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. 2019 Apr:26:9-17.
doi: 10.1016/j.cobeha.2018.09.002. Epub 2018 Sep 21.

Avoidance Problems Reconsidered

Affiliations

Avoidance Problems Reconsidered

Christopher K Cain. Curr Opin Behav Sci. 2019 Apr.

Abstract

Active avoidance is the prototypical paradigm for studying aversively-motivated instrumental behavior. However, avoidance research stalled amid heated theoretical debates and the hypothesis that active avoidance is essentially Pavlovian flight. Here I reconsider key "avoidance problems" and review neurobehavioral data collected with modern tools. Although the picture remains incomplete, these studies strongly suggest that avoidance has an instrumental component and is mediated by brain circuits that resemble appetitive instrumental actions more than Pavlovian fear reactions. Rapid progress may be possible if investigators consider important factors like safety signals, response-competition, goal-directed vs. habitual control and threat imminence in avoidance study design. Since avoidance responses likely contribute to active coping, this research has important implications for understanding human resilience and disorders of control.

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Conflict of interest statement

Conflict of interest statement Nothing declared.

Figures

Figure 1.
Figure 1.. Publications containing Fear Conditioning vs. Active Avoidance
(or related terms) in Title/Abstract (PubMed 6/25/2018). Note that avoidance research plateaued after Bolles’ SSDR Theory. Key behavioral and neurobiological tools that could resolve seemingly intractable “avoidance problems” are represented by numbers: (1) instrumental outcomedevaluation, (2) in vivo Fast-scan cyclic voltammetry measurement of dopamine, (3) instrumental contingency degradation, (4) optogenetic and (5) chemogenetic manipulation of neurons.
Figure 2.
Figure 2.. A. Relationship between stimuli and target response for a typical avoidance protocol.
Failure to perform an AR during the WS leads to delivery of a painful US. Performing the AR leads to immediate WS termination, exposure to feedback (FB; external & internal stimuli not present before the response) and cancelation of the scheduled US. B. Hypothetical associations acquired during SigAA training. Failed trials transform the WS into a Pavlovian threat that predicts the US. Exposure to instrumental contingencies likely produces both hierarchical goal-directed associations, where the WS indicates that response-produced outcomes are possible, and habitual associations, where the WS directly triggers the AR because of negative and/or positive reinforcement. Note that FB stimuli are initially neutral and must develop into safety signals (via negative correlation with aversive WS and painful shock) before they can influence AR learning. Tricolored asterisk denotes outcome(s)/reinforcer(s) since it remains unclear how WS-termination, US-omission and Safety Signals relate to stimuli and ARs during goal-directed vs. habitual avoidance learning.
Figure 3.
Figure 3.. Neurobehavioral model of active avoidance.
(A) Pavlovian SSDRs like freezing dominate early in avoidance training and are controlled by LA and CeA. (B) With exposure to instrumental contingencies, IL is recruited to suppress competing CeA-dependent SSDRs and threat processing is diverted to BA and striatal regions important for the learning and performance of goal-directed ARs. At this stage, VTA responses in striatum also contribute to response-selection (SSDR vs. AR, via suppression or facilitation of WS-evoked dopamine) and encode safety (via facilitation of feedback-evoked dopamine). (C) With continued training, IL suppression of Pavlovian SSDRs is no longer necessary and PL becomes important for AR performance. This may reflect the transition of the WS from a CS that predicts harm to a DS that signals the opportunity to avoid harm (attain safety). (D) After overtraining, habit circuits gain control of ARs and performance no longer depends on amygdala, VTA or goal-directed corticostriatal circuits. Dopaminergic inputs from SNc support reinforcement of habitual associations. Note that LA, BA, IL, NAc-shell and dorsal striatum are also implicated in safety signal learning [,,–81]. Both direct and indirect striatal output pathways contribute to AR performance [69,82]. Note also that latter stages of this model remain to be tested, especially the roles of DMS, DLS and IL. Abbreviations defined in text.
Figure 4.
Figure 4.. Defensive behavior continuum
(based on [21]). Red represents SSDRs and white represents intermixed non-defensive behaviors.

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