12-week lecture series on "the neural basis of consciousness" by Prof Nao Tsuchiya. Given to 3rd year undergraduate level. No prerequisites. Contents: 1) How can we compute integrated information? 2) How we can estimate the proposed boundary of consciousness? 3) What are the reported phenomenology / behaviors of split brain patients? 4) How does IIT explain various known facts about consciousness, such as split brain patients?

1. Week 11
Neural basis of consciousness:
Consciousness and Integration
Prof Nao Tsuchiya
Twitter: @conscious_tlab
Email: naotsugu.tsuchiya@monash.edu
Facebook: Naotsugu Tsuchiya

2. Recap of Wk 10
Introduction to Integrated Information Theory (IIT)
“From the Phenomenology to the Mechanisms”

3. Recap of Wk 10
Introduction to the IIT-inspired measure of consciousness:
Perturbational Complexity Index (PCI)

4. In Wk 11,
We introduce how to compute integrated information.
From the viewpoint of IIT, we will re-examine the cases of
altered states of consciousness: in particular, split brain.

5. Learning Objectives
To be able to answer the following questions:
● How can we compute integrated information? How we can
estimate the proposed boundary of consciousness?
● What are the reported phenomenology / behaviors of split
brain patients?
● How does IIT explain various known facts about
consciousness, such as split brain patients?
Reading: Chapter 17 in QFC

6. IIT is the theory of: level, boundary and
contents of consciousness
Level: system-level integrated information
Boundary: a subset of the mechanisms that maximizes
system-level integrated information
Contents: a pattern of integrated information among all
(subset of) the mechanisms within the boundary
Computing integrated information

7. Remaining questions from Week 10
Computing integrated information
OK, PCI seems to explain level of consciousness inspired by
the ideas of “integrated information”.
How can we measure integrated information?
How can we estimate the boundary of consciousness?
Understanding these is necessary to understand IIT’s
explanations and predictions on consciousness.

8. How to compute integrated information?
For the latest version of IIT 3.0 (more sophisticated, but math
heavy) see Tutorial.
This lecture will be based on IIT 2.0.
(Balduzzi & Tononi 2008 PLoS Comp, Oizumi et al 2016 PNAS,
Tsuchiya 2017 Philosophy Compass)
Computing integrated information

9. Overall idea behind “integrated information”
1. Determine all possible states for a (sub)system can be in.
E.g. photodiode - on or off, neuron - firing / not
2. Determine how much of its [future / past] states are
constrained / determined by its [current] state [=intrinsic
information]
E.g., Random -> no information (about itself)
3. Quantify how much information the (sub)system loses
when it is [minimally] cut [=integrated information]
Computing integrated information

10. A system A & B has only 4 possible states
Neuron A
Neuron B
Copy
OFF
Copy
ON OFFON
ONON OFFOFF
Computing integrated information

11. Let’s consider a simple example
Neuron A
Neuron B
Time
Current
Computing integrated information
CopyCopy

12. Let’s consider a simple example
Neuron A
Neuron B
Time
Current
Computing integrated information
CopyCopy
On
On

13. Let’s consider a simple example
Neuron A
Neuron B
Time
A and B’s future is completely determined!
Current
Computing integrated information
CopyCopy

14. Let’s consider a simple example
Neuron A
Neuron B
Time
Current
A and B’s past is completely known!
Computing integrated information
CopyCopy

15. How much intrinsic information does AB have?
1. Determine all possible states for a (sub)system can be in.
4 states
2. Determine how much of its [future / past] states are
constrained / determined by its [current] state [=intrinsic
information]
Completely (=2 bits = log2
(4) )
Computing integrated information

16. Now, what happens if we cut (= replace with
noisy connection) between AB?
Neuron A
Neuron B
Copy
OFF
Copy
ON OFFON
ONON OFFOFF
NOISE
Computing integrated information

17. AB does not know what its future state will be!
Neuron A
Neuron B
Time
Current
NOISE NOISE
50%
50%
=
Computing integrated information

18. AB does not know what its past state was!
Neuron A
Neuron B
Time
Current
NOISE NOISE
Computing integrated information

19. 3. Quantify how much information it loses when the
(sub)system is [minimally] cut [=integrated information]
Integrated information
=(Original intrinsic information) - (intrinsic information after cut)
= 2 bits - 0 bits
= 2 bits
Computing integrated information

20. What is the minimal cut?
To estimate how much a system is integrated, we need to find
the weakest link and cut there to identify the integratedness.
No matter how we cut the system,
we lose some information
>> High integration
Computing integrated information

21. What is the minimal cut?
To estimate how much a system is integrated, we need to find
the weakest link and cut there to identify the integratedness.
If we cut “between” subsets, we do
not lose anything
Low (=zero) integration
Computing integrated information

22. What is the minimal cut?
To estimate how much a system is integrated, we need to find
the weakest link and cut there to identify the integratedness.
BUT, if we cut “within” subsets, we
lose a lot
>> failure to evaluate integration
Computing integrated information

23. How does this explanation explain the known
properties of consciousness?
Loss of cerebellum (Week 3: Cerebellum contains 4 times
more neurons than in cerebral cortex)
Yu et al 2014 Brain
“Evaluation of the sensory system
showed no abnormalities”
Computing integrated information

24. (Rough) architecture of cerebellum
Many neurons form locally parallel
circuits roughly in a feedforward
computation.
Computing integrated information

25. Summary: integrated information
Phenomenological observation:
Our conscious experience is highly intrinsically
informative; each moment of experience is highly distinct and
differentiated.
IIT’s proposal:
To support intrinsically informative conscious experience,
there must be physical system that is intrinsically informative.
> Quantify how much a system constrain its past/future.

26. Summary: integrated information
Phenomenological observation:
Our conscious experience is always integrated and
experienced as a unified whole.
IIT’s proposal:
To support integration of conscious experience, there
must be physical system that is integrated.
> Quantify how much a system loses its intrinsic
information if the system is minimally cut.

27. Summary: integrated information
Clinical observation:
While cerebellum contains 4 times more neurons than
cerebral cortex and performs highly sophisticated
computation, we do not lose consciousness when it’s lost.
IIT’s explanation:
Cerebellum does not generate much integrated
information.

28. Then, what is the IIT’s proposal about the boundary and
contents of consciousness?

30. What is the boundary of consciousness?
- A proposal from IIT
Boundary - a subset of mechanisms that maximizes
system-level integrated information
Boundary of consciousness

31. A subset that maximizes integrated information
“Complex” in IIT terminology
The most integrated local maximum.
Which of the system ABCD is the complex?
A B
C D
Boundary of consciousness

32. A subset that maximizes integrated information
Try all possible cuts!
A B
C D
A B
C D
A B
C D
A B
C D
A B
C D
A B
C D
A B
C D
Boundary of consciousness

33. A subset that maximizes integrated information
Try all possible cuts!
A B
C D
A B
C D
A B
C D
A B
C D
A B
C D
A B
C D
A B
C D
Boundary of consciousness

34. IIT: explanation on one consciousness from
two hemispheres
Normal two connected
hemispheres
Boundary of consciousness

35. IIT: explanation on two consciousness from two
hemispheres when their connections are cut
Split brain
Boundary of consciousness

36. Anatomy
Boundary of consciousness

37. Anatomy
Boundary of consciousness

38. Boundary of consciousness

39. Boundary of consciousness

40. Phenomenology and behaviors of split-brain patients
Boundary of consciousness

41. What’s happening here?
1.A word presented to [ ] hemifield is sent to [ ]
side of the brain
2.The patient’s [ ] side of the brain controls [ ],
but both sides can [ ]
3. In this patient, communication between [ ] are
impaired
4.[ ] side of the brain comes up with an excuse (?)
Boundary of consciousness

42. However! Recent challenge (by Pinto et al 2017 Brain)
Boundary of consciousness

43. Phenomenology/behaviors
Q. One mind? Or two minds?
https://www.youtube.com/watch?v=0lmfxQ-HK7Y&t=486s
Boundary of consciousness

44. Q. What happens to phenomenology when brains are
connected?
https://www.youtube.com/watch?v=N1Mac4FeKXg
Boundary of consciousness

45. Conjoined brains explained by IIT?
Boundary of consciousness

46. Summary: Boundary of consciousness
Phenomenological observation:
Our conscious experience has definitive boundary.
IIT’s proposal:
The boundary of consciousness corresponds to the local
maximum of integrated information.
> Try out all possible cuts and identify the subset that
maximizes integrated information.

47. Summary: Boundary of consciousness
Clinical observation:
One conscious experience splits into two due to split brain
operations.
IIT’s proposal:
Split brain operations split the complex into two complex.

48. Curious observations in conjoined twins:
Conjoined twins seem to share sensory experience (?).
IIT’s explanation
Two complex can share the same inputs (outside of either
complex).

49. Remaining questions throughout this lecture!
How can IIT, in principle, explain why different areas of the
brain differentially contributes to different aspects of
consciousness?
Faces, motions, colors,
How can we test them?