Transcript Cerebellum_seminar

Cerebellum
By: Shahab Vahdat
Fall 2006
General View
 Cerebellum (Latin, little brain): only 10 % total volume of the brain but
more than half of all its neurons.
 arranged in a highly regular manner as repeating units but with input and
outputs from different parts
similar computational operations
but on different inputs.
 the cerebellum is provided with extensive information (40 times more
axons project into the cerebellum than exit from it)
 three sections of cerebellum: (i) gray matter: cerebellar cortex (ii) white
matter (iii) 3 deep nucleus: fastigial, interposed, dentate.
 the cerebellum is not necessary to basic elements of perception or
movement.
 damage to the cerebellum disrupts the spatial accuracy and temporal
coordination of movement. It impairs balance and reduces muscle tone
and motor learning and certain cognitive functions.
Inputs and Outputs of Cerebellum
General View
Gross features of the cerebellum, including the
nuclei, cerebellar peduncles, lobes, folia, and
fissures. (Adapted from Nieuwenhuys et al. 1988)
A. Dorsal view. Part of the right hemisphere has
been cut out to show the underlying cerebellar
peduncles.
B. Ventral view of the cerebellum detached from
the brain stem.
C. Midsagittal section through the brain stem and
cerebellum, showing the branching structures of
the cerebellum.
The Cerebellum Has Three Functionally Distinct Regions
The cerebellum is divided into anatomically distinct lobes.
A. The cerebellum is unfolded to reveal the lobes normally hidden from view.
B. The main body of cerebellum has three functional regions: the central vermis and the lateral
and intermediate zones in each hemisphere. It is divided by the primary fissure into anterior and
posterior lobes. The posterolateral fissure separates the flocculonodular lobe. Shallower fissures
divide the anterior and posterior lobes into nine lobules (anatomists consider the flocculonodular
lobe as the tenth lobule).
The Cerebellum Has Three Functionally Distinct Regions
The Cerebellum Has Three Functionally Distinct Regions
The three functional regions of the cerebellum have different inputs and outputs.
Neurons in the Cerebellar Cortex Are Organized into Three Layers
The cerebellar cortex is
organized into three layers
and contains five types of
neurons. A vertical section
of a single cerebellar folium,
in both longitudinal and
transverse planes, illustrates
the general organization of
the cerebellar cortex. The
detail
of
a
cerebellar
glomerulus in the granular
layer is also shown. A
glomerulus is a clear space
where the bulbous terminal
of a mossy fiber makes
synaptic contact with Golgi
and granule cells.
Neurons in the Cerebellar Cortex Are Organized into
Three Layers
The Purkinje Cells Receive
Excitatory Input From Two
Afferent Fiber Systems and
Are Inhibited by Three
Local Interneurons
Synaptic organization of the
basic
cerebellar
circuit
module. Mossy and climbing
fibers convey output from the
cerebellum
via
a
main
excitatory loop through the
deep nuclei. This loop is
modulated by an inhibitory
side-loop passing through the
cerebellar cortex. This figure
shows the excitatory (+) and
inhibitory
(-)
connections
among the cell types.
Geometrical Plan of Parallel and Climbing fibers
The geometry of the mossy and
parallel fiber system contrasts
with that of the climbing fiber
system. Mossy fibers excite granule
cells whose parallel fibers branch
transversely to excite hundreds of
Purkinje cells several millimeters
from the branch point, both medially
and laterally. By contrast, climbing
fibers branch in the sagittal
dimension to excite 10 or so Purkinje
cells anterior and posterior to the
branch
point.
The
transverse
connections of the parallel fibers and
the sagittal connections of the
climbing fibers thus form an
orthogonal matrix.
Mossy and Climbing Fibers Encode Peripheral and
Descending Information Differently
Simple and complex spikes
recorded intracellularly from
cerebellar Purkinje cells.
Complex spikes (right bracket)
are evoked by climbing fiber
synapses, while simple spikes
(left bracket) are produced by
mossy fiber input. (From
Martinez et al. 1971.)
Synchronization of complex spikes in the Purkinje neurons
A. A rat performing trained
licking.
B. The grid represents the
spatial locations of 29
Purkinje cells from which
complex
spikes
were
recorded while the rat was
licking. The cells in red fired
synchronously at one time;
those
in
blue
fired
synchronously at another
time; cells represented by
open circles were not
synchronized. Synchronous
complex spikes occurred in
neighboring Purkinje cells
even after the peripheral
nerves from the face had
been sectioned, suggesting
that the synchronized firing
was central in origin. (from
Welsh et.al. 1995 Nature)
Climbing Fiber Activity Produces Long-Lasting Effects
on the Synaptic Efficacy of Parallel Fiber
Some models of the cerebellum in learning
movements:
1. Marr and Albus primary model
2. Forward dynamics model based
3. APG model
4. APPG model of the Cerebellum :
(APG + Motor primitives of spinal cord)
Cerebellum as a forward model: Theoretical and neural organization of forward models. a( Theoretical
organization of information processing streams that use forward models for motor control. Motor commands directed
to systems that control movement are also copied to forward models that mimic input–output relationships exhibited
by these systems (blue, direct route; red, side-loop). b( Anatomical correlates of this theoretical organization. Note that
the anatomical model contains additional components that exert control over motor control systems (for example, by
modulating rubrospinal circuits) (RN, red nucleus). c (Analogous anatomical model involving prefrontal interactions.
The organization is the same as that in panel b. Information arising in the prefrontal cortex is copied to the cerebellum
in the same way that motor commands are copied from the primary motor cortex to the spinal cord. In this scheme,
cerebellar forward models mimic the input–output relationships of prefrontal targets (note that the target of a prefrontal
neuron can be neurons outside the prefrontal cortex, but can also be another prefrontal neuron). Forward models might
therefore be able to mimic information processing that is intrinsic to the prefrontal cortex.
APG model of
the Cerebellum:
•
Proposed by Houk and Barto in
1989 (Adjustable pattern generator)
•
Produces motor commands with
adjustable duration and intensity
•
completely agree with physiological
aspects of the cerebellum
•
Positive feedback pathway between
cerebral cortex and cerebellar nuclei
•
PC receives input from PF,CF and
basket cells
APG model: Phases of movement :
1.
Programming : balance between PF and BS determines the situation
of PC
2.
Initiation : spread of positive feedback in premotor networks
3.
The intensity of command (positive feedback) is determined by the
situation of PC and this produces different elemental movements
4 . PC becomes refractory to further inputs until near end of movement
5 . The movement is terminated by firing a large number of PCs which
were turned off in programming phase due to PF inputs
6 . CF modifies synaptic weights in programming phase and in
termination phase due to PF patterns
Isometric force fields
Motor
primitives in
the Spinal
Cord
Force fields evoked from microstimulation of the
interneuronal regions of the frog spinal cord. a, The ankle
of spinalized frogs was attached to a force transducer and
fixed at different locations in the workspace of the leg,
indicated by the filled circles in the figure. The same site in
the spinal cord was electrically stimulated with the ankle in
each location, and the resulting isometric force was
measured. b, shows an example of a force field resulting
from the stimulation of one such site in the spinal cord.
Reproduced from Bizzi and others (1991).
Linear
Summation
Principle
Vector summation of force vectors when costimulating ites at
different activation levels. The top panel shows the ndividual
fields obtained when site A was stimulated at the ower pulse
duration (PD) and site B at the higher one, and the actual (site
A and B activated simultaneously) and predicted (from linear
summation of the forces at each position) fields obtained
from costimulation of the two sites. The bottom panel shows
the results when the levels of activation were switched.
Similarity between fields is indicated by a black arrow
indicating no difference in average angular deviation across
the measured vectors, and a white arrow indicating that the
force magnitude ratio across positions is not different than 1.
The fields produced by the two combinations of activation
levels (top and bottom panel) were different from each other,
showing the possibility of creating a variety of fields by
modulating the contribution of each original site to the
summated response. Reproduced from Lemay and others
(2001).
•
Responses generated by combinations of muscle synergies may show low
correlation between the activities of muscle pairs. A muscle synergy is
defined here as the recruitment of a group of muscles with a specific balance
of activation. If only one synergy is activated at a time (a), a set of responses
obtained by changing the level of activation of a synergy is obtained by
scaling a single vector in the muscle activity space (b). In this case, all pairs
of muscles have highly correlated activations (c). If instead two synergies
are coactivated (d), the set of responses are generated by combining two
vectors and the activities of the muscles lie on a plane (e). The correlation
between two of the three muscles is now much lower (f).
Brain
Spinal cord solving
the inverse problem
(t) = G-1(q(t)) = S ci i(q(t))
Linear interaction
APPG model of the Cerebellum
APPG model :
Figure illustrates the scheme of our proposed model for cerebellar
learning based on APPG modules. Primitive encoder represents the
Granule cells, which provide cerebellum with sparse expansive
encoding of the coefficients of primitives (ci ) from the spinal cord
and motor cortex. A map transforms a low dimensional variable q(t)
into a multi-dimensional control signal; input of this transformation
is the proprioceptive information of the motor apparatus and the
output represents the mossy fiber. This process is performed in “state
mapping” block shown in Fig. The Cn represents the current
coefficient of motor primitive that corresponds to the efferent copy
of motor information coming from spinal cord to the cerebellum.
Cn+1 represents the information from motor cortex to the cerebellum
(equivalent to next motor coefficient). [q,q’]n-1 represents the
proprioceptive information from the limbs (the previous state of the
limb).