Anxiety has been linked to altered belief formation and uncertainty estimation, impacting learning. Identifying the neural processes underlying these changes is important for understanding brain pathology. Here, we show that oscillatory activity in the medial prefrontal, anterior cingulate and orbitofrontal cortex (mPFC, ACC, OFC) explains anxiety-related learning alterations. In a magnetoencephalography experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a probabilistic reward-based learning task. HTA undermined learning through an overestimation of volatility, leading to faster belief updating, more stochastic decisions and pronounced lose-shift tendencies. On a neural level, we observed increased gamma activity in the ACC, dmPFC, and OFC during encoding of precision-weighted prediction errors in HTA, accompanied by suppressed ACC alpha/beta activity. Our findings support the association between altered learning and belief updating in anxiety and changes in gamma and alpha/beta activity in the ACC, dmPFC, and OFC.

No abstract

Recent advances in the computational understanding of decision-making processes have led to proposals that anxiety biases how individuals form beliefs and estimate uncertainty. The anxiety and decision-making circuitry broadly overlap in regions such as the medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and orbitofrontal cortex (OFC). Changes in activity across these brain areas could help explain how misestimation of uncertainty and altered belief updating can lead to impaired learning in anxiety. To test this prediction, this study built on recent progress in rhythm-based formulations of Bayesian predictive coding to identify sources of oscillatory modulations across the ACC, mPFC, and OFC that are associated with altered learning in subclinical trait anxiety. In a magnetoencephalography (MEG) experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a volatile probabilistic reward-based learning task. We modelled behaviour using a hierarchical Bayesian learning model. Furthermore, we quantified the parametric effects of trial-wise estimates of unsigned precision-weighted prediction errors (pwPEs) and, separately, precision weights and surprise on source-reconstructed MEG time-frequency responses using convolution modelling. We showed that HTA interferes with overall reward-based learning performance associated with more stochastic decisions and more pronounced lose-shift tendencies. These behavioural effects were explained by an overestimation of volatility and faster belief updating in HTA when compared to LTA. On a neural level, we observed enhanced gamma responses and decreased alpha/beta activity in HTA during the encoding of unsigned pwPEs about about stimulus outcomes relative to LTA. These effects emerged primarily in the ACC and dorsomedial PFC (dmPFC), and they were accompanied by additional ACC alpha/beta modulations representing differential encoding of precision weights in each anxiety group. Our study supports the association between subclinical trait anxiety and faster updating of beliefs in a volatile environment through gamma and alpha/beta activity changes in the ACC and dmPFC.

Recent work suggests that anxiety biases how individuals form beliefs and estimate uncertainty, modulating learning. Yet the precise neural underpinnings of these computational alterations remain undetermined. Here we assess whether oscillatory activity in regions of the overlapping anxiety and decision-making circuitry, such as the medial prefrontal, anterior cingulate and orbitofrontal cortex (mPFC, ACC, OFC), is associated with misestimation of uncertainty and altered belief updating in anxiety. In a magnetoencephalography experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a volatile probabilistic reward-based learning task. A hierarchical Bayesian model revealed that HTA undermines learning through an overestimation of volatility leading to faster belief updating, more stochastic decisions and pronounced lose-shift tendencies. Using convolution modelling for oscillatory responses in the source space, we observed enhanced gamma activity in HTA during the encoding of unsigned precision-weighted prediction errors (pwPE). These effects emerged in the ACC, dorsomedial PFC (dmPFC), and OFC, and they were accompanied by additional suppression of ACC alpha/beta activity with pwPE and precision-weights in HTA. Our study supports the association between altered learning in trait anxiety and faster updating of beliefs through gamma and alpha/beta activity changes across the ACC, dmPFC and OFC.