Aversive Imagery Causes De Novo Fear Conditioning

Mueller, Erik M.; Sperl, Matthias F.J.; Panitz, Christian

doi:10.1177/0956797619842261

Cited by 34 publications

(34 citation statements)

References 42 publications

(71 reference statements)

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“…Remembering the past and imagining the future share many similarities (Schacter et al, 2007(Schacter et al, , 2017. Here, we corroborate that we also learn from simulated experiences much as we learn from actual past experiences (Benoit et al, 2019;Driskell et al, 1994;Mueller et al, 2019). Specifically, we build on our previous observation that simulations can change attitudes towards our real-life environment.…”

Section: Discussionsupporting

confidence: 81%

“…Evidence from motor learning supports this idea: Imagining to execute a specific action can boost performance akin to actually carrying out that action (Driskell, Copper, & Moran, 1994). Moreover, fear conditioning can arise not only from the actual experience of an unconditioned stimulus (US) but also from merely imagining an aversive event (e.g., stepping onto a thumbtack) (Mueller, Sperl, & Panitz, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Simulation-based learning influences real-life attitudes

Paulus¹,

Dabas²,

Felber³

2021

Preprint

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Humans can vividly simulate hypothetical experiences. This ability draws on our memories (e.g., of familiar people and locations) to construct imaginings that resemble real-life events (e.g., of meeting a person at a location). Here, we examine the hypothesis that we also learn from such simulated episodes much like from actual experiences. Specifically, we show that the mere simulation of meeting a familiar person (unconditioned stimulus; US) at a known location (conditioned stimulus; CS) changes how people value the location. We provide key evidence that this simulation-based learning strengthens pre-existing CS-US associations and that it leads to a transfer of valence from the US to the CS. The data thus highlight a mechanism by which we learn from simulated experiences.

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Section: Discussionsupporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Simulation-based learning influences real-life attitudes

Paulus¹,

Dabas²,

Felber³

2021

Preprint

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“…In addition, the CS+ and CS-cues can be chosen to reinforce a particular emotion (e.g. [93][94][95]). For instance, the CS+ stimuli could be the image of a fearful face (thus reinforcing the anticipated fear of the US) while the CS-could be a neutral face.…”

Section: State-space Modelmentioning

confidence: 99%

A mixed filter algorithm for sympathetic arousal tracking from skin conductance and heart rate measurements in Pavlovian fear conditioning

Wickramasuriya

Faghih

2020

PLoS ONE

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Pathological fear and anxiety disorders can have debilitating impacts on individual patients and society. The neural circuitry underlying fear learning and extinction has been known to play a crucial role in the development and maintenance of anxiety disorders. Pavlovian conditioning, where a subject learns an association between a biologically-relevant stimulus and a neutral cue, has been instrumental in guiding the development of therapies for treating anxiety disorders. To date, a number of physiological signal responses such as skin conductance, heart rate, electroencephalography and cerebral blood flow have been analyzed in Pavlovian fear conditioning experiments. However, physiological markers are often examined separately to gain insight into the neural processes underlying fear acquisition. We propose a method to track a single brain-related sympathetic arousal state from physiological signal features during fear conditioning. We develop a state-space formulation that probabilistically relates features from skin conductance and heart rate to the unobserved sympathetic arousal state. We use an expectation-maximization framework for state estimation and model parameter recovery. State estimation is performed via Bayesian filtering. We evaluate our model on simulated and experimental data acquired in a trace fear conditioning experiment. Results on simulated data show the ability of our proposed method to estimate an unobserved arousal state and recover model parameters. Results on experimental data are consistent with skin conductance measurements and provide good fits to heartbeats modeled as a binary point process. The ability to track arousal from skin conductance and heart rate within a state-space model is an important precursor to the development of wearable monitors that could aid in patient care. Anxiety and trauma-related disorders are often accompanied by a heightened sympathetic tone and the methods described herein could find clinical applications in remote monitoring for therapeutic purposes.

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“…This phenomenon, often referred to as transfer of valence, is a well-documented learning mechanism at work during actual experiences (e.g., Hofmann et al, 2010;Palombo et al, 2021) but transfer of valence has only recently been observed during simulation. Other work by Mueller et al (2019) likewise shows that aversive mental imagery paired with a neutral stimulus (i.e., a "conditioned stimulus") can lead to a conditioned fear response, including increased subjective and objective indices of fear (also see Dadds et al, 1997;Jones & Davey, 1990;Soeter & Kindt, 2012 for work on imagination and conditioning). That is, de novo fear conditioning was observed in the absence of aversive physical stimuli.…”

Section: Simulations Inform Emotionsmentioning

confidence: 91%

Simulating the best and worst of times: The powers and perils of emotional simulation

Wardell¹,

Grilli

Palombo

2021

Preprint

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We are remarkably capable of simulating events that we have never experienced. These simulated events often paint an emotional picture to behold, such as the best and worst possible outcomes that we might face. This review synthesizes dispersed literature exploring the role of emotion in simulation. Drawing from work that suggests that simulations can influence our preferences, decision making, and prosociality, we argue for a critical role of emotion in informing the consequences of simulation. We further unpack burgeoning evidence suggesting that the effects of emotional simulation transcend the laboratory. We propose avenues by which emotional simulation can be harnessed for both personal and collective good in applied contexts. We conclude by offering important future directions.

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Aversive Imagery Causes De Novo Fear Conditioning

Cited by 34 publications

References 42 publications

Simulation-based learning influences real-life attitudes

Simulation-based learning influences real-life attitudes

A mixed filter algorithm for sympathetic arousal tracking from skin conductance and heart rate measurements in Pavlovian fear conditioning

Simulating the best and worst of times: The powers and perils of emotional simulation

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