Quantitative electroencephalography was assessed in dogs under controlled, 2% end-tidal isoflurane anesthetic conditions, and each variable at each electrode site was tested for normal distribution. With the quantitative electroencephalographic system used, 16 values for each of 21 electrode sites were evaluated. Absolute power ratios also were evaluated. The methods for quantitative electroencephalographic recording and analysis appear to be readily adaptable to the dog. Most of the data do not conform to a normal distribution. Therefore, distribution-free nonparametric statistics should be used when looking for differences under experimental or clinical conditions. Quantitative electroencephalography appears to be a sensitive noninvasive method that could be used to evaluate brain function under anesthetic, clinical, and experimental settings.
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Int J Surg
January 2025
Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Nanjing, Jiangsu, China.
Background: Type A aortic dissection (TAAD) remains a significant challenge in cardiac surgery, presenting high risks of adverse outcomes such as permanent neurological dysfunction and mortality despite advances in medical technology and surgical techniques. This study investigates the use of quantitative electroencephalography (QEEG) to monitor and predict neurological outcomes during the perioperative period in TAAD patients.
Methods: This prospective observational study was conducted at the hospital, involving patients undergoing TAAD surgery from February 2022 to January 2023.
Neurotherapeutics
January 2025
Department of Neurology, Massachusetts General Hospital, Boston MA, USA. Electronic address:
Electroencephalography (EEG) is invaluable in the management of acute neurological emergencies. Characteristic EEG changes have been identified in diverse neurologic conditions including stroke, trauma, and anoxia, and the increased utilization of continuous EEG (cEEG) has identified potentially harmful activity even in patients without overt clinical signs or neurologic diagnoses. Manual annotation by expert neurophysiologists is a major resource limitation in investigating the prognostic and therapeutic implications of these EEG patterns and in expanding EEG use to a broader set of patients who are likely to benefit.
View Article and Find Full Text PDFFront Psychiatry
January 2025
Department of Psychiatry, Kemal Arıkan Psychiatry Clinic, Istanbul, Türkiye.
Background: F-8-coil repetitive transcranial magnetic stimulation (rTMS) and H-1-coil deep repetitive transcranial magnetic stimulation (dTMS) have been indicated for the treatment of major depressive disorder (MDD) in adult patients by applying different treatment protocols. Nevertheless, the evidence for long-term electrophysiological alterations in the cortex following prolonged TMS interventions, as assessed by quantitative electroencephalography (qEEG), remains insufficiently explored. This study aims to demonstrate the qEEG-based distinctions between rTMS and dTMS in the management of depression and to evaluate the potential correlation between the electrophysiological changes induced by these two distinct TMS interventions and the clinical improvement in depressive and anxiety symptoms.
View Article and Find Full Text PDFFunct Integr Genomics
January 2025
Department of Radiology, The Second Xiangya Hospital of Central South University, No. 139, Renmin Middle Road, Furong District, Changsha City, Hunan Province, 410011, China.
Post-traumatic epilepsy (PTE) is a debilitating chronic outcome of traumatic brain injury (TBI). Although FTO has been reported as a possible intervention target of TBI, its precise roles in the PTE remain incompletely understood. Here we used mild or serious mice TBI model to probe the role and molecular mechanism of FTO in PTE.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130.
Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions.
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