On the influence of causal beliefs on the feeling of agency

The sense of agency is the experience of being the origin of a sensory consequence. This study investigates whether contextual beliefs modulate low-level sensorimotor processes which contribute to the emergence of the sense of agency. We looked at the influence of causal beliefs on ‘intentional binding’, a phenomenon which accompanies self-agency. Participants judged the onset-time of either an action or a sound which followed the action. They were induced to believe that the tone was either triggered by themselves or by somebody else, although, in reality, the sound was always triggered by the participants. We found that intentional binding was stronger when participants believed that they triggered the tone, compared to when they believed that another person triggered the tone. These results suggest that high-level contextual information influences sensorimotor processes responsible for generating intentional binding.     

Prime and probability: causal knowledge affects inferential and predictive effects on self-agency experiences

Experiences of having caused a certain outcome may arise from motor predictions based on action–outcome probabilities and causal inferences based on pre-activated outcome representations. However, when and how both indicators combine to affect such self-agency experiences is still unclear. Based on previous research on prediction and inference effects on self-agency, we propose that their (combined) contribution crucially depends on whether people have knowledge about the causal relation between actions and outcomes that is relevant to subsequent self-agency experiences. Therefore, we manipulated causal knowledge that was either relevant or irrelevant by varying the probability of co-occurrence (50% or 80%) of specific actions and outcomes. Afterwards, we measured self-agency experiences in an action–outcome task where outcomes were primed or not. Results showed that motor prediction only affected self-agency when relevant actions and outcomes were learned to be causally related. Interestingly, however, inference effects also occurred when no relevant causal knowledge was acquired.     

Valuing intervention and observation

Understanding causal relations is fundamental to effective action but causal data can be confounded. We examined the value that participants placed on data derived from a hypothetical intervention or observation. Our materials involved a possible cause (“bottled water”), a possible confound (“food”), and a context (“a restaurant”). We supposed that participants seek to draw as specific a causal inference as possible from presented data and value information sources more highly that allow them to do so. On this basis, we predicted that in circumstances where an intervention removed the confounding causal factor but observation did not, participants would prefer data derived from an intervention when the possible cause was present (the bottled water was drunk) but show the reverse preference when the possible cause was absent (the bottled water was not drunk). Experiment 1 confirmed this prediction. Using a between-subjects design, Experiment 2 tested for a difference in confidence in causal judgements given identical data, including data on the confound, as a function of method of data collection (intervention or observation). There was no significant difference in confidence ratings between the two methods but confidence ratings were sensitive to the probability of an effect (illness) given the cause. Using a within-subjects design, Experiment 3 revealed systematic individual differences in preference for the two methods. Participants were divided between those who considered intervention more confounded and those who considered observation more confounded. Our experiments point to the subtleties of participants' evaluation of data from studies of human beings.     

The influence of cognitive ability and instructional set on causal conditional inference

We report a large study in which participants are invited to draw inferences from causal conditional sentences with varying degrees of believability. General intelligence was measured, and participants were split into groups of high and low ability. Under strict deductive-reasoning instructions, it was observed that higher ability participants were significantly less influenced by prior belief than were those of lower ability. This effect disappeared, however, when pragmatic reasoning instructions were employed in a separate group. These findings are in accord with dual-process theories of reasoning. We also took detailed measures of beliefs in the conditional sentences used for the reasoning tasks. Statistical modelling showed that it is not belief in the conditional statement per se that is the causal factor, but rather correlates of it. Two different models of belief-based reasoning were found to fit the data according to the kind of instructions and the type of inference under consideration.     

Evidence that a transient but cognitively demanding process underlies forward blocking

Blocking is a learning phenomenon in which prior experience inhibits learning about novel cues. Though the phenomenon itself has been well documented, the details of blocking-related processes still remain contentious. Two experiments investigated whether participants were engaged in demanding cognitive processing during different portions of a standard blocking paradigm. Participants in Experiment 1 engaged in a simple secondary task while completing a standard blocking procedure. Results showed that performance on the secondary task was briefly diminished early in the second phase of the blocking paradigm, when the novel cue is first paired with the pretrained cue. Participants in Experiment 2 performed a difficult cognitive load task during either the early or the late portions of the second phase of blocking. The blocking effect was eliminated when learners were under load early in the second phase, but not when learners were under load late in the second phase. These results suggest that blocking relies on a cognitively demanding process with a distinct time course. Computational simulations illustrate how a model that includes top-down (i.e., cognitively demanding) attentional modulation can reproduce the observed behaviour. This suggests that purely associative processes are not sufficient to explain the observed behaviour. Implications for current accounts of blocking are discussed.     

Subjectivity and unconsciousness

Concepts of the unconscious were crucial to both Jung's and Freud's thinking. Psychoanalytic and analytical psychological views of the unconscious are compared and contrasted, and both are critically reviewed. It is suggested that we need to revise our conceptualization so as to take better account of the role of the analyst's expectations and inferences, and therefore of his or her subjectivity, whenever he or she makes a clinical judgement that unconscious mental processes are in operation. Some technical implications of a revised definition of unconsciousness are considered, especially indications for self-disclosure by an analyst of his or her own experience of events within the treatment.     

Technical intelligence in animals: the kea model

The ability to act on information flexibly is one of the cornerstones of intelligent behavior. As particularly informative example, tool-oriented behavior has been investigated to determine to which extent nonhuman animals understand means-end relations, object affordances, and have specific motor skills. Even planning with foresight, goal-directed problem solving and immediate causal inference have been a focus of research. However, these cognitive abilities may not be restricted to tool-using animals but may be found also in animals that show high levels of curiosity, object exploration and manipulation, and extractive foraging behavior. The kea, a New Zealand parrot, is a particularly good example. We here review findings from laboratory experiments and field observations of keas revealing surprising cognitive capacities in the physical domain. In an experiment with captive keas, the success rate of individuals that were allowed to observe a trained conspecific was significantly higher than that of naive control subjects due to their acquisition of some functional understanding of the task through observation. In a further experiment using the string-pulling task, a well-probed test for means-end comprehension, we found the keas finding an immediate solution that could not be improved upon in nine further trials. We interpreted their performance as insightful in the sense of being sensitive of the relevant functional properties of the task and thereby producing a new adaptive response without trial-and-error learning. Together, these findings contribute to the ongoing debate on the distribution of higher cognitive skills in the animal kingdom by showing high levels of sensorimotor intelligence in animals that do not use tools. In conclusion, we suggest that the 'Technical intelligence hypothesis' (Byrne, Machiavellian intelligence II: extensions and evaluations, pp 289-211, 1997), which has been proposed to explain the origin of the ape/monkey grade-shift in intelligence by a selection pressure upon an increased efficiency in foraging behavior, should be extended, that is, applied to some birds as well.     

On aims and methods in the neuroimaging of derived relations

Ingenious and seemingly powerful technologies have been developed recently that enable the visualization in some detail of events in the brain concomitant upon the ongoing behavioral performance of a human participant. Measurement of such brain events offers at the very least a new set of dependent variables in relation to which the independent variables familiarly manipulated in the operant laboratory may be explored. Two related paradigms in which a start has been made in such research concern the derivation of novel or emergent relations from a baseline set of trained relations, and include the phenomenon of transitive inference (TI), observed in studies of stimulus equivalence (SE) and serial learning (SL) or seriation. This paper reviews some published and forthcoming neuroimaging studies of these and related phenomena, and considers how this line of research both demands and represents a welcome synthesis between types of question and levels of explanation in behavioral science that often have been seen as antithetical.     

Distinguishing Between Causes and Enabling Conditions—Through Mental Models or Linguistic Cues?

The mental model theory of naive causal understanding and reasoning (Goldvarg & Johnson-Laird, 2001, Cognitive Science, 25, 565–610) claims that people distinguish between causes and enabling conditions on the basis of sets of models that represent possible causal situations. In the tasks used to test this hypothesis, however, the proposed set of models was confounded with linguistic cues that frame which event to assume as given (the enabling condition) and which to consider as responsible for the effect under this assumption (the cause). By disentangling these two factors, we were able to show that when identifying causes and enabling conditions in these tasks, people rely strongly on the linguistic cues but not on the proposed set of models and that this set of models does not even reflect people's typical interpretation of the tasks. We propose an alternative explanation that integrates syntactic and causal considerations.     

Where do "constraints" come from? A comparison between inferences in biology and in word learning

In this paper, as a commentary on the papers in this special issue, the nature of constraints is discussed in terms of the comparison between inferences in biology and in word learning. Young children's inferences in biology could be constrained by three sources of information: factual knowledge, expectations based on a theory, and ontological knowledge. For example, young children's inference about the length of noses could be constrained by the facts the children know about the animals, the similarity between the animals and humans, and the ontological distinction between living things and nonliving things. In the same way, young children might figure out word meanings by linguistic and pragmatic knowledge, expectations of word meanings (e.g., the whole-object assumption), and ontological knowledge. Interactions among these sources of knowledge are documented by the papers in this special issue and related studies. It is argued that learning biases such as the whole-object assumption could not be induced only by linguistic and pragmatic cues in a social context, but should be regarded as a product of the interaction between a social context and children's theories.