Cerebellar Anatomy
and Connectivity
Cerebellum
History: Cerebellum and
Volitional Movement
• 1809: Rolando first showed that cerebellar
removal results in disturbances of posture
and voluntary movement
• 1824: Fluorens showed cerebellum
responsible for coordination of voluntary
movements
• 1939: Holmes analyses of motor and speech
deficits from cerebellar injury provided
basis of modern terminology and
neurological exams
Cerebellum = “Little Brain”
• 10% of the volume
of the total brain
• Contains more than
half of all the
brain’s neurons
Movement Disturbances
Early Reports of Cognitive Disturbances
Early reports of cognitive
disturbance
• Neuropsychological evaluation was
primitive
• Most reports were somewhat anecdotal
• Consequently, cognitive contribution
of cerebellum largely ignored
Schmahmann, J.D. (1997) Int Rev Neurobiol 41, 3-27.
Early Evidence of Cerebellar Link
to Sensory & Associative Cortex
•
•
•
1934: Abbie observed degeneration of human pontine nuclei
following large lesions of parietal, temporal, occipital lobes
1942: Dow determined that dentate nucleus could be divided
into older medial region and lateral neodentate
1942, 1958: Dow and Moruzzi, Snider & Stowell showed that
proprioceptive, cutaneous, vagal, auditory and visual
stimulation reaches the cerebellar cortex
– Dow & Moruzzi: “…a hitherto unknown control may be exerted
by the cerebellum in the sensory sphere and on autonomic
functions.”
– Snider: Concluded that cerebellum gets dual projections, one
from sense organs and one from related sensory and motor
cortical areas
• The cerebellum is “a great modulator of neurologic function.”
– They note that large cerebellar lesions, especially in lateral
regions, produce little motor deficits
Trends in Cerebellar Research
• Pubmed Search:
– Title contains *cerebell*, cerebrocerebell*, or cerebrocerebell*
– Divide into Human and Animal
– Cognitive content if title contains:
• spatial, mental, emotion*, affective, reasoning, language,
linguistic, planning, fluency, cognit*, memory, attention*,
executive, nonmotor, or neuropsych*
– Cognitive/Motor content if title contains:
• timing, learning, conditioning, or speech
– Motor content if title contains
• motor, sensorimotor, oculomotor, movement*, postur*,
balance, gait, gaze,saccad*, nystag*, locomot*, or walking
Human
350
Number of Publications
Number of Publications
300
Cognitive
Motor/Cognitive
Motor
250
200
150
100
50
0
1970
1975
1980
1985
1990
1995
Year
2000
2005
2010
Brain Development
Animal
350
• The nervous system develops from ectoderm
(outer layer) which forms a plate (~day 18)
300
Cognitive
Motor/Cognitive
Motor
250
200
150
100
50
0
1970
1975
1980
1985
1990
1995
Year
2000
2005
2010
– The edges of the plate curl and eventually fuse
together forming a neural tube
– By ~day 28, the rostral end of the neural tube
has formed the ventricles and the tissue that
surrounds these hollow chambers has formed
three major divisions of the brain
• Forebrain, midbrain, and hindbrain
Desmond, J.E. (2010) Behav Neurol 23, 1-2.
Brain Development
~ 4 weeks
~ 5-6 weeks
Brain
Development
Neuroanatomy: Orientation
Brain Development
Superior/Dorsal
Coronal
Sagittal Section
Posterior/Caudal
axial
Anterior/Rostral
coronal
Planes of
Sectioning
Superior View
Inferior/Ventral
Sagittal
Anterior View
Posterior View
Axial
Inferior View
Cerebellum has 3 lobes
3 Lobes of the Cerebellum
• Anterior lobe
• Posterior lobe
– The latter are divided by the primary
fissure
• Flocculonodular lobe
– (most primitive, appears in fish)
Flocculonodular lobe
Superior View of Cerebellum
Flocculus
Nodulus
Longitudinal Zones
Longitudinally, there are
Three Regions
• Vermis (midline)
• Intermediate zone
• Lateral zone
Vermis = “Worm”
Note many parallel
Convolutions, ie.,
“folia”
10 Lobules
• There are 10 vermian and hemispheric
“lobules”
• The naming of the lobules has been
variable across investigators and
species studied
Cerebellar Lobule Naming
Human
Examples
Animal
Human:Posterior
Quadrangular Lobule
Animal: Simplex Lobule
Schmahmann name:
Hemispheric lobule VI
Human: Superior SemiLunar Lobule
Animal: Crus I
Schmahmann name:
Crus I
Brodal, A. (1981) Neurological Anatomy in Relation to Clinical Medicine, Third edn, Oxford University Press, New York.
10 Lobules
Vermis
Nomenclatures
Schmahmann et al (1999) NeuroImage. 10, 233-60.
• Lobules are separated by fissures
Cerebellar Fissures
Schmahmann et al
Atlas Nomenclature
Anterior View
Superior View
Schmahmann et al (1999) NeuroImage. 10, 233-60.
Schmahmann et al (1999) NeuroImage. 10, 233-60.
Cerebellar Fissures
Posterior View
Inferior View
Left Lateral View
Best view of the hemisphere
lobules is on coronal sections
Best view of vermis lobules is
on sagittal section
Cerebellar Deep Nuclei
• Medial: Fastigial nuclei
• Intermediate: Interposed nuclei
– In humans: Emboliform and Globose nuc
• Lateral: Dentate nuclei
Deep Nuclei Visibility
Deep Nuclei
MRI
Cryo section (coronal)
T1-weighted
Schmahmann et al (1999) NeuroImage. 10, 233-60.
Y= -52
MRI
T2-weighted
Deep Nuclei – Children
vs Adults
Deep Nuclei Visibility
Raw functional images from two subjects
Nissl stain
29 years old
12 years old
Courtesy of Dr. Dominic Cheng
Longitudinal Zones Project to
Different Deep Nuclei
• Vermis  Fastigial Nuclei
• Intermediate  Interposed Nuclei
• Lateral  Dentate Nuclei
Y= -52
Myelin stain
Schmahmann et al (1999) NeuroImage. 10, 233-60.
Deep Cerebellar Nuclei
Have Somatotopic Maps
Inputs and Outputs: Big Picture
Thalamus projects to neocortex
Outputs from deep
cerebellar nuclei
via the superior
cerebellar peduncle
Pontine Mossy fiber
inputs via middle
cerebellar peduncle
Inputs to Cerebellum
• Mossy fibers
– Come from (contralateral) pontine nuclei and
spinal cord
– Pontine fibers project through the middle
cerebellar peduncle (aka: brachium pontis)
– Spinal cord fibers project through inferior
cerebellar peduncle (aka: restiform body)
• Climbing fibers
– Come from the (contralateral) inferior olivary
nucleus
– Project through the inferior cerebellar peduncle
Spinal Mossy fiber
inputs via inferior
cerebellar peduncle
Climbing fiber
inputs via inferior
cerebellar peduncle
Cerebellar Peduncles
Anterior View from 4th ventricle
Cerebellar Peduncles
Posterior View – Cerebellum Removed
Superior
Mossy fiber inputs
Climbing fiber inputs
Inferior
Functional divisions
• Vestibulocerebellum = flocculonodular lobe
–
–
–
–
Eye movements, vestibulo-ocular reflexes, gait, balance
Inputs from vestibular organs
Projects to vestibular nuclei
Evolution: oldest part (archicerebellum)
• Spinocerebellum = vermis & intermed zone
– Somatosensory inputs from spinal cord and trigeminal nerve, as well
as auditory, visual and vestibular inputs
– Projects to fastigial and interposed nuclei
– Influences descending motor systems
– Evolution: Newer (paleocerebellum)
Mossy Fiber
Inputs to
Functional
Divisions
• Cerebrocerebellum = lateral zone
– Inputs from cerebral cortex via the pons
– Outputs to dentate nuc
– Evolution: Newest (neocerebellum)
Cortico-Ponto-Cerebellar Circuitry
Decussation from
dentate to thalamus
Decussation from
pons to cbl cortex
Cortico-pontine projections
• Note that cerebellar damage has
ipsilateral motor effects, due to
double decussation of inputs and
outputs
– E.g., left cerebellar damage causes
problems in left limbs
– In contrast left motor cortex
damage causes problems for the
right limbs
Decussation=fibers (axons) cross midline
Kandel, E.R. et al, eds.
Principles of Neural Science
, 3rd Ed. New York: Elsevier, 1991
Schmahmann, J. D. Human Brain Mapping 4:174-198 (1996).
Ponto-Cerebellar Projections
Anatomical Tracing in Animals
• Old: Silver impregnation methods to
view degenerating axons
• Newer: Horseradish peroxidase and
autoradiographical methods
• Newest: Transneuronal tracing using
viruses, e.g., Herpes, Rabies
– Peter Strick & colleagues: Studies
performed in monkeys
Brodal, A. (1981) Neurological Anatomy in Relation to Clinical Medicine, Third edn, Oxford University Press, New York.
Transneuronal transport of virus
Rabies: Retrograde
Neocortex
Thalamus
Injection Sites
Herpes: Anterograde
Neocortex
First order
Pons
Dentate Nuc
Second order
Granule
Cells
Purkinje
Cells
Third order
Purkinje
Cells
Kelly, R.M. and Strick, P.L. (2003) J Neurosci 23, 8432-44.
Retrograde transneuronal transport of rabies virus
M1: Nearly Identical Patterns for Anterograde & Retrograde Tracing
Retrograde Tracing
Anterograde Tracing
Kelly, R.M. and Strick, P.L. (2003) J Neurosci 23, 8432-44.
Dorsal
Ventral
Dorsal Dentate: Primary Motor
Ventral Dentate: Prefrontal
Very Significant: There is connectivity between cerebellum and cognitive neocortex!
Kelly, R.M. and Strick, P.L. (2003) J Neurosci 23, 8432-44.
Area 46: Nearly Identical Patterns for Anterograde & Retrograde Tracing
Retrograde Tracing
Anterograde Tracing
Kelly, R.M. and Strick, P.L. (2003) J Neurosci 23, 8432-44.
Implication: Closed Corticoponto-cerebello-thalamo Loops
Kelly, R.M. and Strick, P.L. (2003) J Neurosci 23, 8432-44.
Lobular Evolution
Climbing Fiber Inputs:
Inferior Olivary Nucleus
Pct of
cerebellum
occupied
by the lobule
Balsters et al (2010) Neuroimage 49, 2045-52.
Inferior Olive: Cross Section
Inf. Olive and Pontine Nuc.
Pontine Nuclei
Inferior Olivary Nuclei
https://www.msu.edu/~brains/brains/human/brainstem/select_cell.html
Inf. Olivary Subdivisions
•
•
•
•
Inf. Olivary Subdivisions
• lPO (purple)=lamina
of principal olive
Three main subdivisions:
Principal olive (PO)
Dorsal accessory olive (DAO)
Medial accessory olive (MAO)
– Can be preceded by l
(lateral), m (medial), d
(dorsal), v (ventral)
• DAO (red)=dorsal
accessory olive
• MAO (blue)=medial
accessory olive
• yellow: dc = subnuclei
of MAO, vlo =
ventrolat. outgrowth
(of MAO)
transverse sections showing left side only,
numbers caudal to rostral. Top is dorsal.
Inferior Olivary Inputs
• Somatosensory input from spinal cord, trigeminal
nuclei, dorsal column nuclei
Cortico-rubroolivary projections
– Mostly in cMAO and DAO
• Vestibular and optokinetic input
– dc, vlo
• Visual information
– cMAO
• Cerebral Cortex via Red Nucleus
– PO, rMAO
• Direct projections from Deep Cerebellar Nuclei
The neocortex can influence climbing
inputs to the cerebellum through this
projection, in addition to influencing the
mossy fiber inputs in the pons via corticopontine projections.
Outputs of Inf. Olive =
“Climbing Fiber” Inputs to
Cerebellum
• Climbing Fibers project to:
– Cerebellar Cortex
– Cerebellar Deep Nuclei
Outputs from Cerebellum
• Come from the deep cerebellar nuclei
• Project through the superior cerebellar
peduncle (aka: brachium
conjunctivum)
– Most fibers cross the midline
(decussation)
Cerebellar Peduncles
Outputs of
Functional
Divisions
Cerebellar Outputs
+ more
+ more
Vestibulocerebellar
and Medial
Spinocerebellar Outputs
• Flocculonodular lobe
receives vestibular input and
projects directly to vestibular
nuclei
• Vermis receives input from
neck, trunk, vestibular, retina
and extraocular muscles.
Output focuses on
ventromedial descending
motor systems
(reticulospinal,
vestibulospinal, and medial
corticospinal)
Zones of cerebellar cortex, deep
nuclei and inferior olive
Lateral Spinocerebellar
and Cerebrocerebellar
Outputs
•
Intermediate zone of
spinocerebellum receives sensory
input from limbs and influences
dorsolateral descending motor
systems (rubrospinal and
corticospinal) acting on ipsilateral
limbs
•
Cerebrocerebellum receives input
from many cortical areas via the
pontine nuclei and influences those
areas via dentato-thalamo-cortical
projections. There is also dentate red nucleus – inferior olive loop
– Note: magnocellular RN involved
– Note: parvocellular RN involved
distal parts of limbs
Sometimes referred to by
its latin name, Nucleus Ruber
Ruber = “red”
Microzones &
Microcomplex
from red nuc.
~5000 microcomplexes in human cerebellum
Microcomplex = microzone + related deep nucleus+nuclear target+olivary region
Cerebellar Cortex
Deep Nuclei
Thalamus
mossy fibers
climbing fibers
Cerebral Cortex
Cerebral Cortex
Cerebellar Cortex
Deep Nuclei
Thalamus
Inferior
Olive
Red
Nucleus
Cortico-ponto-cerebello-thalamo loop
Inferior
Olive
Red
Nucleus
Sensory Input
Motor Execution
Pontine Nuclei
Deep Nuclei
Inferior
Olive
Red
Nucleus
mossy fibers
climbing fibers
Cerebellar Cortex
Olivary Loops Via Red Nucleus
Cerebral Cortex
Deep Nuclei
Thalamus
Sensory Input
Cerebellar Cortex
Inferior
Olive
Red
Nucleus
Motor Execution
Pontine Nuclei
mossy fibers
climbing fibers
Local Inferior Olive Loop
Thalamus
Sensory Input
Motor Execution
Pontine Nuclei
Cerebral Cortex
mossy fibers
climbing fibers
Overall Picture: Cerebellar Loops
Sensory Input
Motor Execution
Pontine Nuclei
Cerebellar Cortex
Neuronal Organization
• Five types of neurons
– Inhibitory:
•
•
•
•
Purkinje
Golgi
Basket
Stellate
– Excitatory
• Granule
Cerebellar Cortex
Neuronal Organization
• Three Layers of Cerebellar Cortex
– Molecular Layer
• Cell bodies of stellate and basket cells
• Axons of granule cells, called parallel fibers
• Dendrites of Purkinje Cells
– Purkinje Cell Layer
• Cell bodies of Purkinje cells
– Granule Cell Layer
• Granule cells, which receive inputs from the mossy
fibers (Most numerous neurons in brain, 1010-1011)
• Golgi cells, also receive mossy fiber input
Cerebellar
Cortical
Cells
Divergence and Convergence
“Fractured somatotopy”
One body part represented in
Multiple regions due to divergence
Parallel Fibers
200 million MF inputs diverge onto
40 billion granule cells
PF fibers converge onto 15 million PC
Further converge on Deep nuclei
Excitatory and
Inhibitory
Connections
Simple and
Complex Spikes
Recording from
Purkinje Cell
Types of Cerebellar
Damage/Disorder
• There are many conditions that can affect
the cerebellum
• In most human research studies, patients
typically have
– Tumor removal (beware of radiation)
– Diffuse cerebellar degeneration (spino-cerebellar
ataxias – inherited – multiple forms)
– Stroke involving cerebellar vascular territory
Cerebellar Vascular Supply
medial branch SCA
lateral SCA
SCA
SCA=superior cerebellar
artery
AICA=anterior inferior
cerebellar artery
PICA=posterior inferior
cerebellar artery
basilar artery
AICA
vertebral artery
Brainstem
PICA
medial PICA
lateral PICA
Superior Cerebellar Arteries
SCA Supply Zones
PICA Supply Zones
Example SCA Territory Infarct
Example of PICA territory
Infarct
Signs of Cerebellar Damage
Dysmetria
Cerebellar damage videos
• A lack of accuracy in voluntary movements
– Hypermetria = overshoot of target
– Hypometria = undershoot
• Delay in initiation of movement is common
• Occurs proximally and distally in upper and
lower limbs
• Affects both single-joint and multi-joint
movements
• Most pronounced in rapid movements
• Often followed by corrective movements
Balance/Walking Tests
Finger-to-nose Test
Abnormal - Finger-to-nose_WMV V9.wmv
DWFC09ftnmov_57_WMV V9.wmv
SPFSG04romb_57-1_WMV V9.wmv
VSFGS02walkturn_57_WMV V9.wmv
DWFSG7ambleturn_57_WMV V9.wmv
VSFC11ftnmov_57_WMV V9.wmv
youtube.com.Cerebellar ataxia_WMV V9.wmv
Heel-to-shin Test
Dysarthria: Impaired Articulation
DWFMSiSpArtic_57_WMV V9.wmv
Abnormal Coordination Exam ; Heel-to-shin_WMV V9.wmv
VSFMSiSpArtic_57_WMV V9.wmv
VSFC12heelkshin_57_WMV V9.wmv
Impaired rapid alternating movement
Ocular Dysmetria
Dysdiadochokinesia
Abnormal - Hand Rapid Alternating Movements_WMV V9.wmv
VSFC07suppro_57_WMV V9.wmv
DWFC11prosup_57_WMV V9.wmv
youtube.com.Dysdiadochokinesia Song_WMV V9.wmv
Dysmetria of Upper Limb: Pointing Movements
Abnormal EMG in
Cerebellar Patients
Healthy Control
Cerebellar Patient
Normal triphasic pattern
Concise elbow
movement
Elbow
2 bursts not demarcated
Reduced rise rate
Shoulder
Comparable
At slow speed
Hyperextension
of elbow causes
overshoot
Increased latency
Single joint movement, e.g. pull a lever, AGO = agonist muscle (biceps), ANTA = antagonist (triceps)
Manto, M. (2009) J Neuroeng Rehabil 6, 10.
Cerebellar Hypermetria
Normal Subject
Manto, M. (2009) J Neuroeng Rehabil 6, 10.
Adaptation in EyeHand Coordination
Cerebellar Patient
A. Special prism glasses bends light so
that you have to look left to see target
directly in front
B. When prisms are first put on, throws
deviate to the left, but there is adaptation.
When the glasses are removed there is
a rebound effect.
Overshoot
Wrist flexion movement (MVT)
C. Adaptation fails in a patient with
unilateral PICA infarction involving
inferior cerebellar peduncle (inferior
olivary climbing fibers!) and inferior
lateral posterior cerebellar cortex
Models of Cerebellar
Function
Marr: Cerebellar Synaptic Plasticity
Joint activity from parallel
fiber and climbing fiber
was hypothesized to
cause synaptic modification
at the parallel fiber synapse
De Schutter (1997) Prog Brain Res 114, 529-42.
Marr (1969) Model
• Hebb (1949) proposed that synaptic
modification based on co-occurrence of preand postsynaptic activity might underlie
learning
• Marr proposed that parallel fiber synapses
onto Purkinje Cells are facilitated (Long
Term Potentiation, or LTP) when they are
activated together with climbing fiber
activation
Marr (cont)
• Through plasticity
mechanism, cerebellum
could learn movement
skills from experience
• From divergence of
mossy fiber to granule
cells, finer representation
of sensory information
can be achieved
Example
finger 1
and 2
finger 1
Albus (1971)
finger 2
Purkinje cells
granule cells
• Suggested that the cerebellum functions
like a perceptron pattern-classification
device, with complex spikes (from
climbing fibers) as the unconditioned
stimulus and mossy fiber input as the
conditioned stimulus
mossy fibers
pontine nuclei
finger 1
finger 2
Cerebellar Perceptron
Albus (cont)
• Proposed that climbing fiber provides an error
signal
• Also proposed that parallel fiber synapse is
weakened instead of facilitated
– He predicted long term depression (LTD), prior to the
demonstration of its existence by Ito (1982) in cerebellar
slices
– Marr’s modified theory is often referred to now as MarrAlbus or Marr-Albus-Ito model
• There is still much debate on whether the
cerebellum is the locus of motor learning or if it is
more of a control machine
Albus, J.S. (1971) Math Biosci 10, 25-61.
Adaptive Filter Models
What is an Adaptive Filter?
• Introduced in 1982 by Fujita
• Influenced by Ito’s suggestion that
vestibulo-ocular reflex could be
understood in terms of engineering
control theory
• A filter is a hardware or software
device that converts an input signal
into a different output signal
• E.g., in music a “low pass” filter
effectively removes high frequencies
of an audio signal
Low Pass Filter
Adjustable Filter
Gain control allows the amplitude to be adjusted
Treble or tone control allows more or less of the high frequencies to come through
Error
Signal
Adaptive Filter
Current
output
Adaptive Filter
• An adaptive filter can learn to
attenuate a signal only in the noise
frequency band
• E.g., aircraft engine noise
• Requires a second input signal from
microphone as an “error” or
“teaching” signal
spike input
x(t)
p1(t)
w1
error: e(t)
p2(t)
w2
p3(t)
Change in
synaptic
weight
Learning
rate constant
(typically < 1)
w3
y(t) =  wipi(t)
Signals positively correlated with error signal get weight reduced
Signals negatively correlated with error signal get weight increased
e.g. p3 onset at t=3 coincides with
error signal, so w3 is reduced
t=3
spike input
x(t)
p1(t)
w1
error: e(t)
p2(t)
w2
If =0.1, e(t)=1 for error,
otherwise e(t)= -1:
w3=(-0.1)(1)(1)= -0.1
p3(t)
w3
y(t) =  wipi(t)
Signals positively correlated with error signal get weight reduced
Signals negatively correlated with error signal get weight increased
Attractions of Adaptive-Filter Model
of Cerebellum
• Such filters are widely used in signal
processing because they are powerful and
deliver best (least squares) solution
• There is structural resemblance to cerebellar
microcircuit
• Adaptive filters are capable of the kinds of
functions associated with the cerebellum
– Predicting a movement’s sensory consequences
– Refinement of movement so that it is fast and
coordinated
Cerebellar Microcircuit & Adaptive Filters
Predicting Sensory Consequences of Movement:
Noise Cancellation
a. (Theoretical) The goal is to teach
the adaptive filter to cancel out the
noise portion of s(t)+n(t)
An explanation of microcircuit features:
A large number of inputs (mossy fiber) are needed for an adaptive filter
The teaching signal (climbing fiber) must be capable of affecting every
weight without altering filter output
…And Speaking of
Predicting Sensory
Feedback
b. (Practical) The goal is to attenuate
touch signals from whiskers that are
generated by the animal’s own
head movements. Otherwise, every
time whiskers scrape the ground the
animal will interpret it as a possible
food stimulus.
Cerebellar Activation Distinguishes
Between Self-Produced and ExternallyProduced Tactile Sensation
Blakemore et al (1998) Nat Neurosci 1, 635-40.
Adaptive Filter Model and
Accurate Movement
Cerebellar Adaptive Filter for VOR
• Vestibulo-ocular reflex (VOR)
• Goal: Keep an image stable on the
retina as the head is moved by
producing a counteracting eye
movement
Eye muscles
Eye velocity must
match head velocity
to keep image stable
on retina. (When you see “+”
and “–” you are hoping the 2
signals match).
Slightly different from noise cancellation module for 3 reasons
1.
2.
3.
Cerebellar Adaptive Filter for VOR
Output of cancellation module is a motor command to oculomotor system
The slip of the image off the retina is the error signal
A copy of motor command feeds back into adaptive filter
Cerebellar Adaptive Filter for VOR
(b) Adjust these weights
(c) Do vestibular signals cause
Enough eye movements?
Eye muscles
(b) Vestibular signals triggerred
Eye movements are initiated
(a) Head starts to move
Vestibular signals arise
(a) Image slipped off retina
Error!
Cerebellar Adaptive Filter for VOR
(c) Adjust these weights
(b) Again, image slips off retina
Error!
(a) Eye muscles old, weak or damaged.
Insufficient movement.
What about the rest of the cerebellum?
• Specific regions of inferior olive project to
specific strips of cerebellar cortex in sagittal
plane (zones, A-D2)
• Each zone projects to specific deep
cerebellar or vestibular nuclei, which project
to targets in the rest of the brain, which in
turn project back to IO
• Thus there are loops that may be functional
subunits
Evaluation of the model:
Cerebellar flocculus and VOR
• Involvement of flocculus in image stabilization has
been established via lesion and inactivation studies
• Main mossy fiber inputs to flocculus carry
vestibular info and efference copy of eye movement
commands
• Climbing fiber inputs to flocculus carry retinal slip
signals
• Floccular Purkinje cells project to ocular
motoneurons
• Plasticity: when VOR gain requirement is altered
experimentally, Purkinje cell firing changes
Zones of cerebellar cortex, deep
nuclei and inferior olive
Microzones
Cerebellar Chip
• Zones can be further subdivided into
microzones – 5000 estimated
• This organization suggests a
“cerebellar chip”
Challenge for Testing the Model
• In most cases we do not know how a
microzone’s output affects behavior
• Thus identifying the error signal of the
climbing fiber is challenging
State Estimation
Internal Models
• The ability of the brain to control movement
is based on its knowledge of the body’s state
at any moment
• State can be defined by a set of variables
such as velocity and position of different
limb segments
• Given accurate knowledge of current state
and motor commands the brain ought to be
able to estimate the state in the near future
and control it
State Estimation Problem
Delay Problem
• Delay in arrival of afferent signals
from periphery, along with central
processing delays causes out-of-date
knowledge of the peripheral system
• Thus, calculation of a state prediction
is hypothesized, i.e., the state of the
limbs before sensory information
arrives
Forward models
• A forward dynamic model is a
representation of limb status, e.g., joint
angles and velocities given forces
applied
• A forward sensory output model
predicts tactile signals, proprioception,
vision, audition
Forward and Inverse models
• Forward model: Given a motor
command, what is the predicted new
motor state
• Inverse model: Given a desired new
motor state, what is the motor
command needed to achieve it?
Forward models
• Rapid movement cannot rely on
sensory feedback alone
– If they did, movement would have to be
slow or instabilities/oscillations would
occur
– Note: Oscillations are characteristic of
cerebellar damage
Forward “Smith-Predictor” Model
Forward “Smith-Predictor” Model
Motor cortex command.
Copy of command goes to cbl
cerebellum
This is the actual sensory
consequences arising
from the movement.
E.g., Motor controller for hand: want to pick up a ball. Corticospinal system on the outer loop is feedback driven.
The efference copy sent to the cerebellum generates a rapid prediction of hand/arm movements in the forward
dynamic model to derive a state estimate. The forward output model is the predicted sensory information
occurring from the movement with the delay built in.
Forward “Smith-Predictor” Model
Forward “Smith-Predictor” Model
Rapid calc of where hand will be
Rapid prediction of
sensory info with
delays accounted for
When sensory
discrepancy is 0 the
state estimate from
the forward model is
perfect.
Discrepancy of predicted and
Actual sensory information provides
Teaching signal for forward dynamic model
Forward “Smith-Predictor” Model
Discrepancy of state estimate and desired state can
Be used to alter subsequent motor command.
This loop represents
the cerebro-cerebellar
loop.
An Example:
Lifting a carton of milk
• How much grip and force to apply?
• Visual input: size
– In the dark this input is reduced and therefore
weighted less
• Proprioception: resistance to lifting force
– Reduced input and thus reduced weighting if
you are wearing gloves
• Prior belief of how full or empty it is
• All of these factors will influence your state
estimation
Cerebellar Patients
Under this model, with no state estimation from the cerebellum, adjustments
of the motor command must rely on the relatively slow reafference signals.