What are we trying to explain? Multiple facets of a simple behavior Stephen G. Lisberger Howard...
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Transcript of What are we trying to explain? Multiple facets of a simple behavior Stephen G. Lisberger Howard...
What are we trying to explain?Multiple facets of a simple behavior
Stephen G. LisbergerHoward Hughes Medical Institute
W.M. Keck Center for Integrative NeuroscienceDepartment of Physiology, UCSF
What we are trying to explain
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What does Barry have to do to hit a home run?
• Sense ball motion and determine speed and direction of motion.
• Decide whether or not to swing the bat.
• Program the correct swing to meet the ball just in front of his right foot.
• Make any corrections as the ball “moves”.
• All in 400 ms!
What we are trying to explain, simplified
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The behavior: pursuit eye movements
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Anatomy of pursuit
Why are there so many different parts to the pursuit circuit?
Perhaps each part of the circuit is doing a different computation.
Caudatenucleus
The signals recorded in different areas are more similar than different: consider
motor cortex (FPA), parietal cortex, and the cerebellum during pursuit
• Transient and sustained responses
• Directional tuning
• Firing related to target speed
• Similar latencies
Neural responses during the behavior don’t distinguish different parts of the pursuit
circuit -- now what?
• It’s especially troubling that all of these areas combine similar blends of signals related to eye velocity, head velocity, and visual motion.
• The same would be true in the basal ganglia, probably.
• The same would probably be true for neural activity related to Barry’s home run swing.
• So, let’s look at the behavior and see if we can use similar signals to support different behavioral features.
What are we trying to explain -- the many features of the pursuit behavior.
• Smooth eye movement persists without image motion.
• Population decoding for visual-motor transformations (probably done at multiple levels)
• On-line gain control
• Target choice in real-world situations
• Long-term adaptive changes (learning)
What are we trying to explain -- the many features of the pursuit behavior.
• Smooth eye movement persists without image motion.
• Population decoding for visual-motor transformations (probably done at multiple levels)
• On-line gain control
• Target choice in real-world situations
• Long-term adaptive changes (learning)
Natural inputs show that image motion goes away during accurate pursuit.
Visual input consists of a big
pulse of image motion
…followed by a time of very little image motion and big sustained eye motion
A simple feedback controller won’t show velocity memory, and requires high internal
gain to achieve excellent tracking
+ gT E+-
I
E = g I = g (T – E) = gT – gEE + gE = gT
E (1 + g) = gTGain = E / T = g / (1+g)
Gain is 0.5, if g = 1Gain is 0.9, if g = 9Gain is 0.99, if g = 99
An idea about how to create velocity memory with a positive feedback circuit
What discharge would we expect if we recorded from F? Signals related to eye velocity. MST, FPA, and the cerebellum all potentially qualify. But this is a nuts-and-bolts function and we imagine it is supported by cerebellar circuits.
Lisberger, Exp. Brain Res. Suppl 6: 501-514, 1982.
What are we trying to explain -- the many features of the pursuit behavior.
• Smooth eye movement persists without image motion.
• Population decoding for visual-motor transformations (probably done at multiple levels)
• On-line gain control
• Target choice in real-world situations
• Long-term adaptive changes (learning)
How do we think about visual-motor transformations in terms of neural circuits?
Population code for image motion
Preliminary command for eye
velocity Motor command
Parieto-ponto-cerebellar circuit
How do we think about visual-motor transformations in terms of neural circuits?
MT
Preliminary command for eye
velocity Motor command
Parieto-ponto-cerebellar circuit
What are we trying to explain -- the many features of the pursuit behavior.
• Smooth eye movement persists without image motion.
• Population decoding for visual-motor transformations (probably done at multiple levels)
• On-line gain control
• Target choice in real-world situations
• Long-term adaptive changes (learning)
So far, we’ve treated pursuit as a negative feedback control system with velocity memory
retina
Feedforward Gain
Next, I’ll show that the feedforward gain of pursuit is variable. Gain control is another feature of pursuit that we need to understand at the level of neural circuits.
Use of perturbations to probe the gain of visual-motor transformations for pursuit
Research of Joshua Schwartz
Target position
Use of perturbations to probe the gain of visual-motor transformations for pursuit
Research of Joshua Schwartz
Target position
Use of perturbations to probe the gain of visual-motor transformations for pursuit
Research of Joshua Schwartz
Target position
Use of perturbations to probe the gain of visual-motor transformations for pursuit
Research of Joshua Schwartz
Target position
Perturbations cause large responses during pursuit: the gain is set to “high”
During fixation During pursuit
Perturbations cause small responses during fixation: the gain is set to “low”
During fixation During pursuit
How do we think about gain control in terms of neural circuits?
MT
Vectoraveraging
Preliminary command for eye
velocityX
Motor command
Parieto-ponto-cerebellar circuit
Site of gain control
Gain control circuit
?
Enhancement is in the direction of the perturbation, not in the direction of the evoked eye movement
Enhancement is in the direction of the perturbation, not in the direction of the evoked eye movement
How do we think about gain control in terms of neural circuits?
MT
Vector averaging
Preliminary command for eye
velocity
Frontal Pursuit Area
XMotor command
What are the input signals that allow the frontal pursuit area to control the gain
of the visual-motor transformation?
Parieto-ponto-cerebellar circuit Parieto-frontal circuit
Site of gain control
How do we think about gain control in terms of neural circuits?
MT
Vector averaging
Preliminary command for eye
velocity
Frontal Pursuit Area
XMotor command
Vision needs to be one input signal, since image motion has to turn the pursuit system on and initiate smooth tracking.
Parieto-ponto-cerebellar circuit Parieto-frontal circuit
Site of gain control
How do we think about gain control in terms of neural circuits?
MT
Vector averaging
Preliminary command for eye
velocity
Frontal Pursuit Area
XMotor command
Feedback of motor command
The frontal pursuit area needs to represent eye velocity as well as image velocity. (Note another positive feedback loop, like the one through the cerebellum)
Parieto-ponto-cerebellar circuit Parieto-frontal circuit
Site of gain control
Now we know why the FPA and cerebellum have very similar outputs during pursuit
FPA Cerebellum
Uses image motion to initiate pursuit by increasing the internal gain of pursuit.
Uses eye velocity to keep the internal gain of pursuit high when image motion vanishes because of perfect tracking.
Uses image motion to initiate pursuit by driving eye acceleration.
Uses eye velocity to keep a moving eye moving when image motion vanishes because of perfect tracking.
Same basic signals, same basic positive feedback circuit, same basic goal of maintaining excellent tracking when the sensory input to the system goes away. Operating at very different levels of the motor hierarchy, one at a modulatory level, one at a nuts-and-bolts level.
What are we trying to explain -- the many features of the pursuit behavior.
• Smooth eye movement persists without image motion.
• Population decoding for visual-motor transformations (probably done at multiple levels)
• On-line gain control
• Target choice in real-world situations
• Long-term adaptive changes (learning)
Anatomy of pursuit
How does it work when each part is doing the same neural computation?
Caudatenucleus