Extended temporal association memory by inhibitory Hebbian learning
Hebbian learning of excitatory synapses plays a central role in storing activity patterns in associative memory models. Furthermore, interstimulus Hebbian learning associates multiple items in the brain by converting temporal correlation to spatial correlation between attractors. However, growing experimental evidence suggests that learning of inhibitory synapses creates "inhibitory engrams", which presumably balance with the patterns encoded in the excitatory network. Controlling inhibitory engrams may modify the behavior of associative memory in neural networks, but the consequence of such control has not been theoretically understood. Noting that Hebbian learning of inhibitory synapses yields an anti-Hebbian effect, we show that the combination of Hebbian and anti-Hebbian learning can increase the span of temporal association between the correlated attractors. The balance of targetted and global inhibition regulates this span of association in the network. Our results suggest a nontrivial role of anti-Hebbian learning and inhibitory engrams in associative memory.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Semantically-correlated memories in a dense associative model
I introduce a novel associative memory model named Correlated Dense Associative Memory (CDAM), which integrates both auto- and hetero-association in a unified framework for continuous-valued memory patterns. Employing an…
Image RetrievalmodelRetrievalTemporal SequencesHeLa-Mem: Hebbian Learning and Associative Memory for LLM Agents
Long-term memory is a critical challenge for Large Language Model agents, as fixed context windows cannot preserve coherence across extended interactions. Existing memory systems represent conversation history as unstruc…
Semantic SimilarityMemory-enriched computation and learning in spiking neural networks through Hebbian plasticity
Memory is a key component of biological neural systems that enables the retention of information over a huge range of temporal scales, ranging from hundreds of milliseconds up to years. While Hebbian plasticity is believ…
One-Shot LearningOut-of-Distribution GeneralizationQuestion AnsweringEmergence and maintenance of modularity in neural networks with Hebbian and anti-Hebbian inhibitory STDP
The modular and hierarchical organization of the brain is believed to support the coexistence of segregated (specialization) and integrated (binding) information processes. A relevant question is yet to understand how su…
H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks
The ability to base current computations on memories from the past is critical for many cognitive tasks such as story understanding. Hebbian-type synaptic plasticity is believed to underlie the retention of memories over…
Question Answering