Traditionally, psychophysiological studies have relied on paired t-tests and repeated-measures analyses of variance to analyze data. However, the linear mixed model (LMM) has recently emerged as a flexible and powerful alternative. This article introduces the LMM to encourage its use in psychophysiological research. First, we compare the LMM with traditional statistical approaches, highlighting key differences and advantages. Next, we describe the structure and parameters of the LMM using hypothetical data. Finally, we illustrate how to apply an LMM to real psychophysiological data. The LMM's capacity to process all available data by accommodating random effects—often overlooked by traditional methods—is expected to improve the validity of statistical inferences in psychophysiology.

Recent advances in digital audio technology have increased interest in binaural recording and reproduction techniques that faithfully recreate the sound space of a recording. A previous study showed that binaural sounds presented during a visual cognitive task were subjectively rated as deeper, wider, softer, and more comfortable than monaural sounds. However, no corresponding differences were found in physiological responses. The present study investigated whether attentive listening to binaural sounds would influence physiological responses. Thirty-five university students listened to 40-second binaural recordings of ocean surf and their monaural counterparts, eight times each in random order. Electroencephalograms, heart rate, and skin conductance levels were recorded during the listening sessions. Subjective ratings showed that binaural sounds were perceived as better-sounding, deeper, wider, and softer than monaural sounds. Moreover, the participants reported more vivid seascape imagery and an increased sense of immersion in the auditory environment. However, physiological responses did not significantly differ between the two conditions. These results suggest that the perceptual qualities of binaural sounds do not necessarily produce measurable changes in cortical or autonomic activity.

The arousal state at bedtime influences the latency to sleep onset, as demonstrated by the difficulty initiating sleep in individuals with psychophysiological insomnia. However, it has not yet determined whether sleep onset latency can be predicted from electroencephalography (EEG) recorded during the awake period preceding sleep. We conducted nap polysomnography in healthy adults. Then, we performed multiple regression analyses to examine whether EEG indices during wakefulness could predict latencies to Sleep Stages 1 and 2. The study identified a significant regression model for predicting Stage 2 sleep latency based on the scaling exponent, a fluctuation index, measured during the awake period. These results indicate the temporal relevance of EEG fluctuations during the transition to sleep and suggest potential applications by predicting sleep onset using pre-sleep EEG data.

The absence of an expected stimulus elicits a series of event-related potentials (ERPs). Recognized since the 1960s, this phenomenon has been used as evidence that ERPs include endogenous components. In this review, these endogenous components are referred to as omitted stimulus potentials (OSPs). Because OSPs occur without sensory input, they offer a unique means of examining the brain’s predictive mechanisms. This review outlines the core characteristics of OSPs and describes the commonly employed experimental paradigms. It also summarizes key findings on the variables that modulate OSPs and presents theoretical interpretations of OSPs through prediction and prediction error frameworks. Finally, the review suggests future directions for OSP research.

Recent advancements in digital technologies have improved the ability to reproduce high-fidelity sound. This study examined the effects of binaural sound, which more accurately recreates the original sound field than monaural sound, on psychophysiological responses. Thirty-four university students completed a visual two-choice reaction time task while listening to two types of sound: a binaural recording of ocean surf and its monaural version created by averaging the left and right channels. To assess physiological states, electroencephalograms (EEG), event-related potentials (P300), electrocardiograms (ECG), and respiratory activity were recorded. Participants perceived binaural sound as deeper, wider, and softer than monaural sound and were more likely to rate it as a comfortable and natural stimulus. However, behavioral and physiological measures showed no significant differences between the two sound conditions. These findings suggest that merely perceiving differences between the two sounds may not be sufficient to demonstrate psychophysiological effects. Future research should be conducted under conditions (e.g., sound type and listening environment) where the characteristics of binaural sounds become more distinct.