A neural state of resilience? Encoding resilience as set points of cortical microcircuit activity
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Abstract
Stress resilience describes the capability of an individual to maintain mental health during or after traumatic, stressful or emotionally challenging situations or to return to a mental state similar to that before the crisis onset. The aim of resilience research is to identify mechanisms that enables an individual to maintain mental health, rather than developing mental disorders and has increasingly come into focus. Studies indicate that resilience is an active adaptive process and not just the absence of symptoms observed in individuals who are deficient in these defense mechanisms and therefore susceptible to stressors. Up to date, no universal concept to grasp resilience exists, but several mechanisms that putatively contribute to stress-resilient or -susceptible behavioral phenotypes were identified. In humans, psychological and socio-environmental factors as adaptive coping and social support can contribute to the maintenance of normal psychological function and avoid serious mental illness, but also a wide range of neurobiological markers such as changes in the neuroendocrinological system or genetic factors have been associated with resilience. Yet, to which extend stress resilience is reflected in a differing functional architecture of neuronal network activity remained largely unexplored. There is evidence of hyperactive neuronal network activity within networks of the primary visual cortex (V1) in animal models of multiple sclerosis, Huntington’s or Alzheimer disease, present long before phenotypic changes become measurable at the behavioral level. It is hypothesized that changes in network activity do not serve the purpose to preserve long-term functionality to achieve behavioral functionality but instead aim for short-term stability to maintain the status quo of network function, coining the term of a selfish network. There is mounting evidence that the historic view on brain architecture of distinct brain regions executing well-defined tasks, does not accurately describe brain functionality. Instead, brain regions such as the sensory cortices are considered not only to process incoming sensory stimuli, but also contribute to action execution and decision making, forming a functionally bound brain. The V1 poses a well suitable brain region to probe for network dysregulations as it receives information from other sensory cortices, locomotion and areas related to emotion.
This thesis aims to elucidate the concept of stress-resilience on the level of neuronal networks within V1 in a mouse model of chronic social stress. Mice are subjected to a behavioral paradigm of chronic social defeat (CSD). The behavioral phenotype is assessed by a social interaction-test (SI-test), dividing the population into a resilient and susceptible behavioral phenotype. Furthermore, a subgroup of mice which is not undergoing CSD is used to answer the question if non-stressed animals show neuronal network patterns comparable to resilient or susceptible animals, or whether they represent a third distinct network state. Neuronal network activity is measured in the awake behaving animal on single cell level in V1 layer II/III employing two-photon functional calcium imaging. The assessment of both spontaneous and sensory-evoked neuronal activity is used to obtain a fine-grained picture of the local functional architecture of a network. For improving the sensitivity of the detection of putative network dysregulation, the two-photon functional calcium imaging analysis pipeline has been streamlined and improved, for optimizing the correlation of calcium transient to underlying neuronal action potentials. Lastly, a three-photon functional calcium imaging microscope is implemented and imaging quality is compared with two-photon microscopy modalities.
It was found that the newly developed analysis pipeline outperforms commonly used analysis routines. Employed to functional calcium imaging data in a mouse model of chronic social defeat, neuronal networks in resilient classified animals exhibit lower spontaneous activity and a more accurate representation of visual afferents compared to susceptible litter mates. Non-stressed animals exhibit network activity close to the dynamics of susceptible animals, both in spontaneous network activity as well as in the representation of visual afferents. Lastly, employing three-photon microscopy revealed an increase of the penetration depth at the cost of imaging frequency and size of the resolved field of view.
The findings underline the importance of the development of analysis routines capable of accurately capturing single cell activity to describe neuronal network patterns. In the field of resilience research, the results suggest that architectures of neuronal networks within sensory cortices itself might constitute a resilience mechanism, contributing to the outcome of a resilient or susceptible behavioral phenotype. Finally, the first datasets collected using three-photon microscopy represent a promising opportunity to resolve neuronal networks in deeper regions such as layer V of V1.