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Socially anxious individuals often engage in subtle avoidance behaviors (SABs) to mitigate their distress during feared social situations, such as avoiding eye-contact during a public speech. However, by preventing direct confrontation with their fears, SABs greatly hinder the efficacy of exposure therapy, the first-line treatment for social anxiety. Here, we test whether neural stimulation of the brain circuits controlling avoidance behavior can augment the efficacy of exposure therapy. This intervention relies on evidence that dual-site transcranial alternating-current simulation (tACS) of theta-gamma phase-amplitude couplings between frontal regions can improve control over social avoidance tendencies. Here, we use the same tACS protocol (active, or sham) on socially anxious individuals undergoing a standardized exposure to public speaking. Additionally, we implement quantitative, multimodal estimates of SABs using motion-tracking, eye-tracking, and prosodic analyses of participants' public speeches. We expect quantifiable reductions in multimodal measures of SABs during active-vs-sham tACS, ultimately enhancing exposure therapy's efficacy.

The ability to flexibly interpret signals in context is at the core of human communication, as even the most conventionalized linguistic signals are necessarily ambiguous and subject to inter-individual variability. We introduce a novel communication game (the Pizzini game) requiring pairs of participants to exchange linguistic signals that are successfully interpreted by using contextual information freshly generated by each pair. By allowing this common ground between once-strangers to be developed interactively in the lab, we are able to characterize the pair-specific contextual information available to participants when inferring intended meanings. We present preliminary data testing the predictions that (1) interactants align on an abstracted conceptual representation of a set of stimuli during the context-building portion of the task and (2) that the characteristics of this pair-specific conceptual representation predict the dynamics of how participants later resolve context-specific references to the same stimuli.

When people are unsure of the intended meaning of a word, they often ask for clarification. One way of doing so-often assumed in models of communication-is to point at a potential target: "Do you mean [points at the rabbit]?'' However, what if the target is unavailable? Then the only recourse is language itself, which seems equivalent to pulling oneself up from a swamp by one's hair. We created two computational models of communication, one able to point and one not. The latter incorporates inference to resolve the meaning of non-pointing signals. Simulations show agents in both models reach perceived understanding equally quickly. While this means agents think they are successfully communicating, non-pointing agents understand each other only at chance level.This shows that state-of-the-art computational explanations have difficulty explaining how people solve the puzzle of underdetermination, and that doing so will require a fundamental leap forward.

Imagine discussing yesterdays dinner with a friend: It wasn’t particularly tasty. Your friend concurs, it was very salty!Thinking you were talking about the appetizer (which wasnt salty at all), youre forced to reconsider which course yourfriend was talking about. Was the appetizer salty to her? Was she talking about the main course? People encounter mis-understandings in everyday conversation, yet quickly and seamlessly resolve them. How people do this is an explanatorychallenge: the thing being talked about (i.e., the referent) is often not physically present during the conversation. Hence,theres no easy way for interlocutors to establish common ground via ostensive signaling (e.g., by pointing at the dish). Wedevelop a model of speakers that use pragmatic reasoning to infer the referent inferred by listeners. We explore the perfor-mance of this model using agent-based simulated conversations. The results imply necessary and sufficient conditions forsuccessful updating.

Background: Fatigue is a central feature of myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS), but many ME/CFS patients also report comorbid pain symptoms. It remains unclear whether these symptoms are related to similar or dissociable brain networks. This study used resting-state fMRI to disentangle networks associated with fatigue and pain symptoms in ME/CFS patients, and to link changes in those networks to clinical improvements following cognitive behavioral therapy (CBT). Methods: Relationships between pain and fatigue symptoms and cortico-cortical connectivity were assessed within ME/CFS patients at baseline (N = 72) and after CBT (N = 33) and waiting list (WL, N = 18) and compared to healthy controls (HC, N = 29). The analyses focused on four networks previously associated with pain and/or fatigue, i.e. the fronto-parietal network (FPN), premotor network (PMN), somatomotor network (SMN), and default mode network (DMN). Results: At baseline, variation in pain and fatigue symptoms related to partially dissociable brain networks. Fatigue was associated with higher SMN-PMN connectivity and lower SMN-DMN connectivity. Pain was associated with lower PMN-DMN connectivity. CBT improved SMN-DMN connectivity, compared to WL. Larger clinical improvements were associated with larger increases in frontal SMN-DMN connectivity. No CBT effects were observed for PMN-DMN or SMN-PMN connectivity. Conclusions: These results provide insight into the dissociable neural mechanisms underlying fatigue and pain symptoms in ME/CFS and how they are affected by CBT in successfully treated patients. Further investigation of how and in whom behavioral and biomedical treatments affect these networks is warranted to improve and individualize existing or new treatments for ME/CFS. [ABSTRACT FROM AUTHOR]

Dopaminergic dysfunction in the basal ganglia, particularly in the posterior putamen, is often viewed as the primary pathological mechanism behind motor slowing (i.e. bradykinesia) in Parkinson's disease. However, striatal dopamine loss fails to account for interindividual differences in motor phenotype and rate of decline, implying that the expression of motor symptoms depends on additional mechanisms, some of which may be compensatory in nature. Building on observations of increased motor-related activity in the parieto-premotor cortex of Parkinson patients, we tested the hypothesis that interindividual differences in clinical severity are determined by compensatory cortical mechanisms and not just by basal ganglia dysfunction. Using functional MRI, we measured variability in motor- and selection-related brain activity during a visuomotor task in 353 patients with Parkinson's disease (≤5 years disease duration) and 60 healthy controls. In this task, we manipulated action selection demand by varying the number of possible actions that individuals could choose from. Clinical variability was characterized in two ways. First, patients were categorized into three previously validated, discrete clinical subtypes that are hypothesized to reflect distinct routes of α-synuclein propagation: diffuse-malignant (n = 42), intermediate (n = 128) or mild motor-predominant (n = 150). Second, we used the scores of bradykinesia severity and cognitive performance across the entire sample as continuous measures. Patients showed motor slowing (longer response times) and reduced motor-related activity in the basal ganglia compared with controls. However, basal ganglia activity did not differ between clinical subtypes and was not associated with clinical scores. This indicates a limited role for striatal dysfunction in shaping interindividual differences in clinical severity. Consistent with our hypothesis, we observed enhanced action selection-related activity in the parieto-premotor cortex of patients with a mild-motor predominant subtype, both compared to patients with a diffuse-malignant subtype and controls. Furthermore, increased parieto-premotor activity was related to lower bradykinesia severity and better cognitive performance, which points to a compensatory role. We conclude that parieto-premotor compensation, rather than basal ganglia dysfunction, shapes interindividual variability in symptom severity in Parkinson's disease. Future interventions may focus on maintaining and enhancing compensatory cortical mechanisms, rather than only attempting to normalize basal ganglia dysfunction. [ABSTRACT FROM AUTHOR]

The ability to create and understand novel communicative signals is exemplary of people’s creative and inferentialabilities. For example, when traveling and unable to speak the local language, we can make ourselves understood by creatingnovel gestures. This ability is a form of abductive inference, and requires people to generate novel hypotheses about possiblemeanings of signals (abduction proper). We propose that novel hypotheses may be generated from scratch by re-conceptualizingperceptual and conceptual representations through analogical augmentation.We plan to use robotics methodology to assess the plausibility of this model. By enhancing a robot with analogical augmentationwe aim to enable it to generate novel gestures based on analogies. This lays the groundwork for more natural human-robotinteraction. Furthermore, by studying the robot’s gestures and to what extent people can understand them, we gain betterunderstanding of the abduction-based computational processes underlying communication.

Pointing movements can serve instrumental goals (‘pointing to press a button’) or communicative goals (‘pointingto indicate to someone which button to press’). Previous work has shown that communicative pointing follows different trajectories,and has different end points than instrumental pointing movements, depending on the addressee’s spatial location. Thissuggests that motor control processes are affected by communicative intentions, but the nature of this interface remains unknown.Using optimal feedback control theory, we construct a model of instrumental pointing, and explore how this model canbe adjusted to reproduce the dependency between communicative trajectories and addressees’ locations. Our results show thatthe variations in end points cannot account for those trajectories. Instead, the kinematic data are best explained by ‘perspectivetaking’ on the part of the communicator, i.e., communicative pointing movements seem to be planned in a frame of referencethat is adjusted to the addressee’s point of view.

The ability to generate novel hypotheses is an important problem-solving capacity of humans. This ability is vital for making sense of the complex and unfamiliar world we live in. Often, this capacity is characterized as an inference to the best explanation--selecting the "best" explanation from a given set of candidate hypotheses. However, it remains unclear where these candidate hypotheses originate from. In this paper we contribute to computationally explaining these origins by providing the contours of the computational problem solved when humans generate hypotheses. The origin of hypotheses, otherwise known as abduction proper, is hallmarked by seven properties: (1) isotropy, (2) open-endedness, (3) novelty, (4) groundedness, (5) sensibility, (6) psychological realism, and (7) computational tractability. In this paper we provide a computational-level theory of abduction proper that unifies the first six of these properties and lays the groundwork for the seventh property of computational tractability. We conjecture that abduction proper is best seen as a process of deep analogical inference.

A paradox of testosterone effects is seen in adolescents versus adults in social emotional approach‐avoidance behavior. During adolescence, high testosterone levels are associated with increased anterior prefrontal (aPFC) involvement in emotion control, whereas during adulthood this neuro‐endocrine relation is reversed. Rodent work shows that, during puberty, testosterone transitions from a neuro‐developmental to a social‐sexual activating hormone. In this study, we explored whether this functional transition is also present in human adolescents and young adults. Using a prospective longitudinal design, we investigated the role of testosterone on neural control of social emotional behavior during the transitions from middle to late adolescence and into young adulthood. Seventy‐one individuals (tested at ages 14, 17, and 20 years) performed an fMRI‐adapted approach‐avoidance (AA) task involving automatic and controlled actions in response to social emotional stimuli. In line with predictions from animal models, the effect of testosterone on aPFC engagement decreased between middle and late adolescence, and shifted into an activational role by young adulthood—impeding neural control of emotions. This change in testosterone function was accompanied by increased testosterone‐modulated amygdala reactivity. These findings qualify the testosterone‐dependent maturation of the prefrontal‐amygdala circuit supporting emotion control during the transition from middle adolescence into young adulthood. [ABSTRACT FROM AUTHOR]