9 resultados para Task Complexity

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Introduction: Nocturnal dreams can be considered as a kind of simulation of the real world on a higher cognitive level (Erlacher & Schredl, 2008). Within lucid dreams, the dreamer is aware of the dream state and thus able to control the ongoing dream content. Previous studies could demonstrate that it is possible to practice motor tasks during lucid dreams and doing so improved performance while awake (Erlacher & Schredl, 2010). Even though lucid dream practice might be a promising kind of cognitive rehearsal in sports, little is known about the characteristics of actions in lucid dreams. The purpose of the present study was to explore the relationship between time in dreams and wakefulness because in an earlier study (Erlacher & Schredl, 2004) we found that performing squads took lucid dreamers 44.5 % more time than in the waking state while for counting the same participants showed no differences between dreaming and wakefulness. To find out if the task modality, the task length or the task complexity require longer times in lucid dreams than in wakefulness three experiments were conducted. Methods: In the first experiment five proficient lucid dreamers spent two to three non-consecutive nights in the sleep laboratory with polysomnographic recording to control for REM sleep and determine eye signals. Participants counted from 1-10, 1-20 and 1-30 in wakefulness and in their lucid dreams. While dreaming they marked onset of lucidity as well as beginning and end of the counting task with a Left-Right-Left-Right eye movement and reported their dreams after being awakened. The same procedure was used for the second experiment with seven lucid dreamers except that they had to walk 10, 20 or 30 steps. In the third experiment nine participants performed an exercise involving gymnastics elements such as various jumps and a roll. To control for length of the task the gymnastic exercise in the waking state lasted about the same time as walking 10 steps. Results: As a general result we found – as in the study before – that performing a task in the lucid dream requires more time than in wakefulness. This tendency was found for all three tasks. However, there was no difference for the task modality (counting vs. motor task). Also the relative time for the different lengths of the tasks showed no difference. And finally, the more complex motor task (gymnastic routine) did not require more time in lucid dreams than the simple motor task. Discussion/Conclusion: The results showed that there is a robust effect of time in lucid dreams compared to wakefulness. The three experiments could not explain that those differences are caused by task modality, task length or task complexity. Therefore further possible candidates needs to be investigated e.g. experience in lucid dreaming or psychological variables. References: Erlacher, D. & Schredl, M. (2010). Practicing a motor task in a lucid dream enhances subsequent performance: A pilot study. The Sport Psychologist, 24(2), 157-167. Erlacher, D. & Schredl, M. (2008). Do REM (lucid) dreamed and executed actions share the same neural substrate? International Journal of Dream Research, 1(1), 7-13. Erlacher, D. & Schredl, M. (2004). Time required for motor activity in lucid dreams. Perceptual and Motor Skills, 99, 1239-1242.

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The relationship between time in dreams and real time has intrigued scientists for centuries. The question if actions in dreams take the same time as in wakefulness can be tested by using lucid dreams where the dreamer is able to mark time intervals with prearranged eye movements that can be objectively identified in EOG recordings. Previous research showed an equivalence of time for counting in lucid dreams and in wakefulness (LaBerge, 1985; Erlacher and Schredl, 2004), but Erlacher and Schredl (2004) found that performing squats required about 40% more time in lucid dreams than in the waking state. To find out if the task modality, the task length, or the task complexity results in prolonged times in lucid dreams, an experiment with three different conditions was conducted. In the first condition, five proficient lucid dreamers spent one to three non-consecutive nights in the sleep laboratory. Participants counted to 10, 20, and 30 in wakefulness and in their lucid dreams. Lucidity and task intervals were time stamped with left-right-left-right eye movements. The same procedure was used for these condition where eight lucid dreamers had to walk 10, 20, or 30 steps. In the third condition, eight lucid dreamers performed a gymnastics routine, which in the waking state lasted the same time as walking 10 steps. Again, we found that performing a motor task in a lucid dream requires more time than in wakefulness. Longer durations in the dream state were present for all three tasks, but significant differences were found only for the tasks with motor activity (walking and gymnastics). However, no difference was found for relative times (no disproportional time effects) and a more complex motor task did not result in more prolonged times. Longer durations in lucid dreams might be related to the lack of muscular feedback or slower neural processing during REM sleep. Future studies should explore factors that might be associated with prolonged durations.

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We investigate a recently proposed model for decision learning in a population of spiking neurons where synaptic plasticity is modulated by a population signal in addition to reward feedback. For the basic model, binary population decision making based on spike/no-spike coding, a detailed computational analysis is given about how learning performance depends on population size and task complexity. Next, we extend the basic model to n-ary decision making and show that it can also be used in conjunction with other population codes such as rate or even latency coding.

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Individual learning is central to the success of the transition phase in software mainte-nance offshoring projects. However, little is known on how learning activities, such as on-the-job training and formal presentations, are effectively combined during the tran-sition phase. In this study, we present and test propositions derived from cognitive load theory. The results of a multiple-case study suggest that learning effectiveness was highest when learning tasks such as authentic maintenance requests were used. Con-sistent with cognitive load theory, learning tasks were most effective when they imposed moderate cognitive load. Our data indicate that cognitive load was influenced by the expertise of the onsite coordinator, by intrinsic task complexity, by the degree of specifi-cation of tasks, and by supportive information. Cultural and semantic distances may in-fluence learning by inhibiting supportive information, specification, and the assignment of learning tasks.

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By means of fixed-links modeling, the present study identified different processes of visual short-term memory (VSTM) functioning and investigated how these processes are related to intelligence. We conducted an experiment where the participants were presented with a color change detection task. Task complexity was manipulated through varying the number of presented stimuli (set size). We collected hit rate and reaction time (RT) as indicators for the amount of information retained in VSTM and speed of VSTM scanning, respectively. Due to the impurity of these measures, however, the variability in hit rate and RT was assumed to consist not only of genuine variance due to individual differences in VSTM retention and VSTM scanning but also of other, non-experimental portions of variance. Therefore, we identified two qualitatively different types of components for both hit rate and RT: (1) non-experimental components representing processes that remained constant irrespective of set size and (2) experimental components reflecting processes that increased as a function of set size. For RT, intelligence was negatively associated with the non-experimental components, but was unrelated to the experimental components assumed to represent variability in VSTM scanning speed. This finding indicates that individual differences in basic processing speed, rather than in speed of VSTM scanning, differentiates between high- and low-intelligent individuals. For hit rate, the experimental component constituting individual differences in VSTM retention was positively related to intelligence. The non-experimental components of hit rate, representing variability in basal processes, however, were not associated with intelligence. By decomposing VSTM functioning into non-experimental and experimental components, significant associations with intelligence were revealed that otherwise might have been obscured.

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Many studies obtained reliable individual differences in speed of information processing (SIP) as measured by elementary cognitive tasks (ECTs). ECTs usually employ response times (RT) as measure of SIP, but different ECTs target different cognitive processes (e.g., simple or choice reaction, inhibition). Here we used modified versions of the Hick and the Eriksen Flanker task to examine whether these tasks assess dissociable or common aspects of SIP. In both tasks, task complexity was systematically varied across three levels. RT data were collected from 135 participants. Applying fixed-links modeling, RT variance increasing with task complexity was separated from RT variance unchanging across conditions. For each task, these aspects of variance were represented by two independent latent variables. The two latent variables representing RT variance not varying with complexity of the two tasks were virtually identical (r = .83). The latent variables representing increasing complexity in the two tasks were also highly correlated (r = .72) but clearly dissociable. Thus, RT measures contain both task-unspecific, person-related aspects of SIP as well as task-specific aspects indicating the cognitive processes manipulated with the respective task. Separating these aspects of SIP facilitates the interpretation of individual differences in RT.

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Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

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The neurocognitive processes underlying the formation and maintenance of paranormal beliefs are important for understanding schizotypal ideation. Behavioral studies indicated that both schizotypal and paranormal ideation are based on an overreliance on the right hemisphere, whose coarse rather than focussed semantic processing may favor the emergence of 'loose' and 'uncommon' associations. To elucidate the electrophysiological basis of these behavioral observations, 35-channel resting EEG was recorded in pre-screened female strong believers and disbelievers during resting baseline. EEG data were subjected to FFT-Dipole-Approximation analysis, a reference-free frequency-domain dipole source modeling, and Regional (hemispheric) Omega Complexity analysis, a linear approach estimating the complexity of the trajectories of momentary EEG map series in state space. Compared to disbelievers, believers showed: more right-located sources of the beta2 band (18.5-21 Hz, excitatory activity); reduced interhemispheric differences in Omega complexity values; higher scores on the Magical Ideation scale; more general negative affect; and more hypnagogic-like reveries after a 4-min eyes-closed resting period. Thus, subjects differing in their declared paranormal belief displayed different active, cerebral neural populations during resting, task-free conditions. As hypothesized, believers showed relatively higher right hemispheric activation and reduced hemispheric asymmetry of functional complexity. These markers may constitute the neurophysiological basis for paranormal and schizotypal ideation.

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In prospective memory tasks different kinds of load can occur. Adding a prospective memory task can impose a load on ongoing task performance. Adding ongoing task load (OTL) can affect prospective memory performance. The existence of multiple target events increases prospective load (PL) and adding complexity to the to-be-remembered action increases retrospective load (RL). In two experiments, we systematically examined the effects of these different types of load on prospective memory performance. Results showed an effect of PL on costs in the ongoing task for categorical targets (Experiment 2), but not for specific targets (Experiment 1). RL and OTL both affected remembering the retrospective component of the prospective memory task. We suggest that PL can enhance costs in the ongoing task due to additional monitoring requirements. RL and OTL seem to impact the division of resources between the ongoing task and retrieval of the retrospective component, which may affect disengagement from the ongoing task. In general, the results demonstrate that the different types of load affect prospective memory differentially.