Keijser, Joram Manasse;
(2024)
Computational and comparative analyses of inhibitory interneuron diversity.
Doctoral thesis (Dr. rer. nat.), Technische Universität Berlin.
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Abstract
The brain is a complex network of many brain cells, in particular neurons. These neurons are very diverse and can be categorized into hundreds of cell types based on their molecular, morphological, and electrophysiological properties. Because different cell types play specialized roles in neural computations, understanding the brain requires understanding its cell types and how they interact. One particularly diverse group of cells is that of inhibitory interneurons, named after their suppressive effect on local neural activity. Interneurons are important to stabilize neural activity, but why this requires many different cell types is unclear. In our first study, we hypothesized that different cell types are needed to stabilize neural activity in the various compartments (soma and dendrites) of excitatory pyramidal cells. To test this hypothesis, we optimized the properties of model interneurons to balance excitation (E) and inhibition (I) in both pyramidal compartments. After the optimization, neurons largely fell into two classes, resembling biological interneuron types known as PV and SST-positive neurons. These cell types may therefore be required for balancing excitation and inhibition in different neuronal compartments. A natural conclusion, then, is that PV+ and SST+ cell types might have developed or evolved for this purpose. In our second study, we tested this idea by comparing cell types across species. Surprisingly, we found evidence that interneurons acquired the ability of compartment-specific inhibition before there was selective pressure for this function. The properties of a cell type may, therefore, have been cobbled together during its evolutionary history rather than being optimized for its current purpose. Finally, we investigated the behavioural response of different interneuron types. When a mouse becomes active and aroused, certain interneuron types also become more active, but others become less active. Testing whether this is true in other species would require measuring both the activity and identity of individual cells. Unfortunately, this is currently unfeasible, especially in humans. We therefore searched more readily available gene expression data for patterns associated with arousal responses. We discovered that these patterns are quite similar in humans but different in turtle and zebra finch interneurons. A mathematical model predicts which of those gene expression differences may translate into functional differences and which may not. In summary, this thesis provides a nuanced perspective on interneuron diversity. Different cell types have distinct functions, but these functions may not be the reason that the cell types exist. Interneurons of different species are evolutionarily related but have, of course, also developed their own specializations.
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