Boosting Cortical Activity at Beta-Band Frequencies Slows Movement in Humans

Neurons have a striking tendency to engage in oscillatory activities. One important type of oscillatory activity prevalent in the motor system occurs in the beta frequency band, at about 20 Hz. It is manifest during the maintenance of tonic contractions and is suppressed prior to and during voluntary movement [1], [2], [3], [4], [5], [6] and [7]. This and other correlative evidence suggests that beta activity might promote tonic contraction, while impairing motor processing related to new movements [3], [8] and [9]. Hence, bursts of beta activity in the cortex are associated with a strengthening of the motor effects of sensory feedback during tonic contraction and with reductions in the velocity of voluntary movements [9], [10] and [11]. Moreover, beta activity is increased when movement has to be resisted or voluntarily suppressed [7], [12] and [13]. Here we use imperceptible transcranial alternating-current stimulation to entrain cortical activity at 20 Hz in healthy subjects and show that this slows voluntary movement. The present findings are the first direct evidence of causality between any physiological oscillatory brain activity and concurrent motor behavior in the healthy human and help explain how the exaggerated beta activity found in Parkinson's disease can lead to motor slowing in this illness [14].     

Encoding of motor skill in the corticomuscular system of musicians

How motor skills are stored in the nervous system represents a fundamental question in neuroscience. Although musical motor skills are associated with a variety of adaptations [1-3], it remains unclear how these changes are linked to the known superior motor performance of expert musicians. Here we establish a direct and specific relationship between the functional organization of the corticomuscular system and skilled musical performance. Principal component analysis was used to identify joint correlation patterns in finger movements evoked by transcranial magnetic stimulation over the primary motor cortex while subjects were at rest. Linear combinations of a selected subset of these patterns were used to reconstruct active instrumental playing or grasping movements. Reconstruction quality of instrumental playing was superior in skilled musicians compared to musically untrained subjects, displayed taxonomic specificity for the trained movement repertoire, and correlated with the cumulated long-term training exposure, but not with the recent past training history. In violinists, the reconstruction quality of grasping movements correlated negatively with the long-term training history of violin playing. Our results indicate that experience-dependent motor skills are specifically encoded in the functional organization of the primary motor cortex and its efferent system and are consistent with a model of skill coding by a modular neuronal architecture [4].     

Octopus vulgaris uses visual information to determine the location of its arm

Octopuses are intelligent, soft-bodied animals with keen senses that perform reliably in a variety of visual and tactile learning tasks. However, researchers have found them disappointing in that they consistently fail in operant tasks that require them to combine central nervous system reward information with visual and peripheral knowledge of the location of their arms. Wells claimed that in order to filter and integrate an abundance of multisensory inputs that might inform the animal of the position of a single arm, octopuses would need an exceptional computing mechanism, and "There is no evidence that such a system exists in Octopus, or in any other soft bodied animal." Recent electrophysiological experiments, which found no clear somatotopic organization in the higher motor centers, support this claim. We developed a three-choice maze that required an octopus to use a single arm to reach a visually marked goal compartment. Using this operant task, we show for the first time that Octopus vulgaris is capable of guiding a single arm in a complex movement to a location. Thus, we claim that octopuses can combine peripheral arm location information with visual input to control goal-directed complex movements.     

Octopuses use a human-like strategy to control precise point-to-point arm movements

One of the key problems in motor control is mastering or reducing the number of degrees of freedom (DOFs) through coordination. This problem is especially prominent with hyper-redundant limbs such as the extremely flexible arm of the octopus. Several strategies for simplifying these control problems have been suggested for human point-to-point arm movements. Despite the evolutionary gap and morphological differences, humans and octopuses evolved similar strategies when fetching food to the mouth. To achieve this precise point-to-point-task, octopus arms generate a quasi-articulated structure based on three dynamic joints. A rotational movement around these joints brings the object to the mouth . Here, we describe a peripheral neural mechanism-two waves of muscle activation propagate toward each other, and their collision point sets the medial-joint location. This is a remarkably simple mechanism for adjusting the length of the segments according to where the object is grasped. Furthermore, similar to certain human arm movements, kinematic invariants were observed at the joint level rather than at the end-effector level, suggesting intrinsic control coordination. The evolutionary convergence to similar geometrical and kinematic features suggests that a kinematically constrained articulated limb controlled at the level of joint space is the optimal solution for precise point-to-point movements.     

Patterns of motor activity in the isolated nerve cord of the octopus arm

The extremely flexible octopus arm provides a unique opportunity for studying movement control in a highly redundant motor system. We describe a novel preparation that allows analysis of the peripheral nervous system of the octopus arm and its interaction with the muscular and mechanosensory elements of the arm's intrinsic muscular system. First we examined the synaptic responses in muscle fibers to identify the motor pathways from the axial nerve cord of the arm to the surrounding musculature. We show that the motor axons project to the muscles via nerve roots originating laterally from the arm nerve cord. The motor field of each nerve is limited to the region where the nerve enters the arm musculature. The same roots also carry afferent mechanosensory information from the intrinsic muscle to the axial nerve cord. Next, we characterized the pattern of activity generated in the dorsal roots by electrically stimulating the axial nerve cord. The evoked activity, although far reaching and long lasting, cannot alone account for the arm extension movements generated by similar electrical stimulation. The mismatch between patterns of activity in the isolated cord and in an intact arm may stem from the involvement of mechanosensory feedback in natural arm extension.     

The octopus: a model for a comparative analysis of the evolution of learning and memory mechanisms

Comparative analysis of brain function in invertebrates with sophisticated behaviors, such as the octopus, may advance our understanding of the evolution of the neural processes that mediate complex behaviors. Until the last few years, this approach was infeasible due to the lack of neurophysiological tools for testing the neural circuits mediating learning and memory in the brains of octopus and other cephalopods. Now, for the first time, the adaptation of modern neurophysiological methods to the study of the central nervous system of the octopus allows this avenue of research. The emerging results suggest that a convergent evolutionary process has led to the selection of vertebrate-like neural organization and activity-dependent long-term synaptic plasticity. As octopuses and vertebrates are very remote phylogenetically, this convergence suggests the importance of the shared properties for the mediation of learning and memory.     

Targeted disruption of the gene encoding DNA ligase IV leads to lethality in embryonic mice

DNA ligase IV is the most recently identified member of a family of enzymes joining DNA strand breaks in mammalian cell nuclei [1] and [2]. The enzyme occurs in a complex with the XRCC4 gene product [3], an interaction mediated via its unique carboxyl terminus [4] and [5]. Cells lacking XRCC4 are hypersensitive to ionising radiation and defective in V(D)J recombination [3] and [6], implicating DNA ligase IV in the pathway of nonhomologous end-joining (NHEJ) of DNA double-strand breaks mediated by XRCC4, the Ku70/80 heterodimer and the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs) in mammalian cells (reviewed in [7]). The phenotype of a null mutant of the Saccharomyces cerevisiae DNA ligase IV homologue indicates that the enzyme is non-essential and functions in yeast NHEJ [8], [9] and [10]. Unlike other mammalian DNA ligases for which cDNAs have been characterised, DNA ligase IV is encoded by an intronless gene (LIG4). Here, we show that targeted disruption of LIG4 in the mouse leads to lethality associated with extensive apoptotic cell death in the embryonic central nervous system. Thus, unlike Ku70/80 and DNA-PKcs [11], [12], [13] and [14], DNA ligase IV has an essential function in early mammalian development.     

A hierarchical neural-network model for control and learning of voluntary movement

In order to control voluntary movements, the central nervous system (CNS) must solve the following three computational problems at different levels: the determination of a desired trajectory in the visual coordinates, the transformation of its coordinates to the body coordinates and the generation of motor command. Based on physiological knowledge and previous models, we propose a hierarchical neural network model which accounts for the generation of motor command. In our model the association cortex provides the motor cortex with the desired trajectory in the body coordinates, where the motor command is then calculated by means of long-loop sensory feedback. Within the spinocerebellum — magnocellular red nucleus system, an internal neural model of the dynamics of the musculoskeletal system is acquired with practice, because of the heterosynaptic plasticity, while monitoring the motor command and the results of movement. Internal feedback control with this dynamical model updates the motor command by predicting a possible error of movement. Within the cerebrocerebellum — parvocellular red nucleus system, an internal neural model of the inverse-dynamics of the musculo-skeletal system is acquired while monitoring the desired trajectory and the motor command. The inverse-dynamics model substitutes for other brain regions in the complex computation of the motor command. The dynamics and the inverse-dynamics models are realized by a parallel distributed neural network, which comprises many sub-systems computing various nonlinear transformations of input signals and a neuron with heterosynaptic plasticity (that is, changes of synaptic weights are assumed proportional to a product of two kinds of synaptic inputs). Control and learning performance of the model was investigated by computer simulation, in which a robotic manipulator was used as a controlled system, with the following results: (1) Both the dynamics and the inverse-dynamics models were acquired during control of movements. (2) As motor learning proceeded, the inverse-dynamics model gradually took the place of external feedback as the main controller. Concomitantly, overall control performance became much better. (3) Once the neural network model learned to control some movement, it could control quite different and faster movements. (4) The neural netowrk model worked well even when only very limited information about the fundamental dynamical structure of the controlled system was available. Consequently, the model not only accounts for the learning and control capability of the CNS, but also provides a promising parallel-distributed control scheme for a large-scale complex object whose dynamics are only partially known.     

Are interlimb interactions disturbed in patients with Parkinson’s disease? A study under unloading conditions

During natural human locomotion, neural connections are activated that are typical of regulation of the quadrupedal walking. The interaction between the neural networks generating rhythmic movements of the upper and lower limbs depends on tonic state of each of these networks regulated by motor signals from the brain. Distortion of these signals in patients with Parkinson’s disease (PD) may lead to disruption of the interlimb interactions. We examined the effect of movements of the limbs of one girdle on the parameters of the motor activity of another limb girdle at their joint cyclic movements under the conditions of arm and leg unloading in 17 patients with PD and 16 healthy subjects. We have shown that, in patients, the effect of voluntary and passive movements of arms, as well as the active movement of the distal parts of arms, on the voluntary movement of legs is weak, while in healthy subjects, the effect of arm movements on the parameters of voluntary stepping is significant. The effect of arm movements on the activation of the involuntary stepping by vibrational stimulation of-legs in patients was absent, while in healthy subjects, the motor activity of arms increased the possibility of involuntary rhythmic movements activation. Differences in the effect of leg movements on the rhythmic movements of arms were found in both patients and healthy subjects. The interlimb interaction appeared after drug administration. However, the effect of the drug was not sufficient for the recovery of normal state of the neural networks in patients. In PD patients, neural networks generating stepping rhythm have an increased tonic activity, which prevents the activation and appearance of involuntary rhythmic movements facilitating the effects of arms on legs.     

Isolation and characterization of a novel small cardioactive peptide-related peptide from the brain of Octopus vulgaris

A novel small cardioactive peptide (SCP)-related peptide (oct-SCPRP: Ser-Asn-Gly-Tyr-Leu-Ala-Leu-Pro-Arg-Gln-NH2) was isolated from the brain of the octopus (Octopus vulgaris). cDNA encoding this precursor protein was cloned. Oct-SCPRP was shown to evoke contraction in the radula protractor muscle, and the precursor protein was highly homologous to the SCP family in the Mollusk but did not encode a related peptide, SCPB. The expression of oct-SCPRP mRNA was present not only in the peripheral nervous system (PNS) which is a motor center for the control of feeding, but also in the central nervous system (CNS) which is capable of complex analysis, learning, and controls behaviors.     

Torque generation by one of the motor subunits of heterotrimeric kinesin-2

Heterotrimeric kinesin-2 motors [1] and [2] transport intraflagellar transport (IFT)-particles from the base to the tip of the axoneme to assemble and maintain cilia [3], [4], [5], [6], [7], [8], [9] and [10]. These motors are distinct in containing two non-identical motor subunits together with an accessory subunit [1], [11], [12], [13], [14] and [15]. We evaluated the significance of this organization by comparing purified wild type kinesin-2 holoenzymes that support IFT in vivo, with mutant trimers containing only one type of motor domain that do not support IFT in vivo. In motility assays, wild type kinesin-2 moved microtubules (MTs) at a rate intermediate between the rates supported by the two mutants. Interestingly, one of the mutants, but not the other mutant or the wild type protein, was observed to drive a persistent counter-clock-wise rotation of the gliding MTs. Thus one of the two motor domains of heterotrimeric kinesin-2 exerts torque as well as axial force as it moves along a MT, which may allow kinesin-2 to control its circumferential position around a MT doublet within the cilium.     

Optimal task-dependent changes of bimanual feedback control and adaptation

The control and adaptation of bimanual movements is often considered to be a function of a fixed set of mechanisms [1, 2]. Here, I show that both feedback control and adaptation change optimally with task goals. Participants reached with two hands to two separate spatial targets (two-cursor condition) or used the same bimanual movements to move a cursor presented at the spatial average location of the two hands to a single target (one-cursor condition). A force field was randomly applied to one of the hands. In the two-cursor condition, online corrections occurred only on the perturbed hand, whereas the other movement was controlled independently. In the one-cursor condition, online correction could be detected on both hands as early as 190 ms after the start. These changes can be shown to be optimal in respect to a simple task-dependent cost function [3]. Adaptation, the influence of a perturbation onto the next movement, also depended on task goals. In the two-cursor condition, only the perturbed hand adapted to a force perturbation [2], whereas in the one-cursor condition, both hands adapted. These findings demonstrate that the central nervous system changes bimanual feedback control and adaptation optimally according to the current task requirements.     

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.     

Speech Misperception: Speaking and Seeing Interfere Differently with Hearing

Speech perception is thought to be linked to speech motor production. This linkage is considered to mediate multimodal aspects of speech perception, such as audio-visual and audio-tactile integration. However, direct coupling between articulatory movement and auditory perception has been little studied. The present study reveals a clear dissociation between the effects of a listener’s own speech action and the effects of viewing another’s speech movements on the perception of auditory phonemes. We assessed the intelligibility of the syllables [pa], [ta], and [ka] when listeners silently and simultaneously articulated syllables that were congruent/incongruent with the syllables they heard. The intelligibility was compared with a condition where the listeners simultaneously watched another’s mouth producing congruent/incongruent syllables, but did not articulate. The intelligibility of [ta] and [ka] were degraded by articulating [ka] and [ta] respectively, which are associated with the same primary articulator (tongue) as the heard syllables. But they were not affected by articulating [pa], which is associated with a different primary articulator (lips) from the heard syllables. In contrast, the intelligibility of [ta] and [ka] was degraded by watching the production of [pa]. These results indicate that the articulatory-induced distortion of speech perception occurs in an articulator-specific manner while visually induced distortion does not. The articulator-specific nature of the auditory-motor interaction in speech perception suggests that speech motor processing directly contributes to our ability to hear speech.     

Sex-specific non-pheromonal taste receptors in Drosophila

Taste receptorshave recently been reported in Drosophila [1] and [2], but little is known of the relation between receptor and response. Morphological studies of the distribution of chemosensory sensilla indicate that the fruit fly has two major sites of gustation: the proboscis and the legs [3]. The taste sensilla on both these sites are similar in structure and each sensillum generally houses four gustatory neurons [4]. Early anatomical observations have demonstrated a sexual dimorphism in the number of tarsal sensilla [5] and in their central projections [6]. We measured the electrophysiological responses of the prothoracic taste sensilla to non-pheromonal substances—salts, sugars and water—and found a clear sexual dimorphism. From the response profile of individual sensilla, we were able to distinguish three types of tarsal sensilla in females as against only two types in males. The female-specific type, which responded specifically to sugar, was absent in males except when male gustatory neurons were genetically feminised. The fact that tarsal gustatory hairs exhibit a sexual dimorphism that affects the perception of non-pheromonal compounds suggests that sexual identity is more complex than has previously been thought [7] and [8].     

THE FUNCTION OF THE BRAIN IN LOCOMOTION OF THE POLYCLAD WORM,YUNGIA AURANTIACA

Coordinated swimming movements in Yungia are not dependent upon the presence of the brain. The neuromuscular mechanism necessary for spontaneous movement and swimming is complete in the body of the animal apart from the brain. Normally this mechanism is set in motion by sensory stimulation arriving by way of the brain. The latter is a region of low threshold and acts as an amplifier by sending the impulses into a great number of channels. When the head is cut off these connections with the sensorium are broken, consequently peripheral stimulation does not have its usual effect. If, however, the motor nerves are stimulated directly as by mechanical stimulation of the median anterior region, then swimming movements result. Also if the threshold of the entire nervous mechanism is lowered by phenol or by an increase in the ion ratios See PDF for Equation and See PDF for Equation then again peripheral stimulation throws the neuromuscular mechanism into activity and swimming movements result.     

The prickle-related gene in vertebrates is essential for gastrulation cell movements

Involving dynamic and coordinated cell movements that cause drastic changes in embryo shape, gastrulation is one of the most important processes of early development. Gastrulation proceeds by various types of cell movements, including convergence and extension, during which polarized axial mesodermal cells intercalate in radial and mediolateral directions and thus elongate the dorsal marginal zone along the anterior-posterior axis [1,2]. Recently, it was reported that a noncanonical Wnt signaling pathway, which is known to regulate planar cell polarity (PCP) in Drosophila [3,4], participates in the regulation of convergent extension movements in Xenopus as well as in the zebrafish embryo [5-8]. The Wnt5a/Wnt11 signal is mediated by members of the seven-pass transmembrane receptor Frizzled (Fz) and the signal transducer Dishevelled (Dsh) through the Dsh domains that are required for the PCP signal [6-8]. It has also been shown that the relocalization of Dsh to the cell membrane is required for convergent extension movements in Xenopus gastrulae. Although it appears that signaling via these components leads to the activation of JNK [9,10] and rearrangement of microtubules, the precise interplay among these intercellular components is largely unknown. In this study, we show that Xenopus prickle (Xpk), a Xenopus homolog of a Drosophila PCP gene [11-13], is an essential component for gastrulation cell movement. Both gain-of-function and loss-of-function of Xpk severely perturbed gastrulation and caused spina bifida embryos without affecting mesodermal differentiation. We also demonstrate that XPK binds to Xenopus Dsh as well as to JNK. This suggests that XPK plays a pivotal role in connecting Dsh function to JNK activation.     

Localization of Motor Neurons and Central Pattern Generators for Motor Patterns Underlying Feeding Behavior in Drosophila Larvae

Motor systems can be functionally organized into effector organs (muscles and glands), the motor neurons, central pattern generators (CPG) and higher control centers of the brain. Using genetic and electrophysiological methods, we have begun to deconstruct the motor system driving Drosophila larval feeding behavior into its component parts. In this paper, we identify distinct clusters of motor neurons that execute head tilting, mouth hook movements, and pharyngeal pumping during larval feeding. This basic anatomical scaffold enabled the use of calcium-imaging to monitor the neural activity of motor neurons within the central nervous system (CNS) that drive food intake. Simultaneous nerve- and muscle-recordings demonstrate that the motor neurons innervate the cibarial dilator musculature (CDM) ipsi- and contra-laterally. By classical lesion experiments we localize a set of CPGs generating the neuronal pattern underlying feeding movements to the subesophageal zone (SEZ). Lesioning of higher brain centers decelerated all feeding-related motor patterns, whereas lesioning of ventral nerve cord (VNC) only affected the motor rhythm underlying pharyngeal pumping. These findings provide a basis for progressing upstream of the motor neurons to identify higher regulatory components of the feeding motor system.     

Cursive writing with smooth pursuit eye movements

The eyes never cease to move: ballistic saccades quickly turn the gaze toward peripheral targets, whereas smooth pursuit maintains moving targets on the fovea where visual acuity is best. Despite the oculomotor system being endowed with exquisite motor abilities, any attempt to generate smooth eye movements against a static background results in saccadic eye movements [1, 2]. Although exceptions to this rule have been reported [3-5], volitional control over smooth eye movements is at best rudimentary. Here, I introduce a novel, temporally modulated visual display, which, although static, sustains smooth eye movements in arbitrary directions. After brief training, participants gain volitional control over smooth pursuit eye movements and can generate digits, letters, words, or drawings at will. For persons deprived of limb movement, this offers a fast, creative, and personal means of linguistic and emotional expression.     

Neuromechanics of muscle synergies for posture and movement

Recent research suggests that the nervous system controls muscles by activating flexible combinations of muscle synergies to produce a wide repertoire of movements. Muscle synergies are like building blocks, defining characteristic patterns of activation across multiple muscles that may be unique to each individual, but perform similar functions. The identification of muscle synergies has strong implications for the organization and structure of the nervous system, providing a mechanism by which task-level motor intentions are translated into detailed, low-level muscle activation patterns. Understanding the complex interplay between neural circuits and biomechanics that give rise to muscle synergies will be crucial to advancing our understanding of neural control mechanisms for movement.