Toward a neuroscience of natural behavior.

One of the most exciting new developments in systems neuroscience is the progress being made toward neurophysiological experiments that move beyond simplified laboratory settings and address the richness of natural behavior. This is enabled by technological advances such as wireless recording in freely moving animals, automated quantification of behavior, and new methods for analyzing large data sets. Beyond new empirical methods and data, however, there is also a need for new theories and concepts to interpret that data. Such theories need to address the particular challenges of natural behavior, which often differ significantly from the scenarios studied in traditional laboratory settings. Here, we discuss some strategies for developing such novel theories and concepts and some example hypotheses being proposed.

Vestibular contributions to online reach execution are processed via mechanisms with knowledge about limb biomechanics.

Studies of reach control with the body stationary have shown that proprioceptive and visual feedback signals contributing to rapid corrections during reaching are processed by neural circuits that incorporate knowledge about the physical properties of the limb (an internal model). However, among the most common spatial and mechanical perturbations to the limb are those caused by our body's own motion, suggesting that processing of vestibular signals for online reach control may reflect a similar level of sophistication. We investigated this hypothesis using galvanic vestibular stimulation (GVS) to selectively activate the vestibular sensors, simulating body rotation, as human subjects reached to remembered targets in different directions (forward, leftward, rightward). If vestibular signals contribute to purely kinematic/spatial corrections for body motion, GVS should evoke reach trajectory deviations of similar size in all directions. In contrast, biomechanical modeling predicts that if vestibular processing for online reach control takes into account knowledge of the physical properties of the limb and the forces applied on it by body motion, then GVS should evoke trajectory deviations that are significantly larger during forward and leftward reaches as compared with rightward reaches. When GVS was applied during reaching, the observed deviations were on average consistent with this prediction. In contrast, when GVS was instead applied before reaching, evoked deviations were similar across directions, as predicted for a purely spatial correction mechanism. These results suggest that vestibular signals, like proprioceptive and visual feedback, are processed for online reach control via sophisticated neural mechanisms that incorporate knowledge of limb biomechanics.NEW & NOTEWORTHY Studies examining proprioceptive and visual contributions to rapid corrections for externally applied mechanical and spatial perturbations during reaching have provided evidence for flexible processing of sensory feedback that accounts for musculoskeletal system dynamics. Notably, however, such perturbations commonly arise from our body's own motion. In line with this, we provide compelling evidence that, similar to proprioceptive and visual signals, vestibular signals are processed for online reach control via sophisticated mechanisms that incorporate knowledge of limb biomechanics.

Reaching decisions during ongoing movements.

Neurophysiological studies suggest that when decisions are made between concrete actions, the selection process involves a competition between potential action representations in the same sensorimotor structures involved in executing those actions. However, it is unclear how such models can explain situations, often encountered during natural behavior, in which we make decisions while were are already engaged in performing an action. Does the process of deliberation characterized in classical studies of decision-making proceed the same way when subjects are deciding while already acting? In the present study, human subjects continuously tracked a target moving in the horizontal plane and were occasionally presented with a new target to which they could freely choose to switch at any time, whereupon it became the new tracked target. We found that the probability of choosing to switch increased with decreasing distance to the new target and increasing size of the new target relative to the tracked target, as well as when the direction to the new target was aligned (either toward or opposite) to the current tracking direction. However, contrary to our expectations, subjects did not choose targets that minimized the energetic costs of execution, as calculated by a biomechanical model of the arm. When the constraints of continuous tracking were removed in variants of the task involving point-to-point movements, the expected preference for lower cost choices was seen. These results are discussed in the context of current theories of nested feedback control, internal models of forward dynamics, and high-dimensional neural spaces.NEW & NOTEWORTHY Current theories of decision-making primarily address how subjects make decisions before executing selected actions. However, in our daily lives we often make decisions while already performing some action (e.g., while playing a sport or navigating through a crowd). To gain insight into how current theories can be extended to such "decide-while-acting" scenarios, we examined human decisions during continuous manual tracking and found some intriguing departures from how decisions are made in classical "decide-then-act" paradigms.

Role of Rostral Fastigial Neurons in Encoding a Body-Centered Representation of Translation in Three Dimensions.

Many daily behaviors rely critically on estimates of our body motion. Such estimates must be computed by combining neck proprioceptive signals with vestibular signals that have been transformed from a head- to a body-centered reference frame. Recent studies showed that deep cerebellar neurons in the rostral fastigial nucleus (rFN) reflect these computations, but whether they explicitly encode estimates of body motion remains unclear. A key limitation in addressing this question is that, to date, cell tuning properties have only been characterized for a restricted set of motions across head-re-body orientations in the horizontal plane. Here we examined, for the first time, how 3D spatiotemporal tuning for translational motion varies with head-re-body orientation in both horizontal and vertical planes in the rFN of male macaques. While vestibular coding was profoundly influenced by head-re-body position in both planes, neurons typically reflected at most a partial transformation. However, their tuning shifts were not random but followed the specific spatial trajectories predicted for a 3D transformation. We show that these properties facilitate the linear decoding of fully body-centered motion representations in 3D with a broad range of temporal characteristics from small groups of 5-7 cells. These results demonstrate that the vestibular reference frame transformation required to compute body motion is indeed encoded by cerebellar neurons. We propose that maintaining partially transformed rFN responses with different spatiotemporal properties facilitates the creation of downstream body motion representations with a range of dynamic characteristics, consistent with the functional requirements for tasks such as postural control and reaching.SIGNIFICANCE STATEMENT Estimates of body motion are essential for many daily activities. Vestibular signals are important contributors to such estimates but must be transformed from a head- to a body-centered reference frame. Here, we provide the first direct demonstration that the cerebellum computes this transformation fully in 3D. We show that the output of these computations is reflected in the tuning properties of deep cerebellar rostral fastigial nucleus neurons in a specific distributed fashion that facilitates the efficient creation of body-centered translation estimates with a broad range of temporal properties (i.e., from acceleration to position). These findings support an important role for the rostral fastigial nucleus as a source of body translation estimates functionally relevant for behaviors ranging from postural control to perception.

The influence of proprioceptive state on learning control of reach dynamics.

The motor system shows a remarkable capacity to generalize learned behavior to new contexts while simultaneously permitting learning of multiple and sometimes conflicting skills. To examine the influence of proprioceptive state on this capacity, we compared the effectiveness of changes in workspace location and limb orientation (horizontal vs. parasagittal plane posture) in facilitating learning of opposing dynamic force-field perturbations. When opposing fields were encountered in similar workspace positions and limb orientations, subjects failed to learn the two tasks. In contrast, differences in initial limb proprioceptive state were sufficient for significant learning to take place. The extent of learning was similar when the two fields were encountered in different arm orientations in a similar workspace location as compared to when learning took place in spatially separated workspace locations, consistent with the generalization of learning mainly in intrinsic joint coordinates. In keeping with these observations, examination of how trial-to-trial adaptation generalized showed that generalization tended to be greater across similar limb postures. However, when the two fields were encountered in distinct spatial locations, the extent of generalization of adaptation to one field depended on the limb orientation in which the other field was encountered. These results suggest that three-dimensional proprioceptive limb state plays an important role in modulating generalization patterns so as to permit the best compromise between broad generalization and the simultaneous learning of conflicting skills.

Evidence for a reference frame transformation of vestibular signal contributions to voluntary reaching.

To contribute appropriately to voluntary reaching during body motion, vestibular signals must be transformed from a head-centered to a body-centered reference frame. We quantitatively investigated the evidence for this transformation during online reach execution by using galvanic vestibular stimulation (GVS) to simulate rotation about a head-fixed, roughly naso-occipital axis as human subjects made planar reaching movements to a remembered location with their head in different orientations. If vestibular signals that contribute to reach execution have been transformed from a head-centered to a body-centered reference frame, the same stimulation should be interpreted as body tilt with the head upright but as vertical-axis rotation with the head inclined forward. Consequently, GVS should perturb reach trajectories in a head-orientation-dependent way. Consistent with this prediction, GVS applied during reach execution induced trajectory deviations that were significantly larger with the head forward compared with upright. Only with the head forward were trajectories consistently deviated in opposite directions for rightward versus leftward simulated rotation, as appropriate to compensate for body vertical-axis rotation. These results demonstrate that vestibular signals contributing to online reach execution have indeed been transformed from a head-centered to a body-centered reference frame. Reach deviation amplitudes were comparable to those predicted for ideal compensation for body rotation using a biomechanical limb model. Finally, by comparing the effects of application of GVS during reach execution versus prior to reach onset we also provide evidence that spatially transformed vestibular signals contribute to at least partially distinct compensation mechanisms for body motion during reach planning versus execution.

Learning to move machines with the mind.

Brain-computer interfaces (BCIs) extract signals from neural activity to control remote devices ranging from computer cursors to limb-like robots. They show great potential to help patients with severe motor deficits perform everyday tasks without the constant assistance of caregivers. Understanding the neural mechanisms by which subjects use BCI systems could lead to improved designs and provide unique insights into normal motor control and skill acquisition. However, reports vary considerably about how much training is required to use a BCI system, the degree to which performance improves with practice and the underlying neural mechanisms. This review examines these diverse findings, their potential relationship with motor learning during overt arm movements, and other outstanding questions concerning the volitional control of BCI systems.

Multisensory integration: resolving sensory ambiguities to build novel representations.

Multisensory integration plays several important roles in the nervous system. One is to combine information from multiple complementary cues to improve stimulus detection and discrimination. Another is to resolve peripheral sensory ambiguities and create novel internal representations that do not exist at the level of individual sensors. Here we focus on how ambiguities inherent in vestibular, proprioceptive and visual signals are resolved to create behaviorally useful internal estimates of our self-motion. We review recent studies that have shed new light on the nature of these estimates and how multiple, but individually ambiguous, sensory signals are processed and combined to compute them. We emphasize the need to combine experiments with theoretical insights to understand the transformations that are being performed.

Internal models and neural computation in the vestibular system.

The vestibular system is vital for motor control and spatial self-motion perception. Afferents from the otolith organs and the semicircular canals converge with optokinetic, somatosensory and motor-related signals in the vestibular nuclei, which are reciprocally interconnected with the vestibulocerebellar cortex and deep cerebellar nuclei. Here, we review the properties of the many cell types in the vestibular nuclei, as well as some fundamental computations implemented within this brainstem-cerebellar circuitry. These include the sensorimotor transformations for reflex generation, the neural computations for inertial motion estimation, the distinction between active and passive head movements, as well as the integration of vestibular and proprioceptive information for body motion estimation. A common theme in the solution to such computational problems is the concept of internal models and their neural implementation. Recent studies have shed new insights into important organizational principles that closely resemble those proposed for other sensorimotor systems, where their neural basis has often been more difficult to identify. As such, the vestibular system provides an excellent model to explore common neural processing strategies relevant both for reflexive and for goal-directed, voluntary movement as well as perception.

Computation of egomotion in the macaque cerebellar vermis.

The nodulus and uvula (lobules X and IX of the vermis) receive mossy fibers from both vestibular afferents and vestibular nuclei neurons and are thought to play a role in spatial orientation. Their properties relate to a sensory ambiguity of the vestibular periphery: otolith afferents respond identically to translational (inertial) accelerations and changes in orientation relative to gravity. Based on theoretical and behavioral evidence, this sensory ambiguity is resolved using rotational cues from the semicircular canals. Recordings from the cerebellar cortex have identified a neural correlate of the brain's ability to resolve this ambiguity in the simple spike activities of nodulus/uvula Purkinje cells. This computation, which likely involves the cerebellar circuitry and its reciprocal connections with the vestibular nuclei, results from a remarkable convergence of spatially- and temporally-aligned otolith-driven and semicircular canal-driven signals. Such convergence requires a spatio-temporal transformation of head-centered canal-driven signals into an estimate of head reorientation relative to gravity. This signal must then be subtracted from the otolith-driven estimate of net acceleration to compute inertial motion. At present, Purkinje cells in the nodulus/uvula appear to encode the output of this computation. However, how the required spatio-temporal matching takes place within the cerebellar circuitry and what role complex spikes play in spatial orientation and disorientation remains unknown. In addition, the role of visual cues in driving and/or modifying simple and complex spike activity, a process potentially critical for long-term adaptation, constitutes another important direction for future studies.

Conversion of a highly selective sigma-1 receptor-ligand to sigma-2 receptor preferring ligands with anticocaine activity.

Cocaine's toxicity can be mitigated by blocking its interaction with sigma-1 receptors. The involvement of sigma-2 receptors remains unclear. To investigate their potential role, we have designed compounds through a convergent synthesis utilizing a highly selective sigma-1 ligand and elements of a selective sigma-2 ligand. Among the synthesized compounds was produced a subnanomolar sigma-2 ligand with an 11-fold preference over sigma-1 receptors. These compounds may be useful in developing effective pharmacotherapies for cocaine toxicity.

Coordinate transformations and sensory integration in the detection of spatial orientation and self-motion: from models to experiments.

An accurate internal representation of our current motion and orientation in space is critical to navigate in the world and execute appropriate action. The force of gravity provides an allocentric frame of reference that defines one's motion relative to inertial (i.e., world-centered) space. However, movement in this environment also introduces particular motion detection problems as our internal linear accelerometers, the otolith organs, respond identically to either translational motion or changes in head orientation relative to gravity. According to physical principles, there exists an ideal solution to the problem of distinguishing between the two as long as the brain also has access to accurate internal estimates of angular velocity. Here, we illustrate how a nonlinear integrative neural network that receives sensory signals from the vestibular organs could be used to implement the required computations for inertial motion detection. The model predicts several distinct cell populations that are comparable with experimentally identified cell types and accounts for a number of previously unexplained characteristics of their responses. A key model prediction is the existence of cell populations that transform head-referenced rotational signals from the semicircular canals into spatially referenced estimates of head reorientation relative to gravity. This chapter provides an overview of how addressing the problem of inertial motion estimation from a computational standpoint has contributed to identifying the actual neuronal populations responsible for solving the tilt-translation ambiguity and has facilitated the interpretation of neural response properties.

Purkinje cells in posterior cerebellar vermis encode motion in an inertial reference frame.

The ability to orient and navigate through the terrestrial environment represents a computational challenge common to all vertebrates. It arises because motion sensors in the inner ear, the otolith organs, and the semicircular canals transduce self-motion in an egocentric reference frame. As a result, vestibular afferent information reaching the brain is inappropriate for coding our own motion and orientation relative to the outside world. Here we show that cerebellar cortical neuron activity in vermal lobules 9 and 10 reflects the critical computations of transforming head-centered vestibular afferent information into earth-referenced self-motion and spatial orientation signals. Unlike vestibular and deep cerebellar nuclei neurons, where a mixture of responses was observed, Purkinje cells represent a homogeneous population that encodes inertial motion. They carry the earth-horizontal component of a spatially transformed and temporally integrated rotation signal from the semicircular canals, which is critical for computing head attitude, thus isolating inertial linear accelerations during navigation.

A reevaluation of the inverse dynamic model for eye movements.

To construct an appropriate motor command from signals that provide a representation of desired action, the nervous system must take into account the dynamic characteristics of the motor plant to be controlled. In the oculomotor system, signals specifying desired eye velocity are thought to be transformed into motor commands by an inverse dynamic model of the eye plant that is shared for all types of eye movements and implemented by a weighted combination of eye velocity and position signals. Neurons in the prepositus hypoglossi and adjacent medial vestibular nuclei (PH-BT neurons) were traditionally thought to encode the "eye position" component of this inverse model. However, not only are PH-BT responses inconsistent with this theoretical role, but compensatory eye movement responses to translation do not show evidence for processing by a common inverse dynamic model. Prompted by these discrepancies between theoretical notions and experimental observations, we reevaluated these concepts using multiple-frequency rotational and translational head movements. Compatible with the notion of a common inverse model, we show that PH-BT responses are unique among all premotor cell types in bearing a consistent relationship to the motor output during eye movements driven by different sensory stimuli. However, because their responses are dynamically identical to those of motoneurons, PH-BT neurons do not simply represent an internal component of the inverse model, but rather its output. They encode and distribute an estimate of the motor command, a signal critical for accurate motor execution and learning.

Sensory convergence solves a motion ambiguity problem.

Our inner ear is equipped with a set of linear accelerometers, the otolith organs, that sense the inertial accelerations experienced during self-motion. However, as Einstein pointed out nearly a century ago, this signal would by itself be insufficient to detect our real movement, because gravity, another form of linear acceleration, and self-motion are sensed identically by otolith afferents. To deal with this ambiguity, it was proposed that neural populations in the pons and midline cerebellum compute an independent, internal estimate of gravity using signals arising from the vestibular rotation sensors, the semicircular canals. This hypothesis, regarding a causal relationship between firing rates and postulated sensory contributions to inertial motion estimation, has been directly tested here by recording neural activities before and after inactivation of the semicircular canals. We show that, unlike cells in normal animals, the gravity component of neural responses was nearly absent in canal-inactivated animals. We conclude that, through integration of temporally matched, multimodal information, neurons derive the mathematical signals predicted by the equations describing the physics of the outside world.

Sensory vestibular contributions to constructing internal models of self-motion.

The ability to navigate in the world and execute appropriate behavioral and motor responses depends critically on our capacity to construct an accurate internal representation of our current motion and orientation in space. Vestibular sensory signals are among those that may make an essential contribution to the construction of such 'internal models'. Movement in a gravitational environment represents a situation where the construction of internal models becomes particularly important because the otolith organs, like any linear accelerometer, sense inertial and gravitational accelerations equivalently. Otolith afferents thus provide inherently ambiguous motion information, as they respond identically to translation and head reorientation relative to gravity. Resolution of this ambiguity requires the nonlinear integration of linear acceleration and angular velocity cues, as predicted by the physical equations of motion. Here, we summarize evidence that during translations and tilts from upright the firing rates of brainstem and cerebellar neurons encode a combination of dynamically processed semicircular canal and otolith signals appropriate to construct an internal model representation of the computations required for inertial motion detection.

Pursuit--vestibular interactions in brain stem neurons during rotation and translation.

Under natural conditions, the vestibular and pursuit systems work synergistically to stabilize the visual scene during movement. How translational vestibular signals [translational vestibuloocular reflex (TVOR)] are processed in the premotor pathways for slow eye movements continues to remain a challenging question. To further our understanding of how premotor neurons contribute to this processing, we recorded neural activities from the prepositus and rostral medial vestibular nuclei in macaque monkeys. Vestibular neurons were tested during 0.5-Hz rotation and lateral translation (both with gaze stable and during VOR cancellation tasks), as well as during smooth pursuit eye movements. Data were collected at two different viewing distances, 80 and 20 cm. Based on their responses to rotation and pursuit, eye-movement-sensitive neurons were classified into position-vestibular-pause (PVP) neurons, eye-head (EH) neurons, and burst-tonic (BT) cells. We found that approximately half of the type II PVP and EH neurons with ipsilateral eye movement preference were modulated during TVOR cancellation. In contrast, few of the EH and none of the type I PVP cells with contralateral eye movement preference modulated during translation in the absence of eye movements; nor did any of the BT neurons change their firing rates during TVOR cancellation. Of the type II PVP and EH neurons that modulated during TVOR cancellation, cell firing rates increased for either ipsilateral or contralateral displacement, a property that could not be predicted on the basis of their rotational or pursuit responses. In contrast, under stable gaze conditions, all neuron types, including EH cells, were modulated during translation according to their ipsilateral/contralateral preference for pursuit eye movements. Differences in translational response sensitivities for far versus near targets were seen only in type II PVP and EH cells. There was no effect of viewing distance on response phase for any cell type. When expressed relative to motor output, neural sensitivities during translation (although not during rotation) and pursuit were equivalent, particularly for the 20-cm viewing distance. These results suggest that neural activities during the TVOR were more motorlike compared with cell responses during the rotational vestibuloocular reflex (RVOR). We also found that neural responses under stable gaze conditions could not always be predicted by a linear vectorial addition of the cell activities during pursuit and VOR cancellation. The departure from linearity was more pronounced for the TVOR under near-viewing conditions. These results extend previous observations for the neural processing of otolith signals within the premotor circuitry that generates the RVOR and smooth pursuit eye movements.

Neurons compute internal models of the physical laws of motion.

A critical step in self-motion perception and spatial awareness is the integration of motion cues from multiple sensory organs that individually do not provide an accurate representation of the physical world. One of the best-studied sensory ambiguities is found in visual processing, and arises because of the inherent uncertainty in detecting the motion direction of an untextured contour moving within a small aperture. A similar sensory ambiguity arises in identifying the actual motion associated with linear accelerations sensed by the otolith organs in the inner ear. These internal linear accelerometers respond identically during translational motion (for example, running forward) and gravitational accelerations experienced as we reorient the head relative to gravity (that is, head tilt). Using new stimulus combinations, we identify here cerebellar and brainstem motion-sensitive neurons that compute a solution to the inertial motion detection problem. We show that the firing rates of these populations of neurons reflect the computations necessary to construct an internal model representation of the physical equations of motion.