Shlomi Haar

Postdoctoral Fellow

Shlomi is a Royal Society – Kohn International Fellow studying the dynamics of real-world motor learning and its neural correlates. Shlomi has BSc and MSc in Biomedical Engineering, and PhD in Brain and Cognitive Sciences from Ben-Gurion University of the Negev. In His PhD he studied the encoding of arm movement in the human brain by running motor experiments with humans using fMRI.

Research Brief

The neural mechanisms of human motor control and learning evolved in free behaving, real-life settings, yet to date we study these questions in highly simplified lab-based settings. In this project we demonstrate the feasibility of studying real-world neuroscience in-the-wild, using entirely data-driven approaches combined with wearable technologies to track full-body kinematics and brain activity. We use the competitive sports of pool billiard to frame an unconstrained real-world skill learning experiment which is amenable to predictive modelling and understanding. Our data-driven approach unfolds the structure and complexity of movement, variability, and motor-learning and reveals a multi-modal learning mechanism which is employed differently by different types of learners. We identify novel neurobehavioural components in real-world skill learning that were not found in simplified lab-tasks.

Lab Publications

Embodied virtual reality for the study of real-world motor learning


Shlomi Haar, Guhan Sundar, and A. Aldo Faisal


Neurobehavioural signatures in race car driving: a case study


Ines Rito Lima, Shlomi Haar, Lucas Di Grassi, and A. Aldo Faisal

Scientific Reports

Brain Activity Reveals Multiple Motor-Learning Mechanisms in a Real-World Task


Shlomi Haar and A. Aldo Faisal

Front. Hum. Neurosci.

Learning to play the piano with the Supernumerary Robotic 3rd Thumb


Ali Shafti, Shlomi Haar, Renato Mio Zaldivar, Pierre Guilleminot, and A. Aldo Faisal


Kinematic signatures of learning that emerge in a real-world motor skill task


Shlomi Haar, Camille M van Assel, and A. Aldo Faisal


Kinematic behavioural fingerprints in Duchenne muscular dystrophy and their clinical applications


Ricotti, V and Haar, S and Selby, V and Voit, T and Faisal, A