Traces of Semantization, from Episodic to Semantic Memory in a Spiking Cortical Network Model

Trial structure of the two simulated variants of the episodic memory task. Items are first associated with one or several contexts (CNX) during the encoding phase in 250-ms cue episodes, with an interstimulus interval of 500 ms. The colors of the coactivated contexts are consistent with their corresponding associated item. The recall phase occurs with a delay of 1 s and involves different trials with either brief cues (50 ms) of the (A) items or (B) contexts presented during the item-context association encoding phase.

Semantization of episodic memory traces. A, Schematic of the Item (green) and Context (blue) networks. Attractor projections are long-range connections across HCs in the same network and learned associative projections are connections between networks. B, Spike raster of pyramidal neurons in HC1 of both the Item and Context networks. Each context/item memory pattern corresponds to the activation of a unique set of MCs in its network. Items and their corresponding context representations are simultaneously cued in their respective networks (compare Fig. 2A). Each item is drawn with a unique color, while contexts inherit their coactivated item’s color in the raster (i.e., the yellow pattern in the Item network is repeated over four different contexts, forming four separate associations marked with the same color). The testing phase occurs 1 s after the encoding. Brief 50-ms cues of already studied items trigger their activation. Following item activation, we detect evoked attractor activation in the Context network. C, Average cued recall performance in the Context network (20 trials). The bar diagram reveals progressive loss of episodic context information (i.e., semantization) over the number of context associations made by individual cued items (compare Fig. 2A). D, Distribution of plastic connection weights between the Item and Context networks (NMDA component shown here). Weights are noticeably weaker for items which participate in multiple associations. The distributions of synaptic weights exhibit a broader range for the items with multiple context associations, as the sample size is larger. The inset displays the distribution of EPSPs for the binding between Item and Context networks. The EPSP distributions follow the trend of the associative weights. The amplitudes (<1 mV) are lower for higher context variability. E, The distribution of intrinsic excitability currents of pyramidal cells coding for specific context representations. The intrinsic excitability features similar distributions because each context is activated exactly once, regardless of whether the associated item forms multiple associations or not. F, Average cued recall performance in the Item network (20 trials). Decontextualization over the number of associations is also observed when we briefly cue episodic contexts instead (compare Fig. 2B). G, Distribution of strength of plastic connections from the contexts to their associated items. Analogously to D, synapses weaken once an item is encoded in another context. H, Intrinsic plasticity distribution of cells in the Item network. Intrinsic excitability distributions are higher for pyramidal cells coding for repeatedly activated items; ***p < 0.001 (Mann–Whitney, N = 20 in C, F). Error bars in C, F represent SDs of Bernoulli distributions. Distributions of one, two, three, and four associations in D, G, H show significant statistical difference (p < 0.001, Mann–Whitney, N = 2000).

Network model where associative projections are implemented using standard STDP synaptic plasticity. A, Spike raster of pyramidal neurons in HC1 of both the Item and Context networks. B, Average item-cued recall performance in the Context network (20 trials). Episodic context retrieval is preserved even for high context variability (as opposed to BCPNN; compare Fig. 3C). C, Distribution of NMDA receptor mediated synaptic weights between the item and context neural assemblies following associative binding. The distributions of item-context weights have comparable means at ∼0.065 nS regardless of how many context associations a given item forms. Bins merely display a higher count for the four-association case as the total count of associative weights is more extensive compared with items with fewer associations. D, Average cued recall performance in the Item network when episodic contexts are cued (20 trials). E, Distribution of NMDA component weights between associated context and item assemblies; ***p < 0.001 (Mann–Whitney, N = 20 in B, D). Error bars in B, D represent SDs of Bernoulli distributions.

Removal of the augmentation mechanism in the network model. A, Distribution of AMPA component weights of the Item network including synaptic augmentation. The multiplicative effect of synaptic augmentation on the consolidated items features stronger combined synaptic strength for items with higher context variability. Slower NMDA receptor weights follow a similar pattern. Weight distributions of one, two, three, and four associations have statistical difference (p < 0.001, Mann–Whitney, N = 2000). B, Distribution of AMPA component weights of the Item network after removing synaptic augmentation. C, Cued recall under STDP after removing synaptic augmentation. Average item-cued recall performance in the Context network (20 trials). To compensate for the removal of augmentation, we increased the stimulation rates and the synaptic gain eliciting comparable spiking activity. Error bars represent SDs of Bernoulli distributions.

Continuous weight recordings in a microcircuit model with plastic synapses under the A, BCPNN or B, STDP learning rule. Neural and synaptic parameters correspond to those in the scaled model. In both cases, two item neurons (ID = 1,2) are trained to form two or three associations, respectively (dashed connections are simulated but their weight development is not shown here). During training, neurons are stimulated to fire at 20 Hz for 2 s. We display the developing synaptic weight between specific item-context pairs (ID = 1 and 3 in the 2-association scenario) and (ID = 2 and 5 in the 3-association scenario), and compare the converged weight values between the two-association and three-association case under both learning rules, following a final readout spike at 11 s.

Plasticity modulation of a specific item-context pair enhances recollection and counteracts semantization. A, Context recall performance. One of the pairs (context-E, item-1) presented in the episodic memory task (compare Fig. 2A) is subjected to enhanced plasticity during encoding, resulting in the boosted recall rate (3 associations, Normal vs Biased, 20 trial average). B, Individual context retrieval contribution in the overall recall (3 associations). Retrieval is similar among the three contexts since plasticity modulation is balanced (left: Normal, κ = κ_normal; compare Table 1). However, when context-E is encoded with enhanced learning (with item-1), its recall increases significantly (right: Biased, κ = κ_boost; compare Table 1). C, Weight distributions of the NMDA weight component. Encoding item-1 with context-E under modulated plasticity yields stronger synaptic weights [3 association, α,β (light red, highly overlapping distributions) vs γ (dark red)]; ***p < 0.001 (Mann–Whitney, N = 20 in A, B, N = 2000 in C)]. Error bars in A, B represent SDs of Bernoulli distributions. Weight distributions of one, two, three-α,-β, and four associations in C show significant statistical difference (p < 0.001, Mann–Whitney, N = 2000).