Functional magnetic resonance imagingMagnetic Resonance Imaging (MRI) (fMRI) has revolutionized the understanding of neural networks and brain function. It is a powerful non-invasive imaging technique that measures changes in blood flow and oxygenation levels in the brain, enabling the researchers to map neural activity and connectivity. While fMRI traditionally has lower temporal resolution compared to techniques like electroencephalography (EEG) or magnetoencephalography (MEG), recent advances such as multiband imaging have significantly improved its ability to capture rapid changes in neural activity. This is important for studying dynamic network interactions. fMRI has found a wide range of clinical applications, from pre-surgical planning in neurology to understanding the neural basis of mental health disorders. It has opened up new possibilities for personalized treatment approaches. Combining fMRI with other neuroimaging techniques like electroencephalography (EEG), magnetoencephalography (MEG), and positron emission tomography (PET) can provide a more comprehensive view of neural networks. This integration of data sources can enhance our understanding of brain function. Real-time fMRI combined with neurofeedback techniques may enable individuals to attain voluntary influence over their brain functions, potentially offering therapeutic benefits for a range of conditions.

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Progress and Prospects in Functional MRI (fMRI) Studies of Neural Networks

  • S. N. Kumar,
  • A. Lenin Fred,
  • H. Ajay Kumar,
  • Parasuraman Padmanabhan,
  • I. Christina Jane

摘要

Functional magnetic resonance imagingMagnetic Resonance Imaging (MRI) (fMRI) has revolutionized the understanding of neural networks and brain function. It is a powerful non-invasive imaging technique that measures changes in blood flow and oxygenation levels in the brain, enabling the researchers to map neural activity and connectivity. While fMRI traditionally has lower temporal resolution compared to techniques like electroencephalography (EEG) or magnetoencephalography (MEG), recent advances such as multiband imaging have significantly improved its ability to capture rapid changes in neural activity. This is important for studying dynamic network interactions. fMRI has found a wide range of clinical applications, from pre-surgical planning in neurology to understanding the neural basis of mental health disorders. It has opened up new possibilities for personalized treatment approaches. Combining fMRI with other neuroimaging techniques like electroencephalography (EEG), magnetoencephalography (MEG), and positron emission tomography (PET) can provide a more comprehensive view of neural networks. This integration of data sources can enhance our understanding of brain function. Real-time fMRI combined with neurofeedback techniques may enable individuals to attain voluntary influence over their brain functions, potentially offering therapeutic benefits for a range of conditions.