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Shuhan He MD Administrator
Shuhan He MD is an Emergency Medicine Physician at Harvard Emergency Medicine Department at the Massachusetts General Hospital. Dr. He is interested in making better tools to Conduct Science, especially regarding scientific outcomes. He is the founder of MazeEngineers.com, Conductscience.com, Sciencen.com and an array of tools to help scientists get the job done better and with more translation to the patient at the bedside.
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Shuhan He MD Administrator
Shuhan He MD is an Emergency Medicine Physician at Harvard Emergency Medicine Department at the Massachusetts General Hospital. Dr. He is interested in making better tools to Conduct Science, especially regarding scientific outcomes. He is the founder of MazeEngineers.com, Conductscience.com, Sciencen.com and an array of tools to help scientists get the job done better and with more translation to the patient at the bedside.
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Episodic Memory

Human long-term memory can be broadly classified into declarative memory and procedural (implicit) memory; The former category involves conscious and intentional recollection of factual information, previous experiences, and concepts. The declarative memory, or explicit memory, is further divided into episodic and semantic memory.

Endel Tulving first coined the term episodic memory in 1972, describing it as,

“Episodic memory receives and stores information about temporally dated episodes or events, and temporal-spatial relations among these events.” (Tulving, 1972)

He distinguishes episodic and semantic memory based on remembering versus knowing principle. While semantic memory is concerned with factual information (structured record of facts, concepts, and skills), episodic memory is concerned with remembering specific past events at a particular time and place. He further adds that episodic memory retrieval also feeds back as input to the system that results in changes in the episodic memory store (episodic learning). Episodic memory recollection, as defined by Tulving, is defined by three key properties: a subjective sense of time, connection to the self, and autonoetic consciousness.

Episodic memory in humans fully develops around the age of 4 years (Scarf, Gross, Colombo, & Hayne, 2011), and is retrieved differently among young and old humans (Maguire, 2003; Piolino et al., 2010). In animal models, episodic memory assessments are done using their episodic-like memory (Clayton, Salwiczek, & Dickinson, 2007), which meets Tulving’s definition. Apparatuses such as Fear Conditioning Chamber and Radial Arm Maze are often employed using protocols that require the rodent to recall an experience (For more behavioral research apparatus and equipment visit MazeEngineers). While animal models have extensively contributed to our understanding of learning and memory, the reliance on animal episodic-like memory has received some criticism. A popular criticism, based on the Bischof-Kohler hypothesis (Suddendorf, & Corballis, 1997), suggests that unlike humans, animals are incapable of mental time travel, a key feature of episodic memory recollection. This incapacity translates to experimentally observed behaviors in animals to be resultant of their immediate needs rather than anticipated future needs. Another argument suggests that animals could possibly be displaying Garcia-type learning rather than relying on episodic-like memory in tasks that make use of consumable rewards.

Virtual Reality and Human Memory Research

While animal models have their advantages, translation of results to human applications always needs to be done with certain considerations. On the other hand, real-world human experiments, however, can be affected by a variety of factors including cost and accessibility to participants. Further, self-scored questionnaires and ancillary tests that rely on the participant’s honesty and understanding (For digital health research tools visit Qolty) may not always provide a complete picture or sufficient information. In these scenarios, virtual reality (VR) offers an alternative, or addition to traditional approaches, that tends to be just as effective as real-world experiments. Further, the variety of virtual reality systems available and the flexibility they offer make them an excellent choice.

Pflueger, Stieglitz, Lemoine, and Leyhe (2018) found that their immersive VR based assessment of older adults provided a more accurate estimation of everyday memory demands. Pflueger et al.’s virtual environment (VE) involved a kitchen scene, an environment that is experienced in everyday life, with tasks that relied on common cognitive demands. As opposed to the California Verbal Learning Test, that uses learning of arbitrary word associations, the ecologically relevant VE provided an age-fair estimate of episodic memory in the healthy older adults. Despite both tests being structurally comparable, performance decrements were primarily observed in the California Verbal Learning Test.

Another study performed by Howett et al. (2019) showcased the promising potential of VR assessments in early detection of Alzheimer’s disease. The study involved patients with mild cognitive impairment with and without cerebrospinal fluid biomarkers (MCI+ and MCI-, respectively). Participants, which also included healthy controls, were evaluated in an immersive virtual reality path integration task using an open, grassy field VE. Compared to healthy controls, MCI patients displayed significantly larger absolute distance errors with the parameter value being significantly larger in MCI+ patients than MCI- patients. The VR task that was based on the central role of the entorhinal cortex in navigation exhibited higher diagnostic sensitivity and specificity for differentiating biomarker than the traditionally used pen-and-paper cognitive tests.

As seen with Pflueger et al. and Howett et al.’s study, conventional neuropsychological tools though useful, tend to offer a partial measure of the episodic memory. This limitation can be attributed to their decontextualized and simplified design that does not fully exploit the complex system’s capacity. In neurodegenerative diseases such as Alzheimer’s disease, episodic memory is the first to be affected. Thus, given the important role that episodic memory plays in everyday life and the fragility of this memory, it is essential that investigation of it is done in spatially and temporally rich naturalistic contexts which virtual reality offers.

Given episodic memory’s subject-specific nature, that makes verification of recollected information difficult; investigations often rely on spatial navigation tasks that are quite similar to the protocols used in rodent based apparatuses such as the Morris Water Maze and the Radial Arm Maze. Of all navigation strategies, sequential egocentric strategies, similar to allocentric spatial learning, require memorization of body turns and sequential ordering of events within a maze which share functional similarity to episodic memory (Arleo, & Rondi-reig, 2007; Iglói, Zaoui, Bertho