Many theories of complex cognitive-motor skill learning are built on the notion that basic cognitive processes group actions into easy-to-perform sequences. The present work examines predictions derived from laboratory-based studies of motor chunking and motor preparation using data collected from the real-time strategy video game StarCraft 2. We examined 996,163 action sequences in the telemetry data of 3,317 players across seven levels of skill. As predicted, the latency to the first action is delayed relative to the other actions in the (...) group. Other predictions, inspired by the memory drum theory of Henry and Rogers, received only weak support. (shrink)

The Action-sentence Compatibility Effect is often taken as supporting the fundamental role of the motor system in understanding sentences that describe actions. This effect would be related to an internal “simulation,” i.e., the reactivation of past perceptual and motor experiences. However, it is not easy to establish whether this simulation predominantly involves spatial imagery or motor anticipation. In the classical ACE experiments, where a real motor response is required, the direction and motor representations are mixed. In order to disentangle spatial (...) and motor aspects involved in the ACE, we performed six experiments in different conditions, where the motor component was always reduced, asking participants to judge the sensibility of sentences by moving a mouse, thus requiring a purely spatial representation, compatible with nonmotor interpretations. In addition, our experiments had the purpose of taking into account the possible confusion of effects of practice and of compatibility. Also, in contrast to the usual paradigm, we included no-transfer filler sentences in the analysis. The ACE was not found in any experiment, a result that failed to support the idea that the ACE could be related to a simulation where spatial aspects rather than motor ones prevail. Strong practice effects were always found and were carved out from results. A surprising effect was that no-transfer sentences were processed much slower than others, perhaps revealing a sort of participants’ awareness of the structure of stimuli, i.e., their finding that some of them involved motion and others did not. The relevance of these outcomes for the embodiment theory is discussed. (shrink)

Several canonical experimental paradigms have been proposed to study the typical behavioral phenomenon and the nature of learning in sequential keypress tasks. A characteristic feature of most paradigms is that they are representative of externally-specified sequencing—motor tasks where the environment or task paradigm extrinsically provides the sequence of stimuli, i.e., the responses are stimulus-driven. Previous studies utilizing such canonical paradigms have largely overlooked the learning behaviors in a more realistic class of motor tasks that involve internally-guided sequencing—where the sequence of (...) motor actions is self-generated or internally-specified. In this work, we use the grid-navigation task as an instance of internally-guided sequencing to investigate the nature of learning in such paradigms. The participants performed Grid-Sailing Task, which required navigating a 5 × 5 grid from start to goal position while using a particular key-mapping among the three cursor-movement directions and the three keyboard buttons. The participants performed two behavioral experiments—Single-SG and Mixed-SG condition. The Single-SG condition required performing GST on a single SG position repeatedly, whereas the Mixed-SG condition involved performing GST using the same KM on two novel SG positions presented in a random, inter-mixed manner. In the Single-SG condition, we show that motor learning contributes to the sequence-specific learning in GST with the repeated execution of the same trajectories. In the Mixed-SG condition, since the participants utilize the previously learned KM, we anticipate a transfer of learning from the Single-SG condition. The acquisition and transfer of a KM-specific internal model facilitates efficient trajectory planning on novel SG conditions. The acquisition of such a KM-specific internal model amounts to trajectory-independent cognitive learning in GST. We show that cognitive learning contributes to the learning in GST by showing transfer-related performance improvements in the Mixed-SG condition. In sum, we show the role of cognitive and motor learning processes in internally-guided sequencing and further make a case for using GST-like grid-navigation paradigms in investigating internally guided skill learning. (shrink)