PSYCH 85 FINAL Flashcards
(31 cards)
LEFT BRAIN
Mostly Language -Grammar -Naming -Repeating -Understanding Verbal Memory
RIGHT BRAIN
Attention
Spatial Processing
Faces
Nonverbal memory
How does handedness relate to dominant hemispheric processing of language?
L Hemisphere processes language. A person’s handedness is opposite from their dominant hemisphere. Left handers had language processes more dispersed through their brain
How does hemispheric damage affect the emotional reaction to brain damage?
Brain damage to the left hemisphere is more likely to be catastrophic;
Result in despair, hopelessness, or anger
Brain damage to the right hemisphere is more likely to result in an indifferent reaction; Euphoric reaction–Minimization of symptoms, placidity or elation
Which side of the brain causes catastrophic response?
LEFT BRAIN. Results in despair, hopelessness, or anger.
-Minimization of symptoms, placidity or elation
How do we assess brain functions of a hemisphere in normal people?
WADA test
- Inject anesthetic (sodium amytol) into the right or left carotid artery
- Puts one hemisphere to sleep so we can see what functions there
What is hemispatial neglect and how likely is it given damage to each hemisphere?
Hemispatial neglect: A failure to report, respond, or orient to stimuli presented contralateral to the side of a brain lesion in the absence of elementary motor or sensory deficits
Most often occurs with right hemisphere damage, loss of left visual field
- See everything on right
- Not just a sensory problem but rather a problem of consciousness
- 86% with Right hemisphere damage
- 7% with left hemisphere damage
- 7% with bilateral damage
What is anosognosia and anosodiaphoria?
Anosognosia: Lack of awareness or denial of any problem
- Left arm paralyzed, right are is fine, doctor says touch nose with left arm, uses right arm to touch nose, says that they are touching nose with left arm, says they can visually see they are touching their nose
- Perceiving something wrong
Anosodiaphoria: Awareness of deficit but without appropriate concern
appropriate concern
What is alien hand syndrome? How does the mirror box treat phantom pain? How does the cortex reorganize after losing a body part?
- Inability to control one hand
- Hand can perform complex behaviors (Like buttoning a shirt)
Mirror box:
Normal arm in one slot
Mirror image is superimposed where phantom arm would be
Move real arm until matches position of phantom limb
Close their eyes and make symmetric movements then open eyes
4/5 subjects with involuntary clenching spasms found relief
Temperature did not transfer (control for confabulation)
Cortex can still feel lost limbs like they are “phantom”
-Eventually cortex reorganizes to other parts of body
What is declarative memory and what are the brain structures that process declarative memory? What is retrograde and anterograde amnesia? How does memory consolidation work? What kind of memory deficits does consolidation produce?
Declarative/Explicit memory associated with Hippocampal formation in medial temporal lobe
Declarative memory is the memory of facts and events
Retrograde Amnesia: Can’t remember things in past
-Temporally graded: Forget things that happened just before accident occurred
-Harder you hit your head the more you forget
Why is it temporally graded?
-Hippocampus formation holds info for a while and “teaches” info to the rest of cortex
-Teaching is part of consolidation
-After new info has been “taught” then is is stored in rest of cortex
-Info that is not taught yet, is lost
What is apperceptive and associative agnosia? Where are faces processed in the brain? What is a face-processing deficit called?
Apperceptive Agnosia: Cannot assemble parts into a meaningful whole
Associative Agnosia: can perceive but can’t label
Faces detected in fusiform area
Inability to recognize faces = prosopagnosia
What is neural synchrony? Describe different types of neural synchrony.
How does shape and color get “bound” together
Simple: Firing together at the same time
Complex: Firing in similar patterns
-May be responsible for much more than binding of perception
-Memory?
-Consciousness?
How can temporal binding be used to represent object shape?
Temporal binding: Combines what we’re processing with where we’re processing it
Imagine you’re looking at a suitcase, which has a rectangle/cube unit (the body of the suitcase) below a tube unit (the handle). Maybe the neurons for the cube units fire at the same time as the “below neuron” and the neurons coding for the arc units fire at the same time as “above units” to bind the parts with their relative location
What are some similarities and differences between the brain and standard computers (like the ones running a typical pc)?
Similarities:
Both store and use info
Both have working memory (Computer = RAM ~8-12 GB, much smaller in humans)
Both have long-term memory (Computer = Hard-disk, CD)
Both have control structures
-Computer = CPU
-Man = Attention
Is there a central part of the brain that directs all other parts of the brain? What controls the brain?
Not completely centralized, much more distributed than a CPU
Differences:
Brains:
-Distributed parallel power, like a billion little computers (relatively slow, but if one brain cell dies, rest of brain is unaffected)
-Fault tolerant (tough to break)
-Very good at learning: Making associations, learning new patterns, probably biggest strength
-Coded in fuzzy analog format (Analog: Means you can take any value, means you can code for any number, not just 1s and 0s)
-Distributed Representation (Distributed: Info is stored between a lot of different neurons)
Computers:
- Usually 1 serial processor (super fast, if processor dies, computer dies)
- Very sensitive to damage (fragile)
- Not naturally suited to learn (super FAST, not meant to learn)
- Coded in 1s and 0s (binary: need to be super careful while creating program, otherwise program won’t work)
- Local representation (Local: computer has all info stored in one location)
Can computers learn? Sure
- Take browser history to suggest ads
- Only possible because a ton of programming makes it happen
What are local and distributed representations?
Local Representations: code a concept with one node
Distributed representations code information by a pattern of activations across a set of units
What is the basic components of a neural network?
Network has nodes (kind of like neurons)-Node: Unit that takes on certain activations
Network has links between nodes (like connections between neurons) -Passes activation from 1 node to many other nodes
Nodes have levels of activation–Activation rules: How we combine activations/how activations spreadd
Links between nodes have connection strengths (weights)-Can have strong excitatory (positive), near neutral strength (0), and strong inhibitory (negative)
Summing inputs:
Multiply strength at A by strength at C and add the product of the strength at A* the strength at B to ged the total activation at A
(see slide 9 of lecture 13)
What is the basic structure of a perceptron? What are it’s limitations? How can those limitations be overcome?
?
First artificial neuronal model
Have 2 inputs that are binary (1 or 0)
Think of input A as true or false
Think of B as another statement T/F
True = 1, False = 0
1. Entire statement is true is A AND B are true (If A = True, B= False, system - false, if A = false, B = true, system = false, if A = false, B = false, system = false, if A = true, B = true, system = True) NEURONAL NETWORK SOLVED IT (Just need to add up inputs to get > 0)
2. A OR B (If A = true, B = false, system = true, if A = false, B = true, system = true, if A = true, B = true, system = true, if A = false, B = false, system = false)
NEURONAL NETWORK SOLVED IT (Just need to add up the inputs to get > 0)
3. A XOR B (Exclusive or)
A can be true
B can be true
BUT NOT BOTH
Neuronal network couldn’t solve this problem because you can’t just add up the inputs
Neuronal network can only solve problems that are linearly separable (can draw a line between what is true and what is false)
Perceptron cannot do:
-Exclusive OR
-Even/odd discrimination (even or odd number)
-Inside/outside discrimination (point inside or outside shape)
-Open/Closed discrimination (open or closed shaped)
Can be fixed by having multiple layer perceptrons
2 layers, easy to make network learn, clear pattern between input and output layer, very limited in what network can learn
3rd hidden layer can solve many more problems, comes at a cost, makes it much harder for network to learn
What is supervised learning? What problem is there in applying supervised learning algorithms to the human brain?
- Feed network inputs
- See what activations become
- Compare this to what it should be (desired output)
- Change the weights between nodes according to how much error they contribute
Problem in human brain: Where does this teacher come from?
What are some desirable characteristics of neural networks?
- Distributed Representation: Ideas, Thoughts, concepts memories are all represented in the brain as patterns of activation across a large number of neurons. As a result, there is a lot of redundancy in neural representation
- Graceful Degradation: Performance of the system decreases gradually as the system is damaged (As neurons get knocked out, entire system doesn’t get destroyed
- Learning: Delta Rule/Backpropagation
- Generalization: Because of how the network learns and its distributed representation, it can respond to inputs it was never officially trained on, generalizing based on similarity to things it was trained on
- Distributed processing: Not only representation, but processing is distributed too, so there is no central controlling function, or CPU, in the brain. It is more cooperative. (Problem with distributed processing for computers is software)
What are some problems with creating artificial neural networks?
- Stability-Plasticity dilemma: Learn new info while retaining old info (want to make sure that new stuff doesn’t affect old stuff
- Catastrophic Interference: System falls apart when new info is learned (learn something new, everything shuts down)
- Supervised networks (Where is the teacher?)
- Biological plausibility of teacher
Supervisor: Knows what the output should be, allows us to check work, see where things went wrong
In human world, don’t always have supervisor
What is the concept of centrality in the discussion of networks? What are some examples of centrality?
Computers-CPU
Armies-Generals
Politics-Presidents and dictators
Human Mind?-Can’t pinpoint area of brain that controls everything else
Give an example of a hierarchical network in the human brain.
Simple cells: Oriented bars
Complex cells: Oriented Bars moving
Hypercomplex cells: Right angle of vertical and horizontal lines moving in the same direction
The further you get into brain, the more cells you get that can detect complex info
What is a small-world network? What is a random network and an ordered network?
- 6 degrees of Separation
- 4 degrees of Kevin Bacon (Takes only 4 steps to get to any American actor to any other American actor)
- Electrical Power Grid
- Railroad
- Nervous systems of many animal
Random networks: Local AND Global links, can connect to any node
Ordered networks: Only local links, only connects neighboring nodes
Ordered networks are more protected but harder to get to different parts of the network
What is an egalitarian and an aristocratic network?
Egalitarian network: Links are evenly distributed
Aristocratic: Some hublinks are especially important (like google on the internet)
