Hannah Sheahan


University position

PhD student
Supervised by Daniel Wolpert

Departments

Department of Engineering

Institutes

Computational and Biological Learning Lab

Email

hrs40@cam.ac.uk

Home page

https://www.linkedin.com/in/hann... (personal home page)

Research Themes

Systems and Computational Neuroscience

Cognitive and Behavioural Neuroscience

Interests

In a nutshell: I research the computational processes that underlie motor learning in humans, and try to understand how the representations of motor memories impact learning and enable skilled voluntary movement. I am also interested in artificial learning systems.

I am supported by a Cambridge-Rutherford Memorial Scholarship, administered by the Royal Society of New Zealand. I am also a current Benefactor's Scholar of St John's College, Cambridge.

Research Focus

Keywords

motor

learning

planning

representations

control

Clinical conditions

No direct clinical relevance

Equipment

Behavioural analysis

Computational modelling

Collaborators

No collaborators listed

Associated News Items


    Key publications

    Sheahan HR, Franklin DW, Wolpert DM (2016), “Motor planning, not execution, separates motor memories” Neuron 92(4): 773-779