Final Report Summary - BRAINPROP (Brain mechanisms of human limb movement sense)
Proprioception is the sense of limb position and limb movement. Without proper proprioception it is not possible to move as smoothly and thoughtlessly as we do in our daily lives. Proprioception includes inputs from mechanoreceptors in the skin, Golgi tendon organs, and muscle spindle receptors. These signals have to be integrated by the brain and combined with motor output signals. It is unknown how all these signals are integrated in the brain. We suggested a role for the primary motor cortex in proprioception.
Indeed we show that proprioceptive information from the arm can cause changes in the representation of hand muscles over the motor cortex; that is, the responses that we record from two intrinsic hand muscles (muscles that lie within the hand) when stimulating the motor cortex and surroundings using transcranial magnetic stimulator (TMS) show differences, depending on the position of the arm and hand in space relative to the body. We suggest that these changes in the representation of hand muscles depends on tasks in which these hand muscles are involved and that those tasks might differ depending on the position of the hand in space.
In another series of fMRI experiments, the hands of healthy participants were moved passively into three different positions, while the arm was kept in the same place: the hand was pointing straight ahead, continuing in the same direction as the arm, the hand was flexed, or the hand was extended. We used a multi-voxel pattern analysis (MVPA) to investigate the detailed activation of the motor cortex. During passive movements, the brain usually shows activation of all areas that are involved in motor control, using a general linear model (GLM). We indeed showed this activation for the short periods of movement. However, during the phase of the static positions, the ‘classic’ GLM was not able to distinguish between these three positions. By using the MVPA, we were able to look at the more detailed patterns of activation within the motor areas. With these analyses we were indeed able to distinguish between the hand being flexed and the hand being extended. That is for the first time we could read out hand position sense from the fine-grained patters of activity in the motor cortex.
Furthermore, experiments have been performed in which we placed an ischaemic cuff around the right upper arm of participants, resulting in complete anaesthesis and paralysis of the right forearm and hand, while they were lying in an MRI scanner. When paralysis was complete, the participants were asked to push with the right hand against a force transducer with either 20% or 40% of their maximal voluntary contraction force (which they had practiced before inducing the ischaemic block). With these experiments we found activity in the motor cortex that reflected to motor efferent output influencing proprioception. This imaging results suggest that motor signals can activate proprioceptive representations in the motor cortex in the absence of afferent signals from skin and muscle spindle receptors..
Overall, these experiments will give more insight in how proprioceptive signals are integrated in the brain and used subsequently for making appropriate movements. Once we know how proprioceptive signals are being processed in the brain, we can try to use these signals to improve for example rehabilitation after stroke or after the loss of a limb and having to learn to use prosthetics.
Indeed we show that proprioceptive information from the arm can cause changes in the representation of hand muscles over the motor cortex; that is, the responses that we record from two intrinsic hand muscles (muscles that lie within the hand) when stimulating the motor cortex and surroundings using transcranial magnetic stimulator (TMS) show differences, depending on the position of the arm and hand in space relative to the body. We suggest that these changes in the representation of hand muscles depends on tasks in which these hand muscles are involved and that those tasks might differ depending on the position of the hand in space.
In another series of fMRI experiments, the hands of healthy participants were moved passively into three different positions, while the arm was kept in the same place: the hand was pointing straight ahead, continuing in the same direction as the arm, the hand was flexed, or the hand was extended. We used a multi-voxel pattern analysis (MVPA) to investigate the detailed activation of the motor cortex. During passive movements, the brain usually shows activation of all areas that are involved in motor control, using a general linear model (GLM). We indeed showed this activation for the short periods of movement. However, during the phase of the static positions, the ‘classic’ GLM was not able to distinguish between these three positions. By using the MVPA, we were able to look at the more detailed patterns of activation within the motor areas. With these analyses we were indeed able to distinguish between the hand being flexed and the hand being extended. That is for the first time we could read out hand position sense from the fine-grained patters of activity in the motor cortex.
Furthermore, experiments have been performed in which we placed an ischaemic cuff around the right upper arm of participants, resulting in complete anaesthesis and paralysis of the right forearm and hand, while they were lying in an MRI scanner. When paralysis was complete, the participants were asked to push with the right hand against a force transducer with either 20% or 40% of their maximal voluntary contraction force (which they had practiced before inducing the ischaemic block). With these experiments we found activity in the motor cortex that reflected to motor efferent output influencing proprioception. This imaging results suggest that motor signals can activate proprioceptive representations in the motor cortex in the absence of afferent signals from skin and muscle spindle receptors..
Overall, these experiments will give more insight in how proprioceptive signals are integrated in the brain and used subsequently for making appropriate movements. Once we know how proprioceptive signals are being processed in the brain, we can try to use these signals to improve for example rehabilitation after stroke or after the loss of a limb and having to learn to use prosthetics.