Computational Model of Episodic Memory Formation, Recalling, and Forgetting

  • Rahul ShrivastavaEmail author
  • Sudhakar Tripathi
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 34)


Our motivation in this paper is to provide a computational model of episodic memory, which is agent and domain independent like human being. Proposed model is smart enough to encode experiences in response to continuous sensory input and able to store in the form of an episode of temporally correlated events based on reward and motivation of agent. In proposed mechanism, event (personal experience) is subdivided into its constituent’s coactive activities, where each constituent activity is shared among different events with certain participation strength in different events. Model dynamically allows forgetting of unimportant activities and events based on participation strength which is recalling and reward dependent. This model extracts the key event based on reward which further incorporates in episode formation by clustering of temporal and correlated events with the key event. Recalling is also supported on coming of noisy and erroneous cue or incomplete pattern. To validate the proposed model, an empirical study was conducted, where the proposed episodic memory model is evaluated based on the recall accuracy using partial and erroneous cues and deployed in a car race environment, where agent learns the episode with reward to play by itself. The analysis shows that the proposed model significantly associated with encoding and recalling of events and episodes even with incomplete and noisy cues.


Episodic memory Encoding Recalling Forgetting Reward learning 


  1. 1.
    Tulving, E.: Organization of memory: quo vadis? In: Gazzaniga, M.S. (ed.) The Cognitive Neuroscience, pp. 839–847 (1995)Google Scholar
  2. 2.
    Rugg, M.D., Kaia, L.V.: Brain networks underlying episodic memory retrieval. Curr. Opin. Neurobiol. 23(2), 255–260 (2013)CrossRefGoogle Scholar
  3. 3.
    Vertes, R.P., Kocsis, B.: Brainstemdiencephalo-septohippocampal systems controlling the theta rhythm of the hippocampus. Neuroscience 81, 893–926 (1997)Google Scholar
  4. 4.
    McGaugh, J.L.: Memory—a century of consolidation. Science 287, 248–251 (2000)CrossRefGoogle Scholar
  5. 5.
    Squire, L.R.: Declarative and nondeclarative memory: multiple brain systems supporting learning and memory. J. Cogn. Neurosci. 4(3), 232–243 (1992)CrossRefGoogle Scholar
  6. 6.
    Janie, B., Thomas, S.: Recalling yesterday and predicting tomorrow. Cogn. Dev. 20(3), 362–372 (2005)Google Scholar
  7. 7.
    Shastri, L., Venkat, A.: From simple associations to systematic reasoning: a connectionist representation of rules, variables and dynamic bindings using temporal synchrony. Behav. Brain Sci. 16(03), 417–451 (1993)CrossRefGoogle Scholar
  8. 8.
    Amaral, D.G., Witter, M.P.: Hippocampal formation. In: Paxinos, G. (ed.) The Rat Nervous System, 2nd edn, pp. 443–493. Academic Press, London (1995)Google Scholar
  9. 9.
    Rolls, E.T.: Information representation, processing and storage in the brain: analysis at the single neuron level. Neural Mol. Bases Learn. 503–540 (1987)Google Scholar
  10. 10.
    Atallah, H.E., Frank, M.J., O’reilly, R.C.: Hippocampus, cortex, and basal ganglia: Insights from computational models of complementary learning systems. Neurobiol. Learn. Mem. 82(3), 253–267 (2004) Google Scholar
  11. 11.
    Edmund, T.R.: A computational theory of episodic memory formation in the hippocampus. Behav. Brain Res. 215(2) (2010)Google Scholar
  12. 12.
    Gilbert, P. E., Kesner, R.P., Lee, I.: Dissociating hippocampal subregions: a double dissociation between dentate gyrus and CA1. Hippocampus. 11(6), pp. 626–636 (2001)CrossRefGoogle Scholar
  13. 13.
    Hermann, E.: Remembering Ebbinghaus. Contemp. Psychol. 30(7), 519–523 (1985)Google Scholar
  14. 14.
    Michael, A.Y., Zachariah M. R.: Competitive trace theory: a role for the hippocampus in contextual interference during retrieval. Front. Behav. Neurosci. 7, 107 (2013)Google Scholar
  15. 15.
    Budhitama, S., Ah-Hwee, T.: Neural modeling of sequential inferences and learning over episodic memory. Neurocomputing 161, 229–242 (2015)CrossRefGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science & EngineeringNational Institute of TechnologyPatnaIndia

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