What do we know about what we cannot remember? Accessing the semantic attributes of words that cannot be recalled

Two experiments examined access to the semantic attributes of words that participants failed to retrieve. The results indicated access to all 3 dimensions of the semantic differential--evaluation, potency, and activity, as revealed by attribute judgments and by the nature of the commission errors made. There was no evidence for superior access to the emotional-evaluative dimension, inconsistent with what may be expected from the claimed primacy of emotion. In comparison with complete recall, partial recall exhibited a slower rate of forgetting and a stronger tendency to elicit know rather than remember responses. The results were discussed in terms of the processes that lead to partial recall and in terms of the possibility that the affective primacy hypothesis does not apply to memory retrieval.     

Face Recognition Depends on Specialized Mechanisms Tuned to View-Invariant Facial Features: Insights from Deep Neural Networks Optimized for Face or Object Recognition

Face recognition is a computationally challenging classification task. Deep convolutional neural networks (DCNNs) are brain-inspired algorithms that have recently reached human-level performance in face and object recognition. However, it is not clear to what extent DCNNs generate a human-like representation of face identity. We have recently revealed a subset of facial features that are used by humans for face recognition. This enables us now to ask whether DCNNs rely on the same facial information and whether this human-like representation depends on a system that is optimized for face identification. In the current study, we examined the representation of DCNNs of faces that differ in features that are critical or non-critical for human face recognition. Our findings show that DCNNs optimized for face identification are tuned to the same facial features used by humans for face recognition. Sensitivity to these features was highly correlated with performance of the DCNN on a benchmark face recognition task. Moreover, sensitivity to these features and a view-invariant face representation emerged at higher layers of a DCNN optimized for face recognition but not for object recognition. This finding parallels the division to a face and an object system in high-level visual cortex. Taken together, these findings validate human perceptual models of face recognition, enable us to use DCNNs to test predictions about human face and object recognition as well as contribute to the interpretability of DCNNs.     

Choice latency as a cue for children’s subjective confidence in the correctness of their answers

Research with adults indicates that confidence in the correctness of an answer decreases as a function of the amount of time it takes to reach that answer, suggesting that people use response latency as a mnemonic cue for subjective confidence. Experiment 1 extended investigation to 2nd, 3rd and 5th graders. When children chose the answer to general knowledge questions, their confidence in the answer was inversely related to choice latency. However, the strength of the relationship increased with grade, suggesting increased reliance with age on the feedback from task performance. The validity of latency as a cue for the accuracy of the answer also increased with age, possibly contributing to the observed age increase in the extent to which confidence judgment discriminated between correct and wrong answers. Whereas these results illustrate the dependence of metacognitive monitoring on the feedback from control operations, Experiments 2 and 3 examined the idea that control‐based monitoring affects subsequent control operations. When children were free to choose which answers to volunteer under a payoff schedule that emphasized accuracy, they tended to volunteer high‐confidence answers more than low‐confidence answers (Experiment 2) and more short‐latency answers than long‐latency answers (Experiment 3). The latter tendency was again stronger for older than for younger children. The results are discussed in terms of the intricate relationships between monitoring and control processes.     

Stereotyping starlings are more ‘pessimistic’

Negative affect in humans and animals is known to cause individuals to interpret ambiguous stimuli pessimistically, a phenomenon termed ‘cognitive bias’. Here, we used captive European starlings (Sturnus vulgaris) to test the hypothesis that a reduction in environmental conditions, from enriched to non-enriched cages, would engender negative affect, and hence ‘pessimistic’ biases. We also explored whether individual differences in stereotypic behaviour (repetitive somersaulting) predicted ‘pessimism’. Eight birds were trained on a novel conditional discrimination task with differential rewards, in which background shade (light or dark) determined which of two covered dishes contained a food reward. The reward was small when the background was light, but large when the background was dark. We then presented background shades intermediate between those trained to assess the birds’ bias to choose the dish associated with the smaller food reward (a ‘pessimistic’ judgement) when the discriminative stimulus was ambiguous. Contrary to predictions, changes in the level of cage enrichment had no effect on ‘pessimism’. However, changes in the latency to choose and probability of expressing a choice suggested that birds learnt rapidly that trials with ambiguous stimuli were unreinforced. Individual differences in performance of stereotypies did predict ‘pessimism’. Specifically, birds that somersaulted were more likely to choose the dish associated with the smaller food reward in the presence of the most ambiguous discriminative stimulus. We propose that somersaulting is part of a wider suite of behavioural traits indicative of a stress response to captive conditions that is symptomatic of a negative affective state.     

A Cognitive Model of Dynamic Cooperation With Varied Interdependency Information

We analyze the dynamics of repeated interaction of two players in the Prisoner's Dilemma (PD) under various levels of interdependency information and propose an instance‐based learning cognitive model (IBL‐PD) to explain how cooperation emerges over time. Six hypotheses are tested regarding how a player accounts for an opponent's outcomes: the selfish hypothesis suggests ignoring information about the opponent and utilizing only the player's own outcomes; the extreme fairness hypothesis weighs the player's own and the opponent's outcomes equally; the moderate fairness hypothesis weighs the opponent's outcomes less than the player's own outcomes to various extents; the linear increasing hypothesis increasingly weighs the opponent's outcomes at a constant rate with repeated interactions; the hyperbolic discounting hypothesis increasingly and nonlinearly weighs the opponent's outcomes over time; and the dynamic expectations hypothesis dynamically adjusts the weight a player gives to the opponent's outcomes, according to the gap between the expected and the actual outcomes in each interaction. When players lack explicit feedback about their opponent's choices and outcomes, results are consistent with the selfish hypothesis; however, when this information is made explicit, the best predictions result from the dynamic expectations hypothesis.     

Agency attributions of mental effort during self-regulated learning

Previous results suggest that the monitoring of one’s own performance during self-regulated learning is mediated by self-agency attributions and that these attributions can be influenced by poststudy effort-framing instructions. These results pose a challenge to the study of issues of self-agency in metacognition when the objects of self-regulation are mental operations rather than motor actions that have observable outcomes. When participants studied items in Experiment 1 under time pressure, they invested greater study effort in the easier items in the list. However, the effects of effort framing were the same as when learners typically invest more study effort in the more difficult items: Judgments of learning (JOLs) decreased with effort when instructions biased the attribution of effort to nonagentic sources but increased when they biased attribution to agentic sources. However, the effects of effort framing were constrained by parameters of the study task: Interitem differences in difficulty constrained the attribution of effort to agentic regulation (Experiment 2) whereas interitem differences in the incentive for recall constrained the attribution of effort to nonagentic sources (Experiment 3). The results suggest that the regulation and attribution of effort during self-regulated learning occur within a module that is dissociated from the learner’s superordinate agenda but is sensitive to parameters of the task. A model specifies the stage at which effort framing affects the effort–JOL relationship by biasing the attribution of effort to agentic or nonagentic sources. The potentialities that exist in metacognition for the investigation of issues of self-agency are discussed.