2012 Program - Society for the Neural Control of Movement

Abstracts | Panel and Individual Sessions
the climbing fibers at the time during the vestibular stimulus when
they normally fire during gain increase training, the gain of the VOR
increased relative to the control condition with no climbing fiber
stimulation. However, if we stimulated the climbing fibers at the time
that they normally fire during gain decrease training, there was no
change in VOR gain relative to control. These results suggest that the
error signals carried by the climbing fibers are not always translated
into long-lasting changes in the motor circuitry, and that climbing
fiber-triggered plasticity mechanisms contribute selectively to certain
aspects of motor learning, and not others.
We also assessed the extent to which direct, optogenetic activation of
the Purkinje cells could replace the visual signals that normally drive
VOR learning. Activation of the Purkinje cells at the time during the
vestibular stimulus when they normally fire during gain increase
training caused an increase in VOR gain relative to control, providing
causal evidence for the longstanding hypothesis that Purkinje cell
simple spike activity can control the induction of plasticity. However, if
we activated the Purkinje cells at the time when they normally fire
during gain decrease training, there was no change in VOR gain
relative to control, suggesting that Purkinje cell activation, like
climbing fiber activation, contributes selectively to VOR gain increase
learning.
Mapping lesions to abnormal arm kinematics during
recovery from cerebellar stroke
Juergen Konczak1, Dagmar Timmann2 1University of Minnesota, 2Universität Essen-Duisburg
Loss of movement coordination is the main symptom after cerebellar
infarction. Detailed kinematic descriptions of acute stage ataxia are
rare and no attempt has been made to link improvements in motor
function to measures of neural recovery and lesion location. This
study provides a comprehensive assessment of how lesion site and
arm dysfunction are associated in the acute stage and outlines the
course of upper limb motor recovery for the first four months after the
infarction.
Methods: 16 adult patients with cerebellar stroke and 11 agematched
healthy controls participated. Kinematics of goal-directed
and unconstrained finger pointing movements were measured at the
acute stage and in a 2-week and 3-month follow-up. Magnetic
resonance imaging (MRI) data were obtained for the acute and 3month
follow-up session. A voxel-based lesion map subtraction
analysis was performed to examine the effect of ischemic lesion sites
on kinematic performance.
Results: In the acute stage nearly 70% of patients exhibited hand
velocity and acceleration maxima below the range of the control
group leading to prolonged movement times. MRI subtraction
analysis revealed that in patients with impaired motor performance
lesions were more common in paravermal lobules IV/V and affected
the deep cerebellar nuclei. By the 2-week-follow-up hand kinematics
had improved dramatically (peak acceleration gains up to 86%).
Improvements between the 2-week and the 3-month-follow-up were
less pronounced.
Conclusion: In the acute stage arm movements were mainly
characterized by abnormal slowness (bradykinesia) and not
dyscoordination (ataxia). The motor signs were associated with
lesions in paravermal regions of lobules IV/V and the deep cerebellar
nuclei. Motor recovery was fast with the majority of gains in upper
limb function occurring in the first two weeks after the acute phase.
Computational control of the conditioned eye blink
reflex in rodents
Robert Prueckl1, Aryeh Taub2, Roni Hogri2, Ari Magal2, Matti Mintz2, Christoph Guger1 1g.tec Guger Technologies OG, 2Tel Aviv University
Brainstem facial nucleus (FN) contains motor neurons which upon
activation by either neuronal afferents or electrical trains induce eye
blink responses. The goal of the present study, which was conducted
in the course of the European Union project ReNaChip, was to replace
the cerebellar micro-circuit, which is responsible for acquisition of the
conditioned eye blink response, with a biocompatible synthetic
prosthesis. In this project, for the first time a functional real-time
system was developed which utilized biological streams directly from
and to the brain.
The conditioned eye blink response is learned along a classical
conditioning paradigm. Typically, it consists of a several hundreds of
milliseconds long tone, which is used as a conditioned stimulus (CS),
co-terminating with a short air puff directed to the eye of the subject.
The air puff serves as unconditioned stimulus (US) and elicits an
unconditioned response (UR) in form of a fast eye blink after its onset.
After a sufficiently large number of paired CS-US trials the cerebellar
microcircuit adapts in a way that it initiates conditioned eye blink
responses (CR) in reaction to the CS’s, and therefore before the arrival
of the air puff. The functionality of the cerebellar micro-circuit is lost
with age and senescent rats fail to acquire the conditioned eye blink
response. This age-related deficiency and the elaborate knowledge
about the cerebellar microcircuit made the cerebellum an eligible
candidate for testing the feasibility of rehabilitation based on
replacement technology.
The neuronal representations of the CS and the US arrive in the
course of the classical conditioning procedure in the brainstem
pontine nucleus (PN) and the inferior olive (IO), respectively, and from
there are routed to the cerebellum. The two pathways converge in the
cerebellar cortex where the association between the stimuli is
established and consequently the cerebellar output conveys a model-
CR to the FN which initiates the peripheral eye blink-CR.
Using the real-time system which was developed for this study, paired
CS-US trials were applied and multiple unit activity from the
mentioned brain regions PN and IO of an anaesthetized rat were
recorded utilizing arrays of microelectrodes, headstages and biosignal
amplifiers. After the training of signal processing algorithms which
were to detect the time of the CS and US onset out of the biosignals,
the real-time experiment started. The stimuli were detected in realtime
and conveyed to an algorithm which modeled the functionality of
the cerebellum and - also in real-time - established the association
between the stimuli. It finally reacted with a trigger which symbolized
the CR. This was sent to an electrical stimulator connected to an
electrode implanted in the FN of the animal. The pulse train, which
had the same duration as a typical CR, caused the eye blink response.
In this study the successful implementation of a prototype neural
prosthesis is presented, which interacts directly with the brain in a
closed loop manner and triggered well timed learned motor
responses. The system is a proof-of-concept for the feasibility of
highly specialized and spatiotemporally accurate neural prostheses.
PANEL Session 10
Friday, April 27
8:00 – 10:15
The contribution of sensory signals in constructing
brain-machine interfaces
Aaron Suminski1, Sliman Bensmaia1, Joseph O’Doherty2, Kevin Otto3 1University of Chicago, 2University of California - San Francisco,
3Purdue University
The ultimate goal of brain-machine interface (BMI) research is to
create a device that provides individuals suffering from severe motor
disabilities a complete restoration of function. Historically, much of the
effort in BMI research has focused on the efferent component of the
device, that is, the decoding of neuronal signals to control mouse
cursors or robots. Comparatively little effort has been devoted to the
afferent (or sensory) component of the BMI despite a wide
acknowledgement of its importance. In this session, we will describe
two ways in which sensory signals will contribute to BMIs. First, we
will describe how precise and behaviorally-relevant sensory percepts
can be conveyed to the patient via intracortical microstimulation
(ICMS). Indeed, we will explore how ICMS can elicit percepts with a
specific sensory magnitude, percepts with specific temporal
properties, and percepts projected to specific locations on the
prosthesis. Second, we will discuss how artificial sensory feedback
24 | SOCIETY FOR THE NEURAL CONTROL OF MOVEMENT | 22ND ANNUAL MEETING PROGRAM