Christopher K. Cain

Brain mechanisms of fear extinction: historical perspectives on the contribution of prefrontal cortex.

What brain regions are involved in regulating behavior when the emotional consequence of a stimulus changes from harmful to harmless? One way to address this question is to study the neural mechanisms underlying extinction of Pavlovian fear conditioning, an important form of emotional regulation that has direct relevance to the treatment of human fear and anxiety disorders. In fear extinction, the capacity of a conditioned stimulus to elicit fear is gradually reduced by repeatedly presenting it in the absence of any aversive consequence. In recent years there has been a dramatic increase in research on the brain mechanisms of fear extinction. One region that has received considerable attention as a component of the brains extinction circuitry is the medial prefrontal cortex (mPFC). In the present article, we review the historical foundations of the modern notion that the mPFC plays a critical role in emotional regulation, a literature that was largely responsible for studies that explored the role of the mPFC in fear extinction. We also consider the role of the mPFC in a broader neural circuit for extinction that includes the amygdala and hippocampus.

Long-term potentiation in the amygdala: a cellular mechanism of fear learning and memory.

Much of the research on long-term potentiation (LTP) is motivated by the question of whether changes in synaptic strength similar to LTP underlie learning and memory. Here we discuss findings from studies on fear conditioning, a form of associative learning whose neural circuitry is relatively well understood, that may be particularly suited for addressing this question. We first review the evidence suggesting that fear conditioning is mediated by changes in synaptic strength at sensory inputs to the lateral nucleus of the amygdala. We then discuss several outstanding questions that will be important for future research on the role of synaptic plasticity in fear learning. The results gained from these studies may shed light not only on fear conditioning, but may also help unravel more general cellular mechanisms of learning and memory.

Therapeutic Utility of Non-Peptidic CRF1 Receptor Antagonists in Anxiety, Depression, and Stress-Related Disorders: Evidence from Animal Models

Adaptive responding to threatening stressors is of fundamental importance for survival. Dysfunctional hyperactivation of corticotropin releasing factor type-1 (CRF(1)) receptors in stress response system pathways is linked to stress-related psychopathology and CRF(1) receptor antagonists (CRAs) have been proposed as novel therapeutic agents. CRA effects in diverse animal models of stress that detect anxiolytics and/or antidepressants are reviewed, with the goal of evaluating their potential therapeutic utility in depression, anxiety, and other stress-related disorders. CRAs have a distinct phenotype in animals that has similarities to, and differences from, those of classic antidepressants and anxiolytics. CRAs are generally behaviorally silent, indicating that CRF(1) receptors are normally in a state of low basal activation. CRAs reduce stressor-induced HPA axis activation by blocking pituitary and possibly brain CRF(1) receptors which may ameliorate chronic stress-induced pathology. In animal models sensitive to anxiolytics and/or antidepressants, CRAs are generally more active in those with high stress levels, conditions which may maximize CRF(1) receptor hyperactivation. Clinically, CRAs have demonstrated good tolerability and safety, but have thus far lacked compelling efficacy in major depressive disorder, generalized anxiety disorder, or irritable bowel syndrome. CRAs may be best suited for disorders in which stressors clearly contribute to the underlying pathology (e.g. posttraumatic stress disorder, early life trauma, withdrawal/abstinence from addictive substances), though much work is needed to explore these possibilities. An evolving literature exploring the genetic, developmental and environmental factors linking CRF(1) receptor dysfunction to stress-related psychopathology is discussed in the context of improving the translational value of current animal models.

Sidman Instrumental Avoidance Initially Depends on Lateral and Basal Amygdala and Is Constrained by Central Amygdala-Mediated Pavlovian Processes

BACKGROUND The lateral (LA) and central (CE), but not basal (B), amygdala nuclei are necessary for reactive Pavlovian fear responses such as freezing. The amygdala also plays a key role in the acquisition and expression of active instrumental defensive behaviors, but little is known about the specific roles of amygdala nuclei. Using a Sidman active avoidance (AA) task, we examined the necessity of LA, B, and CE for learning and performance. Pavlovian freezing was simultaneously assessed to examine the contributions of amygdala nuclei to the transition from reactive to active defensive responding. METHODS Rats received electrolytic lesions of LA, CE, or B before AA training, or following overtraining. Rats that expressed low levels of AA performance during training received bilateral electrolytic lesions to CE to eliminate competing freezing reactions and rescue AA. AA performance and freezing were assessed. RESULTS Damage to LA and B, but not CE, impaired the acquisition of AA. Performance of AA became amygdala-independent following overtraining. CE lesions abolished Pavlovian freezing and rescued instrumental AA performance in rats that expressed low levels of avoidance responses and high levels of freezing during training. CONCLUSIONS Although the acquisition of Pavlovian fear depends on LA and CE, but not B, acquisition of instrumental AA is dependent on LA and B, but not CE. CE-dependent Pavlovian processes that control freezing can constrain avoidance behavior. Performance of well-trained AA becomes independent of all three amygdala nuclei. Thus, it appears that different output pathways of LA mediate reactive and active conditioned defensive responding.

Endogenous GluR1-containing AMPA receptors translocate to asymmetric synapses in the lateral amygdala during the early phase of fear memory formation: an electron microscopic immunocytochemical study.

Although glutamate receptor 1 (GluR1)‐containing α‐amino‐3‐hydroxyl‐5‐methyl‐4‐isoxazole‐propionate receptors (GluR1‐AMPARs) are implicated in synaptic plasticity, it has yet to be demonstrated whether endogenous GluR1‐AMPARs undergo activity‐dependent trafficking in vivo to synapses to support short‐term memory (STM) formation. The paradigm of pavlovian fear conditioning (FC) can be used to address this question, because a discrete region—the lateral amygdala (LA)—has been shown unambiguously to be necessary for the formation of the associative memory between a neutral stimulus (tone [CS]) and a noxious stimulus (foot shock [US]). Acquisition of STM for FC can occur even in the presence of protein synthesis inhibitors, indicating that redistribution of pre‐existing molecules to synaptic junctions underlies STM. We employed electron microscopic immunocytochemistry to evaluate alterations in the distribution of endogenous AMPAR subunits at LA synapses during the STM phase of FC. Rats were sacrificed 40 minutes following three CS‐US pairings. In the LA of paired animals, relative to naïve animals, the proportion of GluR1‐AMPAR‐labeled synapses increased 99% at spines and 167% in shafts. In the LA of unpaired rats, for which the CS was never associated with the US, GluR1 immunoreactivity decreased 84% at excitatory shaft synapses. GluR2/3 immunoreactivity at excitatory synapses did not change detectably following paired or unpaired conditioning. Thus, the early phase of FC involves rapid redistribution specifically of the GluR1‐AMPARs to the postsynaptic membranes in the LA, together with the rapid translocation of GluR1‐AMPARs from remote sites into the spine head cytoplasm, yielding behavior changes that are specific to stimulus contingencies. J. Comp. Neurol. 518:4723–4739, 2010.

Chapter 3.1 Brain mechanisms of Pavlovian and instrumental aversive conditioning

Abstract Fear learning can be broadly divided into two categories: the acquisition of fear reactions, modeled by Pavlovian conditioning, and the acquisition of fear actions, modeled by instrumental avoidance/escape conditioning. Brain research on Pavlovian conditioning has been especially successful at delineating the cellular and molecular mechanisms of fear-reaction learning. Instrumental conditioning research is beginning to shed light on fear-action learning at the brain systems level. In the present chapter we review recent advances in both fields and suggest that the Escape from Fear (EFF) paradigm is an excellent model for studying how these two types of learning interact to subserve fear behavior. The mechanisms of such learning may be related to passive versus active coping strategies in humans suffering from pathological fear and understanding these mechanisms may have important treatment implications.

A robust automated method to analyze rodent motion during fear conditioning

A central question in the study of LTP has been to determine what role it plays in memory formation and storage. One valuable form of learning for addressing this issue is associative fear conditioning. In this paradigm an animal learns to associate a tone and shock, such that subsequent presentation of a tone evokes a fear response (freezing behavior). Recent studies indicate that overlapping cellular processes underlie fear conditioning and LTP. The fear response has generally been scored manually which is both labor-intensive and subject to potential artifacts such as inconsistent or biased results. Here we describe a simple automated method that provides unbiased and rapid analysis of animal motion. We show that measured motion, in units termed significant motion pixels (SMPs), is both linear and robust over a wide range of animal speeds and detection thresholds and scores freezing in a quantitatively similar manner to trained human observers. By comparing the frequency distribution of motion during baseline periods and to the response to fox urine (which causes unconditioned fear), we suggest that freezing and non-freezing are distinct behaviors. Finally, we show how this algorithm can be applied to a fear conditioning paradigm yielding information on long and short-term associative memory as well as habituation. This automated analysis of fear conditioning will permit a more rapid and accurate assessment of the role of LTP in memory.

Asymmetries in long-term and short-term plasticity at thalamic and cortical inputs to the amygdala in vivo

Converging lines of evidence suggest that synaptic plasticity at auditory inputs to the lateral amygdala (LA) is critical for the formation and storage of auditory fear memories. Auditory information reaches the LA from both thalamic and cortical areas, raising the question of whether they make distinct contributions to fear memory storage. Here we address this by comparing the induction of long‐term potentation (LTP) at the two inputs in vivo in anesthetized rats. We first show, using field potential measurements, that different patterns and frequencies of high‐frequency stimulation (HFS) consistently elicit stronger LTP at cortical inputs than at thalamic inputs. Field potential responses elicited during HFS of thalamic inputs were also smaller than responses during HFS of cortical inputs, suggesting less effective postsynaptic depolarization. Pronounced differences in the short‐term plasticity profiles of the two inputs were also observed: whereas cortical inputs displayed paired‐pulse facilitation, thalamic inputs displayed paired‐pulse depression. These differences in short‐ and long‐term plasticity were not due to stronger inhibition at thalamic inputs: although removal of inhibition enhanced responses to HFS, it did not enhance thalamic LTP and left paired‐pulse depression unaffected. These results highlight the divergent nature of short‐ and long‐term plasticity at thalamic and cortical sensory inputs to the LA, pointing to their different roles in the fear learning system.