Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model.
PLoS Comput Biol
; 12(9): e1005099, 2016 09.
Article
em En
| MEDLINE
| ID: mdl-27617747
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Córtex Pré-Frontal
/
Medo
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Tonsila do Cerebelo
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Memória
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Modelos Neurológicos
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
PLoS Comput Biol
Assunto da revista:
BIOLOGIA
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INFORMATICA MEDICA
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Japão
País de publicação:
Estados Unidos