The olivary input to the cerebellum dissociates sensory events from movement plans.

Neurons in the inferior olive are thought to anatomically organize the Purkinje cells (P-cells) of the cerebellum into computational modules, but what is computed by each module? Here, we designed a saccade task in marmosets that dissociated sensory events from motor events and then recorded the complex and simple spikes of hundreds of P-cells. We found that when a visual target was presented at a random location, the olive reported the direction of that sensory event to one group of P-cells, but not to a second group. However, just before movement onset, it reported the direction of the planned movement to both groups, even if that movement was not toward the target. At the end of the movement if the subject experienced an error but chose to withhold the corrective movement, only the first group received information about the sensory prediction error. We organized the P-cells based on the information content of their olivary input and found that in the group that received sensory information, the simple spikes were suppressed during fixation, then produced a burst before saccade onset in a direction consistent with assisting the movement. In the second group, the simple spikes were not suppressed during fixation but burst near saccade deceleration in a direction consistent with stopping the movement. Thus, the olive differentiated the P-cells based on whether they would receive sensory or motor information, and this defined their contributions to control of movements as well as holding still.

Slowing of Movements in Healthy Aging as a Rational Economic Response to an Elevated Effort Landscape.

Why do we move slower as we grow older? The reward circuits of the brain, which tend to invigorate movements, decline with aging, raising the possibility that reduced vigor is due to the diminishing value that our brain assigns to movements. However, as we grow older, it also becomes more effortful to make movements. Is age-related slowing principally a consequence of increased effort costs from the muscles, or reduced valuation of reward by the brain? Here, we first quantified the cost of reaching via metabolic energy expenditure in human participants (male and female), and found that older adults consumed more energy than the young at a given speed. Thus, movements are objectively more costly for older adults. Next, we observed that when reward increased, older adults, like the young, responded by initiating their movements earlier. Yet, unlike the young, they were unwilling to increase their movement speed. Was their reluctance to reach quicker for rewards due to the increased effort costs, or because they ascribed less value to the movement? Motivated by a mathematical model, we next made the young experience a component of aging by making their movements more effortful. Now the young responded to reward by reacting faster but chose not to increase their movement speed. This suggests that slower movements in older adults are partly driven by an adaptive response to an elevated effort landscape. Moving slower may be a rational economic response the brain is making to mitigate the elevated effort costs that accompany aging.

Synchronous spiking of cerebellar Purkinje cells during control of movements.

SignificanceThe information that one region of the brain transmits to another is usually viewed through the lens of firing rates. However, if the output neurons could vary the timing of their spikes, then, through synchronization, they would spotlight information that may be critical for control of behavior. Here we report that, in the cerebellum, Purkinje cell populations that share a preference for error convey, to the nucleus, when to decelerate the movement, by reducing their firing rates and temporally synchronizing the remaining spikes.

Effects of reward and effort history on decision making and movement vigor during foraging.

During foraging, animals explore a site and harvest reward and then abandon that site and travel to the next opportunity. One aspect of this behavior involves decision making, and the other involves movement control. These two aspects of behavior may be linked via an underlying desire to maximize a single normative utility: the sum of all rewards acquired, minus all efforts expended, divided by time. According to this theory, the history of rewards, and not just its immediate availability, should dictate how long one should stay and harvest reward and how vigorously one should travel to the next opportunity. We tested this theory in a series of experiments in which humans used their hand to harvest tokens at a reward patch and then used their arm to reach toward another patch. After a history of high rewards, the subjects not only shortened their harvest duration but also moved more vigorously toward the next reward opportunity. In contrast, after a history of high effort they lengthened their harvest duration but reduced their movement vigor, reaching more slowly to the next reward site. Thus, a history of high reward or low effort biased decisions by promoting early abandonment of the reward site and biased movements by promoting vigor.NEW & NOTEWORTHY Much of life is spent foraging. Whereas previous work has focused on the decision regarding time spent harvesting from a reward patch, here we test the idea that both decision making and movement control are tuned to optimize the net rate of reward in an environment. Our results show that movement patterns reflect not just immediate expectations but also past experiences in the environment, providing fundamental insight into the factors governing volitional control of arm movements.

Rejuvenating silicon probes for acute neurophysiology.

Neurophysiological recording with a new probe often yields better signal quality than with a used probe. Why does the signal quality degrade after only a few experiments? Here, we considered silicon probes in which the contacts are densely packed, and each contact is coated with a conductive polymer that increases its surface area. We tested 12 Cambridge Neurotech silicon probes during 61 recording sessions from the brain of 3 marmosets. Out of the box, each probe arrived with an electrodeposited polymer coating on 64 gold contacts, and an impedance of around 50k Ohms. With repeated use, the impedance increased and there was a corresponding decrease in the number of well-isolated neurons. Imaging of the probes suggested that the reduction in signal quality was due to a gradual loss of the polymer coating. To rejuvenate the probes, we first stripped the contacts, completely removing their polymer coating, and then recoated them in a solution of 10 mM EDOT monomer with 11 mM PSS using a current density of about 3mA/cm2 for 30 seconds. This recoating process not only returned probe impedance to around 50k Ohms, but it also yielded significantly improved signal quality during neurophysiological recordings. Thus, insertion into the brain promoted loss of the polymer that coated the contacts of the silicon probes. This led to degradation of signal quality, but recoating rejuvenated the probes.

The cost of correcting for error during sensorimotor adaptation.

Learning from error is often a slow process. In machine learning, the learning rate depends on a loss function that specifies a cost for error. Here, we hypothesized that during motor learning, error carries an implicit cost for the brain because the act of correcting for error consumes time and energy. Thus, if this implicit cost could be increased, it may robustly alter how the brain learns from error. To vary the implicit cost of error, we designed a task that combined saccade adaptation with motion discrimination: movement errors resulted in corrective saccades, but those corrections took time away from acquiring information in the discrimination task. We then modulated error cost using coherence of the discrimination task and found that when error cost was large, pupil diameter increased and the brain learned more from error. However, when error cost was small, the pupil constricted and the brain learned less from the same error. Thus, during sensorimotor adaptation, the act of correcting for error carries an implicit cost for the brain. Modulating this cost affects how much the brain learns from error.

Impact of unilateral and bilateral impairments on bimanual force production following stroke.

Large bilateral asymmetry and task deficits are typically observed during bimanual actions of stroke survivors. Do these abnormalities originate from unilateral impairments affecting their more-impaired limb, such as weakness and abnormal synergy, or from bilateral impairments such as incoordination of two limbs? To answer this question, 23 subjects including 10 chronic stroke survivors and 13 neurologically intact subjects participated in an experiment where they produced bimanual forces at different hand locations. The force magnitude and directional deviation of the more-impaired arm were measured for unilateral impairments and bimanual coordination across locations for bilateral impairments. Force asymmetry and task error were used to define task performance. Significant unilateral impairments were observed in subjects with stroke; the maximal force capacity of their more-impaired arm was significantly lower than that of their less-impaired arm, with a higher degree of force deviation. However, its force contribution during submaximal tasks was greater than its relative force capacity. Significant bilateral impairments were also observed, as stroke survivors modulated two forces to a larger degree across hand locations but in a less coordinated manner than control subjects did. But only unilateral, not bilateral, impairments explained a significant amount of between-subject variability in force asymmetry across subjects with stroke. Task error, in contrast, was correlated with neither unilateral nor bilateral impairments. Our results suggest that unilateral impairments of the more-impaired arm of stroke survivors mainly contribute to its reduced recruitment, but that the degree of its participation in bimanual task may be greater than their capacity as they attempt to achieve symmetry.NEW & NOTEWORTHY We studied how unilateral and bilateral impairments in stroke survivors affect their bimanual task performance. Unilateral impairments of the more-impaired limb, both weakness and loss of directional control, mainly contribute to bimanual asymmetry, but stroke survivors generally produce higher force with their more-impaired limb than their relative capacity. Bilateral force coordination was significantly impaired in stroke survivors, but its degree of impairment was not related to their unilateral impairments.

Defending against cerebellar disease.

A hedge fund billionaire's children are suffering from cerebellar disease. He invited a group of neuroscientists to plan a search for therapies. What resulted is the outline of an implantable neural emulator that might electronically replace the damaged part of the brain.

Adaptive control of movement deceleration during saccades.

As you read this text, your eyes make saccades that guide your fovea from one word to the next. Accuracy of these movements require the brain to monitor and learn from visual errors. A current model suggests that learning is supported by two different adaptive processes, one fast (high error sensitivity, low retention), and the other slow (low error sensitivity, high retention). Here, we searched for signatures of these hypothesized processes and found that following experience of a visual error, there was an adaptive change in the motor commands of the subsequent saccade. Surprisingly, this adaptation was not uniformly expressed throughout the movement. Rather, after experience of a single error, the adaptive response in the subsequent trial was limited to the deceleration period. After repeated exposure to the same error, the acceleration period commands also adapted, and exhibited resistance to forgetting during set-breaks. In contrast, the deceleration period commands adapted more rapidly, but suffered from poor retention during these same breaks. State-space models suggested that acceleration and deceleration periods were supported by a shared adaptive state which re-aimed the saccade, as well as two separate processes which resembled a two-state model: one that learned slowly and contributed primarily via acceleration period commands, and another that learned rapidly but contributed primarily via deceleration period commands.

Perceived effort affects choice of limb and reaction time of movements.

The decision regarding which arm to use to perform a task reflects a complex process that can be influenced by many factors, including effort requirements of acquiring the goal. In this study, we considered a virtual reality environment in which people reached to a visual target in three-dimensional space. To vary the cost of reaching, we altered the visual feedback associated with motion of one arm but not the other. This altered the extent of motion that was required to reach, thus changing the effort required to acquire the goal. We then measured how that change in effort affected the decision regarding which arm to use, as well as the preparation time for the movement that ensued. As expected, with increased visual amplification of one arm (reduced effort to reach the goal), subjects increased the probability of choosing that arm. Surprisingly, however, the reaction times to start these movements were also reduced: despite constancy of the visual representation of the target, reaction times were shorter for movements with less effort. Thus, as the perceived effort associated with accomplishing a goal was reduced for a given limb, the decision-making process was biased toward use of that limb. Furthermore, movements that were perceived to be less effortful were performed with shorter reaction times. These results suggest that visual amplification can alter the perceived effort associated with using a limb, thus increasing frequency of use. This may provide a useful method to increase use of a limb during rehabilitation.NEW & NOTEWORTHY We report that visual amplification may serve as an effective means to alter the perceived effort associated with use of a limb. This method may provide an effective tool with which use of the affected limb can be encouraged noninvasively after neurological injury.

P-sort: an open-source software for cerebellar neurophysiology.

Analysis of electrophysiological data from Purkinje cells (P-cells) of the cerebellum presents unique challenges to spike sorting. Complex spikes have waveforms that vary significantly from one event to the next, raising the problem of misidentification. Even when complex spikes are detected correctly, the simple spikes may belong to a different P-cell, raising the danger of misattribution. To address these identification and attribution problems, we wrote an open-source, semiautomated software called P-sort, and then tested it by analyzing data from P-cells recorded in three species: marmosets, macaques, and mice. Like other sorting software, P-sort relies on nonlinear dimensionality reduction to cluster spikes. However, it also uses the statistical relationship between simple and complex spikes to merge disparate clusters and split a single cluster. In comparison with expert manual curation, occasionally P-sort identified significantly more complex spikes, as well as prevented misattribution of clusters. Three existing automatic sorters performed less well, particularly for identification of complex spikes. To improve the development of analysis tools for the cerebellum, we provide labeled data for 313 recording sessions, as well as statistical characteristics of waveforms and firing patterns of P-cells in three species.NEW & NOTEWORTHY Algorithms that perform spike sorting depend on waveforms to cluster spikes. However, a cerebellar Purkinje-cell produces two types of spikes; simple and complex spikes. A complex spike coincides with the suppression of generating simple spikes. Here, we recorded neurophysiological data from three species and developed a spike analysis software named P-sort that relies on this statistical property to improve both the detection and the attribution of simple and complex spikes in the cerebellum.

Encoding of action by the Purkinje cells of the cerebellum.

Execution of accurate eye movements depends critically on the cerebellum, suggesting that the major output neurons of the cerebellum, Purkinje cells, may predict motion of the eye. However, this encoding of action for rapid eye movements (saccades) has remained unclear: Purkinje cells show little consistent modulation with respect to saccade amplitude or direction, and critically, their discharge lasts longer than the duration of a saccade. Here we analysed Purkinje-cell discharge in the oculomotor vermis of behaving rhesus monkeys (Macaca mulatta) and found neurons that increased or decreased their activity during saccades. We estimated the combined effect of these two populations via their projections to the caudal fastigial nucleus, and uncovered a simple-spike population response that precisely predicted the real-time motion of the eye. When we organized the Purkinje cells according to each cell's complex-spike directional tuning, the simple-spike population response predicted both the real-time speed and direction of saccade multiplicatively via a gain field. This suggests that the cerebellum predicts the real-time motion of the eye during saccades via the combined inputs of Purkinje cells onto individual nucleus neurons. A gain-field encoding of simple spikes emerges if the Purkinje cells that project onto a nucleus neuron are not selected at random but share a common complex-spike property.

The Origins of Anterograde Interference in Visuomotor Adaptation.

Anterograde interference refers to the negative impact of prior learning on the propensity for future learning. There is currently no consensus on whether this phenomenon is transient or long lasting, with studies pointing to an effect in the time scale of hours to days. These inconsistencies might be caused by the method employed to quantify performance, which often confounds changes in learning rate and retention. Here, we aimed to unveil the time course of anterograde interference by tracking its impact on visuomotor adaptation at different intervals throughout a 24-h period. Our empirical and model-based approaches allowed us to measure the capacity for new learning separately from the influence of a previous memory. In agreement with previous reports, we found that prior learning persistently impaired the initial level of performance upon revisiting the task. However, despite this strong initial bias, learning capacity was impaired only when conflicting information was learned up to 1 h apart, recovering thereafter with passage of time. These findings suggest that when adapting to conflicting perturbations, impairments in performance are driven by two distinct mechanisms: a long-lasting bias that acts as a prior and hinders initial performance and a short-lasting anterograde interference that originates from a reduction in error sensitivity.

Control of movement vigor and decision making during foraging.

During foraging, animals decide how long to stay at a patch and harvest reward, and then, they move with certain vigor to another location. How does the brain decide when to leave, and how does it determine the speed of the ensuing movement? Here, we considered the possibility that both the decision-making and the motor control problems aimed to maximize a single normative utility: the sum of all rewards acquired minus all efforts expended divided by total time. This optimization could be achieved if the brain compared a local measure of utility with its history. To test the theory, we examined behavior of people as they gazed at images: they chose how long to look at the image (harvesting information) and then moved their eyes to another image, controlling saccade speed. We varied reward via image content and effort via image eccentricity, and then, we measured how these changes affected decision making (gaze duration) and motor control (saccade speed). After a history of low rewards, people increased gaze duration and decreased saccade speed. In anticipation of future effort, they lowered saccade speed and increased gaze duration. After a history of high effort, they elevated their saccade speed and increased gaze duration. Therefore, the theory presented a principled way with which the brain may control two aspects of behavior: movement speed and harvest duration. Our experiments confirmed many (but not all) of the predictions, suggesting that harvest duration and movement speed, fundamental aspects of behavior during foraging, may be governed by a shared principle of control.

Movement control, decision-making, and the building of Roman roads to link them.

In science, as in life, one can only hope to both inform others, and be informed by them. The commentaries associated with our book Vigor have highlighted the many ways in which the theory that we proposed can be improved. For example, there are a myriad of factors that need to be considered in a fully encompassing objective function. The neural mechanisms underlying the links between movement and decision-making have yet to be unraveled. The implications of a two-way interaction between movement and decisions at both the individual and social levels remain to be understood. The commentaries outline future questions, and encouragingly highlight the diversity of science communities that may be linked via the concept of vigor.

Reward Prediction Error Modulates Saccade Vigor.

Movement vigor, defined as the reciprocal of the latency from availability of reward to its acquisition, changes with reward magnitude: movements exhibit shorter reaction time and increased velocity when they are directed toward more rewarding stimuli. This invigoration may be due to release of dopamine before movement onset, which has been shown to be modulated by events that signal reward prediction error (RPE). Here, we generated an RPE event in the milliseconds before movement onset and tested whether there was a relationship between RPE and vigor. Human subjects (both sexes) made saccades toward an image. During execution of the primary saccade, we probabilistically changed the position and content of that image, encouraging a secondary saccade. On some trials, the content of the secondary image was more valuable than the first image, resulting in a positive RPE (+RPE) event that preceded the secondary saccade. On other trials, this content was less valuable (-RPE event). We found that reaction time of the secondary saccade was affected in an orderly fashion by the magnitude and direction of the preceding RPE event: the most vigorous saccades followed the largest +RPE, whereas the least vigorous saccades followed the largest -RPE. Presence of the secondary saccade indicated that the primary saccade had experienced a movement error, inducing trial-to-trial adaptation. However, this learning from movement error was not modulated by the RPE event. The data suggest that RPE events, which are thought to transiently alter the release of dopamine, modulate the vigor of the ensuing movement.SIGNIFICANCE STATEMENT Does dopamine release in response to a stimulus serve to invigorate the ensuing movement? To test this hypothesis, we relied on the fact that reward prediction error (RPE) is a strong modulator of dopamine. Our innovation was a task in which an RPE event occurred precisely before onset of a stimulus-driven movement. We probabilistically produced a combination of large or small, negative or positive RPE events and observed that saccade vigor carried a robust signature of the preceding RPE event: high vigor saccades followed +RPE events, whereas low vigor saccades followed -RPE events. This suggests that in humans, vigor is partly controlled through release of dopamine in the moments before onset of a movement.

Population coding in the cerebellum: a machine learning perspective.

The cere resembles a feedforward, three-layer network of neurons in which the "hidden layer" consists of Purkinje cells (P-cells) and the output layer consists of deep cerebellar nucleus (DCN) neurons. In this analogy, the output of each DCN neuron is a prediction that is compared with the actual observation, resulting in an error signal that originates in the inferior olive. Efficient learning requires that the error signal reach the DCN neurons, as well as the P-cells that project onto them. However, this basic rule of learning is violated in the cerebellum: the olivary projections to the DCN are weak, particularly in adulthood. Instead, an extraordinarily strong signal is sent from the olive to the P-cells, producing complex spikes. Curiously, P-cells are grouped into small populations that converge onto single DCN neurons. Why are the P-cells organized in this way, and what is the membership criterion of each population? Here, I apply elementary mathematics from machine learning and consider the fact that P-cells that form a population exhibit a special property: they can synchronize their complex spikes, which in turn suppress activity of DCN neuron they project to. Thus complex spikes cannot only act as a teaching signal for a P-cell, but through complex spike synchrony, a P-cell population may act as a surrogate teacher for the DCN neuron that produced the erroneous output. It appears that grouping of P-cells into small populations that share a preference for error satisfies a critical requirement of efficient learning: providing error information to the output layer neuron (DCN) that was responsible for the error, as well as the hidden layer neurons (P-cells) that contributed to it. This population coding may account for several remarkable features of behavior during learning, including multiple timescales, protection from erasure, and spontaneous recovery of memory.

Saccade vigor and the subjective economic value of visual stimuli.

Decisions are made based on the subjective value that the brain assigns to options. However, subjective value is a mathematical construct that cannot be measured directly, but rather is inferred from choices. Recent results have demonstrated that reaction time, amplitude, and velocity of movements are modulated by reward, raising the possibility that there is a link between how the brain evaluates an option and how it controls movements toward that option. Here, we asked people to choose among risky options represented by abstract stimuli, some associated with gain (points in a game), and others with loss. From their choices we estimated the subjective value that they assigned to each stimulus. In probe trials, a single stimulus appeared at center, instructing subjects to make a saccade to a peripheral target. We found that the reaction time, peak velocity, and amplitude of the peripherally directed saccade varied roughly linearly with the subjective value that the participant had assigned to the central stimulus: reaction time was shorter, velocity was higher, and amplitude was larger for stimuli that the participant valued more. Naturally, participants differed in how much they valued a given stimulus. Remarkably, those who valued a stimulus more, as evidenced by their choices in decision trials, tended to move with shorter reaction time and greater velocity in response to that stimulus in probe trials. Overall, the reaction time of the saccade in response to a stimulus partly predicted the subjective value that the brain assigned to that stimulus.NEW & NOTEWORTHY Behavioral economics relies on subjective evaluation, an abstract quantity that cannot be measured directly but must be inferred by fitting decision models to the choice patterns. Here, we present a new approach to estimate subjective value: with nothing to fit, we show that it is possible to estimate subjective value based on movement kinematics, providing a modest ability to predict a participant's preferences without prior measurement of their choice patterns.

Précis of Vigor: Neuroeconomics of Movement Control.

Why do we run toward people we love, but only walk toward others? Why do people in New York seem to walk faster than other cities? Why do our eyes linger longer on things we value more? There is a link between how the brain assigns value to things, and how it controls our movements. This link is an ancient one, developed through shared neural circuits that on one hand teach us how to value things, and on the other hand control the vigor with which we move. As a result, when there is damage to systems that signal reward, like dopamine and serotonin, that damage not only affects our mood and patterns of decision-making, but how we move. In this book, we first ask why, in principle, evolution should have developed a shared system of control between valuation and vigor. We then focus on the neural basis of vigor, synthesizing results from experiments that have measured activity in various brain structures and neuromodulators, during tasks in which animals decide how patiently they should wait for reward, and how vigorously they should move to acquire it. Thus, the way we move unmasks one of our well-guarded secrets: how much we value the thing we are moving toward.

Behavioral training of marmosets and electrophysiological recording from the cerebellum.

The common marmoset (Callithrix jacchus) is a promising new model for study of neurophysiological basis of behavior in primates. Like other primates, it relies on saccadic eye movements to monitor and explore its environment. Previous reports have demonstrated some success in training marmosets to produce goal-directed actions in the laboratory. However, the number of trials per session has been relatively small, thus limiting the utility of marmosets as a model for behavioral and neurophysiological studies. In this article, we report the results of a series of new behavioral training and neurophysiological protocols aimed at increasing the number of trials per session while recording from the cerebellum. To improve the training efficacy, we designed a precisely calibrated food regulation regime that motivates the subjects to perform saccade tasks, resulting in ~1,000 reward-driven trials on a daily basis. We then developed a multichannel recording system that uses imaging to target a desired region of the cerebellum, allowing for simultaneous isolation of multiple Purkinje cells in the vermis. In this report, we describe 1) the design and surgical implantation of a computer tomography (CT)-guided, subject-specific head post, 2) the design of a CT- and MRI-guided alignment tool for trajectory guidance of electrodes mounted on an absolute encoder microdrive, 3) development of a protocol for behavioral training of subjects, and 4) simultaneous recordings from pairs of Purkinje cells during a saccade task.NEW & NOTEWORTHY Marmosets present the opportunity to investigate genetically based neurological disease in primates, in particular, diseases that affect social behaviors, vocal communication, and eye movements. All of these behaviors depend on the integrity of the cerebellum. We present training methods that better motivate the subjects, allowing for improved performance, and we also present electrophysiological techniques that precisely target the subject's cerebellum, allowing for simultaneous isolation of multiple Purkinje cells.