Action-effect Learning Research Articles

Action–effect knowledge transfers to similar effect stimuli

The ability to anticipate the sensory consequences of our actions (i.e., action–effects) is known to be important for intentional action initiation and control. Learned action–effects can select the responses that previously have been associated with them. What has been largely unexplored is how learned action–effect associations can aid action selection for effects that have not previously associated with an action but are similar to learned effects. In two studies, we aimed to show that when presented new, unknown action–effects, participants select the responses that have previously been associated with similar action–effects. In the first study (n = 27), action–effect similarity was operationalized via stimuli belonging to the same or different categories as the previously learned action–effects. In the second study (n = 31), action–effect similarity was realized via stimuli that require comparable motor responses in real life. Participants first learned that specific responses are followed by specific visual effect stimuli. In the test phase, learned effect stimuli, new but similar effect stimuli and new but dissimilar effect stimuli were presented ahead of the response. The findings revealed that both learned effect stimuli and new similar effect stimuli affected response times, whereas new dissimilar effects did not. When a learned or a new similar effect was followed by a learned response, compared to an unlearned response, the responses were faster. We interpret these findings in terms of action–effect learning. The action–effect once bound to an action is used to select an action if a similar effect for which no action has been learned yet is presented. However, it is noteworthy that, due to our design, other explanations for the found transfer are conceivable. We address these limitations in the General Discussion.

Unintentional response priming from verbal action–effect instructions

Action–effect learning is based on a theoretical concept that actions are associated with their perceivable consequences through bidirectional associations. Past research has mostly investigated how these bidirectional associations are formed through actual behavior and perception of the consequences. The present research expands this idea by investigating how verbally formulated action–effect instructions contribute to action–effect learning. In two online experiments (Exp. 1, N = 41, student sample; Exp. 2, N = 349, non-student sample), participants memorized a specific action–effect instruction before completing a speeded categorization task. We assessed the consequences of the instructions by presenting the instructed effect as an irrelevant stimulus in the classification task and compared response errors and response times for instruction-compatible and instruction-incompatible responses. Overall, we found evidence that verbal action–effect instructions led to associations between an action and perception (effect) that are automatically activated upon encountering the previously verbally presented effect. In addition, we discuss preliminary evidence suggesting that the order of the action–effect components plays a role; only instructions in a perception–action order showed the expected effect. The present research contributes evidence to the idea that action–effect learning is not exclusively related to actual behavior but also achievable through verbally formulated instructions, thereby providing a flexible learning mechanism that does not rely on specific actual experiences.

Learning to expect and monitor the future: How fast do anticipatory saccades toward future action consequences emerge?

When an action contingently yields the same effect, we form bidirectional action-effect associations that allow us to anticipate the effects of our actions. Importantly, our eyes already move toward the expected future location of our actions' effects in anticipation of them, that is, we perform anticipatory saccades. These anticipatory saccades are linked to a proactive effect-monitoring process that prepares the comparison of expected and actual effect. However, how fast such anticipatory saccades emerge (i.e., how fast learning leads to monitoring) is unknown. To address this question, correct left/right responses were followed by a visual effect either on the same side (response-effect compatible) or on the opposite side (response-effect incompatible). In Experiment 1, action-effect compatibility switched after sequences of four, eight, or 12 trials (randomly allocated; partly predictable environment). In Experiment 2, random trials (two to seven) separated sequences of three, five, or seven experimental trials. Again, action-effect compatibility switched after a sequence of trials and sequences were randomly allocated (unpredictable environment). In both experiments, participants started to perform anticipatory saccades toward future effects after experiencing a new action-effect mapping once/twice (response-effect compatible/incompatible). That is, a single to two action-effect (re-)learning instances were sufficient to develop action-effect associations that trigger attentional shifts toward the expected future consequences of our actions (i.e., monitoring processes), whereas influences on action selection are only observed after a substantially larger number of (re-)learning instances. These results suggest that monitoring processes modulate the expression of action-effect associations in action planning based on observed action-effect contingencies. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Revisiting intersubjective action-effect binding: No evidence for social moderators.

Effect-based accounts of human action control have recently highlighted the possibility of representing one's own actions in terms of anticipated changes in the behavior of social interaction partners. In contrast to action effects that pertain to the agent's body or the agent's physical environment, social action effects have been proposed to come with peculiarities inherent to their social nature. Here, we revisit the currently most prominent demonstration of such a peculiarity: the role of eye contact for action-effect learning in social contexts (Sato & Itakura, 2013, Cognition, 127, 383-390). In contrast to the previous demonstration of action-effect learning, a conceptual and a direct replication both yielded evidence for the absence of action-effect learning in the proposed design, irrespective of eye contact. Bayesian statistics supported this claim by demonstrating evidence in favor of the null hypothesis of no effect. These results suggest a limited generalizability of the original findings-for example, due to limitations that are inherent in the proposed study design or due to cultural differences.

Effect-based action control with body-related effects: Implications for empirical approaches to ideomotor action control.

Ideomotor accounts of human action control posit that human agents represent actions in terms of their perceivable consequences; selecting, planning, and initiating a voluntary action is thus assumed to be mediated by action-effect anticipations. Corresponding empirical investigations have often employed arbitrary effects in the agent's environment to study action-effect learning and effect-based action control. This strategy has provided accumulating evidence in support of ideomotor mechanisms, but the widespread focus on environment-related action effects has also created misperceptions of what ideomotor accounts aim to explain. Moreover, this strategy has also given rise to misunderstandings of critical epistemological limitations, especially regarding the theoretical relevance of negative results in common experimental paradigms. These recent developments call for a theoretical clarification of the concept of action effects. I propose that many misunderstandings can be resolved by embracing the theoretical role of body-related compared to environment-related actions' effects. I show how the concept of such effects may inform current debates and how this focus can guide future research related to ideomotor action control, with a main challenge being the derivation of testable and falsifiable theories from the ideomotor framework. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Action-Effect Associations in Voluntary and Cued Task-Switching.

The literature of action control claims that humans control their actions in two ways. In the stimulus-based approach, actions are triggered by external stimuli. In the ideomotor approach, actions are elicited endogenously and controlled by the intended goal. In the current study, our purpose was to investigate whether these two action control modes affect task-switching differently. We combined a classical task-switching paradigm with action-effect learning. Both experiments consisted of two experimental phases: an acquisition phase, in which associations between task, response and subsequent action effects were learned and a test phase, in which the effects of these associations were tested on task performance by presenting the former action effects as preceding effects, prior to the task (called practiced effects). Subjects either chose freely between tasks (ideomotor action control mode) or they were cued as to which task to perform (sensorimotor action control mode). We aimed to replicate the consistency effect (i.e., task is chosen according to the practiced task-effect association) and non-reversal advantage (i.e., better task performance when the practiced effect matches the previously learned task-effect association). Our results suggest that participants acquired stable action-effect associations independently of the learning mode. The consistency effect (Experiment 1) could be shown, independent of the learning mode, but only on the response-level. The non-reversal advantage (Experiment 2) was only evident in the error rates and only for participants who had practiced in the ideomotor action control mode.

Anticipation of delayed action-effects: learning when an effect occurs, without knowing what this effect will be.

According to the ideomotor principle, behavior is controlled via a retrieval of the sensory consequences that will follow from the respective movement ("action-effects"). These consequences include not only what will happen, but also when something will happen. In fact, recollecting the temporal duration between response and effect takes time and prolongs the initiation of the response. We investigated the associative structure of action-effect learning with delayed effects and asked whether participants acquire integrated action-time-effect episodes that comprise a compound of all three elements or whether they acquire separate traces that connect actions to the time until an effect occurs and actions to the effects that follow them. In three experiments, results showed that participants retrieve temporal intervals that follow from their actions even when the identity of the effect could not be learned. Furthermore, retrieval of temporal intervals in isolation was not inferior to retrieval of temporal intervals that were consistently followed by predictable action-effects. More specifically, when tested under extinction, retrieval of action-time and action-identity associations seems to compete against each other, similar to overshadowing effects reported for stimulus-response conditioning. Together, these results suggest that people anticipate when the consequences of their action will occur, independently from what the consequences will be.

HiTEC: a connectionist model of the interaction between perception and action planning

Increasing evidence suggests that perception and action planning do not represent separable stages of a unidirectional processing sequence, but rather emerging properties of highly interactive processes. To capture these characteristics of the human cognitive system, we have developed a connectionist model of the interaction between perception and action planning: HiTEC, based on the Theory of Event Coding (Hommel et al. in Behav Brain Sci 24:849–937, 2001). The model is characterized by representations at multiple levels and by shared representations and processes. It complements available models of stimulus–response translation by providing a rationale for (1) how situation-specific meanings of motor actions emerge, (2) how and why some aspects of stimulus–response translation occur automatically and (3) how task demands modulate sensorimotor processing. The model is demonstrated to provide a unitary account and simulation of a number of key findings with multiple experimental paradigms on the interaction between perception and action such as the Simon effect, its inversion (Hommel in Psychol Res 55:270–279, 1993), and action–effect learning.

Influence of action-effect associations acquired by ideomotor learning on imitation.

According to the ideomotor theory, actions are represented in terms of their perceptual effects, offering a solution for the correspondence problem of imitation (how to translate the observed action into a corresponding motor output). This effect-based coding of action is assumed to be acquired through action-effect learning. Accordingly, performing an action leads to the integration of the perceptual codes of the action effects with the motor commands that brought them about. While ideomotor theory is invoked to account for imitation, the influence of action-effect learning on imitative behavior remains unexplored. In two experiments, imitative performance was measured in a reaction time task following a phase of action-effect acquisition. During action-effect acquisition, participants freely executed a finger movement (index or little finger lifting), and then observed a similar (compatible learning) or a different (incompatible learning) movement. In Experiment 1, finger movements of left and right hands were presented as action-effects during acquisition. In Experiment 2, only right-hand finger movements were presented during action-effect acquisition and in the imitation task the observed hands were oriented orthogonally to participants’ hands in order to avoid spatial congruency effects. Experiments 1 and 2 showed that imitative performance was improved after compatible learning, compared to incompatible learning. In Experiment 2, although action-effect learning involved perception of finger movements of right hand only, imitative capabilities of right- and left-hand finger movements were equally affected. These results indicate that an observed movement stimulus processed as the effect of an action can later prime execution of that action, confirming the ideomotor approach to imitation. We further discuss these findings in relation to previous studies of action-effect learning and in the framework of current ideomotor approaches to imitation.

Response selection difficulty modulates the behavioral impact of rapidly learnt action effects.

It is well-established that we can pick up action effect associations when acting in a free-choice intentional mode. However, it is less clear whether and when action effect associations are learnt and actually affect behavior if we are acting in a forced-choice mode, applying a specific stimulus–response (S–R) rule. In the present study, we investigated whether response selection difficulty imposed by S–R rules influences the initial rapid learning and the behavioral expression of previously learnt but weakly practiced action effect associations when those are re-activated by effect exposure. Experiment 1 showed that the rapid learning of action effect associations is not directly influenced by response selection difficulty. By contrast, the behavioral expression of re-activated action effect associations is prevented when actions are directly activated by highly over-learnt response cues and thus response selection difficulty is low. However, all three experiments showed that if response selection difficulty is sufficiently high during re-activation, the same action effect associations do influence behavior. Experiments 2 and 3 revealed that the effect of response selection difficulty cannot be fully reduced to giving action effects more time to prime an action, but seems to reflect competition during response selection. Finally, the present data suggest that when multiple novel rules are rapidly learnt in succession, which requires a lot of flexibility, action effect associations continue to influence behavior only if response selection difficulty is sufficiently high. Thus, response selection difficulty might modulate the impact of experiencing multiple learning episodes on action effect expression and learning, possibly via inducing different strategies.

Associating peripheral and foveal visual input across saccades: a default mode of the human visual system?

Spatial processing resolution of a particular object in the visual field can differ considerably due to eye movements. The same object will be represented with high acuity in the fovea but only coarsely in periphery. Herwig and Schneider (in press) proposed that the visual system counteracts such resolution differences by predicting, based on previous experience, how foveal objects will look in the periphery and vice versa. They demonstrated that previously learned transsaccadic associations between peripheral and foveal object information facilitate performance in visual search, irrespective of the correctness of these associations. False associations were learned by replacing the presaccadic object with a slightly different object during the saccade. Importantly, participants usually did not notice this object change. This raises the question of whether perception of object continuity is a critical factor in building transsaccadic associations. We disturbed object continuity during learning with a postsaccadic blank or a task-irrelevant shape change. Interestingly, visual search performance revealed that neither disruption of temporal object continuity (blank) nor disruption of spatial object continuity (shape change) impaired transsaccadic learning. Thus, transsaccadic learning seems to be a very robust default mechanism of the visual system that is probably related to the more general concept of action-effect learning.

Representing the hyphen in action-effect associations: automatic acquisition and bidirectional retrieval of action-effect intervals.

We examined whether a temporal interval between an action and its sensory effect is integrated in the cognitive action structure in a bidirectional fashion. In 3 experiments, participants first experienced that actions produced specific acoustic effects (high and low tones) that occurred temporally delayed after their actions. In a following test phase, the tones that were presented as action effects in the previous phase were now presented as primes for the responses that had caused them previously and, critically, also as primes for the interval that previously separated action and effects. The tones were presented as go-signals in a free-choice test and as response-imperative stimuli in a forced-choice test. In the free choice test, participants were more likely to choose responses consistent with the previous pairing, but these responses were initiated slower than responses that were inconsistent with previous action-effect learning (Experiment 1). Effect-consistent responses were also initiated slower in the speeded forced-choice test (Experiment 2). These observations suggest that retrieval of a long action-effect interval slows down response initiation. In Experiment 3, response-contingent effects were presented with a long or short delay after a response. Reaction times in both, a forced-choice and free-choice setup, were faster in the short- than in the long-interval condition. We conclude that temporal information about the interval between actions and effects is integrated into a cognitive action structure and is automatically retrieved during response selection.

The interaction between attention and motor prediction. An ERP study

Performing a voluntary action involves the anticipation of the intended effect of that action. Interaction with the environment also requires the allocation of attention. However, the effects of attention upon motor predictive processes remain unclear. Here we use a novel paradigm to investigate attention and motor prediction orthogonally. In an acquisition phase, high and low tones were associated with left and right key presses. In the following test phase, tones were presented at random and participants attended to only one ear whilst ignoring tones presented in the unattended ear. In the test phase a tone could therefore be presented at the attended or unattended ear, as well as being congruent or incongruent with prior action–effect learning. We demonstrated early and late effects of attention as well as a later independent motor prediction effect with a larger P3a for incongruent tones. Interestingly, we demonstrated an intermediate interaction, showing an action–effect negativity (NAE) for tones which were unattended, whilst no motor prediction effect was found for attended tones. This interaction pattern suggests that attention and motor prediction are not opposing processes but can both operate to modulate prediction, providing valuable new insight into the relationship between attention and the effects of motor prediction.

The neural substrate of the ideomotor principle revisited: Evidence for asymmetries in action-effect learning

Ideomotor theory holds that the perception or anticipatory imagination of action effects activates motor tendencies toward the action that is known to produce these effects, herein referred to as ideomotor response activation (IRA). IRA presupposes that the agent has previously learned which action produces which effects, and that this learning process has created bidirectional associations between the sensory effect codes and the motor codes producing the sensory effects. Here, we refer to this process as ideomotor learning. In the presented fMRI study, we adopted a standard two-phase ideomotor learning paradigm; a mixed between/within-subjects design allowed us to assess the neural substrate of both, IRA and ideomotor learning. We replicated earlier findings of a hand asymmetry in ideomotor processing with significantly stronger IRA by left-hand than right-hand action effects. Crucially, we traced this effect back to more pronounced associative learning for action-contingent effects of the left hand compared with effects of the right hand. In this context, our findings point to the caudate nucleus and the angular gyrus as central structures of the neural network underlying ideomotor learning.

Too Good to be True? Ideomotor Theory from a Computational Perspective.

In recent years, Ideomotor Theory has regained widespread attention and sparked the development of a number of theories on goal-directed behavior and learning. However, there are two issues with previous studies’ use of Ideomotor Theory. Although Ideomotor Theory is seen as very general, it is often studied in settings that are considerably more simplistic than most natural situations. Moreover, Ideomotor Theory’s claim that effect anticipations directly trigger actions and that action-effect learning is based on the formation of direct action-effect associations is hard to address empirically. We address these points from a computational perspective. A simple computational model of Ideomotor Theory was tested in tasks with different degrees of complexity. The model evaluation showed that Ideomotor Theory is a computationally feasible approach for understanding efficient action-effect learning for goal-directed behavior if the following preconditions are met: (1) The range of potential actions and effects has to be restricted. (2) Effects have to follow actions within a short time window. (3) Actions have to be simple and may not require sequencing. The first two preconditions also limit human performance and thus support Ideomotor Theory. The last precondition can be circumvented by extending the model with more complex, indirect action generation processes. In conclusion, we suggest that Ideomotor Theory offers a comprehensive framework to understand action-effect learning. However, we also suggest that additional processes may mediate the conversion of effect anticipations into actions in many situations.

Early Markers of Ongoing Action-Effect Learning

Acquiring knowledge about the relationship between stimulus conditions, one’s own actions, and the resulting consequences or effects, is one prerequisite for intentional action. Previous studies have shown that such contextualized associations between actions and their effects (S-R-E associations) can be picked up very quickly. The present study examined how such weakly practiced associations might affect overt behavior during the process of initial learning and during subsequent retrieval, and how these two measures are inter-related. We examined incidental (S-)R-E learning in the context of trial-and-error S-R learning and in the context of instruction-based S-R learning. Furthermore, as a control condition, common outcome (CO) learning blocks were included in which all responses produced one common sound effect, hence precluding differential (S-)R-E learning. Post-learning retrieval of R-E associations was tested by re-using previously produced sound effects as novel imperative stimuli combined with actions that were either compatible or incompatible with the previously encountered R-E mapping. The central result was that the size of the compatibility effect could be predicted by the size of relative response slowing during ongoing learning in the preceding acquisition phase, both in trial-and-error learning and in instruction-based learning. Importantly, this correlation was absent for the CO control condition, precluding accounts based on unspecific factors. Instead, the results suggest that differential outcomes are “actively” integrated into action planning and that this takes additional planning time. We speculate that this might be especially true for weakly practiced (S-)R-E associations before an initial goal-directed action mode transitions into a more stimulus-based action mode.

On the timescale of stimulus-based action–effect learning

When performing an action, people pick up associations between their actions and the resulting consequences of that action, a phenomenon that has been termed response (R)-effect (E) learning. In the present study, we investigated incidental R-E learning in a forced-choice-that is, a stimulus (S)-based-acquisition mode. Specifically, the study examined at which timescale R-E learning evolves-that is, how many encounters are actually needed to form stable R-E associations. The learning of R-E associations was assessed in a subsequent test phase via effect-based response priming. Experiment 1 tested 4 different numbers of S-R-E repetitions for a 2-2-2 S-R-E mapping. Experiment 2 disentangled the contributions of S-E and R-E associations to the facilitating impact of effect-based response priming by means of a 4-2-4 S-R-E mapping. Experiment 3 investigated whether R-E associations can be picked up even when a given E cannot be unequivocally predicted based on the antecedent S in case of inconsistent S-R-E couplings. Together, the results of the present study clearly show that R-E learning occurs in a stimulus-based action mode and that it evolves very rapidly after only 12 S-R-E repetitions. Moreover, the present findings suggest that at least in this initial phase of learning, complete S-R-E consistency seems to be relevant for R-E learning.

Time in action contexts: learning when an action effect occurs

Action effects do not occur randomly in time but follow our actions at specific delays. The ideomotor principle (IMP) is widely used to explain how the relation between actions and contingently following effects is acquired and numerous studies demonstrate robust action-effect learning. Yet, little is known about the acquisition of temporal delays of action effects. Here, we demonstrate that participants learn that action effects occur at specific delays. Participants responded slower to action effects that occurred earlier than usual. In addition, participants often prematurely responded before the effect when it occurred later than expected. Thus, in contrast to biases of time perception in action contexts (e.g., Haggard, Trends Cogn Sci 9:290-295, 2005; Stetson et al., Neuron 51:651-659, 2006), participants learn and exploit temporal regularities between actions and effects for behavioral control.

Action-effect learning in early childhood: does language matter?

Previous work showed that language has an important function for the development of action control. This study examined the role of verbal processes for action–effect learning in 4-year-old children. Participants performed an acquisition phase including a two-choice key-pressing task in which each key press (action) was followed by a particular sound (effect). Children were instructed to either (1) label their actions along with the corresponding effects, (2) verbalize task-irrelevant words, (3) or perform without verbalization. In a subsequent test phase, they responded to the same sound effects either under consistent or under inconsistent sound-key mappings. Evidence for action–effect learning was obtained only if action and effects were labeled or if no verbalization was performed, but not if children verbalized task-irrelevant labels. Importantly, action–effect learning was most pronounced when children verbalized the actions and the corresponding effects, suggesting that task-relevant verbal labeling supports the integration of event representations.

Learning at any rate: action–effect learning for stimulus-based actions

Recent studies reported converging evidence for action-effect associations if participants adopted an intention-based action control mode in free choice conditions, whereas no evidence for action-effect associations was found when participants adopted a stimulus-based mode in forced choice conditions. However, it is not yet clear whether action control modes moderate acquisition or usage of action-effect associations. In the present experiment, two groups of participants underwent an acquisition phase consisting of either free or forced choice key presses that produced irrelevant, but contingent effect tones. In a subsequent test phase, participants freely chose the key to press after former effect tones were presented. A reliable consistency effect resulted for both the groups, i.e. participants preferred the key that produced the irrelevant tone in the preceding acquisition phase. In combination with prior findings, this consistency effect suggests that usage, but not acquisition of action-effect associations depends on an intention-based action control mode.