Duplication of the PMP22 gene in 17p partial trisomy patients with Charcot-Marie-Tooth type-1A neuropathy

Autosomal dominant Charcot-Marie-Tooth type-1A neuropathy (CMT1A) is a demyelinating peripheral nerve disorder that is commonly associated with a submicroscopic tandem DNA duplication of a 1.5-Mb region of 17p11.2p12 that contains the peripheral myelin gene PMP22. Clinical features of CMT1A include progressive distal muscle atrophy and weakness, foot and hand deformities, gait abnormalities, absent reflexes, and the completely penetrant electrophysiologic phenotype of symmetric reductions in motor nerve conduction velocities (NCVs). Molecular and fluorescence in situ hybridization (FISH) analyses were performed to determine the duplication status of the PMP22 gene in four patients with rare cytogenetic duplications of 17p. Neuropathologic features of CMT1A were seen in two of these four patients, in addition to the complex phenotype associated with 17p partial trisomy. Our findings show that the CMT1A phenotype of reduced NCV is specifically associated with PMP22 gene duplication, thus providing further support for the PMP22 gene dosage mechanism for CMT1A. Received: 3 May 1995 / Revised: 1 August 1995     

Reaction null-space filter: extracting reactionless synergies for optimal postural balance from motion capture data

This paper introduces the notion of a reactionless synergy: a postural variation for a specific motion pattern/strategy, whereby the movements of the segments do not alter the force/moment balance at the feet. Given an optimal initial posture in terms of stability, a reactionless synergy can ensure optimality throughout the entire movement. Reactionless synergies are derived via a dynamical model wherein the feet are regarded to be unfixed. Though in contrast with the conventional fixed-feet models, this approach has the advantage of exhibiting the reactions at the feet explicitly. The dynamical model also facilitates a joint-space decomposition scheme yielding two motion components: the reactionless synergy and an orthogonal complement responsible for the dynamical coupling between the feet and the support. Since the reactionless synergy provides the basis (a feedforward control component) for optimal balance control, it may play an important role when evaluating balance abnormalities or when assessing optimality in balance control. We show how to apply the proposed method for analysis of motion capture data obtained from three voluntary movement patterns in the sagittal plane: squat, sway, and forward bend.     

Biomechanical mechanism of lateral trunk lean gait for knee osteoarthritis patients

The biomechanical mechanism of lateral trunk lean gait employed to reduce external knee adduction moment (KAM) for knee osteoarthritis (OA) patients is not well known. This mechanism may relate to the center of mass (COM) motion. Moreover, lateral trunk lean gait may affect motor control of the COM displacement. Uncontrolled manifold (UCM) analysis is an evaluation index used to understand motor control and variability of the motor task. Here we aimed to clarify the biomechanical mechanism to reduce KAM during lateral trunk lean gait and how motor variability controls the COM displacement. Twenty knee OA patients walked under two conditions: normal and lateral trunk lean gait conditions. UCM analysis was performed with respect to the COM displacement in the frontal plane. We also determined how the variability is structured with regards to the COM displacement as a performance variable. The peak KAM under lateral trunk lean gait was lower than that under normal gait. The reduced peak KAM observed was accompanied by medially shifted knee joint center, shortened distance of the center of pressure to knee joint center, and shortened distance of the knee–ground reaction force lever arm during the stance phase. Knee OA patients with lateral trunk lean gait could maintain kinematic synergy by utilizing greater segmental configuration variance to the performance variable. However, the COM displacement variability of lateral trunk lean gait was larger than that of normal gait. Our findings may provide clinical insights to effectively evaluate and prescribe gait modification training for knee OA patients.     

A Mutation in PMP2 Causes Dominant Demyelinating Charcot-Marie-Tooth Neuropathy

Charcot-Marie-Tooth disease (CMT) is a heterogeneous group of peripheral neuropathies with diverse genetic causes. In this study, we identified p.I43N mutation in PMP2 from a family exhibiting autosomal dominant demyelinating CMT neuropathy by whole exome sequencing and characterized the clinical features. The age at onset was the first to second decades and muscle atrophy started in the distal portion of the leg. Predominant fatty replacement in the anterior and lateral compartment was similar to that in CMT1A caused by PMP22 duplication. Sural nerve biopsy showed onion bulbs and degenerating fibers with various myelin abnormalities. The relevance of PMP2 mutation as a genetic cause of dominant CMT1 was assessed using transgenic mouse models. Transgenic mice expressing wild type or mutant (p.I43N) PMP2 exhibited abnormal motor function. Electrophysiological data revealed that both mice had reduced motor nerve conduction velocities (MNCV). Electron microscopy revealed that demyelinating fibers and internodal lengths were shortened in both transgenic mice. These data imply that overexpression of wild type as well as mutant PMP2 also causes the CMT1 phenotype, which has been documented in the PMP22. This report might expand the genetic and clinical features of CMT and a further mechanism study will enhance our understanding of PMP2-associated peripheral neuropathy.     

Predicting dynamic postural instability using center of mass time-to-contact information

Our purpose was to determine whether spatiotemporal measures of center of mass motion relative to the base of support boundary could predict stepping strategies after upper-body postural perturbations in humans. We expected that inclusion of center of mass acceleration in such time-to-contact (TtC) calculations would give better predictions and more advanced warning of perturbation severity. TtC measures were compared with traditional postural variables, which do not consider support boundaries, and with an inverted pendulum model of dynamic stability developed by Hof et al. [2005. The condition for dynamic stability. Journal of Biomechanics 38, 1-8]. A pendulum was used to deliver sequentially increasing perturbations to 10 young adults, who were strapped to a wooden backboard that constrained motion to sagittal-plane rotation about the ankle joint. Subjects were instructed to resist the perturbations, stepping only if necessary to prevent a fall. Peak center of mass and center of pressure velocity and acceleration demonstrated linear increases with postural challenge. In contrast, boundary-relevant minimum TtC values decreased nonlinearly with postural challenge, enabling prediction of stepping responses using quadratic equations. When TtC calculations incorporated center of mass acceleration, the quadratic fits were better and gave more accurate predictions of the TtC values that would trigger stepping responses. In addition, TtC minima occurred earlier with acceleration inclusion, giving more advanced warning of perturbation severity. Our results were in agreement with TtC predictions based on Hof's model, and suggest that TtC may function as a control parameter, influencing the postural control system's decision to transition from a stationary base of support to a stepping strategy.     

Micromechanics and ultrastructure of actin filament networks crosslinked by human fascin: a comparison with alpha-actinin.

Fascin is an actin crosslinking protein that organizes actin filaments into tightly packed bundles believed to mediate the formation of cellular protrusions and to provide mechanical support to stress fibers. Using quantitative rheological methods, we studied the evolution of the mechanical behavior of filamentous actin (F-actin) networks assembled in the presence of human fascin. The mechanical properties of F-actin/fascin networks were directly compared with those formed by alpha-actinin, a prototypical actin filament crosslinking/bundling protein. Gelation of F-actin networks in the presence of fascin (fascin to actin molar ratio >1:50) exhibits a non-monotonic behavior characterized by a burst of elasticity followed by a slow decline over time. Moreover, the rate of gelation shows a non-monotonic dependence on fascin concentration. In contrast, alpha-actinin increased the F-actin network elasticity and the rate of gelation monotonically. Time-resolved multiple-angle light scattering and confocal and electron microscopies suggest that this unique behavior is due to competition between fascin-mediated crosslinking and side-branching of actin filaments and bundles, on the one hand, and delayed actin assembly and enhanced network micro-heterogeneity, on the other hand. The behavior of F-actin/fascin solutions under oscillatory shear of different frequencies, which mimics the cell's response to forces applied at different rates, supports a key role for fascin-mediated F-actin side-branching. F-actin side-branching promotes the formation of interconnected networks, which completely inhibits the motion of actin filaments and bundles. Our results therefore show that despite sharing seemingly similar F-actin crosslinking/bundling activity, alpha-actinin and fascin display completely different mechanical behavior. When viewed in the context of recent microrheological measurements in living cells, these results provide the basis for understanding the synergy between multiple crosslinking proteins, and in particular the complementary mechanical roles of fascin and alpha-actinin in vivo.     

Formation and control of optimal trajectory in human multijoint arm movement

In this paper, we study trajectory planning and control in voluntary, human arm movements. When a hand is moved to a target, the central nervous system must select one specific trajectory among an infinite number of possible trajectories that lead to the target position. First, we discuss what criterion is adopted for trajectory determination. Several researchers measured the hand trajectories of skilled movements and found common invariant features. For example, when moving the hand between a pair of targets, subjects tended to generate roughly straight hand paths with bell-shaped speed profiles. On the basis of these observations and dynamic optimization theory, we propose a mathematical model which accounts for formation of hand trajectories. This model is formulated by defining an objective function, a measure of performance for any possible movement: square of the rate of change of torque integrated over the entire movement. That is, the objective function CT is defined as follows: (formula; see text) We overcome this difficult by developing an iterative scheme, with which the optimal trajectory and the associated motor command are simultaneously computed. To evaluate our model, human hand trajectories were experimentally measured under various behavioral situations. These results supported the idea that the human hand trajectory is planned and controlled in accordance with the minimum torque-change criterion.     

Neuronal Mechanisms Encoding Global-to-Fine Information in Inferior-Temporal Cortex

Sugase et al. found that global information is represented at the initial transient firing of a single face-responsive neuron in inferior-temporal (IT) cortex, and that finer information is represented at the subsequent sustained firing. A feed-forward model and an attractor network are conceivable models to reproduce this dynamics. The attractor network, specifically an associative memory model, is employed to elucidate the neuronal mechanisms producing the dynamics. The results obtained by computer simulations show that a state of neuronal population initially approaches to a mean state of similar memory patterns, and that it finally converges to a memory pattern. This dynamics qualitatively coincides with that of face-responsive neurons. The dynamics of a single neuron in the model also coincides with that of a single face-responsive neuron. Furthermore, we propose two physiological experiments and predict the results from our model. Both predicted results are not explainable by the feed-forward model. Therefore, if the results obtained by actual physiological experiments coincide with our predicted results, the attractor network might be the neuronal mechanisms producing the dynamics of face-responsive neurons.     

Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.     

Optimization of muscle activity for task-level goals predicts complex changes in limb forces across biomechanical contexts

Optimality principles have been proposed as a general framework for understanding motor control in animals and humans largely based on their ability to predict general features movement in idealized motor tasks. However, generalizing these concepts past proof-of-principle to understand the neuromechanical transformation from task-level control to detailed execution-level muscle activity and forces during behaviorally-relevant motor tasks has proved difficult. In an unrestrained balance task in cats, we demonstrate that achieving task-level constraints center of mass forces and moments while minimizing control effort predicts detailed patterns of muscle activity and ground reaction forces in an anatomically-realistic musculoskeletal model. Whereas optimization is typically used to resolve redundancy at a single level of the motor hierarchy, we simultaneously resolved redundancy across both muscles and limbs and directly compared predictions to experimental measures across multiple perturbation directions that elicit different intra- and interlimb coordination patterns. Further, although some candidate task-level variables and cost functions generated indistinguishable predictions in a single biomechanical context, we identified a common optimization framework that could predict up to 48 experimental conditions per animal (n = 3) across both perturbation directions and different biomechanical contexts created by altering animals' postural configuration. Predictions were further improved by imposing experimentally-derived muscle synergy constraints, suggesting additional task variables or costs that may be relevant to the neural control of balance. These results suggested that reduced-dimension neural control mechanisms such as muscle synergies can achieve similar kinetics to the optimal solution, but with increased control effort (≈2×) compared to individual muscle control. Our results are consistent with the idea that hierarchical, task-level neural control mechanisms previously associated with voluntary tasks may also be used in automatic brainstem-mediated pathways for balance.     

Stimulus and network dynamics collide in a ratiometric model of the antennal lobe macroglomerular complex

Time is considered to be an important encoding dimension in olfaction, as neural populations generate odour-specific spatiotemporal responses to constant stimuli. However, during pheromone mediated anemotactic search insects must discriminate specific ratios of blend components from rapidly time varying input. The dynamics intrinsic to olfactory processing and those of naturalistic stimuli can therefore potentially collide, thereby confounding ratiometric information. In this paper we use a computational model of the macroglomerular complex of the insect antennal lobe to study the impact on ratiometric information of this potential collision between network and stimulus dynamics. We show that the model exhibits two different dynamical regimes depending upon the connectivity pattern between inhibitory interneurons (that we refer to as fixed point attractor and limit cycle attractor), which both generate ratio-specific trajectories in the projection neuron output population that are reminiscent of temporal patterning and periodic hyperpolarisation observed in olfactory antennal lobe neurons. We compare the performance of the two corresponding population codes for reporting ratiometric blend information to higher centres of the insect brain. Our key finding is that whilst the dynamically rich limit cycle attractor spatiotemporal code is faster and more efficient in transmitting blend information under certain conditions it is also more prone to interference between network and stimulus dynamics, thus degrading ratiometric information under naturalistic input conditions. Our results suggest that rich intrinsically generated network dynamics can provide a powerful means of encoding multidimensional stimuli with high accuracy and efficiency, but only when isolated from stimulus dynamics. This interference between temporal dynamics of the stimulus and temporal patterns of neural activity constitutes a real challenge that must be successfully solved by the nervous system when faced with naturalistic input.     

Chaotic neural network applied to two-dimensional motion control

Chaotic dynamics generated in a chaotic neural network model are applied to 2-dimensional (2-D) motion control. The change of position of a moving object in each control time step is determined by a motion function which is calculated from the firing activity of the chaotic neural network. Prototype attractors which correspond to simple motions of the object toward four directions in 2-D space are embedded in the neural network model by designing synaptic connection strengths. Chaotic dynamics introduced by changing system parameters sample intermediate points in the high-dimensional state space between the embedded attractors, resulting in motion in various directions. By means of adaptive switching of the system parameters between a chaotic regime and an attractor regime, the object is able to reach a target in a 2-D maze. In computer experiments, the success rate of this method over many trials not only shows better performance than that of stochastic random pattern generators but also shows that chaotic dynamics can be useful for realizing robust, adaptive and complex control function with simple rules.     

Twirling Motion of Actin Filaments in Gliding Assays with Nonprocessive Myosin Motors

We present a model study of gliding assays in which actin filaments are moved by nonprocessive myosin motors. We show that even if the power stroke of the motor protein has no lateral component, the filaments will rotate around their axis while moving over the surface. Notably, the handedness of this twirling motion is opposite from that of the actin filament structure. It stems from the fact that the gliding actin filament has target zones, where its subunits point toward the surface and are therefore more accessible for myosin heads. Each myosin head has a higher binding probability before it reaches the center of the target zone than afterwards, which results in a left-handed twirling. We present a stochastic simulation and an approximative analytical solution. The calculated pitch of the twirling motion depends on the filament velocity (ATP concentration). It reaches ∼400 nm for low speeds and increases with higher speeds.     

A unified model of spatial and episodic memory

Medial temporal lobe structures including the hippocampus are implicated by separate investigations in both episodic memory and spatial function. We show that a single recurrent attractor network can store both the discrete memories that characterize episodic memory and the continuous representations that characterize physical space. Combining both types of representation in a single network is actually necessary if objects and where they are located in space must be stored. We thus show that episodic memory and spatial theories of medial temporal lobe function can be combined in a unified model.     

Changes of mind in an attractor network of decision-making

Attractor networks successfully account for psychophysical and neurophysiological data in various decision-making tasks. Especially their ability to model persistent activity, a property of many neurons involved in decision-making, distinguishes them from other approaches. Stable decision attractors are, however, counterintuitive to changes of mind. Here we demonstrate that a biophysically-realistic attractor network with spiking neurons, in its itinerant transients towards the choice attractors, can replicate changes of mind observed recently during a two-alternative random-dot motion (RDM) task. Based on the assumption that the brain continues to evaluate available evidence after the initiation of a decision, the network predicts neural activity during changes of mind and accurately simulates reaction times, performance and percentage of changes dependent on difficulty. Moreover, the model suggests a low decision threshold and high incoming activity that drives the brain region involved in the decision-making process into a dynamical regime close to a bifurcation, which up to now lacked evidence for physiological relevance. Thereby, we further affirmed the general conformance of attractor networks with higher level neural processes and offer experimental predictions to distinguish nonlinear attractor from linear diffusion models.     

Role of motor cortex in coordinating multi-joint movements: is it time for a new paradigm?

Reaching movements to spatial targets require motor patterns at the shoulder to be coordinated carefully with those at the elbow to smoothly move the hand through space. While the motor cortex is involved in this volitional task, considerable debate remains about how this cortical region participates in planning and controlling movement. This article reviews two opposing interpretations of motor cortical function during multi-joint movements. On the one hand, studies performed predominantly on single-joint movement generally support the notion that motor cortical activity is intimately involved in generating motor patterns at a given joint. In contrast, studies on reaching demonstrate correlations between motor cortical activity and features of movement related to the hand, suggesting that the motor cortex may be involved in more global features of the task. Although this latter paradigm involves a multi-joint motor task in which neural activity is correlated with features of movement related to the hand, this neural activity is also correlated to other movement variables. Therefore it is difficult to assess if and how the motor cortex contributes to the coordination of motor patterns at different joints. In particular, present paradigms cannot assess whether motor cortical activity contributes to the control of one joint or multiple joints during whole-arm tasks. The final point discussed in this article is the development of a new experimental device (KINARM) that can both monitor and manipulate the mechanics of the shoulder and elbow independently during multi-joint motor tasks. It is hoped that this new device will provide a new approach for examining how the motor cortex is involved in motor coordination.     

Visually guided orientation in flies: case studies in computational neuroethology

To understand the functioning of nervous systems and, in particular, how they control behaviour we must bridge many levels of complexity from molecules, cells and synapses to perception behaviour. Although experimental analysis is a precondition for understanding by nervous systems, it is in no way sufficient. The understanding is aided at all levels of complexity by modelling. Modelling proved to be an inevitable tool to test the experimentally established hypotheses. In this review it will by exemplified by three case studies that the appropriate level of modelling needs to be adjusted to the particular computational problems that are to be solved. (1) Specific features of the highly virtuosic pursuit behaviour of male flies can be understood on the basis of a phenomenological model that relates the visual input to the motor output. (2) The processing of retinal image motion as is experienced by freely moving animals can be understood on the basis of a model consisting of algorithmic components and components which represent a simple equivalent circuit of nerve cells. (3) Behaviourally relevant features of the reliability of encoding of visual motion information can be understood by modelling the transformation of postsynaptic potentials into sequences of spike trains.     

The reversible oxidation of vicinal SH groups in 4-aminobutyrate aminotransferase. Probes of conformational changes

4-Aminobutyrate aminotransferase is inactivated by preincubation with iodosobenzoate at pH 7. The reaction of 2 SH residues/dimer resulted in formation of an oligomeric species of Mr = 100,000 detectable by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The subunits cross-linked via a disulfide bond are dissociated by addition of 2-mercaptoethanol which also restores full catalytic activity (Choi, S. Y., and Churchich, J.E. (1985) J. Biol. Chem. 260, 993-997). The substrate 2-oxoglutarate prevents inactivation of the enzyme by iodosobenzoate and the subsequent formation of one disulfide bond, whereas 4-aminobutyrate has no effect on the reactivity of SH groups with iodosobenzoate. Modified 4-aminobutyrate aminotransferase (containing 1 disulfide bond) catalyzes a half-transamination reaction; but it is unable to react with 2-oxoglutarate to generate the aldimine form of the enzyme. The spectroscopic properties (fluorescence yield and polarization of fluorescence) of PMP bound to the modified enzyme are different from those of pyridoxamine phosphate (PMP) bound to the native enzyme. The polarization of fluorescence values of PMP bound to the cross-linked enzyme, excited over the spectral range 310-370 nm, are greater (25%) than those of the cofactor of the native enzyme. An increase in the polarization values implies that the motion of PMP is restricted when the subunits are cross-linked via a disulfide bond.