The amygdala plays a central role in diverse learned behaviors. By integrating the sensory information with stress, punishment, and reward signals, the circuitry within the amygdala is thought to be modified during learning to mediate specific behavioral outcomes. However, the circuit principles governing what is changed and how different types of learning give rise to qualitatively distinct behaviors remains largely unknown. It has been recognized that an important step towards dissecting the circuitry mechanism underlying amygdala- dependent learning is to determine the activities of individual neurons within discrete amygdala circuits before, during, and after a learning task. However, this goal has been challenging to achieve for technical reasons. First, the amygdala is buried deep within the brain, making it difficult to access by imaging methods, such as calcium imaging, which has become a technique of choice for interrogating neuronal action potential activities with cellular resolution over large neuronal populations. Second, the stress and reward signals are in part encoded as neuromodulatory activities, which do not usually result in direct changes in neuronal electrical activities and cannot be measured by calcium imaging or voltage measurements. Measuring neuromodulation in vivo, especially during behavior, remains challenging. Adding to the difficulty, the identity of individual amygdala circuits, as well as where each circuit receives input and where it sends output, are only partially understood. We plan to meet these challenges by integrating the most recent, complementary technological advances from the three co-PIs. In defined behavioral paradigms we will image calcium as a proxy for neuronal firing in the amygdalae of behaving mice by performing two-photon imaging via a tiny GRIN lens (?~0.5 mm), which offers optical access to deep brain structures with relatively little damage. Simultaneously through the same GRIN lens, we will image the activity dynamics of the cAMP/protein kinase A (PKA) signaling pathway, which is a common downstream signaling pathway for many neuromodulators, including norepinephrine and dopamine, as readout for stress/reward-induced neuromodulatory signals by using two-photon fluorescence lifetime imaging microscopy. In conjunction, we will perform computation-based anatomical circuitry analyses to dissect novel functional subdivisions of the amygdala, and identify the input-output of each subdivision with cell-type specificity. Based on these techniques, we will systematically map circuits, including previously unknown circuits, within the amygdala and determine how neurons from each circuit are recruited by and contribute to the generation of specific behaviors.
The amygdala is a structure located deep within the brain that plays an essential role in diverse learned behaviors, and its dysfunction is associated with mood disorders. We aim to integrate cutting-edge technological advances spanning multiple disciplines to visualize the precise neuronal activities and subcellular signaling events involved in learning in behaving animals. We expect that our study will reveal the logic of circuitry mechanisms underlying amygdala-dependent learning, which will in turn lead to an increased understanding of neuropsychiatric diseases associated with amygdala dysfunction.
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