The Fixation and Saccade P3

Although most instances of object recognition during natural viewing occur in the presence of saccades, the neural correlates of objection recognition have almost exclusively been examined during fixation. Recent studies have indicated that there are post-saccadic modulations of neural activity immediately following eye movement landing; however, whether post-saccadic modulations affect relatively late occurring cognitive components such as the P3 has not been explored. The P3 as conventionally measured at fixation is commonly used in brain computer interfaces, hence characterizing the post-saccadic P3 could aid in the development of improved brain computer interfaces that allow for eye movements. In this study, the P3 observed after saccadic landing was compared to the P3 measured at fixation. No significant differences in P3 start time, temporal persistence, or amplitude were found between fixation and saccade trials. Importantly, sensory neural responses canceled in the target minus distracter comparisons used to identify the P3. Our results indicate that relatively late occurring cognitive neural components such as the P3 are likely less sensitive to post saccadic modulations than sensory neural components and other neural activity occurring shortly after eye movement landing. Furthermore, due to the similarity of the fixation and saccade P3, we conclude that the P3 following saccadic landing could possibly be used as a viable signal in brain computer interfaces allowing for eye movements.     

Parallel and interrelated neural systems underlying adaptive navigation

The ability to process in parallel multiple forms of sensoryinformation, and link sensory-sensory associations to behavior,presumably allows for the opportunistic use of the most reliableand predictive sensory modalities in diverse behavioral contexts.Evolutionary considerations indicate that such processing mayrepresent a fundamental operating principle underlying complexsensory associations and sensory-motor integration. Here, wesuggest that animal navigation is a particularly useful modelof such opportunistic use of sensory and motor information becauseit is possible to study directly the effects of memory on neuralsystem functions. First, comparative evidence for parallel processingacross multiple brain structures during navigation is providedfrom the literatures on fish and rodent navigation. Then, basedon neurophysiological evidence of coordinated, multiregionalprocessing, we provide a neurobiological explanation of learningand memory effects on neural circuitry mediating navigation.     

A neural model for nonassociative learning in a prototypical sensory-motor scheme: the landing reaction in flies

Nonassociative learning is an important property of neural organization in both vertebrate and invertebrate species. In this paper we propose a neural model for nonassociative learning in a well studied prototypical sensory-motor scheme: the landing reaction of flies. The general structure of the model consists of sensory processing stages, a sensory-motor gate network, and motor control circuits. The paper concentrates on the sensory-motor gate network which has an agonist-antagonist structure. Sensory inputs to this circuit are transduced by chemical messenger systems whose dynamics include depletion and replenishment terms. The resulting circuit is a gated dipole anatomy and we show that it gives a good account of nonassociative learning in the landing reaction of the fly.Supported by a grant from the National Institute of Mental Health     

Temporal Production Signals in Parietal Cortex

We often perform movements and actions on the basis of internal motivations and without any explicit instructions or cues. One common example of such behaviors is our ability to initiate movements solely on the basis of an internally generated sense of the passage of time. In order to isolate the neuronal signals responsible for such timed behaviors, we devised a task that requires nonhuman primates to move their eyes consistently at regular time intervals in the absence of any external stimulus events and without an immediate expectation of reward. Despite the lack of sensory information, we found that animals were remarkably precise and consistent in timed behaviors, with standard deviations on the order of 100 ms. To examine the potential neural basis of this precision, we recorded from single neurons in the lateral intraparietal area (LIP), which has been implicated in the planning and execution of eye movements. In contrast to previous studies that observed a build-up of activity associated with the passage of time, we found that LIP activity decreased at a constant rate between timed movements. Moreover, the magnitude of activity was predictive of the timing of the impending movement. Interestingly, this relationship depended on eye movement direction: activity was negatively correlated with timing when the upcoming saccade was toward the neuron''s response field and positively correlated when the upcoming saccade was directed away from the response field. This suggests that LIP activity encodes timed movements in a push-pull manner by signaling for both saccade initiation towards one target and prolonged fixation for the other target. Thus timed movements in this task appear to reflect the competition between local populations of task relevant neurons rather than a global timing signal.     

Shaping the dynamics of a bidirectional neural interface

Progress in decoding neural signals has enabled the development of interfaces that translate cortical brain activities into commands for operating robotic arms and other devices. The electrical stimulation of sensory areas provides a means to create artificial sensory information about the state of a device. Taken together, neural activity recording and microstimulation techniques allow us to embed a portion of the central nervous system within a closed-loop system, whose behavior emerges from the combined dynamical properties of its neural and artificial components. In this study we asked if it is possible to concurrently regulate this bidirectional brain-machine interaction so as to shape a desired dynamical behavior of the combined system. To this end, we followed a well-known biological pathway. In vertebrates, the communications between brain and limb mechanics are mediated by the spinal cord, which combines brain instructions with sensory information and organizes coordinated patterns of muscle forces driving the limbs along dynamically stable trajectories. We report the creation and testing of the first neural interface that emulates this sensory-motor interaction. The interface organizes a bidirectional communication between sensory and motor areas of the brain of anaesthetized rats and an external dynamical object with programmable properties. The system includes (a) a motor interface decoding signals from a motor cortical area, and (b) a sensory interface encoding the state of the external object into electrical stimuli to a somatosensory area. The interactions between brain activities and the state of the external object generate a family of trajectories converging upon a selected equilibrium point from arbitrary starting locations. Thus, the bidirectional interface establishes the possibility to specify not only a particular movement trajectory but an entire family of motions, which includes the prescribed reactions to unexpected perturbations.     

A Sensorimotor Model for Computing Intended Reach Trajectories

The presumed role of the primate sensorimotor system is to transform reach targets from retinotopic to joint coordinates for producing motor output. However, the interpretation of neurophysiological data within this framework is ambiguous, and has led to the view that the underlying neural computation may lack a well-defined structure. Here, I consider a model of sensorimotor computation in which temporal as well as spatial transformations generate representations of desired limb trajectories, in visual coordinates. This computation is suggested by behavioral experiments, and its modular implementation makes predictions that are consistent with those observed in monkey posterior parietal cortex (PPC). In particular, the model provides a simple explanation for why PPC encodes reach targets in reference frames intermediate between the eye and hand, and further explains why these reference frames shift during movement. Representations in PPC are thus consistent with the orderly processing of information, provided we adopt the view that sensorimotor computation manipulates desired movement trajectories, and not desired movement endpoints.     

Expression of the Immunoglobulin Superfamily Cell Adhesion Molecules in the Developing Spinal Cord and Dorsal Root Ganglion

Cell adhesion molecules belonging to the immunoglobulin superfamily (IgSF) control synaptic specificity through hetero- or homophilic interactions in different regions of the nervous system. In the developing spinal cord, monosynaptic connections of exquisite specificity form between proprioceptive sensory neurons and motor neurons, however, it is not known whether IgSF molecules participate in regulating this process. To determine whether IgSF molecules influence the establishment of synaptic specificity in sensory-motor circuits, we examined the expression of 157 IgSF genes in the developing dorsal root ganglion (DRG) and spinal cord by in situ hybridization assays. We find that many IgSF genes are expressed by sensory and motor neurons in the mouse developing DRG and spinal cord. For instance, Alcam, Mcam, and Ocam are expressed by a subset of motor neurons in the ventral spinal cord. Further analyses show that Ocam is expressed by obturator but not quadriceps motor neurons, suggesting that Ocam may regulate sensory-motor specificity in these sensory-motor reflex arcs. Electrophysiological analysis shows no obvious defects in synaptic specificity of monosynaptic sensory-motor connections involving obturator and quadriceps motor neurons in Ocam mutant mice. Since a subset of Ocam⁺ motor neurons also express Alcam, Alcam or other functionally redundant IgSF molecules may compensate for Ocam in controlling sensory-motor specificity. Taken together, these results reveal that IgSF molecules are broadly expressed by sensory and motor neurons during development, and that Ocam and other IgSF molecules may have redundant functions in controlling the specificity of sensory-motor circuits.     

Video-oculography in Mice

Eye movements are very important in order to track an object or to stabilize an image on the retina during movement. Animals without a fovea, such as the mouse, have a limited capacity to lock their eyes onto a target. In contrast to these target directed eye movements, compensatory ocular eye movements are easily elicited in afoveate animals^1,2,3,4. Compensatory ocular movements are generated by processing vestibular and optokinetic information into a command signal that will drive the eye muscles. The processing of the vestibular and optokinetic information can be investigated separately and together, allowing the specification of a deficit in the oculomotor system. The oculomotor system can be tested by evoking an optokinetic reflex (OKR), vestibulo-ocular reflex (VOR) or a visually-enhanced vestibulo-ocular reflex (VVOR). The OKR is a reflex movement that compensates for "full-field" image movements on the retina, whereas the VOR is a reflex eye movement that compensates head movements. The VVOR is a reflex eye movement that uses both vestibular as well as optokinetic information to make the appropriate compensation. The cerebellum monitors and is able to adjust these compensatory eye movements. Therefore, oculography is a very powerful tool to investigate brain-behavior relationship under normal as well as under pathological conditions (f.e. of vestibular, ocular and/or cerebellar origin).Testing the oculomotor system, as a behavioral paradigm, is interesting for several reasons. First, the oculomotor system is a well understood neural system⁵. Second, the oculomotor system is relative simple⁶; the amount of possible eye movement is limited by its ball-in-socket architecture ("single joint") and the three pairs of extra-ocular muscles⁷. Third, the behavioral output and sensory input can easily be measured, which makes this a highly accessible system for quantitative analysis⁸. Many behavioral tests lack this high level of quantitative power. And finally, both performance as well as plasticity of the oculomotor system can be tested, allowing research on learning and memory processes⁹.Genetically modified mice are nowadays widely available and they form an important source for the exploration of brain functions at various levels¹⁰. In addition, they can be used as models to mimic human diseases. Applying oculography on normal, pharmacologically-treated or genetically modified mice is a powerful research tool to explore the underlying physiology of motor behaviors under normal and pathological conditions. Here, we describe how to measure video-oculography in mice⁸.     

Computing with neural synchrony

Neurons communicate primarily with spikes, but most theories of neural computation are based on firing rates. Yet, many experimental observations suggest that the temporal coordination of spikes plays a role in sensory processing. Among potential spike-based codes, synchrony appears as a good candidate because neural firing and plasticity are sensitive to fine input correlations. However, it is unclear what role synchrony may play in neural computation, and what functional advantage it may provide. With a theoretical approach, I show that the computational interest of neural synchrony appears when neurons have heterogeneous properties. In this context, the relationship between stimuli and neural synchrony is captured by the concept of synchrony receptive field, the set of stimuli which induce synchronous responses in a group of neurons. In a heterogeneous neural population, it appears that synchrony patterns represent structure or sensory invariants in stimuli, which can then be detected by postsynaptic neurons. The required neural circuitry can spontaneously emerge with spike-timing-dependent plasticity. Using examples in different sensory modalities, I show that this allows simple neural circuits to extract relevant information from realistic sensory stimuli, for example to identify a fluctuating odor in the presence of distractors. This theory of synchrony-based computation shows that relative spike timing may indeed have computational relevance, and suggests new types of neural network models for sensory processing with appealing computational properties.     

Predictability of visual perturbation during locomotion: implications for corrective efference copy signaling

In guiding adaptive behavior, efference copy signals or corollary discharge are traditionally considered to serve as predictors of self-generated sensory inputs and by interfering with their central processing are able to counter unwanted consequences of an animal??s own actions. Here, in a speculative reflection on this issue, we consider a different functional role for such intrinsic predictive signaling, namely in stabilizing gaze during locomotion where resultant changes in head orientation in space require online compensatory eye movements in order to prevent retinal image slip. The direct activation of extraocular motoneurons by locomotor-related efference copies offers a prospective substrate for assisting self-motion derived sensory feedback, rather than being subtracted from the sensory signal to eliminate unwanted reafferent information. However, implementing such a feed-forward mechanism would be critically dependent on an appropriate phase coupling between rhythmic propulsive movement and resultant head/visual image displacement. We used video analyzes of actual locomotor behavior and basic theoretical modeling to evaluate head motion during stable locomotion in animals as diverse as Xenopus laevis tadpoles, teleost fish and horses in order to assess the potential suitability of spinal efference copies to the stabilization of gaze during locomotion. In all three species, and therefore regardless of aquatic or terrestrial environment, the head displacements that accompanied locomotor action displayed a strong correlative spatio-temporal relationship in correspondence with a potential predictive value for compensatory eye adjustments. Although spinal central pattern generator-derived efference copies offer appropriately timed commands for extraocular motor control during self-generated motion, it is likely that precise image stabilization requires the additional contributions of sensory feedback signals. Nonetheless, the predictability of the visual consequences of stereotyped locomotion renders intrinsic efference copy signaling an appealing mechanism for offsetting these disturbances, thus questioning the exclusive role traditionally ascribed to sensory-motor transformations in stabilizing gaze during vertebrate locomotion.     

Evolutionary and structural diversification of the larval nervous system among marine bryozoans

Regardless of the morphological divergence among larval forms of marine bryozoans, the larval nervous system and its major effector organs (musculature and ciliary fields) are largely molded on the basis of functional demands of feeding, ciliary propulsion, phototactic behaviors, and substrate exploration. Previously published ultrastructural information and immunohistochemical reconstructions presented here indicate that neuronal pathways are largely ipsilateral, with more complex synaptic connections localized within the nerve nodule. Multiciliated sensory-motor neurons diversify structurally and functionally on the basis of their position along the axis of swimming largely due to the functional demands of photoklinotaxis and substrate exploration. Vesiculariform, buguliform, and ascophoran coronate larvae all have patches of sensory neurons bordering the pyriform organ's ciliated groove (juxtapapillary cells and border cells) that are active during substrate selection. Despite their simplified form, cyclostome larvae maintain swimming and probing behaviors with sensory-motor systems functionally similar to those of some parenchymella and planula larval types. Considering the evolutionary relationships among the morphological grades of marine bryozoans, particular lineages within the gymnolaemates have independently evolved larval traits that convey a greater range of sensory abilities and increased propulsive capacity. The larval nervous system of bryozoans may be evolutionarily derived from the pretrochal region of a trochophore-like larval form.     

Normalization regulates competition for visual awareness

Signals in our brain are in a constant state of competition, including those that vie for motor control, sensory dominance, and awareness. To shed light on the mechanisms underlying neural competition, we exploit binocular rivalry, a phenomenon that allows us to probe the competitive process that ordinarily transpires outside of our awareness. By measuring psychometric functions under different states of rivalry, we discovered a pattern of gain changes that are consistent with a model of competition in which attention interacts with normalization processes, thereby driving the ebb and flow between states of awareness. Moreover, we reveal that attention plays a crucial role in modulating competition; without attention, rivalry suppression for high-contrast stimuli is negligible. We propose a framework whereby our visual awareness of competing sensory representations is governed by a common neural computation: normalization.     

Fluctuations and synchronizations of neural activities during sleep: Neural basis of possible sleep functions?

Physiological and psychological evidence have been accumulated concerning the function of sleep in development and learning/memory. Many conceptual ideas have been proposed to elucidate the mechanisms underlying them. Sleep consists of a wide variety of physiological processes. It has not yet been clarified which processes are involved in development and learning/memory processes. We have found that single neuronal activity exhibits a slowly fluctuating rate of discharge during rapid eye movement (REM) sleep and a random low discharge rate during non-rapid eye movement (NREM) sleep. It is suggested that a structural change of the neural network attractor underlies this neuronal dynamics-alternation by mathematical modeling. Functional interpretation of the neuronal dynamics-alternation was provided in combination with the phase locking of ponto-geniculo-occipital (PGO)/pontine (P) wave to the hippocampal theta wave, each of which is known to be involved in learning/memory processes. More directly, by the long-term sensory deprivation, the dynamics of neural activity during sleep was found to progressively change in a non-monotonic way. This finding reveals a possible interaction between sleep and reorganization of neural network in the matured brain. Here, in addition to the related findings, we described our idea about how sleep contributes to the learning/memory processes and reorganization of neural network of the matured brain through characteristic neural activities during sleep.

     

The Mechanism of Saccade Motor Pattern Generation Investigated by a Large-Scale Spiking Neuron Model of the Superior Colliculus

The subcortical saccade-generating system consists of the retina, superior colliculus, cerebellum and brainstem motoneuron areas. The superior colliculus is the site of sensory-motor convergence within this basic visuomotor loop preserved throughout the vertebrates. While the system has been extensively studied, there are still several outstanding questions regarding how and where the saccade eye movement profile is generated and the contribution of respective parts within this system. Here we construct a spiking neuron model of the whole intermediate layer of the superior colliculus based on the latest anatomy and physiology data. The model consists of conductance-based spiking neurons with quasi-visual, burst, buildup, local inhibitory, and deep layer inhibitory neurons. The visual input is given from the superficial superior colliculus and the burst neurons send the output to the brainstem oculomotor nuclei. Gating input from the basal ganglia and an integral feedback from the reticular formation are also included.We implement the model in the NEST simulator and show that the activity profile of bursting neurons can be reproduced by a combination of NMDA-type and cholinergic excitatory synaptic inputs and integrative inhibitory feedback. The model shows that the spreading neural activity observed in vivo can keep track of the collicular output over time and reset the system at the end of a saccade through activation of deep layer inhibitory neurons. We identify the model parameters according to neural recording data and show that the resulting model recreates the saccade size-velocity curves known as the saccadic main sequence in behavioral studies. The present model is consistent with theories that the superior colliculus takes a principal role in generating the temporal profiles of saccadic eye movements, rather than just specifying the end points of eye movements.     

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

Background

Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning.

Methodology/Principal Findings

We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN.

Conclusions/Significance

These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.     

Xenopus laevis: an ideal experimental model for studying the developmental dynamics of neural network assembly and sensory-motor computations

The amphibian Xenopus laevis represents a highly amenable model system for exploring the ontogeny of central neural networks, the functional establishment of sensory-motor transformations, and the generation of effective motor commands for complex behaviors. Specifically, the ability to employ a range of semi-intact and isolated preparations for in vitro morphophysiological experimentation has provided new insights into the developmental and integrative processes associated with the generation of locomotory behavior during changing life styles. In vitro electrophysiological studies have begun to explore the functional assembly, disassembly and dynamic plasticity of spinal pattern generating circuits as Xenopus undergoes the developmental switch from larval tail-based swimming to adult limb-based locomotion. Major advances have also been made in understanding the developmental onset of multisensory signal processing for reactive gaze and posture stabilizing reflexes during self-motion. Additionally, recent evidence from semi-intact animal and isolated CNS experiments has provided compelling evidence that in Xenopus tadpoles, predictive feed-forward signaling from the spinal locomotor pattern generator are engaged in minimizing visual disturbances during tail-based swimming. This new concept questions the traditional view of retinal image stabilization that in vertebrates has been exclusively attributed to sensory-motor transformations of body/head motion-detecting signals. Moreover, changes in visuomotor demands associated with the developmental transition in propulsive strategy from tail- to limb-based locomotion during metamorphosis presumably necessitates corresponding adaptive alterations in the intrinsic spinoextraocular coupling mechanism. Consequently, Xenopus provides a unique opportunity to address basic questions on the developmental dynamics of neural network assembly and sensory-motor computations for vertebrate motor behavior in general.     

Velocity of head movements and sensory-motor adaptation during and after short spaceflight

To investigate to time course of sensory-motor adaptation to microgravity, we tested spatially-directed voluntary head movements before, during and after short spaceflight. We also tested the re-adaptation of postural responses to sensory stimulation after space flight. The cosmonaut performed in microgravity six cycles of voluntary head rotation in pitch, roll and yaw directions. During the first days of weightlessness the angular velocity of head movements increased. Over the next days of microgravity the velocity of head movements gradually decreased. On landing day a significant decrease of head rotation velocity was observed compared to the head movement velocity before spaceflight. Re-adaptation to Earth condition measured by body sway on soft support showed similar time course, but re-adaptation measured by postural responses to vestibular galvanic stimulation was prolonged. These results showed that the angular velocity of aimed head movements of cosmonauts is a good indicator of sensory-motor adaptation in altered gravity conditions.     

Biological modeling of complex chemotaxis behaviors for C. elegans under speed regulation—a dynamic neural networks approach

In this paper, the modeling of several complex chemotaxis behaviors of C. elegans is explored, which include food attraction, toxin avoidance, and locomotion speed regulation. We first model the chemotaxis behaviors of food attraction and toxin avoidance separately. Then, an integrated chemotaxis behavioral model is proposed, which performs the two chemotaxis behaviors simultaneously. The novelty and the uniqueness of the proposed chemotaxis behavioral models are characterized by several attributes. First, all the chemotaxis behavioral model sare on biological basis, namely, the proposed chemotaxis behavior models are constructed by extracting the neural wire diagram from sensory neurons to motor neurons, where sensory neurons are specific for chemotaxis behaviors. Second, the chemotaxis behavioral models are able to perform turning and speed regulation. Third, chemotaxis behaviors are characterized by a set of switching logic functions that decide the orientation and speed. All models are implemented using dynamic neural networks (DNN) and trained using the real time recurrent learning (RTRL) algorithm. By incorporating a speed regulation mechanism, C. elegans can stop spontaneously when approaching food source or leaving away from toxin. The testing results and the comparison with experiment results verify that the proposed chemotaxis behavioral models can well mimic the chemotaxis behaviors of C. elegans in different environments.     

Prominent Inhibitory Projections Guide Sensorimotor Computation: An Invertebrate Perspective

From single‐cell organisms to complex neural networks, all evolved to provide control solutions to generate context‐ and goal‐specific actions. Neural circuits performing sensorimotor computation to drive navigation employ inhibitory control as a gating mechanism as they hierarchically transform (multi)sensory information into motor actions. Here, the focus is on this literature to critically discuss the proposition that prominent inhibitory projections form sensorimotor circuits. After reviewing the neural circuits of navigation across various invertebrate species, it is argued that with increased neural circuit complexity and the emergence of parallel computations, inhibitory circuits acquire new functions. The contribution of inhibitory neurotransmission for navigation goes beyond shaping the communication that drives motor neurons, and instead includes encoding of emergent sensorimotor representations. A mechanistic understanding of the neural circuits performing sensorimotor computations in invertebrates will unravel the minimum circuit requirements driving adaptive navigation.