Fig 1.
Safety Estimation Task and Safety Value Updating Task schematics, including safety probabilities, a conceptual model of safety estimation and integration, and MRI session procedure details.
(A) Safety Estimation Task. An example trial is presented. Subjects were told to imagine they were battling dangerous animals with powerful weapons. On each trial, subjects saw stimuli pairs comprised of a threat (animal) and protection (weapon) with presentation of threat/protection counterbalanced. First a weapon or animal was presented (Safety Prediction) and subjects made an initial estimation of whether they would win or lose the battle, responding with a button press. Then, the paired stimulus was presented (Safety Meta-representation) and subjects made an updated judgment as to whether they would win or lose, responding with a button press. After both stimuli were presented, subjects saw the outcome of the battle depicted as either a shock (loss) or no shock (win) (Safety Recognition). If subjects lost and received the shock image, they had a 20% chance of receiving an electric shock to the wrist. (B) Safety probabilities. Threat and protection stimuli were each set on a four-point continuum with equivalent experimentally established safety probabilities. Italics depict the average shock value for each stimulus across all pairings. Paired probabilities are depicted in the heatmap. Probabilities were experimentally established prior to testing and were not made known to participants although the continua were easily identified based on prior knowledge and outcomes during the task. (C) MRI session procedure. On the first day, subjects completed the naive version of the Safety Value Updating Task. At this point, subjects had not completed instructions for the Safety Estimation Task and thus had no knowledge of the task or stimuli relevance. Subjects then completed a structural scan, during which they learned about the Safety Estimation Task. After completing 5 practice trials, subjects completed Run 1 and Run 2 of the Safety Estimation Task. An average of 26 min elapsed from the start of Run 1 to the start of Run 2. On the second day, subjects completed Run 3 and Run 4 of the Safety Estimation Task, with an average of 25 min from the start of Run 3 to the start of Run 4. After Run 4 ended, subjects completed the knowledgeable version of the Safety Value Updating Task. Day 2 of testing took place on average 1 day and 7 h after day 1. Task images are approximate reproductions. Source data can be found at https://osf.io/8qg7y/ under “Behavioral data”.
Fig 2.
Behavioral results showing safety estimation and biased predictions based on stimulus type.
(A) Mixed effects logistic regression depicting the association between experimentally established safety (x-axis) and subjective safety estimate derived from subject ratings for win/lose during battles (y-axis; 0 = lose, 1 = win). Threat and protection safety continuums are equivalent (x-axis). Results indicated subjects differentiated safety in accordance with the experimentally established safety continuum and tracked safety probabilities across the safety continuum for both stimulus types. See Table A in S1 Text. (B) Psychometric curves were fit for Safety Prediction in both samples. Subjects reached the safety detection threshold (α) faster when protection was presented as the first stimulus in the battle pair. Behavioral N = 100 (left), MRI N = 30 (right). (C) Subjects were more likely to modify their safety estimations during Safety Meta-representation when threat stimuli were presented first followed by protective stimuli, especially when the safety value of the second stimulus changed to increase safety probability. Source data can be found at https://osf.io/8qg7y/ under “Behavioral data”.
Fig 3.
Behavioral results showing safety estimation updating as a function of stimulus presentation order.
(A) When threat was presented first and protection second, subjects were overconfident about their safety estimates when armed with a high-value weapon. (B) When protection was presented first and threat second, subjects were more likely to differentiate according to the threat pairing in line with experimental probabilities. Heatmap scales for subjective safety ratings are normalized for responses in each of the Behavioral and MRI samples. Source data can be found at https://osf.io/8qg7y/ under “Behavioral data”.
Fig 4.
Neural response to safety increases during each task phase, highlighting the role of the vmPFC in responding to safety increases and protection stimuli.
Analyses in were conducted using FSL Randomise, TFCE, FWE-corrected p < 0.05. Color bar indicates t-intensity values. (A–C) Parametric increases in whole-brain neural activity that track increases in experimentally established safety value of stimuli during Safety Prediction. The first stimulus presented represented a bias to partial information, which measures a differentiation in neural activity as a function of stimulus type (threat versus protection). Significant clusters indicate activation increased in those regions as safety probability increased. Safety increase was based on the average experimentally established safety probability of each stimulus (protection continuum order: fist, stick, gun grenade; threat continuum order: cat, goose, lion, grizzly). (A) Threat and Protection collapsed, (B) Threat only, (C) Protection only. (D–F) Parametric increases in whole-brain neural activity that track increases in experimentally established safety value of stimuli during Safety Meta-representation. The second stimulus safety value was based on the combined safety probability of the first and second stimuli. For analyses, safety was based on comparison with the average safety value of the stimulus. For example, if a stick was shown as the second stimulus and was paired with a cat, the probability of safety would increase from 35.72% (safety average for all stick trials) to 57.14% (safety when stick is paired with cat) (see Fig 1B). (D) Threat and Protection collapsed, (E) Threat only, (F) Protection only. (G) Conjunction of Shared Activation between Safety Prediction and Safety Meta-representation. Conjunction analyses for the safety prediction phase of increasing safety versus increasing danger and shared activation with the safety meta-representation phase of increasing safety versus increasing danger. All stimuli represented. Results indicate overlapping activation in the vmPFC; Z = 2.3, p < 0.05. (H) Neural activation in response to Safety Recognition. Analyses focused on the outcome screen after subjects learned they had been successful during the battle and had achieved 100% certainty of safety compared with unsuccessful battles when the outcome screen indicated potential for electric shock. (I) Safety Value Updating. Multivariate searchlight revealed neural activation change in the vmPFC when subjects engaged in Safety Value Updating for the high safety block (see Fig 1D). Analyses examined the contrast of the Knowledgeable version (post-task viewing) versus the Naive version (pre-task viewing) (E). Searchlight was a priori restricted to the vmPFC using an ROI defined via Neurovault. Source data can be found at https://osf.io/8qg7y/ under “MRI data.” ROI, region of interest; vmPFC, ventromedial prefrontal cortex.
Fig 5.
vmPFC overlap for all stages of Safety Estimation.
Results indicate a posterior to anterior shift as safety becomes more certain. Source data can be found at https://osf.io/8qg7y/ under “MRI data.” vmPFC, ventromedial prefrontal cortex.
Fig 6.
Multivariate functional network connectivity for trials of increased safety value versus those with increased danger value among a network of 10 a priori selected ROIs identified as relevant for threat/safety identification in the existing literature.
(A) ROIs used in analyses. Multivariate functional connectivity (Informational Connectivity) was computed by using covariation trial-by-trial decoding accuracy between each pair of regions. (B) Informational Connectivity analyses resulted in a connectivity matrix between ROIs for the first stimulus presentation indicating regions that communicated while decoding states of safety for all stimuli collapsed, threat stimuli, and protection stimuli (left to right), all connections p < 0.05 corrected. We computed betweenness centrality within this network to find hubs connecting regions during decoding. (C) For second stimulus presentation, regions of connectivity were decoded based on whether stimuli increased in safety or increased in danger as a function of the stimulus pairing, all connections p < 0.05 corrected. For example, a lion paired with a fist would increase in danger, whereas a lion paired with a grenade would decrease in danger. Source data can be found at https://osf.io/8qg7y/ under “MRI data.” ACC, anterior cingulate cortex; ROI, region of interest; vmPFC, ventromedial prefrontal cortex.