ABSTRACT The individual alpha frequency (IAF) refers to the frequency at which the alpha rhythm shows peak power. This index is of great interest to neuroscience as it represents a marker of cortical timing and temporal resolution of neural processing. Renewed interest stems from the opportunity to consider IAF not only as a descriptive marker of intrinsic brain dynamics but also as a neural marker serving as a personalized parameter in neuromodulation interventions. In this narrative review, we synthesize empirical and theoretical evidence that supports current understanding of IAF across methodological, biological, cognitive, clinical, and interventional domains. Methodologically, IAF estimation does not follow a uniform approach and would benefit from greater convergence, including explicit separation of the periodic oscillation signal from the aperiodic background. Physiologically, evidence indicates substantial heritability and short‐to‐medium‐term test–retest reliability of IAF, while support for clear and stable structural and neurochemical characteristics is weaker. Cognitively, IAF modulation is associated with specific abilities, depending on the task and cognitive domain. Faster IAF is associated with finer temporal resolution, better attentional and visuospatial performance, and increased processing speed, with more limited and region‐dependent evidence for working memory. Clinical and longitudinal evidence suggests that deviations from the expected age‐related trajectory, a non‐linear rise into early adulthood followed by gradual slowing, accompany pathological aging, neurological, and mental disorders. However, these deviations are graded, indicating how far individuals depart from normative values, rather than providing stand‐alone diagnostic cut‐offs. Finally, interventional studies on IAF‐tuned neuromodulation are consistent with increased transient neural entrainment and improved performance in the context of substantial IAF index stability. This positions IAF as a constraint rather than a target for personalization: an individual‐specific resonance range within which stimulation is likely to interact optimally with ongoing dynamics, and a candidate parameter for personalized brain stimulation protocols.
ABSTRACT This methodological study aims at exploring several extensions of physiological synchrony. As yet, synchrony is commonly analyzed within the same physiological modality and between different people, whereas in the present project we were specifically interested in crossmodal synchronies between people (interpersonal), as well as within the same person (intrapersonal). In recent years, interpersonal synchrony has received increased attention as a research field and a methodology in various disciplines where social interaction is pivotal. Synchrony is often computed on a time scale of a few seconds, predominantly based on physiological measures or motor behavior. Systematic reviews and meta‐analyses have shown that interpersonal synchrony is a phenomenon that characterizes people's social interaction in different contexts. Synchrony arises spontaneously in social systems, often outside the awareness of the persons interacting, and is often considered a signature of relationship quality. Synchrony was also shown to be induced by salient stimulation contexts, for example by music synchronizing concert audiences. To explore such synchronies, we used a large dataset of 703 participants who listened to classical music in a concert setting. Heart rate, heart‐rate variability, electrodermal activity, breathing behavior, and respiration rate were recorded simultaneously in all participants. Using the surrogate synchrony algorithm (R package SUSY), which is based on cross‐correlations, the participants' crossmodal synchronies were determined for all 10 combinations of these 5 modalities. The psychological meaning of physiological synchronies is the goal of empirical aesthetics, and findings were published previously. The present study, however, concerns methodological topics of multimodal synchrony: do crossmodal synchronies arise intra‐ and interpersonally? Using surrogate tests as a control condition, we found that about half of such synchronies were significantly present in the dataset at substantial effect sizes. We additionally explored the lag structure of the underlying cross‐correlations to describe the leading‐following dynamics between synchronized physiological modalities. We expected that crossmodal synchronies of modalities representing sympathetic activation would be significantly synchronized positively (in‐phase synchrony). This was, however, not always the case, as co‐activation of sympathetic and parasympathetic signals was also found. In conclusion, the present findings on crossmodal synchronies provide novel information and suggest new measures for synchrony research, which is relevant for both induced synchrony and synchrony of social interaction.
ABSTRACT In triadic social interaction, autonomic coordination is dynamic and may be poorly captured by session‐level synchrony estimates. We propose a state‐based framework to quantify time‐varying interpersonal synchrony during a laboratory group decision‐making task (Desert Survival Task) using concurrently recorded electrodermal activity (EDA) and ECG‐derived heart rate variability (HRV). Twelve triads (36 participants) with complete physiological recordings were analyzed. Signals were segmented into overlapping 60 s windows (1 s step). For each participant, window‐level features were extracted (EDA: 4 features; HRV: 74 features), standardized within individuals, and converted to dyadic divergence vectors (absolute differences) for the three dyads in each triad. Divergence vectors (combined EDA plus HRV) were reduced with PCA (95% variance retained) and clustered using a single global k ‐means model trained on pooled windows to yield five discrete synchrony states shared across triads. States were ordered along the first principal component (PC1) of the divergence space, with its orientation chosen so that State 0 corresponded to the highest‐synchrony state (HSS). Triad‐level state metrics quantified both prevalence and temporal stability: fractional occupancy rate (FOR), mean dwell time (MDT), and conditional long‐run fraction (CLRF; ≥ 10 s runs). Empirical triads showed a graded continuum of synchrony across states and a strong bias toward the HSS. Surrogate validation using a leave‐one‐fixed Iterative Amplitude Adjusted Fourier Transform (IAAFT) null applied at the signal level demonstrated that HSS occupancy and stability exceeded chance alignment (FOR; p < 0.001; MDT and CLRF; p < 0.001). Convergent validity of the proposed state representation was further supported by continuous signal‐based benchmarks: compared with State 4, State 0 showed lower dynamic time warping distances and higher lag‐optimized physiological linkage (max R 2 ) for both EDA and HRV (all p < 0.001). In contrast, group‐mean anxiety measures (SPIN, STAI) were not reliably associated with HSS prevalence or stability in this sample. These findings suggest that discrete synchrony states capture interpretable, non‐random coordination regimes in triads and provide a complementary framework for characterizing the temporal organization of autonomic synchrony beyond conventional continuous synchrony measures.
ABSTRACT Mathematics achievement can be influenced by negative emotions and expectations related to numerical tasks. Individuals with high mathematics anxiety often show poorer numerical performance. This study investigated the neural mechanisms underlying different levels of numerical processing associated with mathematics anxiety using number line estimation and arithmetic verification tasks during fMRI. Participants were classified into high ( n = 22, age = 23.09 ± 2.22) and low ( n = 24, age = 22.67 ± 3.29) mathematics anxiety groups based on detailed screening prior to scanning. Trait and test anxiety were also assessed to capture broader anxiety‐related characteristics. Before the fMRI session, participants completed assessments of calculation performance and digit span, and a mock MRI session was used to reduce scanner‐related stress. Participants completed task and control conditions for each numerical task during fMRI. Neuroimaging data were analyzed using 2 × 2 whole‐brain voxel‐wise ANOVA. Group differences in task‐related brain activation were further examined both before and after statistically controlling for trait and test anxiety. Results showed that low mathematics anxiety was associated with greater frontal eye field activity during number‐space mapping and stronger supramarginal gyrus activity during arithmetic computation compared with high mathematics anxiety. Controlling for trait and test anxiety helped clarify which neural effects remained associated with mathematics anxiety after accounting for variance shared with broader anxiety‐related factors. Overall, attentional and memory‐related effects remained associated with mathematics anxiety after this adjustment, whereas additional effects involving motor processes and cognitive control were attenuated, suggesting that these effects may partly reflect variance shared with broader anxiety‐related constructs.
ABSTRACT It is widely known that sleep has a role in modulating emotional processing. However, while sleep facilitates the consolidation of emotional memories, its influence on emotional reactivity remains unclear. Most prior work has not fully addressed emotional reactivity, often relying solely on subjective or physiological measures, nor has it disentangled the contribution of different sleep stages. Here, using a between‐subjects design, we asked participants to complete two picture‐based tasks assessing emotional memory and emotional reactivity before and after a manipulation condition (nap, N = 40; wake, N = 40), and again 2 days later. Spontaneous variations in nap duration resulted in participants reaching REM sleep (REM group, N = 20) or not (No‐REM group, N = 20). Emotional reactivity, assessed using an emotional picture task consisting of 28 images with different emotional contents (negative and neutral), was measured through subjective ratings and physiological responses (phasic cardiac response and skin conductance response). Sleep preserved memory performance relative to wakefulness, but after 2 days, only negative images maintained a memory advantage in the Nap group; however, no differences emerged as a function of REM sleep occurrence during the nap. For emotional reactivity, subjective arousal decreased after sleep in the REM group, whereas valence ratings declined only after 2 days. Physiologically, heart rate habituation was greater in the No‐REM group. Together, these findings indicate that sleep fosters emotional memory consolidation while modulating reactivity in ways that diverge across subjective and physiological domains, with a decrease in subjective arousal ratings and an increase in phasic cardiac response. These findings, which should be interpreted in the context of the observed differences in participants' sleep architecture, highlight the complex role of sleep in emotional processing and underscore the need for standardized experimental paradigms.
