Task-based Data Research Articles

FMRIprep: a robust preprocessing pipeline for task-based and resting-state fMRI data

FMRIprep: a robust preprocessing pipeline for task-based and resting-state fMRI data

Investigating the Group-Level Impact of Advanced Dual-Echo fMRI Combinations.

Multi-echo fMRI data acquisition has been widely investigated and suggested to optimize sensitivity for detecting the BOLD signal. Several methods have also been proposed for the combination of data with different echo times. The aim of the present study was to investigate whether these advanced echo combination methods provide advantages over the simple averaging of echoes when state-of-the-art group-level random-effect analyses are performed. Both resting-state and task-based dual-echo fMRI data were collected from 27 healthy adult individuals (14 male, mean age = 25.75 years) using standard echo-planar acquisition methods at 3T. Both resting-state and task-based data were subjected to a standard image pre-processing pipeline. Subsequently the two echoes were combined as a weighted average, using four different strategies for calculating the weights: (1) simple arithmetic averaging, (2) BOLD sensitivity weighting, (3) temporal-signal-to-noise ratio weighting and (4) temporal BOLD sensitivity weighting. Our results clearly show that the simple averaging of data with the different echoes is sufficient. Advanced echo combination methods may provide advantages on a single-subject level but when considering random-effects group level statistics they provide no benefit regarding sensitivity (i.e., group-level t-values) compared to the simple echo-averaging approach. One possible reason for the lack of clear advantages may be that apart from increasing the average BOLD sensitivity at the single-subject level, the advanced weighted averaging methods also inflate the inter-subject variance. As the echo combination methods provide very similar results, the recommendation is to choose between them depending on the availability of time for collecting additional resting-state data or whether subject-level or group-level analyses are planned.

MICA-A toolbox for masked independent component analysis of fMRI data.

Independent component analysis (ICA) is a widely used technique for investigating functional connectivity (fc) in functional magnetic resonance imaging data. Masked independent component analysis (mICA), that is, ICA restricted to a defined region of interest, has been shown to detect local fc networks in particular brain regions, including the cerebellum, brainstem, posterior cingulate cortex, operculo-insular cortex, hippocampus, and spinal cord. Here, we present the mICA toolbox, an open-source GUI toolbox based on FSL command line tools that performs mICA and related analyses in an integrated way. Functions include automated mask generation from atlases, essential preprocessing, mICA-based parcellation, back-reconstruction of whole-brain fc networks from local ones, and reproducibility analysis. Automated slice-wise calculation and cropping are additional functions that reduce computational time and memory requirements for large analyses. To validate our toolbox, we tested these different functions on the cerebellum, hippocampus, and brainstem, using resting-state and task-based data from the Human Connectome Project. In the cerebellum, mICA detected six local networks together with their whole-brain counterparts, closely replicating previous results. MICA-based parcellation of the hippocampus showed a longitudinally discrete configuration with greater heterogeneity in the anterior hippocampus, consistent with animal and human literature. Finally, brainstem mICA detected motor and sensory nuclei involved in the motor task of tongue movement, thereby replicating and extending earlier results. Hum Brain Mapp 37:3544-3556, 2016. © 2016 Wiley Periodicals, Inc.

Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives

Functional connectivity provides an informative and powerful framework for exploring brain organization. Despite this, few statistical methods are available for the accurate estimation of dynamic changes in functional network architecture. To date, the majority of existing statistical techniques have assumed that connectivity structure is stationary, which is in direct contrast to emerging data that suggests that the strength of connectivity between regions is variable over time. Therefore, the development of statistical methods that enable exploration of dynamic changes in functional connectivity is currently of great importance to the neuroscience community. In this paper, we introduce the ‘Multiplication of Temporal Derivatives’ (MTD) and then demonstrate the utility of this metric to: (i) detect dynamic changes in connectivity using data from a novel state-switching simulation; (ii) accurately estimate graph structure in a previously-described ‘ground-truth’ simulated dataset; and (iii) identify task-driven alterations in functional connectivity. We show that the MTD is more sensitive than existing sliding-window methods in detecting dynamic alterations in connectivity structure across a range of correlation strengths and window lengths in simulated data. In addition to the temporal precision offered by MTD, we demonstrate that the metric is also able to accurately estimate stationary network structure in both simulated and real task-based data, suggesting that the method may be used to identify dynamic changes in network structure as they evolve through time.

Skin Exposure to Aliphatic Polyisocyanates in the Auto Body Repair and Refinishing Industry: III. A Personal Exposure Algorithm

Isocyanate skin exposure may play an important role in sensitization and the development of isocyanate asthma, but such exposures are frequently intermittent and difficult to assess. Exposure metrics are needed to better estimate isocyanate skin exposures. The goal of this study was to develop a semiquantitative algorithm to estimate personal skin exposures in auto body shop workers using task-based skin exposure data and daily work diaries. The relationship between skin and respiratory exposure metrics was also evaluated. The development and results of respiratory exposure metrics were previously reported. Using the task-based data obtained with a colorimetric skin exposure indicator and a daily work diary, we developed a skin exposure algorithm to estimate a skin exposure index (SEI) for each worker. This algorithm considered the type of personal protective equipment (PPE) used, the percentage of skin area covered by PPE and skin exposures without and underneath the PPE. The SEI was summed across the day (daily SEI) and survey week (weekly average SEI) for each worker, compared among the job title categories and also compared with the respiratory exposure metrics. A total of 893 person-days was calculated for 232 workers (49 painters, 118 technicians and 65 office workers) from 33 auto body shops. The median (10th-90th percentile, maximum) daily SEI was 0 (0-0, 1.0), 0 (0-1.9, 4.8) and 1.6 (0-3.5, 6.1) and weekly average SEI was 0 (0-0.0, 0.7), 0.3 (0-1.6, 4.2) and 1.9 (0.4-3.0, 3.6) for office workers, technicians and painters, respectively, which were significantly different (P < 0.0001). The median (10th-90th percentile, maximum) daily SEI was 0 (0-2.4, 6.1) and weekly average SEI was 0.2 (0-2.3, 4.2) for all workers. A relatively weak positive Spearman correlation was found between daily SEI and time-weighted average (TWA) respiratory exposure metrics (microg NCO m(-3)) (r = 0.380, n = 893, P < 0.0001) and between weekly SEI and TWA respiratory exposure metrics (r = 0.482, n = 232, P < 0.0001). The skin exposure algorithm developed in this study provides task-based personal daily and weekly average skin exposure indices that are adjusted for the use of PPE. These skin exposure indices can be used to assess isocyanate exposure-response relationships.

The use of finite state machines for task-based machine tool control

Nowadays machine tool control, for small batch sizes, suffers from a lack of flexibility at machine level. The paper proposes a new architecture for machine tool control based on two concepts to increase the flexibility: decentralisation of planning and monitoring towards machine tool control, and the replacement of the traditional ISO-based input format by a task-based data representation. The decentralised planning and monitoring functionalities are grouped into the planning and monitoring module. The implementation of this module is based on a finite state machine (FSM). The use of an FSM offers the possibility to model the planning and monitoring knowledge.

通信回線を介したロボットの遠隔操作におけるタスク規範型データ伝送手法

This paper proposes the task based data exchange for teleoperation systems through communication network as an efficient transmission method of data between an operation device and a remote robot. On the task-based data exchange, the more important information according to the contents and conditions of the task which the robot performs is given priority to transmit, for example, by altering the contents of the transmitted data. We have built the experimental system in which the master arm in Tsukuba and the slave arm in Kawasaki are connected through N-ISDN and the standard techniques are utilized, such as TCP/IP, socket, JPEG, etc. A series of experimental task has been effectively carried out by the task based data exchange, that is, the crank operation which consists of grasp and revolution. The communication network with capacity limitation was used effectively and the high maneuverability in real-time with bilateral servo control has been realized. Then the effectiveness of the task based data exchange has been confirmed.

A task‐based approach to assessing lead exposure among iron workers engaged in bridge rehabilitation

The assessment of worker exposures to airborne contaminants in the dynamic environment present at most construction sites poses considerable challenges to the industrial hygienist. In this study, we applied a task-based approach to the assessment of lead exposure among structural steel iron workers engaged in a large, complex bridge rehabilitation project. We evaluated the usefulness of task-based exposure data for the development of worker protection programs. Task-specific and multitask samples were collected, and operation-specific and 8-hr time-weighted averages were calculated. The task-specific data showed significant differences in exposure levels among different tasks. Arithmetic mean exposures varied from 1,357 μg/m3 lead for torch cutting and 989 μg/m3 for scaling to 31 μg/m3 for reaming and 4 μg/m3 for drilling. Our task-specific data were compared with the task-based exposure levels presented by OSHA in its Lead Exposure in Construction-Interim Final Rule (29 CFR 1926). There was good general agreement between our results and OSHA's reported data. Task-based data were very useful in exposure assessment and much more precise than full-shift and operation-based measurements in guiding strategies for worker protection. These findings suggest that task-based data should routinely be collected in evaluating exposure to lead and perhaps other toxic substances in construction work. Am. J. Ind. Med. 31:310–318, 1997. © 1997 Wiley-Liss, Inc.

A task-based approach to assessing lead exposure among iron workers engaged in bridge rehabilitation.

The assessment of worker exposures to airborne contaminants in the dynamic environment present at most construction sites poses considerable challenges to the industrial hygienist. In this study, we applied a task-based approach to the assessment of lead exposure among structural steel iron workers engaged in a large, complex bridge rehabilitation project. We evaluated the usefulness of task-based exposure data for the development of worker protection programs. Task-specific and multitask samples were collected, and operation-specific and 8-hr time-weighted averages were calculated. The task-specific data showed significant differences in exposure levels among different tasks. Arithmetic mean exposures varied from 1,357 micrograms/m3 lead for torch cutting and 989 micrograms/m3 for scaling to 31 micrograms/m3 for reaming and 4 micrograms/m3 for drilling. Our task-specific data were compared with the task-based exposure levels presented by OSHA in its Lead Exposure in Construction-Interim Final Rule (29 CFR 1926). There was good general agreement between our results and OSHA's reported data. Task-based data were very useful in exposure assessment and much more precise than full-shift and operation-based measurements in guiding strategies for worker protection. These findings suggest that task-based data should routinely be collected in evaluating exposure to lead and perhaps other toxic substances in construction work.

Editorial: The Start of Neuroscience Research .........

The temporal lobe has been associated with various cognitive functions which include memory, auditory cognition and semantics. However, at a higher level of conceptualisation, all of the functions associated with the temporal lobe can be considered as lying along one major axis; from modality-specific to modality-general processing. This paper used a spectral reordering technique on resting-state and task-based functional data to extract the major organisational axis of the temporal lobe in a bottom-up, data-driven fashion. Independent parcellations were performed on resting-state scans from 71 participants and active semantic task scans from 23 participants acquired using dual echo gradient echo planar imaging in order to preserve signal in inferior temporal cortex. The resulting organisational axis was consistent (over dataset and hemisphere) and progressed from superior temporal gyrus and posterior inferior temporal cortex to ventrolateral anterior temporal cortex. A hard parcellation separated a posterior (superior temporal and posterior fusiform and inferior temporal gyri) and an anterior cluster (ventrolateral anterior temporal lobe). The functional connectivity of the hard clusters supported the hypothesis that the connectivity gradient separated modality-specific and modality-general regions. This hypothesis was then directly tested by performing a VOI analysis upon an independent semantic task-based data set including auditory and visually presented stimuli. This confirmed that the ventrolateral anterior aspects of the temporal lobe are associated with modality-general processes whilst posterior and superior aspects are specific to certain modalities, with the posterior inferior subregions involved in visual processes and superior regions involved in audition.