Periodic Reporting for period 1 - FISHNAV (Following a path of breadcrumbs: How fish recognize landmarks during navigation)
Reporting period: 2015-08-31 to 2017-08-30
Recognition of 3D object can be completely flexible, whereby an object can be recognised regardless of the viewing position of the observer (view-invariant), partly flexible in which recognition is somewhat limited by viewing position (view-dependent), or completely inflexible and recognition can only occur when the observed view matches that of a learned template (view-dependent template matching). When presented with new objects, humans have a flexible, but view-dependent system and there are limits to how much the appearance of an object can change before recognition breaks down. Some insects on the other hand, appear to use a template matching system. Using template matching, a large number of snapshots of an image would need to be stored in order for the observer to recognise the object under different conditions. This would require a significant memory capacity. Yet insects have demonstrated that they can reliably recognise objects for important tasks such as navigation. To achieve this, insects appear to reduce the number of snapshots required when navigating using a behavioural adaptation called ‘active vision,’ in which they follow previously learned paths between landmarks and reduce the number of views that they actually encounter.
The objectives of this Marie Skłodowska Curie Action (MSCA) has been to determine a) whether fish have a flexible recognition system, and b) if they can use behavioural adaptations such as active vision to reduce the processing burden of the task. Fish were used as they lack a cortex, the area of the brain associated with complex mammalian behaviour, yet they have also demonstrated other behaviours typically associated with advanced processing abilities (e.g. social learning, numeracy). This project used behavioural experiments with a species of coral reef fish, Rhinecanthus aculeatus, to test the two primary research questions. The long-term impact of this fundamental research is to improve our understanding of the brain; particularly how brain architecture influences behavioural capabilities. This project may also inform computer vision systems as it suggests there are methods of recognition that don’t require extensive processing capacity.
WP2 explored the movement trajectories of fish in relation to local objects. Although the use of active vision was not explicitly tested, it was found that fish do alter their movement trajectories based on the visibility of targets and that they are far less efficient at locating food when visibility is poor. This work has resulted in one submitted manuscript and is expected to produce further conference presentations and manuscripts, including one detailing new analysis methods.
A further four publications were produced during this project through collaborations, and two review articles, as part of the career development plan of the Fellow. The Fellow undertook training in programming as part of this project, which has led to the development of a follow-on project examining the movement behaviour of fish in their natural environment and the development of two state-of-the-art fish tracking and terrain mapping systems. Throughout this project, the Fellow has contributed to the transfer of knowledge through outreach with the general public, teaching, and advising of students.
This project has also resulted in two review papers which describe specialisations in the visual system of a species of fish with a unique hunting strategy, and what is currently known about abstract concept learning in fish. Both of these reviews not only synthesise information from a large number of other studies, but detail research directions for future work. An additional four papers were published on related topics as part of international collaborations. These studies add to our knowledge of fish visual behaviour and visual signal processing.
The impact of this project was increased through sharing results within the academic community as well as the general public and students. During this MSCA, the Fellow captured the interest of the general public with work showing that fish could learn to differentiate pictures of human faces. The Fellow participated in over 30 interviews with national and international media sources and results were discussed in over 100 outlets in print, TV, and radio. This news reached a range of audiences from all over the world including the U.K. Canada, Australia, U.S. Ireland, India, Germany, Russia, and many more. The impacts of this coverage are likely to be long lasting as it can foster interest and empathy in science and nature in the general public. The Fellow also communicated more directly with students through public lectures, personal video chats, and the University of Oxfords Pathways Program. A website has been created to provide non-specialist explanations of research.