MT1 Flashcards
(44 cards)
What are cognitive instincts?
innate, biologically-driven behaviors and mental processes that are hardwired into the brain
- guide our responses to certain stimuli and are thought to have evolved because they provided survival advantages to our ancestors
- e.g., reflexes, basic motor skills, and certain social behaviors
What’s instinct blindness?
idea that people often overlook or are unaware of their own cognitive instincts
- intuitive responses and automatic behaviors are so ingrained that we don’t consciously recognize them
- this can lead to misunderstandings about why we think or act in certain ways
Marr’s 3 levels?
computational, algorithmic, and implementation level
Computational Level
This level focuses on the goals and logic of the computation
- “What is the problem being solved, and why is this approach appropriate?”
- Understanding this level helps us grasp the purpose and strategy behind the system
Importance: Without understanding the purpose and goals, we can’t fully appreciate why certain processes are necessary or how they contribute to the system’s overall function
Algorithmic level
This level describes the specific processes and rules used to solve the problem identified at the computational level
- “How is the computation carried out?”
Importance: Knowing the specific processes and rules helps us understand the mechanics of how the system operates, which is essential for troubleshooting and improving performance
Implementational level
This level concerns the physical realization of the computation
- “How is the algorithm physically implemented?”
- involves looking at the hardware or biological substrate that performs the computation
Importance: Understanding the physical implementation is crucial for practical applications, such as designing artificial systems or studying biological ones
Why specialize?
- Different areas use knowledge in different ways
- You may have the same information, but can be used in different ways depending on the need
- Based on what we need (perceptual narrowing)
- Functional incompatibility
What are signatures of modularity?
- Mandatory processing because of encapsulation
- e.g., when you see a face on a house, you can’t unseen the face!
- Fast processing (circumscribed database, no need to decide)
- e.g., being shown 1 face 100 milliseconds and your brain can analyze the face
- Characters breakdown (cognitive neural modularity)
- prosopagnosia
- Domain specificity (specialization)
What determines if something is modular?
- Information encapsulation: processing internal to the module cannot access external information (e.g., visual illusions)
- Lack of access to interlevels: processing external to the module cannot access intermediate processing inside (explains instinct blindness) ( e.g., can’t access what is going on internally)
physical vs. functional modularity
Physical modularity: looking at specialized areas of the brain
Functional modularity: looking at specialized processes of the brain
Why have things built-in?
- Some things are TOO important to learn (e.g., depth detection)
- Some things are impossible to learn
- Frame problem: how do we attend to only the relevant information?
What are general concerns with neuroscience?
- Description vs. Explanation
- Activation can mean many things
- Lingua franca problem
- Means obscure the individuals
What can neuroscience do today? (How to read neuroscience methods)
- Communciate with patients who are in a vegetative state
- Tennis vs. House for yes vs. No
- Use voxels to decode what you are dreaming/ thinking of
- Exposure therapy WITHOUT exposing people!
What is a Turing machine, and why is it useful for the cognitive approach?
Turing machine: used to decipher german transcripts
- Simple steps —> complex behaviour
Conditions:
1. know rules/ assumptions
2. test it out with simple string
3. look for patterns in results
Why use symbols?
reason #1: symbols can take on diff values
- syntactic productivity —> it can take on any symbols!
reason #2: operation can be performed on the symbols, regardless of values
- you can build complex programs out of symbols and operations (symbols can be combined and become building blocks)
- recursiveness = you can build functions into functions into functions (keep going into rabbit hole)
reason #3: meaning comes from parts + how they are combined
- compositional semantics = meaning may change depending on the order
- the baby ate the slug —> slug ate the baby (meaning def changes)
How can we tap into underlying representations and steps?
method #1: protocol analysis
- explicitly probe intermediate steps
- e.g., walk me through what you did
- includes eye tracking or explicit questions!
method #2: analysis by error
- error reveals underlying representation
- difference between true and false
method #3: analysis by processing times
- response times reveal underlying steps
- the further back in time, the longer it will take
What’s special about vision?
- The capacity to see unlocked all these functions (detection, predation, navigation)
- Light —> colours —> differentiation —> better spatial resolutions —> wins out
- The directness of seeing
- Vision is like touch
How should we integrate evolutionary accounts to the cognitive approach?
- Attention is helpful to prevent predators and eat prey
- imagery is helpful for kinship and rituals
- Memory is helpful for foraging, navigation
- Reasoning ???
Describing perception via hardware/ implementational level (i.e., the eye)
- Eye movements implement vision processing
- Vision prioritizes potential for change
- Eye-tracking reveal underlying representations and beliefs (objects vs. Potential for change
Why is vision impossible?
How the retina works: any given input that becomes projected to your retina becomes 2D (from being 3D)
What do we see—and why/how? (Computations in low-level vision)
- inverse problem: Anything can be seen as 2d and 3d
- Cube: changing the direction from where you look at it may make it look 2D
- depth, contrast, luminence
What do we see—beyond low-level features? (Computations in high-level vision)
- Motion/ emotion: movement move us (spontaneously bring in emotions)
- We can choose to interpret: one cans say I see black and red shapes, another may say I see pain and struggle
How do we represent and navigate space?
- Roaming entropy: measure of variability in physical location over course of day —> positively related to positive affect —> reward centres are more active!
orientation in space
- place, grid, and head direction cells!
place, grid, and head direction cells
- place cells: fire when you are in that particular location (how we found out about replaying during sleep)
- grid cells: fire at multiple location, forming map of place (you enter a room, and grid cells will remap locations within that room, extremely sensitive to layout of space
- we care about doorways, not so much of what is in the room (don’t need to know what’s inside room, but that we’ve entered)
- when grid cells stop working, you find difficulty in learning but can still orient in space
- head direction cells: fire depending on direction, regardless where they are in space
