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.Fil: Beining, Marcel. Ernst Strungmann Institute; Alemania. Frankfurt Institute for Advanced Studies; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Mongiat, Lucas Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Schwarzacher, Stephan Wolfgang. Goethe Universitat Frankfurt; AlemaniaFil: Cuntz, Hermann. Frankfurt Institute for Advanced Studies; Alemania. Ernst Strungmann Institute; AlemaniaFil: Jedlicka, Peter. Goethe Universitat Frankfurt; Alemani

Time-lapse imaging reveals highly dynamic structural maturation of postnatally born dentate granule cells in organotypic entorhino-hippocampal slice cultures

Neurogenesis of hippocampal granule cells (GCs) persists throughout mammalian life and is important for learning and memory. How newborn GCs differentiate and mature into an existing circuit during this time period is not yet fully understood. We established a method to visualize postnatally generated GCs in organotypic entorhino-hippocampal slice cultures (OTCs) using retroviral (RV) GFP-labeling and performed time-lapse imaging to study their morphological development in vitro. Using anterograde tracing we could, furthermore, demonstrate that the postnatally generated GCs in OTCs, similar to adult born GCs, grow into an existing entorhino-dentate circuitry. RV-labeled GCs were identified and individual cells were followed for up to four weeks post injection. Postnatally born GCs exhibited highly dynamic structural changes, including dendritic growth spurts but also retraction of dendrites and phases of dendritic stabilization. In contrast, older, presumably prenatally born GCs labeled with an adeno-associated virus (AAV), were far less dynamic. We propose that the high degree of structural flexibility seen in our preparations is necessary for the integration of newborn granule cells into an already existing neuronal circuit of the dentate gyrus in which they have to compete for entorhinal input with cells generated and integrated earlier

The Role of Sogo-Zaibatsu in the Economic Development of Modern Japan

<div><p>Adult neurogenesis is frequently studied in the mouse hippocampus. We examined the morphological development of adult-born, immature granule cells in the suprapyramidal blade of the septal dentate gyrus over the period of 7–77 days after mitosis with BrdU-labeling in 6-weeks-old male Thy1-GFP mice. As Thy1-GFP expression was restricted to maturated granule cells, it was combined with doublecortin-immunolabeling of immature granule cells. We developed a novel classification system that is easily applicable and enables objective and direct categorization of newborn granule cells based on the degree of dendritic development in relation to the layer specificity of the dentate gyrus. The structural development of adult-generated granule cells was correlated with age, albeit with notable differences in the time course of development between individual cells. In addition, the size of the nucleus, immunolabeled with the granule cell specific marker Prospero-related homeobox 1 gene, was a stable indicator of the degree of a cell's structural maturation and could be used as a straightforward parameter of granule cell development. Therefore, further studies could employ our doublecortin-staging system and nuclear size measurement to perform investigations of morphological development in combination with functional studies of adult-born granule cells. Furthermore, the Thy1-GFP transgenic mouse model can be used as an additional investigation tool because the reporter gene labels granule cells that are 4 weeks or older, while very young cells could be visualized through the immature marker doublecortin. This will enable comparison studies regarding the structure and function between young immature and older matured granule cells.</p></div

Nuclear size measurement as a valuable tool to discriminate between early and late stages in structural maturation and age of newborn DGCs.

<p>(A, D) The correlation of nuclear size with structural stage and cell age is illustrated as a dot plot (each dot represents a single cell, pooled from all animals per group) to highlight the variability. (B, E) Newborn DGCs were pooled in an early (DCX stage 1–3, cell age 7–14 dpi) and a late phase (DCX stage 4–6, cell age 21–77 dpi). The mean nuclear sizes of each group were determined and used to calculate the equidistance between early and late phases, which was then used as a threshold to discriminate and assign newborn DGCs to the early or the late phase of development (shown as red dashed line). (C, F). Based on that threshold, cells were categorized into true positive, false positive and false negative predictive values. True positive classifications were found with a reliability of about 70% across all stages. Number of animals: (A, D) DCX stage 1: n = 5, stage 2: n = 7, stage 3: n = 4, stage 4: n = 6, stage 5: n = 9, stage 6: n = 11; cell age: n = 3 per group. (B, E) DCX stage 1–3: n = 8, stage 4–6: n = 12; cell age 7–14 dpi: n = 6, age 21–77 dpi: n = 18. Error bars represent SEM.</p

Doublecortin-labeling does not co-localize with Thy1-GFP expression.

<p>(A) Frontal section of the dorsal hippocampal formation from a Thy-1-GFP mouse. Thy1-GFP expression was observed in a subpopulation of dentate granule cells (DGCs) and was expressed throughout dendritic processes of DGCs which extend into the inner molecular layer (IML) and outer molecular layer (OML) toward the hippocampal fissure (hif). Prospero homeobox protein 1 (Prox1, magenta), a specific nuclear marker of granule cells, was confined to granule cell nuclei of the granule cell layer (GCL). Doublecortin (DCX, cyan) labeled young maturing cells that are positioned in the subgranular zone (SGZ). (B) There was no co-localization of DCX and Thy1-GFP which suggests that Thy1-GFP is generally expressed in more mature (DCX-) DGCs. Both DCX+ and Thy1-GFP+ granule cells co-localized with Prox1 even during early stages of DCX expression (see small DCX+ cells in the SGZ). Scale bars: (A) 100 μm; (B) 20 μm. CA1, Cornu Ammonis area 1; H, hilus.</p

A general principle of dendritic constancy a neuron’s size and shape invariant excitability

Reducing neuronal size results in less cell membrane and therefore lower input conductance. Smaller neurons are thus more excitable as seen in their voltage responses to current injections in the soma. However, the impact of a neuron’s size and shape on its voltage responses to synaptic activation in dendrites is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs and show that these are entirely independent of dendritic length. For a given synaptic density, a neuron’s response depends only on the average dendritic diameter and its intrinsic conductivity. These results remain true for the entire range of possible dendritic morphologies irrespective of any particular arborisation complexity. Also, spiking models result in morphology invariant numbers of action potentials that encode the percentage of active synapses. Interestingly, in contrast to spike rate, spike times do depend on dendrite morphology. In summary, a neuron’s excitability in response to synaptic inputs is not affected by total dendrite length. It rather provides a homeostatic input-output relation that specialised synapse distributions, local non-linearities in the dendrites and synaptic plasticity can modulate. Our work reveals a new fundamental principle of dendritic constancy that has consequences for the overall computation in neural circuits

Nuclear size and soma position are positively correlated with structural maturation and age of newborn DGCs.

<p>(A) Examples of a 21-day-old stage 1 DCX/Prox1+ cell that is located in the subgranular zone (SGZ) and has no dendritic processes (arrowheads, upper panel) and a 21-day-old stage 6 DCX/Prox1+ cell (arrows, lower panel) with a dendrite extending into the outer molecular layer (OML; arrowheads, lower panel). Asterisk denotes the soma of an intensively labeled Thy1-GFP+ cell. (B) Nuclear size (determined with the nuclear marker Prox1, green) increased with structural maturity. There were significant differences in nuclear size between stages 1 and 6, as well as between stages 1 and 5, stages 2 and 6, and stages 3 and 6 (Kruskal-Wallis Dunn's multiple comparison test between animals, *P < 0.05; stage 1: n = 5 animals, stage 2: n = 7, stage 3: n = 4, stage 4: n = 6, stage 5: n = 9, stage 6: n = 11). (C) In BrdU/Prox1+ DGCs, nuclear size increased gradually with age until it reached a plateau at 35 dpi (n = 3 per group). (D, E) The majority of newborn DGCs was positioned in the SGZ and the inner half of the granule cell layer (GCL), regardless of structural stage and age. Error bars represent SEM. Scale bars in (A): 10μm. IML, inner molecular layer.</p