The neuroscience of volition is an emerging subfield of the brain sciences, with hundreds of papers on the role of consciousness in action initiation published each year. This makes the state-of-the-art in the discipline poorly accessible to newcomers, as well as difficult to follow for already engaged researchers. Here we aim to provide a comprehensive introduction to the field, with newcomers in mind. Furthermore, by means of systematic review, we identified interesting ideas that received little to no coverage in the literature, and which might hence prove useful even to experts in the field. We reviewed a set of more than 2100 papers following Benjamin Libet’s seminal experiment. With a detailed consideration for close to 500 of the most relevant papers, we extensively introduce the reader to Libet’s work (both his early studies on delays in conscious processing and his later, 1980’s experiments on volitional actions). We follow with common criticisms of temporal introspection, the interpretational challenges of the assumed physiological and anatomical correlates of volition, conceptual issues with the classical interpretation of Libet’s experiment. We conclude with recent advances and potential future directions of the field.

The human ability for random-sequence generation (RSG) is limited but improves in a competitive game environment with feedback. However, it remains unclear how random people can be during games and whether RSG during games can improve when explicitly informing people that they must be as random as possible to win the game. Nor is it known whether any such improvement in RSG transfers outside the game environment. To investigate this, we designed a pre/post intervention paradigm around a Rock-Paper-Scissors game followed by a questionnaire. During the game, we manipulated participants’ level of awareness of the computer’s strategy; they were either (a) not informed of the computer’s algorithm or (b) explicitly informed that the computer used patterns in their choice history against them, so they must be maximally random to win. Using a compressibility metric of randomness, our results demonstrate that human RSG can reach levels statistically indistinguishable from computer pseudo- random generators in a competitive-game setting. However, our results also suggest that human RSG cannot be further improved by explicitly informing participants that they need to be random to win. In addition, the higher RSG in the game setting does not transfer outside the game environment. Furthermore, we found that the underrepresentation of long repetitions of the same entry in the series explains up to 29% of the variability in human RSG, and we discuss what might make up the variance left unexplained.