Lecture: Distributed Representations & Neural Network Dynamics
24 important questions on Lecture: Distributed Representations & Neural Network Dynamics
What are the 3 principles of neural network processing?
2. Connectivity
3. Excitation/Inhibition
What are benefits of Distributed Representations?
- Robust against damage: 1 cell damaged =/= byebye grandma
- Increased capacity: Overlap --> more things possible
- Dynamic/flexible behaviour: Neural networks show competitive behavior`
What is long term potention function?
- Stronger connections
- Synapses strengthened
- Higher grades + faster learning
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What is synaptic plasticity?
What is long term depression?
- Cell B fires before Cell A gives input
Reasons B fired:
- Accident
- B belongs to other representation by another stimulus
B might belong to stimulus related to A, but not A:
- LTD: Decrease in synapse strength (disassosciation)
- LTD function: Neural pattern difference with similar patterns
What makes a neural representation (anatomy wise)?
How does retrieval/remembering work (neural representations)?
Cue activates some neurons in the representation --> Representation is activated
What is pattern completion in memory retrieval?
What is autoassosciation? What is heteroassosciation?
Heteroassociation: Connection between neural patterns in different layers
What types of heteroassociations can there be in neural representations?
- other aspects of stimuli
Have to be coded in a different layer
What the fuck is visual processing organization design direction shit?
- Ganglion cell gets input from round patch of sensory cells
- V1 responds to stripes?. So what happens
Ganglion cells --> LGN before --> V1
- LGN: cells are lined in circle with the retina
- LGN receptive fields still circular
- LGN RF'S are along a line in visual space
V1 elongated RF's are constructed from the RF's of this LGN
What is convergence (connectivity)?
Compression: Multiple cells --> 1 target cell
What is point-to-point (connectivity)?
named: topological connectivity
What are the 2 types of divergence (connectivity)?(functions)
- Parallel processing (what/where pathway)
Source area --> 1 target area (multiple cells)
- More dense projection
- Association area's mostly (MTL): connect it to input of more other areas in this area
What is density (connectivity?)
More projections --> More dense
What types of convergence are there (connectivity)?
- Within the visual hierarchy
Across modalities:
- Larger scale: Episodic memory, combining information from multiple systems
What is the function of convergence (connectivity)?
Simple --> comination into complex environmental aspects
What is topological connectivity (examples?)?
- Retinotopic maps
- Tonotopic maps
- Homunculus
Where does topological connectivity happen?
What is the difference in plasticity between high levels & low levels?
V1 = constrast
Higher = Specific objects
What receptors cause fast inhibition?
GABA-A receptors?
What is feedforward inhibition? (& function)
Source --> Interneuron --> target
Function:
- Networks canhandle input at variable strength & different size cues
What is feedback inhibition? (& Function)
Function:
- Proportional activity in target layer
- Pattern size limits
- No other patterns get activated
- Gamma oscillations
What does feedforward and feedback inhibition control?
Level of Propagation (spreading to other regions):
- Too much inhibition: Spreading dies out
- Too low inhibition --> Excitation & spreading of noise
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