Poh, Eugene PhD

The overarching goal of my research is to understand the computational underpinnings of motor learning, and its associated neural representations. Toward this goal, I have adopted multiple complementary strategies, including motor psychophysics, computational modelling, non-invasive brain stimulation and neuropsychological approaches, to reveal how the brain represents what it learns. First, I use behavioral paradigms where visual feedback of hand movements is distorted to characterize how humans learn to compensate for such perturbations, and generalize the learning to novel contexts. Such approaches have the capacity to uncover the underlying representations of learning (or how the brain encodes movement). Second, I develop computational models to analyze the generalization pattern to gain a better understanding of the interactions between different representations during learning. This will provide important theoretical insights into the representational changes that transpire during motor learning, and how information from multiple sensory modalities is integrated in the brain for movement planning. Third, I leverage non-invasive brain stimulation techniques such as transcranial magnetic stimulation to directly investigate the role of different neuroanatomical substrates in encoding for motor learning. In addition, to further explore the underlying mechanisms of learning, I turn to neuropsychological studies, where I examine patients with movement deficiencies, such as essential tremor, to reveal the extent to which learning and generalization is impaired due to damage to the afflicted brain areas. Ultimately, this multifaceted approach to understanding the characteristics of the internal representation, which drives generalization, may lead to development of optimal neurorehabilitation protocols that help patients maximize the transfer of learning from the clinical setting to activities of daily living.

Project 1:

Title and Description: Applications of non-invasive brain stimulation techniques to study how the brain is reorganized to allow transfer of motor learning between limbs. 

Available for: Third-year research placement students, Honours and PhD

My research interest in learning and generalization are also manifest in my teaching philosophy. I am a strong proponent of active learning, and I believe there is no learning experience more powerful than a participatory-based classroom which engage students as active participants in their learning during interaction with their instructors. I aim to develop courses that not only to equip students with scientific knowledge, but also challenge them to be creative, independent problem solvers that rigorously prepare them for research beyond the classroom. I feel that my years of experience, initially as a high school teacher, and later as educator to undergraduate students, have given me a unique perspective on the different kinds of challenges learning takes at different levels. I would relish the opportunity to bring my experience to the position to educate and inspire the next generation of movement scientists.

What are the mechanisms that determine whether what we learn in one behavioral context can generalize to another context? This question is at the heart of my research interests, with the goal of developing a computational framework of motor learning capable of establishing the principles used by the brain to determine generalization. To understand how generalization is achieved behaviorally and neurophysiologically, I have adopted multiple complementary strategies, including motor psychophysics, computational modelling, non-invasive brain stimulation and neuropsychological approaches, to reveal how the brain represents what it learns. Ultimately, my multifaceted approach to understanding the characteristics of the internal representation of motor learning will not only lead to development of optimal neurorehabilitation protocols that help patients maximize the transfer of learning from the clinical setting to activities of daily living, but also affords critical new insights into the design and development of human-machine interfaces used in industrial, commercial and leisure activities.

The overarching goal of my research is to understand the computational underpinnings of motor learning, and its associated neural representations. Toward this goal, I have adopted multiple complementary strategies, including motor psychophysics, computational modelling, non-invasive brain stimulation and neuropsychological approaches, to reveal how the brain represents what it learns. First, I use behavioral paradigms where visual feedback of hand movements is distorted to characterize how humans learn to compensate for such perturbations, and generalize the learning to novel contexts. Such approaches have the capacity to uncover the underlying representations of learning (or how the brain encodes movement). Second, I develop computational models to analyze the generalization pattern to gain a better understanding of the interactions between different representations during learning. This will provide important theoretical insights into the representational changes that transpire during motor learning, and how information from multiple sensory modalities is integrated in the brain for movement planning. Third, I leverage non-invasive brain stimulation techniques such as transcranial magnetic stimulation to directly investigate the role of different neuroanatomical substrates in encoding for motor learning. In addition, to further explore the underlying mechanisms of learning, I turn to neuropsychological studies, where I examine patients with movement deficiencies, such as essential tremor, to reveal the extent to which learning and generalization is impaired due to damage to the afflicted brain areas. Ultimately, this multifaceted approach to understanding the characteristics of the internal representation, which drives generalization, may lead to development of optimal neurorehabilitation protocols that help patients maximize the transfer of learning from the clinical setting to activities of daily living.

Project 1:

Title and Description: Applications of non-invasive brain stimulation techniques to study how the brain is reorganized to allow transfer of motor learning between limbs. 

Available for: Third-year research placement students, Honours and PhD

My research interest in learning and generalization are also manifest in my teaching philosophy. I am a strong proponent of active learning, and I believe there is no learning experience more powerful than a participatory-based classroom which engage students as active participants in their learning during interaction with their instructors. I aim to develop courses that not only to equip students with scientific knowledge, but also challenge them to be creative, independent problem solvers that rigorously prepare them for research beyond the classroom. I feel that my years of experience, initially as a high school teacher, and later as educator to undergraduate students, have given me a unique perspective on the different kinds of challenges learning takes at different levels. I would relish the opportunity to bring my experience to the position to educate and inspire the next generation of movement scientists.