Dissecting the neural circuits for visual perceptual learning (360G-Wellcome-211258_Z_18_Z)

£1,317,544

Visual perceptual learning (VPL) is an improvement of performance of a visually guided task as a result of visual experience. However, it is not well understood whether improvements are due to changes in lower-level visual or in higher-level association brain areas, and whether improvements can transfer to untrained visual features and tasks. Here I propose to dissect the neural circuits of VPL in mice and test the theory that VPL consists of both: 1) enhanced task-independent encoding of sensory features in low-level areas in cells with selective feature-preference, generalising poorly to different features. 2) enhancement of task-relevant features, initially in higher level areas with broad feature-preference, generalising to a broader range of features. Mice can quickly learn a visual discrimination task, which I will combine with cell-type specific 2-photon calcium imaging and optogenetic manipulation of neural activity. I hypothesize that PV interneurons are necessary for task-independent learning, while SOM interneurons can gate feedback from high-level areas to boost task-relevant features. I will address the following specific aims: 1) identify the changes during VPL in visual and association areas during learning 2) determine the role of task-engagement in VPL 3) determine how VPL generalises to untrained or previously irrelevant features.

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Grant Details

Amount Awarded 1317544
Applicant Surname Poort
Approval Committee Sir Henry Dale Fellowship Interview Committee
Award Date 2018-06-06T00:00:00+00:00
Financial Year 2017/18
Grant Programme: Title Sir Henry Dale Fellowship
Internal ID 211258/Z/18/Z
Lead Applicant Dr Jasper Poort
Partnership Name Royal Society/Wellcome Trust Sir Henry Dale Fellowship
Partnership Value 1317544
Planned Dates: End Date 2025-05-01T00:00:00+00:00
Planned Dates: Start Date 2019-01-01T00:00:00+00:00
Recipient Org: Country United Kingdom
Region East of England
Sponsor(s) Prof Mark Johnson