About the Project
Theoretical work and psychophysical studies have led to the hypothesis that autism phenotypes may be manifestations of an underlying impairment in predictive abilities. Within this theoretical framework, autism is characterized by a greater weighting of sensory information in updating internal representations of the environment. With compromised prediction skills, an individual with autism faces an environment in which events occur unexpectedly and without cause. Therefore, an insistence on sameness or stereotyped and repetitive behaviours can be seen as attempts to provide a reassuring sense of a predictable environment in a world otherwise filled with unexpected changes.
Testing the hypothesis of predictive coding requires an experimental design in which predictions are constrained experimentally. One possibility is to use learned associations between behaviour and sensory feedback. For example, sensory feedback couples in a predictable way to motor output. Hence, the experimental assumption is that signals generated during movement that are fed back to sensory areas should constitute an experience-dependent prediction of sensory feedback. Recent studies in the mouse primary visual cortex (V1) have tested whether top-down projections to V1 carry a prediction of visual input based on motor output. Using a virtual reality environment combined with two-photon calcium imaging, these experiments have identified a neuronal circuit for visual flow predictions between the cortical area Anterior Cingulate Cortex (ACC) and V1 (Leinweber et al. 2017).
The aim of this project is to test whether visual flow predictions are disrupted in the primary visual cortex of mouse models of ASDs. We plan to use mouse models of fragile X syndrome (Fmr1-/y), and SYNGAP happloinsufficiency (Syngap1+/-), as two well established models to determine how these mutations affect the propagation of neural activity through cortical networks, focussing on sensory areas where inputs are readily controllable. Specifically, the project is organized around 3 aims.
Aim 1: To characterize movement-related activity of ACC axons in V1 of mouse models of fragile X syndrome (Fmr1-/y), and SYNGAP happloinsufficiency (Syngap1+/-).
Aim 2: To establish the contribution of measured top-down inputs to V1 activity through the development of a computational model of the V1 circuit
Aim 3. To test pharmacological treatments that rescue cortical dysfunction in Fmr1-/y and Syngap1+/- mice.
- In vivo imaging in awake behaving mice: training in 2-photon calcium imaging
- Computational methods: model-based analysis of the data, computational modeling of neural circuits; programming skills in Python.
- Data Management: managing and analyzing big imaging data
- Research Ethics, animal research regulations
- Presentation of data, written and orally
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.
Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.
For more information about Precision Medicine visit:
Qualifications criteria: Applicants applying for an MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualification, in an appropriate science/technology area. The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £15,285 (UKRI rate 2020/21).
Full eligibility details are available: View Website
Enquiries regarding programme: email@example.com
 Henschke J.*, Dylda E.*, Katsanevaki D.*, Dupuy N., Currie S.P., Amvrosiadis T., Pakan J.M.P. and Rochefort N.L., Reward association enhances stimulus-specific representations in primary visual cortex, Current Biology, doi:https://doi.org/10.1016/j.cub.2020.03.018. 2020.
 Pakan J.M.P.*, Currie S.P.*, Fischer L.*, Rochefort N.L. The Impact of Visual Cues, Reward, and Motor Feedback on the Representation of Behaviorally Relevant Spatial Locations in Primary Visual Cortex. Cell Reports. 24(10):2521-2528. 2018.
 Leinweber, Marcus, Daniel R. Ward, Jan M. Sobczak, Alexander Attinger, and Georg B. Keller. 2017. “A Sensorimotor Circuit in Mouse Cortex for Visual Flow Predictions.” Neuron 95 (6): 1420–1432.e5. 2017.
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