameric ion channels that play crucial roles in brain function. Among all the NMDAR subtypes, GluN1-N3 receptors exhibit unique agonist binding and gating properties. Unlike "conventional" GluN1-N2...

Deep learning-based EEG source imaging is robust under varying electrode configurations.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
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
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
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...

A deep learning approach for quantifying CT perfusion parameters in stroke.

Biomedical physics & engineering express
. Computed tomography perfusion (CTP) imaging is widely used for assessing acute ischemic stroke. However, conventional methods for quantifying CTP images, such as singular value decomposition (SVD), often lead to oscillations in the estimated residu...

Brain-guided convolutional neural networks reveal task-specific representations in scene processing.

Scientific reports
Scene categorization is the dominant proxy for visual understanding, yet humans can perform a large number of visual tasks within any scene. Consequently, we know little about how different tasks change how a scene is processed, represented, and its ...

Multi-scale convolutional transformer network for motor imagery brain-computer interface.

Scientific reports
Brain-computer interface (BCI) systems allow users to communicate with external devices by translating neural signals into real-time commands. Convolutional neural networks (CNNs) have been effectively utilized for decoding motor imagery electroencep...