Abstract
Is the cognitive process of random number generation implemented via person-specific strategies corresponding to highly individual random generation behaviour? We examined random number sequences of 115 healthy participants and developed a method to quantify the similarity between two number sequences on the basis of Damerau and Levenshtein’s edit distance. “Same-author” and “different author” sequence pairs could be distinguished (96.5% AUC) based on 300 pseudo-random digits alone. We show that this phenomenon is driven by individual preference and inhibition of patterns and stays constant over a period of 1 week, forming a cognitive fingerprint.
Highlights
Is the cognitive process of random number generation implemented via person-specific strategies corresponding to highly individual random generation behaviour? We examined random number sequences of 115 healthy participants and developed a method to quantify the similarity between two number sequences on the basis of Damerau and Levenshtein’s edit distance
We address the general question of interindividual differences in the specific context of human random number generation and search for a cognitive fingerprint in random sequences
In the present study we address interindividual differences in the cognitive process of random number generation
Summary
Is the cognitive process of random number generation implemented via person-specific strategies corresponding to highly individual random generation behaviour? We examined random number sequences of 115 healthy participants and developed a method to quantify the similarity between two number sequences on the basis of Damerau and Levenshtein’s edit distance. “Same-author” and “different author” sequence pairs could be distinguished (96.5% AUC) based on 300 pseudo-random digits alone We show that this phenomenon is driven by individual preference and inhibition of patterns and stays constant over a period of 1 week, forming a cognitive fingerprint. Variations in executive function are reflected in the characteristic ways in which humans deviate from mathematical randomness[2] Based on this premise, random number generation has previously been used to investigate cognitive changes in brain disorders, such as in Parkinson’s disease and s chizophrenia[3,4]. The sum of the inverses of the distances (each incremented by one to avoid dividing by zero), divided by the sequence length, returns the score of the pattern on the random sequence The efficacy of this approach was demonstrated by predicting the pseudorandom sequences based on the sequence’s immediate history.
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