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Neuroscience Graduate Program at UCSF

Faculty - Stephen Lisberger, Ph.D.

Computational and Neural Studies of Eye Movement


Research Description

Basic approach and rationale

Eye movements provide many advantages for investigating neural mechanisms of both reflexive and voluntary behavior. Eye movements exhibit voluntary behaviors such as choice and attention, more hardwired features such as visual-motor coordination, and the ability to learn and remember. Yet, the neural machinery of eye movement is accessible for quantitative study and modeling. Our experiments are conducted in awake, behaviorally trained rhesus monkeys and entail quantitative assessment of motor performance, extracellular recording from single brain cells during eye movement, theory based analyses of neural and behavioral data, and computational analyses of models that are based on biological observations.

Visual-motor transformations for smooth pursuit eye movements

When a small, smoothly moving object appears, primates are able to generate a smooth eye movement having a velocity nearly equal to the velocity of the target. The basic anatomical circuit for pursuit is known -- from retina to motoneuron. We are trying to understand how visual inputs related to moving targets are converted by the brain to commands for motor action. In the past 5 years, we have discovered that pursuit is a complex voluntary motor behavior that comprises many components. These include: the representation of target motion with respect to the eye, primarily in extrastriate area MT (Lisberger & Movshon 1999; Osborne et al 2004); pooling of the population response in MT to acquire good estimates of the direction and speed of target motion (Churchland & Lisberger 2001; Gardner et al 2004); an on-line volume control that regulates how strongly visual inputs are transmitted to the motor system (Tanaka & Lisberger 2001); the ability to choose targets based on a spatial window of motor attention under the control of orienting, saccadic eye movements (Gardner & Lisberger 2002); learning based on the recent history of target motions (Chou & Lisberger 2004; Medina & Lisberger 2005); and cerebellar compensation for the physical properties of the eye and orbit.

Our work is currently focusing on two main concepts.

1) We are using theoretical approaches to exploit the variation in natural pursuit behavior and neural responses. Our goal is to correlate the variation in neural and motor behavior as a way of understanding how different groups of neurons contribute to pursuit behavior. Recent results have revealed that the variation in pursuit behavior can be understood in terms of errors in estimates of the direction, speed, and time of onset of target motion. The coordinate system of the variations implies pursuit operates at the precision to sensory coding, and that motor noise may arise primarily from sensory representations (Osborne et al 2005). By relating variations in sensory representation to variations in motor behavior, we are exploring how variation, signal, and noise are handled in a noisy brain.

2) We are using a combination of precise measurements of eye movement, electrical stimulation, and neural recordings to evaluate the neural basis for modulation of the strength of visual transmission to the motor system. We have evidence that the neural mechanism of this "gain" modulation is related to learning, target choice, and motor attention (Schoppik and Lisberger 2006). Our goal is to identify the neural loci and mechanisms of gain modulation, learning, and target choice.

Learning and memory in the vestibulo-ocular reflex (VOR)

The VOR responds to head turns with compensatory eye movements that keep the eyes stable in space. Even in total darkness, the performance of the VOR is superb -- a head turn in one direction produces an equal amplitude smooth eye rotation in the opposite direction. If a monkey views the stationary environment through telescope spectacles, there are gradual "learned" changes in the eye movements evoked by head turns in darkness. After several days, the eye movements of the VOR in the dark are nearly appropriate for the visual conditions seen through the spectacles, demonstrating "memory" of the learned changes. In 1994, we published the results of a long series of experiments leading to the hypothesis that there are two sites of memory: one in the cerebellar cortex and one in the brainstem (Lisberger et al 1994a,b,c; Lisberger 1994). In 1998, we published the analysis of possible error signals to control modifications at both sites (Raymond & Lisberger 1998), revealing that different signals might be important for vestibular stimuli over different frequency ranges. A comparison of vestibular inputs and climbing fiber responses would be an effective error signal only if each climbing fiber response was compared with the vestibular inputs from 100 ms earlier.

Our work is currently exploiting a new set of stimuli to learn more about the site and neural mechanism of learning in the VOR. By extending the range of sinusoidal vestibular stimuli used to test the VOR up to 50 Hz, we have discovered that the VOR becomes very large at high frequencies, but that the responses at super-high frequencies do not express learning (Ramachandran and Lisberger 2005). We are currently recording from vestibular afferents, interneurons in the brainstem, Purkinje cells in the cerebellum, and motoneurons in the Abducens nucleus to determine the neural basis for these behavioral phenomena (Ramachandran and Lisberger 2006).

Research opportunities

Many projects are available to study either smooth pursuit eye movements, the VOR, or the cerebellum. Projects can use any combination of analysis of motor behavior, recordings from single neurons and microstimulation, and theoretical/computational analyses. In the latter areas, opportunities include participation in the creation of tools for analysis of neural and behavioral data, and large scale modeling at sensory, sensory-motor, and cerebellar levels of either movement system.

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Current Projects

Ongoing projects include:

1. Recordings from multiple single neurons simultaneously to determine the relationship between variation and neural and behavioral responses throughout the circuit for smooth pursuit eye movements.

2. Cortical and cerebellar recordings to determine first the representation and ultimately the site of pursuit learning.

3. Recordings throughout the cortical pursuit system of behaving monkeys to understand the sites and neural mechanisms of vector averaging, immediate modulation of pursuit gain, and post-saccadic enhancement

4. Evaluation of the relationship between pursuit responses in the frontal pursuit area and the cerebellum.

5. Evaluation of pursuit eye movements of humans.

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Lab Members

Hohl, Sonja
Graduate Student
Relationship between neural and pursuit variation in area MT

Schoppik, David
Graduate Student
Analysis of neural variation in pursuit motor cortex

Garbutt, Siobhan
Postdoctoral Fellow
PhD
Smooth pursuit behavior in humans

Heuer, Hilary
Postdoctoral Fellow
PhD, UC Davis
Neural basis for gain control in pursuit

Medina, Javier
Postdoctoral Fellow
PhD, Univ. Texas
Signal, noise, and variation in the cerebellum

Osborne, Leslie
Postdoctoral Fellow
PhD, UC Berkeley
Sensory basis for motor variations

Li, Jenn
Graduate Student
Role of basal ganglia in smooth pursuit

Yang, Jin
Postdoctoral Fellow
PhD, Univ. Beijing
Decoding of population response in area MT

Huang, Xin
Postdoctoral Fellow
PhD, Brown Univ.
Neuron-neuron correlations in areas MT and MST

O'Leary, John
Graduate Student
Representation and decoding of target acceleration

Roitman, Alex
Postdoctoral Fellow
PhD, Univ. Minnesota
Cortical inputs to the cerebellum

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Selected Publications

Link to Publication via PubMed

Schoppik, D. and Lisberger S.G. (2006) Saccades exert spatial control of motion processing for smooth pursuit eye movements. J. Neurosci. 26: 7607-7618.

Priebe, N.J., Lisberger, S.G., and Movshon, J.A. (2006) The neural representation of stimulus speed in macaque primary visual cortex. J. Neurosci. 26: 2941-2950.

Osborne, L.C., Lisberger, S.G., and Bialek, W. (2005) A sensory source for motor variation. Nature. 437: 412-416.

Carey, M.C., Medina, J., and Lisberger, S.G. (2005) Instructive signals for motor learning from visual cortical area MT. Nature Neurosci. 8: 813-819

Medina, J., Carey, M.C., and Lisberger, S.G. (2005) Representation of time in motor control. Neuron 45: 157-167.

Tanaka, M. and Lisberger, S.G. (2001) Regulation of the gain of visually-guided smooth pursuit eye movements by frontal cortex. Nature, 409: 191-194.

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Stephen Lisberger, Ph.D.



Email

sgl@phy.ucsf.edu

Phone

415-476-1062

Physical Address

513 Parnassus, HSE-812

Mailing Address

UCSF, Dept. of Physiology
513 Parnassus
Box 0444
San Francisco, CA 94143-0444

For Internal Campus Mail

Box 0444

other Websites

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