Only coherent spiking in posterior parietal cortex coordinates looking and reaching

Rapid eye and hand responses in an interception task are differentially modulated by context-dependent predictability

When catching a falling ball or avoiding a collision with traffic, humans can quickly generate eye and limb responses to unpredictable changes in their environment. Mechanisms of limb and oculomotor control when responding to sudden changes in the environment have mostly been investigated independently. Here, we investigated eye-hand coordination in a rapid interception task where human participants used a virtual paddle to intercept a moving target. The target moved vertically down a computer screen and could suddenly jump to the left or right. In high-certainty blocks, the target always jumped; in low-certainty blocks, the target only jumped in a portion of the trials. Further, we manipulated response urgency by varying the time of target jumps, with early jumps requiring less urgent responses and late jumps requiring more urgent responses. Our results highlight differential effects of certainty and urgency on eye-hand coordination. Participants initiated both eye and hand responses earlier for high-certainty compared with low-certainty blocks. Hand reaction times decreased and response vigor increased with increasing urgency levels. However, eye reaction times were lowest for medium-urgency levels and eye vigor was unaffected by urgency. Across all trials, we found a weak positive correlation between eye and hand responses. Taken together, these results suggest that the limb and oculomotor systems use similar early sensorimotor processing; however, rapid responses are modulated differentially to attain system-specific sensorimotor goals.

Functional organization of posterior parietal cortex circuitry based on inferred information flow

Many studies infer the role of neurons by asking what information can be decoded from their activity or by observing the consequences of perturbing their activity. An alternative approach is to consider information flow between neurons. We applied this approach to the parietal reach region (PRR) and the lateral intraparietal area (LIP) in posterior parietal cortex. Two complementary methods imply that across a range of reaching tasks, information flows primarily from PRR to LIP. This indicates that during a coordinated reach task, LIP has minimal influence on PRR and rules out the idea that LIP forms a general purpose spatial processing hub for action and cognition. Instead, we conclude that PRR and LIP operate in parallel to plan arm and eye movements, respectively, with asymmetric interactions that likely support eye-hand coordination. Similar methods can be applied to other areas to infer their functional relationships based on inferred information flow.

Eye-hand coordination all the way: from discrete to continuous hand movements

The differentiation between continuous and discrete actions is key for behavioral neuroscience. Although many studies have characterized eye-hand coordination during discrete (e.g., reaching) and continuous (e.g., pursuit tracking) actions, all these studies were conducted separately, using different setups and participants. In addition, how eye-hand coordination might operate at the frontier between discrete and continuous movements remains unexplored. Here we filled these gaps by means of a task that could elicit different movement dynamics. Twenty-eight participants were asked to simultaneously track with their eyes and a joystick a visual target that followed an unpredictable trajectory and whose position was updated at different rates (from 1.5 to 240 Hz). This procedure allowed us to examine actions ranging from discrete point-to-point movements (low refresh rate) to continuous pursuit (high refresh rate). For comparison, we also tested a manual tracking condition with the eyes fixed and a pure eye tracking condition (hand fixed). The results showed an abrupt transition between discrete and continuous hand movements around 3 Hz contrasting with a smooth trade-off between fixations and smooth pursuit. Nevertheless, hand and eye tracking accuracy remained strongly correlated, with each of these depending on whether the other effector was recruited. Moreover, gaze-cursor distance and lag were smaller when eye and hand performed the task conjointly than separately. Altogether, despite some dissimilarities in eye and hand dynamics when transitioning between discrete and continuous movements, our results emphasize that eye-hand coordination continues to smoothly operate and support the notion of synergies across eye movement types.NEW & NOTEWORTHY The differentiation between continuous and discrete actions is key for behavioral neuroscience. By using a visuomotor task in which we manipulate the target refresh rate to trigger different movement dynamics, we explored eye-hand coordination all the way from discrete to continuous actions. Despite abrupt changes in hand dynamics, eye-hand coordination continues to operate via a gradual trade-off between fixations and smooth pursuit, an observation confirming the notion of synergies across eye movement types.

Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity

Objective.Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics and enable better decoding of behavior through multimodal fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially for real-time learning applications such as brain-machine interfaces (BMIs). However, efficient learning remains elusive for multimodal spike-field data due to their heterogeneous discrete-continuous distributions and different timescales.Approach.Here, we develop a multiscale subspace identification (multiscale SID) algorithm that enables computationally efficient learning for modeling and dimensionality reduction for multimodal discrete-continuous spike-field data. We describe the spike-field activity as combined Poisson and Gaussian observations, for which we derive a new analytical SID method. Importantly, we also introduce a novel constrained optimization approach to learn valid noise statistics, which is critical for multimodal statistical inference of the latent state, neural activity, and behavior. We validate the method using numerical simulations and with spiking and local field potential population activity recorded during a naturalistic reach and grasp behavior.Main results.We find that multiscale SID accurately learned dynamical models of spike-field signals and extracted low-dimensional dynamics from these multimodal signals. Further, it fused multimodal information, thus better identifying the dynamical modes and predicting behavior compared to using a single modality. Finally, compared to existing multiscale expectation-maximization learning for Poisson-Gaussian observations, multiscale SID had a much lower training time while being better in identifying the dynamical modes and having a better or similar accuracy in predicting neural activity and behavior.Significance.Overall, multiscale SID is an accurate learning method that is particularly beneficial when efficient learning is of interest, such as for online adaptive BMIs to track non-stationary dynamics or for reducing offline training time in neuroscience investigations.

Beta oscillations in vision: a (preconscious) neural mechanism for the dorsal visual stream?

Neural oscillations in alpha (8-12 Hz) and beta (13-30 Hz) frequency bands are thought to reflect feedback/reentrant loops and large-scale cortical interactions. In the last decades a main effort has been made in linking perception with alpha-band oscillations, with converging evidence showing that alpha oscillations have a key role in the temporal and featural binding of visual input, configuring the alpha rhythm a key determinant of conscious visual experience. Less attention has been historically dedicated to link beta oscillations and visual processing. Nonetheless, increasing studies report that task conditions that require to segregate/integrate stimuli in space, to disentangle local/global shapes, to spatially reorganize visual inputs, and to achieve motion perception or form-motion integration, rely on the activity of beta oscillations, with a main hub in parietal areas. In the present review, we summarize the evidence linking oscillations within the beta band and visual perception. We propose that beta oscillations represent a neural code that supports the functionality of the magnocellular-dorsal (M-D) visual pathway, serving as a fast primary neural code to exert top-down influences on the slower parvocellular-ventral visual pathway activity. Such M-D-related beta activity is proposed to act mainly pre-consciously, providing the spatial coordinates of vision and guiding the conscious extraction of objects identity that are achieved with slower alpha rhythms in ventral areas. Finally, within this new theoretical framework, we discuss the potential role of M-D-related beta oscillations in visuo-spatial attention, oculo-motor behavior and reading (dis)abilities.

Top-down control of exogenous attentional selection is mediated by beta coherence in prefrontal cortex

Salience-driven exogenous and goal-driven endogenous attentional selection are two distinct forms of attention that guide selection of task-irrelevant and task-relevant targets in primates. Top-down attentional control mechanisms enable selection of the task-relevant target by limiting the influence of sensory information. Although the lateral prefrontal cortex (LPFC) is known to mediate top-down control, the neuronal mechanisms of top-down control of attentional selection are poorly understood. Here, we trained two rhesus monkeys on a two-target, free-choice luminance-reward selection task. We demonstrate that visual-movement (VM) neurons and nonvisual neurons or movement neurons encode exogenous and endogenous selection. We then show that coherent beta activity selectively modulates mechanisms of exogenous selection specifically during conflict and consequently may support top-down control. These results reveal the VM-neuron-specific network mechanisms of attentional selection and suggest a functional role for beta-frequency coherent neural dynamics in the modulation of sensory communication channels for the top-down control of attentional selection.

Transient Oscillations of Neural Firing Rate Associated With Routing of Evidence in a Perceptual Decision

To form a perceptual decision, the brain must acquire samples of evidence from the environment and incorporate them in computations that mediate choice behavior. While much is known about the neural circuits that process sensory information and those that form decisions, less is known about the mechanisms that establish the functional linkage between them. We trained monkeys of both sexes to make difficult decisions about the net direction of visual motion under conditions that required trial-by-trial control of functional connectivity. In one condition, the motion appeared at different locations on different trials. In the other, two motion patches appeared, only one of which was informative. Neurons in the parietal cortex produced brief oscillations in their firing rate at the time routing was established: upon onset of the motion display when its location was unpredictable across trials, and upon onset of an attention cue that indicated in which of two locations an informative patch of dots would appear. The oscillation was absent when the stimulus location was fixed across trials. We interpret the oscillation as a manifestation of the mechanism that establishes the source and destination of flexibly routed information, but not the transmission of the information per se Significance Statement It has often been suggested that oscillations in neural activity might serve a role in routing information appropriately. We observe an oscillation in neural firing rate in the lateral intraparietal area consistent with such a role. The oscillations are transient. They coincide with the establishment of routing, but they do not appear to play a role in the transmission (or conveyance) of the routed information itself.

Putative cell-type-specific multiregional mode in posterior parietal cortex during coordinated visual behavior

In the reach and saccade regions of the posterior parietal cortex (PPC), multiregional communication depends on the timing of neuronal activity with respect to beta-frequency (10-30 Hz) local field potential (LFP) activity, termed dual coherence. Neural coherence is believed to reflect neural excitability, whereby spiking tends to occur at a particular phase of LFP activity, but the mechanisms of multiregional dual coherence remain unknown. Here, we investigate dual coherence in the PPC of non-human primates performing eye-hand movements. We computationally model dual coherence in terms of multiregional neural excitability and show that one latent component, a multiregional mode, reflects shared excitability across distributed PPC populations. Analyzing the power in the multiregional mode with respect to different putative cell types reveals significant modulations with the spiking of putative pyramidal neurons and not inhibitory interneurons. These results suggest a specific role for pyramidal neurons in dual coherence supporting multiregional communication in PPC.

Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity

Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics and enable better decoding of behavior through multimodal fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially for real-time learning applications such as brain-machine interfaces (BMIs). However, efficient learning remains elusive for multimodal spike-field data due to their heterogeneous discrete-continuous distributions and different timescales. Here, we develop a multiscale subspace identification (multiscale SID) algorithm that enables computationally efficient modeling and dimensionality reduction for multimodal discrete-continuous spike-field data. We describe the spike-field activity as combined Poisson and Gaussian observations, for which we derive a new analytical subspace identification method. Importantly, we also introduce a novel constrained optimization approach to learn valid noise statistics, which is critical for multimodal statistical inference of the latent state, neural activity, and behavior. We validate the method using numerical simulations and spike-LFP population activity recorded during a naturalistic reach and grasp behavior. We find that multiscale SID accurately learned dynamical models of spike-field signals and extracted low-dimensional dynamics from these multimodal signals. Further, it fused multimodal information, thus better identifying the dynamical modes and predicting behavior compared to using a single modality. Finally, compared to existing multiscale expectation-maximization learning for Poisson-Gaussian observations, multiscale SID had a much lower computational cost while being better in identifying the dynamical modes and having a better or similar accuracy in predicting neural activity. Overall, multiscale SID is an accurate learning method that is particularly beneficial when efficient learning is of interest.

Top-down control of exogenous attentional selection is mediated by beta coherence in prefrontal cortex

Salience-driven exogenous and goal-driven endogenous attentional selection are two distinct forms of attention that guide selection of task-irrelevant and task-relevant targets in primates. During conflict i.e, when salience and goal each favor the selection of different targets, endogenous selection of the task-relevant target relies on top-down control. Top-down attentional control mechanisms enable selection of the task-relevant target by limiting the influence of sensory information. Although the lateral prefrontal cortex (LPFC) is known to mediate top-down control, the neuronal mechanisms of top-down control of attentional selection are poorly understood. Here, using a two-target free-choice luminance-reward selection task, we demonstrate that visual-movement neurons and not visual neurons or movement neurons encode exogenous and endogenous selection. We then show that coherent-beta activity selectively modulates mechanisms of exogenous selection specifically during conflict and consequently may support top-down control. These results reveal the VM-neuron-specific network mechanisms of attentional selection and suggest a functional role for beta-frequency coherent neural dynamics in the modulation of sensory communication channels for the top-down control of attentional selection.

Modulation of inhibitory communication coordinates looking and reaching

Looking and reaching are controlled by different brain regions and are coordinated during natural behaviour1. Understanding how flexible, natural behaviours such as coordinated looking and reaching are controlled depends on understanding how neurons in different regions of the brain communicate2. Neural coherence in a gamma-frequency (40-90 Hz) band has been implicated in excitatory multiregional communication3. Inhibitory control mechanisms are also required to flexibly control behaviour4, but little is known about how neurons in one region transiently suppress individual neurons in another to support behaviour. How neuronal firing in a sender region transiently suppresses firing in a receiver region remains poorly understood. Here we study inhibitory communication during a flexible, natural behaviour, termed gaze anchoring, in which saccades are transiently inhibited by coordinated reaches. During gaze anchoring, we found that neurons in the reach region of the posterior parietal cortex can inhibit neuronal firing in the parietal saccade region to suppress eye movements and improve reach accuracy. Suppression is transient, only present around the coordinated reach, and greatest when reach neurons fire spikes with respect to beta-frequency (15-25 Hz) activity, not gamma-frequency activity. Our work provides evidence in the activity of single neurons for a novel mechanism of inhibitory communication in which beta-frequency neural coherence transiently inhibits multiregional communication to flexibly coordinate natural behaviour.

Lower resting brain entropy is associated with stronger task activation and deactivation

Brain entropy (BEN) calculated from resting state fMRI has been the subject of increasing research interest in recent years. Previous studies have shown the correlations between rest BEN and neurocognition and task performance, but how this relates to task-evoked brain activations and deactivations remains unknown. The purpose of this study is to address this open question using large data (n = 862). Voxel wise correlations were calculated between rest BEN and task activations/deactivations of five different tasks. For most of the assessed tasks, lower rest BEN was found to be associated with stronger activations (negative correlations) and stronger deactivations (positive correlations) only in brain regions activated or deactivated by the tasks. Higher workload evoked spatially more extended negative correlations between rest BEN and task activations. These results not only confirm that resting brain activity can predict brain activity during task performance but also for the first time show that resting brain activity may facilitate both task activations and deactivations. In addition, the results provide a clue to understanding the individual differences of task performance and brain activations.

Marmosets: a promising model for probing the neural mechanisms underlying complex visual networks such as the frontal-parietal network

The technology, methodology and models used by visual neuroscientists have provided great insights into the structure and function of individual brain areas. However, complex cognitive functions arise in the brain due to networks comprising multiple interacting cortical areas that are wired together with precise anatomical connections. A prime example of this phenomenon is the frontal–parietal network and two key regions within it: the frontal eye fields (FEF) and lateral intraparietal area (area LIP). Activity in these cortical areas has independently been tied to oculomotor control, motor preparation, visual attention and decision-making. Strong, bidirectional anatomical connections have also been traced between FEF and area LIP, suggesting that the aforementioned visual functions depend on these inter-area interactions. However, advancements in our knowledge about the interactions between area LIP and FEF are limited with the main animal model, the rhesus macaque, because these key regions are buried in the sulci of the brain. In this review, we propose that the common marmoset is the ideal model for investigating how anatomical connections give rise to functionally-complex cognitive visual behaviours, such as those modulated by the frontal–parietal network, because of the homology of their cortical networks with humans and macaques, amenability to transgenic technology, and rich behavioural repertoire. Furthermore, the lissencephalic structure of the marmoset brain enables application of powerful techniques, such as array-based electrophysiology and optogenetics, which are critical to bridge the gaps in our knowledge about structure and function in the brain.

The neurocognitive correlates of brain entropy estimated by resting state fMRI

Resting state brain activity consumes most of brain energy, likely creating and maintaining a reserve of general brain functionality. The latent reserve if it exists may be reflected by the profound long-range fluctuations of resting brain activity. The long-range temporal coherence (LRTC) can be characterized by resting state fMRI (rsfMRI)-based brain entropy (BEN) mapping. While BEN mapping results have shown sensitivity to neuromodulations or disease conditions, the underlying neuromechanisms especially the associations of BEN or LRTC to neurocognition still remain unclear. To address this standing question and to test a novel hypothesis that resting BEN reflects a latent functional reserve through the link to general functionality, we mapped resting BEN of 862 young adults and comprehensively examined its associations to neurocognitions using data from the Human Connectome Project (HCP). Our results unanimously highlighted two brain circuits: the default mode network (DMN) and executive control network (ECN) through their negative associations of BEN to general functionality, which is independent of age and sex. While BEN in DMN/ECN increases with age, it decreases with education years. These results demonstrated the neurocognitive correlates of resting BEN in DMN/ECN and suggest resting BEN in DMN/ECN as a potential proxy of the latent functional reserve that facilitates general brain functionality and may be enhanced by education.

Computational Mechanisms Mediating Inhibitory Control of Coordinated Eye-Hand Movements

Significant progress has been made in understanding the computational and neural mechanisms that mediate eye and hand movements made in isolation. However, less is known about the mechanisms that control these movements when they are coordinated. Here, we outline our computational approaches using accumulation-to-threshold and race-to-threshold models to elucidate the mechanisms that initiate and inhibit these movements. We suggest that, depending on the behavioral context, the initiation and inhibition of coordinated eye-hand movements can operate in two modes-coupled and decoupled. The coupled mode operates when the task context requires a tight coupling between the effectors; a common command initiates both effectors, and a unitary inhibitory process is responsible for stopping them. Conversely, the decoupled mode operates when the task context demands weaker coupling between the effectors; separate commands initiate the eye and hand, and separate inhibitory processes are responsible for stopping them. We hypothesize that the higher-order control processes assess the behavioral context and choose the most appropriate mode. This computational mechanism can explain the heterogeneous results observed across many studies that have investigated the control of coordinated eye-hand movements and may also serve as a general framework to understand the control of complex multi-effector movements.

Local field potentials in the parietal reach region reveal mechanisms of bimanual coordination

Primates use their arms in complex ways that frequently require coordination between the two arms. Yet the planning of bimanual movements has not been well-studied. We recorded spikes and local field potentials (LFP) from the parietal reach region (PRR) in both hemispheres simultaneously while monkeys planned and executed unimanual and bimanual reaches. From analyses of interhemispheric LFP-LFP and spike-LFP coherence, we found that task-specific information is shared across hemispheres in a frequency-specific manner. This shared information could arise from common input or from direct communication. The population average unit activity in PRR, representing PRR output, encodes only planned contralateral arm movements while beta-band LFP power, a putative PRR input, reflects the pattern of planned bimanual movement. A parsimonious interpretation of these data is that PRR integrates information about the movement of the left and right limbs, perhaps in service of bimanual coordination.

Dynamic Suppression of Average Facial Structure Shapes Neural Tuning in Three Macaque Face Patches

The visual perception of identity in humans and other primates is thought to draw upon cortical areas specialized for the analysis of facial structure. A prominent theory of face recognition holds that the brain computes and stores average facial structure, which it then uses to efficiently determine individual identity, though the neural mechanisms underlying this process are controversial. Here, we demonstrate that the dynamic suppression of average facial structure plays a prominent role in the responses of neurons in three fMRI-defined face patches of the macaque. Using photorealistic face stimuli that systematically varied in identity level according to a psychophysically based face space, we found that single units in the AF, AM, and ML face patches exhibited robust tuning around average facial structure. This tuning emerged after the initial excitatory response to the face and was expressed as the selective suppression of sustained responses to low-identity faces. The coincidence of this suppression with increased spike timing synchrony across the population suggests a mechanism of active inhibition underlying this effect. Control experiments confirmed that the diminished responses to low-identity faces were not due to short-term adaptation processes. We propose that the brain's neural suppression of average facial structure facilitates recognition by promoting the extraction of distinctive facial characteristics and suppressing redundant or irrelevant responses across the population.

Functional Use of Eye Movements for an Acting System

Movements of the eyes assist vision and support hand and body movements in a cooperative way. Despite their strong functional coupling, different types of movements are usually studied independently. We integrate knowledge from behavioral, neurophysiological, and clinical studies on how eye movements are coordinated with goal-directed hand movements and how they facilitate motor learning. Understanding the coordinated control of eye and hand movements can provide important insights into brain functions that are essential for performing or learning daily tasks in health and disease. This knowledge can also inform applications such as robotic manipulation and clinical rehabilitation.

Multiregional communication and the channel modulation hypothesis

Multiregional communication is important to understanding the brain mechanisms supporting complex behaviors. Work in animals and human subjects shows that multiregional communication plays significant roles in cognitive function and is associated with neurological and neuropsychiatric disorders of brain function. Recent experimental advances enable empirical tests of the mechanisms of multiregional communication. Recent mechanistic insights into brain network function also suggest new therapies to treat disordered brain networks. Here, we discuss how to use the concept of communication channel modulation can help define and constrain what we mean by multiregional communication. We discuss behavioral and neurophysiological evidence for multiregional channels modulation. We then consider the role of causal manipulations and their implications for developing novel therapies based on multiregional communication.

Brain Entropy Mapping in Healthy Aging and Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease, for which aging remains the major risk factor. Aging is under a consistent pressure of increasing brain entropy (BEN) due to the progressive brain deteriorations. Noticeably, the brain constantly consumes a large amount of energy to maintain its functional integrity, likely creating or maintaining a big "reserve" to counteract the high entropy. Malfunctions of this latent reserve may indicate a critical point of disease progression. The purpose of this study was to characterize BEN in aging and AD and to test an inverse-U-shape BEN model: BEN increases with age and AD pathology in normal aging but decreases in the AD continuum. BEN was measured with resting state fMRI and compared across aging and the AD continuum. Associations of BEN with age, education, clinical symptoms, and pathology were examined by multiple regression. The analysis results highlighted resting BEN in the default mode network, medial temporal lobe, and prefrontal cortex and showed that: (1) BEN increased with age and pathological deposition in normal aging but decreased with age and pathological deposition in the AD continuum; (2) AD showed catastrophic BEN reduction, which was related to more severe cognitive impairment and daily function disability; and (3) BEN decreased with education years in normal aging, but not in the AD continuum. BEN evolution follows an inverse-U trajectory when AD progresses from normal aging to AD dementia. Education is beneficial for suppressing the entropy increase potency in normal aging.

Phase of firing coding of learning variables across the fronto-striatal network during feature-based learning

The prefrontal cortex and striatum form a recurrent network whose spiking activity encodes multiple types of learning-relevant information. This spike-encoded information is evident in average firing rates, but finer temporal coding might allow multiplexing and enhanced readout across the connected network. We tested this hypothesis in the fronto-striatal network of nonhuman primates during reversal learning of feature values. We found that populations of neurons encoding choice outcomes, outcome prediction errors, and outcome history in their firing rates also carry significant information in their phase-of-firing at a 10–25 Hz band-limited beta frequency at which they synchronize across lateral prefrontal cortex, anterior cingulate cortex and anterior striatum when outcomes were processed. The phase-of-firing code exceeds information that can be obtained from firing rates alone and is evident for inter-areal connections between anterior cingulate cortex, lateral prefrontal cortex and anterior striatum. For the majority of connections, the phase-of-firing information gain is maximal at phases of the beta cycle that were offset from the preferred spiking phase of neurons. Taken together, these findings document enhanced information of three important learning variables at specific phases of firing in the beta cycle at an inter-areally shared beta oscillation frequency during goal-directed behavior.

The average spiking frequency in the fronto-striatal network encodes multiple types of learning-relevant information. Here, the authors show that populations of neurons in non-human primates also carry significant information in their phase-of-firing when learning-relevant outcomes are processed.

Molecular layer interneurons in the cerebellum encode for valence in associative learning

The cerebellum plays a crucial role in sensorimotor and associative learning. However, the contribution of molecular layer interneurons (MLIs) to these processes is not well understood. We used two-photon microscopy to study the role of ensembles of cerebellar MLIs in a go-no go task where mice obtain a sugar water reward if they lick a spout in the presence of the rewarded odorant and avoid a timeout when they refrain from licking for the unrewarded odorant. In naive animals the MLI responses did not differ between the odorants. With learning, the rewarded odorant elicited a large increase in MLI calcium responses, and the identity of the odorant could be decoded from the differential response. Importantly, MLIs switched odorant responses when the valence of the stimuli was reversed. Finally, mice took a longer time to refrain from licking in the presence of the unrewarded odorant and had difficulty becoming proficient when MLIs were inhibited by chemogenetic intervention. Our findings support a role for MLIs in learning valence in the cerebellum.

Timing of phase-amplitude coupling is essential for neuronal and functional maturation of audiovisual integration in adolescents

OBJECTIVE

The ability to integrate audiovisual information matures late in adolescents, but its neuronal mechanism is still unknown. Recent studies showed that phase-amplitude coupling (PAC) of neuronal oscillations, which is defined as the modulation of high-frequency amplitude by low-frequency phase, is associated with audiovisual integration in adults. Thus, we investigated how PAC develops in adolescents and whether it is related to the functional maturation of audiovisual integration. In particular, we focused on the timing of PAC (or the coupling phase), which is defined as the low-frequency phase with maximum high-frequency amplitude.

METHODS

Using magnetoencephalography (MEG) on 15 adults and 14 adolescents while they performed an audiovisual speech integration task, we examined PAC in association cortexes with a trial-by-trial analysis.

RESULTS

Whereas delta-beta coupling was consistently observed in both adults and adolescents, we found that the timing of delta-beta PAC was delayed by 20-40 milliseconds in adolescents compared with adults. In addition, a logistic regression analysis revealed that the task performance improves as the timing of delta-beta PAC in the right temporal pole (TP) got closer to the trough position (180 degrees).

CONCLUSION

These results suggest that the timing of PAC is essential for binding audiovisual information and underlies the developmental process in adolescents.

A Brief History of the Encoding of Hand Position by the Cerebral Cortex: Implications for Motor Control and Cognition

Encoding hand position by the cerebral cortex is essential not only for the neural representation of the body image but also for different actions based on eye-hand coordination. These include reaching for visual objects as well as complex movement sequences, such as tea-making, tool use, and object construction, among many others. All these functions depend on a continuous refreshing of the hand position representation, relying on both predictive signaling and afferent information. The hand position influence on neural activity in the parietofrontal system, together with eye position signals, are the basic elements of an eye-hand matrix from which all the above functions can emerge and could be regarded as key features of a network with several entry points, command nodes and outflow pathways, as confirmed by the discovery of a direct parietospinal projection for the control of hand action. The integrity of this system is crucial for daily life, as testified by the consequences of cortical lesions, spanning from severe paralysis to complex forms of apraxia. In this review, I will sketch my personal understanding of the scientific and conceptual trajectory of a line of investigation with many unexpected influences on cortical function and disease, from motor behavior to cognition.

Open-Source Joystick Manipulandum for Decision-Making, Reaching, and Motor Control Studies in Mice

To make full use of optogenetic and molecular techniques in the study of motor control, rich behavioral paradigms for rodents must rise to the same level of sophistication and applicability. We describe the layout, construction, use and analysis of data from joystick-based reaching in a head-fixed mouse. The step-by-step guide is designed for both experienced rodent motor labs and new groups looking to enter into this research space. Using this platform, mice learn to consistently perform large, easily-quantified reaches, including during a two-armed bandit probabilistic learning task. The metrics of performance (reach trajectory, amplitude, speed, duration, and inter-reach interval) can be used to quantify behavior or administer stimulation in closed loop with behavior. We provide a highly customizable, low cost and reproducible open-source behavior training platform for studying motor control, decision-making, and reaching reaction time. The development of this software and hardware platform enables behavioral work to complement recent advances in rodents, while remaining accessible to smaller institutions and labs, thus providing a high-throughput method to study unexplored features of action selection, motivation, and value-based decisions.

Excitatory/Inhibitory Responses Shape Coherent Neuronal Dynamics Driven by Optogenetic Stimulation in the Primate Brain

Coherent neuronal dynamics play an important role in complex cognitive functions. Optogenetic stimulation promises to provide new ways to test the functional significance of coherent neural activity. However, the mechanisms by which optogenetic stimulation drives coherent dynamics remain unclear, especially in the nonhuman primate brain. Here, we perform computational modeling and experiments to study the mechanisms of optogenetic-stimulation-driven coherent neuronal dynamics in three male nonhuman primates. Neural responses arise from stimulation-evoked, temporally dynamic excitatory (E) and inhibitory (I) activity. Spiking activity is more likely to occur during E/I imbalances. Thus the relative difference in the driven E and I responses precisely controls spike timing by forming a brief time interval of increased spiking likelihood. Experimental results agree with parameter-dependent predictions from the computational models. These results demonstrate that optogenetic stimulation driven coherent neuronal dynamics are governed by the temporal properties of E/I activity. Transient imbalances in excitatory and inhibitory activity may provide a general mechanism for generating coherent neuronal dynamics without the need for an oscillatory generator.SIGNIFICANCE STATEMENT We examine how coherent neuronal dynamics arise from optogenetic stimulation in the primate brain. Using computational models and experiments, we demonstrate that coherent spiking and local field potential activity is generated by stimulation-evoked responses of excitatory and inhibitory activity in networks, extending the growing literature on neuronal dynamics. These responses create brief time intervals of increased spiking tendency and are consistent with previous observations in the literature that balanced excitation and inhibition controls spike timing, suggesting that optogenetic-stimulation-driven coherence may arise from intrinsic E/I balance. Most importantly, our results are obtained in nonhuman primates and thus will play a leading role in driving the use of causal manipulations with optogenetic tools to study higher cognitive functions in the primate brain.

Neurorestoration: Advances in human brain–computer interface using microelectrode arrays

Neural damage has been a great challenge to the medical field for a very long time. The emergence of brain–computer interfaces (BCIs) offered a new possibility to enhance the activity of daily living and provide a new formation of entertainment for those with disabilities. Intracortical BCIs, which require the implantation of microelectrodes, can receive neuronal signals with a high spatial and temporal resolution from the individual’s cortex. When BCI decoded cortical signals and mapped them to external devices, it displayed the ability not only to replace part of the human motor function but also to help individuals restore certain neurological functions. In this review, we focus on human intracortical BCI research using microelectrode arrays and summarize the main directions and the latest results in this field. In general, we found that intracortical BCI research based on motor neuroprosthetics and functional electrical stimulation have already achieved some simple functional replacement and treatment of motor function. Pioneering work in the posterior parietal cortex has given us a glimpse of the potential that intracortical BCIs have to control external devices and receive various sensory information.

A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects

Cross frequency coupling (CFC) is emerging as a fundamental feature of brain activity, correlated with brain function and dysfunction. Many different types of CFC have been identified through application of numerous data analysis methods, each developed to characterize a specific CFC type. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. To address this, we propose a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. We show in simulations that the proposed method successfully detects CFC between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples. Applying the method to in vivo data, we illustrate examples of CFC during a seizure and in response to electrical stimuli.

Eye movements do not play an important role in the adaptation of hand tracking to a visuomotor rotation

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior. Although eye movements are known to assist hand movement control, how eye movements might contribute to the adaptation of hand movements remains largely unexplored. To determine to what extent eye movements contribute to visuomotor adaptation of hand tracking, participants were asked to track a visual target that followed an unpredictable trajectory with a cursor using a joystick. During blocks of trials, participants were either allowed to look wherever they liked or required to fixate a cross at the center of the screen. Eye movements were tracked to ensure gaze fixation as well as to examine free gaze behavior. The cursor initially responded normally to the joystick, but after several trials, the direction in which it responded was rotated by 90°. Although fixating the eyes had a detrimental influence on hand tracking performance, participants exhibited a rather similar time course of adaptation to rotated visual feedback in the gaze-fixed and gaze-free conditions. More importantly, there was extensive transfer of adaptation between the gaze-fixed and gaze-free conditions. We conclude that although eye movements are relevant for the online control of hand tracking, they do not play an important role in the visuomotor adaptation of such tracking. These results suggest that participants do not adapt by changing the mapping between eye and hand movements, but rather by changing the mapping between hand movements and the cursor’s motion independently of eye movements.

NEW & NOTEWORTHY Eye movements assist hand movements in everyday activities, but their contribution to visuomotor adaptation remains largely unknown. We compared adaptation of hand tracking under free gaze and fixed gaze. Although our results confirm that following the target with the eyes increases the accuracy of hand movements, they unexpectedly demonstrate that gaze fixation does not hinder adaptation. These results suggest that eye movements have distinct contributions for online control and visuomotor adaptation of hand movements.

Mixed Spatial and Movement Representations in the Primate Posterior Parietal Cortex

The posterior parietal cortex (PPC) of humans and non-human primates plays a key role in the sensory and motor transformations required to guide motor actions to objects of interest in the environment. Despite decades of research, the anatomical and functional organization of this region is still a matter of contention. It is generally accepted that specialized parietal subregions and their functional counterparts in the frontal cortex participate in distinct segregated networks related to eye, arm and hand movements. However, experimental evidence obtained primarily from single neuron recording studies in non-human primates has demonstrated a rich mixing of signals processed by parietal neurons, calling into question ideas for a strict functional specialization. Here, we present a brief account of this line of research together with the basic trends in the anatomical connectivity patterns of the parietal subregions. We review, the evidence related to the functional communication between subregions of the PPC and describe progress towards using parietal neuron activity in neuroprosthetic applications. Recent literature suggests a role for the PPC not as a constellation of specialized functional subdomains, but as a dynamic network of sensorimotor loci that combine multiple signals and work in concert to guide motor behavior.

Understanding Sensory Information Processing Through Simultaneous Multi-area Population Recordings

The goal of sensory neuroscience is to understand how the brain creates its myriad of representations of the world, and uses these representations to produce perception and behavior. Circuits of neurons in spatially segregated regions of brain tissue have distinct functional specializations, and these regions are connected to form a functional processing hierarchy. Advances in technology for recording neuronal activity from multiple sites in multiple cortical areas mean that we are now able to collect data that reflects how information is transformed within and between connected members of this hierarchy. This advance is an important step in understanding the brain because, after the sensory organs have transduced a physical signal, every processing stage takes the activity of other neurons as its input, not measurements of the physical world. However, as we explore the potential of studying how populations of neurons in multiple areas respond in concert, we must also expand both the analytical tools that we use to make sense of these data and the scope of the theories that we attempt to define. In this article, we present an overview of some of the most promising analytical approaches for making inferences from population recordings in multiple brain areas, such as dimensionality reduction and measuring changes in correlated variability, and examine how they may be used to address longstanding questions in sensory neuroscience.

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Independent selection of eye and hand targets suggests effector-specific attentional mechanisms

Both eye and hand movements bind visual attention to their target locations during movement preparation. However, it remains contentious whether eye and hand targets are selected jointly by a single selection system, or individually by independent systems. To unravel the controversy, we investigated the deployment of visual attention – a proxy of motor target selection – in coordinated eye-hand movements. Results show that attention builds up in parallel both at the eye and the hand target. Importantly, the allocation of attention to one effector’s motor target was not affected by the concurrent preparation of the other effector’s movement at any time during movement preparation. This demonstrates that eye and hand targets are represented in separate, effector-specific maps of action-relevant locations. The eye-hand synchronisation that is frequently observed on the behavioral level must emerge from mutual influences of the two effector systems at later, post-attentional processing stages.

Lateral intraparietal area (LIP) is largely effector-specific in free-choice decisions

Despite many years of intense research, there is no strong consensus about the role of the lateral intraparietal area (LIP) in decision making. One view of LIP function is that it guides spatial attention, providing a “saliency map” of the external world. If this were the case, it would contribute to target selection regardless of which action would be performed to implement the choice. On the other hand, LIP inactivation has been shown to influence spatial selection and oculomotor metrics in free-choice decisions, which are made using eye movements, arguing that it contributes to saccade decisions. To dissociate between a more general attention role and a more effector specific saccade role, we reversibly inactivated LIP while non-human primates freely selected between two targets, presented in the two hemifields, with either saccades or reaches. Unilateral LIP inactivation induced a strong choice bias to ipsilesional targets when decisions were made with saccades. Interestingly, the inactivation also caused a reduction of contralesional choices when decisions were made with reaches, albeit the effect was less pronounced. These findings suggest that LIP is part of a network for making oculomotor decisions and is largely effector-specific in free-choice decisions.

Spatial eye-hand coordination during bimanual reaching is not systematically coded in either LIP or PRR

When we reach for something, we also look at it. If we reach for two objects at once, one with each hand, we look first at one and then the other. It is not known which brain areas underlie this coordination. We studied two parietal areas known to be involved in eye and arm movements. Neither area was sensitive to the order in which the targets were looked at. This implies that coordinated saccades are driven by downstream areas and not by the parietal cortex as is commonly assumed.

We often orient to where we are about to reach. Spatial and temporal correlations in eye and arm movements may depend on the posterior parietal cortex (PPC). Spatial representations of saccade and reach goals preferentially activate cells in the lateral intraparietal area (LIP) and the parietal reach region (PRR), respectively. With unimanual reaches, eye and arm movement patterns are highly stereotyped. This makes it difficult to study the neural circuits involved in coordination. Here, we employ bimanual reaching to two different targets. Animals naturally make a saccade first to one target and then the other, resulting in different patterns of limb–gaze coordination on different trials. Remarkably, neither LIP nor PRR cells code which target the eyes will move to first. These results suggest that the parietal cortex plays at best only a permissive role in some aspects of eye–hand coordination and makes the role of LIP in saccade generation unclear.

Neural mechanisms of mental schema: a triplet of delta, low beta/spindle and ripple oscillations

Schemas are higher-level knowledge structures that integrate and organise lower-level representations. As internal templates, schemas are formed according to how events are perceived, interpreted and remembered. Although these higher-level units are assumed to play a fundamental role in our daily life from an early age, the neuronal basis and mechanisms of schema formation and use remain largely unknown. It is important to elucidate how the brain constructs and maintains these higher-level units. In order to examine the possible neural underpinnings of schema, we recapitulate previous work and discuss their findings related to schemas as the brain template. We specifically focused on low beta/spindle oscillations, which are assumed to be the key components of schemas, and propose that the brain template is implemented with a triplet of neural oscillations, that is delta, low beta/spindle and ripple oscillations.

Limited Contribution of Primary Motor Cortex in Eye-Hand Coordination: A TMS Study

The ability to track a moving target with the eye is substantially improved when the target is self-moved compared with when it is moved by an external agent. To account for this observation, it has been postulated that the oculomotor system has access to hand efference copy, thereby allowing to predict the motion of the visual target. Along this scheme, we tested the effect of transcranial magnetic stimulation (TMS) over the hand area of the primary motor cortex (M1) when human participants (50% females) are asked to track with their eyes a visual target whose horizontal motion is driven by their grip force. We reasoned that, if the output of M1 is used by the oculomotor system to keep track of the target, on top of inducing short latency disturbance of grip force, single-pulse TMS should also quickly disrupt ongoing eye motion. For comparison purposes, the effect of TMS over M1 was monitored when subjects tracked an externally moved target (while keeping their hand at rest or not). In both cases, results showed no alterations in smooth pursuit, meaning that its velocity was unaffected within the 25-125 ms epoch that followed TMS. Overall, our results imply that the output of M1 has limited contribution in driving the eye motion during our eye-hand coordination task. This study suggests that, if hand motor signals are accessed by the oculomotor system, this is upstream of M1.SIGNIFICANCE STATEMENT The ability to coordinate eye and hand actions is central in everyday activity. However, the neural mechanisms underlying this coordination remain to be clarified. A leading hypothesis is that the oculomotor system has access to hand motor signals. Here we explored this possibility by means of transcranial magnetic stimulation (TMS) over the hand area of the primary motor cortex (M1) when humans tracked with the eyes a visual target that was moved by the hand. As expected, ongoing hand action was perturbed 25-30 ms after TMS, but our results fail to show any disruption of eye motion, smooth pursuit velocity being unaffected. This work suggests that, if hand motor signals are accessed by the oculomotor system, this is upstream of M1.

Multiple spatial representations interact to increase reach accuracy when coordinating a saccade with a reach

Reaching is an essential behavior that allows primates to interact with the environment. Precise reaching to visual targets depends on our ability to localize and foveate the target. Despite this, how the saccade system contributes to improvements in reach accuracy remains poorly understood. To assess spatial contributions of eye movements to reach accuracy, we performed a series of behavioral psychophysics experiments in nonhuman primates (Macaca mulatta). We found that a coordinated saccade with a reach to a remembered target location increases reach accuracy without target foveation. The improvement in reach accuracy was similar to that obtained when the subject had visual information about the location of the current target in the visual periphery and executed the reach while maintaining central fixation. Moreover, we found that the increase in reach accuracy elicited by a coordinated movement involved a spatial coupling mechanism between the saccade and reach movements. We observed significant correlations between the saccade and reach errors for coordinated movements. In contrast, when the eye and arm movements were made to targets in different spatial locations, the magnitude of the error and the degree of correlation between the saccade and reach direction were determined by the spatial location of the eye and the hand targets. Hence, we propose that coordinated movements improve reach accuracy without target foveation due to spatial coupling between the reach and saccade systems. Spatial coupling could arise from a neural mechanism for coordinated visual behavior that involves interacting spatial representations.NEW & NOTEWORTHY How visual spatial representations guiding reach movements involve coordinated saccadic eye movements is unknown. Temporal coupling between the reach and saccade system during coordinated movements improves reach performance. However, the role of spatial coupling is unclear. Using behavioral psychophysics, we found that spatial coupling increases reach accuracy in addition to temporal coupling and visual acuity. These results suggest that a spatial mechanism to couple the reach and saccade systems increases the accuracy of coordinated movements.

Simultaneous analysis of the LFP and spiking activity reveals essential components of a visuomotor transformation in the frontal eye field

The frontal eye field (FEF) is a key brain region to study visuomotor transformations because the primary input to FEF is visual in nature, whereas its output reflects the planning of behaviorally relevant saccadic eye movements. In this study, we used a memory-guided saccade task to temporally dissociate the visual epoch from the saccadic epoch through a delay epoch, and used the local field potential (LFP) along with simultaneously recorded spike data to study the visuomotor transformation process. We showed that visual latency of the LFP preceded spiking activity in the visual epoch, whereas spiking activity preceded LFP activity in the saccade epoch. We also found a spatially tuned elevation in gamma band activity (30-70 Hz), but not in the corresponding spiking activity, only during the delay epoch, whose activity predicted saccade reaction times and the cells' saccade tuning. In contrast, beta band activity (13-30 Hz) showed a nonspatially selective suppression during the saccade epoch. Taken together, these results suggest that motor plans leading to saccades may be generated internally within the FEF from local activity represented by gamma activity.

Computational Architecture of the Parieto-Frontal Network Underlying Cognitive-Motor Control in Monkeys

The statistical structure of intrinsic parietal and parieto-frontal connectivity in monkeys was studied through hierarchical cluster analysis. Based on their inputs, parietal and frontal areas were grouped into different clusters, including a variable number of areas that in most instances occupied contiguous architectonic fields. Connectivity tended to be stronger locally: that is, within areas of the same cluster. Distant frontal and parietal areas were targeted through connections that in most instances were reciprocal and often of different strength. These connections linked parietal and frontal clusters formed by areas sharing basic functional properties. This led to five different medio-laterally oriented pillar domains spanning the entire extent of the parieto-frontal system, in the posterior parietal, anterior parietal, cingulate, frontal, and prefrontal cortex. Different information processing streams could be identified thanks to inter-domain connectivity. These streams encode fast hand reaching and its control, complex visuomotor action spaces, hand grasping, action/intention recognition, oculomotor intention and visual attention, behavioral goals and strategies, and reward and decision value outcome. Most of these streams converge on the cingulate domain, the main hub of the system. All of them are embedded within a larger eye–hand coordination network, from which they can be selectively set in motion by task demands.

Temporal coding of reward-guided choice in the posterior parietal cortex

Making a decision involves computations across distributed cortical and subcortical networks. How such distributed processing is performed remains unclear. We test how the encoding of choice in a key decision-making node, the posterior parietal cortex (PPC), depends on the temporal structure of the surrounding population activity. We recorded spiking and local field potential (LFP) activity in the PPC while two rhesus macaques performed a decision-making task. We quantified the mutual information that neurons carried about an upcoming choice and its dependence on LFP activity. The spiking of PPC neurons was correlated with LFP phases at three distinct time scales in the theta, beta, and gamma frequency bands. Importantly, activity at these time scales encoded upcoming decisions differently. Choice information contained in neural firing varied with the phase of beta and gamma activity. For gamma activity, maximum choice information occurred at the same phase as the maximum spike count. However, for beta activity, choice information and spike count were greatest at different phases. In contrast, theta activity did not modulate the encoding properties of PPC units directly but was correlated with beta and gamma activity through cross-frequency coupling. We propose that the relative timing of local spiking and choice information reveals temporal reference frames for computations in either local or large-scale decision networks. Differences between the timing of task information and activity patterns may be a general signature of distributed processing across large-scale networks.

Role of motor execution in the ocular tracking of self-generated movements

When human observers track the movements of their own hand with their gaze, the eyes can start moving before the finger (i.e., anticipatory smooth pursuit). The signals driving anticipation could come from motor commands during finger motor execution or from motor intention and decision processes associated with self-initiated movements. For the present study, we built a mechanical device that could move a visual target either in the same direction as the participant's hand or in the opposite direction. Gaze pursuit of the target showed stronger anticipation if it moved in the same direction as the hand compared with the opposite direction, as evidenced by decreased pursuit latency, increased positional lead of the eye relative to target, increased pursuit gain, decreased saccade rate, and decreased delay at the movement reversal. Some degree of anticipation occurred for incongruent pursuit, indicating that there is a role for higher-level movement prediction in pursuit anticipation. The fact that anticipation was larger when target and finger moved in the same direction provides evidence for a direct coupling between finger and eye motor commands.

Uniting functional network topology and oscillations in the fronto-parietal single unit network of behaving primates

The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks.

DOI:http://dx.doi.org/10.7554/eLife.15719.001

The network of neurons in our brain generates all of our actions, yet it is not well understood how these neurons coordinate their activity with each other. Rhythmic electrical activity that happens at the same time across many different neurons is thought to be crucial for allowing different areas of the brain to communicate. However, it is still unclear what purpose rhythmic activity serves for communication. Are there groups of ‘hub’ neurons in different brain regions that coordinate overall activity by rhythmically synchronizing the network of neurons? Or is rhythmic activity insignificant for network coordination?

Dann et al. trained three monkeys to follow specific instructions to grasp a handle in different ways. While the monkeys performed the task, the activity of about 100 neurons was recorded simultaneously in three brain regions that are involved in planning and carrying out grasping movements. This revealed that the activity of the neurons was coordinated by a group of strongly connected hub neurons, which were distributed across all three of the brain regions. Nearly all of the hub neurons were rhythmically synchronized with each other, and also communicated with other neurons using rhythmic electrical activity.

Overall, the results presented by Dann et al. suggest that rhythmically synchronized activity is essential for neurons to coordinate how information is processed across the brain. Further studies into this method of communicating information will help to reveal how the primate brain can generate an immense range of behaviors.

DOI:http://dx.doi.org/10.7554/eLife.15719.002

Oculomatic: High speed, reliable, and accurate open-source eye tracking for humans and non-human primates

BACKGROUND

Video-based noninvasive eye trackers are an extremely useful tool for many areas of research. Many open-source eye trackers are available but current open-source systems are not designed to track eye movements with the temporal resolution required to investigate the mechanisms of oculomotor behavior. Commercial systems are available but employ closed source hardware and software and are relatively expensive, limiting wide-spread use.

NEW METHOD

Here we present Oculomatic, an open-source software and modular hardware solution to eye tracking for use in humans and non-human primates.

RESULTS

Oculomatic features high temporal resolution (up to 600Hz), real-time eye tracking with high spatial accuracy (<0.5°), and low system latency (∼1.8ms, 0.32ms STD) at a relatively low-cost.

COMPARISON WITH EXISTING METHOD(S)

Oculomatic compares favorably to our existing scleral search-coil system while being fully non invasive.

CONCLUSIONS

We propose that Oculomatic can support a wide range of research into the properties and neural mechanisms of oculomotor behavior.

Coherent neuronal ensembles are rapidly recruited when making a look-reach decision

Selecting and planning actions recruits neurons across many areas of the brain but how ensembles of neurons work together to make decisions is unknown. Temporally-coherent neural activity may provide a mechanism by which neurons coordinate their activity in order to make decisions. If so, neurons that are part of coherent ensembles may predict movement choices before other ensembles of neurons. We recorded neuronal activity in the lateral and medial banks of the intraparietal sulcus (IPS) of the posterior parietal cortex, while monkeys made choices about where to look and reach and decoded the activity to predict the choices. Ensembles of neurons that displayed coherent patterns of spiking activity extending across the IPS, “dual coherent” ensembles, predicted movement choices substantially earlier than other neuronal ensembles. We propose that dual-coherent spike timing reflects interactions between groups of neurons that play an important role in how we make decisions.