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<p>Spontaneous fluctuations in attention can impede adaptation to changing goals and environments. Endogenous control over attentional shifts, referred to as attentional flexibility, is prone to disruption in children with attention deficit disorders. Here we studied in vivo intracranial recordings in children with epilepsy to identify a reproducible neural signature of attentional control that could predict and prevent impending lapses in real time. Machine learning classifiers were trained on intracranial signals while each child performed an attentional set-shifting task and predicted delays in attention shifting over multiple days and across several pediatric populations. Intracranial electrical stimulation in response to impending delays rescued attention shifts indexed by eye tracking, reaction time and accuracy. Simultaneous electroencephalography identified corresponding scalp signatures that enabled noninvasive modulation of attention shifting in healthy participants. These findings provide insight into the neural basis of attentional shifts with implications for targeted neuromodulation and exogenous attentional control.</p>

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Closed-loop stimulation modulates attention shifting in children

  • 期刊论文

  • 发表日期：

    2026年5月13日

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  • Nebras M. Warsi,
  • Simeon M. Wong,
  • Karim Mithani,
  • Sebastian C. Coleman,
  • Olivia N. Arski,
  • Hrishikesh Suresh,
  • Jürgen Germann,
  • Alexandre Boutet,
  • Lauren Erdman,
  • Flavia Venetucci Gouveia,
  • Barbara Berger,
  • Tamas Minarik,
  • Fa-Hsuan Lin,
  • Hsin-Ju Lee,
  • Benjamin R. Morgan,
  • Elizabeth Kerr,
  • Mary Lou Smith,
  • Ayako Ochi,
  • Hiroshi Otsubo,
  • Rohit Sharma,
  • Carolina Gorodetsky,
  • Puneet Jain,
  • Shelly Weiss,
  • Elizabeth J. Donner,
  • Andres M. Lozano,
  • O. Carter Snead,
  • Sabine Kastner,
  • Margot J. Taylor,
  • George M. Ibrahim

摘要

Spontaneous fluctuations in attention can impede adaptation to changing goals and environments. Endogenous control over attentional shifts, referred to as attentional flexibility, is prone to disruption in children with attention deficit disorders. Here we studied in vivo intracranial recordings in children with epilepsy to identify a reproducible neural signature of attentional control that could predict and prevent impending lapses in real time. Machine learning classifiers were trained on intracranial signals while each child performed an attentional set-shifting task and predicted delays in attention shifting over multiple days and across several pediatric populations. Intracranial electrical stimulation in response to impending delays rescued attention shifts indexed by eye tracking, reaction time and accuracy. Simultaneous electroencephalography identified corresponding scalp signatures that enabled noninvasive modulation of attention shifting in healthy participants. These findings provide insight into the neural basis of attentional shifts with implications for targeted neuromodulation and exogenous attentional control.