Selective attention in predatory insects
Lead Research Organisation:
University of Cambridge
Department Name: Zoology
Abstract
Theme: World-Class Underpinning Bioscience
The PhD project would be placed in a lab that investigates the neural basis of target tracking and interception in predatory invertebrates using a multilevel approach (behaviour, microscopy and electrophysiology). The project itself will specifically investigate selective attention in insects that use visually targeted predation. The focus would be to understand the conversion of visual sensorimotor information that underlies predation in environments with competing visual stimuli.
Investigation of neuronal activity could be achieved through either electrophysiological experiments or imaging of cells pre-loaded with calcium or voltage indicators. Electrophysiological experiments can produce large amounts of data in a short period of time. Raw data will require automatised spike sorting in response to visual stimulation and, in some instances, principal component analysis and cluster analysis. Similarly, neuronal activation reported by calcium or voltage indicators will need to be measured in an automatic or semi-automatic fashion, by extracting luminance values from raw images. This would produce similarly large datasets that will need substantial computational methods to be analysed.
The PhD project would be placed in a lab that investigates the neural basis of target tracking and interception in predatory invertebrates using a multilevel approach (behaviour, microscopy and electrophysiology). The project itself will specifically investigate selective attention in insects that use visually targeted predation. The focus would be to understand the conversion of visual sensorimotor information that underlies predation in environments with competing visual stimuli.
Investigation of neuronal activity could be achieved through either electrophysiological experiments or imaging of cells pre-loaded with calcium or voltage indicators. Electrophysiological experiments can produce large amounts of data in a short period of time. Raw data will require automatised spike sorting in response to visual stimulation and, in some instances, principal component analysis and cluster analysis. Similarly, neuronal activation reported by calcium or voltage indicators will need to be measured in an automatic or semi-automatic fashion, by extracting luminance values from raw images. This would produce similarly large datasets that will need substantial computational methods to be analysed.
Organisations
People |
ORCID iD |
Matthias Landgraf (Primary Supervisor) | |
Sergio Rossoni (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
BB/M011194/1 | 01/10/2015 | 31/03/2024 | |||
2411295 | Studentship | BB/M011194/1 | 01/10/2016 | 31/03/2021 | Sergio Rossoni |