A Recurrent Network in the Lateral Amygdala: A Mechanism for Coincidence Detection

W. M. Keck Foundation Laboratory of Neurobiology, Center for Neural Science New York, USA.
Frontiers in Neural Circuits (Impact Factor: 3.6). 02/2008; 2:3. DOI: 10.3389/neuro.04.003.2008
Source: PubMed


Synaptic changes at sensory inputs to the dorsal nucleus of the lateral amygdala (LAd) play a key role in the acquisition and storage of associative fear memory. However, neither the temporal nor spatial architecture of the LAd network response to sensory signals is understood. We developed a method for the elucidation of network behavior. Using this approach, temporally patterned polysynaptic recurrent network responses were found in LAd (intra-LA), both in vitro and in vivo, in response to activation of thalamic sensory afferents. Potentiation of thalamic afferents resulted in a depression of intra-LA synaptic activity, indicating a homeostatic response to changes in synaptic strength within the LAd network. Additionally, the latencies of thalamic afferent triggered recurrent network activity within the LAd overlap with known later occurring cortical afferent latencies. Thus, this recurrent network may facilitate temporal coincidence of sensory afferents within LAd during associative learning.

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Available from: Luke R Johnson, Oct 01, 2015
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    • "In addition, an improved amygdala model is required. The recurrent nature of the main input nuclei in the amygdala [23] encourages us to explore a reservoir approach for the future implementation of the BLA module. As we are aiming to develop an embodied model of auditory-cue fear conditioning a CE module with more output units may be necessary to encode a variety of different conditioned behaviors. "
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    ABSTRACT: In this work, we present a neurocomputational model for auditory-cue fear acquisition. Computational fear conditioning has experienced a growing interest over the last few years, on the one hand, because it is a robust and quick learning paradigm that can contribute to the development of more versatile robots, and on the other hand, because it can help in the understanding of fear conditioning and dysfunctions in animals. Fear learning involves sensory and motor aspects [1] and it is essential for adaptive self-protective systems. We argue that a deeper study of the mechanisms underlying fear circuits in the brain will contribute not only to the development of safer robots but eventually also to a better conceptual understanding of neural fear processing in general. Towards the development of a robotic adaptive self-protective system, we have designed a neural model of fear conditioning based on LeDoux's dual-route hypothesis of fear [2] and also dopamine modulated Pavlovian conditioning [3]. Our hybrid approach is capable of learning the temporal relationship between auditory sensory cues and an aversive or appetitive stimulus. The model was tested as a neural network simulation but it was designed to be used with minor modifications on a robotic platform.
    Proceedings of the International Joint Conference on Neural Networks (IJCNN), Brisbane, QLD, Australia; 06/2012
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    • "One possible mechanism that may allow for the two temporally segregated sensory inputs to converge in time as well as in space is a recurrent network in the LA. This network may allow for thalamo-LA signals to feedback to the superior parts of the LA during conditioning where they will meet incoming cortical signals (Johnson et al., 2008). It is not known if this recurrent feedback is directed to the same neurons which received the cortical input or to adjacent neurons. "
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    ABSTRACT: Pavlovian fear conditioning, also known as classical fear conditioning is an important model in the study of the neurobiology of normal and pathological fear. Progress in the neurobiology of Pavlovian fear also enhances our understanding of disorders such as posttraumatic stress disorder (PTSD) and with developing effective treatment strategies. Here we describe how Pavlovian fear conditioning is a key tool for understanding both the neurobiology of fear and the mechanisms underlying variations in fear memory strength observed across different phenotypes. First we discuss how Pavlovian fear models aspects of PTSD. Second, we describe the neural circuits of Pavlovian fear and the molecular mechanisms within these circuits that regulate fear memory. Finally, we show how fear memory strength is heritable; and describe genes which are specifically linked to both changes in Pavlovian fear behavior and to its underlying neural circuitry. These emerging data begin to define the essential genes, cells and circuits that contribute to normal and pathological fear. This article is part of a Special Issue entitled 'Post-Traumatic Stress Disorder'.
    Neuropharmacology 02/2012; 62(2):638-46. DOI:10.1016/j.neuropharm.2011.07.004 · 5.11 Impact Factor
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    • "Potentials were sequentially activated, with a suitable separation latency, which allowed for direct comparison of potentials. Extracellular evoked fEPSP amplitudes were measured as previously described (Lamprecht et al., 2006; Johnson et al., 2008, 2009; see also Huang et al., 2000). The fEPSP in both pathways ranged in size from 0.2 to 0.6 mV without picrotoxin (PTX) and from 0.5 to 1.2 mV in the presence of PTX (Figure 1B). "
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    ABSTRACT: Pavlovian auditory fear conditioning involves the integration of information about an acoustic conditioned stimulus (CS) and an aversive unconditioned stimulus in the lateral nucleus of the amygdala (LA). The auditory CS reaches the LA subcortically via a direct connection from the auditory thalamus and also from the auditory association cortex itself. How neural modulators, especially those activated during stress, such as norepinephrine (NE), regulate synaptic transmission and plasticity in this network is poorly understood. Here we show that NE inhibits synaptic transmission in both the subcortical and cortical input pathway but that sensory processing is biased toward the subcortical pathway. In addition binding of NE to β-adrenergic receptors further dissociates sensory processing in the LA. These findings suggest a network mechanism that shifts sensory balance toward the faster but more primitive subcortical input.
    Frontiers in Behavioral Neuroscience 05/2011; 5:23. DOI:10.3389/fnbeh.2011.00023 · 3.27 Impact Factor
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