Experience-driven recalibration of learning from surprising events.

Different environments favor different patterns of adaptive learning. A surprising event that in one context would accelerate belief updating might, in another context, be downweighted as a meaningless outlier. Here, we investigated whether people would spontaneously regulate the influence of surprise on learning in response to event-by-event experiential feedback. Across two experiments, we examined whether participants performing a perceptual judgment task under spatial uncertainty (n = 29, n = 63) adapted their patterns of predictive gaze according to the informativeness or uninformativeness of surprising events in their current environment. Uninstructed predictive eye movements exhibited a form of metalearning in which surprise came to modulate event-by-event learning rates in opposite directions across contexts. Participants later appropriately readjusted their patterns of adaptive learning when the statistics of the environment underwent an unsignaled reversal. Although significant adjustments occurred in both directions, performance was consistently superior in environments in which surprising events reflected meaningful change, potentially reflecting a bias towards interpreting surprise as informative and/or difficulty ignoring salient outliers. Our results provide evidence for spontaneous, context-appropriate recalibration of the role of surprise in adaptive learning.

Eye movements reflect adaptive predictions and predictive precision.

Successful decision-making depends on the ability to form predictions about uncertain future events. Existing evidence suggests predictive representations are not limited to point estimates but also include information about the associated level of predictive uncertainty. Estimates of predictive uncertainty have an important role in governing the rate at which beliefs are updated in response to new observations. It is not yet known, however, whether the same form of uncertainty-modulated learning occurs naturally and spontaneously when there is no task requirement to express predictions explicitly. Here, we used a gaze-based predictive inference paradigm to show that (a) predictive inference manifested in spontaneous gaze dynamics, (b) feedback-driven updating of spontaneous gaze-based predictions reflected adaptation to environmental statistics, and (c) anticipatory gaze variability tracked predictive uncertainty in an event-by-event manner. Our results demonstrate that sophisticated predictive inference can occur spontaneously and that oculomotor behavior can provide a multidimensional readout of internal predictive beliefs. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Variability in the analysis of a single neuroimaging dataset by many teams.

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

FEFsem neuronal response during combined volitional and reflexive pursuit.

Although much is known about volitional and reflexive smooth eye movements individually, much less is known about how they are coordinated. It is hypothesized that separate cortico-ponto-cerebellar loops subserve these different types of smooth eye movements. Specifically, the MT-MST-DLPN pathway is thought to be critical for ocular following eye movements, whereas the FEF-NRTP pathway is understood to be vital for volitional smooth pursuit. However, the role that these loops play in combined volitional and reflexive behavior is unknown. We used a large, textured background moving in conjunction with a small target spot to investigate the eye movements evoked by a combined volitional and reflexive pursuit task. We also assessed the activity of neurons in the smooth eye movement subregion of the frontal eye field (FEFsem). We hypothesized that the pursuit system would show less contribution from the volitional pathway in this task, owing to the increased involvement of the reflexive pathway. In accordance with this hypothesis, a majority of FEFsem neurons (63%) were less active during pursuit maintenance in a combined volitional and reflexive pursuit task than during purely volitional pursuit. Interestingly and surprisingly, the neuronal response to the addition of the large-field motion was highly correlated with the neuronal response to a target blink. This suggests that FEFsem neuronal responses to these different perturbations-whether the addition or subtraction of retinal input-may be related. We conjecture that these findings are due to changing weights of both the volitional and reflexive pathways, as well as retinal and extraretinal signals.

Temporal dynamics of retinal and extraretinal signals in the FEFsem during smooth pursuit eye movements.

Neurons in the smooth eye movement subregion of the frontal eye field (FEFsem) are known to play an important role in voluntary smooth pursuit eye movements. Underlying this function are projections to parietal and prefrontal visual association areas and subcortical structures, all known to play vital but differing roles in the execution of smooth pursuit. Additionally, the FEFsem has been shown to carry a diverse array of signals (e.g., eye velocity, acceleration, gain control). We hypothesized that distinct subpopulations of FEFsem neurons subserve these diverse functions and projections, and that the relative weights of retinal and extraretinal signals could form the basis for categorization of units. To investigate this, we used a step-ramp tracking task with a target blink to determine the relative contributions of retinal and extraretinal signals in individual FEFsem neurons throughout pursuit. We found that the contributions of retinal and extraretinal signals to neuronal activity and behavior change throughout the time course of pursuit. A clustering algorithm revealed three distinct neuronal subpopulations: cluster 1 was defined by a higher sensitivity to eye velocity, acceleration, and retinal image motion; cluster 2 had greater activity during blinks; and cluster 3 had significantly greater eye position sensitivity. We also performed a comparison with a sample of medial superior temporal neurons to assess similarities and differences between the two areas. Our results indicate the utility of simple tests such as the target blink for parsing the complex and multifaceted roles of cortical areas in behavior.NEW & NOTEWORTHY The frontal eye field (FEF) is known to play a critical role in volitional smooth pursuit, carrying a variety of signals that are distributed throughout the brain. This study used a novel application of a target blink task during step ramp tracking to determine, in combination with a clustering algorithm, the relative contributions of retinal and extraretinal signals to FEF activity and the extent to which these contributions could form the basis for a categorization of neurons.

Individual differences in amygdala-medial prefrontal anatomy link negative affect, impaired social functioning, and polygenic depression risk.

Individual differences in affective and social processes may arise from variability in amygdala-medial prefrontal (mPFC) circuitry and related genetic heterogeneity. To explore this possibility in humans, we examined the structural correlates of trait negative affect in a sample of 1050 healthy young adults with no history of psychiatric illness. Analyses revealed that heightened negative affect was associated with increased amygdala volume and reduced thickness in a left mPFC region encompassing the subgenual and rostral anterior cingulate cortex. The most extreme individuals displayed an inverse correlation between amygdala volume and mPFC thickness, suggesting that imbalance between these structures is linked to negative affect in the general population. Subgroups of participants were further evaluated on social (n = 206) and emotional (n = 533) functions. Individuals with decreased mPFC thickness exhibited the poorest social cognition and were least able to correctly identify facial emotion. Given prior links between disrupted amygdala-mPFC circuitry and the presence of major depressive disorder (MDD), we explored whether the individual differences in anatomy observed here in healthy young adults were associated with polygenic risk for MDD (n = 438) using risk scores derived from a large genome-wide association analysis (n = 18,759). Analyses revealed associations between increasing polygenic burden for MDD and reduced cortical thickness in the left mPFC. These collective findings suggest that, within the healthy population, there is significant variability in amygdala-mPFC circuitry that is associated with poor functioning across affective and social domains. Individual differences in this circuitry may arise, in part, from common genetic variability that contributes to risk for MDD.