The Role of the Medial Prefrontal Cortex in Spatial Margin of Safety Calculations

Qi, Song; Cross, Logan; Wise, Toby; Sui, Xin; O’Doherty, John P.; Mobbs, Dean

doi:10.2139/ssrn.3653545

Cited by 3 publications

(4 citation statements)

References 2 publications

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“…While we cannot pinpoint the precise source of this reactivation using MEG alone, the regions within this cluster include those proposed to represent cognitive maps across multiple task domains ( 41 , 42 ). These regions are implicated also in counterfactual thinking ( 43 – 45 ) and avoidance ( 35 , 46 , 47 ). Our results extend upon this prior work and would be consistent with a proposal that these regions support a form of counterfactual updating based on a learned model of the environment.…”

Section: Discussionmentioning

confidence: 99%

Model-based aversive learning in humans is supported by preferential task state reactivation

et al. 2021

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Harm avoidance is critical for survival, yet little is known regarding the neural mechanisms supporting avoidance in the absence of trial-and-error experience. Flexible avoidance may be supported by a mental model (i.e., model-based), a process for which neural reactivation and sequential replay have emerged as candidate mechanisms. During an aversive learning task, combined with magnetoencephalography, we show prospective and retrospective reactivation during planning and learning, respectively, coupled to evidence for sequential replay. Specifically, when individuals plan in an aversive context, we find preferential reactivation of subsequently chosen goal states. Stronger reactivation is associated with greater hippocampal theta power. At outcome receipt, unchosen goal states are reactivated regardless of outcome valence. Replay of paths leading to goal states was modulated by outcome valence, with aversive outcomes associated with stronger reverse replay than safe outcomes. Our findings are suggestive of avoidance involving simulation of unexperienced states through hippocampally mediated reactivation and replay.

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Section: Discussionmentioning

confidence: 99%

Model-based aversive learning in humans is supported by preferential task state reactivation

et al. 2021

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“…The demographic information of the remaining 12 patients (5 females; age, 29.42 ± 10.04 years, mean ± SD) is shown in Table 1. During intracranial recordings, participants performed a modified FID task [11, 42]. In this task, participants were instructed to imagine themselves as prey and need to escape from the predator, during which they were also instructed to escape as late as possible to obtain more survival resources (Figure 1 A).…”

Section: Resultsmentioning

confidence: 99%

“…(iii) The activities in the reactive and cognitive fear circuits would exhibit a contradictory relationship under rapid attack, with higher activity in the reactive circuit associated with lower activity in the cognitive circuit. To test these hypotheses, we conducted sEEG recordings from 12 patients while they performed a modified FID task [11, 42] (Figure 1 A, B, C). In this task, participants were instructed to imagine themselves as prey and need to escape from the predators (Figure 1 A).…”

Section: Introductionmentioning

confidence: 99%

An intracranial dissection of human escape circuits

Zhang,

Cheng,

et al. 2024

Preprint

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Predators attack at different spatiotemporal scales, spurring prey to elicit escape responses that range from simple motor reactions and strategic planning that involve more complex cognitive processes. Recent work in humans suggests that escape relies on two distinct circuits: the reactive and cognitive fear circuits. However, the specific involvement of these two circuits in different stages of human escaping remains poorly characterized. In this study, we recorded intracranial electroencephalography (iEEG) from epilepsy patients while they performed a modified flight initiation distance (FID) task. We found brain regions in the cognitive fear circuit, including the ventromedial prefrontal cortex and hippocampus, encoded the threat level during the information processing stage. The actual escaping stage, especially under rapid attack, prominently activated areas within the reactive fear circuit, including the midcingulate cortex and amygdala. Furthermore, we observed a negative correlation between the high gamma activity (HGA) of the amygdala and the HGA of the vmPFC and HPC under rapid attacks. This indicates that the amygdala may suppress the activity of the cognitive fear circuit under rapid attacks, enabling the organism to react quickly to ensure survival under the imminent threat. These findings highlight the distinct roles of the reactive and cognitive fear circuits in human escaping, and provide a foundation for further research and potential applications.

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“…Our prior work shows that neural systems involved in defensive responding are dissociable along the threat imminence continuum. 36,39 The task used in the current study was not designed to examine dynamic threat nor did it evoke escape behavior. Further work is needed to determine under what conditions vmPFC-supported cognition is unavailable.…”

Section: The Vmpfc Was Identified Through Searchlight Analyses As Inv...mentioning

confidence: 99%

Adaptive Safety Coding in the Prefrontal Cortex

Tashjian,

Cussen,

Deng

et al. 2024

Preprint

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Pivotal to self-preservation is the ability to identify when we are safe and when we are in danger. Previous studies have focused on safety estimations based on the features of external threats and do not consider how the brain integrates other key factors, including estimates about our ability to protect ourselves. Here we examine the neural systems underlying the online dynamic encoding of safety. The current preregistered study used two novel tasks to test four facets of safety estimation: Safety Prediction, Meta-representation, Recognition, and Value Updating. We experimentally manipulated safety estimation changing both levels of external threats and self-protection. Data were collected in two independent samples (behavioral N=100; fMRI N=30). We found consistent evidence of subjective changes in the sensitivity to safety conferred through protection. Neural responses in the ventromedial prefrontal cortex (vmPFC) tracked increases in safety during all safety estimation facets, with specific tuning to protection. Further, informational connectivity analyses revealed distinct hubs of safety coding in the posterior and anterior vmPFC for external threats and protection, respectively. These findings reveal a central role of the vmPFC for coding safety.

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The Role of the Medial Prefrontal Cortex in Spatial Margin of Safety Calculations

Cited by 3 publications

References 2 publications

Model-based aversive learning in humans is supported by preferential task state reactivation

Model-based aversive learning in humans is supported by preferential task state reactivation

An intracranial dissection of human escape circuits

Adaptive Safety Coding in the Prefrontal Cortex

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