Cellular and synaptic mechanisms of learning in cortical circuits. (360G-Wellcome-095853_Z_11_A)
Genetically encoded calcium indicators combined with two-photon imaging enable the repeated measurement of response properties of individual neurons in the cortex of living animals through a cranial window. These indicators are also suitable for repeatedly recording activity at single synaptic inputs in vivo and, when combined with other markers, further allow determining the dynamics of synaptic structures (dendritic spines and axonal boutons). First, I will apply these methods in mouse visua l cortex to follow long-term changes in neuronal responses and associated spine and bouton reorganization, as well as changes in the visual properties of synaptic inputs in the same cells during experience-dependent plasticity induced by repeated episodes of monocular deprivation. This will enable me to relate synaptic rewiring to changes in neuronal response properties, and to determine which synaptic changes may underlie long-term information storage. Second, I will use the same methods to stu dy cortical changes during perceptual learning by training mice in visual discrimination tasks. By relating neuronal response changes to structural and functional synaptic modifications induced by perceptual improvements, I will test if similar mechanisms underlie this form of learning. Together, this work will give insights into the cellular and circuit mechanisms of learning and memory formation.
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Grant Details
Amount Awarded | 25000 |
Applicant Surname | Hofer |
Approval Committee | Neurosciences And Mental Health |
Award Date | 2012-01-27T00:00:00+00:00 |
Financial Year | 2011/12 |
Grant Programme: Title | Research Career Development Fellowship |
Internal ID | 095853/Z/11/A |
Lead Applicant | Dr Sonja Hofer |
Partnership Value | 25000 |
Planned Dates: End Date | 2013-04-18T00:00:00+00:00 |
Planned Dates: Start Date | 2011-12-19T00:00:00+00:00 |
Recipient Org: Country | United Kingdom |
Region | Greater London |
Sponsor(s) | Prof Trevor Smart |