Pre-stimulus endogenous neural activity can influence the processing of upcoming sensory input and subsequent behavioral reactions. Despite it is known that spontaneous oscillatory activity mostly appears in stochastic bursts, typical approaches based on trial averaging fail to capture this. We aimed at relating spontaneous oscillatory bursts in the alpha band (8–13 Hz) to visual detection behavior, via an electroencephalography-based brain-computer interface (BCI) that allowed for burst-triggered stimulus presentation in real-time. According to alpha theories, we hypothesized that visual targets presented during alpha-bursts should lead to slower responses and higher miss rates, whereas targets presented in the absence of bursts (low alpha activity) should lead to faster responses and higher false alarm rates. Our findings support the role of bursts of alpha oscillations in visual perception and exemplify how real-time BCI systems can be used as a test bench for brain-behavioral theories.

Electrical brain oscillations reflect fluctuations in neural excitability. Fluctuations in the alpha band (α, 8-12 Hz) in the occipito-parietal cortex are thought to regulate sensory responses, leading to cyclic variations in visual perception. Inspired by this theory, some past and recent studies have addressed the relationship between α-phase from extra-cranial EEG and behavioural responses to visual stimuli in humans. The latest studies have used offline approaches to confirm α-gated cyclic patterns. However, a particularly relevant implication is the possibility to use this principle online for real-time neurotechnology, whereby stimuli are time-locked to specific α-phases leading to predictable outcomes in performance. Here we aimed at providing a proof-of-concept for such real-time neurotechnology. Participants performed a speeded response task to visual targets that were presented upon a real-time estimation of the α-phase via an EEG closed-loop brain-computer interface (BCI). We predicted, according to the theory, a modulation of reaction times (RTs) along the α-cycle. Our BCI system achieved reliable trial-to-trial phase-locking of stimuli to the phase of individual occipito-parietal α-oscillations. Yet, the behavioural results did not support a consistent relation between RTs and the phase of the α-cycle neither at group nor single participant levels. We must conclude that although the α-phase might play a role in perceptual decisions from a theoretical perspective, its impact on EEG-based BCI application appears negligible.

Spontaneous oscillatory neural activity can influence the processing of incoming sensory input and subsequent behavioural reactions. Spontaneous oscillatory activity mostly appears in stochastic bursts, but typical trial-averaged approaches fail to capture this. We aimed at relating oscillatory bursts in the alpha band (8-13 Hz) to behaviour directly, via an EEG-based brain-computer interface (BCI) that allowed for burst-triggered stimulus presentation in real-time in a visual detection task. According to alpha theories, we hypothesised that targets presented during alpha-bursts should lead to slower responses and higher miss rates, whereas targets presented in the absence of bursts should lead to faster responses and higher false alarm rates. Our findings support the role of bursts in alpha-oscillations in visual perception and exemplify how real-time BCI systems can be used as a test bench for brain-behavioural theories.

Sensory deprivation studies often rely on blindfolds to eliminate visual input, yet residual light inside the mask cavity is rarely quantifi ed. This work presents a dual-channel, photodiode-based light-sensing system integrated into a research blindfold to measure intra-blindfold illuminance in real time at the micro-lux scale. Two large-area photodiodes positioned in front of each eye feed a low-noise analog front end and a microcontroller-based digital processing pipeline with oversampling, low-pass fi ltering, and wireless telemetry. In addition to a direct-current (DC) measurement path, an alternating-current (AC) path centered at 80 Hz is introduced to mitigate drift and improve sensitivity by removing the baseline component and amplifying only the modulated signal. A calibration protocol is reported to map device counts to illuminance using an external reference lux meter under a fi xed-geometry confi guration. The system is validated by showing that residual illuminance inside the blindfold depends systematically on fi tting condition and sensor position, with tighter fi ts yielding lower light levels and consistent left–right asymmetries across participants. The results support quantitative, participant-level verifi cation of visual occlusion and provide a practical tool to improve experimental control and reproducibility in blindfold-based perception research.

Emotional communication is a multi-modal phenomenon involving posture, gestures, facial expressions, and the human voice. Affective states systematically modulate the acoustic signals produced during speech production through the laryngeal muscles via the central nervous system, transforming the acoustic signal into a means of affective transmission. Additionally, a substantial body of research in sonobiology has shown that audible acoustic waves (AAW) can affect cellular dynamics. This pilot study explores whether the physical–acoustic changes induced by gratitude states in human speech could influence cell proliferation and Ki67 expression in non-auditory cells (661W cell line). We conduct a series of assays, including affective electroencephalogram (EEG) measurements, an affective text quantification algorithm, and a passive vibro-acoustic treatment (PVT), to control the CO₂ incubator environment acoustically, and a proliferation assay with immunolabeling to quantify cell dynamics. Although a larger sample size is needed, the hypothesis that emotions can act as biophysical agents remains a plausible possibility, and feasible physical and biological pathways are discussed. In summary, studying the impact of gratitude AAW on cell biology represents an unexplored research area with the potential to enhance our understanding of the interaction between human cognition and biology through physics principles.