The Pupillary Light Reflex as a Biomarker of Cognitive Age and Subjective Time Dilation

Abstract

Analysis of 41,053 pupillary light reflex recordings demonstrates that specific pupillary dynamics vary predictably with age, exhibiting high explanatory power (R² ≈ 0.80–0.89) for multiple parameters. This research proposes that the pupillary light reflex constitutes a fundamental, involuntary measure of neural processing speed, awareness, and perceptual integration, enabling estimation of "cognitive age" as a biologically grounded construct distinct from chronological age.

Introduction

The subjective cognitive experience is not constant across the human lifespan. Older adults consistently report that experience of time and information changes with age, a phenomenon documented across cultures and historical periods. Traditional explanations emphasize psychological accounts such as proportional theory, which posits that each successive year represents a smaller fraction of total lived experience. While intuitively appealing, such explanations remain descriptive and lack direct neurophysiological linkage.

Converging evidence from cognitive neuroscience indicates that aging is accompanied by a generalized slowing of neural processing speed, affecting perception, attention, working memory, and motor responses. Processing speed has been proposed as a core limiting factor underlying age-related cognitive decline. However, most measures of processing speed rely on voluntary responses and are confounded by motivation, strategy, and task familiarity.

The pupillary light reflex offers a unique solution to this limitation. The PLR is a rapid, involuntary neurophysiological response mediated by a well-characterized subcortical circuit. Because the PLR operates outside conscious control, it provides a direct assay of neural transmission speed, synaptic efficiency, and neuromuscular execution. Recent advances in app-based pupillometry enable decomposition of the PLR into amplitude, speed, and latency parameters.

Methods

Data were aggregated and anonymized from 13,762 neurologically diverse individuals aged 10–80 years across 361 test administrators. Participants reported no history of neurological disease and were symptom-free at the time of testing. Pupillary responses were recorded using mobile app-based pupillometry operating at 30 Hz temporal resolution, with light stimuli delivered monocularly at approximately 30 lumens.

Nine PLR parameters were extracted: latency, maximum diameter, minimum diameter, constriction amplitude, maximum constriction speed, average constriction speed, constriction time, average diameter, and release amplitude. These parameters jointly capture mechanical, temporal, and speed-related aspects of the PLR. Model fitting was conducted using least-squares optimization across multiple function types, with model selection based on R² values.

Key Findings

Age-related effects were observed across all PLR parameters, with particularly strong and consistent trends in amplitude, diameters, and constriction speeds. Maximum diameter (R²=0.89), minimum diameter (R²=0.88), and average diameter (R²=0.89) all showed strong decreases with age, reflecting well-documented age-related decrease in pupillary size. Constriction amplitude demonstrated a strong exponential relationship with age (R²=0.81).

Speed measures exhibited some of the strongest age associations in the dataset. Average constriction speed declined linearly with age (R²=0.85), while maximum constriction speed followed an exponential decay (R²=0.80). Response latency showed no significant relationship with age (R²=0.01), suggesting that initial response timing remains relatively preserved despite other age-related changes.

Temporal Perception and Time Dilation

Age-related slowing of PLR dynamics may reflect a broader slowing of neural "clock speed." If perceptual and cognitive events are sampled more slowly, subjective experience remains internally coherent while objective time advances further between sampled events. This provides a mechanistic account of why time appears to accelerate with age, consistent with neurocomputational models of temporal perception.

Consider: if a neural event that required 100ms at age 20 requires 150ms at age 70, the subjective experience of that event remains constant while objective time has progressed 50% further. Accumulated across millions of neural events, this produces the sensation that time is "speeding up" when in fact one's internal processing has slowed down. The pupillary system, with its rapid time course and precise measurement, may offer an objective correlate of this subjective phenomenon.

Cognitive Age as a Biomarker

The high R² values observed for multiple parameters (particularly diameter and speed measures, R² > 0.80) suggest that PLR metrics could serve as biomarkers for "cognitive age." Unlike chronological age, cognitive age reflects actual neurophysiological function and may better predict cognitive performance, disease risk, and functional capacity.

A composite PLR-derived metric combining speed, diameter, and temporal parameters could estimate cognitive age. Individuals whose PLR profile resembles younger cohorts may possess "younger" neural function regardless of birth date. Conversely, accelerated PLR aging could identify individuals at risk for cognitive decline before clinical symptoms emerge.

Clinical Implications

Because pupillometry is non-invasive, rapid, and inexpensive, PLR-based cognitive age estimation is well suited for large-scale screening and clinical deployment. Importantly, deviations between chronological and cognitive age may identify individuals at elevated risk for neurodegenerative and other neurological diseases before overt symptoms emerge. The observed changes likely reflect multiple mechanisms including reduced myelination, synaptic loss, reduced neurotransmitter function, and structural changes in the iris musculature.

Conclusion

Age-related changes in pupillary light reflex demonstrate measurable neurophysiological slowing that parallels cognitive decline across the lifespan. Highly correlated decreases in pupillary parameters provide an explanation for the neural basis of altered time perception in aging. PLR-derived metrics can estimate "cognitive age," potentially distinguishing chronological age from neurophysiological function.

This approach offers a rapid, non-invasive biomarker for cognitive aging that may enable early detection of decline and monitoring of interventions aimed at preserving cognitive function. Future research should examine the relationship between PLR parameters and subjective experience as a means of quantifying subjective time distortion, as well as environmental, genetic, and circadian influences on PLR aging.