ABSTRACT Conventional autonomic metrics primarily quantify fluctuation magnitude while remaining relatively insensitive to the structural organization of underlying physiological dynamics. This limitation contributes to persistent interpretative ambiguities, including the observation that similar patterns of vagal activity may be associated with markedly different physiological and clinical states. To address this conceptual gap, I introduce the Neurodynamic Manifold, a theoretical topological framework that recontextualizes fluctuation magnitude within a multidimensional dynamical space. By integrating fractal scaling (DFA α 1 ), informational irregularity (Sample Entropy), and geometric organization (SD2/SD1), the framework maps autonomic activity onto distinct candidate regulatory regimes. It proposes a quasicritical zone characterized by adaptive complexity and multiscale coordination, alongside hypothesized subcritical and supercritical regimes associated with progressive forms of decomplexification. Within this framework, similar variability magnitudes may emerge from fundamentally different dynamical organizations, highlighting the interpretative limitations of amplitude‐based metrics such as RMSSD. Drawing on concepts from clinical physiology, statistical physics, complexity science, and dynamical systems theory, the Neurodynamic Manifold reconceptualizes autonomic regulation as a problem of dynamical organization rather than magnitude alone. If empirically supported, the framework may provide a unified foundation for investigating neurovisceral regulation, adaptive capacity, and physiological resilience across health, dysfunction, and performance.
ABSTRACT Physiological synchrony has been studied both at the dyadic level, where pairs are examined in isolation, and at the group level, where the collective is often characterized by a single index. Yet neither approach captures the full relational architecture of synchrony within a group. Here we propose a framework combining a sequential round‐robin design, in which each group member interacts one‐on‐one with every other member, with Small World Network (SWN) analysis. Although synchrony is measured as a dyadic property of each pair, this design permits characterization at three levels simultaneously: the individual level, who synchronizes consistently across partners; the dyadic level, which pairs synchronize more; and the group level, the overall architecture of coupling. Physiological synchrony (e.g., breathing, heart rate, electrodermal activity and even body odor) can be quantified for each dyad and used to construct a weighted synchrony network, where nodes represent individuals and edges represent the degree of physiological coupling. To leverage dyadic measures in order to characterize the network‐level topology of physiological synchrony, we suggest applying graph theory measures such as clustering coefficients, average shortest path length, density, degree distribution, and modularity. This enables answering novel questions: whether synchrony is transitive, whether it shows small‐world properties, and whether some individuals act as hubs, serving as “super synchronizers”. If there are “super synchronizers”, is this due to their interpersonal adaptability, the typicality of their physiological signals, or both? We present a framework for uncovering the multi‐level structure of physiological synchrony that emerges when individuals are observed across multiple dyadic interactions within a session. We illustrate our suggestions using an existing sequential round‐robin dataset (two sessions, 66 dyads), with body odor as the physiological measure and inclusion of the other in the self, a measure for perceived self‐other overlap and interpersonal closeness, as the outcome.
ABSTRACT Vagally‐mediated heart rate variability (vmHRV) is widely proposed as a biomarker for physical and mental health, but its utility hinges on psychometric robustness, particularly temporal stability and consistency across measurement contexts. Prior reliability studies have been constrained by small samples, short retest intervals, and analytic approaches that cannot disentangle stable individual differences from situational fluctuations and measurement error. The present study examined the temporal and transsituational stability of vmHRV over a 1‐year interval in a large, population‐based sample ( N = 175) from the Dresden Burnout Study. Short‐term inter‐beat‐interval (IBI) recordings were obtained at two annual assessments under two conditions: recumbent recovery following venipuncture and seated rest. Four cardiac and HRV‐derived parameters, the established vmHRV indices root mean square of successive differences (RMSSD), percentage of successive RR intervals differing by more than 50 ms (pNN50), and high‐frequency power (HF power), complemented by mean RR interval (RR) as a general cardiac timing parameter, were analyzed using single‐trait–multistate–method‐minus‐one [STMSM(M–1)] models within the latent state–trait (LST) framework, with recovery specified as the reference condition and resting modeled as a condition‐specific method factor. Reliability ranged from 0.650 to 0.903, and trait specificity ranged from 0.375 to 0.773. RR and RMSSD showed the most consistent trait‐like profiles across occasions and conditions. pNN50 showed the highest individual trait‐specificity estimate, but also greater heterogeneity across occasions, whereas HF power showed comparatively lower trait specificity and greater occasion‐specific variance. Method specificity was small (0.034–0.087), indicating that stable condition‐specific deviations from recovery accounted for a limited proportion of variance. These findings support the interpretation of vmHRV, particularly RMSSD and pNN50, as mainly trait‐like indicators of cardiac vagal function, while also showing that single short‐term assessments contain meaningful occasion‐related variance. Standardized assessment conditions and repeated measurements remain essential for biomarker applications of vmHRV.
ABSTRACT The late positive potential (LPP) is a robust neural marker of attention toward emotionally salient stimuli, yet it is unknown how the LPP is modulated by personal preferences for specific types of pleasant objects/experiences. The present study aimed to evaluate whether personal preferences for pleasant experiences modulate the LPP to images reflecting those situations. Secondary analyses examined whether depressive symptoms and a positive emotion intervention were associated with individual differences in this modulation. College students ( N = 92; M age = 19.44, SD = 1.15) reported depressive symptoms before randomization to a positive emotion intervention ( n = 47) or study skills comparison group ( n = 45). Participants then rank‐ordered a list of eight categories of positive objects/experiences (e.g., cute animals, adventure, social activities, junk food) based on which they enjoyed most and viewed images of each while EEG data were recorded. The LPP was modulated by personal preferences broadly, such that the LPP to images depicting top‐ranked pleasant categories was enhanced compared to low‐ranked pleasant categories; however, significant effects were not observed linearly between each individual ranking. In secondary analyses, depressive symptoms moderated preference effects on the LPP, with greater symptoms associated with less differentiation between highly preferred and less preferred positive stimuli. The positive emotion intervention did not significantly impact LPP modulation by personal preference. Results highlight the utility of considering personal salience in selecting stimuli for clinical neuroscience tasks and indicate that depression may be characterized by difficulty sustaining attention to personally salient pleasant experiences.
ABSTRACT Prioritized processing of emotionally relevant faces compared to neutral faces is reflected in differential event‐related potentials (ERPs). However, there is an ongoing debate about the extent to which faces, in general, and fear‐conditioned faces, in particular, enhance early ERPs when they are not consciously perceived. Here, we tested whether early ERP components (P1 and N170) differentiate between fear‐conditioned (CS+) and non‐aversive (CS−) faces presented for 17 ms in a backward‐masking design using a sequential Bayesian sampling procedure ( N = 40). Consciousness was manipulated by presenting the mask directly (0 ms) or after a delay (200 ms) following the target stimulus. Participants were asked to rate their subjective perception after each trial to differentiate between trials in which they perceived nothing beyond the mask, brief glimpses of anything other than a face, vague impressions of a face, or clear impressions of a face. CS+ as compared to CS− faces led to increased N170 amplitudes in the conscious condition among successfully conditioned participants, but not in the nonconscious condition, while no differential effects were observed for the other ERP components. Thus, the data do not support the assumption that fear‐conditioned stimuli are processed nonconsciously in the visual cortex.
