Lucas Y. Tian

Abstract A hallmark of intelligence is proficiency in solving new problems, including those that substantially differ from previously seen problems. Problem solving in turn depends on the goal-directed generation of novel ideas and behaviours1, which has been proposed to involve internal representations of discrete units (or symbols) that can be recombined into numerous possible composite representations1,2,3,4,5,6,7.

Abstract At the core of intelligence is proficiency in solving new problems, including those that differ dramatically from problems seen before. Problem-solving, in turn, depends on goal-directed generation of novel thoughts and behaviors, which has been proposed to rely on internal representations of discrete units, or symbols, and processes that can recombine them into a large set of possible composite representations.

We used a modified version of EvTaf that enabled electrical stimulation to be delivered independently of WN feedback. In order to stimulate at a controlled time relative to the syllable targeted for learning, we detected ‘predictor’ syllables that consistently preceded the targeted syllable.