AIMC Topic: Cerebral Cortex

Clear Filters Showing 31 to 40 of 280 articles

Neuroimaging Insights: Structural Changes and Classification in Ménière's Disease.

Ear and hearing
OBJECTIVES: This study aimed to comprehensively investigate the neuroanatomical alterations associated with idiopathic Ménière's disease (MD) using voxel-based morphometry and surface-based morphometry techniques. The primary objective was to explore...

Longitudinally consistent registration and parcellation of cortical surfaces using semi-supervised learning.

Medical image analysis
Temporally consistent and accurate registration and parcellation of longitudinal cortical surfaces is of great importance in studying longitudinal morphological and functional changes of human brains. However, most existing methods are developed for ...

Machine learning approach for recognition and morphological analysis of isolated astrocytes in phase contrast microscopy.

Scientific reports
Astrocytes are glycolytically active cells in the central nervous system playing a crucial role in various brain processes from homeostasis to neurotransmission. Astrocytes possess a complex branched morphology, frequently examined by fluorescent mic...

End-to-end deep learning approach to mouse behavior classification from cortex-wide calcium imaging.

PLoS computational biology
Deep learning is a powerful tool for neural decoding, broadly applied to systems neuroscience and clinical studies. Interpretable and transparent models that can explain neural decoding for intended behaviors are crucial to identifying essential feat...

Enhancing neural encoding models for naturalistic perception with a multi-level integration of deep neural networks and cortical networks.

Science bulletin
Cognitive neuroscience aims to develop computational models that can accurately predict and explain neural responses to sensory inputs in the cortex. Recent studies attempt to leverage the representation power of deep neural networks (DNNs) to predic...

A thermodynamical model of non-deterministic computation in cortical neural networks.

Physical biology
Neuronal populations in the cerebral cortex engage in probabilistic coding, effectively encoding the state of the surrounding environment with high accuracy and extraordinary energy efficiency. A new approach models the inherently probabilistic natur...

Facemap: a framework for modeling neural activity based on orofacial tracking.

Nature neuroscience
Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relat...

A state-of-the-art review on deep learning for estimating eloquent cortex from resting-state fMRI.

Neurosurgical review
Deep learning algorithms have greatly improved our ability to estimate eloquent cortex regions from resting-state brain scans for patients about to undergo neurosurgery. The use of deep learning has the potential to fully automate functional mapping ...

High-resolution CMOS-based biosensor for assessing hippocampal circuit dynamics in experience-dependent plasticity.

Biosensors & bioelectronics
Experiential richness creates tissue-level changes and synaptic plasticity as patterns emerge from rhythmic spatiotemporal activity of large interconnected neuronal assemblies. Despite numerous experimental and computational approaches at different s...

Accessing the brain with soft deployable electrocorticography arrays.

Science robotics
Soft robotics facilitates the deployment of large radial electrode arrays on the brain cortex through small craniotomies.