ArticleNPJ science of learning2016
Biologically based neural circuit modelling for the study of fear learning and extinction.
Article in NPJ science of learning, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- Regulation of amygdala and dopamine system in naïve and chronic alcohol states.Alcohol (Fayetteville, N.Y.) · 2026Article
- Effects of Sex, Estradiol, and Acute Stress on Spontaneous Recovery of a Conditioned Touchscreen Response in Rats.Neuroscience insights · 2026Article
- Article
- Basolateral amygdala oscillations enable fear learning in a biophysical model.bioRxiv : the preprint server for biology · 2024Article
- Developing a 3-D computational model of neurons in the central amygdala to understand pharmacological targets for pain.Frontiers in pain research (Lausanne, Switzerland) · 2023Article
- A Biologically Inspired Neural Network Model to Gain Insight Into the Mechanisms of Post-Traumatic Stress Disorder and Eye Movement Desensitization and Reprocessing Therapy.Frontiers in psychology · 2022Article
- Modelling learning in Caenorhabditis elegans chemosensory and locomotive circuitry for T-maze navigation.The European journal of neuroscience · 2022Article
- Neural Circuits Underlying Social Fear in Rodents: An Integrative Computational Model.Frontiers in systems neuroscience · 2022Article
- Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.PLoS computational biology · 2021Article
- A Computational Model Integrating Multiple Phenomena on Cued Fear Conditioning, Extinction, and Reinstatement.Frontiers in systems neuroscience · 2020Article
- Integrating Model-Based Approaches into a Neuroscience Curriculum-An Interdisciplinary Neuroscience Course in Engineering.IEEE transactions on education · 2019Article
- A neural mass model to predict electrical stimulation evoked responses in human and non-human primate brain.Journal of neural engineering · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.