A Qualitative Study of the Decision-Making and Needs of Adolescents and Young Adults With Acetabular Dysplasia Regarding Periacetabular Osteotomy.
Authors: Augi TH, Luck C, Disantis AE, Stransky OM, McClincy MP, Kazmerski TM
Journal: Journal of the Pediatric Orthopaedic Society of North America
mental health
psychology
open access
Abstract
Tinnitus, defined as the perception of sound in the absence of an external acoustic stimulus, is a prevalent and distressing neurological disorder that affects approximately 10%–15% of the adult population worldwide. While tinnitus is frequently associated with hearing loss, a substantial proportion of individuals with clinically normal hearing thresholds (pure-tone average [PTA] ≤ 25 dB HL at 0.5–4 kHz) also experience persistent tinnitus. In such cases, the peripheral trigger may involve subclinical pathologies not captured by standard audiometry—most notably cochlear synaptopathy (the loss of inner hair cell ribbon synapses) or high-frequency hearing loss above 8 kHz—which in turn initiate central maladaptive plasticity and network-level dysregulation, operationalized as functional reconfiguration of large-scale brain networks (including the salience, executive, and auditory networks) driven by reduced thalamocortical sensory input, rather than age-related structural atrophy or the direct consequence of threshold hearing loss. The neurophysiological model of tinnitus posits that aberrant neural activity is interpreted as a salient signal that subsequently engages the limbic and executive networks, leading to distress and attentional capture. A cornerstone theoretical framework for understanding tinnitus neurophysiology is the thalamocortical dysrhythmia (TCD) model. The TCD model proposes that peripheral auditory deafferentation—whether overt (e.g., high-frequency hearing loss) or subclinical (e.g., cochlear synaptopathy)—leads to reduced sensory input to the thalamus, causing thalamocortical relay neurons to shift from tonic to burst-firing mode, leading to a reduction in normal alpha oscillations and the emergence of pathological cross-frequency coupling, particularly theta-gamma coupling, in the auditory cortex and connected limbic and frontal regions. This process is hypothesized to involve a large-scale network imbalance, particularly a dysregulation between the salience network (SN), which directs attention to significant stimuli, and the central executive network (CEN), which is responsible for cognitive control and habituation. Understanding the dynamic interplay between these networks across the progression of tinnitus is crucial for elucidating its pathophysiology. Electroencephalography (EEG) microstate analysis has emerged as a powerful tool to investigate the rapid spatiotemporal dynamics of large-scale brain networks. EEG microstates are quasi-stable topographical maps of neuronal activity that persist for tens to hundreds of milliseconds, reflecting the transient synchronization of the underlying neural generators. Four canonical microstate classes (A–D) have been consistently linked to the activity of distinct resting-state networks: auditory/visuospatial (A), visual (B), salience (C), and central executive (D) networks. Previous studies applying microstate analysis to tinnitus have primarily focused on patients with chronic tinnitus (CT), revealing alterations in microstate temporal dynamics, such as duration, occurrence, and transition, compared with those in healthy controls (HCs). However, a significant limitation of these studies is the frequent confounding effect of concomitant hearing loss, making it difficult to distinguish tinnitus-specific neural adaptations from those related to auditory deafferentation. While microstate analysis excels at characterizing macroscopic temporal dynamics, it offers limited insight into the frequency-specific functional integration within and between these networks. Dynamic functional network (DFN) analysis addresses this gap by quantifying time-varying changes in functional connectivity within specific oscillatory bands (e.g., δ, θ, α, β, and γ), thereby capturing rapid shifts in network efficiency and integration. DFN approaches have demonstrated sensitivity in capturing state-dependent neural dynamics in other neurological conditions, such as migraine, epilepsy, and chronic pain; however, their application in tinnitus, particularly in relation to microstates, remains nascent.