In the neuroscience field the scientists aim to understand how the brain
works. In order to study the brain mechanisms underlying behaviour and cognition,
they perform standardized laboratory experiments with animal models.
The main goal of this Master Thesis is the development of an experimental
set-up to run behavioral experiments using rats in the DeLaRocha Lab
at IDIBAPS (Institut d’Investigacions Biomédiques August Pi i Sunyer) of
Barcelona. Here there are many people that are studying the brain and its
features. Every day the researchers makes hypothesis and try to demonstrate
it. In order to perform that, it is necessary to make many experiments.
Therefore, a system that can contain the rat, run the task and obtain results
is needed. Moreover, it has to control the task in an automatized way, to
show in real-time some useful information about the running task to the user
and to save all the data in the proper format to be read easily afterwords.
The entire system is programmed using Python and an Arduino boards to
communicate with the experimental devices, i.e. water valves, lights, speakers
and camera. The system monitors in real time and in a quantitative manner
the behavior of the animal and serves as an interface to the experimenter to
assess performance, statistic about responses, etc. To make everything works
the system has to be fast (real-time) in terms of communication between the
hardware, response of the devices and visualization of the data. All these
parts are organized to work together.
The majority of the experiments are based on Two Alternative Forced-Choice
(2AFC) tasks. In 2AFC, the subject receives a stimulus and after that, two
alternatives are presented. Only one is the correct choice. Normally, a reward
or a punishment are used after the decision, depending on the choice
(this strategy is also called Reinforcement Learning). Therefore, the environment
of the experiment has three ports: left, central and right. The right
and left one are used as alternatives while the center one is used to get the
task starts. Each of them has a infra-red beams to detect when the rats pokes
in/out, a LED that can be turn on/off and a metal tube for the water delivery as reward. Furthermore, there are two speakers, through which the sound
stimuli are delivered, and a big light that turns-on as a punishment for a
wrong choice. All the components are controlled as Finite State-Machines by
the Arduino board. It means that the states and the transitions are defined by
external input, e.g. by the computer. The latter is connected to the Arduino
board that controls the devices, to a camera that records the experiments,
and to a sound card to trig the stimulus. All these components need to work
jointly.
This Master Thesis will include the development of a video tracking system,
a feature of capital importance for certain studies, that has been missing in
the previous system’s that have been used at the laboratory. The algorithm
is specifically designated and developed for these kind of experiments with
rats. It is useful to tracks the head during the tasks for many application
such as to detect when a “Change of Mind” occurs. Many approaches of
foreground subtraction are exposed and commented. Then a novel adaptiveselective
background updating method is proposed to avoid some issue where
other methods fail. Afterwords, the method is used to track the position of
the rat. Finally, the algorithm is compared with the others methods in terms
of general problem of foreground detection. Then it is tested comparing the
tracking with the experiments results of a real task to obtain a measure of
accuracy and precision of this method.
All the details of the behaviour boxes where rats perform the tasks, the system
that controls the experiment and the video analysis are explained step by step
in this Master Thesis.
En col·laboració amb la Universitat de Barcelona (UB) i la Universitat Rovira i Virgili (URV)
