Impact of infralimbic inputs on intercalated amygdala neurons: A biophysical modeling study

Department of Psychology, Cornell University, Ithaca, New York 14850, USA.
Learning & memory (Cold Spring Harbor, N.Y.) (Impact Factor: 4.38). 03/2011; 18(4):226-40. DOI: 10.1101/lm.1938011
Source: PubMed

ABSTRACT Intercalated (ITC) amygdala neurons regulate fear expression by controlling impulse traffic between the input (basolateral amygdala; BLA) and output (central nucleus; Ce) stations of the amygdala for conditioned fear responses. Previously, stimulation of the infralimbic (IL) cortex was found to reduce fear expression and the responsiveness of Ce neurons to BLA inputs. These effects were hypothesized to result from the activation of ITC cells projecting to Ce. However, ITC cells inhibit each other, leading to the question of how IL inputs could overcome the inter-ITC inhibition to regulate the responses of Ce neurons to aversive conditioned stimuli (CSs). To investigate this, we first developed a compartmental model of a single ITC cell that could reproduce their bistable electroresponsive properties, as observed experimentally. Next, we generated an ITC network that implemented the experimentally observed short-term synaptic plasticity of inhibitory inter-ITC connections. Model experiments showed that strongly adaptive CS-related BLA inputs elicited persistent responses in ITC cells despite the presence of inhibitory interconnections. The sustained CS-evoked activity of ITC cells resulted from an unusual slowly deinactivating K(+) current. Finally, over a wide range of stimulation strengths, brief IL activation caused a marked increase in the firing rate of ITC neurons, leading to a persistent decrease in Ce output, despite inter-ITC inhibition. Simulations revealed that this effect depended on the bistable properties and synaptic heterogeneity of ITC neurons. These results support the notion that IL inputs are in a strategic position to control extinction of conditioned fear via the activation of ITC neurons.

Download full-text


Available from: Denis Paré, Aug 24, 2015
  • Source
    • "Both soma and dendritic compartments had the following currents: I L , I Na , I DR , persistent muscarinic, and I Ca . In addition to these, the dendrite had the following currents: I KCa , slow apamininsensitive , voltage-independent afterhyperpolarization channel, I D , and I H (same as in Li et al. 2011). For the Ce lateral (CeL) neurons, we used a modified version of the regular spiking CeM cell, with the same passive properties above, except for E L which was Ϫ70 mV. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The acquisition and expression of conditioned fear depends on prefrontal-amygdala circuits. Auditory fear conditioning increases the tone responses of lateral amygdala (LA) neurons, but the increase is transient, lasting only a few hundred milliseconds after tone onset. It was recently reported that that the prelimbic (PL) prefrontal cortex transforms transient LA input into a sustained PL output, which could drive fear responses via projections to the lateral division of basal amygdala (BL). To explore the possible mechanisms involved in this transformation, we developed a large-scale biophysical model of the BL-PL network, consisting of 850 conductance-based Hodgkin-Huxley type cells, calcium-based learning, and neuromodulator effects. The model predicts that sustained firing in PL can be derived from BL-induced release of dopamine and norepinephrine that is maintained by PL-BL interconnections. These predictions were confirmed with physiological recordings from PL neurons during fear conditioning with the selective β-blocker propranolol and by inactivation of BL with muscimol. Our model suggests that PL has a higher bandwidth than BL, due to PL's decreased internal inhibition and lower spiking thresholds. It also suggests that variations in specific micro-circuits in the PL-BL interconnection can have a significant impact on the expression of fear, possibly explaining individual variability in fear responses. The human homologue of PL could thus be an effective target for anxiety disorders.
    Journal of Neurophysiology 05/2013; 110(4). DOI:10.1152/jn.00961.2012 · 3.04 Impact Factor
  • Source
    • "In summary, the available data suggest a prominent role of Imp cells of amygdala in fear learning, and the α2 and/or α3 subunit of GABA A receptors appears to be a novel molecular target for anxiolytic drugs (Likhtik et al., 2008; Rudolph and Knoflach, 2011). Therefore, we aimed to define whether these subunit-containing GABA A receptors are functionally present at synapses between Imp neurons. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In the amygdala, GABAergic neurons in the intercalated medial paracapsular cluster (Imp) have been suggested to play a key role in fear learning and extinction. These neurons project to the central (CE) amygdaloid nucleus and to other areas within and outside the amygdala. In addition, they give rise to local collaterals that innervate other neurons in the Imp. Several drugs, including benzodiazepines (BZ), are allosteric modulators of GABA(A) receptors. BZ has both anxiolytic and sedative actions, which are mediated through GABA(A) receptors containing α2/α3 and α1 subunits, respectively. To establish whether α1 or α2/α3 subunits are expressed at Imp cell synapses, we used paired recordings of anatomically identified Imp neurons and high resolution immunocytochemistry in the mouse. We observed that a selective α3 subunit agonist, TP003 (100 nM), significantly increased the decay time constant of the unitary IPSCs. A similar effect was also induced by zolpidem (10 μM) or by diazepam (1 μM). In contrast, lower doses of zolpidem (0.1-1 μM) did not significantly alter the kinetics of the unitary IPSCs. Accordingly, immunocytochemical experiments established that the α2 and α3, but not the α1 subunits of the GABA(A) receptors, were present at Imp cell synapses of the mouse amygdala. These results define, for the first time, some of the functional GABA(A) receptor subunits expressed at synapses of Imp cells. The data also provide an additional rationale to prompt the search of GABA(A) receptor α3 selective ligands as improved anxiolytic drugs.
    Frontiers in Neural Circuits 05/2012; 6:32. DOI:10.3389/fncir.2012.00032 · 2.95 Impact Factor
  • Source
    • "Alternatively, SPS effects on extinction retention can be mediated through SPS-induced changes in excitatory neurotransmitter levels, as SPS exposure attenuates glutamate levels in the mPFC (Knox et al. 2010). If SPS effects on glutamate levels in the IL cortex reflect the physiological status of glutamatergic neurotransmission in these animals, then this could result in decreased excitatory tone in the IL cortex, which, in turn, could directly affect extinction retention by disrupting IL cortical modulation of downstream targets, such as the intercalated region of the amygdala (Rosenkranz and Grace 2002; Rosenkranz et al. 2003; Pare et al. 2004; Quirk et al. 2006; Li et al. 2011). It has Figure 3. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Clinical research has linked post-traumatic stress disorder (PTSD) with deficits in fear extinction. However, it is not clear whether these deficits result from stress-related changes in the acquisition or retention of extinction or in the regulation of extinction memories by context, for example. In this study, we used the single prolonged stress (SPS) animal model of PTSD and fear conditioning procedures to examine the effects of prior traumatic stress on the acquisition, retention, and context-specificity of extinction. SPS administered one week prior to fear conditioning had no effect on the acquisition of fear conditioning or extinction but disrupted the retention of extinction memories for both contextual and cued fear. This SPS effect required a post-stress incubation period to manifest. The results demonstrate that SPS disrupts extinction retention, leading to enhanced fear renewal; further research is needed to identify the neurobiological processes through which SPS induces these effects.
    Learning & memory (Cold Spring Harbor, N.Y.) 01/2012; 19(2):43-9. DOI:10.1101/lm.024356.111 · 4.38 Impact Factor
Show more

Similar Publications