Leslie C. Osborne

A sensory source for motor variation.

Suppose that the variability in our movements is caused not by noise in the motor system itself, nor by fluctuations in our intentions or plans, but rather by errors in our sensory estimates of the external parameters that define the appropriate action. For tasks in which precision is at a premium, performance would be optimal if no noise were added in movement planning and execution: motor output would be as accurate as possible given the quality of sensory inputs. Here we use visually guided smooth-pursuit eye movements in primates as a testing ground for this notion of optimality. In response to repeated presentations of identical target motions, nearly 92% of the variance in eye trajectory can be accounted for as a consequence of errors in sensory estimates of the speed, direction and timing of target motion, plus a small background noise that is observed both during eye movements and during fixations. The magnitudes of the inferred sensory errors agree with the observed thresholds for sensory discrimination by perceptual systems, suggesting that the very different neural processes of perception and action are limited by the same sources of noise.

Time course of information about motion direction in visual area MT of macaque monkeys.

We used the responses of neurons in extrastriate visual area MT to determine how well neural noise can be reduced by averaging the responses of neurons across time. For individual MT neurons, we calculated the time course of Shannon information about motion direction from sustained motion at constant velocities. Stimuli were random dot patterns moving at the preferred speed of the cell for 256 msec, in a direction chosen randomly with 15° increments. Information about motion direction calculated from cumulative spike count rose rapidly from the onset of the neural response and then saturated, reaching 80% of maximum information in the first 100 msec. Most of the early saturation of information could be attributed to correlated fluctuations in the spike counts of individual neurons on time scales in excess of 100 msec. Thus, temporal correlations limit the benefits of averaging across time, much as correlations among the responses of different neurons limit the benefits of averaging across large populations. Although information about direction was available quickly from MT neurons, the direction discrimination by individual MT neurons was poor, with mean thresholds above 30° in most neurons. We conclude that almost all available directional information could be extracted from the first few spikes of the response of the neuron, on a time scale comparable with the initiation of smooth pursuit eye movements. However, neural responses still must be pooled across the population in MT to account for the direction discrimination of the pursuit behavior.

The Neural Basis for Combinatorial Coding in a Cortical Population Response

We have used a combination of theory and experiment to assess how information is represented in a realistic cortical population response, examining how motion direction and timing is encoded in groups of neurons in cortical area MT. Combining data from several single-unit experiments, we constructed model population responses in small time windows and represented the response in each window as a binary vector of 1s or 0s signifying spikes or no spikes from each cell. We found that patterns of spikes and silence across a population of nominally redundant neurons can carry up to twice as much information about visual motion than does population spike count, even when the neurons respond independently to their sensory inputs. This extra information arises by virtue of the broad diversity of firing rate dynamics found in even very similarly tuned groups of MT neurons. Additionally, specific patterns of spiking and silence can carry more information than the sum of their parts (synergy), opening up the possibility for combinatorial coding in cortex. These results also held for populations in which we imposed levels of nonindependence (correlation) comparable to those found in cortical recordings. Our findings suggest that combinatorial codes are advantageous for representing stimulus information on short time scales, even when neurons have no complicated, stimulus-dependent correlation structure.

Imaging and vibrational analysis with laser-feedback interferometry.

We have constructed a scanning confocal laser-feedback microscope that determines surface profiles in the range of 5 nm to 3 μm with ~200-nm lateral discrimination. A direct comparison is made with scanning electron microscopy, and an image of a silicon resolution standard with 40-nm-high structures is shown. The device is also capable of characterizing surface motion with a sensitivity of <1 pm (Hz)−1/2 across a bandwidth of several megahertz. Vibrational analysis of a miniature piezoelectric microphone is demonstrated from 50 Hz to 50 kHz. An operational description of the device is presented in addition to a generalization of laser-feedback theory that includes gas-laser dynamics.

Time course of precision in smooth-pursuit eye movements of monkeys

To evaluate the nature and possible sources of variation in sensory–motor behavior, we measured the signal-to-noise ratio for the initiation of smooth-pursuit eye movements as a function of time and computed thresholds that indicate how well the pursuit system discriminates small differences in the direction, speed, or time of onset of target motion. Thresholds improved rapidly as a function of time and came close to their minima during the interval when smooth eye movement is driven only by visual motion inputs. Many features of the data argued that motor output and sensory discrimination are limited by the same noise source. Pursuit thresholds reached magnitudes similar to those for perception: <2–3° of direction, ∼11–15% of target speed, and 8 ms of change in the time of onset of target motion. Pursuit and perceptual thresholds had similar dependencies on the duration of the motion stimulus and showed similar effects of target speed. The evolution of information about direction of target motion followed the same time course in pursuit behavior and in a previously reported sample of neuronal responses from extrastriate area MT. Changing the form of the sensory input while keeping the motor response fixed had significant effects on the signal-to-noise ratio in pursuit for direction discrimination, whereas holding the sensory input constant while changing the combination of muscles used for the motor output did not. We conclude that noise in sensory processing of visual motion provides the major source of variation in the initiation of pursuit.

Concurrent Imaging of Synaptic Vesicle Recycling and Calcium Dynamics

Synaptic transmission involves the calcium dependent release of neurotransmitter from synaptic vesicles. Genetically encoded optical probes emitting different wavelengths of fluorescent light in response to neuronal activity offer a powerful approach to understand the spatial and temporal relationship of calcium dynamics to the release of neurotransmitter in defined neuronal populations. To simultaneously image synaptic vesicle recycling and changes in cytosolic calcium, we developed a red-shifted reporter of vesicle recycling based on a vesicular glutamate transporter, VGLUT1-mOrange2 (VGLUT1-mOr2), and a presynaptically localized green calcium indicator, synaptophysin-GCaMP3 (SyGCaMP3) with a large dynamic range. The fluorescence of VGLUT1-mOr2 is quenched by the low pH of synaptic vesicles. Exocytosis upon electrical stimulation exposes the luminal mOr2 to the neutral extracellular pH and relieves fluorescence quenching. Reacidification of the vesicle upon endocytosis again reduces fluorescence intensity. Changes in fluorescence intensity thus monitor synaptic vesicle exo- and endocytosis, as demonstrated previously for the green VGLUT1-pHluorin. To monitor changes in calcium, we fused the synaptic vesicle protein synaptophysin to the recently improved calcium indicator GCaMP3. SyGCaMP3 is targeted to presynaptic varicosities, and exhibits changes in fluorescence in response to electrical stimulation consistent with changes in calcium concentration. Using real time imaging of both reporters expressed in the same synapses, we determine the time course of changes in VGLUT1 recycling in relation to changes in presynaptic calcium concentration. Inhibition of P/Q- and N-type calcium channels reduces calcium levels, as well as the rate of synaptic vesicle exocytosis and the fraction of vesicles released.

Searching for simplicity in the analysis of neurons and behavior

What fascinates us about animal behavior is its richness and complexity, but understanding behavior and its neural basis requires a simpler description. Traditionally, simplification has been imposed by training animals to engage in a limited set of behaviors, by hand scoring behaviors into discrete classes, or by limiting the sensory experience of the organism. An alternative is to ask whether we can search through the dynamics of natural behaviors to find explicit evidence that these behaviors are simpler than they might have been. We review two mathematical approaches to simplification, dimensionality reduction and the maximum entropy method, and we draw on examples from different levels of biological organization, from the crawling behavior of Caenorhabditis elegans to the control of smooth pursuit eye movements in primates, and from the coding of natural scenes by networks of neurons in the retina to the rules of English spelling. In each case, we argue that the explicit search for simplicity uncovers new and unexpected features of the biological system and that the evidence for simplification gives us a language with which to phrase new questions for the next generation of experiments. The fact that similar mathematical structures succeed in taming the complexity of very different biological systems hints that there is something more general to be discovered.

Searching for simplicity: Approaches to the analysis of neurons and behavior

What fascinates us about animal behavior is its richness and complexity, but understanding behavior and its neural basis requires a simpler description. Traditionally, simplification has been imposed by training animals to engage in a limited set of behaviors, by hand scoring behaviors into discrete classes, or by limiting the sensory experience of the organism. An alternative is to ask whether we can search through the dynamics of natural behaviors to find explicit evidence that these behaviors are simpler than they might have been. We review two mathematical approaches to simplification, dimensionality reduction and the maximum entropy method, and we draw on examples from different levels of biological organization, from the crawling behavior of Caenorhabditis elegans to the control of smooth pursuit eye movements in primates, and from the coding of natural scenes by networks of neurons in the retina to the rules of English spelling. In each case, we argue that the explicit search for simplicity uncovers new and unexpected features of the biological system and that the evidence for simplification gives us a language with which to phrase new questions for the next generation of experiments. The fact that similar mathematical structures succeed in taming the complexity of very different biological systems hints that there is something more general to be discovered.

Spatial and Temporal Integration of Visual Motion Signals for Smooth Pursuit Eye Movements in Monkeys

To probe how the brain integrates visual motion signals to guide behavior, we analyzed the smooth pursuit eye movements evoked by target motion with a stochastic component. When each dot of a texture executed an independent random walk such that speed or direction varied across the spatial extent of the target, pursuit variance increased as a function of the variance of visual pattern motion. Noise in either target direction or speed increased the variance of both eye speed and direction, implying a common neural noise source for estimating target speed and direction. Spatial averaging was inefficient for targets with >20 dots. Together these data suggest that pursuit performance is limited by the properties of spatial averaging across a noisy population of sensory neurons rather than across the physical stimulus. When targets executed a spatially uniform random walk in time around a central direction of motion, an optimized linear filter that describes the transformation of target motion into eye motion accounted for approximately 50% of the variance in pursuit. Filters had widths of approximately 25 ms, much longer than the impulse response of the eye, and filter shape depended on both the range and correlation time of motion signals, suggesting that filters were products of sensory processing. By quantifying the effects of different levels of stimulus noise on pursuit, we have provided rigorous constraints for understanding sensory population decoding. We have shown how temporal and spatial integration of sensory signals converts noisy population responses into precise motor responses.

Shared Sensory Estimates for Human Motion Perception and Pursuit Eye Movements

Are sensory estimates formed centrally in the brain and then shared between perceptual and motor pathways or is centrally represented sensory activity decoded independently to drive awareness and action? Questions about the brains information flow pose a challenge because systems-level estimates of environmental signals are only accessible indirectly as behavior. Assessing whether sensory estimates are shared between perceptual and motor circuits requires comparing perceptual reports with motor behavior arising from the same sensory activity. Extrastriate visual cortex both mediates the perception of visual motion and provides the visual inputs for behaviors such as smooth pursuit eye movements. Pursuit has been a valuable testing ground for theories of sensory information processing because the neural circuits and physiological response properties of motion-responsive cortical areas are well studied, sensory estimates of visual motion signals are formed quickly, and the initiation of pursuit is closely coupled to sensory estimates of target motion. Here, we analyzed variability in visually driven smooth pursuit and perceptual reports of target direction and speed in human subjects while we manipulated the signal-to-noise level of motion estimates. Comparable levels of variability throughout viewing time and across conditions provide evidence for shared noise sources in the perception and action pathways arising from a common sensory estimate. We found that conditions that create poor, low-gain pursuit create a discrepancy between the precision of perception and that of pursuit. Differences in pursuit gain arising from differences in optic flow strength in the stimulus reconcile much of the controversy on this topic.