Movement error/variability is proportional with velocity and force.

The brain’s choice of spatial coordinate system depends on the task. This can sometimes be determined by:

*Plotting the movement errors along the different components of different suspected coordinate systems. *A likely coordinate system would result in uncorrelated errors in its principle axis/components. *This is similar to eigenvector analysis - decompose the movements into uncorrelated components, thes components/eigenvectors is then the used coordinate system.

Examples used include [Gordon, Ghilardi, and Ghez 1994] and [Soechting and Flanders 1989].

Fitt’s law describes the speed-accuracy trade-off, roughly log-inverse[Jeannerod 1988].

Stereotypical patterns are employed in many movements. Tendency to make straight-line movements characterizes a large class of movements, regardless of the motions of the joints required. Joint motions often vary while hand-trajectory reamin more invariant, also suggests planning with respect to hand [Morasso 1981].

Two-thrids Power Law - the relationship between the speed of hand motion and the degree of curvature of the hand path is roughly constant: velocity varies as a continuous function of the curvature raised to the power of two-thrids [Lacquaniti, Terzuolo, and Viviani 1983].

Feedback control cannot generate a command in anticipation of an error: It is always driven by an error. Feedforward control is based only on a desired/expected state and can therefore null the error. Most likely used to initiate an action, followed by feedback error correction.

Feedback control suffers from sensory delay. Feedforward control suffers from inaccurate estimates. Therefore, movement controls uses a combination of sensory feedback and motor prediction, using a forward model to estimate the current state of the body.

Sensory processing is different for action and perception - sensory information used to control actions is processed in neural pathways that are distinct from the afferent pathways that contribute to perception. Key points: visual information flows in two streams in the brain. Dorsal stream projects to the posterior parietal cortex, involved in use of vision for action. Ventral stream projects to the inferotemporal cortex and invovled in conscious visual perception.

Evidence for motor learning in reaching experiment: In [Brashers-Krug, Shadmehr, and Bizzi 1996], person’s arm holding an apparatus reaches for targets. The apparatus then applies a CCW force against the user, disturbing his otherwise straight trajectories. The user eventually adapts and forms relatively straight lines again. Two possible learning strategies are possible: 1) Stiffening arms to resist force; 2) Anticipate and learn a new internal model to compensate for the new forces. After turning force off, we see overcompensation in the trajectories, indicating that learning strategy 2 was used.

Dynamic motor task learning mainly through prioception and less vision. Kinematic motor task can be guided more by vision. Proprioception is critical for planning hand trajectories and controlling dynamics, is needed to update both inverse models ued to control movement and forward models used to estimate boyd positions resulting from motor commands. Derived from experiments comparing control vs. those that have lost proprioception [Ghez, Gordon, and Ghilardi 1995],[Sainburg et al., 1995].