Mazes are an integral part of rodent behavioral research. In recent years, scientific data collected from maze studies have moved towards more cloud-based and electronic storage as opposed to traditional paper-based storage. Naturally, there are plenty of benefits to this, but also some limitations to consider. In this article, we discuss modern mazes with Shuhan He, founder of ConductScience.com, a scientific equipment site that includes the maze developer MazeEngineers.com.
Ruairi Mackenzie (RM): How can the cloud help improve the reliability of preclinical data?
Shuhan He (SH): In theory, a well-trained scientist would have no trouble collecting high quality data from a maze study. Let’s say that they are observing spatial memory in rodents - they would have a well defined key that constitutes different movements a rodent could make. All they would have to do is observe the rodent and keep a written tally of its movements.
I think that most scientists would have to concede that an automated version of themselves would be less likely to make an error when it comes to encoding data as described above. Reduced chance of an error is a primary benefit of automated software that records a rodent’s behavior within a maze, and creates usable data.
One key player in the maze market is video tracking, like the Noldus EthoVision technology. Such video tracking technology automatically records and tracks an animal’s movement, to the extent of being able to pinpoint the tail, center and head of a rodent. This is a flexible piece of kit that is able to track rodent movement in any type of maze, even when the background setting of an environment changes. The data is easy to sync up with compatible data acquisition and storage systems.
Video tracking technology goes hand-in-hand with cloud-based data storage solutions like BehaviorCloud. With this, data taken from rodent maze studies, for example, can be logged in an electronic notebook. Experiments can be plugged into the storage solution, allowing it to automatically extract and begin to analyze data before the experiment is even complete.
The main benefit of using cloud-based storage for preclinical data is the time it saves researchers and scientists. Later on, I will expand on this point some more.
RM: Is the cloud a secure environment for storing sensitive preclinical data?
SH: This is a completely understandable concern, and one which of course merits discussion before taking the decision to use cloud-based data storage systems. It has actually been shown that cloud-based storage is more secure than traditional hard drive storage.
As long as employees of a company know how to access the cloud securely and implement strong passwords, your preclinical data will always be safer there when compared to a local hard drive.
Data in the cloud is protected by a number of defenses, including:
Advanced firewalls that approve a data packet’s integrity
Effective intrusion detection using event logging - only authorized people will have access to your preclinical data
Encryption - data is always jumbled up and encrypted for any potential thief. Without the correct password or key, the data will be unreadable
Take a reputable source such as Amazon Web Services - they offer cloud-based computing platforms to individuals and businesses.
RM: How do you think that researchers will utilize the sharing capability of BehaviorCloud?
SH: I feel sure that BehaviorCloud and similar data storage systems will allow science to become more of a team game. As researchers from any part of the world can now be invited to view data and collaborate on projects stored in these systems, the relevant expertise will be applied to each study.
For example, let’s say that a study is conducted in the US on the way in which rodents huddle for warmth in their first weeks of life. If this data is uploaded to the cloud in real time and available for analysis, the US-based researchers could contact a scientist in the UK who is an expert on this topic. They would then be given the necessary details to access the cloud, and would be able to begin work on analyzing this dataset.
Before the provision of cloud-based storage systems, researchers would have had to travel out to other laboratories in order to participate in the studies of others. In this way, I think that many researchers will jump on solutions like BehaviorCloud to massively cut down the time needed to collaborate on studies.
RM: How can we encourage researchers to embrace solutions like automation and ELNs in their day-to-day research?
SH: As touched on previously, I think that the time saved on tracking and scoring data is the primary benefit to help sell the appeal of automated tracking software. All of our mazes integrate with these video tracking providers and it’s really important for the optimal function of mazes. For example, our advanced Labyrinth system requires integration with Ethovision so that the maze talks to the video tracking system, and vice versa, while also potentially integrating with optogenetics systems, meaning that the live neuron firing is interacting with the maze via the hub of Ethovision. This allows for smart mazes that test rodents based on live neuron data. The dream is an intelligent maze that tests rodents and interfaces with the brain directly.
Instead of spending hours ensuring that their experiment is being tracked properly, researchers can become much more efficient by letting the tracking software take care of their current study, while they prepare for a new one or come up with new ideas for other work.
Electronic lab notebooks (ELNs) are a considerable upgrade on the traditional paper notebooks, simply because they are less likely to get lost/destroyed. Your notes will remain untouchable in a cloud storage system for as long as you want them to. With the separation of notes into different experiments, it is an easy task to pull up notes you are interested in reading.
Imagine your traditional notebook, but with search and share functions!
I can see why many scientists and researchers would be hesitant to make the switch from traditional methods to automated experiment tracking and cloud-based storage systems. Ultimately though, video tracking and ELNs are capable of cutting down hours of time spent on experiments, and allow scientists to get through even more work than they thought possible.
Shuhan He was speaking to Ruairi J Mackenzie, Science Writer for Technology Networks