Distinguishing the Attentional Mechanisms of Distinct Mindfulness States: A Computational Modeling Comparison of Focused Attention and Open Monitoring

Abstract Objectives Focused attention (FA) and open monitoring (OM) meditation are theorized to confer distinct neurobehavioral influences, yet the specific cognitive mechanisms underlying these effects remain poorly understood. This study leveraged computational modeling to formally test and distinguish how these two mindfulness states modulate theoretical processes of attention control. Method We analyzed flanker task data from a prior study in which 29 meditation-naïve participants completed a fully within-subject crossover protocol, involving brief state inductions of FA, OM, and active control. We then fit a shrinking spotlight (SSP) computational model to quantify parameters of attentional scope, decision thresholds, and nondecision-related processing. Results As hypothesized, FA decreased the maximum “width” of the attentional spotlight compared to OM and control conditions (all t >|8.43|, all p < 0.001), while slowing the rate of narrowing (all t >|7.29|, all p < 0.001). In contrast, OM accelerated the rate of attention narrowing ( t (82) = 2.18, p = 0.032) and increased nondecision time (all t > 2.01, all p < 0.048). Conclusions These results indicate that FA narrows attentional scope, possibly reducing initial distraction but with limitations to rapidly recalibrate attention beyond the initial scope of focus. In contrast, OM appears to improve the speed of selecting relevant targets, while slowing perceptual-motor encoding and motor execution. Together, these findings provide model-based evidence for the distinct attentional mechanisms of FA and OM and illustrate the utility of computational cognitive modeling for testing key theories within mindfulness science. Preregistration This study was not preregistered.

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Journal
Mindfulness
Published
2026-03-09
DOI
https://doi.org/10.1007/s12671-026-02781-2
Primary Topic
Mindfulness and Compassion Interventions
Type
article
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article

Distinguishing the Attentional Mechanisms of Distinct Mindfulness States: A Computational Modeling Comparison of Focused Attention and Open Monitoring

Yanli Lin, Grant S. Shields
Mindfulness
Mindfulness and Compassion Interventions
article

Distinguishing the Attentional Mechanisms of Distinct Mindfulness States: A Computational Modeling Comparison of Focused Attention and Open Monitoring

Yanli Lin, Grant S. Shields
article en

Abstract

Abstract Objectives Focused attention (FA) and open monitoring (OM) meditation are theorized to confer distinct neurobehavioral influences, yet the specific cognitive mechanisms underlying these effects remain poorly understood. This study leveraged computational modeling to formally test and distinguish how these two mindfulness states modulate theoretical processes of attention control. Method We analyzed flanker task data from a prior study in which 29 meditation-naïve participants completed a fully within-subject crossover protocol, involving brief state inductions of FA, OM, and active control. We then fit a shrinking spotlight (SSP) computational model to quantify parameters of attentional scope, decision thresholds, and nondecision-related processing. Results As hypothesized, FA decreased the maximum “width” of the attentional spotlight compared to OM and control conditions (all t >|8.43|, all p < 0.001), while slowing the rate of narrowing (all t >|7.29|, all p < 0.001). In contrast, OM accelerated the rate of attention narrowing ( t (82) = 2.18, p = 0.032) and increased nondecision time (all t > 2.01, all p < 0.048). Conclusions These results indicate that FA narrows attentional scope, possibly reducing initial distraction but with limitations to rapidly recalibrate attention beyond the initial scope of focus. In contrast, OM appears to improve the speed of selecting relevant targets, while slowing perceptual-motor encoding and motor execution. Together, these findings provide model-based evidence for the distinct attentional mechanisms of FA and OM and illustrate the utility of computational cognitive modeling for testing key theories within mindfulness science. Preregistration This study was not preregistered.

Mindfulness
University of Arkansas at Fayetteville (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 34%
Mindfulness and Compassion Interventions
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Distinguishing the Attentional Mechanisms of Distinct Mindfulness States: A Computational Modeling Comparison of Focused Attention and Open Monitoring — Yanli Lin, Grant S. Shields · Mindfulness (2026) | TGRS Research Map | TGRS