In the last decades, electrophysiological and imaging-based approaches provided significant new insights into the mechanisms of neuronal development. Nevertheless, many important questions remain unanswered. How does the fine control of a motor output develop? How does sensorimotor integration in the early and subsequent phases of brain development shape behavior? How does sensorimotor development evolve in awake and sleeping states? What role do myoclonic twitches play in this process? Answering these questions requires performing high-precision tests in the brain of non-anesthetized animals across sleep and wake during the early stages of their postnatal development. Such tests require head-fixation apparatus suitable for neonatal and juvenile rodents. The Mobile HomeCage combines a stable head-fixation with an air-lifted cage that closely resembles laboratory rodents’ natural habitat – an optimal platform for studying early postnatal brain development. In this webinar, Dr. Cavaccini (Prof. Karayannis’s lab at the Brain Research Institute, University of Zurich) and Dr. Dooley (Prof. Blumberg’s lab at the University of Iowa), share their insights into the development of rodent sensorimotor neuronal circuits during early postnatal life. They elucidate the cortical and subcortical mechanisms involved in the development of sensorimotor circuitry during wakefulness (in a mouse model) and REM sleep (in a rat model). Key Takeaways Dr. Anna Cavaccini: - Anatomical and functional changes occur at the striatal level before and after the onset of different sensory modalities - Locomotor activity changes throughout early development, and it correlates with striatal function - Sensory information coming from whiskers affects locomotion and striatal function before and after the onset of different sensory modalities Dr. James Dooley: - Myoclonic twitches in REM sleep continue to trigger cortical and thalamic activity beyond the early postnatal period - Twitch-related thalamic activity is spatiotemporally refined by the third postnatal week - Motor thalamus activity reflects an internal model of movement produced by twitches and is dependent on the cerebellar output

1. Sensorimotor Network Development
During Early Postnatal Life in the
Awake and Sleeping Brain
Anna Cavaccini, PhD
Post-Doctoral Fellow
Brain Research Institute
University of Zurich
James Dooley, PhD
Assistant Research Scientist
Psychological and Brain Sciences
University of Iowa

2. Sensorimotor Network Development
During Early Postnatal Life in the
Awake and Sleeping Brain
Dr. Anna Cavaccini and Dr. James Dooley share insights into the
development of rodent sensorimotor neuronal circuits during early
postnatal life in wakefulness and REM sleep.

3. Anna Cavaccini, PhD
Post-Doctoral Fellow
Laboratory of Neural Circuit Assembly, Prof. Karayannis’ lab
Brain Research Institute
University of Zurich
Striatal Development
and Motor Behaviors
Copyright 2021 A. Cavaccini and InsideScientific. All Rights Reserved.

4. • Introduction
• Central Hypothesis
• Aims
• Methods
• Results
• Conclusion
• Future Perspectives
Agenda

5. Basal Ganglia Circuits and Movements
Striatum
Motor
Control

6. Basal Ganglia Circuits and Movements
Cortex
Striatum
Gpi/SNr
Brainstem
Spinal Cord
Muscles
Thalamus
Athalye VR., et al., Current Opinion
in Neurobiology, 2020
Arber S. & Costa RM., Science, 2018

7. Locomotion Changes Over Development
P10 P28
van der Bourg A. et al., Cerebral Cortex, 2017

8. Sensory Systems Development
Xu X., et al., Front. Neurorobot., 2020
Onset of different sensory modalities

9. Cortical inputs to striatum
Hunnicutt B.J., et al., eLife, 2016
Cortex Adult Mice
Sensory
Cortical
Areas
M1
Striatum

10. • In Striatum, excitatory synapse
density rises dramatically between
P10 and P21
• mIPSCs frequency increases
• Glutamate uncaging induces
synaptogenesis in brain slices from
P10 mice pups
• Changes in morphology and intrinsic
properties of striatal neurons
Striatal Circuits Changes Over Development
Glutamate
GABA
Kozorovitskiy Y., et al., Nature, 2012
Krajeskiet R.N. al., J. Physiol., 2019

11. • Introduction
• Central Hypothesis
• Aims
• Methods
• Results
• Conclusion
• Future Perspectives
Agenda

12. Central Hypothesis
Hunnicutt B.J., et al., eLife, 2016
Cortex Adult Mice
Sensory
Cortical
Areas
M1
Striatum

13. Central Hypothesis
Hunnicutt B.J., et al., eLife, 2016
Cortex in Adult Mice
S1 M1
Thalamus
Sensory Inputs
Motor Output
modulation

14. Central Hypothesis
Hunnicutt B.J., et al., eLife, 2016
Cortex in Pups
S1 M1
Thalamus
Sensory Inputs

15. Central Hypothesis
Hunnicutt B.J., et al., eLife, 2016
Cortex in Pups
S1 M1
Thalamus
Sensory Inputs
Gόmez L.J., et al., J. Neurosci., 2021

16. Central Hypothesis
Hunnicutt B.J., et al., eLife, 2016
Cortex in Pups
Cortex
Thalamus Striatum
Locomotion

17. Aims
• To evaluate the striatal output
over development
• To evaluate the correlation of
striatal output with locomotion
over development
Onset of different sensory modalities
<P15 >P15

18. • Introduction
• Central Hypothesis
• Aims
• Methods
• Results
• Conclusion
• Future Perspectives
Agenda

19. Methods: what do we need to do?
Striatum
Neuronal recording
Locomotion

20. Methods: how can we record brain activity and locomotion in mouse pups?
• Need for acute experiment with head-
fixed mice:
 Mouse pups cannot carry an
implant, it would be too heavy
 Mothers cannibalize pups with
implants, so it cannot be chronic
• Mouse pups are not so strong and don’t move a lot, so a system that they
can easily move, not too heavy, allowing for the head-fixation and
locomotion tracking is needed

21. Methods
• Mobile Home Cage with
locomotion tracking system
• Silicon Probe Recordings
Experimental Setup

22. • Introduction
• Central Hypothesis
• Aims
• Methods
• Results
• Conclusion
• Future Perspectives
Agenda

23. Locomotion Changes Over Development
P10 P28
van der Bourg A. et al., Cerebral Cortex, 2017

24. Results:
Locomotion
Analysis
• Speed increases over
development
P11
180 mm
P15
180 mm 180 mm
P24
This content is confidential and not intended to be distributed to anyone

25. Results:
Locomotion
Analysis
• Travel Distance and the
exploratory behavior
increase over development
over development
P11
180 mm
P15
180 mm 180 mm
P24
This content is confidential and not intended to be distributed to anyone

26. DII
Results:
Silicon Probe
Recordings
This content is confidential and not intended to be distributed to anyone

27. • Striatal firing rate increases
over development
• Early on striatal activity
shows a lower correlation
with locomotion
MUA
Speed
This content is confidential and not intended to be distributed to anyone
Results:
Spiking Activity
Analysis

28. • Introduction
• Central Hypothesis
• Aims
• Methods
• Results
• Conclusion
• Future Perspectives
Agenda

29. Conclusion
• Mouse pups show a reduced
explorative behavior, and locomote less
than young adult mice, considering the
speed and the travel distance
• Early on stratal firing rate is decreased
compared to young adult mice, thus
suggesting a different engagement of
striatum
• Early on striatal activity is less
correlated to locomotion
This content is confidential and not intended
to be distributed to anyone
Mouse Pups
Cortex
Thalamus Striatum
Locomotion

30. • Introduction
• Central Hypothesis
• Aims
• Methods
• Results
• Conclusion
• Future Perspectives
Agenda

31. Future Perspective
• Anatomical characterization of the
inputs engaging striatum at different
time points
• Functional characterization of the
circuit at different time points through
silicon probe and patch-clamp
recordings
Image caption
This content is confidential and not intended
to be distributed to anyone

32. Acknowledgments
Prof. Dr.
Theofanis Karayannis
Gwenn Renaud Jaquier

33. …and Keep Moving
Thanks a lot!!!

34. James Dooley, PhD
Assistant Research Scientist
Psychological and Brain Sciences
University of Iowa
james-c-dooley@uiowa.edu
The Developmental Emergence of Cerebellar
Models of Movement Revealed During Sleep
Copyright 2021 J. Dooley and InsideScientific. All Rights Reserved.

35. Catching a treat

36. Catching a treat
Let’s watch this again, but
this time, pay attention to
how Zelda needs to move
her head to where the
treat is going to be, rather
than where it is.

37. Catching a treat
Let’s watch this again, but
this time, pay attention to
how Zelda needs to move
her head to where the
treat is going to be, rather
than where it is.

38. Grabbing a ball – toddler
edition

39. Grabbing a ball – toddler
edition
This task challenging because every
time his hand got to where the ball was,
it had moved.
This highlights the biggest problem with
sensory-driven actions:
Because of unavoidable delays, our
sensory inputs tell us where things
were, not where they are.

40. How do our brains solve the
problem of sensory delays?
Instead of moving to where the object is,
move to where the object is going to be.
To do this, our brain has to be capable of
predicting:
The sensory delay
The motor delay
The ball’s trajectory
How the brain predicts these two delays
are what today’s talk is about

41. Sensory and motor delays
Motor delay
Motor

42. Sensory and motor delays
Motor
Sensory

43. Sensory and motor delays
Sensory delay
Motor
Sensory

44. Sensory and motor delays
Together, these two delays result in highly
predictable sensory feedback.
“If I produce a given motor command, I
expect sensory feedback after ___
milliseconds.”
Motor delay Sensory delay
Motor
Sensory

45. Sensory and motor delays
Together, these two delays result in highly
predictable sensory feedback.
“If I produce a given motor command, I
expect sensory feedback after ___
milliseconds.”
This is the basis for a type of prediction
called a forward model.
Forward models predict the sensory
feedback that will result from a given
motor command and shift it ahead in
time.
Motor
Sensory
Motor copy

46. Sensory and motor delays
Together, these two delays result in highly
predictable sensory feedback.
“If I produce a given motor command, I
expect sensory feedback after ___
milliseconds.”
This is the basis for a type of prediction
called a forward model.
Forward models predict the sensory
feedback that will result from a given
motor command and shift it ahead in
time.
Motor
Sensory
Motor copy

47. Sensory and motor delays
Together, these two delays result in highly
predictable sensory feedback.
“If I produce a given motor command, I
expect sensory feedback after ___
milliseconds.”
This is the basis for a type of prediction
called a forward model.
Forward models predict the sensory
feedback that will result from a given
motor command and shift it ahead in
time.
Motor
Sensory
Motor copy

48. Sensory and motor delays
Together, these two delays result in highly
predictable sensory feedback.
“If I produce a given motor command, I
expect sensory feedback after ___
milliseconds.”
This is the basis for a type of prediction
called a forward model.
Forward models predict the sensory
feedback that will result from a given
motor command and shift it ahead in
time.
Motor
Sensory
Motor copy

49. The Cerebellum
This combination of a forward model and
sensory inhibition was hypothesized to
occur in the cerebellum in 1993.
They further predicted that this internal
model could not be “pre-programmed,”
concluding that it must develop.
“The size of the feedback time delay
could be estimated by measuring the
delay between issuing a motor command
and assessing its result. This would be
most easy to do if the motor command
were discrete…, for the reafferent signal
would then change abruptly.”
Motor
Sensory
Motor copy
Miall et al., 1993

50. What do we know about internal models?
Because internal models of movement are noisy, researchers
need 100s or even 1000s of identical movements in order to
reliably determine how neural activity is patterned.
Bova et al, 2020; eLife
The need for training makes studying the development of
internal models difficult, if not impossible.

51. You would need a self-generated
movement that:
• Is produced spontaneously 100s of
times a day
• Is discrete and highly stereotyped
• Drives precise neural activity
In order to see an internal model during development…

52. You would need a self-generated
movement that:
• Is produced spontaneously 100s of
times a day
• Is discrete and highly stereotyped
• Drives precise neural activity
In order to see an internal model during development…

53. Confirm that twitches:
1. Are produced spontaneously 100s of times a day.
2. Are discrete and highly stereotyped.
3. Drive precise neural activity.
4. Are represented by an internal model of movement.
Outline

54. Experimental subjects
P12
P20

55. Visualizing twitches
Twitching at full speed

56. Twitching at one quarter speed
Visualizing twitches

57. Experimental Design
All data was collected in the Mobile
HomeCage
Data were collected continuously across
3-6 hours as pups cycled between sleep
and wake
The pup’s behavior was recorded using
highspeed (100 fps) video synchronized to
the electrophysiological data

58. Recording locations
Motor
Sensory
Motor copy

59. Recording locations
VP, which receives exclusively sensory
input.
VL, which receives both sensory inputs
and inputs from the cerebellum.
Motor
Sensory
Motor copy

60. Representative data during active sleep

61. Outline
Confirm that twitches:
1. Are produced spontaneously 100s of times a day.
2. Are discrete and highly stereotyped.
3. Drive precise neural activity.
4. Are represented by an internal model of movement.

62. Representative data during active sleep
Number
of twitches ~2000
~1000
~500

63. Confirm that twitches:
1. Are produced spontaneously 100s of times a day.
2. Are discrete and highly stereotyped.
3. Drive precise neural activity.
4. Are represented by an internal model of movement.
Outline

64. The time course of a twitch
Width at half-height

65. The time course of a twitch

66. Confirm that twitches:
1. Are produced spontaneously 100s of times a day.
2. Are discrete and highly stereotyped.
3. Drive precise neural activity.
4. Are represented by an internal model of movement.
Outline

67. Thalamic neurons show somatotopic precision
We’ve previously shown that twitches
drive neural activity at P12
VP neural
activity
(z-score)

68. Thalamic neurons show somatotopic precision
We’ve previously shown that twitches
drive neural activity at P12
This is the mean response of forelimb-
responsive neurons to forelimb
twitches
VP neural
activity
(z-score)

69. Thalamic neurons show somatotopic precision
These are the same forelimb-
responsive neurons
They show no change in activity
following hindlimb, whisker, and tail
twitches
VP neural
activity
(z-score)
VL neural
activity
(z-score)

70. Thalamic neurons show somatotopic precision
These are the same forelimb-
responsive neurons
They show no change in activity
following hindlimb, whisker, and tail
twitches
VP neural
activity
(z-score)
VL neural
activity
(z-score)

71. Thalamic neurons are temporally precise by P20
VP neural
activity
VL neural
activity

72. Confirm that twitches:
1. Are produced spontaneously 100s of times a day.
2. Are discrete and highly stereotyped.
3. Drive precise neural activity.
4. Are represented by an internal model of movement.
Outline

73. Relationship between movement and neural activity

74. Relationship between movement and neural activity
Time

75. Relationship between movement and neural activity
Representative
neural
activity (sps)
Baseline
Max
VP P12

76. Relationship between movement and neural activity
% of
neurons

77. Is the twitch-related
activity inVL at P20 really a
forward model?
If it is, we should be able to eliminate
it by blocking cerebellar inputs
We injected either muscimol or saline
into the deep cerebellar nuclei.
Motor
Sensory
Motor copy

78. Is the twitch-related
activity inVL at P20 really a
forward model?
If it is, we should be able to eliminate
it by blocking cerebellar inputs
We injected either muscimol or saline
into the deep cerebellar nuclei.
Muscimol should block the forward
model, but not sensory inputs, in VL.
Motor
Sensory
Motor copy

79. Inhibition of cerebellar inputs inVL at P20

80. Confirm that twitches:
1. Are produced spontaneously 100s of times a day.
2. Are discrete and highly stereotyped.
3. Drive precise neural activity.
4. Are represented by an internal model of movement.
Outline

81. Internal models of movement emerge between P16 and P20.
Twitches reveal the development of internal models of movement.
The cerebellum both creates a forward model and cancels expected
sensory feedback.
Conclusions

82. From Miall et al., 1993
“The size of the feedback time delay could be estimated by measuring the
delay between issuing a motor command and assessing its result. This
would be most easy to do if the motor command were discrete…, for the
reafferent signal would then change abruptly.”
Future direction:
Test whether twitches are necessary to create and calibrate the timing
of these cerebellar models of movement.
Conclusions

83. Thank you!
Questions? Email me at james-c-dooley@uiowa.edu

84. 1. Learn more about the Dr. Cavaccini’s and the Karyannis Lab’s research:
www.hifo.uzh.ch/en/research/karayannis.html
2. Learn more about Dr. Dooley’s and the Blumberg Lab’s research:
https://psychology.uiowa.edu/blumberg-lab
3. Learning more about Neurotar’s MobileHomecage:
www.neurotar.com/the-mobile-homecage/
Thank you for participating!
Before you go…