Motor Systems (Lecture 11)

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Motor Systems(Lecture 11)

• Harry R. Erwin, PhD
• COMM2E
• University of Sunderland

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Resources

• Nicholls et al. (well-referenced, possibly the
  best for neuroscientists)
• Kandel et al. (medical school textbook)
• Shepherd (general textbook)
• Johnston and Wu (emphasizes neurophysiology, I
  dont have)
• Avis Cohen (UMd Bio 708C course notes)
• Bower and Beeman, The Book of Genesis, ch 8.

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Outline

• Motor System Architecture
• The Muscle
• Central Pattern Generators
• Motor Systems in the CNS
• Biologically-Inspired Motor System Models
• Book of Genesis, Chapter 8

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Motor System Architecture

• Hierarchical
• Cortex
• Cerebellum
• Brainstem
• Spinal cord
• Motoneurons
• Muscles

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Muscles

• Muscles are springs and correct for errors. As
  for any spring, oscillation can be an issue, but
  the muscle controls it. The muscle thinks!
• A muscle is made up of multiple muscle
  fibersmultinucleate cells in mammals that
  contain myosin and actin (elastic). These are
  excitable cells like neurons.
• In higher vertebrates, each fiber is innervated
  by a single motoneuron, but a single motoneuron
  can innervate many fibers of a single type. Fine
  motor skills can involve one fiber/one neuron,
  though more usually about 20. (That makes it
  interesting that H. erectus had a significantly
  smaller spinal cord diameter than H. sapiens.)

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Muscle Fibers

• Several types of muscle fibers (the first three
  listed are important)
• SS use oxidative metabolism, are weak, do not
  appear to fatigue, have a role in maintaining
  posture.
• FR are fatigue-resistant, use both oxidative and
  non-oxidative enzymes, are stronger, and their
  motoneurons have intermediate input resistance
  and rheobase (current threshold for initiating a
  spike).
• FF fatigue rapidly, are non-oxidative
  (glycolysis), are strongest with low input
  resistance and high rheobase.
• SS are recruited first, followed by FR, and
  finally FF.
• S are slow and have a slow relaxation time.

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Muscle Contraction Mechanisms

• Individual fibers twitch. Muscle contraction
  uses multiple muscle fibers twitching in a
  pattern. This is non-stochastic action
  potentials always work.
• Myosin and actin are connected by protein
  bridges. The angles of these bridges define the
  force that can be exerted, depending on the type
  of myosin.
• Muscles maximize force when stretched. Going
  beyond that maximum length (pulled), they have
  no force.
• Muscle fibers respond to action potentials (ACh)
  allowing entry of Ca. Cramps reflect a calcium
  deficit.

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Muscle Efferents

• Axon terminals synapse on the fiber. The AP must
  invade entire fiber.
• ACh is the neurotransmitter. Vesicle release
  leads to diffusion across the junction, where it
  binds to receptors and is hydrolyzed by AChE.
  Binding opens cationic (non-specific) channels
  and the membrane potential collapses.

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Spindle Systems

• Some muscle fibers are stretch receptors, rather
  than force producers.
• Lack contractile elements.
• Types include primary and secondary muscle
  spindles.
• Primary spindles report that the fiber theyre
  monitoring is carrying force. Measure rate of
  change, allowing you to control velocity.
• Secondary spindles measure tension directly.
• Not servo control!the muscle turns on first,
  control is later.

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The Spinal Cord

• Organized functionally
• Characterized by fully coordinated rhythmic
  movements.
• Consists of fused dorsal and ventral roots
  surrounding a central canal
• Dorsal roots are sensory (stretch receptors,
  pain, touch, joint position)
• Ventral roots contain motoneurons
• Organized locally into central pattern generators
  (CPGs)
• Ends at the level of the kidneys.

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Rhythmic Movements

• Questions for research
• How do they happen?
• What do they mean?
• Where do they come from?
• Reflex chain?
• Sequential pattern of activation?
• Reverberatory circuits?
• Cutting the spinal cord removes the inhibition of
  flexion/extension movements (Brown, 1914).
• These issues are also present in the CNS, but the
  two communities do not interact much.

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Central Pattern Generators (CPGs)

• A Central Pattern Generator is a system of
  neurons that can generate a stereotyped rhythmic
  movement without sensory afference or somatic
  feedback.
• It can be activated/sustained by a triggering
  stimulus (either tonic or phasic), but requires
  no modulation of the input to generate the basic
  pattern.
• Lundberg and Grillner had a nasty argument on
  whether CPGs are present in the motor system.
  This is Avis Cohens specialty.

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Research into CPGs

• To demonstrate the existence of a CPG
• The stereotyped movement must not be extinguished
  by the removal of varying sensory afference.
• The movement must not be extinguished by the
  removal of somatic feedback.
• Experiments beginning in 1960s produced evidence
  for CPGs. Russian studies of decorticated cats
  showed they could maintain walking motion without
  a cortex.
• Hence the cortex turns walking on.
• Strength of stimulation controls power, not
  frequency.
• Gait changes are automatic.
• Limbs controlled as a whole.
• Primitive mammal-like reptiles give insight here.
  (discuss)

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CPGs and the Spine

• CPG models have been effective in describing how
  coordinated rhythmic movements might be generated
  in the spinal column.
• Involves interneurons (Renshaw cells) in the
  spinal cord. However, these can be turned off and
  the animal still walks.
• Most motor actions are indirectly managed using
  opposing pairs of muscles controlled by a CPG.
  Motor cortex neurons synapse on the spinal
  interneurons (and directly on the motoneurons
  used in delicate finger movements).
• The Renshaw cells are driven hard.

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CPGs in Context

• CPGs seem to generate body shape, not force
  commands.
• An acute spinalized curarized deafferented cat
  still walks.
• CPG does not require sensory feedback
• CPG does not require descending control
• Reflex loops do not operate during locomotion.
  The spinal cord decides whether you step on
  something sharp. Corrections and adjustments to
  ground features are all handled by the CPG.

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Motor Systems in the CNS

• Motor cortex (and related cortices)
• Basal ganglia
• Cerebellum
• Brain-stem nuclei

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Issues

• How are CPGs controlled by the CNS?
• Do as I do?
• Do as I say?
• Do as I suggest?
• Is the response
• An act? (time-dependent)
• A place? (autonomous)
• A combination?

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Hypothesis

• Motor commands are suspected of specifying an
  image of attainment.
• Passiveposture
• Activean action

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Mechanisms of Coordination

• Preservation of phase relationships
• Non-linear
• Developmentally tuned
• Phase differences are fixed
• CNS provides drive
• Spine returns periodic signal to the CNS
• Mutual entrainment of spine and CNS

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Motor Cortex

• Probably uses dense (vector) rather than sparse
  coding.
• Specifies terminal position of movement in
  world-centered coordinates.
• The spinal cord seems to work in body-centered
  coordinates. Giszter et al. claim that there are
  only four degrees of freedom in the spinal cord
  of frog.
• Cerebellum may be responsible for the change of
  coordinates.

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Cerebellum

• Seems to be a sensory system (Bower)
• Receives motoneuron and sensory copies, via
  separate pathways.
• Outputs a periodic inhibitory signal to the
  spinal cord
• Very fast response
• Extremely large primary (Purkinje) cells.
• Need to be modeled below the ion channel level.
  5000 compartments are typical.

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Basal Ganglia

• Play a role in willed (rather than
  stimulus-triggered) acts.
• No convergence in the striatum. Multiple parallel
  modules.
• Convergence at the Globus pallidus (GP).
• Feedback loop
• Cortices (PM, SuppM, M, SS)
• Putamen (part of the striatum, hard to excite,
  hence sensitive to synchronization, input from
  Substantia nigraParkinsons)
• GPext (feedback relationship with the SubThalNuc,
  inhibited by Putamen)
• GPinf and SNreticulata (excited by GPext and
  inhibited by Putamen)
• Thalamus (inhibited by GPinf and SNR, excites the
  prefrontal and premotor cortex).

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Biologically-Inspired Motor System Models

• Two-way street all the way down. The cortex
  should command a CPG, which then drives the
  cortex in return, signals the motoneurons, and
  interacts with sensory afferents.
• This is a universal picture, using comparisons at
  all levels. See Rodney Brooks robot models.
• Note that if feedback is specific,
  cell-to-cell-back-to-original cell (as in the
  inferior colliculus), this supports a
  back-propagation model for training (not just
  reinforcement learning!).

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Back to Central Pattern Generators

• The neuronal circuits that support rhythmic
  muscle contractions are referred to as central
  pattern generators (CPGs)
• These circuits can generate this activity in
  isolation.
• The ability to switch between CPGs relies on
  feedback from proprioceptors and higher CNS
  control.

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Two-Neuron Oscillators
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The Math of the System

• d?i(t) ?i (in modular terms)
• ?i(t) (?i ?i(0) ) (mod 2?)
• When coupled, we get
• d?1(t) ?1 h12(?1, ?2)
• d?2(t) ?2 h21(?2, ?1)
• ?(t) ?1(t) - ?2(t)
• This describes the phase lag of oscillator 2
  relative to oscillator 1.

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Calculating

• d?(t)/dt d?1(t)/dt - d?2(t)/dt
• (?1- ?2)(h12(?1, ?2) - h21(?2, ?1))
• Now assume hij is a function of ?1-?2, and is
  zero at zero. This is called diffusive coupling.
• For the phase lag to remain constant,
• d?(t)/dt 0.
• If hij is proportional to the sin of the
  difference, we get different solutions depending
  on the constant of proportionality, depending on
  the ratio of ?1 - ?2 to the sum of the constants
  of proportionality.

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Why is this interesting?

• It suggests that the typical behaviour of CPGs
  should move from phase drift to phase-locking and
  potentially oscillator death for large networks.

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Four Neuron Oscillators

• Show similar but more complex behaviour.
• Representative to fish swimming (and by
  implication of tetrapod walking)
• Gives some insight into how gaits might be
  modelled.
• Gives us confidence that our models allow us to
  understand more complex CPGs.