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Models of Brain Function > Week 3: Spinal Cord Network of Lamprey = CHECKED > Flashcards

Week 3: Spinal Cord Network of Lamprey = CHECKED Flashcards

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1
Q

Hierarchy of computation models going from very simplified to very detailed

A

Standard artifical neurons with no dynamics to multi-comaprtment condutance based models HH

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2
Q

we may predisposed to pick the “most realistic” model (close to biology)

A

that would be the most complicated model

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3
Q

All models are approximations (e.g., It does not model everything that is going on in the cell) , even..

A

even the most complex model; the multi-compartment conductance based models (HH)

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4
Q

All models are approximation so aim is not to imitate

A

close to biology but pick right model for question you are answering

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5
Q

Research has found that the spinal cord is not just a relay station (Cabelugen et al., 2003; Delvolve et al., 1997)

Methods (3)

A

They did a decerebrated preparation on a salamander so its only left with brain stem and spinal cord

Fixed their body in a solution which keeps their tissue in a viable state

Injected two electrodes to the MLR (just above the brain stem) that has a constant signal of current (no oscillation)

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6
Q

What is MLR stand for?

A

Mesencephalic Locomotor Region

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7
Q

Research has found that the spinal cord is not just a relay station (Cabelugen et al., 2003; Delvolve et al., 1997)

Results (2)

A

At low MLR stimulation, rest of the body attached to spinal cord will perform a walking gait

At high MLR stimulation, it will turn into a swimming gait

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8
Q

Research has found that the spinal cord is not just a relay station (Cabelugen et al., 2003; Delvolve et al., 1997)

Conclusion (2)

A

They found depending on strength of input to brainstem we get different movements

This shows that we don’t need higher brain areas to produce locomotion patterns and that spinal cord is not a mere relay

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9
Q

Two ways to record locomotor modes of salamanders (2)

A

Fictive locomotion

In vivo EMG data

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10
Q

EMG records the

A

electrical activity in muscles via electrodes

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11
Q

EMG data of salamander shows that muscle activation is different for the salamander’s

A

different locomotor modes

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12
Q

From EMG data, the swimming gait of the salamander shows (2)

A

Wave of muscle activity that travels down the body (travelling wave)

There is a constant lag between one muscle and the next

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13
Q

From EMG data, the walking gait of the salamander shows (2)

A

All muscles on one side of the trunk being active at first in unison with two legs

next cycle these muscles are silent and other side of the trunk is active (standing wave)

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14
Q

Fictive locomotion metholodgy (2)

A

Extract the whole spinal cord and put it into a solution (which has NMDA) that keeps tissues in a viable state

Electrodes are placed directly on the ganglia

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15
Q

What is ganglia?

A

Nerves that come out of the spinal cord

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16
Q

Ficitive Locomotion what do you measure?

A

Measure the electrical activation of the spinal cord nerves which will summed to be the collective output of many spinal cord neurons sending action potential along the nerves

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17
Q

Ficitive Locomotion what do you measure?

A

Measure the electrical activation of the spinal cord nerves which will summed to be the collective output of many spinal cord neurons sending action potential along the nerves

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18
Q

NMDA is…

A

Excitatory NT which makes neuron fire

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19
Q

Ficitive locomotion measured from

A

Ventral root recordings (VRs) - nerve ending that goes the muscles

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20
Q

Fictive locomotion collective input graph (2)

A

Neighbouring spinal segments peak at slightly offset times

–> there is a phase lag

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21
Q

Diagram of fictive locomotion collective input graph:

A
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22
Q

From fictive locomotion collective input example from graphs, this reflects the properties we have seen in spinal networks like in …. as … (2)

A

muscle activation in the salamander’s swimming pattern

there is a wave of muscle active that travels down their body (traveling wave) and there is a constant lag between one muscle and the next one.

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23
Q

In fictive locomotion, the neighbouring spinal segments peak at slightly different them and have a phase lag

suggests the neural organisation of the spinal cord that… (2)

A

Suggests that spinal segments (as neural networks) must be coupled to each other to influence each other locally

(e.g.,, one side of muscle is active the other side of muscle is relaxed)

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24
Q

In terms of understanding how neurons work in salamanders on how they generate muscle activation for swimming, we have to use lampreys to ask this as (2)

A

more single neuron data on lampreys

swims like a salamander (i.e., muscle contract in alteration, left-right, left-right and slightly delayed along the body)

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25
Q

Extra Reading Actual swimming behaviour of lampreys from EMG data (4)

A
  • The lamprey swims by producing an alternating activation of motor neurons on left and ride of each segment
  • 100 different segments are activated successively with a phase delay
  • This allows the animal to push through water
  • The higher the frequency of alternation, the faster it will swim
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26
Q

Extra Reading Fictive methodology in lampreys show that

A

Activation of NMDA receptors can give rise to alternating burst activity in low-frequency (0.1-3Hz)

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27
Q

Various studies recorded individual neurons of lampreys, measured their ion channels and measured synaptic connectivity to produce

A

spinal network of lampreys

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28
Q

Diagram of lamprey locomotor network

A
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29
Q

In the diagram of lamprey locomotor network it represents

A

one segment of the spinal cord

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30
Q

Lamprey locomotor network

What does CCIN mean?

A

cross inhibitory neurons

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31
Q

Lamprey locomotor network

What does EIN mean?

A

excitatory inter neuron

32
Q

Lamprey locomotor network

MN is

A

motor neurons

33
Q

**Extra Reading The spinal cord network of lampreys how does it work to produce locomotion? (5) **

A
  1. The alternating rhythmic activity is initiated when the interneurons and motor neurons (MN) receives the descending excitation from reticulospinal (RS) neurons in the brainstem (McCllellan & Grillner, 1984)
  2. Recurrent connection between the EIN within half-segment of spinal cord
  3. These EINs have an excitatory connection to MNs which will make muscle contract
  4. At same time, EINs
    excite the CCINS which have inhibitory connections to all the neurons of the other side of the spinal cord (contra-lateral half segment)
  5. This means inhibition of contra-lateral half segment means one side of the spinal cord is active while other side is silenced (prevent from firing APs) so both sides not active simultaneously
34
Q

What does it mean when there is tonic input from the brain stem?

A

constant flow of action potentials is impacting the spinal cord neurons

35
Q

Diagram of recurrent connection

A
36
Q

Extra ReadingWhat makes one-half of the spinal cord segment stop firing action potentials if tonic input is from the brain stem? (2)

A
  1. Spike-frequency adapation
  2. Lateral Interneurons (LINs) being active mid-cycle and inhbiting CCINs
37
Q

Extra Reading: LINs terminate ongoing activity so alternating activity occurs by

A

Later during ipsilateral bursting activity of EINs and MNs, the LIN becomes active, inhibiting the CCIN and allowing network neurons on the contralateral side to disinhibit (Wallén et al., 1992).

38
Q

Spike frequency adaptation means..

A

the reduction of a neuron’s firing rate to a stimulus of constant intensity.

39
Q

Spike frequency adaption research,

Yasunhiko and Tadashi (1999) found that

A

As you increase the input of current that is injected, number of action potentials increased and takes longer to reach to a steady state

40
Q

How does spike-frequency adaptation help to terminate activity on one side of a spinal cord segment? (4)

A

One side of spinal cord segment becomes active first in which EINs fire loads of APs which inhibits the other side of spinal cord

After a while of firing APs, spike-frequency adaptation takes place so firing rate of EINs reduces

The intervals of EINs without spikes becomes larger with time which makes other side of spinal cord not as strongly inhibited (i.e., fewer inhibitory APs arrive at the contra-lateral side)

This means the other side time to become active and starts firing multiple action potentials quickly in succession and inhibits the previously active side (called escape from inhibition)

41
Q

Spike-frequency adapation is due to a phenomenon called

A

sAPH

42
Q

sAPH is

A

spike after hyer-polarisation

43
Q

Hyperpolarisation means that (2)

A

Membrane potential becomes more negative than resting membrane potential

It makes it more difficult for next spikes (i.e., fire action potentials ) to be emitted in that neuron

44
Q

sAPH is because of (4)

A

Ca+ flows into the cell (due to Ca+ ion channel opening) with each action potentials (alongside Na+) and slowly accumulates in neuron

Ca+ has a hyperpolarization
current through different ion channel (Kaca channel) that brings down the MP down slowly

The accumulation of Ca+ is sensed by a channel called Calcium-dependent Potassium Kca channel

The Ca+ accumulates slowly until it reaches a steady-state where the amount of Ca+ transported away (decay of Ca+ concentration) equals to the amount of Ca+ that flows in.

45
Q

How is neural properties of spinal cord determining this network function of locomotion?

A

A single cell model using HH neuron model

46
Q

In HH we have an equation for each

A

individual ion channel

47
Q

In multi-compart HH model, it is different from HH model as it has (2)

A

they have multiple compartments that constitute different parts of the neuron

Each compartment has different channels (Na, K, Ca, Kca)

48
Q

Diagram of Ekeberg’s single cell compartment model

A
49
Q

Single-cell model of multi-compartment HH has a

A

soma compartment and three other compartment for the dendrites of the neuron.

compartment is made up of sodium , potassium , calcium [Ca] and calcium-dependent potassium ion channels [KCa]

50
Q

Single-cell multi-compartment model of HH was proposed by

A

Ekeberg et al., (1991)

51
Q

In the multi-compartment HH model, equation of rate of change of MP over time,

if Eleak (resting MP) is equal to E (current MP) and there aren’t any inputs then (2)

A

change of MP over time (dE/dt) is 0

neuron stays at rest

52
Q

Pros of multi-compartment HH model (2)

A

It is more realistic and closer to biology

stimulate effects of ion channels (i.e., ion channels given by separate equations)

53
Q

Cons of multi-compartment HH model (3)

A
  • Need more data to fix the composition of ion channels as need to measure elements of equation in real neurons for model to map loosely to biology (very labour intensive task)
  • Very expensive computationally to stimulate in computer (perform equation for every compartment for every different ion channel)
  • Hard to tune parameters (because haven’t measured all parameters then come up with plausible values but there is whole range of values to utilise and have to make a decision of which ones)
54
Q

In the multi-compartment HH model, the equation of rate of chanve of MP over time

tells how (2) and Ekeberg at each timestep get

A

MP changes over time

At each timestep, get value of MP and plot it

55
Q

Evidence of sAPH in multi-compartment HH model (3) using DE/dt (change of MP over time)

A

Ca+ flows in, activates a hyperpolarising current bringing MP down

as Ca+ decays, MP goes up

This is what gives increase in spike distance (spike frequency adaptation)

56
Q

The change in calcium concentration is modelled in Ekeberg’s single cell model by a

A

differential equation:

57
Q

From experiments, they found there are two types of calcium pools (2)

A

First calcium pool is one where Ca+ flows in and entering through Ca+ channels due to each AP in soma

Second Ca+ pool is Ca+ flows in at NMDA synapse (when NMDA receptors are activated)

58
Q

The calcium-dependent potassium current strength equation in Ekeberg’s paper is

A

driven by the two calcium pools

59
Q

Two pools of Ca+ in whcih we have fast and slow

Inflow and decay of Ca+ ions happen

Fast for

Slow for
(4)

A

Ca+ dynamics

Inflow and decay of Ca+ ions happen at different time scales for these two pools

It is fast for membrane Ca+

It is slow for NMDA-synapse Ca+

60
Q

For Ca+ membrane, Ca+ goes in

A

with each AP

61
Q

For NMDA-synapse Ca+ goes in due to…. (2)

A

Ca+ goes in due to receptor-docked on NMDA synapse

After enough Ca+ accumulates (accumulation of Ca+ sensed by Calcium-dependent Potassium channel), triggers a strong hyper-polarising current to bring MP down.

62
Q

What is plateau potentials generally?

A

When action potentials are blocked with Tetrodotoxin

63
Q

In NMDA plateau potentials,

It is when you block the generation of action potentials with TTX (tetrodotoxin) which - (3)

A

suppresses Na+ channel from opening and closing as well as no Ca+ flowing in soma so does not affect MP

Still can affect MP with other ion channels

There is strong and constant NMDA input (Ca+ flowing in NMDA synapse) which brings MP up, MP plateaus and then decays (When enough Ca+ accumulates, one of Calcium-dependent Potassium channels brings MP down)

64
Q

FL is slower than

A

in vivo locomotion

65
Q

Plateau potentials related to fictive locomotion since (4)

in FL what happens…. NMDA docks

Thus hypothesised NMDA Ca+ dynamics produce

In other words…

(4)

A

In FL, isolated spinal cord is placed in a solution that contains large NMDA concentration

NMDA docks to all the receptors in the spinal cord neurons

Thus it is hypothesised that NMDA Ca+ dynamics produce these slow fictive locomotion signals that are slower than actual in-vivo locomotion

In other words, FL is slower than actual in vivo locomotion due to product of un-naturally large NMDA concentration

66
Q

Wallen et al., (1992) paper where

A

connect multi-compartment HH model neurons in network looks similar for lamprey’s spinal cord network

67
Q

In a paper by Wallen et al., (1992), they stimulated the network of neurons with Kainate that activates non-NMDA receptors which gives

A

There is left and right side alternative of APs (e.g., left side firing APs, other side disinhibited until left side is fatigued then other side active and fires APs; vice-versa)

68
Q

Extra ReadingIn paper by Wallen et al., (1992), with increased stimulation of Kainate,

A

faster oscillations, increased spikes per cycle, translates to faster swimming

69
Q

In paper by Wallen et al., (1992), if you add serontin (5-HT) to HH model of spinal cord (4)

A

It will reduce the influence of Ca-dependent Potassium channel

It will reduce the amplitude of AHP which will be weaker so takes longer for Spike adaptation frequency to occur

Oscillations will last longer

Swimming frequency will be slower

70
Q

In a paper by Wallen et al., (1992),
Higher NMDA added to model,

(2)

A

the slower and longer NMDA osciliations it has

This is because more Ca+ flows in and once have oscillations terminated it takes a long time for Ca+ to decays before neuron becomes active again

71
Q

Evidence of LIN as burst terminating factor (terminates activity of one side) in Wallen et al., paper (3)

A
  • Compared bursting activity of network with LINs connected and disconnected from the network model
  • The rhythm becomes more slower and irregular when LINs as disconnected
  • Thus synaptic inhibitory connections from the LINS onto CCINs constitute this burst terminating factor at the level of activation.
72
Q

In a paper by Wallen et al., (1992),
As we can block action potential generation by blocking Na+ with TTX in the model by (2)

A

Setting sodium conductance to 0

Produces NMDA-plateau potentials

73
Q

The lamprey locomotor network is an example of a

A

central pattern generator (CPG)

74
Q

CPG is

A

networks that take simple inputs (e.g., tonic [i.e., constant] signal from brain stem) and produce a more complex pattern of neural activity (e.g., oscillations for rhythmic muscle activation)

75
Q

Examples of CPG (3)

A

Locomotor networks for different gaits (swimming, stepping trotting etc…)

Heartbeat

Digestion

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