A biologically realistic network model of acquisition and extinction of conditioned fear associations in lateral amygdala neurons

A scalable spiking amygdala model that explains fear conditioning, extinction, renewal and generalization

The amygdala (AMY) is widely implicated in fear learning and fear behaviour, but it remains unclear how the many biological components present within AMY interact to achieve these abilities. Building on previous work, we hypothesize that individual AMY nuclei represent different quantities and that fear conditioning arises from error-driven learning on the synapses between AMY nuclei. We present a computational model of AMY that (a) recreates the divisions and connections between AMY nuclei and their constituent pyramidal and inhibitory neurons; (b) accommodates scalable high-dimensional representations of external stimuli; (c) learns to associate complex stimuli with the presence (or absence) of an aversive stimulus; (d) preserves feature information when mapping inputs to salience estimates, such that these estimates generalize to similar stimuli; and (e) induces a diverse profile of neural responses within each nucleus. Our model predicts (1) defensive responses and neural activities in several experimental conditions, (2) the consequence of artificially ablating particular nuclei and (3) the tendency to generalize defensive responses to novel stimuli. We test these predictions by comparing model outputs to neural and behavioural data from animals and humans. Despite the relative simplicity of our model, we find significant overlap between simulated and empirical data, which supports our claim that the model captures many of the neural mechanisms that support fear conditioning. We conclude by comparing our model to other computational models and by characterizing the theoretical relationship between pattern separation and fear generalization in healthy versus anxious individuals.

Olfactory threat extinction in the piriform cortex: An age-dependent employment of NMDA receptor-dependent long-term depression

Extinction of threat memory is a measure of behavioral flexibility. In the absence of additional reinforcement, the extinction of learned behaviors allows animals and humans to adapt to their changing environment. Extinction mechanisms and their therapeutic implications for maladaptive learning have been extensively studied. However, how aging affects extinction learning is much less understood. Using a rat model of olfactory threat extinction, we show that the extinction of olfactory threat memory is impaired in aged Sprague-Darley rats. Following extinction training, long-term depression (LTD) in the piriform cortex (PC) was inducible ex vivo in aged rats and was NMDA receptor (NMDAR)-independent. On the other hand, adult rats acquired successful olfactory threat extinction, and LTD was not inducible following extinction training. Neuronal cFos activation in the posterior PC correlated with learning and extinction performance in rats. NMDAR blockade either systemically or locally in the PC during extinction training prevented successful extinction in adult rats, following which NMDAR-dependent LTD became inducible ex vivo. This suggests that extinction learning employs NMDAR-dependent LTD mechanisms in the PC of adult rats, thus occluding further LTD induction ex vivo. The rescue of olfactory threat extinction in aged rats by D-cycloserine, a partial NMDAR agonist, suggests that the impairment in olfactory threat extinction of aged animals may relate to NMDAR hypofunctioning and a lack of NMDAR-dependent LTD. These findings are consistent with an age-related switch from NMDAR-dependent to NMDAR-independent LTD in the PC. Optimizing NMDAR function in sensory cortices may improve learning and flexible behavior in the aged population.

Mathematical models of learning and what can be learned from them

Learning is a multi-faceted phenomenon of critical importance and hence attracted a great deal of research, both experimental and theoretical. In this review, we will consider some of the paradigmatic examples of learning and discuss the common themes in theoretical learning research, such as levels of modeling and their corresponding relation to experimental observations and mathematical ideas common to different types of learning.

Reverse engineering information processing in lateral amygdala during auditory tones

Learning in the mammalian lateral amygdala (LA) during auditory fear conditioning (tone - foot shock pairing), one form of associative learning, requires N-methyl-D-aspartate (NMDA) receptor-dependent plasticity. Despite this fact being known for more than two decades, the biophysical details related to signal flow and the involvement of the coincidence detector, NMDAR, in this learning, remain unclear. Here we use a 4000-neuron computational model of the LA (containing two types of pyramidal cells, types A and C, and two types of interneurons, fast spiking FSI and low-threshold spiking LTS) to reverse engineer changes in information flow in the amygdala that underpin such learning; with a specific focus on the role of the coincidence detector NMDAR. The model also included a Ca^2s based learning rule for synaptic plasticity. The physiologically constrained model provides insights into the underlying mechanisms that implement habituation to the tone, including the role of NMDARs in generating network activity which engenders synaptic plasticity in specific afferent synapses. Specifically, model runs revealed that NMDARs in tone-FSI synapses were more important during the spontaneous state, although LTS cells also played a role. Training trails with tone only also suggested long term depression in tone-PN as well as tone-FSI synapses, providing possible hypothesis related to underlying mechanisms that might implement the phenomenon of habituation.

Emotional Memory Processing during REM Sleep with Implications for Post-Traumatic Stress Disorder

REM sleep is important for the processing of emotional memories, including fear memories. Rhythmic interactions, especially in the theta band, between the medial prefrontal cortex (mPFC) and limbic structures are thought to play an important role, but the ways in which memory processing occurs at a mechanistic and circuits level are largely unknown. To investigate how rhythmic interactions lead to fear extinction during REM sleep, we used a biophysically based model that included the infralimbic cortex (IL), a part of the mPFC with a critical role in suppressing fear memories. Theta frequency (4-12 Hz) inputs to a given cell assembly in IL, representing an emotional memory, resulted in the strengthening of connections from the IL to the amygdala and the weakening of connections from the amygdala to the IL, resulting in the suppression of the activity of fear expression cells for the associated memory. Lower frequency (4 Hz) theta inputs effected these changes over a wider range of input strengths. In contrast, inputs at other frequencies were ineffective at causing these synaptic changes and did not suppress fear memories. Under post-traumatic stress disorder (PTSD) REM sleep conditions, rhythmic activity dissipated, and 4 Hz theta inputs to IL were ineffective, but higher-frequency (10 Hz) theta inputs to IL induced changes similar to those seen with 4 Hz inputs under normal REM sleep conditions, resulting in the suppression of fear expression cells. These results suggest why PTSD patients may repeatedly experience the same emotionally charged dreams and suggest potential neuromodulatory therapies for the amelioration of PTSD symptoms.SIGNIFICANCE STATEMENT Rhythmic interactions in the theta band between the mPFC and limbic structures are thought to play an important role in processing emotional memories, including fear memories, during REM sleep. The infralimbic cortex (IL) in the mPFC is thought to play a critical role in suppressing fear memories. We show that theta inputs to the IL, unlike other frequency inputs, are effective in producing synaptic changes that suppress the activity of fear expression cells associated with a given memory. Under PTSD REM sleep conditions, lower-frequency (4 Hz) theta inputs to the IL do not suppress the activity of fear expression cells associated with the given memory but, surprisingly, 10 Hz inputs do. These results suggest potential neuromodulatory therapies for PTSD.

From descriptive connectome to mechanistic connectome: Generative modeling in functional magnetic resonance imaging analysis

As a newly emerging field, connectomics has greatly advanced our understanding of the wiring diagram and organizational features of the human brain. Generative modeling-based connectome analysis, in particular, plays a vital role in deciphering the neural mechanisms of cognitive functions in health and dysfunction in diseases. Here we review the foundation and development of major generative modeling approaches for functional magnetic resonance imaging (fMRI) and survey their applications to cognitive or clinical neuroscience problems. We argue that conventional structural and functional connectivity (FC) analysis alone is not sufficient to reveal the complex circuit interactions underlying observed neuroimaging data and should be supplemented with generative modeling-based effective connectivity and simulation, a fruitful practice that we term "mechanistic connectome." The transformation from descriptive connectome to mechanistic connectome will open up promising avenues to gain mechanistic insights into the delicate operating principles of the human brain and their potential impairments in diseases, which facilitates the development of effective personalized treatments to curb neurological and psychiatric disorders.

Neural Circuits Underlying Social Fear in Rodents: An Integrative Computational Model

Social avoidance in rodents arises from a complex interplay between the prefrontal cortex and subcortical structures, such as the ventromedial hypothalamus and the dorsal periaqueductal gray matter. Experimental studies are revealing the contribution of these areas, but an integrative view and model of how they interact to produce adaptive behavior are still lacking. Here, we present a computational model of social avoidance, proposing a set of integrated hypotheses on the possible macro organization of the brain system underlying this phenomenon. The model is validated by accounting for several different empirical findings and produces predictions to be tested in future experiments.

Multiscale neural modeling of resting-state fMRI reveals executive-limbic malfunction as a core mechanism in major depressive disorder

Major depressive disorder (MDD) represents a grand challenge to human health and society, but the underlying pathophysiological mechanisms remain elusive. Previous neuroimaging studies have suggested that MDD is associated with abnormal interactions and dynamics in two major neural systems including the default mode - salience (DMN-SAL) network and the executive - limbic (EXE-LIM) network, but it is not clear which network plays a central role and which network plays a subordinate role in MDD pathophysiology. To address this question, we refined a newly developed Multiscale Neural Model Inversion (MNMI) framework and applied it to test whether MDD is more affected by impaired circuit interactions in the DMN-SAL network or the EXE-LIM network. The model estimates the directed connection strengths between different neural populations both within and between brain regions based on resting-state fMRI data collected from normal healthy subjects and patients with MDD. Results show that MDD is primarily characterized by abnormal circuit interactions in the EXE-LIM network rather than the DMN-SAL network. Specifically, we observe reduced frontoparietal effective connectivity that potentially contributes to hypoactivity in the dorsolateral prefrontal cortex (dlPFC), and decreased intrinsic inhibition combined with increased excitation from the superior parietal cortex (SPC) that potentially lead to amygdala hyperactivity, together resulting in activation imbalance in the PFC-amygdala circuit that pervades in MDD. Moreover, the model reveals reduced PFC-to-hippocampus excitation but decreased SPC-to-thalamus inhibition in MDD population that potentially lead to hypoactivity in the hippocampus and hyperactivity in the thalamus, consistent with previous experimental data. Overall, our findings provide strong support for the long-standing limbic-cortical dysregulation model in major depression but also offer novel insights into the multiscale pathophysiology of this debilitating disease.

Microcircuit mechanisms for the generation of sharp-wave ripples in the basolateral amygdala: A role for chandelier interneurons

Synchronized activity in neural circuits, detected as oscillations in the extracellular field potential, has been associated with learning and memory. Neural circuits in the basolateral amygdala (BLA), a mid-temporal lobe structure, generate oscillations in specific frequency bands to mediate emotional memory functions. However, how BLA circuits generate oscillations in distinct frequency bands is not known. Of these, sharp-waves (SWs) are repetitive, brief transitions that contain a low-frequency (<20 Hz) envelope, often coupled with ripples (100–300 Hz), have been associated with memory consolidation. Here, we show that SWs are retained in the BLA ex vivo and generated by local circuits. We demonstrate that an action potential in a chandelier interneuron is sufficient to initiate SWs through local circuits. Using a physiologically constrained model, we show that microcircuits organized as chandelier-interneuron-driven modules reproduce SWs and associated cellular events, revealing a functional role for chandelier interneurons and microcircuits for SW generation.

Perumal et al. investigate circuits that generate network oscillations called sharp waves (SWs) in the basolateral amygdala. They show that discharge in a chandelier interneuron can initiate SW oscillations—a network activity associated with memory consolidation. They develop a network model with chandelier-interneuron-driven modular microcircuits for SW generation.

BEHAVIORAL AND NEUROBIOLOGICAL MECHANISMS OF PAVLOVIAN AND INSTRUMENTAL EXTINCTION LEARNING

This article reviews the behavioral neuroscience of extinction, the phenomenon in which a behavior that has been acquired through Pavlovian or instrumental (operant) learning decreases in strength when the outcome that reinforced it is removed. Behavioral research indicates that neither Pavlovian nor operant extinction depends substantially on erasure of the original learning but instead depends on new inhibitory learning that is primarily expressed in the context in which it is learned, as exemplified by the renewal effect. Although the nature of the inhibition may differ in Pavlovian and operant extinction, in either case the decline in responding may depend on both generalization decrement and the correction of prediction error. At the neural level, Pavlovian extinction requires a tripartite neural circuit involving the amygdala, prefrontal cortex, and hippocampus. Synaptic plasticity in the amygdala is essential for extinction learning, and prefrontal cortical inhibition of amygdala neurons encoding fear memories is involved in extinction retrieval. Hippocampal-prefrontal circuits mediate fear relapse phenomena, including renewal. Instrumental extinction involves distinct ensembles in corticostriatal, striatopallidal, and striatohypothalamic circuits as well as their thalamic returns for inhibitory (extinction) and excitatory (renewal and other relapse phenomena) control over operant responding. The field has made significant progress in recent decades, although a fully integrated biobehavioral understanding still awaits.

A Computational Model Integrating Multiple Phenomena on Cued Fear Conditioning, Extinction, and Reinstatement

Conditioning, extinction, and reinstatement are fundamental learning processes of animal adaptation, also strongly involved in human pathologies such as post-traumatic stress disorder, anxiety, depression, and dependencies. Cued fear conditioning, extinction, restatement, and systematic manipulations of the underlying brain amygdala and medial prefrontal cortex, represent key experimental paradigms to study such processes. Numerous empirical studies have revealed several aspects and the neural systems and plasticity underlying them, but at the moment we lack a comprehensive view. Here we propose a computational model based on firing rate leaky units that contributes to such integration by accounting for 25 different experiments on fear conditioning, extinction, and restatement, on the basis of a single neural architecture having a structure and plasticity grounded in known brain biology. This allows the model to furnish three novel contributions to understand these open issues: (a) the functioning of the central and lateral amygdala system supporting conditioning; (b) the role played by the endocannabinoids system in within- and between-session extinction; (c) the formation of three important types of neurons underlying fear processing, namely fear, extinction, and persistent neurons. The model integration of the results on fear conditioning goes substantially beyond what was done in previous models.

A systems-neuroscience model of phasic dopamine

We describe a neurobiologically informed computational model of phasic dopamine signaling to account for a wide range of findings, including many considered inconsistent with the simple reward prediction error (RPE) formalism. The central feature of this PVLV framework is a distinction between a primary value (PV) system for anticipating primary rewards (Unconditioned Stimuli [USs]), and a learned value (LV) system for learning about stimuli associated with such rewards (CSs). The LV system represents the amygdala, which drives phasic bursting in midbrain dopamine areas, while the PV system represents the ventral striatum, which drives shunting inhibition of dopamine for expected USs (via direct inhibitory projections) and phasic pausing for expected USs (via the lateral habenula). Our model accounts for data supporting the separability of these systems, including individual differences in CS-based (sign-tracking) versus US-based learning (goal-tracking). Both systems use competing opponent-processing pathways representing evidence for and against specific USs, which can explain data dissociating the processes involved in acquisition versus extinction conditioning. Further, opponent processing proved critical in accounting for the full range of conditioned inhibition phenomena, and the closely related paradigm of second-order conditioning. Finally, we show how additional separable pathways representing aversive USs, largely mirroring those for appetitive USs, also have important differences from the positive valence case, allowing the model to account for several important phenomena in aversive conditioning. Overall, accounting for all of these phenomena strongly constrains the model, thus providing a well-validated framework for understanding phasic dopamine signaling. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Structural MRI at 7T reveals amygdala nuclei and hippocampal subfield volumetric association with Major Depressive Disorder symptom severity

Subcortical volumetric changes in major depressive disorder (MDD) have been purported to underlie depressive symptomology, however, the evidence to date remains inconsistent. Here, we investigated limbic volumes in MDD, utilizing high-resolution structural images to allow segmentation of the hippocampus and amygdala into their constituent substructures. Twenty-four MDD patients and twenty matched controls underwent structural MRI at 7T field strength. All participants completed the Montgomery-Asberg Depression Rating Scale (MADRS) to quantify depressive symptomology. For the MDD group, volumes of the amygdala right lateral nucleus (p = 0.05, r2 = 0.24), left cortical nucleus (p = 0.032, r2 = 0.35), left accessory basal nucleus (p = 0.04, r2 = 0.28) and bilateral corticoamygdaloid transition area (right hemisphere p = 0.032, r2 = 0.38, left hemisphere p = 0.032, r2 = 0.35) each displayed significant negative associations with MDD severity. The bilateral centrocortical (right hemisphere p = 0.032, r2 = 0.31, left hemisphere p = 0.032, r2 = 0.32) and right basolateral complexes (p = 0.05, r2 = 0.24) also displayed significant negative relationships with depressive symptoms. Using high-field strength MRI, we report the novel finding that MDD severity is consistently negatively associated with amygdala nuclei, linking volumetric reductions with worsening depressive symptoms.

A model of amygdala function following plastic changes at specific synapses during extinction

The synaptic networks in the amygdala have been the subject of intense interest in recent times, primarily because of the role of this structure in emotion. Fear and its extinction depend on the workings of these networks, with particular interest in extinction because of its potential to ameliorate adverse symptoms associated with post-traumatic stress disorder. Here we place emphasis on the extinction networks revealed by recent techniques, and on the probable plasticity properties of their synaptic connections. We use modules of neurons representing each of the principal components identified as involved in extinction. Each of these modules consists of neural networks, containing specific ratios of excitatory and specialized inhibitory neurons as well as synaptic plasticity mechanisms appropriate for the component of the amygdala they represent. While these models can produce dynamic output, here we concentrate on the equilibrium outputs and do not model the details of the plasticity mechanisms. Pavlovian fear conditioning generates a fear memory in the lateral amygdala module that leads to activation of neurons in the basal nucleus fear module but not in the basal nucleus extinction module. Extinction protocols excite infralimbic medial prefrontal cortex neurons (IL) which in turn excite so-called extinction neurons in the amygdala, leading to the release of endocannabinoids from them and an increase in efficacy of synapses formed by lateral amygdala neurons on them. The model simulations show how such a mechanism could explain experimental observations involving the role of IL as well as endocannabinoids in different temporal phases of extinction.

Gamma Oscillations in the Basolateral Amygdala: Biophysical Mechanisms and Computational Consequences

The basolateral nucleus of the amygdala (BL) is thought to support numerous emotional behaviors through specific microcircuits. These are often thought to be comprised of feedforward networks of principal cells (PNs) and interneurons. Neither well-understood nor often considered are recurrent and feedback connections, which likely engender oscillatory dynamics within BL. Indeed, oscillations in the gamma frequency range (40 − 100 Hz) are known to occur in the BL, and yet their origin and effect on local circuits remains unknown. To address this, we constructed a biophysically and anatomically detailed model of the rat BL and its local field potential (LFP) based on the physiological and anatomical literature, along with in vivo and in vitro data we collected on the activities of neurons within the rat BL. Remarkably, the model produced intermittent gamma oscillations (∼50 − 70 Hz) whose properties matched those recorded in vivo, including their entrainment of spiking. BL gamma-band oscillations were generated by the intrinsic circuitry, depending upon reciprocal interactions between PNs and fast-spiking interneurons (FSIs), while connections within these cell types affected the rhythm’s frequency. The model allowed us to conduct experimentally impossible tests to characterize the synaptic and spatial properties of gamma. The entrainment of individual neurons to gamma depended on the number of afferent connections they received, and gamma bursts were spatially restricted in the BL. Importantly, the gamma rhythm synchronized PNs and mediated competition between ensembles. Together, these results indicate that the recurrent connectivity of BL expands its computational and communication repertoire.

Mechanisms of fear learning and extinction: synaptic plasticity-fear memory connection

RATIONALE

The ability to memorize threat-associated cues and subsequently react to them, exhibiting escape or avoidance responses, is an essential, often life-saving behavioral mechanism that can be experimentally studied using the fear (threat) conditioning training paradigm. Presently, there is substantial evidence supporting the Synaptic Plasticity-Memory (SPM) hypothesis in relation to the mechanisms underlying the acquisition, retention, and extinction of conditioned fear memory.

OBJECTIVES

The purpose of this review article is to summarize findings supporting the SPM hypothesis in the context of conditioned fear control, applying the set of criteria and tests which were proposed as necessary to causally link lasting changes in synaptic transmission in corresponding neural circuits to fear memory acquisition and extinction with an emphasis on their pharmacological diversity.

RESULTS

The mechanisms of synaptic plasticity in fear circuits exhibit complex pharmacological profiles and satisfy all four SPM criteria-detectability, anterograde alteration, retrograde alteration, and mimicry.

CONCLUSION

The reviewed findings, accumulated over the last two decades, provide support for both necessity and sufficiency of synaptic plasticity in fear circuits for fear memory acquisition and retention, and, in part, for fear extinction, with the latter requiring additional experimental work.

Maintenance of postsynaptic neuronal excitability by a positive feedback loop of postsynaptic BDNF expression

Experiments have demonstrated that in mice, the PVT strongly projects to the CeL and participates in the formation of fear memories by synaptic potentiation in the amygdala. Herein, we propose a mathematical model based on a positive feedback loop of BDNF expression and signaling to investigate PVT manipulation of synaptic potentiation. The model is validated by comparisons with experimental observations. We find that a high postsynaptic firing frequency after stimulation is induced by presynaptic Ca2+ when the rates of BDNF secretion from PVT and LA neurons to the CeL are above a threshold value. Moreover, the positive feedback of postsynaptic BDNF production is important for the maintenance of the high excitability of the SOM+ CeL neuron after stimulation. The model brings insight into the underlying mechanisms of PVT modulation of synaptic potentiation at LA-CeL synapses and provides a framework of understanding other similar processes associated with synaptic plasticity.

Underlying Mechanisms of Cooperativity, Input Specificity, and Associativity of Long-Term Potentiation Through a Positive Feedback of Local Protein Synthesis

Long-term potentiation (LTP) is a specific form of activity-dependent synaptic plasticity that is a leading mechanism of learning and memory in mammals. The properties of cooperativity, input specificity, and associativity are essential for LTP; however, the underlying mechanisms are unclear. Here, based on experimentally observed phenomena, we introduce a computational model of synaptic plasticity in a pyramidal cell to explore the mechanisms responsible for the cooperativity, input specificity, and associativity of LTP. The model is based on molecular processes involved in synaptic plasticity and integrates gene expression involved in the regulation of neuronal activity. In the model, we introduce a local positive feedback loop of protein synthesis at each synapse, which is essential for bimodal response and synapse specificity. Bifurcation analysis of the local positive feedback loop of brain-derived neurotrophic factor (BDNF) signaling illustrates the existence of bistability, which is the basis of LTP induction. The local bifurcation diagram provides guidance for the realization of LTP, and the projection of whole system trajectories onto the two-parameter bifurcation diagram confirms the predictions obtained from bifurcation analysis. Moreover, model analysis shows that pre- and postsynaptic components are required to achieve the three properties of LTP. This study provides insights into the mechanisms underlying the cooperativity, input specificity, and associativity of LTP, and the further construction of neural networks for learning and memory.

Distribution of type I corticotropin-releasing factor (CRF1) receptors on GABAergic neurons within the basolateral amygdala

The neuropeptide corticotropin-releasing factor (CRF) plays a critical role in mediating anxiety-like responses to stressors, and dysfunction of the CRF system has been linked to the etiology of several psychiatric disorders. Extra-hypothalamic CRF can also modulate learning and memory formation, including amygdala-dependent learning. The basolateral nucleus of the amygdala (BLA) contains dense concentrations of CRF receptors, yet the distribution of these receptors on specific neuronal subtypes within the BLA has not been characterized. Here, we quantified the expression of CRF receptors on three nonoverlapping classes of GABAergic interneurons: those containing the calcium-binding protein parvalbumin (PV), and those expressing the neuropeptides somatostatin (SOM) or cholecystokinin (CCK). While the majority of PV+ neurons and roughly half of CCK+ neurons expressed CRF receptors, they were expressed to a much lesser extent on SOM+ interneurons. Knowledge of the distribution of CRF receptors within the BLA can provide insight into how manipulations of the CRF system modulate fear and anxiety-like behaviors.

Biologically based neural circuit modelling for the study of fear learning and extinction

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.

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 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.

Animals live in environments that contain uncertainty. To adapt to uncertain situations, they flexibly learn to associate environmental cues with rewards and punishments. Understanding how the brain processes uncertainty has remained an important issue in neuroscience. To address this question, we focused on neural processing in the amygdala and mPFC during fear conditioning and extinction. We developed a neural circuit model that incorporates distinct neural populations in the amygdala and mPFC. Our model first successfully reproduced uncertainty-dependent resistance to the extinction of fear memory. An extension of the model provided a possible explanation for observations made during optogenetic manipulation of the ventral mPFC. Finally, we proposed a procedure to accelerate the efficacy of subsequent extinction based on our model.

Synaptic competition in the lateral amygdala and the stimulus specificity of conditioned fear: a biophysical modeling study

Competitive synaptic interactions between principal neurons (PNs) with differing intrinsic excitability were recently shown to determine which dorsal lateral amygdala (LAd) neurons are recruited into a fear memory trace. Here, we explored the contribution of these competitive interactions in determining the stimulus specificity of conditioned fear associations. To this end, we used a realistic biophysical computational model of LAd that included multi-compartment conductance-based models of 800 PNs and 200 interneurons. To reproduce the continuum of spike frequency adaptation displayed by PNs, the model included three subtypes of PNs with high, intermediate, and low spike frequency adaptation. In addition, the model network integrated spatially differentiated patterns of excitatory and inhibitory connections within LA, dopaminergic and noradrenergic inputs, extrinsic thalamic and cortical tone afferents to simulate conditioned stimuli as well as shock inputs for the unconditioned stimulus. Last, glutamatergic synapses in the model could undergo activity-dependent plasticity. Our results suggest that plasticity at both excitatory (PN-PN) and di-synaptic inhibitory (PN-ITN and, particularly, ITN-PN) connections are major determinants of the synaptic competition governing the assignment of PNs to the memory trace. The model also revealed that training-induced potentiation of PN-PN synapses promotes, whereas that of ITN-PN synapses opposes, stimulus generalization. Indeed, suppressing plasticity of PN-PN synapses increased, whereas preventing plasticity of interneuronal synapses decreased the CS specificity of PN recruitment. Overall, our results indicate that the plasticity configuration imprinted in the network by synaptic competition ensures memory specificity. Given that anxiety disorders are characterized by tendency to generalize learned fear to safe stimuli or situations, understanding how plasticity of intrinsic LAd synapses regulates the specificity of learned fear is an important challenge for future experimental studies.

Amygdala volume is reduced in early course schizophrenia

Subcortical structural alterations have been implicated in the neuropathology of schizophrenia. Yet, the extent of anatomical alterations for subcortical structures across illness phases remains unknown. To assess this, magnetic resonance imaging (MRI) was used to examine volume differences of major subcortical structures: thalamus, nucleus accumbens, caudate, putamen, globus pallidus, amygdala and hippocampus. These differences were examined across four groups: (i) healthy comparison subjects (HCS, n=96); (ii) individuals at high risk (HR, n=21) for schizophrenia; (iii) early-course schizophrenia patients (EC-SCZ, n=28); and (iv) chronic schizophrenia patients (C-SCZ, n=20). Raw gray matter volumes and volumetric ratios (volume of specific structure/total gray matter volume) were extracted using automated segmentation tools. EC-SCZ group exhibited smaller bilateral amygdala volumetric ratios, compared to HCS and HR subjects. Findings did not change when corrected for age, level of education and medication use. Amygdala raw volumes did not differ among groups once adjusted for multiple comparisons, but the smaller amygdala volumetric ratio in EC-SCZ survived Bonferroni correction. Other structures were not different across the groups following Bonferroni correction. Smaller amygdala volumes during early illness course may reflect pathophysiologic changes specific to illness development, including disrupted salience processing and acute stress responses.

Mechanisms underlying the formation of the amygdalar fear memory trace: A computational perspective

Recent experimental and modeling studies on the lateral amygdala (LA) have implicated intrinsic excitability and competitive synaptic interactions among principal neurons (PNs) in the formation of auditory fear memories. The present modeling studies, conducted over an expanded range of intrinsic excitability in the network, revealed that only excitable PNs that received tone inputs participate in the competition. Strikingly, the number of model PNs integrated into the fear memory trace remained constant despite the much larger range considered, and model runs highlighted several conditioning-induced tone responsive characteristics of the various PN populations. Furthermore, these studies showed that although excitation was important, disynaptic inhibition among PNs is the dominant mechanism that keeps the number of plastic PNs stable despite large variations in the network's excitability. Finally, we found that the overall level of inhibition in the model network determines the number of projection cells integrated into the fear memory trace.

The Posterodorsal Medial Amygdala Regulates the Timing of Puberty Onset in Female Rats

Obesity is the major risk factor for early puberty, but emerging evidence indicates other factors including psychosocial stress. One key brain region notable for its role in controlling calorie intake, stress, and behavior is the amygdala. Early studies involving amygdala lesions that included the medial nucleus advanced puberty in rats. More recently it was shown that a critical site for lesion-induced hyperphagia and obesity is the posterodorsal subnucleus of the medial amygdala (MePD), which may explain the advancement of puberty. Glutamatergic activity also increases in the MePD during puberty without a corresponding γ-aminobutyric acid (GABA)ergic change, suggesting an overall activation of this brain region. In the present study, we report that neurotoxic lesioning of the MePD advances puberty and increases weight gain in female rats fed a normal diet. However, MePD lesioned rats fed a 25% nonnutritive bulk diet also showed the dramatic advancement of puberty but without the increase in body weight. In both dietary groups, MePD lesions resulted in an increase in socialization and a decrease in play fighting behavior. Chronic GABAA receptor antagonism in the MePD from postnatal day 21 for 14 days also advanced puberty, increased socialization, and decreased play fighting without altering body weight, whereas glutamate receptor antagonism delayed puberty and decreased socialization without affecting play fighting. In conclusion, our results suggest the MePD regulates the timing of puberty via a novel mechanism independent of change in body weight and caloric intake. MePD glutamatergic systems advance the timing of puberty whereas local GABAergic activation results in a delay.

Out with the old and in with the new: Synaptic mechanisms of extinction in the amygdala

Considerable research indicates that long-term synaptic plasticity in the amygdala underlies the acquisition of emotional memories, including those learned during Pavlovian fear conditioning. Much less is known about the synaptic mechanisms involved in other forms of associative learning, including extinction, that update fear memories. Extinction learning might reverse conditioning-related changes (e.g., depotentiation) or induce plasticity at inhibitory synapses (e.g., long-term potentiation) to suppress conditioned fear responses. Either mechanism must account for fear recovery phenomena after extinction, as well as savings of extinction after fear recovery. This article is part of a Special Issue entitled SI: Brain and Memory.

A multi-pathway hypothesis for human visual fear signaling

A hypothesis is proposed for five visual fear signaling pathways in humans, based on an analysis of anatomical connectivity from primate studies and human functional connectvity and tractography from brain imaging studies. Earlier work has identified possible subcortical and cortical fear pathways known as the "low road" and "high road," which arrive at the amygdala independently. In addition to a subcortical pathway, we propose four cortical signaling pathways in humans along the visual ventral stream. All four of these traverse through the LGN to the visual cortex (VC) and branching off at the inferior temporal area, with one projection directly to the amygdala; another traversing the orbitofrontal cortex; and two others passing through the parietal and then prefrontal cortex, one excitatory pathway via the ventral-medial area and one regulatory pathway via the ventral-lateral area. These pathways have progressively longer propagation latencies and may have progressively evolved with brain development to take advantage of higher-level processing. Using the anatomical path lengths and latency estimates for each of these five pathways, predictions are made for the relative processing times at selective ROIs and arrival at the amygdala, based on the presentation of a fear-relevant visual stimulus. Partial verification of the temporal dynamics of this hypothesis might be accomplished using experimental MEG analysis. Possible experimental protocols are suggested.

From neural to genetic substrates of panic disorder: Insights from human and mouse studies

Fear is an ancestral emotion, an intrinsic defensive response present in every organism. Although fear is an evolutionarily advantageous emotion, under certain pathologies such as panic disorder it might become exaggerated and non-adaptive. Clinical and preclinical work pinpoints that changes in cognitive processes, such as perception and interpretation of environmental stimuli that rely on brain regions responsible for high-level function, are essential for the development of fear-related disorders. This review focuses on the involvement of cognitive function to fear circuitry disorders. Moreover, we address how animal models are contributing to understand the involvement of human candidate genes to pathological fear and helping achieve progress in this field. Multidisciplinary approaches that integrate human genetic findings with state of the art genetic mouse models will allow to elucidate the mechanisms underlying pathology and to develop new strategies for therapeutic targeting.

A pavlovian model of the amygdala and its influence within the medial temporal lobe

Recent advances in neuroscience give us a better view of the inner structure of the amygdala, of its relations with other regions in the Medial Temporal Lobe (MTL) and of the prominent role of neuromodulation. They have particularly shed light on two kinds of neurons in the basal nucleus of the amygdala, the so-called fear neurons and extinction neurons. Fear neurons mediate context-dependent fear by receiving contextual information from the hippocampus, whereas extinction neurons are linked with the medial prefrontal cortex (mPFC) and involved in fear extinction. The computational model of the amygdala that we describe in this paper is primarily a model of pavlovian conditioning, but its architecture also emphasizes the central role of the amygdala in the MTL memory processes through three main information flows. (i) Thalamic and higher order sensory cortical inputs including from the perirhinal cortex are received in the lateral amygdalar nucleus, where CS-US associations can be acquired. (ii) These associations are subsequently modulated, in the basal nucleus of the amygdala, by contextual inputs coming from the hippocampus and the mPFC. Basal fear and extinction neurons indicate the currently valid association to their main targets including in the MTL and the mPFC. (iii) The competition for the choice of the pavlovian response is ultimately performed by projection of these amygdalar neurons in the central nucleus of the amygdala where, beyond motor responding, a hormonal response, including cholinergic modulation, is also triggered via the basal forebrain. In turn, acetylcholine modulates activation in the basal nucleus and facilitates learning in the hippocampus. Based on biologically founded arguments, our model replicates a number of biological experiments, proposes some predictions about the role of amygdalar regions and describes pavlovian conditioning as a distributed systemic learning, binding memory processes in the MTL.

Systems biology approach to understanding post-traumatic stress disorder

This review paper presents known biological facts about PTSD and the mathematical/systems biology tools used to understand the underpinning molecular principles.

Long-term behavioral programming induced by peripuberty stress in rats is accompanied by GABAergic-related alterations in the Amygdala

Stress during childhood and adolescence is a risk factor for psychopathology. Alterations in γ-aminobutyric acid (GABA), the main inhibitory neurotransmitter in the brain, have been found following stress exposure and fear experiences and are often implicated in anxiety and mood disorders. Abnormal amygdala functioning has also been detected following stress exposure and is also implicated in anxiety and social disorders. However, the amygdala is not a unitary structure; it includes several nuclei with different functions and little is known on the potential differences the impact of early life stress may have on this system within different amygdaloid nuclei. We aimed here to evaluate potential regional differences in the expression of GABAergic-related markers across several amygdaloid nuclei in adult rats subjected to a peripuberty stress protocol that leads to enhanced basal amygdala activity and psychopathological behaviors. More specifically, we investigated the protein expression levels of glutamic acid decarboxylase (GAD; the principal synthesizing enzyme of GABA) and of GABA-A receptor subunits α2 and α3. We found reduced GAD and GABA-A α3, but not α2, subunit protein levels throughout all the amygdala nuclei examined (lateral, basolateral, basomedial, medial and central) and increased anxiety-like behaviors and reduced sociability in peripubertally stressed animals. Our results identify an enduring inhibition of the GABAergic system across the amygdala following exposure to early adversity. They also highlight the suitability of the peripuberty stress model to investigate the link between treatments targeting the dysfunctional GABAergic system in specific amygdala nuclei and recovery of specific stress-induced behavioral dysfunctions.

Assignment of model amygdala neurons to the fear memory trace depends on competitive synaptic interactions

We used biophysical modeling to examine a fundamental, yet unresolved, question regarding how particular lateral amygdala (LA) neurons are assigned to fear memory traces. This revealed that neurons with high intrinsic excitability are more likely to be integrated into the memory trace, but that competitive synaptic interactions also play a critical role. Indeed, when the ratio of intrinsically excitable cells was increased or decreased, the number of plastic cells remained relatively constant. Analysis of the connectivity of plastic and nonplastic cells revealed that subsets of principal LA neurons effectively band together by virtue of their excitatory interconnections to suppress plasticity in other principal cells via the recruitment of inhibitory interneurons.

Fear signaling in the prelimbic-amygdala circuit: a computational modeling and recording study

The acquisition and expression of conditioned fear depends on prefrontal-amygdala circuits. Auditory fear conditioning increases the tone responses of lateral amygdala 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 lateral amygdala 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 microcircuits in the PL-BL interconnection can have a significant impact on the expression of fear, possibly explaining individual variability in fear responses. The human homolog of PL could thus be an effective target for anxiety disorders.

Mechanisms contributing to the induction and storage of Pavlovian fear memories in the lateral amygdala

The relative contributions of plasticity in the amygdala vs. its afferent pathways to conditioned fear remain controversial. Some believe that thalamic and cortical neurons transmitting information about the conditioned stimulus (CS) to the lateral amygdala (LA) serve a relay function. Others maintain that thalamic and/or cortical plasticity is critically involved in fear conditioning. To address this question, we developed a large-scale biophysical model of the LA that could reproduce earlier findings regarding the cellular correlates of fear conditioning in LA. We then conducted model experiments that examined whether fear memories depend on (1) training-induced increases in the responsiveness of thalamic and cortical neurons projecting to LA, (2) plasticity at the synapses they form in LA, and/or (3) plasticity at synapses between LA neurons. These tests revealed that training-induced increases in the responsiveness of afferent neurons are required for fear memory formation. However, once the memory has been formed, this factor is no longer required because the efficacy of the synapses that thalamic and cortical neurons form with LA cells has augmented enough to maintain the memory. In contrast, our model experiments suggest that plasticity at synapses between LA neurons plays a minor role in maintaining the fear memory.

A role for maternal physiological state in preserving auditory cortical plasticity for salient infant calls

A growing interest in sensory system plasticity in the natural context of motherhood has created the need to investigate how intrinsic physiological state (e.g., hormonal, motivational, etc.) interacts with sensory experience to drive adaptive cortical plasticity for behaviorally relevant stimuli. Using a maternal mouse model of auditory cortical inhibitory plasticity for ultrasonic pup calls, we examined the role of pup care versus maternal physiological state in the long-term retention of this plasticity. Very recent experience caring for pups by Early Cocarers, which are virgins, produced stronger call-evoked lateral-band inhibition in auditory cortex. However, this plasticity was absent when measured post-weaning in Cocarers, even though it was present at the same time point in Mothers, whose pup experience occurred under a maternal physiological state. A two-alternative choice phonotaxis task revealed that the same animal groups (Early Cocarers and Mothers) demonstrating stronger lateral-band inhibition also preferred pup calls over a neutral sound, a correlation consistent with the hypothesis that this inhibitory mechanism may play a mnemonic role and is engaged to process sounds that are particularly salient. Our electrophysiological data hint at a possible mechanism through which the maternal physiological state may act to preserve the cortical plasticity: selectively suppressing detrimental spontaneous activity in neurons that are responsive to calls, an effect observed only in Mothers. Taken together, the maternal physiological state during the care of pups may help maintain the memory trace of behaviorally salient infant cues within core auditory cortex, potentially ensuring a more rapid induction of future maternal behavior.

Inhibition of the PI3 kinase cascade in corticolimbic circuit: temporal and differential effects on contextual fear and extinction

We studied the role of PI3K cascade in the basolateral amygdala (BLA) and the infralimbic region of the medial prefrontal cortex (IL-mPFC), in contextual fear learning and extinction in the rat. To that end, we micro-infused the phosphoinositide-3-kinase (PIK3) inhibitor LY294002 into either the mPFC or the BLA. Infusion of LY294002 into the BLA following fear conditioning was associated with enhanced freezing levels and impaired extinction in the subsequent sessions. Similarly, inhibition of PI3K in the BLA before the retrieval of fear memory was associated with impaired retrieval of the fear memory, which was expressed as reduced freezing levels that persisted over 2 d. In the IL-mPFC, only consolidation of fear extinction was impaired: micro-infusion of PI3K inhibitor following the retrieval of fear was associated with impaired extinction on the following days. These results indicate differences in the temporal parameters of the effects of PI3K inhibition in the IL-mPFC and in the BLA, which suggest differential involvement of these structures in long-term fear and in extinction of fear memory. Our findings provide additional evidence for the critical roles played by PI3K in intact formation of fear memory and in its extinction and add new evidence for a role of PI3K in consolidation of memory of extinction. Better understanding of the differential involvement of the PI3K cascade during acquisition and extinction of fear conditioning in the mPFC-amygdala circuit could potentially contribute to the understanding and treatment of anxiety disorders.

Role of sensory input distribution and intrinsic connectivity in lateral amygdala during auditory fear conditioning: a computational study

We propose a novel reduced-order neuronal network modeling framework that includes an enhanced firing rate model and a corresponding synaptic calcium-based synaptic learning rule. Specifically, we propose enhancements to the Wilson-Cowan firing-rate neuron model that permit full spike-frequency adaptation seen in biological lateral amygdala (LA) neurons, while being sufficiently general to accommodate other spike-frequency patterns. We also report a technique to incorporate calcium-dependent plasticity in the synapses of the network using a regression scheme to link firing rate to postsynaptic calcium. Together, the single-cell model and the synaptic learning scheme constitute a general framework to develop computationally efficient neuronal networks that employ biologically realistic synaptic learning. The reduced-order modeling framework was validated using a previously reported biophysical conductance-based neuronal network model of a rodent LA that modeled features of Pavlovian conditioning and extinction of auditory fear (Li et al., 2009). The framework was then used to develop a larger LA network model to investigate the roles of tone and shock distributions and of intrinsic connectivity in auditory fear learning. The model suggested combinations of tone and shock densities that would provide experimental estimates of tone responsive and conditioned cell proportions. Furthermore, it provided several insights including how intrinsic connectivity might help distribute sensory inputs to produce conditioned responses in cells that do not directly receive both tone and shock inputs, and how a balance between potentiation of excitation and inhibition prevents stimulus generalization during fear learning.

C57 mice increase wheel-running behavior following stress: preliminary findings

Exercise has been shown to reduce anxiety in both humans and animals. To date, there are few, if any studies that examine the effect of stress on self-selected exercise using an animal model. This study examined the effect of acute stress on wheel-running distance in mice. Forty 8-week-old, male C57BL/6J mice were randomly assigned to one of three groups: no stress + wheel-running experience, stress + wheel-running experience, or stress with no wheel-running experience. Stressed mice were exposed to foot shock in a brightly lit environment. Following treatment, wheel-running distances were observed for three hours. Stress significantly increased voluntary wheel-running in mice with wheel-running experience as compared to nonstressed controls and stressed mice with no wheel-running experience. These results suggest that mice familiar with wheel-running may self-select this exercise as a modality for the mitigation of accumulated anxiety.

Social anxiety modulates amygdala activation during social conditioning

Aversive social learning experiences might play a significant role in the aetiology of social anxiety disorder. Therefore, we investigated emotional learning and unlearning processes in healthy humans using a social conditioning paradigm. Forty-nine healthy subjects participated in a 2-day fMRI differential conditioning protocol. Acquisition and extinction were conducted on Day 1 and extinction recall on Day 2. BOLD responses, ratings and skin conductance responses were collected. Our data indicate successful conditioning and extinction on the neural and subjective level. As a main result, we observed a positive correlation of social anxiety and conditioning responses on the subjective level (valence and fear) as well as on the neural level with significant CS(+)/CS(-) differentiation in the left amygdala and the left hippocampus. Further, significant CS(+)/CS(-) differentiation in the left amygdala was found during extinction and was associated with lower scores in social anxiety. During extinction recall, we found a tendentially negative correlation of social anxiety and CS(+)/CS(-) differentiation in the vmPFC. In sum, we were able to show that social anxiety is related to conditionability with socially threatening stimuli. This could point to an important aspect in the aetiology of social anxiety disorder.

Periaqueductal gray c-Fos expression varies relative to the method of conditioned taste aversion extinction employed

A conditioned taste aversion (CTA) is acquired when an animal consumes a novel taste (CS) and then experiences the symptoms of poisoning (US). Following CTA training, animals will avoid the taste that was previously associated with malaise. This defensive reaction to a learned fear can be extinguished by repeated exposure to the CS alone (CS-only; CSO-EXT). However, following a latency period in which the CS is not presented, the CTA will spontaneously recover (SR). Through the use of an explicitly unpaired extinction procedure (EU-EXT) we have shown that we can speed up extinction and attenuate SR of the CTA. Here we compared and contrasted the ability of CSO and EU extinction procedures to affect c-Fos expression in the periaqueductal gray (PAG). Fluid-deprived Sprague-Dawley rats acquired a strong CTA [via 3 pairings of 0.3% oral saccharin (SAC; the CS) and 81mg/kg i.p. lithium chloride (LiCl; the US)] followed by extinction trials consisting of multiple exposures to either, (a) the CS every-other day (CSO-EXT), or (b) CS and US on alternate days (EU-EXT). A different group of rats did not receive multiple CS exposures and served as a "no extinction" (NE) control. Both extinction procedures resulted in ≥90% reacceptance of SAC (achieving asymptotic extinction). Some of the animals were sacrificed for c-Fos immunohistochemical analysis following asymptotic extinction. Other rats entered a 30-day latency period where they drank water only. These remaining animals were then tested for SR with a final exposure to SAC before being sacrificed for c-Fos immunohistochemistry. As reported previously, rats in the CS-only group exhibited a significant SR of the CTA. However, animals in the EU extinction group reached asymptotic extinction more rapidly than did CSO rats and they did not show SR of the CTA. As compared to rats that retained their CTA, both groups of extinguished rats showed suppression in the number of c-Fos-labeled neurons in all 4 longitudinal columns of the PAG. The number of c-Fos-labeled cells in the PAG was generally low but there was a reliable increase in c-Fos expression in dorsolateral PAG (dlPAG) following the SR test in the brains of rats that went through the EU-EXT procedure as compared with those that either went through the more-traditional CSO extinction procedure or experienced no extinction at all. The number of c-Fos-labeled neurons in the dlPAG was significantly correlated with the amount of SAC consumed at the SR test. Surprisingly, the brains of EU-extinguished rats and CSO extinguished rats did not differ in the number of c-Fos-labeled neurons in gustatory neocortex, medial prefrontal cortex, basolateral amygdala, or the central nucleus of the amygdala. Thus, behavioral differences in SR between the EU and CSO extinction animals were not represented by corresponding changes in the neural activity of several brain nuclei classically associated with extinction learning. However a detailed analysis of PAG c-Fos expression provided hints about some of the physiological changes evoked by these 2 extinction paradigms that produce very different behavioral outcomes. The findings are clinically relevant as we seek the development of treatments for deficits in fear extinction (e.g. PTSD, phobias).

Postsynaptic BDNF signalling regulates long-term potentiation at thalamo-amygdala afferents

The neurotrophin brain-derived neurotrophic factor (BDNF) is known to regulate synaptic plasticity and memory formation in the hippocampus and the neocortex of the mammalian brain. In contrast, a role of BDNF in mediating synaptic plasticity and fear learning in the amygdala is just beginning to evolve. Using patch clamp recordings from projection neurons of the dorsal lateral amygdala (LA) in acute slices of mice, we now investigated the cellular mechanism of BDNF-mediated long-term potentiation (LTP) of excitatory postsynaptic currents (EPSCs) in the amygdala. LTP was elicited in cortical and thalamic synaptic inputs by pairing postsynaptic depolarisation with presynaptic stimulation. LTP in the cortico-amygdala pathway was not changed in heterozygous BDNF-knockout (BDNF(+/-)) mice. In contrast, pairing induced LTP in the thalamic input was abolished in BDNF(+/-) mice (BDNF(+/-): 104.0 ± 5.7% of initial EPSC values; WT: 132.5 ± 7.3%). Likewise, inhibition of BDNF/TrkB signalling with TrkB-IgGs as scavenger molecules for endogenous BDNF blocked LTP in wild-type mice in this pathway (TrkB-IgG: 102.7 ± 6.9% of initial EPSC values; control: 132.5 ± 8.7%). Inclusion of the tyrosine kinase inhibitor K252a in the pipette solution also prevented the induction of LTP in the thalamic pathway, indicating a postsynaptic site of action of BDNF in regulating LTP. Reduced BDNF levels in BDNF(+/-) mice did not affect intrinsic membrane properties of LA projection neurons. Likewise, presynaptic glutamate release, and postsynaptic membrane properties also remained unaffected in BDNF(+/-) mice. These data suggest a postsynaptic site of action of BDNF in mediating LTP selectively in the thalamic fear conditioning pathway.

Dissociations between medial prefrontal cortical subregions in the modulation of learning and action

The medial prefrontal cortex (mPFC) has been implicated in various attentional functions. This experiment examined the involvement of mPFC subregions in the allocation of attention in learning and action as a function of the predictive accuracy of cues. Rats with dorsal (encompassing anterior cingulate, prelimbic, and infralimbic cortices) or ventral (encompassing mainly infralimbic and dorsopeduncular cortices and tenia tecta) mPFC lesions were trained in a multiple-choice discrimination task in which operant nosepoke responses to some visual cues were consistently (100%) reinforced (CRF) with food, whereas responses to other visual cues were partially (50%) reinforced (PRF). In challenge tests designed to assess attention in the control of action, responding was directed more to CRF cues than to PRF cues in sham and dorsal mPFC-lesioned rats, but ventral mPFC-lesioned rats showed similar levels of responding to both CRF and PRF cues. Nevertheless, when given a choice between simultaneously presented CRF and PRF cues in a cue competition test, all groups responded more to CRF cues. In a subsequent Pavlovian overshadowing phase designed to assess attention in the acquisition of new learning, previously trained CRF cues overshadowed conditioning to novel auditory cues more than did PRF cues in dorsal mPFC-lesioned rats, whereas the opposite pattern was observed in sham and ventral mPFC-lesioned rats. These results suggest a dissociation within the mPFC in the use of reinforcement prediction information to allocate attention for new learning and for the control of action.

Design of a neurally plausible model of fear learning

A neurally oriented conceptual and computational model of fear conditioning manifested by freezing behavior (FRAT), which accounts for many aspects of delay and context conditioning, has been constructed. Conditioning and extinction are the result of neuromodulation-controlled LTP at synapses of thalamic, cortical, and hippocampal afferents on principal cells and inhibitory interneurons of lateral and basal amygdala. The phenomena accounted for by the model (and simulated by the computational version) include conditioning, secondary reinforcement, blocking, the immediate shock deficit, extinction, renewal, and a range of empirically valid effects of pre- and post-training ablation or inactivation of hippocampus or amygdala nuclei.

Stochastic amplification of calcium-activated potassium currents in Ca2+ microdomains

Small conductance (SK) calcium-activated potassium channels are found in many tissues throughout the body and open in response to elevations in intracellular calcium. In hippocampal neurons, SK channels are spatially co-localized with L-Type calcium channels. Due to the restriction of calcium transients into microdomains, only a limited number of L-Type Ca(2+) channels can activate SK and, thus, stochastic gating becomes relevant. Using a stochastic model with calcium microdomains, we predict that intracellular Ca(2+) fluctuations resulting from Ca(2+) channel gating can increase SK2 subthreshold activity by 1-2 orders of magnitude. This effectively reduces the value of the Hill coefficient. To explain the underlying mechanism, we show how short, high-amplitude calcium pulses associated with stochastic gating of calcium channels are much more effective at activating SK2 channels than the steady calcium signal produced by a deterministic simulation. This stochastic amplification results from two factors: first, a supralinear rise in the SK2 channel's steady-state activation curve at low calcium levels and, second, a momentary reduction in the channel's time constant during the calcium pulse, causing the channel to approach its steady-state activation value much faster than it decays. Stochastic amplification can potentially explain subthreshold SK2 activation in unified models of both sub- and suprathreshold regimes. Furthermore, we expect it to be a general phenomenon relevant to many proteins that are activated nonlinearly by stochastic ligand release.

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

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.

Context-dependent encoding of fear and extinction memories in a large-scale network model of the basal amygdala

The basal nucleus of the amygdala (BA) is involved in the formation of context-dependent conditioned fear and extinction memories. To understand the underlying neural mechanisms we developed a large-scale neuron network model of the BA, composed of excitatory and inhibitory leaky-integrate-and-fire neurons. Excitatory BA neurons received conditioned stimulus (CS)-related input from the adjacent lateral nucleus (LA) and contextual input from the hippocampus or medial prefrontal cortex (mPFC). We implemented a plasticity mechanism according to which CS and contextual synapses were potentiated if CS and contextual inputs temporally coincided on the afferents of the excitatory neurons. Our simulations revealed a differential recruitment of two distinct subpopulations of BA neurons during conditioning and extinction, mimicking the activation of experimentally observed cell populations. We propose that these two subgroups encode contextual specificity of fear and extinction memories, respectively. Mutual competition between them, mediated by feedback inhibition and driven by contextual inputs, regulates the activity in the central amygdala (CEA) thereby controlling amygdala output and fear behavior. The model makes multiple testable predictions that may advance our understanding of fear and extinction memories.

The amygdaloid complex is one of the key brain structures involved in fear-related processes. A typical way to study neural correlates of fear expression (e.g. freezing response) in the amygdala is to perform a fear conditioning paradigm, which yields a conditioned fear response. This response can be reversed by another procedure called fear extinction. Thanks to the experimental approaches to date we have some understanding about the putative roles of specific subnuclei within the amygdala in the formation of these fear and extinction memories. Here, we complement the experimental studies by providing a computational model that addresses the question of how fear and extinction memories are encoded in the amygdala, and specifically, in the basal nucleus (BA). We propose a specific neural mechanism to explain how the BA may integrate information about a salient, conditioned stimulus and the environment, thereby enabling it to switch the state of the animal from low to high fear and vice versa. We also provide possible explanations for various other behavioral findings, such as the recovery of fear after it had been extinguished (renewal). Finally, we make specific, experimentally testable predictions that need to be addressed in future work.