Adult neurogenesis reconciles flexibility and stability of olfactory perceptual memory
- Engineering Sciences and Applied Mathematics, Northwestern University, United States
Figures
Figure 1
Computational model.
(A) MCs relay stimuli to cortex. Reciprocal synapses with GCs can be functional or non-functional (C). Adult neurogenesis adds GCs and apoptosis removes GCs. (B) Calcium controls synaptic plasticity (Graupner and Brunel, 2012). Influx into spine through MC-driven NMDARs and through voltage-gated calcium channels (VGCC) opened by global depolarization of GCs. (C) Unconsolidated spines are formed with rate and removed with rate . Spines become consolidated with a rate and deconsolidated with rate (Top). depend on the local calcium concentration in the spine (Bottom). (D) GCs are removed with a rate that depends on activity and age of the cells, as well as environmental factors (see Materials and methods). (E) Development of abGCs. At age 8–14 days, they integrate silently into the OB. The formation and elaboration of their dendrites depends on sensory input. During their critical period (14–28 days), the abGCs are more excitable and plastic and have a higher rate of apoptosis. Beyond 28 days the abGCs are mature GCs.
Figure 2 with 2 supplements
Age-dependent plasticity.
(A) AbGCs in their critical period (14–28 days) exhibit greater spine turnover. (B) Left: Activity of MCs arranged on a two-dimensional grid and stimulated with stimulus A or B, respectively. Each pixel represents a single MC, and the arrangement is for visualization only. Right: MCs initially respond similarly to both stimuli, but responses diverge after a 10 day enrichment. Over time, spontaneous synaptic changes lead to forgetting. (C) Memory is measured as a function of the network connectivity (see Materials and methods) for three different models: neurons with fast plasticity (green), neurons with slow plasticity (blue), neurons with age-dependent plasticity (red). Dashed curves are networks without neurogenesis. Lines: mean across eight trials, shaded areas: full range. The memory evolution is similar to that of the odor discriminability as measured using the Fisher discriminant (Figure 2—figure supplement 1B). (D) abGCs also exhibit increased excitability during their critical period. (E) The initial memory is enhanced by the increased excitability. Lines: mean across eight trials, shaded areas: full range (F) Delayed enrichment simulation in which the model was allowed to grow for longer and longer times preceding enrichment. MC responses to the test odors show diminished learning for delayed enrichment. Lines: mean memory across eight trials, shaded areas: full range. (G) The memory immediately following enrichment as a function of the number of GCs at enrichment onset for the case with (orange) and without (purple) age-dependent excitability. Lines: mean across eight trials, shaded areas: full range. (H) Reciprocal MC-GC connectivity at the end of the enrichment period of one simulation; orange: odor-specific connectivity (‘learning’ GCs), purple: unspecific connectivity (‘non-learning’). Center: connectivity matrix. Top: dendrogram reflecting hierarchical clustering of GCs according to their connectivity. Bottom: number of connections of each GC. Sides: number of connections of each MC to learning and non-learning GCs, respectively. MCs sorted according to input strength (leftmost panel). (I,J) Birthdates relative to enrichment onset of learning (orange) and non-learning (purple) GCs for models without and with increased excitability, respectively. At enrichment onset, GCs in the blue and yellow regions were in the developing and young stages, respectively (A). Green region shows enrichment period. Only GCs that were incorporated into the OB network (age >14 days) at the end of enrichment are shown. and were used for all simulations in this figure.
Figure 2—figure supplement 1
Spine turnover and consistency of memory measure.
(A) Parameters governing spine turnover were fit so that the 2-day spine turnover rates in young and mature abGCs matched those previously reported in Sailor et al., 2016. (B) Odor-discriminability as characterized by the Fisher discriminant (Appendix 1) exhibits the same behavior as the connectivity-based memory shown in Figure 2C. Lines: mean across eight trials, shaded areas: full range.
Figure 2—figure supplement 2
Buildup of abGCs interferes with learning.
(A) Activity of abGCs during initial day of enrichment in the model with increased excitability (orange) and without (purple). Lines: mean across eight trials, shaded areas: full range. (B) Number of GCs in the learning cluster in the model with increased excitability (orange) and without (purple). Lines: mean across eight trials, shaded areas: full range. (C) Percentage of engram GCs connected to each MC for the data in A, B. MCs sorted as in Figure 2B. Top: model with increased excitability. Bottom: model without increased excitability.
Figure 3 with 1 supplement
Dendritic structure.
(A) Sensory-dependent silent integration of juvenile abGCs (Figure 2A and D and Materials and methods). (B) Memory following enrichment as a function of the number of potential synapses with random (purple) and activity-dependent (orange) dendritic elaboration. Lines: mean across eight trials, shaded areas: full range. (C) Birthdate analysis as in Figure 2I. Learning mostly by abGCs that develop their dendrites during enrichment (blue region). (D) Enrichment was followed by a period of spontaneous activity until the memory cleared, then re-enrichment occurred with the same set of stimuli. (E) Birthdate analysis with a second set of colored regions corresponding to the re-enrichment (C). (F) Memory evolution during the initial enrichment (dotted line) and second enrichment both with (purple solid line) and without (orange solid line) neurogenesis. Lines: mean across eight trials, shaded areas: full range.
Figure 3—figure supplement 1
Dependence of memory on dendritic development.
(A) The same memory measurements were taken as in Figure 2C for the model with sensory-dependent dendritic development as well as increased excitability. The results are similar to those in Figure 2E, although the shifted birth-date dependence of abGC recruitment (Figure 3C) means that odor-encoding GCs are still in their critical period at the end of enrichment, leading to a short period of rapid memory decay. Lines: mean across eight trials, shaded areas: full range (B) Repeating the simulation in Figure 3D and F without sensory-dependent dendritic development. Relearning is no longer faster than the initial learning and is especially slow when neurogenesis is blocked. Here, to allow the network to learn fully. Lines: mean across eight trials, shaded areas: full range.
Figure 4 with 2 supplements
Apoptosis.
(A) AbGCs in their critical period (14–28 days) require a higher level of activity to survive. (B) The growth of the GC layer over time. Line: mean across eight trials, shaded area: full range (C) The portion of surviving GCs as a function of birthdate. The shaded regions are as in Figure 2E. Line: mean across eight trials, shaded area: mean ± standard deviation. (D, E) Sequential enrichment simulations differing in the inter-enrichment interval. Each curve corresponds to the mean memory of a stimulus over eight trials, and the shaded areas show the range over all trials. The bar plots show the mean initial memory for each stimulus. Lines: mean across eight trials, shaded areas: full range.
Figure 4—figure supplement 1
Effects of increased abGC survival during enrichment.
(A) Example sparse, random stimuli. For each stimulus pair, 20% of MCs were randomly selected to be stimulated. Of these MCs, half were highly stimulated and half were moderately stimulated for the first stimulus in the pair. For the second stimulus, the MCs that were previously highly stimulated were moderately stimulated, and those that were previously moderately stimulated became highly stimulated. This was to ensure the stimuli in the pair are difficult to discriminate. (B,C) Simulations in Figure 4D and E were repeated while doubling the number of new, fully functional abGCs on each day of enrichment to mimic the established results that olfactory enrichment increases the number of abGCs that survive until they start integrating into the network (Rochefort et al., 2002). This functional doubling of neurogenesis slightly increases the initial memory of each enrichment (see also Appendix 3—figure 2), but does not impact the prediction that more frequent enrichment improves memory. (D) The number of GCs over time for the model with a constant neurogenesis rate (orange) and with enrichment-increased neurogenesis (purple). Solid lines indicate trials with 20-day inter-enrichment intervals (orange: Figure 4D, purple: B), dotted lines indicate trials with 110-day inter-enrichment intervals (orange: Figure 4E, purple: C). Lines: mean across eight trials, shaded areas: full range.
Figure 4—figure supplement 2
Retrograde interference.
The experiments in Forest et al., 2019 were simulated for different pairs of artificial stimuli. (A–C) Experimental protocols in Forest et al., 2019. There were two enrichment periods with two different pairs of stimuli separated by either a 4 (A, C) or 14 (B) day interval. In (C), the odors from the first enrichment were also presented during the second enrichment period in addition to the new odors. (i-iii) Enrichment stimuli. In (i), the enrichment odors were largely non-overlapping. For (ii) and (iii), moderately and highly overlapping stimuli were generated, respectively, by using for stimulus 2 correspondingly cyclically shifted versions of stimulus 1. Line plots show the memory traces resulting from the enrichment protocol marked with the corresponding color in the same row and the stimuli in the same column. Lines: mean over eight trials, shaded areas: range of values. Bar plots show the percentage of GCs that encoded the first enrichment that survived at the end of the simulation. Odor-encoding GCs were determined by clustering the connectivity of GCs at the end of the first enrichment (Figure 2). Bars indicate the mean and error bars show the standard deviation. (Ai) The memory of the first enrichment was extinguished during the second enrichment, and there was a significant level of apoptosis among odor-encoding GCs. (Bi) The second enrichment did not substantially affect the initial memory, and there was little apoptosis among odor-encoding GCs. (Ci) The initial memory and the GCs that encoded that memory persisted through the second enrichment. (Aii) There is a significant decline in the initial memory during the second enrichment, although the odor-encoding GCs survive throughout the simulation, indicating the memory decline is a result of overwriting rather than apoptosis. (Bii) A slight memory decline occurs during the second enrichment. (Cii) The initial memory is maintained, but the network struggles to encode the second memory. (Aiii-Ciii) The second enrichment does not lead to any deficit in the initial memory, and there is no significant apoptosis. Lines: mean across eight trials, shaded areas: full range.
Figure 5 with 1 supplement
Neurogenesis for life-long learning.
(A) Protocol for sequential enrichment simulations. (B–E) Memory evolution of full model, model without apoptosis, model without apoptosis or age-dependent excitability, and model without neurogenesis, respectively. Each curve corresponds to the memory of a different set of stimuli. First bar plot plots show the mean initial memory, while the second bar plot shows the mean memory at the end of the simulation. Lines: mean across eight trials, shaded areas: full range. In (E), and so that the model learns and forgets at a rate similar to that of the full model. (F) Memory of the first enrichment in (B-E) relative to the memory of that same enrichment without subsequent enrichments. Lines: average across trials, shading: standard error of the mean. Shaded areas: times when the model is exposed to a new stimulus. (G) Memory for sequential enrichment if the connectivity of mature abGCs is frozen. Lines: mean across eight trials, shaded areas: full range.
Figure 5—figure supplement 1
GC population size over time.
Number of GCs over time for the data in Figure 5.
Appendix 2—figure 1
Mean-field model.
(A) We assume there exists an optimal configuration that can process a given stimulus. In this framework, the network directly encodes this configuration stochastically according to the plasticity rate at each synapse, and at each time point, a new stimulus is presented to the network. We track the memory of the network as the degree of overlap between the optimal network for a given stimulus and the current configuration of the network (see Appendix ‘Comparison with other methods resolving the flexibility-stability dilemma’). Note that a lack of connection can also represent an overlap. (B) Overlap between each stimulus and the current configuration of the network in (A). (C) Results of the mean-field approximation to the model described in (A) with age-dependent synaptic plasticity rates have similar initial memory and memory duration as the cascade model Fusi et al., 2005, and the partitioned-memory model Roxin and Fusi, 2013. (D) Results of the age-dependent model for different values of the number of synapses . (E) Initial memory as a function of . (F) Memory duration as a function of .
Appendix 3—figure 1
Post-learning changes in neurogenesis rate.
(A) Simulation protocol. Following a 10-day enrichment (using the odors in Figure 2B), the neurogenesis rate was permanently changed. (B, C) Fisher discriminant between the two similar odors for the full model and the model without apoptosis. The Fisher discriminant was chosen in order to investigate the degree that abGCs interfere with MC activity, which represents the output of the network. The full model can tolerate the addition of vast numbers of new neurons without substantially affecting memory. Without apoptosis, the accumulation of neurons has substantial impact on memory. Lines: mean across eight trials, shaded areas: full range.
Appendix 3—figure 2
Parameter sensitivity.
In all plots, the values indicated in black are the parameter values used throughout this study. Lines indicate the mean and shaded areas represent the range over eight trials. (A) Final memory following the standard enrichment experiment as a function of and . (B–F) Memory trace over the course of the standard enrichment experiment for different values of (for abGCs in their critical period), , , , and , respectively. Lines: mean across eight trials, shaded areas: full range. In (D), was increased to 1 following enrichment to illustrate the final memory value after forgetting. (G) GC survival following enrichment for different values of during the critical period of the abGCs (Figure 4C). Lines: mean across eight trials, shaded areas: full range. (H) Results of the relearning experiment Figure 3F for different values of . Solid: initial learning, dashed: re-learning. Lines: mean across eight trials, shaded areas: full range(I) As in (H) but for instead of 30.
Author response image 1
Number of GCs over time for neurogenic (solid line) and non-neurogenic (dotted line) networks.
Author response image 2
Disynaptic connectivity.
Top: MC activity in response to the two stimuli, sorted by MC selectivity. Bottom: Disynaptic connectivity matrix (diagonal subtracted).
Author response image 3
Simulating learning in more complex odor environments.
Top: enrichment consisted of three odor pairs presented sequentially in a random order. Bottom: enrichment consisted of five odor pairs. Left: discriminability of the odor pairs over time. Middle: connectivity between MCs (sorted by odor selectivity) and GCs (sorted by age). In both cases AbGCs develop a clear connectivity structure. In more complex environments neonatal GCs also start to develop a clear connectivity structure. Right: combined engram membership across all stimuli by GC age.
Tables
Table 1
Age-dependent parameters.
GCs were considered immature if they were added to the network within 14 time steps, corresponding to their critical period.
| Critical period | Fully mature | Description | Usage | |
|---|---|---|---|---|
| 0.2 | 0.02 | Plasticity rate | Scales α, β, , | |
| 1.5 | 1 | Excitability of GCs | Equations 2, 6 | |
| 0.5 (enriched), 0 (unenriched) | –0.45 | Survival threshold | Equation 11 |
Table 2
Age-independent parameters.
Parameter values used in the simulation of the model unless stated otherwise.
| Value | Description | Usage | |
|---|---|---|---|
| 225 | Number of MCs | Network architecture | |
| 900 | Initial number of GCs | Network architecture | |
| 8 | Number of GCs added each neurogenesis step | Network architecture | |
| 30 | Number of MCs with which a GC can form synapses | Network architecture | |
| 10 | Number initial synapses made by each abGC | Network architecture | |
| 1.5 | Rate of unconsolidated spine formation | Network architecture | |
| 1.5 | Rate of unconsolidated spine removal | Network architecture | |
| 0.1 | Spontaneous activity of sensory input | Equation 1 | |
| 0.004 | Inhibitory strength of GCs | Equation 1 | |
| 0.15 | Threshold to induce dendritic growth | Equation 3 | |
| Noise in dendritic formation | Equation 3 | ||
| 0.01 | Spontaneous rate of synaptic changes | Equations 4, 5 | |
| 13 | Scaler | Equations 4, 5 | |
| 0.7 | Relative rate of deconsolidation to consolidation | Equation 5 | |
| 3.6 | Presynaptic calcium contribution | Equation 6 | |
| 1.1 | Postsynaptic calcium contribution | Equation 6 | |
| 3.33 | Timescale of calcium dynamics | Equation 6 | |
| 0.95 | Consolidation threshold scalar | Equations 9, 10 | |
| 1.05 | Minimum threshold for consolidation | Equation 9 | |
| 1 | Minimum threshold for deconsolidation | Equation 10 |
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Adult neurogenesis reconciles flexibility and stability of olfactory perceptual memory
eLife 14:RP104443.
https://doi.org/10.7554/eLife.104443.3
