Meng Zhang

Objective stressor offset does not mark a common onset of recovery: cardiovascular activation may be waning while cortisol is still rising and threat-related cognition persists. This structured narrative review integrates molecular, autonomic, neural, cognitive, and immune evidence on the post-stressor interval, primarily in adult psychosocial-stress paradigms. We propose the Post-Stressor Transition Model (PSTM) as an operational extension of existing recovery and allostatic accounts, not as a newly discovered biological system. Three regulatory functions organize the synthesis: updating whether threat remains current, changing cardiac autonomic influence, and regulating continuing hypothalamic–pituitary–adrenocortical output. Glucocorticoid receptor signaling, catecholamines, endocannabinoids, oxytocin, and vasopressin contribute across these functions. The framework distinguishes objective offset from system-specific extrema, physiological resolution from demonstrated adaptation, and shared timing from directional coupling. Eight propositions specify outcomes, temporal windows, competing explanations, and prespecified effect bounds. Measurement recommendations address cortisol nonresponse, respiratory influences on heart rate variability, assessment reactivity, and multirate sampling. Hormonal state and development modify candidate parameters rather than define fixed response types. No universal recovery threshold or clinically validated transition profile is claimed. The model is useful only if its additional parameters are identifiable, improve independent prediction, and withstand phase-specific experimental tests.

Introduction: Intrinsic EEG oscillations provide a non-invasive window into arousal- and attention-related individual differences, but resting low-frequency EEG correlates of adult attention-deficit/hyperactivity disorder (ADHD) trait symptoms remain incompletely characterized in non-clinical young adults. Methods: We analyzed eyes-closed resting-state EEG from a cohort of 337 Chinese undergraduates with usable EEG data; the primary analysis included 334 participants. ADHD trait symptoms were assessed dimensionally with a 26-item adult ADHD self-report scale. The prespecified EEG family comprised log posterior-occipital delta power, log posterior delta power, log global delta power, and frontocentral log theta/beta ratio. The primary HC3 regression adjusted for age, sex, trait anxiety, depressive symptoms, and Beck Anxiety Inventory total score, with false-discovery-rate correction across the planned EEG family. Results: Higher ADHD trait symptoms were associated with lower posterior-occipital delta power [β = 0.114, 95% CI (0.199, 0.029), p = 0.008]. Posterior delta, global delta, and frontocentral theta/beta ratio showed convergent negative associations after false-discovery-rate correction. The posterior-occipital delta association remained negative and statistically significant across extended covariate models and robustness analyses. Across 64 reasonable covariate specifications, all coefficients were negative and 65.6% reached p < 0.05. Discussion: Adult ADHD trait symptoms were modestly associated with lower posterior-occipital and broader low-frequency resting EEG power after accounting for internalizing symptoms. The findings support a stable group-level dimensional association within this sample, but not individual-level screening, diagnostic support, risk classification, or causal inference.

Background: Non-suicidal self-injury (NSSI) is highly prevalent in adolescence, yet the fast dynamics of large-scale brain networks remain poorly understood. We aimed to characterize resting-state EEG microstate dynamics in a clinically recruited adolescent NSSI sample and to examine state-dependent changes following acute social exclusion. Methods: Resting-state EEG was recorded in hospitalized, medicated adolescents with NSSI and in healthy controls (HCs). An NSSI subgroup then completed EEG assessments before and after either Cyberball-induced social exclusion or a non-stress control condition. Microstate parameters and transition probabilities were analyzed. Results: After multiple-comparison correction, the core baseline finding was robustly reduced microstate A duration in the NSSI group relative to HCs. In uncorrected exploratory analyses, additional differences included shorter durations of microstates B and F, higher occurrence of microstate D, and increased F→D transition probability. A multivariate pattern analysis suggested group-related information but must be interpreted cautiously given the modest sample size. Within the NSSI group, the exclusion group showed reduced microstate A expression and increased microstate D expression relative to the non-stress subgroup, with a broader transition shift toward microstate D. Several interaction effects survived correction. Conclusions: In this medicated inpatient sample, resting-state microstate dynamics differed from HCs, most robustly in reduced microstate A duration, and reorganized after social exclusion. Specificity to NSSI remains uncertain given the absence of an MDD-only clinical-control group and healthy Cyberball comparison. These preliminary findings require replication in larger studies including medication-naive MDD-only, MDD+NSSI, and HC groups.

Trait emotional intelligence（trait EI） is an important individual-difference construct, yet its resting electrophysiological correlates remain poorly specified. We tested whether trait EI was associated with frontocentral theta-beta balance in 337 Chinese undergraduates with usable resting-state EEG. Trait EI was measured with the 33-item Emotional Intelligence Scale. The primary EEG marker was the log theta/beta ratio averaged over frontocentral electrodes. Regression models controlled for age, sex, trait anxiety, depressive symptoms, and somatic anxiety; extended models added affect, emotion-regulation strategies, Big Five traits, general self-efficacy, and Raven reasoning. Higher trait EI was associated with higher frontocentral log theta/beta ratio in the primary model (β = 0.143, 95% CI [0.051, 0.235], p = .002), explaining an additional 2.0% of variance beyond internalizing symptoms. The association remained significant after Big Five adjustment (β = 0.116, p = .023) and after joint adjustment for Big Five traits, affect, and emotion-regulation strategies (β = 0.114, p = .012). Specification-curve analyses showed positive coefficients across 64 reasonable covariate specifications. The association was strongest for emotion awareness and self-management and was driven mainly by frontocentral theta/theta-beta balance rather than beta or alpha power. These findings identify a modest but reliable resting EEG correlate of trait-EI-related individual differences.

The nucleus accumbens (NAcc) plays a central role in motivation and reward processing, and its dysfunction is implicated in various psychiatric disorders. While invasive neuromodulation of the NAcc has shown therapeutic benefits, current noninvasive techniques cannot effectively reach this deep target. Recently, transcranial temporal interference stimulation (tTIS) has emerged as a promising approach to noninvasively modulate deep brain regions. Here, we explored whether tTIS could noninvasively modulate NAcc activity and its associated networks in humans. Fifteen healthy adults received a single 30-minute tTIS session targeting the right NAcc; resting-state fMRI was acquired immediately before stimulation (T0), immediately after (T1), and again 30 minutes later (T2). Analyses focused on local spontaneous activity, functional connectivity (FC), and effective connectivity (EC) using ROI-based linear mixed models and voxel-wise whole-brain contrasts. Electric-field simulations confirmed focal targeting of the NAcc with minimal current spread. Although no significant change in the amplitude of spontaneous activity was observed, local activity coherence within the NAcc significantly increased immediately after stimulation. FC between the NAcc and the limbic network and caudate, as well as EC from the NAcc to the default mode network and limbic network, were significantly enhanced at T1. These effects largely returned to baseline by T2, indicating transient short-term modulation. Collectively, these findings show that a single tTIS session can modulate both local NAcc dynamics and large-scale network interactions, supporting the feasibility of noninvasive deep-brain modulation of the NAcc and highlighting its potential as a neuromodulatory approach for disorders involving dysregulated reward and affective processing.