PSYC 130: Introduction to Cognitive
Science Study Notes
Foundations of Cognitive Science
Cognitive science: the interdisciplinary study of how the mind works
Why do we need so many disciplines?
1. Natural alignment of our interests (across fields)
a. Different fields with different methods have interests which converge at
studying and understanding the brain → cog sci is more about the
question being asked than the methods being used
i. PEEP LECTURE SLIDES FOR William James example
2. Shortcuts to the truth (we get to the truth better and faster)
a. Instinct blindness → getting distance from our intuitions and everyday
experiences about how the mind works by using multiple fields is the
way we avoid instinct blindness (the idea that our brain functions are so
connected to us that we naturally feel like we know what’s going on)
i. Example of square colors and perception
b. Computer science as an example of a field which forces us to realize
instinct blindness when looking at how brain works (trying to build
models for brain functions is very difficult)
c. Neuropsychology as another field which does this → when healthy, the
brain works too seamlessly to recognize its parts
i. Brain damage allows us to tease apart some mental processes
3. Intrinsic scientific reasons
a. You simply need multiple viewpoints in order to understand the
brain i. Marr’s 3 levels of analysis
1. Computational → what is the problem being solved? (ex. field of
computer science looks at this)
2. Algorithmic → what are the steps taken to solve the problem? (ex.
field of psychology looks at this)
3. Implementation → how are these steps implemented in the
underlying hardware (biological or otherwise)? (neuroscience
looks at this)
a. Multiple lower level types of matter can do the same
computations
, ii. Is each level critical? Yes → each level does / reveals something
unique 1. Only looking at the computational level won’t work
because there
are things that we can only explain when looking at the level of the
neurons (need implementation level of analysis) → ex. neurons
and afterimages
2. Only implementational level won’t work because it may stop us
from capturing generalizations → ex. just looking at brain circuitry
wouldn’t allow us to compare similarities in brain studies of dif.
people/organisms
Foundations of Cognitive Science
Why don’t we call it “cognitive sciences?”
1. The generalizations made in each field involved in cognitive science
restrict/constraint theorizing in other fields involved in cognitive science
a. Constraints from above → studying neurons telling us that psychology
theories of the brain may be wrong, aka going from implementation level to
critique algorithmic level (ex. 100 step rule in our ability to understand
language)
b. Constraints from below → studying psychology telling us that theories
based on neurons may be wrong, aka going from algorithmic level to
implementation level (ex. “Structure from motion” theorem)
Cognitive Architecture
1. Idea comes from cognitive science (“primitive” information processing
mechanisms) - Basic memory capacities (how much?)
a. Fundamental operations (adding, shifting things over)
b. Brute constraints (serial vs. parallel)
2. Normalization → responses of our neurons divided by the summed activity of
those neurons
3. Cognitive architecture important for understanding the scope of cognitive science
a. Think of cognitive architecture as a set of mechanisms that make possible
a certain range of activities (not necessarily about causing specific
thoughts / behaviors)
4. Though we will mainly focus on what we all have in common regarding cognitive
architecture, we will focus on a few exceptions
a. Certain neurological differences (ex. synaesthesia)
b. ‘Gender’ differences → real, but balanced, nuances, and significant (just
means we can be sure that the differences are real, though they may be
Science Study Notes
Foundations of Cognitive Science
Cognitive science: the interdisciplinary study of how the mind works
Why do we need so many disciplines?
1. Natural alignment of our interests (across fields)
a. Different fields with different methods have interests which converge at
studying and understanding the brain → cog sci is more about the
question being asked than the methods being used
i. PEEP LECTURE SLIDES FOR William James example
2. Shortcuts to the truth (we get to the truth better and faster)
a. Instinct blindness → getting distance from our intuitions and everyday
experiences about how the mind works by using multiple fields is the
way we avoid instinct blindness (the idea that our brain functions are so
connected to us that we naturally feel like we know what’s going on)
i. Example of square colors and perception
b. Computer science as an example of a field which forces us to realize
instinct blindness when looking at how brain works (trying to build
models for brain functions is very difficult)
c. Neuropsychology as another field which does this → when healthy, the
brain works too seamlessly to recognize its parts
i. Brain damage allows us to tease apart some mental processes
3. Intrinsic scientific reasons
a. You simply need multiple viewpoints in order to understand the
brain i. Marr’s 3 levels of analysis
1. Computational → what is the problem being solved? (ex. field of
computer science looks at this)
2. Algorithmic → what are the steps taken to solve the problem? (ex.
field of psychology looks at this)
3. Implementation → how are these steps implemented in the
underlying hardware (biological or otherwise)? (neuroscience
looks at this)
a. Multiple lower level types of matter can do the same
computations
, ii. Is each level critical? Yes → each level does / reveals something
unique 1. Only looking at the computational level won’t work
because there
are things that we can only explain when looking at the level of the
neurons (need implementation level of analysis) → ex. neurons
and afterimages
2. Only implementational level won’t work because it may stop us
from capturing generalizations → ex. just looking at brain circuitry
wouldn’t allow us to compare similarities in brain studies of dif.
people/organisms
Foundations of Cognitive Science
Why don’t we call it “cognitive sciences?”
1. The generalizations made in each field involved in cognitive science
restrict/constraint theorizing in other fields involved in cognitive science
a. Constraints from above → studying neurons telling us that psychology
theories of the brain may be wrong, aka going from implementation level to
critique algorithmic level (ex. 100 step rule in our ability to understand
language)
b. Constraints from below → studying psychology telling us that theories
based on neurons may be wrong, aka going from algorithmic level to
implementation level (ex. “Structure from motion” theorem)
Cognitive Architecture
1. Idea comes from cognitive science (“primitive” information processing
mechanisms) - Basic memory capacities (how much?)
a. Fundamental operations (adding, shifting things over)
b. Brute constraints (serial vs. parallel)
2. Normalization → responses of our neurons divided by the summed activity of
those neurons
3. Cognitive architecture important for understanding the scope of cognitive science
a. Think of cognitive architecture as a set of mechanisms that make possible
a certain range of activities (not necessarily about causing specific
thoughts / behaviors)
4. Though we will mainly focus on what we all have in common regarding cognitive
architecture, we will focus on a few exceptions
a. Certain neurological differences (ex. synaesthesia)
b. ‘Gender’ differences → real, but balanced, nuances, and significant (just
means we can be sure that the differences are real, though they may be
