Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model.
Uncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings; this effect is know...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2016-09-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1005099 |
| _version_ | 1819007714570797056 |
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| author | Yuzhe Li Ken Nakae Shin Ishii Honda Naoki |
| author_facet | Yuzhe Li Ken Nakae Shin Ishii Honda Naoki |
| author_sort | Yuzhe Li |
| collection | DOAJ |
| description | Uncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings; this effect is known as the partial reinforcement extinction effect (PREE). Although the PREE has been explained by psychological theories, the neural mechanisms underlying the PREE remain largely unclear. Here, we developed a neural circuit model based on three distinct types of neurons (fear, persistent and extinction neurons) in the amygdala and medial prefrontal cortex (mPFC). In the model, the fear, persistent and extinction neurons encode predictions of net severity, of unconditioned stimulus (US) intensity, and of net safety, respectively. Our simulation successfully reproduces the PREE. We revealed that unpredictability of the US during extinction was represented by the combined responses of the three types of neurons, which are critical for the PREE. In addition, we extended the model to include amygdala subregions and the mPFC to address a recent finding that the ventral mPFC (vmPFC) is required for consolidating extinction memory but not for memory retrieval. Furthermore, model simulations led us to propose a novel procedure to enhance extinction learning through re-conditioning with a stronger US; strengthened fear memory up-regulates the extinction neuron, which, in turn, further inhibits the fear neuron during re-extinction. Thus, our models increased the understanding of the functional roles of the amygdala and vmPFC in the processing of uncertainty in fear conditioning and extinction. |
| first_indexed | 2024-12-21T00:28:58Z |
| format | Article |
| id | doaj.art-3ce91be655e9452985ad1f7c90e21357 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-21T00:28:58Z |
| publishDate | 2016-09-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-3ce91be655e9452985ad1f7c90e213572022-12-21T19:21:55ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582016-09-01129e100509910.1371/journal.pcbi.1005099Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model.Yuzhe LiKen NakaeShin IshiiHonda NaokiUncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings; this effect is known as the partial reinforcement extinction effect (PREE). Although the PREE has been explained by psychological theories, the neural mechanisms underlying the PREE remain largely unclear. Here, we developed a neural circuit model based on three distinct types of neurons (fear, persistent and extinction neurons) in the amygdala and medial prefrontal cortex (mPFC). In the model, the fear, persistent and extinction neurons encode predictions of net severity, of unconditioned stimulus (US) intensity, and of net safety, respectively. Our simulation successfully reproduces the PREE. We revealed that unpredictability of the US during extinction was represented by the combined responses of the three types of neurons, which are critical for the PREE. In addition, we extended the model to include amygdala subregions and the mPFC to address a recent finding that the ventral mPFC (vmPFC) is required for consolidating extinction memory but not for memory retrieval. Furthermore, model simulations led us to propose a novel procedure to enhance extinction learning through re-conditioning with a stronger US; strengthened fear memory up-regulates the extinction neuron, which, in turn, further inhibits the fear neuron during re-extinction. Thus, our models increased the understanding of the functional roles of the amygdala and vmPFC in the processing of uncertainty in fear conditioning and extinction.https://doi.org/10.1371/journal.pcbi.1005099 |
| spellingShingle | Yuzhe Li Ken Nakae Shin Ishii Honda Naoki Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model. PLoS Computational Biology |
| title | Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model. |
| title_full | Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model. |
| title_fullStr | Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model. |
| title_full_unstemmed | Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model. |
| title_short | Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model. |
| title_sort | uncertainty dependent extinction of fear memory in an amygdala mpfc neural circuit model |
| url | https://doi.org/10.1371/journal.pcbi.1005099 |
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