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What is the pathophysiology of inflammation-induced cortical injury in the perinatal brain?
Neural Regen Res
January 2025
The Ritchie Centre, Hudson Institute of Medical Research, Melbourne, VIC, Australia.
Perinatal exposure to infection/inflammation is highly associated with neural injury, and subsequent impaired cortical growth, disturbances in neuronal connectivity, and impaired neurodevelopment. However, our understanding of the pathophysiological substrate underpinning these changes in brain structure and function is limited. The objective of this review is to summarize the growing evidence from animal trials and human cohort studies that suggest exposure to infection/ inflammation during the perinatal period promotes regional impairments in neuronal maturation and function, including loss of high-frequency electroencephalographic activity, and reduced growth and arborization of cortical dendrites and dendritic spines resulting in reduced cortical volume.
View Article and Find Full Text PDFRhythmic EEG patterns: The oldest idea in the EEG world, but without an obvious definition.
Clin Neurophysiol
January 2025
Epilepsy and EEG Unit, Johns Hopkins Bayview Medical Center, Baltimore, MD, USA.
The word "rhythmic" was quickly introduced in the vocabulary of the electroencephalographers with the discovery of the alpha rhythm and typical discharges of spike-and-waves at 3 Hz in childhood absence epilepsy, but without any definition until recently. In its last revision (2017), the International Federation of Clinical Neurophysiology proposed a specific definition. The word "rhythmic" is "applied to regular waves occurring at a constant period and of relatively uniform morphology.
View Article and Find Full Text PDFFew-shot transfer learning for individualized braking intent detection on neuromorphic hardware.
J Neural Eng
January 2025
Mechanical and Aerospace, Missouri University of Science and Technology, 400 W 13th St., Rolla, Missouri, 65409, UNITED STATES.
This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a BrainChip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used group-level, models using electroencephalographic data. The efficacy of the method is studied on an advanced driver assist system related task of predicting braking intention. \emph{Approach}: Data are collected from participants operating an NVIDIA JetBot on a testbed simulating urban streets for three different scenarios.
View Article and Find Full Text PDFRecognizing drivers' sleep onset by detecting slow eye movement using a parallel multimodal one-dimensional convolutional neural network.
Comput Methods Biomech Biomed Engin
January 2025
School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, Changzhou University, Changzhou, P.R. China.
Slow eye movements (SEMs) are a reliable physiological marker of drivers' sleep onset, often accompanied by EEG alpha wave attenuation. A parallel multimodal 1D convolutional neural network (PM-1D-CNN) model is proposed to classify SEMs. The model uses two parallel 1D-CNN blocks to extract features from EOG and EEG signals, which are then fused and fed into fully connected layers for classification.
View Article and Find Full Text PDFSTIT-Net- A Wavelet based Convolutional Transformer Model for Motor Imagery EEG Signal Classification in the Sensorimotor Bands.
Clin EEG Neurosci
January 2025
Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, India.
Motor Imagery (MI) electroencephalographic (EEG) signal classification is a pioneer research branch essential for mobility rehabilitation. This paper proposes an end-to-end hybrid deep network "Spatio Temporal Inception Transformer Network (STIT-Net)" model for MI classification. Discrete Wavelet Transform (DWT) is used to derive the alpha (8-13) Hz and beta (13-30) Hz EEG sub bands which are dominant during motor tasks to enhance the performance of the proposed work.
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