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Related Concept Videos

Brain Imaging01:14

Brain Imaging

263
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
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Neural Circuits01:25

Neural Circuits

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
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Organization of the Brain01:30

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The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
Hindbrain
The hindbrain, located at the base of the brain, plays a vital role in regulating automatic processes that sustain life. It includes the medulla oblongata, which is essential for...
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Updated: Jul 25, 2025

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
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Generative AI for brain image computing and brain network computing: a review.

Changwei Gong1,2, Changhong Jing1,2, Xuhang Chen1,3

  • 1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Frontiers in Neuroscience
|June 29, 2023
PubMed
Summary
This summary is machine-generated.

Generative artificial intelligence (AI) is advancing brain imaging and network analysis. This review explores AI models, tasks, and challenges in neuroimaging for better brain feature extraction and connectivity reconstruction.

Keywords:
brain imagingbrain networkdiffusion modelgenerative adversarial networkgenerative modelsvariational autoencoder

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Area of Science:

  • Neuroimaging
  • Artificial Intelligence
  • Computational Neuroscience

Background:

  • Non-invasive brain imaging techniques have advanced significantly.
  • Generative artificial intelligence (AI) has grown substantially, creating new data from existing patterns.
  • Integrating generative AI with neuroimaging offers new possibilities for brain research.

Purpose of the Study:

  • To review advanced generative AI models, tasks, challenges, and prospects in brain imaging and network computing.
  • To provide a comprehensive overview of current generative AI techniques in neuroimaging.
  • To focus on novel methodological approaches and applications in the field.

Main Methods:

  • Discussed fundamental theories and algorithms of four classic generative models.
  • Systematically surveyed and categorized tasks including co-registration, super-resolution, enhancement, classification, segmentation, cross-modality, brain network analysis, and brain decoding.
  • Highlighted challenges and future directions in the latest work.

Main Results:

  • Identified key generative AI applications in neuroimaging, such as feature extraction and network reconstruction.
  • Categorized various tasks where generative AI is applied within brain imaging.
  • Provided insights into the current state and potential of generative AI in neuroscience.

Conclusions:

  • Generative AI in neuroimaging is a promising field with significant potential for advancing brain mapping and network analysis.
  • Further research is needed to address current challenges and explore future directions.
  • This review offers a foundational understanding for researchers in generative AI and neuroimaging.