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Insect visual cognition and neural computation


   School of Biological and Behavioural Sciences

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  Prof Lars Chittka, Dr Daniel Bor  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

  • Supervisors: Prof Lars Chittka and Dr Daniel Bor
  • Funding: QMUL Principal's Studentship
  • Deadline: 31st January 2023

Research environment

The School of Biological and Behavioural Sciences at Queen Mary is one of the UK’s elite research centres, according to the 2021 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 180 PhD students working on projects in the biological and psychological sciences. Our students have access to a variety of research facilities supported by experienced staff, as well as a range of student support services.

Supervisors Chittka and Bor are international research leaders in human and insect cognition; they have over 300 publications between them, many in leading international journals such as Nature and Science. Their labs are furnished with cutting edge technology and computing equipment. Please see their lab web pages at: http://chittkalab.sbcs.qmul.ac.uk/Lars.html and https://www.neuroscience.cam.ac.uk/directory/profile.php?DanielBor. 

Training and development

Our PhD students become part of Queen Mary’s Doctoral College which provides training and development opportunities, advice on funding, and financial support for research. Our students also have access to a Researcher Development Programme designed to help recognise and develop key skills and attributes needed to effectively manage research, and to prepare and plan for the next stages of their career.

The supervisors have trained >30 PhD students, many of whom are now full professors at top international universities, since they receive outstanding training and have often published in leading international journals as part of their PhDs. 

Project description

One possibility is a project on high-efficiency, low energy visual information processing, using insects as a model. The rationale is that presently, supercomputers are spectacularly inefficient compared to biological brains in terms of energy consumption. IBM’s “Summit” supercomputer is hailed as one of the most energy-efficient – it runs at 13 Megawatts, weighs 340 tons and occupies 5600 square feet. The human brain weighs ~1kg, runs on 12W, yet easily outperforms any supercomputer. Insect brains are smaller still – a bee’s is ~1mm2, and runs on a drop of nectar – but delivers highly accurate long distance navigation, collision avoidance, face recognition, concept learning, numerical skills, tool use and high memory capacities for visual landmarks and objects.

Leveraging the principles of energy-efficient computing in miniature brains will revolutionise computer science and AI. A fundamental energy-saving principle in brains is to send (and store) information only when absolutely necessary, and the goal of this PhD project is to identify behavioural and computational strategies by which the bee brain achieves this. One way in which this could be achieved is by sequential scanning of salient target features in ways determined by the spatial arrangement of said features. Another is by selective attention – a sort of “inner eye” that focusses only on those aspects of incoming sensory information that is salient at any one time. In this PhD we study both “bottom up” (stimulus or event driven) attentional processes as well as “top down” processes, by which the central nervous system controls which visual targets are being sought and identified.

We explore the extent to which insect eyes can be viewed as biological event-driven cameras, and the extent to which such cameras can be made more efficient by leveraging principles of insect vision. We investigate attention as the biological equivalent of electronic foveation (as used in computerised visual recognition mechanisms) and we use computational modelling to understand the neural underpinnings of visual information processing in bees.

Funding

The studentship is funded by Queen Mary and will cover home tuition fees, and provide an annual tax-free maintenance allowance for 3 years at the UKRI rate (£19,668 in 2022/23).

For international students interested in applying, please note that this studentship only covers home tuition fees and students will need to cover the difference in fees between the home and overseas basic rate. Tuition fee rates for 2023-24 are to be confirmed. Details on current (2022-23) tuition fee rates can be found at: https://www.qmul.ac.uk/postgraduate/research/funding_phd/tuition-fees/

Eligibility and applying

Applications are invited from outstanding candidates with or expecting to receive a first or upper-second class honours degree or a masters degree in an area relevant to the project (biological sciences, genetics, genomics, behavioural neuroscience, psychology). 

Basic understanding and experience in statistical and data analysis would be an advantage, but not essential.

Applicants from outside of the UK are required to provide evidence of their English language ability. Please see our English language requirements page for details: https://www.qmul.ac.uk/international-students/englishlanguagerequirements/postgraduateresearch/

Informal enquiries about the project can be sent to Lars Chittka at [Email Address Removed]. Formal applications must be submitted through our online form by 31st January 2023.

The School of Biological and Behavioural Sciences is committed to promoting diversity in science; we have been awarded an Athena Swan Silver Award. We positively welcome applications from underrepresented groups.

http://hr.qmul.ac.uk/equality/

https://www.qmul.ac.uk/sbcs/about-us/athenaswan/

Apply Online


Funding Notes

The studentship is funded by Queen Mary and will cover home tuition fees, and provide an annual tax-free maintenance allowance for 3 years at the UKRI rate (£19,668 in 2022/23).
For international students interested in applying, please note that this studentship only covers home tuition fees and students will need to cover the difference in fees between the home and overseas basic rate. Tuition fee rates for 2023-24 are to be confirmed. Details on current (2022-23) tuition fee rates can be found at: https://www.qmul.ac.uk/postgraduate/research/funding_phd/tuition-fees/

References


Mediano, P. A., Rosas, F. E., Farah, J. C., Shanahan, M., Bor, D., & Barrett, A. B. (2022). Integrated information as a common signature of dynamical and information-processing complexity. Chaos 013115 (2022); https://doi.org/10.1063/5.0063384
Mediano, P., Ikkala, A., Kievit, R. A., Jagannathan, S. R., Varley, T. F., Stamatakis, E. A., ... & Bor, D. (2021). Fluctuations in neural complexity during wakefulness relate to conscious level and cognition. bioRxiv.
Loukola O.J., Perry C.J., Coscos L. & Chittka L. (2017) Bumblebees show cognitive flexibility by improving on an observed complex behavior. Science 355(6327): 833-836. DOI: 10.1126/science.aag2360
Luppi, A. I., Mediano, P. A., Rosas, F. E., Harrison, D. J., Carhart-Harris, R. L., Bor, D., & Stamatakis, E. A. (2021). What it is like to be a bit: an integrated information decomposition account of emergent mental phenomena. Neuroscience of Consciousness, 2021(2), niab027.
Peng F. & Chittka L. (2017) A Simple Computational Model of the Bee Mushroom Body Can Explain Seemingly Complex Forms of Olfactory Learning and Memory. Current Biology 27(2): 224-230. DOI: http://dx.doi.org/10.1016/j.cub.2016.10.054
Solvi C., Gutierrez Al-Khudhairy S. & Chittka L. (2020) Bumble bees display cross-modal object recognition between visual and tactile senses. Science 367, 910-912. DOI:http://doi.org/10.1126/science.aay8064 B13
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