Single-unit Recording and Action (2)

Question 1

What “times” are analyses locked to?

Answer 1

• stimulus-locked: to see stimulus related activity
• response-locked: to see response related activity
• otherwise, difficult to see peaks

Question 2

How is a singular goal obtained?

Answer 2

• through a specific series of motor movements
• motor control is a hierarchy
• ex. write name -> first name and last name -> individual letters -> individual lines -> specific fingers moving -> specific muscles moving

Question 3

What is motor equivalence?

Answer 3

• movement is consistent with abstract motor plans
• upper part of motor plan is being preserved but getting translated to different motor areas
• ex. writing name with different hands, teeth or feet

Question 4

What is the general motor system?

Answer 4

• premotor and supplementary regions
• (cerebellum and basal ganglia)
• motor cortex
• brainstem
• spinal cord
• output to muscles

Question 5

What does the topography of motor and somatosensory areas look like?

Answer 5

• homunculus

- body mapped on brain upside down and flipped

Question 6

What is cortical magnification?

Answer 6

• large representations for “important” areas

Question 7

Where does the motor pathway decussate?

Answer 7

• at the medulla

Question 8

What do connections from the cortex to motor neurons look like?

Answer 8

• cortex neurons synapse on many motor neurons and may affect many muscles
• one given cell is not responsible for one specific muscle

Question 9

What was seen when recording from monkeys moving joy sticks?

Answer 9

• animal cued to move joy stick in particular direction
• neurons fires more depending on direction
• directional sensitivity

Question 10

What is a directional tuning curve?

Answer 10

• graph made from direction of movement and response rate

- peak shows preferred direction

Question 11

How are tuning curves used to produce population vectors?

Answer 11

• two cells preferred directions are plotted
• the arrows for each cell are produced in the preferred direction with magnitude indicated by length
• the population vector is produced from these two

Question 12

What are the two pieces of information acquired from population vectors?

Answer 12

• direction: preferred direction

- length: firing rate

Question 13

How is a population vector made up of?

Answer 13

• add up vectors for all neurons

Question 14

What does a population vector represent?

Answer 14

• accurately represents actual movement direction
• population vector in red
• individual neuron vectors and actual direction in black

Question 15

Why does data for one neuron not give us important information?

Answer 15

• you have nothing to compare it to
• the context is important and we don’t have it
• cannot produce population vector

Question 16

How is 3D directional sensitivity measured?

Answer 16

• set-up: 3D space and reach towards targets
• depicted as a cube
• tuning volume is depicted as a sphere with a dip in it (this is where no activity is taking place)
• 3D individual vectors pictured on xyz graph

Question 17

What does the cone represent on the 3D population vector?

Answer 17

• 95% directional variability cone

- 95% confident that movement direction is within this cone

Question 18

How many neurons does it take to have an accurate representation of the movement direction?

Answer 18

• as you record from more and more neurons, the confidence cone gets narrower
• good at 150 neurons and doesn’t substantially improve from there
• will never reach no cone because there will always be noise (other stuff going on)

Question 19

What is the problem with a localist representation?

Answer 19

• localist: each neuron has specific representation (fires strongly only for specific location)
• if we lose a neuron, we would lose the specific function of that neuron
• can no longer move in that direction

Question 20

What neural representation do we see?

Answer 20

• distributed and spatially organized
• neuron fire most for particular direction
• surrounding neurons fire smaller amounts

Question 21

What are the types of neural representations?

Answer 21

• distributed and arbitrary
• distributed and spatial!!
• sparse (high firing for random cells)
• localist