Selective manipulation of target identification demands in visual search: the role of stimulus contrast in CDA activations.

In classic visual pop-out search, response times are slowed remarkably when participants are required to precisely identify (e.g., vertical vs. horizontal orientation) as compared to simply localize (e.g., left vs. right position) a feature singleton target. This cost associated with stimulus identification has been recently proposed (Töllner, Rangelov, & Müller, 2012) to derive from the engagement of postselective recurrent processes that via feedback connections extract the information required for motor-response selection. Here, we examined whether the contralateral delay activity (CDA), an asymmetric neural marker generally assumed to reflect active maintenance of stimulus information in visual short-term memory (vSTM), may further index the degree of postselective processing requirements in visual search. Employing a compound-search task, we selectively manipulated the ease/difficulty of identifying the response-critical target orientation attribute (horizontal vs. vertical)--irrespective of the target-defining color feature (red vs. green)--by introducing different levels of stimulus-background contrast. As expected, we found a monotonic reaction time increase to be associated with gradually increasing CDA magnitudes as the stimulus contrast decreased. Thus, our findings provide direct evidence that CDA activations provide a useful tool to estimate the amount of postselective recurrent processing recruited to extract detailed object information from vSTM.

COVID-Dynamic: A large-scale longitudinal study of socioemotional and behavioral change across the pandemic.

The COVID-19 pandemic has caused enormous societal upheaval globally. In the US, beyond the devastating toll on life and health, it triggered an economic shock unseen since the great depression and laid bare preexisting societal inequities. The full impacts of these personal, social, economic, and public-health challenges will not be known for years. To minimize societal costs and ensure future preparedness, it is critical to record the psychological and social experiences of individuals during such periods of high societal volatility. Here, we introduce, describe, and assess the COVID-Dynamic dataset, a within-participant longitudinal study conducted from April 2020 through January 2021, that captures the COVID-19 pandemic experiences of >1000 US residents. Each of 16 timepoints combines standard psychological assessments with novel surveys of emotion, social/political/moral attitudes, COVID-19-related behaviors, tasks assessing implicit attitudes and social decision-making, and external data to contextualize participants' responses. This dataset is a resource for researchers interested in COVID-19-specific questions and basic psychological phenomena, as well as clinicians and policy-makers looking to mitigate the effects of future calamities.

Humans depart from optimal computational models of interactive decision-making during competition under partial information.

Decision making under uncertainty in multiagent settings is of increasing interest in decision science. The degree to which human agents depart from computationally optimal solutions in socially interactive settings is generally unknown. Such understanding provides insight into how social contexts affect human interaction and the underlying contributions of Theory of Mind. In this paper, we adapt the well-known 'Tiger Problem' from artificial-agent research to human participants in solo and interactive settings. Compared to computationally optimal solutions, participants gathered less information before outcome-related decisions when competing than cooperating with others. These departures from optimality were not haphazard but showed evidence of improved performance through learning. Costly errors emerged under conditions of competition, yielding both lower rates of rewarding actions and accuracy in predicting others. Taken together, this work provides a novel approach and insights into studying human social interaction when shared information is partial.

Caltech Conte Center, a multimodal data resource for exploring social cognition and decision-making.

This data release of 117 healthy community-dwelling adults provides multimodal high-quality neuroimaging and behavioral data for the investigation of brain-behavior relationships. We provide structural MRI, resting-state functional MRI, movie functional MRI, together with questionnaire-based and task-based psychological variables; many of the participants have multiple datasets from retesting over the course of several years. Our dataset is distinguished by utilizing open-source data formats and processing tools (BIDS, FreeSurfer, fMRIPrep, MRIQC), providing data that is thoroughly quality checked, preprocessed to various extents and available in multiple anatomical spaces. A customizable denoising pipeline is provided as open-source code that includes tools for the generation of functional connectivity matrices and initialization of individual difference analyses. Behavioral data include a comprehensive set of psychological assessments on gold-standard instruments encompassing cognitive function, mood and personality, together with exploratory factor analyses. The dataset provides an in-depth, multimodal resource for investigating associations between individual differences, brain structure and function, with a focus on the domains of social cognition and decision-making.

Domain specificity versus process specificity: The "social brain" during strategic interaction.

Are social brain responses domain specific, or do domain-general but socially prevalent cognitive processes drive activity in this network? In this issue of Neuron, Konovalov et al. (2021) address this by dissociating general sociality from reactivity, one defining feature of social interactions.

Dose-dependent effects of estrogen on prediction error related neural activity in the nucleus accumbens of healthy young women.

RATIONALE: Whereas the effect of the sex steroid 17-beta-estradiol (E2) on dopaminergic (DA) transmission in the nucleus accumbens (NAc) is well evidenced in female rats, studies in humans are inconsistent. Moreover, linear and inverted u-shaped dose response curves have been observed for E2's effects on hippocampal plasticity, but the shape of dose response curves for E2's effects on the NAc is much less characterized. OBJECTIVES: Investigation of dose response curves for E2's effects on DA-related neural activity in the human NAc. METHODS: Placebo or E2 valerate in doses of 2, 4, 6 or 12 mg was orally administered to 125 naturally cycling young women during the low-hormone menstruation phase on two consecutive days using a randomized, double-blinded design. The E2 treatment regimen induced a wide range of E2 levels, from physiological (2- and 4-mg groups; equivalent to cycle peak) to supraphysiological levels (6- and 12-mg groups; equivalent to early pregnancy). This made it possible to study different dose response functions for E2's effects on NAc activity. During E2 peak, participants performed a well-established reversal learning paradigm. We used trial-wise prediction errors (PE) estimated via a computational reinforcement learning model as a proxy for dopaminergic activity. Linear and quadratic regression analyses predicting PE-related NAc activity from salivary E2 levels were calculated. RESULTS: There was a positive linear relationship between PE-associated NAc activity and salivary E2 increases. CONCLUSIONS: The randomized, placebo-controlled elevation of E2 levels stimulates NAc activity in the human brain, likely mediated by dopaminergic processes.

Theory of mind and decision science: Towards a typology of tasks and computational models.

The ability to form a Theory of Mind (ToM), i.e., to theorize about others' mental states to explain and predict behavior in relation to attributed intentional states, constitutes a hallmark of human cognition. These abilities are multi-faceted and include a variety of different cognitive sub-functions. Here, we focus on decision processes in social contexts and review a number of experimental and computational modeling approaches in this field. We provide an overview of experimental accounts and formal computational models with respect to two dimensions: interactivity and uncertainty. Thereby, we aim at capturing the nuances of ToM functions in the context of social decision processes. We suggest there to be an increase in ToM engagement and multiplexing as social cognitive decision-making tasks become more interactive and uncertain. We propose that representing others as intentional and goal directed agents who perform consequential actions is elicited only at the edges of these two dimensions. Further, we argue that computational models of valuation and beliefs follow these dimensions to best allow researchers to effectively model sophisticated ToM-processes. Finally, we relate this typology to neuroimaging findings in neurotypical (NT) humans, studies of persons with autism spectrum (AS), and studies of nonhuman primates.

No evidence for abnormal priors in early vision in schizophrenia.

The predictive coding account of psychosis postulates the abnormal formation of prior beliefs in schizophrenia, resulting in psychotic symptoms. One domain in which priors play a crucial role is visual perception. For instance, our perception of brightness, line length, and motion direction are not merely based on a veridical extraction of sensory input but are also determined by expectation (or prior) of the stimulus. Formation of such priors is thought to be governed by the statistical regularities within natural scenes. Recently, the use of such priors has been attributed to a specific set of well-documented visual illusions, supporting the idea that perception is biased toward what is statistically more probable within the environment. The Predictive Coding account of psychosis proposes that patients form abnormal representations of statistical regularities in natural scenes, leading to altered perceptual experiences. Here we use classical vision experiments involving a specific set of visual illusions to directly test this hypothesis. We find that perceptual judgments for both patients and control participants are biased in accordance with reported probability distributions of natural scenes. Thus, despite there being a suggested link between visual abnormalities and psychotic symptoms in schizophrenia, our results provide no support for the notion that altered formation of priors is a general feature of the disorder. These data call for a refinement in the predictions of quantitative models of psychosis.

A Two-Way Street between Attention and Learning.

In an elegant model-based fMRI study, Leong et al. (2017) demonstrate how attention and learning interact to facilitate value-based decision-making. They combine computational modeling with empirical measures of attentional selection derived from eye-tracking data and multivariate pattern analyses.

Contralateral delay activity reveals dimension-based attentional orienting to locations in visual working memory.

In research on visual working memory (WM), a contentiously debated issue concerns whether or not items are stored independently of one another in WM. Here we addressed this issue by exploring the role of the physical context that surrounds a given item in the memory display in the formation of WM representations. In particular, we employed bilateral memory displays that contained two or three lateralized singleton items (together with six or five distractor items), defined either within the same or in different visual feature dimensions. After a variable interval, a retro-cue was presented centrally, requiring participants to discern the presence (vs. the absence) of this item in the previously shown memory array. Our results show that search for targets in visual WM is determined interactively by dimensional context and set size: For larger, but not smaller, set sizes, memory search slowed down when targets were defined across rather than within dimensions. This dimension-specific cost manifested in a stronger contralateral delay activity component, an established neural marker of the access to WM representations. Overall, our findings provide electrophysiological evidence for the hierarchically structured nature of WM representations, and they appear inconsistent with the view that WM items are encoded in isolation.

Alpha-band rhythms in visual task performance: phase-locking by rhythmic sensory stimulation.

Oscillations are an important aspect of neuronal activity. Interestingly, oscillatory patterns are also observed in behaviour, such as in visual performance measures after the presentation of a brief sensory event in the visual or another modality. These oscillations in visual performance cycle at the typical frequencies of brain rhythms, suggesting that perception may be closely linked to brain oscillations. We here investigated this link for a prominent rhythm of the visual system (the alpha-rhythm, 8-12 Hz) by applying rhythmic visual stimulation at alpha-frequency (10.6 Hz), known to lead to a resonance response in visual areas, and testing its effects on subsequent visual target discrimination. Our data show that rhythmic visual stimulation at 10.6 Hz: 1) has specific behavioral consequences, relative to stimulation at control frequencies (3.9 Hz, 7.1 Hz, 14.2 Hz), and 2) leads to alpha-band oscillations in visual performance measures, that 3) correlate in precise frequency across individuals with resting alpha-rhythms recorded over parieto-occipital areas. The most parsimonious explanation for these three findings is entrainment (phase-locking) of ongoing perceptually relevant alpha-band brain oscillations by rhythmic sensory events. These findings are in line with occipital alpha-oscillations underlying periodicity in visual performance, and suggest that rhythmic stimulation at frequencies of intrinsic brain-rhythms can be used to reveal influences of these rhythms on task performance to study their functional roles.