Neurovascular instability, impaired cortical recruitment, and network dysconnectivity across the transdiagnostic anxiety spectrum: a functional multi-channel near-infrared spectroscopy study

Authors

Abstract

BackgroundAnxiety-spectrum disorders (ANSD) are highly prevalent, yet the underlying neurovascular mechanisms remain unclear. Functional near-infrared spectroscopy (fNIRS) comprises a non-invasive method to assess cortical hemodynamics, neurovascular coupling, and network organization during cognitive processing. MethodsWe investigated healthy controls (HC), generalized anxiety disorder (GAD), anxious depression (AD), and anxiety-depression comorbidity (CO) using multichannel fNIRS during a verbal fluency task. Multiple hemodynamic features were extracted, including peak response, temporal hemodynamic variability, {beta}{square}activation, and HbO, HbR, and HbT signals. Functional connectivity, graph-theoretical network measures, machine-learning classification, and associations with depressive, anxiety and psychosomatic scores were examined. ResultsCompared to controls, ANSD patients showed reduced task-evoked HbO and HbT responses, preserved HbR levels, increased temporal hemodynamic variability, and reduced {beta}{square}activation. Activation deficits were most prominent in bilateral frontopolar and medial prefrontal cortices and followed a gradient, with the CO group exhibiting highest abnormalities. Functional connectivity was increased, whereas clustering coefficient, nodal local efficiency, and nodal efficiency were reduced, indicating maladaptive hyperconnectivity accompanied by inefficient network organization. The AD and CO groups showed the greatest network disintegration. Temporal hemodynamic variability emerged as the strongest predictor of anxiety, depressive, and physiosomatic symptom severity. Reduced prefrontal activation was significantly associated with higher symptom domain scores. Machine-learning analyses demonstrated adequate discrimination between HC and ANSD. ConclusionsANSD are characterized by impaired neurovascular recruitment, increased hemodynamic instability, maladaptive hyperconnectivity, and disrupted cortical network topology. These abnormalities appear to represent transdiagnostic neurovascular processes underlying anxiety, depressive, and physiosomatic symptoms across the anxiety spectrum. HighlightsO_LIA 53-channel fNIRS verbal-fluency paradigm revealed widespread neurovascular and cortical network abnormalities across the anxiety spectrum. C_LIO_LIANSD were characterized by increased hemodynamic variability and reduced peak neurovascular recruitment, indicating unstable yet hyporesponsive cortical dynamics. C_LIO_LIDifference metrics within the right frontal eye field, right Brocas area, and right frontopolar cortex emerged as robust discriminative biomarkers across machine learning models. C_LIO_LIANSD exhibited reduced prefrontal activation, impaired network efficiency, and maladaptive hyperconnectivity despite preserved HbR responses. C_LI

Tags

Topics