Imagine you have a group of friends who all enjoy different hobbies – one likes to paint, another likes to play guitar, and another likes to play soccer. Despite their differences, they all come together to create a fun and diverse group. Similarly, neural circuits in our brains can also be diverse while still performing the same function. In this study, scientists looked specifically at the neural circuits involving dopamine and serotonin neuromodulators, which play crucial roles in reward and punishment-based learning. By using computational modeling and analysis techniques, they discovered that these neural circuits can exhibit degeneracy, meaning they can have different wiring patterns but still produce the same network activity. This finding has important implications for our understanding of how the brain maintains stable and robust neuromodulatory functions. To further explore this concept, the researchers simulated the effects of a D2 receptor agonist on the neural circuits and found that it could distinguish between specific sub-groups within the degenerate circuits based on their activity patterns. The results of this study provide valuable insights into the complexity of neural circuitry and open up new avenues for investigating neuromodulatory function.

Degenerate neural circuits perform the same function despite being structurally different. However, it is unclear whether neural circuits with interacting neuromodulator sources can themselves degenerate while maintaining the same neuromodulatory function. Here, we address this by computationally modeling the neural circuits of neuromodulators serotonin and dopamine, local glutamatergic and GABAergic interneurons, and their possible interactions, under reward/punishment-based conditioning tasks. The neural modeling is constrained by relevant experimental studies of the VTA or DRN system using, e.g., electrophysiology, optogenetics, and voltammetry. We first show that a single parsimonious, sparsely connected neural circuit model can recapitulate several separate experimental findings that indicated diverse, heterogeneous, distributed, and mixed DRNVTA neuronal signaling in reward and punishment tasks. The inability of this model to recapitulate all observed neuronal signaling suggests potentially multiple circuits acting in parallel. Then using computational simulations and dynamical systems analysis, we demonstrate that several different stable circuit architectures can produce the same observed network activity profile, hence demonstrating degeneracy. Due to the extensive D2-mediated connections in the investigated circuits, we simulate the D2 receptor agonist by increasing the connection strengths emanating from the VTA DA neurons. We found that the simulated D2 agonist can distinguish among sub-groups of the degenerate neural circuits based on substantial deviations in specific neural populations’ activities in reward and punishment conditions. This forms a testable model prediction using pharmacological means. Overall, this theoretical work suggests the plausibility of degeneracy within neuromodulator circuitry and has important implications for the stable and robust maintenance of neuromodulatory functions.

Read Full Article (External Site)