No impact of instructions and feedback on task integration in motor learning

This study examined the effect of instructions and feedback on the integration of two tasks. Task-integration of covarying tasks are thought to help dual-task performance. With complete task integration of covarying dual tasks, a dual-task becomes more like a single task and dual-task costs should be reduced as it is no longer conceptualized as a dual task. We covaried a tracking task with an auditory go/no-go task and tried to manipulate the extent of task-integration by using two different sets of instructions and feedback. A group receiving task-integration promoting instructions and feedback (N = 18) and a group receiving task-separation instructions and feedback (N = 20) trained a continuous tracking task. The tracking task covaried with the auditory go/no-go reaction time task because high-pitch sounds always occurred 250 ms before turns, which has been demonstrated to foster task integration before. The tracking task further contained a repeating segment to investigate implicit learning. Results showed that neither instructions, feedback, nor participants’ conceptualization of performing a single task vs. a dual task significantly affected task-integration. However, the covariation manipulation improved performance in both the tracking and the go/no-go task, exceeding performance in non-covarying and single tasks. We conclude that task-integration between covarying motor tasks is a robust phenomenon that is not influenced by instructions or feedback

The impact of predictability on dual-task performance and implications for resource-sharing accounts.

The aim of this study was to examine the impact of predictability on dual-task performance by systematically manipulating predictability in either one of two tasks, as well as between tasks. According to capacity-sharing accounts of multitasking, assuming a general pool of resources two tasks can draw upon, predictability should reduce the need for resources and allow more resources to be used by the other task. However, it is currently not well understood what drives resource-allocation policy in dual tasks and which resource allocation policies participants pursue. We used a continuous tracking task together with an audiomotor task and manipulated advance visual information about the tracking path in the first experiment and a sound sequence in the second experiments (2a/b). Results show that performance predominantly improved in the predictable task but not in the unpredictable task, suggesting that participants did not invest more resources into the unpredictable task. One possible explanation was that the re-investment of resources into another task requires some relationship between the tasks. Therefore, in the third experiment, we covaried the two tasks by having sounds 250 ms before turning points in the tracking curve. This enabled participants to improve performance in both tasks, suggesting that resources were shared better between tasks

Switch rates vary due to expected payoff but not due to individual risk tendency.

When switching between different tasks, the initiation of task switches may depend on task characteristics (difficulty, salient cues, etc.) or reasons within the person performing the task (decisions, behavioral variability, etc.). The reasons for variance in switching strategies, especially in paradigms where participants are free to choose the order of tasks and the amount of switching between tasks, are not well researched. In this study, we follow up the recent discussion that variance in switching strategies might be partly explained by the characteristics of the person fulfilling the task. We examined whether risk tendency and impulsiveness differentiate individuals in their response (i.e., switch rates and time spent on tasks) to different task characteristics on a tracking-while-typing paradigm. In detail, we manipulated two aspects of loss prospect (i.e., "payoff" as the amount of points that could be lost when tracking was unattended for too long, and "cursor speed" determining the likelihood of such a loss occurring). To account for between-subject variance and within-subject variability in the data, we employed linear mixed effect analyses following the model selection procedure (Bates, Kliegl, et al., 2015). Besides, we tested whether risk tendency can be transformed into a decision parameter which could predict switching strategies when being computationally modelled. We transferred decision parameters from the Decision Field Theory to model "switching thresholds" for each individual. Results show that neither risk tendency nor impulsiveness explain between-subject variance in the paradigm, nonetheless linear mixed-effects models confirmed that within-subject variability plays a significant role for interpreting dual-task data. Our computational model yielded a good model fit, suggesting that the use of a decision threshold parameter for switching may serve as an alternative means to classify different strategies in task switching. [Abstract copyright: Copyright © 2022. Published by Elsevier B.V.

How visual information influences dual-task driving and tracking

The study examined the impact of visual predictability on dual-task performance in driving and tracking tasks. Participants (N = 27) performed a simulated driving task and a pursuit tracking task. In either task, visual predictability was manipulated by systematically varying the amount of advance visual information: in the driving task, participants drove at night with low beam, at night with high beam, or in daylight; in the tracking task, participants saw a white line that specified the future target trajectory for 200, 400 or 800 ms. Concurrently with driving or tracking, participants performed an auditory task. They had to discriminate between two sounds and press a pedal upon hearing the higher sound. Results show that in general, visual predictability benefited driving and tracking; however, dual-task driving performance was best with highest visual predictability (daylight), dual-task tracking performance was best with medium visual predictability (400 ms). Braking/reaction times were higher in dual tasks compared to single tasks, but were unaffected by visual predictability, showing that its beneficial effects did not transfer to the auditory task. In both tasks, manual accuracy decreased around the moment the foot pressed the pedal, indicating interference between tasks. We, therefore, conclude that despite a general beneficial impact of predictability, the integration of visual information seems to be rather task specific, and that interference between driving and audiomotor tasks, and tracking and audiomotor tasks, seems comparable

What is a task? An ideomotor perspective

Although multitasking has been the subject of a large number of papers and experiments, the term task is still not well defined. In this opinion paper, we adopt the ideomotor perspective to define the term task and distinguish it from the terms goal and “action”. In our opinion, actions are movements executed by an actor to achieve a concrete goal. Concrete goals are represented as anticipated sensory consequences that are associated with an action in an ideomotor manner. Concrete goals are nested in a hierarchy of more and more abstract goals, which form the context of the corresponding action. Finally tasks are depersonalized goals, i.e., goals that should be achieved by someone. However tasks can be assigned to a specific person or group of persons, either by a third party or by the person or the group of persons themselves. By accepting this assignment the depersonalized task becomes a personal goal. In our opinion, research on multitasking needs to confine its scope to the analysis of concrete tasks, which result in concrete goals as anticipated sensory consequences of the corresponding action. We further argue that the distinction between dual- and single-tasking is dependent on the subjective conception of the task assignment, the goal representation and previous experience. Finally, we conclude that it is not the tasks, but the performing of the tasks, i.e. the actions that cause costs in multi-tasking experiments

Why prediction matters in multitasking and how predictability can improve it

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission. Prediction1 is an omnipresent principle of human behavior that can be fostered by predictability in the environment. We regard prediction as the mental representation of future event states or anticipated action consequences, and predictability as a property of certain events in the environment. On the assumption that predictability and prediction are beneficial for any kind of behavior, we argue that their benefits to relieving the human system are most evident when encountering multiple tasks. However, we predicate that their impact on multitasking is understudied and so we aim at dissociating prediction and predictability within multitasking contexts and at outlining different sources of predictability that have not been conflated under this term so far. From our opinion it follows that future multitasking research requires experimental designs and analyses that consider and unveil principles of prediction and the impact of predictability on multitasking performance

Dissolved Organic Carbon in the North Atlantic Meridional Overturning Circulation

The quantitative role of the Atlantic Meridional Overturning Circulation (AMOC) in dissolved organic carbon (DOC) export is evaluated by combining DOC measurements with observed water mass transports. In the eastern subpolar North Atlantic, both upper and lower limbs of the AMOC transport high-DOC waters. Deep water formation that connects the two limbs of the AMOC results in a high downward export of non-refractory DOC (197 Tg-C·yr-1). Subsequent remineralization in the lower limb of the AMOC, between subpolar and subtropical latitudes, consumes 72% of the DOC exported by the whole Atlantic Ocean. The contribution of DOC to the carbon sequestration in the North Atlantic Ocean (62 Tg-C·yr-1) is considerable and represents almost a third of the atmospheric CO 2 uptake in the region

Dosage Effects of Cohesin Regulatory Factor PDS5 on Mammalian Development: Implications for Cohesinopathies

Cornelia de Lange syndrome (CdLS), a disorder caused by mutations in cohesion proteins, is characterized by multisystem developmental abnormalities. PDS5, a cohesion protein, is important for proper chromosome segregation in lower organisms and has two homologues in vertebrates (PDS5A and PDS5B). Pds5B mutant mice have developmental abnormalities resembling CdLS; however the role of Pds5A in mammals and the association of PDS5 proteins with CdLS are unknown. To delineate genetic interactions between Pds5A and Pds5B and explore mechanisms underlying phenotypic variability, we generated Pds5A-deficient mice. Curiously, these mice exhibit multiple abnormalities that were previously observed in Pds5B-deficient mice, including cleft palate, skeletal patterning defects, growth retardation, congenital heart defects and delayed migration of enteric neuron precursors. They also frequently display renal agenesis, an abnormality not observed in Pds5B−/− mice. While Pds5A−/− and Pds5B−/− mice die at birth, embryos harboring 3 mutant Pds5 alleles die between E11.5 and E12.5 most likely of heart failure, indicating that total Pds5 gene dosage is critical for normal development. In addition, characterization of these compound homozygous-heterozygous mice revealed a severe abnormality in lens formation that does not occur in either Pds5A−/− or Pds5B−/− mice. We further identified a functional missense mutation (R1292Q) in the PDS5B DNA-binding domain in a familial case of CdLS, in which affected individuals also develop megacolon. This study shows that PDS5A and PDS5B functions other than those involving chromosomal dynamics are important for normal development, highlights the sensitivity of key developmental processes on PDS5 signaling, and provides mechanistic insights into how PDS5 mutations may lead to CdLS

Gene discovery in EST sequences from the wheat leaf rust fungus Puccinia triticina sexual spores, asexual spores and haustoria, compared to other rust and corn smut fungi

© 2011 Xu et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.DOI: 10.1186/1471-2164-12-161Background.Rust fungi are biotrophic basidiomycete plant pathogens that cause major diseases on plants and trees world-wide, affecting agriculture and forestry. Their biotrophic nature precludes many established molecular genetic manipulations and lines of research. The generation of genomic resources for these microbes is leading to novel insights into biology such as interactions with the hosts and guiding directions for breakthrough research in plant pathology. Results. To support gene discovery and gene model verification in the genome of the wheat leaf rust fungus, Puccinia triticina (Pt), we have generated Expressed Sequence Tags (ESTs) by sampling several life cycle stages. We focused on several spore stages and isolated haustorial structures from infected wheat, generating 17,684 ESTs. We produced sequences from both the sexual (pycniospores, aeciospores and teliospores) and asexual (germinated urediniospores) stages of the life cycle. From pycniospores and aeciospores, produced by infecting the alternate host, meadow rue (Thalictrum speciosissimum), 4,869 and 1,292 reads were generated, respectively. We generated 3,703 ESTs from teliospores produced on the senescent primary wheat host. Finally, we generated 6,817 reads from haustoria isolated from infected wheat as well as 1,003 sequences from germinated urediniospores. Along with 25,558 previously generated ESTs, we compiled a database of 13,328 non-redundant sequences (4,506 singlets and 8,822 contigs). Fungal genes were predicted using the EST version of the self-training GeneMarkS algorithm. To refine the EST database, we compared EST sequences by BLASTN to a set of 454 pyrosequencing-generated contigs and Sanger BAC-end sequences derived both from the Pt genome, and to ESTs and genome reads from wheat. A collection of 6,308 fungal genes was identified and compared to sequences of the cereal rusts, Puccinia graminis f. sp. tritici (Pgt) and stripe rust, P. striiformis f. sp. tritici (Pst), and poplar leaf rust Melampsora species, and the corn smut fungus, Ustilago maydis (Um). While extensive homologies were found, many genes appeared novel and species-specific; over 40% of genes did not match any known sequence in existing databases. Focusing on spore stages, direct comparison to Um identified potential functional homologs, possibly allowing heterologous functional analysis in that model fungus. Many potentially secreted protein genes were identified by similarity searches against genes and proteins of Pgt and Melampsora spp., revealing apparent orthologs. Conclusions. The current set of Pt unigenes contributes to gene discovery in this major cereal pathogen and will be invaluable for gene model verification in the genome sequence