Kim Gyeongtae, Kim Pilwon
Department of Mathematical Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
PLoS Comput Biol. 2025 Jul 7;21(7):e1013267. doi: 10.1371/journal.pcbi.1013267. eCollection 2025 Jul.
Engrams corresponding to distinct memories compete for retrieval in the CA3 region of the hippocampus, yet the detailed mechanisms underlying their formation remain elusive. Recent findings indicate that hippocampal inhibitory neurons display feature-selective firing patterns and diverse forms of synaptic plasticity, suggesting a crucial role in engram formation. Conventional CA3 attractor network models typically employ global inhibition, where inhibitory neurons uniformly suppress the activity of excitatory neurons. However, such models fail to capture the dynamics arising from sparse distributed coding or reflect inhibitory neurons' roles in the competition between engrams during memory retrieval. We propose a mechanism for engram formation in CA3 using a spiking neural network model that emphasizes heterosynaptic plasticity at excitatory-to-inhibitory (E-to-I) synapses. In our model, inhibitory neurons associate with specific neural assemblies during encoding and selectively inhibit competing engrams during retrieval. Driven by a simplified feedforward dentate gyrus (DG), this mechanism generates sparse, distributed engrams in CA3. This representation allows us to examine the effects of selective inhibition on pattern completion across various conditions, including partially overlapping engrams. Simulations show that selective inhibition substantially enhances recall stability and accuracy compared to global inhibition alone. Furthermore, emergent activity patterns across DG, CA3, and CA1 of the model replicate experimental signatures of pattern separation and completion. These results suggest that assembly-specific inhibition mediated by heterosynaptic plasticity could provide a parsimonious mechanism for engram formation and competition in CA3, offering testable predictions for future experiments.
与不同记忆相对应的记忆痕迹在海马体的CA3区域竞争提取,但它们形成的详细机制仍不清楚。最近的研究结果表明,海马体抑制性神经元表现出特征选择性放电模式和多种形式的突触可塑性,这表明其在记忆痕迹形成中起关键作用。传统的CA3吸引子网络模型通常采用全局抑制,即抑制性神经元均匀地抑制兴奋性神经元的活动。然而,这类模型无法捕捉稀疏分布式编码产生的动态变化,也无法反映抑制性神经元在记忆提取过程中记忆痕迹竞争中的作用。我们使用一个尖峰神经网络模型提出了一种CA3中记忆痕迹形成的机制,该模型强调兴奋性到抑制性(E-to-I)突触处的异突触可塑性。在我们的模型中,抑制性神经元在编码过程中与特定的神经集合相关联,并在提取过程中选择性地抑制相互竞争的记忆痕迹。在简化的前馈齿状回(DG)驱动下,这种机制在CA3中产生稀疏、分布式的记忆痕迹。这种表征使我们能够研究选择性抑制在各种条件下对模式完成的影响,包括部分重叠的记忆痕迹。模拟结果表明,与单独的全局抑制相比,选择性抑制显著提高了回忆的稳定性和准确性。此外,模型中DG、CA3和CA1的出现活动模式复制了模式分离和完成的实验特征。这些结果表明,由异突触可塑性介导的集合特异性抑制可能为CA3中记忆痕迹的形成和竞争提供一种简洁的机制,为未来的实验提供可测试的预测。