How a Lateralized Brain Supports Symmetrical Bimanual Tasks

A large repertoire of natural object manipulation tasks require precisely coupled symmetrical opposing forces by both hands on a single object. We asked how the lateralized brain handles this basic problem of spatial and temporal coordination. We show that the brain consistently appoints one of the hands as prime actor while the other assists, but the choice of acting hand is flexible. When study participants control a cursor by manipulating a tool held freely between the hands, the left hand becomes prime actor if the cursor moves directionally with the left-hand forces, whereas the right hand primarily acts if it moves with the opposing right-hand forces. In neurophysiological (electromyography, transcranial magnetic brain stimulation) and functional magnetic resonance brain imaging experiments we demonstrate that changes in hand assignment parallels a midline shift of lateralized activity in distal hand muscles, corticospinal pathways, and primary sensorimotor and cerebellar cortical areas. We conclude that the two hands can readily exchange roles as dominant actor in bimanual tasks. Spatial relationships between hand forces and goal motions determine hand assignments rather than habitual handedness. Finally, flexible role assignment of the hands is manifest at multiple levels of the motor system, from cortical regions all the way down to particular muscles

Influence of Mapping Rule on Tool Movements during Performance with Left-Hand and Right-Hand Maps

<p>Superimposed time traces of longitudinal force and lateral tool movement (upper panels) and of twist force and rotational tool movement (lower panels) from a single participant during the last 20 s of target chasing in the first experiment; <i>r_LO</i> and <i>r_TW</i> indicate hand-asymmetry indices for longitudinal and twist forces. Bottom trace represents instances of target hits (spikes). For the last 20 s of runs by all participants and mapping rules, the slope coefficients of the linear regressions indicated that the tool moved 0.84 (0.28–1.23) mm/N longitudinal force and rotated 0.84 (0.36–1.42) °/N twist force (median and 25th–75th percentile). The corresponding values for the 30-s periods of target chasing for which fMRI data were analyzed (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040158#pbio-0040158-g005" target="_blank">Figure 5</a>A and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040158#pbio-0040158-g005" target="_blank">5</a>B), where the wrists of the participants were strapped, were 0.28 (0.19–0.68) mm/N and 0.63 (0.42–1.04) °/N. </p

The Bimanual Target-Chasing Task and Flexible Role Assignment of the Hands

<div><p>(A) Mappings between applied forces and cursor movements (top graph). With the left-hand map, the cursor moved horizontally in the direction of the longitudinal force applied by the left hand (solid purple arrows). A counter-clockwise twist force applied between the handles (as if unscrewing the lid of a jar) moved the cursor upward (solid green arrows). With the right-hand map the cursor moved in the opposite directions and thus in the direction of the forces of the right hand.</p> <p>(B and C) Performance under each mapping rule shown for a complete first session with 602 hits and from the last 100 hits of a second session. Superimposed thin lines show hit time and path index for each participant as a function of target number (data median-filtered over a ± 10-s period around each hit). Solid curve give medians across participants. Inserts in (C) exemplify cursor trajectories with a median path index of 4.6 and 1.4 across 10 target transitions. The targets, distributed about uniformly over the screen, were located 5.1 ± 2.1° (mean ± 1 SD) visual angle from its center, which corresponded to 2.2 ± 0.3 N force applied tangentially to the surfaces of the handles.</p> <p>(D and E) Hand-asymmetry indices computed for a sliding ± 10-s time window. Horizontal lines give the upper and lower 95% confidence limit of the index, postulating that hand selection would have occurred randomly. A significant positive and negative index indicates left and right-hand primarily acting, respectively.</p></div

Premotor Cortical Areas with Increased BOLD Responses with Both the Left- and the Right-Hand Map Overlaid on Coronal Slices of the MNI T1-Weighted Brain Template

<p>For the left hemisphere (L), significant activations ( <i>p</i> < 0.01, FWE-corrected) occurred in one cluster (443 voxels) with two maxima in precentral gyrus (#2 and #4; BA 6), in one single-peak cluster (153 voxels) in superior frontal gyrus (#3; BA 6), in one cluster (281 voxels) with two maxima in medial frontal gyrus (#5 and #6; BA 6), and in one small single-peak cluster (29 voxels) in left inferior frontal gyrus (#1; BA 44). In the right hemisphere (R), there was one cluster (303 voxels) with three maxima, one of which was located in the precentral gyrus outside the cluster delineated by left-hand-map > right-hand-map contrast (#7; BA 6). Solid black lines in the left and right hemisphere outline the clusters identified with the right-hand-map > left-hand-map and left-hand-map > right-hand-map contrasts, respectively (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040158#pbio-0040158-g004" target="_blank">Figure 4</a>C). Histograms give percent BOLD signal change relative to mean of session for the local maxima of identified clusters. Red and blue columns refer to left- and right-hand maps, respectively. Column height gives data averaged across participants and error bar ± 1SEM ( <i>n</i> = 16). Coordinates (X, Y, Z in MNI stereotaxic space) and <i>t</i>₍₃₀₎ values for the maxima are presented below each histogram. </p

Development of a Modeling Architecture Incorporating the Industry 4.0 View for a Company in the Gas Sector

Part 7: Cyber-Physical SystemsInternational audienceIndustry 4.0 is a fast growing concept which has started to gain ground over the last few years and strives to achieve a higher and more efficient production rate through the usage of automations. This concept is directly correlated with Business Process Management because its implementation concerns the improvement of business processes. Business Process Modeling is a tool of Business Process Management which can depict the processes of an organization in order to be elaborated and improved. For that reason models are widely used for the better understanding of processes and as a first step of new concepts insertion, such as Industry 4.0, in an organization. Hence, a comprehensive framework of a modeling architecture is essential for a company which desires the transition to new concepts according to its needs, its processes and its structure. In this paper, a complete architecture which proposed in a company activating in gas industry is presented including the appropriate models for the recording of business processes and how Industry 4.0 principles could be incorporated to them

A Dynamic Approach to Multi-stage Job Shop Scheduling in an Industry 4.0-Based Flexible Assembly System

Part 7: Operations Planning, Scheduling and ControlInternational audienceIndustry 4.0 technology is based on the concepts of flexibility and dynamic assembly system design. This enables new production strategies and creates new challenges for job shop scheduling. In particular, manufacturing processes for different customer orders may have individual machine structures whereas the flexible stations are able to execute different functions subject to individual sets of operations within the jobs. This study develops a control approach to job shop scheduling in a customized manufacturing process and job sequencing of operations within the jobs. The developed approach presents a contribution to flexible distributed scheduling in the emerging field of Industry 4.0-based innovative production systems