Smooth pursuit eye movements are used by primates to track moving objects. They are initiated by sensory estimates of target speed represented in the middle temporal (MT) area of extrastriate visual cortex and then supported by motor feedback to maintain steady-state eye speed at target speed. Here, we show that reducing the coherence in a patch of dots for a tracking target degrades the eye speed both at the initiation of pursuit and during steady-state tracking, when eye speed reaches an asymptote well below target speed. The deficits are quantitatively different between the motor-supported steady-state of pursuit and the sensory-driven initiation of pursuit, suggesting separate mechanisms. The deficit in visually guided pursuit initiation could not explain the deficit in steady-state tracking. Pulses of target speed during steady-state tracking revealed lower sensitivities to image motion across the retina for lower values of dot coherence. However, sensitivity was not zero, implying that visual motion should still be driving eye velocity toward target velocity. When we changed dot coherence from 100% to lower values during accurate steady-state pursuit, we observed larger eye decelerations for lower coherences, as expected if motor feedback was reduced in gain. A simple pursuit model accounts for our data based on separate modulation of the strength of visual-motor transmission and motor feedback. We suggest that reduced dot coherence allows us to observe evidence for separate modulations of the gain of visual-motor transmission during pursuit initiation and of the motor corollary discharges that comprise eye velocity memory and support steady-state tracking. NEW & NOTEWORTHY We exploit low-coherence patches of dots to control the initiation and steady state of smooth pursuit eye movements and show that these two phases of movement are modulated separately by the reliability of visual motion signals. We conclude that the neural circuit for pursuit includes separate modulation of the strength of visual-motor transmission for movement initiation and of eye velocity positive feedback to support steady-state tracking.

19Smooth pursuit eye movements are used by primates to track moving objects. They are initiated 20 by sensory estimates of target speed represented in the middle temporal (MT) area of extrastriate 21 visual cortex and then supported by motor feedback to maintain steady-state eye speed at target 22 speed. Here, we show that reducing the coherence in a patch of dots for a tracking target 23 degrades the eye speed both at the initiation of pursuit and during steady-state tracking, when eye 24 speed reaches an asymptote well below target speed. The deficits are quantitatively different 25 between the motor-supported steady-state of pursuit and the sensory-driven initiation of pursuit, 26 suggesting separate mechanisms. The deficit in visually-guided pursuit initiation could not 27 explain the deficit in steady-state tracking. Pulses of target speed during steady-state tracking 28 revealed lower sensitivities to image motion across the retina for lower values of dot coherence. 29However, sensitivity was not zero, implying that visual motion should still be driving eye 30 velocity towards target velocity. When we changed dot coherence from 100% to lower values 31 during accurate steady-state pursuit, we observed larger eye decelerations for lower coherences, 32 as expected if motor feedback was reduced in gain. A simple pursuit model accounts for our data 33 based on separate modulation of the strength of visual-motor transmission and motor feedback. 34 We suggest that reduced dot coherence creates less reliable target motion that impacts pursuit 35 initiation by changing the gain of visual-motor transmission and perturbs steady-state tracking by 36 modulation of the motor corollary discharges that comprise eye velocity memory. 37 67 a neural correlate of target velocity (Miles and Fuller, 1976; Lisberger and Fuchs, 1978; Stone 68 and Lisberger, 1990). Floccular Purkinje cells receive input from the sensory pathway as well as 69 positive motor feedback and generate simple-spike firing that represents a kinematic model of 70 eye movements (Shidara et al., 1993; Medina and Lisberger, 2009). In turn, Purkinje cells have 71 disynaptic connections to the motoneurons for the eye muscles and therefore drive pursuit 72 (Highstein, 1973; Scudder and Fuchs, 1992; Lisberger et al., 1994). 73Most previous thinking about the role of the floccular complex has assumed that eye velocity 74 positive feedback is fixed and immutable (Stone and Lisberger, 1990; Krauzlis and Lisberger, 75 1994; Schwartz and Lisberger, 1994). However, our analysis of the expression of motor learning 76 in pursuit raised the possibility that it is subject to modulation (Yang and Lisberger, 2010; Hall et 77 al., 2018). To determine if the steady-state of pursuit is modulated by motion reliability, and if 78the modulation is separate from that for the initiation of pursuit, we have developed a target and 79 a task that reliably perturbs both pursuit initiation and steady-state tracking. We use motion 80 coherence in a patch of dots (Newsome and Paré, 1...

Visual motion drives smooth pursuit eye movements through a sensory-motor decoder that uses multiple parallel components and neural pathways to transform the population response in extrastriate area MT into movement. We evaluated the decoder by challenging pursuit in monkeys with reduced motion reliability created by reducing coherence of motion in patches of dots. Reduced dot coherence caused deficits in both the initiation of pursuit and steady-state tracking, revealing the paradox of steady-state eye speeds that fail to accelerate to target speed in spite of persistent image motion. We recorded neural responses to reduced dot coherence in MT and found a decoder that transforms MT population responses into eye movements. During pursuit initiation, decreased dot coherence reduces MT population response amplitude without changing the preferred speed at the peak of the population response. The successful decoder reproduces the measured eye movements by multiplication of (i) the estimate of target speed from the peak of the population response with (ii) visual-motor gain based on the amplitude of the population response. During steady-state tracking, the decoder that worked for pursuit initiation failed. It predicted eye acceleration to target speed even when monkeys' eye speeds were steady at a level well below target speed. We can account for the effect of dot coherence on steady-state eye speed if sensory-motor gain also modulates the eye velocity positive feedback that normally sustains perfect steady-state tracking. Then, poor steady-state tracking persists because of balance between deceleration caused by low positive feedback gain and acceleration driven by MT.

Visual motion drives smooth pursuit eye movements through a sensory-motor decoder that uses multiple parallel neural pathways to transform the population response in extrastriate area MT into movement. We evaluated the decoder by challenging pursuit in monkeys with reduced motion reliability created by reducing coherence of motion in patches of dots. Our strategy was to determine how reduced dot coherence changes the population response in MT. We then predicted the properties of a decoder that transforms the MT population response into dot-coherence-induced deficits in the initiation of pursuit and steady-state tracking. During pursuit initiation, decreased dot coherence reduces MT population response amplitude without changing the preferred speed at its peak. The successful decoder reproduces the measured eye movements by multiplication of (i) the estimate of target speed from the peak of the population response with (ii) visual-motor gain based on the amplitude of the population response. During steady-state tracking, the decoder that worked for pursuit initiation failed to reproduce the paradox that steady-state eye speeds don't accelerate to target speed in spite of persistent image motion. It predicted eye acceleration to target speed even when monkeys' eye speeds were steady at well below target speed. To account for the effect of dot coherence on steady-state eye speed we postulate that the decoder uses sensory-motor gain to modulate the eye velocity positive feedback that normally sustains perfect steady-state tracking. Then, poor steady-state tracking persists because of balance between eye deceleration caused by low positive feedback gain and acceleration driven by MT.