Spatial learning sculpts the dendritic arbor of adult-born hippocampal neurons

Abstract

Neurogenesis in the hippocampus is characterized by the birth of thousand of cells that generate neurons throughout life. The fate of these adult newborn neurons depends on life experiences. In particular, spatial learning promotes the survival and death of new neurons. Whether learning influences the development of the dendritic tree of the surviving neurons (a key parameter for synaptic integration and signal processing) is unknown. Here we show that learning accelerates the maturation of their dendritic trees and their integration into the hippocampal network. We demonstrate that these learning effects on dendritic arbors are homeostatically regulated, persist for several months, and are specific to neurons born during adulthood. Finally, we show that this dendritic shaping depends on the cognitive demand and relies on the activation of NMDA receptors. In the search for the structural changes underlying long-term memory, these findings lead to the conclusion that shaping neo-networks is important in forming spatial memories.

Fig. 1.

Spatial learning increases the survival and the dendritic arbor complexity of adult-born neurons generated 1 week before learning. (A) Latency to find the escape platform. The syringe represents BrdU injection. (B) Total number of BrdU-IR cells (t₁₅ = −3.85; P < 0.001). (Inset) Illustration of a BrdU-IR cell. (C) Illustration of a BrdU-IR cell expressing Dcx. (D) Examples of neuron tracings for one animal of each group. (E) Length of the dendritic arbor (t₁₅ = −3.44; P < 0.01). (F) Number of nodes (t₁₅ = −2.37; P < 0.05). (G) Number of endings (t₁₅ = −2.35; P < 0.05). C, n = 6; L-RM, n = 11. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 compared with control. (Scale bar: 10 μm.)

Fig. 2.

Spatial learning increases the dendritic arbor complexity of adult-born neurons generated during the early phase of training. (A) Number of BrdU-IR cells in the septal region of the DG (t₁₁ = 4.66; P < 0.001). (B) Length of the dendritic arbor (t₁₁ = −2.77; P < 0.05). (C) Number of nodes (t₁₁ = −2.84; P < 0.05). (D) Number of endings (t₁₁ = −2.79; P < 0.05). C, n = 6; L-RM, n = 7. *P ≤ 0.05; ***P ≤ 0.001 compared with control.

Fig. 3.

Homeostatic regulation of the dendritic arbor of adult-born neurons by spatial learning. (A and B) Effects of zVAD and vehicle treatments on the number of IdU-IR cells (in the septal region of the DG) generated 7 days before exposure to the task (A) and the number of CldU-IR cells generated 3 days before exposure to the task (B). (C and D) Effects of zVAD and vehicle treatments on the length of dendrites of IdU-Dcx-IR cells (F_3,25 = 8.2; P < 0.001) (E) and CldU-Dcx-IR cells (F_3,25 = 5.18; P < 0.01) (F). C: Veh, n = 6, zVAD, n = 6; L-RM: Veh, n = 10, zVAD, n = 7. Veh, □; zVAD, ■. *P ≤ 0.05; **P ≤ 0.01 compared with control veh. °P ≤ 0.05; °°P ≤ 0.01 compared with zVad group.

Fig. 4.

The effect of spatial learning on the dendritic arbor is long-lasting. (A) Latency to find the escape platform. The symbol represents retrovirus infusions; the syringe, BrdU injection; and the arrows, the time of sacrifice (3 months after training). (B) Total number of BrdU-IR cells. (C) Length of dendrites and 3-month-old adult-born neurons labeled with a GFP retrovirus. C, n = 7; L-RM, n = 8. ***P ≤ 0.001 compared with control.

Fig. 5.

Spatial learning increases the number of dendritic spines of adult-born neurons. (A) Number of spines (per 40 μm) (t₁₀₃ = 9.25; P < 0.0001). (B) Spine width (t₁₀₃ = 2.94; P < 0.01). (C) Spine length (t₁₀₃ = 2.47; P < 0.01). (D) Number of thin spines and mushroom spines (% compared with control) (thin spines, t₈ = -5.06, P < 0.001; mushroom spines, t₈ = −5.75, P < 0.001). (E) Number of spines (per 40 μm) in neurons generated 1 week before the task (t₁₅ = −3.53, P < 0.01). (F) Three-dimensional reconstruction of a confocal photomicrograph of a GFP-IR dendrite (green) contacted by synaptophysin (red) fibers. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 compared with control.

Fig. 6.

The learning effect on the dendritic arbor is governed by the cognitive demand of the task. (A) Latency to find the escape platform. (B) Total number of BrdU-IR cells (F_2,21 = 4.58; P = 0.02). (C) Total number of apoptotic cells measured by the number of fractine-IR cells (F_2,21 = 6.45; P = 0.06). (D) Total number of proliferating cells measured by the number of HH3-IR cells (F_2,21 = 3.7; P = 0.04). (E) Length of the dendritic arbor (F_2,21 = 9.85; P < 0.001). (F) BrdU-IR cell (red) stained with NeuN (green), a typical marker for mature newborn neurons. (G) Percentage of BrdU-IR cells expressing NeuN (F_2,21 = 44.22; P < 0.001). C, n = 8; L-RM, n = 8; L-DMP, n = 8. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 compared with control. °P ≤ 0.05, L-RM compared with L-DMP.

Fig. 7.

Influence of NMDA receptors on spatial learning and learning-induced changes in the number of adult-born neurons and their dendritic arbor complexity. (A) Latency to find the escape platform. (B) Total number of BrdU-IR cells (F_3,33 = 8.32; P < 0.001). (C) Total number of apoptotic cell measured by the number of fractine-IR cells (F_3,33 = 9.66; P < 0.001). (D) Total number of proliferating cells measured by the number of HH3-IR cells (F_3,33 = 3.21; P < 0.05). (E) Length of the dendritic arbor (F_3,31 = 6.47, P < 0.001). (F) Number of nodes (F_3,31 = 5.80, P < 0.01). (G) Number of endings (F_3,31 = 5.74, P < 0.01). (H) Percentage of BrdU-IR cells expressing NeuN (F_3,31 = 3.70, P < 0.05). C: CSF, n = 7, APV, n = 9; L-DMP: CSF, n = 10, APV, n = 9. Vehicle, □; AVP, ■. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 compared with control CSF. °P ≤ 0.05; °°P ≤ 0.01 compared with APV group.