Identifying Neuroinflammation: The Diagnostic Potential of Spindling Excessive Beta in the EEG.

Publication date: Sep 24, 2025

This manuscript examines the pivotal role of neuroinflammation in the central nervous system (CNS), particularly considering the impact of the COVID-19 pandemic. Neuroinflammation serves as a defense mechanism against various insults, including toxins, infections, and trauma. However, if left untreated, neuroinflammation can become chronic, leading to significant symptomatic and structural brain damage. Notably, neuroinflammation can mimic psychological disorders, complicating diagnosis and treatment. Current diagnostic methods for neuroinflammation-such as lumbar punctures, MRIs, brain biopsies, blood tests, and PET scans-are often hindered by inaccuracy, invasiveness, and cost. This study posits that electroencephalography (EEG), particularly identifying spindling excessive beta (SEB) activity, offers a promising, non-invasive, and cost-effective alternative for detecting neuroinflammation. This study investigates the relationship between SEB activity and neuroinflammation, focusing on traumatic brain injury (TBI). Through statistical analysis of EEG data from 1,233 psychiatric patients, we identified and compared two groups: 75 non-benzodiazepine-using adults without TBI and 79 non-benzodiazepine using adults with TBI exhibiting SEB activity. We identified a significant prevalence of SEB in individuals with refractory psychiatric conditions, underscoring the significance of this biomarker for neuroinflammation. Furthermore, we examine the therapeutic implications of reducing SEB through interventions such as guanfacine combined with N-Acetyl Cysteine (NAC), photobiomodulation, and hyperbaric oxygen therapy, all of which have demonstrated efficacy in mitigating neuroinflammation. These findings suggest that EEG could play a transformative role in the early detection and management of neuroinflammatory conditions, paving the way for more personalized and effective treatments for mental health disorders.

Semantics

Original Article