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Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Professor Paul Tiesinga, Radboud University, The Netherlands
- Second opponent: Associate professor Maximiliano J. Nigro, Norwegian University of Science and Technology,
- Third member and chair of the evaluation committee: Associate professor Jørgen Sugar, University of Oslo
Chair of the Defence
Professor Svend Davanger, University of Oslo
Principal Supervisor
Professor Trygve B. Leergaard, University of Oslo
Summary
Sensory signals from our environment and somatomotor signals from the body organise as patterns in the brain mirroring the spatial position of the sensory surface. This organisation pattern is known as topography. Topographical organisation has been thoroughly investigated in mouse and rat brains. For the rat pontine nuclei, axonal projections from neocortex arrange in a concentric inside-out organisation pattern, establishing general organisational principles. However, it is unclear if similar principles are present in subcortical areas in the mouse.
This thesis addresses general principles of topographical organisation in the mouse caudoputamen, thalamus, pontine nuclei, and superior colliculus. In the pontine nuclei, we observed the same general principles as seen in the rat. The inside-out pattern was also observed in the thalamus, and we identified a fan-shaped pattern in the caudoputamen and superior colliculus. To address the development of corticopontine topography in the mouse, we altered the neocortical development by removing the Nr2f1 gene in neuron progenitor and postmitotic phases. The topographical organisation was not affected by removing the gene in the progenitor phase, but altering the postmitotic phase resulted in a lack of axonal projections in the centre of the pontine nuclei.
These results provide new insights into topographical patterns in the mouse, including how patterns form during development and organise in the adult brain. Better understanding of the organisation of neuronal networks can help scientists understand how the brain processes information and create better computational brain models.
Additional information
Contact the research support staff.