Exam 1 Flashcards
Is the distinction between the mind and brain Cartesian dualism? Why or why not?
NO! Descartes thought there were two kinds of things in the universe: matter and energy. In humans, there’s a third thing: a soul/mind, which is fundamentally separate from the body and does not obey the laws of the natural world.
ACTUALLY, minds are subject to natural laws, but different ones from brains.
Characterize the distinction between minds and brains.
The mind is not equivalent to the brain. It derives from the activity of the brain, but the laws that govern the way the brain works (neurophysiology) are not the laws that govern the way the mind works (psychology)
Describe Marr’s Computational Theory level of analysis.
Computational theory level:
~Most abstract
~Essentially understanding the problem
- What problems is the system solving, and why?
- What are the constraints on its solution? (note: constraints make a solution possible)
Describe Marr’s Representational Algorithm level of analysis.
Representational Algorithm level:
~What info does the system represent about the problem and how?
~What does it do with that information? (this is the algorithm)
~What is the output, etc.
Describe Marr’s Physical Implementation level of analysis.
Physical implementation:
~How are these representations and algorithms realized in the physical hardware of the device itself?
-the algorithm is the same, even when the hardware changes
Describe the interaction of constraints among Marr’s levels of analysis.
The levels are separate, but not fully independent. For example, something you find out about one level constrains questions you can ask about another.
Each level constrains others but it is more so in the top-down direction than bottom-up.
Some kinds of hardware are better at implementing some kinds of algorithms than others.
What are Marr’s levels 4 hoomanz?
1) The world that supplies the constraints that allow a function to be computed
2) The mind!
3) The brain
Generally, what are we talking about in Marr’s paper?
~Operation of ganglion cells in the retina
- send outputs along optic nerve (axon of ganglion cell)
- photoreceptors respond to (represent) luminance at each location in the image
- ganglion cells respond to (represent) contrast
What one main goal of early vision discussed in Marr’s paper? What is the problem with reaching this goal?
GOAL: surface boundaries are useful indicators of object boundaries, so we wish to find them!
PROBLEM: retinal image tells you about the luminance at each point, not surface boundaries :c
What are the constraints that make finding surface boundaries possible in Marr’s paper? Given these constraints, what is the new goal?
CONSTRAINTS:
~Smoothness: reflectance tends to change smoothly within surfaces and abruptly between them
~Projective geometry: adjacent points in the world project to adjacent points in the image
–>adjacent points in the image tend to be adjacent IRL because light travels in straight lines
NEW GOAL: find contrast!
What is the representation and algorithm used by the visual system to find contrast?
Representation: input = luminance map (retinal image) –> output: contrast map
Algorithm: compute contrast map by convolving luminance map with a difference of Gaussians at multiple locations
What does a nonlinear change in luminance correspond to?
Surface boundary!
What is the significance of the first and second derivative of a luminance map?
The first derivative shows where the slope of the luminance map changes – if that change is abrupt, there will be a corresponding dip in the first derivative graph.
The second derivative shows where the slope of the first derivative changes – if there is a dip, there will be a corresponding zero crossing in the second derivative graph.
What is a zero crossing? What is its significance?
A zero crossing is negative on one side, and positive on the other. This indicates an edge location.
How do you compute a difference of Gaussians?
Point-by-point, subtract one Gaussian from the other. We are left with a Mexican hat distribution
What is the algorithm used to detect contrast?
Convolution of DOG with luminance map.
basically, take the dot product of the vectors that represent the DOG’s height and the luminance of the image
What does it mean to say a DOG is unbalanced? What is the significance of this?
If it is unbalanced, convolution will yield a nonzero result. This is basically meaningless. It means: there’s something edge-like somewhere near me (within the scope of the particular DOG at that particular place)
What does it mean to say a DOG is balanced? What is the significance of this?
When balanced, the convolution algorithm yields a result of 0. This means, to a first approximation, there is no edge within the scope of the DOG.
How can we use DOGs to detect zero crossings in a luminance map?
Look at DOG responses at different locations over (across) the image
In this way, DOGs compute the second derivative of a luminance map
What are some characteristics of the DOG response?
~Vary with location ~Insensitive to uniform luminance ~Insensitive to linear changes ~Sensitive to spatial scale -neurons downstream know spatial scale of edge depending on which DOG detected the edge
What is disparity? Why is it a useful cue to depth?
~Disparity: a single point in the world can project to different locations in the two eyes
-Location in right - location in left
This is cool because…disparity varies with depth (distance from viewer) so it is useful for computing differences
What is the horopter?
Fixation point resides on an imaginary sphere…
-Horopter: collection of points out in the world that are as far away as the fixation point
Why is there no disparity at the fixation point?
The point at fixation projects to the same location (the center) in both eyes
So, it projects to the fovea in both eyes.
Since it is the same point, there is no disparity between the two eyes
Let’s say we have a fixation point, F. Point A is beyond fixation. What kind of disparity will we experience with point A, and why?
~Uncrossed disparity: appears to the left of fixation in the left eye and to the right of fixation in the right eye
-this is uncrossed because the image projects to the retina upside-down and backwards –> uncrossed from the perspective of the viewer