Using neural networks to uncover the relationship between highly variable behavior and eeg during a working memory task with distractors

HIGHLIGHTS

• who: Christine Beauchene et al. from the Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA have published the Article: Using Neural Networks to Uncover the Relationship between Highly Variable Behavior and EEG during a Working Memory Task with Distractors, in the Journal: Mathematics 2022, 1848 of /2022/
• what: The authors develop the first participant-specific feedforward neural network models of reaction time from neural data during a VDAC WM task. The study shows that NN models can link neural activity to highly variable behavior and can identify potential new targets for . . .
  

   

  

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