Deep learning method for gesture tracking and neural activity segmentation in mice
In order to find a causal relationship between neural activity and physical activities, neuroscientists usually record animals' behavior and their brain activity in a controlled environment. Then they manually annotate the behavioral/physical activity and neural activity data. It is an inefficient, time-consuming process that is subjective and conducive to human error, as it depends on who is recording the observations and therefore is not reproducible.
In recent years, there has been a growing trend toward automated processing of this data to improve efficiency and reproducibility. This is precisely the approach that the researcher Waseem Abbas has proposed in his thesis as part of the UOC's doctoral program in Network and Information Technologies. Part of the research has already been published in three scientific journals: