Dopamine Modulates Homeostatic Excitatory Synaptic Plasticity of Immature Dentate Granule Cells in Entorhino-Hippocampal Slice Cultures.

Homeostatic plasticity mechanisms maintain neurons in a stable state. To what extent these mechanisms are relevant during the structural and functional maturation of neural tissue is poorly understood. To reveal developmental changes of a major homeostatic plasticity mechanism, i.e., homeostatic excitatory synaptic plasticity, we analyzed 1-week- and 4-week-old entorhino-hippocampal slice cultures and investigated the ability of immature and mature dentate granule cells (GCs) to express this form of plasticity. Our experiments demonstrate that immature GCs are capable of adjusting their excitatory synaptic strength in a compensatory manner at early postnatal stages, i.e., in 1-week-old preparations, as is the case for mature GCs. This ability of immature dentate GCs is absent in 4-week-old slice cultures. Further investigations into the signaling pathways reveal an important role of dopamine (DA), which prevents homeostatic synaptic up-scaling of immature GCs in young cultures, whereas it does not affect immature and mature GCs in 4-week-old preparations. Together, these results disclose the ability of immature GCs to express homeostatic synaptic plasticity during early postnatal development. They hint toward a novel role of dopaminergic signaling, which may gate activity-dependent changes of newly born neurons by blocking homeostasis.

T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells.

Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.

Adult-born dentate granule cells show a critical period of dendritic reorganization and are distinct from developmentally born cells.

Adult-born dentate granule cells (abGCs) exhibit a critical developmental phase during function integration. The time window of this phase is debated and whether abGCs become indistinguishable from developmentally born mature granule cells (mGCs) is uncertain. We analyzed complete dendritic reconstructions from abGCs and mGCs using viral labeling. AbGCs from 21-77 days post intrahippocampal injection (dpi) exhibited comparable dendritic arbors, suggesting that structural maturation precedes functional integration. In contrast, significant structural differences were found compared to mGCs: AbGCs had more curved dendrites, more short terminal segments, a different branching pattern, and more proximal terminal branches. Morphological modeling attributed these differences to developmental dendritic pruning and postnatal growth of the dentate gyrus. We further correlated GC morphologies with the responsiveness to unilateral medial perforant path stimulation using the immediate-early gene Arc as a marker of synaptic activation. Only abGCs at 28 and 35 dpi but neither old abGCs nor mGCs responded to stimulation with a remodeling of their dendritic arbor. Summarized, abGCs stay distinct from mGCs and their dendritic arbor can be shaped by afferent activity during a narrow critical time window.