Professor Maurice Smith has invited
Reza Shadmehr to Speak at a Seminar entitled
"Motor Adaptation and the Timescales of Memory "
in G135 MD -- Thursday, 5/17 -- 4 PM
and invites you to attend.
The abstract is below.

Motor Adaptation and the Timescales of Memory
Abstract

When the brain generates a motor command, it also predicts the sensory
consequences of that command via an "internal model".  The reliance on a
model appears to make the brain able to sense the world better than is
possible from the sensors alone.  However, this happens only when the models
are accurate.  To keep the models accurate, the brain must constantly learn
from prediction errors.  Here I use examples from saccade and reach
adaptation to demonstrate that learning is guided by multiple timescales: a
fast system that strongly responds to error but rapidly forgets, and a slow
system that weakly responds to error but has good retention.

Why should learning be guided by multiple timescales?  The response of the
motor apparatus to neural commands varies due to many causes. Fast timescale
disturbances occur when muscles fatigue. Disturbances with a slow timescale
occur when muscles are damaged, or limb dynamics change due to development.
To maintain performance, motor commands need to adapt.  Computing the best
adaptation in response to any performance error results in a credit
assignment problem: what timescale is responsible for this disturbance?  I
show that a Bayesian solution to this problem accounts for numerous
behaviors of animals during both short and long-term training. Our analysis
focuses on characteristics of the oculomotor system during learning,
including effects of time passage.  However, I suggest that learning and
memory in other paradigms, such as reach adaptation, the adaptation of
visual neurons, and retrieval of declarative memories, largely follow
similar rules.