GIszter

Question 1

simplest possible model

Answer 1

input weighted
function
output

Question 2

cascade

Answer 2

layered, acyclic, one direction

has hidden layers

Question 3

recurrent/recursive

Answer 3

cyclic
some go back
can be self exciting as is the case for CPGs

Question 4

interconnected

Answer 4

like everything is cyclic

Question 5

hidden layers

Answer 5

layers of interneurons between input and output

Question 6

perceptrons

Answer 6

edeg detection
movinge directions
inhibitory layer
step functions 
cant take derivative
so difficult to analyze but easy to program

Question 7

edge detection

Answer 7

edges have less activation so they activate less inhibitors so a set of outputs get inhibited less and are higher than middle ones which are higher than outter ones which dont even have much activation

Question 8

McCulloch-Pitts

Answer 8

inhibition trumps al; discrete thrshould neurons

turing machine with fixed weights and binary output

Question 9

hopfield content addressable memory CAM

Answer 9

fully interconnected
matching with something it already knows
very recursive
plastic weights so updatable

Question 10

fan in

Answer 10

converging

averages population

Question 11

fan out

Answer 11

diverging for accuracty

Question 12

weight strength

Answer 12

all networks incorporate weights

like how strong is the EPSP/IPSP

Question 13

spiking

Answer 13

digital code
longe range
fast
discrete

Question 14

non spiking

Answer 14

analog 
short range
slow
no action potetnial
in retina and olfactory bulb

Question 15

lateral inhibition

Answer 15

like edge detection again

output is better than input because modified

Question 16

mauthner cells

Answer 16

turn
inhibition of other
singl cell drives decision and controlls lots of motor neurons to evade

Question 17

DCMD

Answer 17

decending contralateral motion detection
used to guid flight and direction
intermediate proccestion of info to uide motor output
AXON CROSSES MIDLINE
from eye to opposite side to turn away from looming object
just mediates, not a binary response

Question 18

contralateral

Answer 18

excitatory toward stim

inhibitory away from stim

Question 19

ipsilateral

Answer 19

excitatorr away from stim

inhibitory toward

Question 20

plasticity

Answer 20

local - Hebb fire and wire, so use or lose

external teacher - reinforce as it gets close to correct

Question 21

occams razor

Answer 21

as simple as possible but as complex as necessary to perform a function/describe a mechanism

Question 22

NMJ

Answer 22

1:1 firing ratio so no integration or info processiing at this point

Question 23

motor neuron populaitons

Answer 23

firing of single neurone can recruit others in relay fashion
recruitment makes smoother
motor pools as integration layer in spinal network

Question 24

Size (henneman) principle

Answer 24

slow fibers recruited first for fine controlled tasks

slow motor neurons have smaller somas and therefore have higher resistence so a lower threshold