Visual motion processing recruits regions selective for auditory motion in early deaf individuals.

In early deaf individuals, the auditory deprived temporal brain regions become engaged in visual processing. In our study we tested further the hypothesis that intrinsic functional specialization guides the expression of cross-modal responses in the deprived auditory cortex. We used functional MRI to characterize the brain response to horizontal, radial and stochastic visual motion in early deaf and hearing individuals matched for the use of oral or sign language. Visual motion showed enhanced response in the 'deaf' mid-lateral planum temporale, a region selective to auditory motion as demonstrated by a separate auditory motion localizer in hearing people. Moreover, multivariate pattern analysis revealed that this reorganized temporal region showed enhanced decoding of motion categories in the deaf group, while visual motion-selective region hMT+/V5 showed reduced decoding when compared to hearing people. Dynamic Causal Modelling revealed that the 'deaf' motion-selective temporal region shows a specific increase of its functional interactions with hMT+/V5 and is now part of a large-scale visual motion selective network. In addition, we observed preferential responses to radial, compared to horizontal, visual motion in the 'deaf' right superior temporal cortex region that also show preferential response to approaching/receding sounds in the hearing brain. Overall, our results suggest that the early experience of auditory deprivation interacts with intrinsic constraints and triggers a large-scale reallocation of computational load between auditory and visual brain regions that typically support the multisensory processing of motion information.

Functional selectivity for face processing in the temporal voice area of early deaf individuals.

Brain systems supporting face and voice processing both contribute to the extraction of important information for social interaction (e.g., person identity). How does the brain reorganize when one of these channels is absent? Here, we explore this question by combining behavioral and multimodal neuroimaging measures (magneto-encephalography and functional imaging) in a group of early deaf humans. We show enhanced selective neural response for faces and for individual face coding in a specific region of the auditory cortex that is typically specialized for voice perception in hearing individuals. In this region, selectivity to face signals emerges early in the visual processing hierarchy, shortly after typical face-selective responses in the ventral visual pathway. Functional and effective connectivity analyses suggest reorganization in long-range connections from early visual areas to the face-selective temporal area in individuals with early and profound deafness. Altogether, these observations demonstrate that regions that typically specialize for voice processing in the hearing brain preferentially reorganize for face processing in born-deaf people. Our results support the idea that cross-modal plasticity in the case of early sensory deprivation relates to the original functional specialization of the reorganized brain regions.

Enhancing human-AI collaboration: The case of colonoscopy.

Diagnostic errors impact patient health and healthcare costs. Artificial Intelligence (AI) shows promise in mitigating this burden by supporting Medical Doctors in decision-making. However, the mere display of excellent or even superhuman performance by AI in specific tasks does not guarantee a positive impact on medical practice. Effective AI assistance should target the primary causes of human errors and foster effective collaborative decision-making with human experts who remain the ultimate decision-makers. In this narrative review, we apply these principles to the specific scenario of AI assistance during colonoscopy. By unraveling the neurocognitive foundations of the colonoscopy procedure, we identify multiple bottlenecks in perception, attention, and decision-making that contribute to diagnostic errors, shedding light on potential interventions to mitigate them. Furthermore, we explored how existing AI devices fare in clinical practice and whether they achieved an optimal integration with the human decision-maker. We argue that to foster optimal Human-AI collaboration, future research should expand our knowledge of factors influencing AI's impact, establish evidence-based cognitive models, and develop training programs based on them. These efforts will enhance human-AI collaboration, ultimately improving diagnostic accuracy and patient outcomes. The principles illuminated in this review hold more general value, extending their relevance to a wide array of medical procedures and beyond.

Dynamic modulation of social influence by indirect reciprocity.

Indirect reciprocity is a pervasive social norm that promotes human cooperation. Helping someone establishes a good reputation, increasing the probability of receiving help from others. Here we hypothesize that indirect reciprocity regulates not only cooperative behavior but also the exchange of opinions within a social group. In a novel interactive perceptual task (Experiment 1), we show that participants relied more on the judgments of an alleged human partner when a second alleged peer had been endorsing participants' opinions. By doing so, participants did not take into account the reliability of their partners' judgments and did not maximize behavioral accuracy and monetary reward. This effect declined when participants did not expect future interactions with their partners, suggesting the emergence of downstream mechanisms of reciprocity linked to the management of reputation. Importantly, all these effects disappeared when participants knew that the partners' responses were computer-generated (Experiment 2). Our results suggest that, within a social group, individuals may weight others' opinions through indirect reciprocity, highlighting the emergence of normative distortions in the process of information transmission among humans.

The role of reciprocity in human-robot social influence.

Humans are constantly influenced by others' behavior and opinions. Of importance, social influence among humans is shaped by reciprocity: we follow more the advice of someone who has been taking into consideration our opinions. In the current work, we investigate whether reciprocal social influence can emerge while interacting with a social humanoid robot. In a joint task, a human participant and a humanoid robot made perceptual estimates and then could overtly modify them after observing the partner's judgment. Results show that endowing the robot with the ability to express and modulate its own level of susceptibility to the human's judgments represented a double-edged sword. On the one hand, participants lost confidence in the robot's competence when the robot was following their advice; on the other hand, participants were unwilling to disclose their lack of confidence to the susceptible robot, suggesting the emergence of reciprocal mechanisms of social influence supporting human-robot collaboration.

I'm not a little kid anymore! Reciprocal social influence in child-adult interaction.

Human decisions are often influenced by others' opinions. This process is regulated by social norms: for instance, we tend to reciprocate the consideration received from others, independently of their reliability as information sources. Nonetheless, no study to date has investigated whether and how reciprocity modulates social influence in child-adult interaction. We tested 6-, 8- and 10-year-old children in a novel joint perceptual task. A child and an adult experimenter made perceptual estimates and then took turns in making a final decision, choosing between their own and partner's response. We manipulated the final choices of the adult partner, who in one condition chose often the child's estimates, whereas in another condition tended to confirm her own response. Results reveal that 10-year-old children reciprocated the consideration received from the partner, increasing their level of conformity to the adult's judgements when the partner had shown high consideration towards them. At the same time, 10-year-old children employed more elaborate decision criteria in choosing when trusting the adult partner compared to younger children and did not show egocentric biases in their final decisions. Our results shed light on the development of the cognitive and normative mechanisms modulating reciprocal social influence in child-adult interaction.

Timing of social feedback shapes observational learning in strategic interaction.

Many types of social interaction require the ability to anticipate others' behavior, which is commonly referred to as strategic sophistication. In this context, observational learning can represent a decisive tool for behavioral adaptation. However, little is known on whether and when individuals learn from observation in interactive settings. In the current study, 321 participants played one-shot interactive games and, at a given time along the experiment, they could observe the choices of an overtly efficient player. This social feedback could be provided before or after the participant's choice in each game. Results reveal that players with a sufficient level of strategic skills increased their level of sophistication only when the social feedback was provided after their choices, whereas they relied on blind imitation when they received feedback before their decision. Conversely, less sophisticated players did not increase their level of sophistication, regardless of the type of social feedback. Our findings disclose the interplay between endogenous and exogenous factors modulating observational learning in strategic interaction.

Gaze data reveal individual differences in relational representation processes.

In our everyday life, we often need to anticipate the potential occurrence of events and their consequences. In this context, the way we represent contingencies can determine our ability to adapt to the environment. However, it is not clear how agents encode and organize available knowledge about the future to react to possible states of the world. In the present study, we investigated the process of contingency representation with three eye-tracking experiments. In Experiment 1, we introduced a novel relational-inference task in which participants had to learn and represent conditional rules regulating the occurrence of interdependent future events. A cluster analysis on early gaze data revealed the existence of 2 distinct types of encoders. A group of (sophisticated) participants built exhaustive contingency models that explicitly linked states with each of their potential consequences. Another group of (unsophisticated) participants simply learned binary conditional rules without exploring the underlying relational complexity. Analyses of individual cognitive measures revealed that cognitive reflection is associated with the emergence of either sophisticated or unsophisticated representation behavior. In Experiment 2, we observed that unsophisticated participants switched toward the sophisticated strategy after having received information about its existence, suggesting that representation behavior was modulated by strategy generation mechanisms. In Experiment 3, we showed that the heterogeneity in representation strategy emerges also in conditional reasoning with verbal sequences, indicating the existence of a general disposition in building either sophisticated or unsophisticated models of contingencies. (PsycINFO Database Record (c) 2020 APA, all rights reserved).