Barnes maze and other HVS-tracked mazes

The question

Last stop on the tour, and it's a busy one. What if you want a spatial test without swimming? You're watching Morris Water Maze Software Guide, over at morriswatermazesoftware.com.

Meet the Barnes maze and other HVS-tracked mazes

The Barnes maze is a bright, round table with holes around the edge; one hole leads to a dark escape box. Animals learn its location from room cues, like the water maze but dry. HVS Image tracking also covers the elevated plus maze, the Y-maze, a dry water maze, three-chamber sociability and object recognition, so one system can run a whole battery.

How it runs

Here's how it plays out. First, use bright light and, if needed, mild noise as gentle motivation to escape. Next, train over several days from the centre of the table. Then, remove or close the escape box for a probe trial. Finally, record hole visits (errors), path and latency.

Strengths and limits

So what's in it for you? No swimming stress, which suits mice and some strains well. Errors at holes give a discrete spatial accuracy score. Shares analysis logic with the water maze. Where does it bite? The motivation to escape is weaker, so some animals simply explore. Serial strategies (checking each hole in turn) can solve it without a map.

What to measure

Now for the numbers, my favourite bit. Primary errors and primary latency: holes visited before the first visit to the goal. Search strategy class: direct, serial or random, mirroring water maze strategy identification. Time near the goal hole in the probe: a proximity measure. Path efficiency: as in the pool. If a mouse finds the goal fast by checking every hole clockwise, the latency improves but the strategy classification shows serial searching, not spatial memory.

The takeaway

Short version: search strategy class and its neighbours tell you how the task was done, not just how fast. The full transcript is on this page, with sources.