Knowledge Graphs and Cognitive Memories

Declarative and nondeclarative memories are two components of the brain’s long-term memory, where declarative memory can be further divided into semantic memory, episodic memory, and autobiographic memory [32]. Declarative memory refers to the memory of facts and events which can be recalled and described with language. Whereas semantic memory refers to conscious recollection of factual knowledge and concepts, episodic memory is an intentional retrieval of previous events with their spatial and temporal contexts. The difference between episodic memory and autobiographic memory is that autobiographical memory is only associated with specific personal experiences. Nondeclarative memory, on the other hand, is an unconscious memory, including perceptual and procedural memories, which are related to the acquisition of better skills and formation of habits. Figure 1.3 demonstrates a simple classification of the brain’s different types of memory.

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Figure 1.3: Basic classification of human memory functions.

A technical realization of semantic memory is a collection of semantic triples, e.g., the triple (California, locatedIn, USA) storing the factual knowledge that California locates in the USA. The collection of quadruples, or semantic triples accompanied with times-

tamps, realizes the episodic memory, e.g., the quadruple (Jack, diagnosedWith, Diabetes,

Feb10) recording the fact that Jack was diagnosed with diabetes on February 10. A se- mantic knowledge describing the current health condition of Jack can be derived from the

quadruple by ignoring the temporal information, namely(Jack, diagnosedWith, Diabetes).

As motivated previously, a 3-way semantic tensor, with dimensions for subjects, predi- cates, and objects, is a suitable representation of semantic memory, while a 4-way episodic tensor with additional timestamp dimension is suitable a data representation of episodic memory. The tensor view of declarative memory is not efficient and compressed. Hence, a biologically more plausible view of declarative memory is proposed in [113]. In this framework, declarative memory tenors are first decomposed, and each generalized entity, predicate, and timestamp obtains a unique latent representation, such that memory tensors can be approximately reconstructed from latent representations. The tensor decomposi- tion approach provides a compressed form of declarative memory, and more advanced, knowledge generalization becomes plausible by inferring new semantic triples or episodic quadruples using latent representations.

The tensor decomposition framework for declarative memories is biologically plausible since generalized entities and distributed representations can find their counterparts in the brain, which are widely studied in cognitive neuroscience. Entities for abstract and symbolic concepts are encoded as concept cells resided in the medial temporal lobe (MTL)

- the hippocampus and its surrounding cortex [91]. Concept cell represents one neuron or a separate assembly of neurons that become activated when perceiving a specific concept. The activation of the concept cell corresponding to a specific concept can be triggered by different aspects of the same concept, e.g., the visual or acoustic features of the concept, since there exist links between the concept cell and cortical areas that store different aspects of the corresponding concept. For example, concept cell is also called as Jennifer Aniston cell, since it might be invoked by Jennifer’s appearance, voice, or even the movies she starred.

Furthermore, the entity representations in the tensor decomposition framework resem- ble the distributed representations of concepts stored in different cortical areas. Reversely, the activation of a concept cell brings the conscious retrieval of various attributes of the corresponding concept. The localized storage of concepts and distributed storage of con- ceptual representations form a flexible system of long-term memory, which even contributes to perception, language, and thought [55].

Cognitive studies suggest that semantic and episodic memories are interdependent both at encoding and retrieval phases [36]. Baddeley [8] argues that semantic memory might arise from blurred episodic memory by losing temporal information, in the sense that re- peatedly experienced episodic events become consolidated, and during conscious retrieval, only decontextualized events can be recalled. For example, by consistently noticing that Jack is diagnosed with diabetes on February 10, one becomes aware that Jack has di- abetes. As proposed in [113, 112], in the tensor decomposition framework of declarative memories, the technical realization of decontextualization of episodic memory and the tran- sition from episodic memory to semantic memory are implemented via marginalization in the time dimension. The marginalization is performed using the latent representations of

timestamps. However, since semantic memory reflects the factual knowledge of current

timestamp, marginalization should be implemented while minding the end timestamps of repeatedly experienced episodic events [69].

Until now, we have assumed that the distributed representations of timestamps only come from the tensor decomposition of the episodic tensor, and the semantic decoding of episodic events is realized by marginalization over time dimension. However, according to the definition of episodic memory, it refers to the memory of specific events and re- lated contexts, such as spatial, temporal, visual information, and associated emotion, etc. Previous theory of episodic memory, such as the Hippocampal Memory Indexing Theory (HMIT) [109], suggests that episodic events are stored by forming time indices in the brain

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that connect to the representation layer. Activation of the time indices brings the rec- ollection of previous experiences. However, the hippocampal memory indexing theory is subsymbolic, which contradicts the fact that episodic memory is declarative.