The StarMaze is an aquatic maze in which complex processes of decision making are demanded.



The aim of this apparatus is to analyze learning and memory capacities, as well as several other executive functions of rodents in a navigation context. The animal has to swim in an aquatic maze in order to reach the submerged platform or to find a reward in a dry version of the test. During the acquisition, rodents learn to navigate through the maze or to memorize a pathway thanks to visuals cues.


The Starmaze has been developed by Dr Laure Rondi-Reig in 2006 (Rondi-Reig et al., 2006 J.Neuro). It allows to test and identify navigation strategies on mice and to study hippocampal neuronal activity through electrophysiological recordings paired to behavioral analyses (Cabral et al., 2014). Several scientifical publications investigated new neuronal functions involved in navigation through the Starmaze (Fouquet et al., 2011, 2013, …).

Starmaze-principle-trio bis


In its aquatic version, the apparatus is composed of a tank divided on 5 alleys, which radiate from the pentagonal central part. One platform, the goal, is positioned just below the surface of the water. The aluminium frame that bears the tank, as well as the Starmaze structure are built in our premise. So, we can adapt the structure’s dimensions to your constraints and your needs.

The video camera is positioned on the ceiling, on an aluminium bar placed between two walls of the experimental room.

You can combine the analysis of the behavior on the Starmaze with optogenetic stimulation through our synchronization. This box allows to activate a laser by TTL according to the real-time performances of the animal or to its location in the Starmaze. Click on this link to access to the synchronized videotracking page.

Our rotation assistant allows the connected animal to move freely in the environment. We install our system on the camera bar in order to help the connected mice moving without constraint in the Starmaze. Click on this link to consult our rotation assistant page.


Water-Maze <–> Starmaze adaptation

If your laboratory is already equipped with a water-maze, we can adapt a Starmaze that will fit on your tank. No needs to dedicate one room for this test, we can adapt the size of the Starmaze with your tank.

Click on this link to access to the Water-Maze page.


Videotracking system

You can build your areas of interest (AOI) through simple and direct tools. During the installation, we set up AOI that you can modify freely. Our system detects the animal and communicates its coordinates to our POLY software. The software processes these coordinates, calculates performances and activates electronic outputs if necessary.

The video is automatically recorded during the experiment. In this way, you can redefine areas or modify parameters of animal detection in order to obtain complementary results. For more information on our tracking system, click on this link.

Videotrack with ROI

POLY: management of experiments, real-time calculation of performances

On the basis of the animal’s location transmitted by our videotracking system, our POLY software displays in real-time sets of output variables e.g. the number of entries in the alleys, the distance travelled and the time spent in each AOI. Moreover, the software computes specific behaviors developed for the Starmaze, as the location and the navigation score. These variables facilitate an immediate evaluation of the spatio-temporal memory of the animal.

POLY_FILES: Data analysis

Our software can calculate 2 types of variables:

  1. qualitative analysis of pathways and distribution of time spent in the alleys,
  2. quantitative analysis of locomotion and performances specific to the Starmaze.

Please find a non-exhaustive listing of variables that you can get: trial duration, total distance travelled as well as distance travelled in each AOI, time spent in each AOI, crossing score, location score, ..etc.


Starmaze forhuman

A virtual version of the Starmaze has been developed for adults (Igloi et al., 2009) and children (Bullens et al., 2010). In aged subjects, it allows differentiating Alzheimer disease front fronto-temporal dementia (Bellassen et al., 2012). This model also allows to characterize the neuronal network underlying spatial and navigation memories (Igloi et al., 2010 ; 2015).