🧬 biology

A common neural mechanism underlies experiences of passage of time

Using EEG in virtual reality environments, this study demonstrates that a common, situation-independent neural oscillatory mechanism underlies the subjective experience of the passage of time, regardless of specific visual stimuli or actual duration.

Original authors: Mathis Jording, Mark Wünsche, Megha Madathil, David H.V. Vogel, Shivakumar Viswanathan, Kai Vogeley

Published 2026-10-19

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Mathis Jording, Mark Wünsche, Megha Madathil, David H.V. Vogel, Shivakumar Viswanathan, Kai Vogeley

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Time feels different depending on what you are doing. When you are waiting in a dull line, the minutes can drag on forever, yet when you are caught up in a fascinating conversation, hours can vanish in a blink. This feeling that time is passing slowly or quickly is a universal human experience, distinct from simply counting how many seconds have actually ticked by. Scientists have long wondered if this subjective feeling of time's passage is just a collection of different mental tricks our brains play in different situations, or if there is a single, consistent engine running underneath all of it. Is the brain using one specific method to create the feeling of time flying, regardless of whether we are bored or excited, or does it switch gears entirely depending on the context?

To answer this, researchers at Forschungszentrum Jülich and the University of Cologne designed an experiment that placed volunteers inside a virtual reality world to watch a sky full of moving stars. They wanted to see if they could find a common pattern in the brain's electrical activity that predicted whether a person would feel time was moving fast or slow, no matter how the stars were moving. The team used a head-mounted display to show participants a view from a spaceship cockpit, looking out at a field of colored stars. These stars moved at different speeds and appeared in different numbers, creating a visual environment that could be made to feel like time was speeding up or slowing down. While the participants watched these stars for about twenty seconds, the researchers recorded their brain waves using a cap with sixty-four sensors placed on their scalp.

The study focused on two main variables: how fast the stars were moving and how many stars were in the sky. By changing these two factors, the researchers created six different versions of the starfield. Some had no movement at all, some moved slowly, and some moved quickly. Similarly, some had only a few stars, while others were packed with many. After each viewing, the participants were asked to report which color was most dominant and then to rate how fast they felt time had passed on a scale from zero to one hundred. The results confirmed that the visual changes worked: when the stars moved faster or were more numerous, people consistently reported that time felt like it was passing more quickly.

The core of the research, however, was not just about what the participants felt, but what their brains were doing while they felt it. The researchers broke the twenty-second viewing periods into small two-second snapshots and analyzed the electrical rhythms of the brain during those moments. They used a computer program to look for a relationship between the specific pattern of brain waves and the rating the participant would later give. They found that the brain's electrical state during the viewing was indeed a reliable predictor of how the person would judge the passage of time. If the brain showed a certain pattern of activity, the computer could accurately guess whether the person would say time felt slow or fast.

The most significant discovery came when the researchers tested whether this brain pattern was specific to just one type of starfield or if it was a universal signal. They trained the computer to recognize the brain pattern for one specific combination of speed and star density, and then asked if that same pattern could predict the time feeling in a completely different combination. For example, could the brain pattern learned from watching slow-moving stars predict the feeling of time while watching fast-moving stars? The answer was yes. The same neural signature that predicted the feeling of time passing quickly in a crowded, fast-moving sky also predicted it in a sparse, slow-moving sky. This suggests that the brain does not use a different mechanism for every different situation. Instead, it relies on a single, stable process that translates the intensity of change in the environment into the feeling of time moving forward.

This finding challenges the idea that our sense of time is just a retrospective story we tell ourselves after an event is over. If that were true, the brain patterns during the event would not be able to predict the feeling so accurately, and the rules for one situation would not apply to another. Instead, the evidence points to a perception-like process, where the brain continuously converts the rate of change in the world around us into a direct experience of time flowing. While the study was conducted in a controlled virtual environment with specific visual stimuli, it provides the first clear evidence of a common neural mechanism underlying the diverse ways we experience time. It suggests that whether we are watching a starfield or living through a busy day, the brain uses the same fundamental language to tell us that time is passing.

Technical Summary: A Common Neural Mechanism Underlies Experiences of Passage of Time

Problem Statement
The subjective experience of the passage of time (PoT)—often described as time "flying" or "standing still"—varies significantly across different situations, independent of the actual physical duration. While PoT judgments (PoTJs) are used to describe diverse sensory, cognitive, and emotional contexts, it remains unresolved whether these varying experiences stem from a single, common neural mechanism or if they are merely retrospective reflections (a "vocabulary" for different situational states) that rely on situation-dependent processes. This study aims to distinguish between two competing accounts: the "PER account," which posits a perception-like process with a consistent neural signature across situations, and the "REF account," which suggests PoTJs are retrospective reconstructions where the brain-state-to-judgment relationship varies by situation.

Methodology
The researchers employed a controlled Virtual Reality (VR) environment combined with high-density electroencephalography (EEG) to systematically manipulate PoT experiences.

Stimuli: Participants (N=41) viewed a "starfield" stimulus inside a fully immersive VR headset (HTC Vive Pro Eye). The starfield consisted of colored moving stars. Two visual features were systematically varied to influence PoT: velocity (zero, slow, fast) and density (few, many stars), creating six distinct variants.
Task: Participants performed a "starfield color tracking task" for 19–21 seconds per trial, monitoring the predominant color of the stars. Immediately following each trial, they reported the dominant color and provided a PoTJ on a visual analog scale (0 = very slow, 100 = very fast).
Data Acquisition: 64-channel EEG was recorded throughout the trials. Data were preprocessed to remove artifacts, and continuous trial data were split into 2-second "snapshots."
Feature Extraction: For each 2-second snapshot, the oscillatory power in five canonical frequency bands (delta, theta, alpha, beta-low, beta-high) was calculated across all 64 channels, resulting in a 320-dimensional feature vector per snapshot.
Analysis: A machine learning approach using Support Vector Regression (SVR) was employed.
1. Prediction: The model was trained to predict PoTJs from neural snapshots within specific starfield variants.
2. Generalization: Crucially, the study tested whether predictors trained on one specific variant (e.g., slow velocity) could accurately predict PoTJs in other variants (e.g., fast velocity or different density). This cross-variant generalization was the primary test for a common neural mechanism.
3. Validation: A 5-fold cross-validation procedure and permutation tests (5,000 runs) were used to ensure prediction accuracy exceeded chance levels.

Key Results

Behavioral Validation: The manipulation of velocity and density successfully influenced PoTJs. Higher velocities and, in moving conditions, higher densities led to reports of time passing faster. Accuracy in the color tracking task confirmed participant attention.
Neural State Distinctiveness: EEG analysis confirmed that the starfield task induced a distinct neural state compared to resting state (characterized by decreased occipital alpha power). Furthermore, neural patterns were more similar within the same starfield variant than between different variants, confirming that the stimuli induced specific, measurable brain states.
Prediction of PoT: Neural oscillatory patterns during the stimulus presentation successfully predicted subsequent PoTJs. The correlation between predicted and actual PoTJs was significantly above zero ( $r \approx 0.474$ ), demonstrating that the brain state contains information about the subjective experience of time.
Generalization Across Situations: The core finding was that predictors trained on data from one starfield variant (specific velocity or density) successfully generalized to predict PoTJs in other variants.
- Predictors trained on a specific velocity level predicted PoTJs in other velocity levels.
- Predictors trained on a specific density level predicted PoTJs in other density levels.
- This generalization held even when testing across combinations of velocity and density, suggesting the underlying neural mechanism is stable and independent of the specific moment-to-moment change rate of the stimulus.

Significance and Claims
The authors claim that these findings provide the first evidence of a stable "brain signature" for the experience of the passage of time. The results support the PER account, suggesting that PoT experiences, despite being highly sensitive to situational context, rely on a common neural mechanism.

The significance of this work lies in:

Mechanistic Insight: It demonstrates that the relationship between brain state and PoT experience is consistent across different sensory contexts, arguing against the idea that PoTJs are merely retrospective labels for disparate experiences.
Temporal Distinction: It reinforces the distinction between PoT (subjective flow) and duration perception (objective estimation), showing that PoT is grounded in a continuous, perception-like neural process rather than a post-hoc cognitive reconstruction.
Future Directions: The authors note that while this study establishes a common mechanism for visual dynamic stimuli, the origin of PoT likely involves integrating multiple sensory sources (auditory, interoceptive, etc.). The identification of this neural signature opens the door for further experimental investigations into the neurobiological foundations of time perception and its potential dysregulation in psychiatric conditions.

The paper remains modest in its scope, stating that the origin of PoT experience will likely be determined through a continued process of collecting evidence rather than a single study, and it does not propose immediate clinical applications or specific future experimental protocols beyond the general call for further investigation into the functional role of PoT.

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