Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Selected Data About Geographic Locations

Selected Data About Geographic Locations

Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...

Avoidance Learning and Learned Helplessness

Avoidance Learning and Learned Helplessness

Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...

Censoring Survival Data

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...

Steps in Outbreak Investigation

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:

Subliminal Perception

Subliminal Perception

Subliminal perception refers to the processing of sensory information that occurs below the level of conscious awareness. Researchers study subliminal perception by presenting a stimulus, such as a word or image, very quickly, typically around 50 milliseconds. This rapid presentation is often followed by another stimulus, such as a pattern of dots or lines, which blocks further mental processing of the initial stimulus. As a result, if participants cannot identify the initial stimulus better...

Manipulation and Analysis

Manipulation and Analysis

GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Learned statistical regularity modulates anticipatory micro-saccades toward suppressed distractor locations.

Nature communications·2026

Same author

Visual Selection Is Spatially Constrained During Working Memory Consolidation.

Quarterly journal of experimental psychology (2006)·2026

Same author

35+ years of the additional singleton task: Design features and guidelines.

Attention, perception & psychophysics·2026

Same author

Dynamic competition between bottom-up saliency and top-down goals in early visual cortex.

Communications biology·2026

Same author

Sparse Spatial Scaffolding for Visual Working Memory.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026

Same author

Incidental learning of time-event relationships across processing stages.

Journal of experimental psychology. Human perception and performance·2026

Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026

Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026

Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026

Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026

Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026

Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Dec 20, 2025

Author Spotlight: Investigating the Impact of Aging on Hippocampal-Dependent Spatial Learning

Author Spotlight: Investigating the Impact of Aging on Hippocampal-Dependent Spatial Learning

Published on: February 16, 2024

Proactively location-based suppression elicited by statistical learning.

Siyang Kong¹, Xinyu Li¹, Benchi Wang^2,3,4,5

¹Department of Psychology, Zhejiang Normal University, Jinhua, China.

|June 2, 2020

Summary

This summary is machine-generated.

Statistical learning suppresses locations likely to contain distractors, reducing attentional capture. This pre-stimulus suppression enhances target attention by reallocating resources away from potential distractor sites.

More Related Videos

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

A Method for Remotely Silencing Neural Activity in Rodents During Discrete Phases of Learning

A Method for Remotely Silencing Neural Activity in Rodents During Discrete Phases of Learning

Published on: June 22, 2015

Related Experiment Videos

Last Updated: Dec 20, 2025

Author Spotlight: Investigating the Impact of Aging on Hippocampal-Dependent Spatial Learning

Author Spotlight: Investigating the Impact of Aging on Hippocampal-Dependent Spatial Learning

Published on: February 16, 2024

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

A Method for Remotely Silencing Neural Activity in Rodents During Discrete Phases of Learning

A Method for Remotely Silencing Neural Activity in Rodents During Discrete Phases of Learning

Published on: June 22, 2015

Area of Science:

Cognitive Psychology
Neuroscience
Visual Attention

Background:

Attentional capture by salient distractors is a fundamental aspect of visual processing.
Previous research indicated that statistical learning can reduce attentional capture at predictable distractor locations.
The underlying mechanisms of this predictive suppression and its effect on resource allocation remained unclear.

Purpose of the Study:

To replicate findings on reduced attentional capture at predictable distractor locations.
To investigate the initial distribution of attentional resources using a search-probe paradigm.
To test the predictions of space-based resource allocation models, such as biased competition.

Main Methods:

Replication of the additional singleton task to assess attentional capture.
Introduction of a search-probe condition to measure attentional resource distribution.
Comparison of probe representation suppression at predictable distractor locations versus other locations.

Main Results:

Confirmed that predictable distractor locations are suppressed due to statistical learning.
Demonstrated that probe representation at these suppressed locations was diminished, consistent with biased competition.
Showed that suppression of distractor locations led to increased attention allocation towards the target.

Conclusions:

Predictive suppression of distractor locations enhances target processing by reallocating attentional resources.
This suppression occurs before stimulus onset, influencing early visual processing.
Findings support models where attention is allocated based on learned statistical regularities of the visual environment.