Neural oscillations in the infralimbic cortex after electrical stimulation of the amygdala. Relevance to acute stress processing

Abstract

The stress system coordinates the adaptive reactions of the organism to stressors. Therefore, dysfunctions in this circuit may correlate to anxiety-related disorders, including depression. Comprehending the dynamics of this network may lead to a better understanding of the mechanisms that underlie these diseases. The central nucleus of the amygdala (CeA) activates the hypothalamic-pituitary-adrenal axis and brainstem nodes by triggering endocrine, autonomic and behavioral stress responses. The medial prefrontal cortex plays a significant role in regulating reactions to stressors, and is specifically important for limiting fear responses. Brain oscillations reflect neural systems activity. Synchronous neuronal assemblies facilitate communication and synaptic plasticity, mechanisms that cooperatively support the temporal representation and long-term consolidation of information. The purpose of this article was to delve into the interactions between these structures in stress contexts by evaluating changes in oscillatory activity. We particularly analyzed the local field potential in the infralimbic region of the medial prefrontal cortex (IL) in urethane-anesthetized rats after the electrical activation of the central nucleus of the amygdala by mimicking firing rates induced by acute stress. Electrical CeA activation induced a delayed, but significant, change in the IL, with prominent slow waves accompanied by an increase in the theta and gamma activities, and spindles. The phase-amplitude coupling of both slow waves and theta oscillations significantly increased with faster oscillations, including theta-gamma coupling and the nesting of spindles, theta and gamma oscillations in the slow wave cycle. These results are further discussed in neural processing terms of the stress response and memory formation.

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“…The cross‐frequency coupling among slow waves, spindles, and ripples was assessed by the modulation index (MI) as explained in (Neurophysiol, Tort, Komorowski, Eichenbaum, & Kopell, ). The detailed methods have been described before by our group (Luque‐García et al, ). Briefly, raw data were filtered within the two frequency ranges of interest and the MI index was calculated.…”

Molecular characterization of the stress network in the human brain

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