# Citation Ghilardi, T. (Tommaso), Meyer, M. (Marlene), Hunnius, S. (Sabine) (2022). Predictive motor activation: Modulated by expectancy or predictability? [Data set]. https://doi.org/10.34973/hskr-3j38. # Abstract Predicting actions is a fundamental ability that helps us to comprehend what is happening in our environment and to interact with others. The motor system was previously identified as source of action predictions. Yet, which aspect of the statistical likelihood of upcoming actions the motor system is sensitive to remains an open question. This EEG study investigated how regularities in observed actions are reflected in the motor system and utilized to predict upcoming actions. Prior to measuring EEG, participants watched videos of action sequences with different transitional probabilities at home. After training, participants’ brain activity over motor areas was measured using EEG while watching videos of action sequences with the same statistical structure. Focusing on the mu and beta frequency bands we tested whether activity of the motor system reflects the statistical likelihood of upcoming actions. We also explored two distinct aspects of the statistical structure that reflect different prediction processes, expectancy and predictability. Expectancy reflects participants’ expectation of the most likely action minimizing the cognitive load to the expense of the prediction’s flexibility. On the other hand, predictability, represents all possible actions and their relative probabilities maximizing the flexibility of the prediction at the expenses of a higher cognitive load. Results revealed that mu and beta play different roles during action prediction. While the mu rhythm reflected anticipatory activity without any link to the statistical structure, the beta rhythm was related to the expectancy of an action. Our findings support theories proposing that the motor system underlies action prediction, and they extend such theories by showing that multiple forms of statistical information are extracted when observing action sequences. This information is integrated in the prediction generated by the neural motor system of which action is going to happen next. # Background information You can find more information, including relevant publications pertaining to this dataset on the collection overview page at https://doi.org/10.34973/hskr-3j38. A complete list of files that are part of this dataset can be found in the file MANIFEST.txt, including a SHA256 hash for each file to allow verification of correct data transfer. # Restrictions on data access and reuse The access to and use of this dataset is only allowed under the conditions listed in the data use agreement, as detailed in the file LICENSE.txt. Neither the Radboud University, nor the researchers that provide this dataset should be included as an author of publications or presentations if this authorship would be based solely on the use of this data. However, we ask you to acknowledge the use of the data and data derived from the data when publicly presenting any results or algorithms that benefitted from their use: 1) Papers, book chapters, books, posters, oral presentations, and all other presentations of results derived from the data should acknowledge the origin of the data as follows: "Data were provided (in part) by the Radboud University, Nijmegen, The Netherlands". 2) Authors of publications or presentations using the data should cite relevant publications describing the methods developed and used by the Radboud University to acquire and process the data. The specific publications that are appropriate to cite in any given study will depend on what the data were used for and for what purposes. When applicable, a list of publications will be specified on the collection overview page.