Sensation

1
Introduction
2
Perception and Reality

• What is real? How do you define real? If youre
  talking about what you can feel, what you can
  smell, what you can taste and see, then real is
  simply electrical signals interpreted by your
  brain. This is the world that you know.
• Morpheus answer to Neo in The Matrix, 1999
• Compare the Brain in a Vat scenario, e.g.
  Arnold Zuboffs
• The Story of a Brain

3
Some Themes

• 1.    Perception as the construction of a model
  of the environment
•  
• 2.    Why do we take perception for granted?
• 3.    Nature of the model constructed in
  perception a symbolic description (or symbolic
  representation)
•  
• 4.    Perception really is a difficult and
  impressive accomplishment
•  
• 5.    The physiological approach to perception
  the perceptual process as a causal chain
•  
• 6.    Parallel approaches to perception from
  studies of visual phenomena or visual performance
  (Psychophysics) and from physiology and anatomy
• 7. Perception as an Inverse Problem
• 8. Marrs three levels of Analysis Hardware,
  Algorithmic, Computational

4
Some Themes

• 1.   The world as we perceive it is an internal
  neural representation or model, that we
  construct and rely on.  

5
Some Themes

• 2.    Why do we take perception for granted?
• If the model is to be useful we have to take it
  for real thats why we evolved the ability to
  make it.
• Perceptual ability is universal not very much
  individual variation
• Perception generally requires no conscious
  effort, unlike other challenging cognitive
  accomplishments
•  

6
Some Themes

• 3.    Nature of the model constructed in
  perception a symbolic description (or symbolic
  representation)
• A point-to-point projection, preserving the
  information in the stimulus, is NOT enough
  (homunculus fallacy)
• Example of a better approach bug detectors
•  

7
Some Themes

• 4.    Evidence that perception really is a
  difficult and impressive accomplishment
• It takes up nearly half the brain for vision
  alone
• Infants spend the first year of life mainly
  learning it
• Engineers can barely achieve even the most
  primitive symbolic description with artificial
  vision systems
•  

8
Early Philosophy of Perception

• Platos The Allegory of the Cave (380 BCE)

9
Some Themes

• 5.    The physiological approach to perception
  the perceptual process as a causal chain
•                 Phantom limbs
•                 Phosphenes
•  

10
Descartes and Phantom Limbs

• Descartes
• Reflex arc for action vs
  Consciousness (Pineal )

11
Phosphenes
Tapping in at an intermediate stage of
processing A visual prosthesiscan use retina,
optic nerve or cortex
Compare auditory or visual phosphenes
12
Some Themes

• 5. The physiological approach to perception the
  perceptual process as a causal chain
• - Phantom limbs
• - Phosphenes
• 6. Parallel approaches to perception from studies
  of visual phenomena or visual performance
  (Psychophysics) and from physiology and anatomy
• Why these should yield a consistent understanding
• 7. Perception as an Inverse Problem
• - Assumptions/natural constraints Ames room,
  etc.
• 8. Marrs three levels of Analysis
• - Computational, Algorithmic, Hardware
•  

13
7. Perception as an Inverse Problem An example
Use of assumptions/natural constraints (Ames
room, etc.)
Without binocular vision, projection still
happens But now it requires solution of an
inverse problem What object size and distance
produced the given image? Given one value (image
size), we must infer two. The mapping from
objects to images is many to one. The
restoration of a definite object distance in
perception resolves some of this uncertainty --
correctly if the inverse problem is solved
correctly -- incorrectly otherwise A rational
way to attack the inverse problem --Choose the
most plausible of the alternatives. --In a
Bayesian framework, this would simply be the most
statistically likely, given the context as we
know it. Although Hoffman says this is circular
logic --Example in Chapter 2, assume uniformity
of texture density in order to compute tilt and
slant from the pattern of non-uniformity in the
image
14
7. Perception as an Inverse Problem - Use of
assumptions about natural constraints Ames
room(below)
Other constraints Chapter 2 (texture uniformity
constraint), etc
15
(No Transcript)
16
(No Transcript)
17
Are not the Species images, in modern
terminology of Objects seen with both Eyes
united where the optick Nerves meet before they
come into the Brain, the fibres on the right side
of both Nerves uniting there, and after union
going thence into the Brain in the Nerve which is
on the right side of the Head the right optic
tract, in present usage, and the fibres on the
left side of both Nerves uniting in the same
place, and after union going into the Brain in
the Nerve optic tract which is on the left side
of the Head, and these two Nerves meeting in the
Brain in such a manner that their fibres make but
one entire Species or Picture, half of which on
the right side of the Sensorium comes from the
right side of both Eyes through the right side of
both optick Nerves to the place where the Nerves
meet chiasm, and from thence on the right side
of the Head into the Brain, and the other half on
the left side of the Sensorium comes in like
manner from the left side of both Eyes. For the
optick Nerves of such Animals as look the same
way with both Eyes (as of Men, Dogs, Sheep, Oxen,
c.) meet before they come into the Brain,
but the optick Nerves of such Animals as do not
look the same way with both Eyes (as of Fishes
and of the Chameleon) do not meet, if I am
rightly informed.
Newton, 1682
Projection (Kepler 1611) 1 world -gt2 images -gt
1 perceived object (projected into
3D) Binocular disparity can fix distance
Descartes 1637 (stick analogy) Briggs,
1676 Barlow et al., 1968, etc. Partial
decussation Newton, 1682 (pub. 1704)
18
When perceptual constancy is achieved, instead of
failing as it does in the Ames room, the result
is a closer correspondence, or isomorphism,
between the state of the external environment and
the perceptual impression of it(closer than the
correspondence between the external environment
and the sensory stimulus through which we know
it.) Action depends on such a simple and orderly
mapping, eg x,y vs pixel (Hayek, Kohonen)
pointing Frog computations to control
action --Prediction --Generalization --Example
of pitch and frequency (and period,
and) Failure of perceptual isomorphism in
intermediate representations Perception as a
model, with afferent neural representation as
data, which neednt look like the model, just as
a scientific theory should be a model of reality
(and therefore isomorphic with reality in some
sense), yet neither the theory nor the reality it
describes has any similarity to the data as such
(vectors of numbers, marks on paper, etc). A
different point of view Don Hoffman.
19
8. Marrs three levels of Analysis -
Computational, Algorithmic, Hardware
20
A Hymn to the 3 levels of analysis Onward,
Marrian soldiers Onward, vision scientists,
Marching on with Marr Algorithmic theories
Beckon from afar. Leave aside the neurons
Filling up your head Think of computations,
They will do instead. For those computations,
From their hardware freed, Form the firm
foundation Of our noble creed. Fear no
contradiction While Marr leads the way Views
of such abstraction Few will dare gainsay.
Armed with zero-crossings, ?2G our shield, We
can spread confusion Oer the battlefield.
With its special concepts Deep and broad and
true Marrs approach is surely Good enough for
you.
Refrain Onward, vision scientists, Marching on
with Marr. Algorithmic theories Beckon from afar
http//www.hymnsite.com/lyrics/umh575.sht Text
Sabine Baring-Gould, 1834-1924 Music Arthur S.
Sullivan, 1842-1900
Textbook reference Preface, page xi and Ch2, p38