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Automation of the Y-maze requires accurate detection of arm entries and often involves analysis of the sequence of movements between the arms

ANY-maze provides both these features. Whole body tracking ensures arm entries are scored in a way analogous to the traditional four-paws-in-the-arm rule, while sequences provide a mechanism to automatically score such things as spontaneous alternations. Full details can be found on the Benefits tab, below.

On the other tabs you'll find videos of Y-maze tests, recommended equipment and a list of results that are especially useful in this test.

Page Intro picture

Accurate scoring of arm entries

A key element of tests in the Y-maze is analysis of the sequence of movements between the arms. But if arm entries aren’t scored accurately then any such analysis will clearly be incorrect.

ANY-maze’s whole body tracking allows you specify precisely when an arm entry should be scored. For example, specifying an arm entry as occurring when 80% of the animal’s body is in the arm, equates very well with the traditional four-paws-in-the-arm rule.

Scoring movements between arms

ANY-maze includes the ability to define sequences, which as the name implies, detect sequences of movements between different parts of the maze.

In the Y-maze, sequences, together with calculations, can be used to automatically score behaviours such as spontaneous alternations.

Scoring movements between arms picture

Flexible zone designs

In some Y-maze paradigms, the animals are denied access to one of the arms during their first exposure to the maze and then allowed access to this ‘novel’ arm during a subsequent test.

It’s common to balance the arm that is blocked between treatment groups, so for some animals it will be on the left, while for others it will be on the right. This video shows how easy it is to set up zones like this in ANY-maze.

Viewing the animal's track

ANY-maze can plot the animal’s track as a line or as a heat map.

Heat maps indicate how much time the animal spent in different parts of the apparatus and can either show data for individual tests (as shown here) or averaged data for different groups.

In this example, we can see that the animal spent most time at the end of the start arm and in the centre of the maze.

Viewing the animal's track picture