Real-time imaging of amygdalar network dynamics in vitro reveals a neurophysiological link to behavior in a mouse model of extremes in trait anxiety

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Abstract

In humans and numerous other mammalian species, individuals considerably vary in their level of trait anxiety. This well known phenomenon is closely related to the etiology of several psychiatric disorders, but its neurophysiological basis remains poorly understood. Here, we applied voltage-sensitive dye imaging to brain slices from animals of the high (HAB), normal (NAB), and low (LAB) trait anxietymousemodel and investigated whether evoked neuronal activity propagations from the lateral (LA) to the central (CeA) amygdala differ in their relative strength among HAB, NAB, andLABmice. For this purpose, we divided a real-time measure of neuronal population activity in the CeA by a respective measure obtained for the LA. This calculation yielded the metric "CeA/LA activity." Our data clearly demonstrate a positive correlation between trait anxiety levels evaluated by the elevated plus-maze test and CeA/LA activity. Moreover, we found reduced CeA/LA activity in HAB mice, which responded with decreased anxiety levels to an environmental enrichment and, inversely, detected increased anxiety levels and CeA/LA activity in LAB mice that experienced chronic mild stress. We did not observe differences in the spread of neuronal activity in the motor and visual cortex among HAB, NAB, and LAB animals. Collectively, these findings provide evidence that, in mammals, interindividual variability in trait anxiety is causally linked to individual variations in the physiological constitution of the LA-to-CeA circuitry that give rise to a differential regulation of neuronal signal flow through this fundamental input-output network of the amygdala. © 2013 the authors.

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Avrabos, C., Sotnikov, S. V., Dine, J., Markt, P. O., Holsboer, F., Landgraf, R., & Eder, M. (2013). Real-time imaging of amygdalar network dynamics in vitro reveals a neurophysiological link to behavior in a mouse model of extremes in trait anxiety. Journal of Neuroscience, 33(41), 16262–16267. https://doi.org/10.1523/JNEUROSCI.2397-13.2013

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