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Updated: May 15, 2026

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Closed-loop stimulation modulates attention shifting in children.

Nebras M Warsi1,2, Simeon M Wong2,3, Karim Mithani1,2

  • 1Division of Neurosurgery, The Hospital for Sick Children, Toronto, Ontario, Canada.

Nature Neuroscience
|May 13, 2026
PubMed

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Summary
This summary is machine-generated.

Researchers identified a brain signal predicting attention lapses in children. Real-time brain stimulation using this signal improved attention control, offering new therapeutic possibilities for attention deficits.

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Neuromodulation

Background:

  • Spontaneous attention fluctuations disrupt adaptation to changing environments.
  • Attentional flexibility is impaired in children with attention deficit disorders.
  • Understanding the neural basis of attentional control is crucial for developing interventions.

Purpose of the Study:

  • To identify a reproducible neural signature of attentional control in children.
  • To predict and prevent attention lapses in real time using intracranial recordings.
  • To explore the potential for targeted neuromodulation to enhance attentional flexibility.

Main Methods:

  • In vivo intracranial recordings were obtained from children with epilepsy during an attentional set-shifting task.

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Last Updated: May 15, 2026

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Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning

Published on: October 22, 2015

  • Machine learning classifiers were trained to predict delays in attention shifting.
  • Intracranial electrical stimulation was applied in response to predicted attention lapses.
  • Simultaneous electroencephalography (EEG) was used to identify scalp signatures.

    • Main Results:

    • A reproducible neural signature of attentional control was identified.
    • Machine learning models accurately predicted attention shifting delays.
    • Intracranial electrical stimulation successfully rescued attention shifts, improving eye tracking, reaction time, and accuracy.
    • Corresponding scalp signatures were identified via EEG, enabling noninvasive modulation.

    Conclusions:

    • The study reveals a neural basis for attentional shifts and control.
    • Real-time prediction and modulation of attention lapses are feasible.
    • Findings have implications for targeted neuromodulation and exogenous attentional control strategies.
    • This research offers potential for novel interventions for attention deficits.