The Morris Water Maze (MWM) is practically synonymous with place cells, the spatially-tuned neurons of the hippocampus believed to be central to spatial navigation. Place cells fire preferentially when animals are in different spatial locations, or in some cases, orientations. These cells are believed to collectively form a “cognitive map” that serves to guide spatial navigation. The discovery of place cells is credited to John O’Keefe in 1971(1), who won the Nobel Prize for his discovery jointly with colleagues May-Britt and Edvard Moser in 2014 (2). More recent work on place cells suggests that nonspatial information is stored and referenced in a similar manner to spatial information, whereby place cells serve as a reference point for locating memories stored in the cortex, rather than as a reference point in physical space (3,4). Early studies on place cells by O’Keefe were largely performed on elevated arm mazes, including the T-Maze and Radial Arm Maze (RAM) (5,6). Animals are commonly incentivized to explore such mazes using food deprivation. A hungry animal will search each arm of the maze for a food reward, and various tests can be run to test the animals’ memory capacity for the spatial location of the food reward.
In early 1980s, Richard Morris, a researcher studying spatial navigation in rats, developed a new kind of test for spatial memory, which he published in 1984 under the title “Developments of a water-maze procedure for studying spatial learning in the rat” (7). This new “maze”, was actually a pool of water with a submerged platform hidden from view. The Morris Water Maze came to be used for variety of navigation tasks which the researcher tailors to best parse specific questions at hand. The MWM relies on both rats’ natural swimming ability and their dislike of water, which respectively enable and motivate rats to search the water pool for a hidden, raised platform. The MWM offers several advantages over food-deprivation motivated tasks. Firstly, all trials are equal with respect to the animal’s motivation to complete the task, as opposed to food-motivated tasks, where satiation can influence drive. Secondly, the size of an animal does not influence the degree of motivation, where the assumption that larger animals require more food before reaching satiety holds true (8).
The work of neuroscientists in the 1970s and 1980s set the groundwork for the techniques and standards for hippocampal research now and in the future. Early behavioral studies were pivotal to our understanding of the relationship between neuronal activity and behavior. Not only did these tests lay the groundwork for much of modern Neuroscience, they also effectively set the standard by which future work would measure its relevance and accuracy. While recording techniques have evolved and increased in complexity over time (9), the standard behavioral tests serve as a constant to validate new findings.
In one way however, the behavioral tests are evolving as well. It has historically been common practice for researchers to rely on machine shops at their institutions for behavioral apparatus, and these shops can charge from around $2,000 to $5,000 per maze, according to some working in behavioral labs. Because there is inherently some variability between apparatus, the current practice introduces a potential confound for comparing results across institutions, labs and studies. A new company, Maze Engineers, is paving the way future behavioral studies. In their own words, their goal is: “big data – for neuroscience” (10). Not only does this startup offer standardized apparatus like the Morris Water Maze at a reduced price to academic researchers, they provide a valuable service to privately funded researchers who might otherwise find it more difficult and expensive to access quality behavioral assays. This furthers the ability of scientific research to excel in many settings, and still provide validated, replicable behavioral results.
The field of neuroscience has matured rapidly in the last 50 years. As interest in AI increases, industries of all kinds have rushed to develop their own research in support of better understanding and harnessing the power of the brain and AI. Companies that understand and effectively serving these needs will be leading the charge.
O’Keefe J and Dostrovsky J. “The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat.” Brain Research. 34(1):171-175. PMID: 5124915.
Burgess N (2014). “The 2014 Nobel Prize in Physiology or Medicine: A Spatial Model for Cognitive Neuroscience.” Neuron. 84(6): 1120-1125. PMCID: PMC4276740
Smith DM and Mizumori SJ (2006). “Hippocampal place cells, context and episodic memory”. Hippocampus. 16(9):716-729. PMID: 16897724
Leutgeb S, et al (2005). “Independent spatial and episodic memory in hippocampal neuronal ensembles.” Science. 309(5734): 619-623. PMID: 16040709
O’Keefe J (1976). “Place units in the hippocampus of the freely moving rat.” Neurology. 51(1): 78-109. PMID: 1261644
Barnes CA, McNaughton BL, O’Keefe J (1983). “Loss of place specificity in hippocampal complex spike cells of senescent rat.” Neurobiology of Aging. 4(2):113-119. PMID: 6633780
Morris R (1984). “Developments of a water-maze procedure for studying spatial learning in the rat.” J Neurosci Methods. 11(1):47-60. PMID: 6471907
Vorhees CV and Williams MT (2014) . “Assessing spatial learning and memory in rodents.” ILAR J. 55(2):310-332. PMCID: PMC4240437
Stevenson IH and Kording KP (2011). “How advances in neural recording affect data analysis.” Nat Neuroscience. 14: 139-142. PMID: 21270781
“Frequently Asked Questions”. Maze Engineers, referenced Nov 9, 2017.
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