A vector calculus for neural computation in the cerebellum.

When a neuron modulates its firing rate during a movement, we tend to assume that it is contributing to control of that movement. However, null space theory makes the counter-intuitive prediction that neurons often generate spikes not to cause behavior, but to prevent the effects that other neurons would have on behavior. What is missing is a direct way to test this theory in the brain.

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 three marmosets.

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.

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.

A software tool for at-home measurement of sensorimotor adaptation.

Sensorimotor adaptation is traditionally studied in well-controlled laboratory settings with specialized equipment. However, recent public health concerns such as the COVID-19 pandemic, as well as a desire to recruit a more diverse study population, have led the motor control community to consider at-home study designs. At-home motor control experiments are still rare because of the requirement to write software that can be easily used by anyone on any platform.

Effort cost of harvest affects decisions and movement vigor of marmosets during foraging.

Our decisions are guided by how we perceive the value of an option, but this evaluation also affects how we move to acquire that option. Why should economic variables such as reward and effort alter the vigor of our movements? In theory, both the option that we choose and the vigor with which we move contribute to a measure of fitness in which the objective is to maximize rewards minus efforts, divided by time. To explore this idea, we engaged marmosets in a foraging task in which on each trial they decided whether to work by making saccades to visual targets, thus accumulating food, or to harvest by licking what they had earned.

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.

Complex spikes perturb movements and reveal the sensorimotor map of Purkinje cells.

Computations that are performed by the cerebellar cortex are transmitted via simple spikes of Purkinje cells (P-cells) to downstream structures, but because P-cells are many synapses away from muscles, we do not know the relationship between modulation of simple spikes and control of behavior. Here, we recorded the spiking activities of hundreds of P-cells in the oculomotor vermis of marmosets during saccadic eye movements and found that following the presentation of a visual stimulus, the olivary input to a P-cell coarsely described the direction and amplitude of the visual stimulus as well as the upcoming movement. Occasionally, the complex spike occurred just before saccade onset, suppressing the P-cell's simple spikes and disrupting its output during that saccade.

Effort cost of reaching prompts vigor reduction in older adults.

Unlabelled: As people age, they move slower. Is age-related reduction in vigor a reflection of a reduced valuation of reward by the brain, or a consequence of increased effort costs by the muscles? Here, we quantified cost of movements objectively via the metabolic energy that young and old participants consumed during reaching and found that in order reach at a given speed, older adults expended more energy than the young. We next quantified how reward modulated movements in the same populations and found that like the young, older adults responded to increased reward by initiating their movements earlier.

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.

Complex spikes perturb movements, revealing the sensorimotor map of Purkinje cells.

The cerebellar cortex performs computations that are critical for control of our actions, and then transmits that information via simple spikes of Purkinje cells (P-cells) to downstream structures. However, because P-cells are many synapses away from muscles, we do not know how their output affects behavior. Furthermore, we do not know the level of abstraction, i.

Choice of Arm Use in Stroke Survivors is Largely Driven by the Energetic Cost of the Movement.

Background: The decision of which arm to use to achieve a goal depends on energetic costs and performance abilities of each arm. Following a stroke, there is a reduction in the use of the more-impaired arm. Is it because the energetic costs of the more-impaired arm are increased, or because its use dictates a lower chance of success?

Objective: We sought to elucidate the impact of energetic cost and task success on the arm choice of stroke survivors.

Effort cost of harvest affects decisions and movement vigor of marmosets during foraging.

Unlabelled: Our decisions are guided by how we perceive the value of an option, but this evaluation also affects how we move to acquire that option. Why should economic variables such as reward and effort alter the vigor of our movements? In theory, both the option that we choose and the vigor with which we move contribute to a measure of fitness in which the objective is to maximize rewards minus efforts, divided by time. To explore this idea, we engaged marmosets in a foraging task in which on each trial they decided whether to work by making saccades to visual targets, thus accumulating food, or to harvest by licking what they had earned.

Saccade vigor reflects the rise of decision variables during deliberation.

During deliberation, as we quietly consider our options, the neural activities representing the decision variables that reflect the goodness of each option rise in various regions of the cerebral cortex. If the options are depicted visually, we make saccades, focusing gaze on each option. Do the kinematics of these saccades reflect the state of the decision variables? To test this idea, we engaged human participants in a decision-making task in which they considered two effortful options that required walking across various distances and inclines.

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.

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.

Competition between parallel sensorimotor learning systems.

Sensorimotor learning is supported by at least two parallel systems: a strategic process that benefits from explicit knowledge and an implicit process that adapts subconsciously. How do these systems interact? Does one system's contributions suppress the other, or do they operate independently? Here, we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system's response siphons away resources that are needed for implicit adaptation, thus reducing its learning.

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 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.

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.

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).

An implicit memory of errors limits human sensorimotor adaptation.

During extended motor adaptation, learning appears to saturate despite persistence of residual errors. This adaptation limit is not fixed but varies with perturbation variance; when variance is high, residual errors become larger. These changes in total adaptation could relate to either implicit or explicit learning systems.

Précis of .

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.

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.

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.