Depression, a mental health disorder, has emerged as one of the significant challenges in the global public health domain. Investigating the pathogenesis of depression and accurately assessing the symptomatic changes are fundamental to formulating effective clinical diagnosis and treatment strategies. Utilizing non-invasive brain imaging technologies such as functional magnetic resonance imaging and scalp electroencephalography, existing studies have confirmed that the onset of depression is closely associated with abnormal neural activities and altered functional connectivity in multiple brain regions. Magnetoencephalography, unaffected by tissue conductivity and skull thickness, boasts high spatial resolution and signal-to-noise ratio, offering unique advantages and significant value in revealing the abnormal brain mechanisms and neural characteristics of depression. This review, starting from the rhythmic characteristics, nonlinear dynamic features, and connectivity characteristics of magnetoencephalography in depression patients, revisits the research progress on magnetoencephalography features related to depression, discusses current issues and future development trends, and provides insights for the study of pathophysiological mechanisms, as well as for clinical diagnosis and treatment of depression.
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http://dx.doi.org/10.7507/1001-5515.202406072 | DOI Listing |
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
February 2025
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China.
Depression, a mental health disorder, has emerged as one of the significant challenges in the global public health domain. Investigating the pathogenesis of depression and accurately assessing the symptomatic changes are fundamental to formulating effective clinical diagnosis and treatment strategies. Utilizing non-invasive brain imaging technologies such as functional magnetic resonance imaging and scalp electroencephalography, existing studies have confirmed that the onset of depression is closely associated with abnormal neural activities and altered functional connectivity in multiple brain regions.
View Article and Find Full Text PDFJ Neurosci
February 2025
Department of Psychology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, China
The extraction and analysis of pitch underpin speech and music recognition, sound segregation, and other auditory tasks. Perceptually, pitch can be represented as a helix composed of two factors: height monotonically aligns with frequency, while chroma cyclically repeats at doubled frequencies. Although the early perceptual and neurophysiological mechanisms for extracting pitch from acoustic signals have been extensively investigated, the equally essential subsequent stages that bridge to high-level auditory cognition remain less well understood.
View Article and Find Full Text PDFJ Physiol
February 2025
Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Motor cortical high-gamma oscillations (60-90 Hz) occur at movement onset and are spatially focused over the contralateral primary motor cortex. Although high-gamma oscillations are widely recognized for their significance in human motor control, their precise function on a cortical level remains elusive. Importantly, their relevance in human stroke pathophysiology is unknown.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, 37 Xueyuan Rd., Haidian District, Beijing 100083, China.
Optically pumped magnetometer magnetoencephalography (OPM-MEG) represents a novel method for recording neural signals in the brain, offering the potential to measure critical neuroimaging characteristics such as effective brain networks. Effective brain networks describe the causal relationships and information flow between brain regions. In constructing effective brain networks using Granger causality, the noise in the multivariate autoregressive model (MVAR) is typically assumed to follow a Gaussian distribution.
View Article and Find Full Text PDFFront Neurol
December 2024
Department of Psychiatry, Shizuoka Psychiatric Medical Center, Shizuoka, Japan.
Recent studies focusing on neural activity captured by neuroimaging modalities have provided various metrics for elucidating the functional networks and dynamics of the entire brain. Functional magnetic resonance imaging (fMRI) can depict spatiotemporal functional neural networks and dynamic characteristics due to its excellent spatial resolution. However, its temporal resolution is limited.
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