Introduction.
Perceptual load refers to the amount and complexity of visual information processed in a given task. Understanding how it affects recognition performance is fundamental to cognitive psychology and applied contexts such as education, human factors, and visual safety. According to Lavie's Perceptual Load Theory, when visual complexity increases, attentional resources become limited, reducing awareness of irrelevant stimuli.


Objective.
This study examined how different levels of perceptual load influence accuracy and reaction times in recognizing visual stimuli, and whether these effects provide empirical support for selective attention mechanisms described by Lavie (1995, 2010).


Method.
Sixty university students (aged 18-25) participated in a computerized visual task developed in PsychoPy and executed on Pavlovia. Participants viewed geometric figures under two conditions: (1) low perceptual load - simple shapes (triangles, squares, circles) in solid primary colors; and (2) high perceptual load - complex, irregular figures with gradients and patterns. Each stimulus was displayed for 500 ms, followed by response screens measuring recognition accuracy, reaction time, and cognitive strategy (memory, familiarity, intuition, or guessing).


Results.
Data from ~2200 trials showed significant differences between conditions. Under low load, participants achieved higher recognition accuracy (76.7 %) and faster reaction times (1.47 s) compared with high load (61.6 %, 1.63 s). Independent t-tests confirmed these effects as statistically significant.


Conclusions.
The results confirm that perceptual load strongly modulates visual attention and recognition processes. Increased visual complexity constrains attentional capacity, leading to slower and less accurate recognition. These findings support Lavie's model and align with irrelevance-induced blindness frameworks (Eitam & Higgins, 2010). Understanding how perceptual load affects selective attention has practical implications for optimizing educational materials, improving visual ergonomics in complex environments, and enhancing clinical assessments of attentional control.