DLN Spatial self-motion estimation for motor control in the cerebellum, Prof. Andrea Green
Event details
| Date | 16.03.2021 |
| Hour | 16:00 › 17:00 |
| Speaker | Prof Andrea Green |
| Location | Online |
| Category | Conferences - Seminars |
ABSTRACT
Whether running to catch a ball or turning to reach for a coffee cup, in our daily lives we are constantly in motion, interacting with objects in the environment. Experiments under simplified laboratory conditions, in which body movements are limited, have provided essential insights into how we plan and control voluntary motor actions (e.g., reaching). However, it remains to be established how such insights generalize to the more complex real-life problem of planning and coordinating our actions as we move through space. How do we integrate multisensory cues (e.g., vestibular, visual, proprioceptive) to compute the types of self-motion estimates that are relevant for different tasks? What are the mechanisms by which we use such estimates in the online control of motor behavior? In this talk, I will discuss the role of a distributed brainstem-cerebellar circuit in computing the types of self-motion estimates essential for activities such as postural control and voluntary reaching. I will also describe the results of recent studies investigating how vestibular estimates of the body’s motion contribute to voluntary reaching and what the implications might be for understanding how we integrate sensory feedback to control voluntary movement.
BIO
Andrea Green is a professor in the Department of Neuroscience at the University of Montreal. She was originally trained as electrical engineer, but after becoming interested in neural prosthetics applications she soon concluded that the most interesting circuits and control systems are real physiological ones. She therefore decided to pursue graduate studies in biomedical engineering with Henrietta Galiana at McGill University, working on computational modelling of the neural networks involved in visual and vestibular control of gaze. She continued her training in experimental neuroscience testing some of the computational predictions from her PhD work in the laboratory of Dora Angelaki. There she combined computational modeling work with neurophysiological recordings in alert behaving primates to explore how self-motion estimates are computed within brainstem-cerebellar circuits. This work led to her interest in how self-motion estimates are used to coordinate our voluntary actions while the body is moving, and motivated her to gain experience in the cortical control of reaching with John Kalaska. She subsequently established her own lab at the University of Montreal, where she investigates both how multisensory signals are combined to compute different types of spatial motion estimates and how we use these estimates to plan and coordinate our motor behaviors as we move around in space.
Whether running to catch a ball or turning to reach for a coffee cup, in our daily lives we are constantly in motion, interacting with objects in the environment. Experiments under simplified laboratory conditions, in which body movements are limited, have provided essential insights into how we plan and control voluntary motor actions (e.g., reaching). However, it remains to be established how such insights generalize to the more complex real-life problem of planning and coordinating our actions as we move through space. How do we integrate multisensory cues (e.g., vestibular, visual, proprioceptive) to compute the types of self-motion estimates that are relevant for different tasks? What are the mechanisms by which we use such estimates in the online control of motor behavior? In this talk, I will discuss the role of a distributed brainstem-cerebellar circuit in computing the types of self-motion estimates essential for activities such as postural control and voluntary reaching. I will also describe the results of recent studies investigating how vestibular estimates of the body’s motion contribute to voluntary reaching and what the implications might be for understanding how we integrate sensory feedback to control voluntary movement.
BIO
Andrea Green is a professor in the Department of Neuroscience at the University of Montreal. She was originally trained as electrical engineer, but after becoming interested in neural prosthetics applications she soon concluded that the most interesting circuits and control systems are real physiological ones. She therefore decided to pursue graduate studies in biomedical engineering with Henrietta Galiana at McGill University, working on computational modelling of the neural networks involved in visual and vestibular control of gaze. She continued her training in experimental neuroscience testing some of the computational predictions from her PhD work in the laboratory of Dora Angelaki. There she combined computational modeling work with neurophysiological recordings in alert behaving primates to explore how self-motion estimates are computed within brainstem-cerebellar circuits. This work led to her interest in how self-motion estimates are used to coordinate our voluntary actions while the body is moving, and motivated her to gain experience in the cortical control of reaching with John Kalaska. She subsequently established her own lab at the University of Montreal, where she investigates both how multisensory signals are combined to compute different types of spatial motion estimates and how we use these estimates to plan and coordinate our motor behaviors as we move around in space.
Practical information
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- Free