Motor abilities in autism: a review using a computational context.

Gowen et al. (2013) looked at every paper they could find on how autistic people move. They used computer-style thinking to spot the weak links.

They asked: is the problem in learning new moves, in planning them, or in the noisy signals between brain and body?

Planning and sensorimotor noise are shaky in autism. Motor learning itself is mostly fine.

In plain words: kids can learn to kick a ball, but their brain may trip over the steps or pick up extra noise while doing it.

Goulardins et al. (2013) seems to disagree. They watched kids grasp a bar and found planning stayed intact; only the move itself ran slow. The clash fades when you see Emma’s review talks about broad sensorimotor noise, while B et al. zoomed in on one grasp plan.

Sparaci et al. (2015) backs Emma up. Autistic and typical kids learned a tracking task at the same speed, but the paths they took showed hidden planning hiccups.

Izadi-Najafabadi et al. (2015) sharpens the picture. Implicit motor learning (picking things up without knowing) stays strong, while explicit learning (when you have to explain the steps) lags behind.

When you test motor skills, probe how the client plans the move and how much noise creeps in, not just whether they can copy you. Build drills that let them learn by doing, not by talking through rules, and watch the path their hand takes, not only the final score.