Target Error Research Articles

Real-time motion force-feedback system with predictive-vision for improving motor accuracy

Many haptic guidance systems have been studied over the years; however, most of them have been limited to predefined guidance methods. Calculating guidance according to the operator’s motion is important for efficient human motor adaptation and learning. In this study, we developed a system that haptically provides guidance trajectory by sequential weighting between the operator’s trajectory and the ideal trajectory calculated from a predictive-vision system. We investigated whether motion completion with a predictive-vision system affects human motor accuracy and adaptation in time-constrained goal-directed reaching and ball-hitting tasks through subject experiments. The experiment was conducted with 12 healthy participants, and all participants performed ball-hitting tasks. Half of the participants get forceful guidance from the proposed system in the middle of the experiment. We found that the use of the proposed system improved the operator’s motor performance. Furthermore, we observed a trend in which the improvement in motor performance using this system correlated with that after the washout of this system. These results suggest that the predictive-vision system effectively enhances motor accuracy to the target error in dynamic and time-constrained reaching and hitting tasks and may contribute to facilitating motor learning.

ACCURACY OF A FRAMELESS OPTICAL STEREOTACTIC NEURONAVIGATION SYSTEM FOR BRAIN BIOPSY IN CATS: A CADAVERIC STUDY

Image-guided stereotactic techniques can display the locations of surgical instruments and biopsy targets in real time, allowing minimally invasive brain biopsies with reduced risk. This study aimed to assess the accuracy of an optical frameless neuronavigation system in feline cadavers and describe potential influencing factors. Phantom lesions were created in different brain regions and depths in 15 feline cadavers. After installing eight fiducial markers in the frontal bone and zygomatic arches, magnetic resonance imaging (MRI) was performed, and the images were imported into the neuronavigation system. Following patient and instrument registration, diluted gadolinium was injected into the phantom lesion (target), guided by the neuronavigation system. The coordinates of the target and contrast points were determined on repeated MRI scans and the distance between them was defined as the targeting error. The time from target selection to the completion of gadolinium injection was recorded as the required time. The targeting error and required time were compared between the initial 30% and final 30% of the collected data to assess the influence of operator experience. Among 76 lesions, the mean targeting error was [Formula: see text][Formula: see text]mm (95% confidence interval 2.76–3.15[Formula: see text]mm). Lesion location, lesion depth, and operator experience did not affect the accuracy; however, operator experience reduced the required time. This frameless optical neuronavigation system is potentially feasible for feline brain biopsy. The demonstrated accuracy substantiates its clinical utility for feline brain lesions [Formula: see text][Formula: see text]mm, and is comparable to that of other neuronavigation systems described in dogs.

Quantifying motor adaptation in a sport-specific table tennis setting

Studies on motor adaptation aim to better understand the remarkable, largely implicit capacity of humans to adjust to changing environmental conditions. So far, this phenomenon has mainly been investigated in highly controlled laboratory setting, allowing only limited conclusions and consequences for everyday life scenarios. Natural movement tasks performed under externally valid conditions would provide important support on the transferability of recent laboratory findings. Therefore, one major goal of the current study was to create and assess a new table tennis paradigm mapping motor adaptation in a more natural and sport-specific setting. High-speed cinematographic measurements were used to determine target accuracy in a motor adaptation table tennis paradigm in 30 right-handed participants. In addition, we investigated if motor adaptation was affected by temporal order of perturbations (serial vs. random practice). In summary, we were able to confirm and reproduce typical motor adaptation effects in a sport-specific setting. We found, according to previous findings, an increase in target errors with perturbation onset that decreased during motor adaptation. Furthermore, we observed an increase in target errors with perturbation offset (after-effect) that decrease subsequently during washout phase. More importantly, this motor adaptation phenomenon did not differ when comparing serial vs. random perturbation conditions.

Practical targeting errors during optically tracked transcranial focused ultrasound using MR-ARFI and array-based steering.

Transcranial focused ultrasound (tFUS) is being explored for neuroscience research and clinical applications due to its ability to affect precise brain regions noninvasively. The ability to target specific brain regions and localize the beam during these procedures is important for these applications to avoid damage and minimize off-target effects. Here, we present a method to combine optical tracking with magnetic resonance (MR) acoustic radiation force imaging to achieve targeting and localizing of the tFUS beam. This combined method provides steering coordinates to target brain regions within a clinically practical time frame. Using an optically tracked hydrophone and bias correction with MR imaging we transformed the FUS focus coordinates into the MR space for targeting and error correction. We validated this method in vivo in 18 macaque FUS studies. Across these in vivo studies a single localization scan allowed for the average targeting error to be reduced from 4.8 mm to 1.4 mm and for multiple brain regions to be targeted with one transducer position. By reducing targeting error and providing the means to target multiple brain regions within a single session with high accuracy this method will allow further study of the effects of tFUS neuromodulation with more advanced approaches such as simultaneous dual or multi-site brain stimulation.

Predicting social assistance beneficiaries: On the social welfare damage of data biases

Abstract Cash transfer programs are the most common anti-poverty tool in low- and middle-income countries, reaching more than one billion people globally. Benefits are typically targeted using prediction models. In this paper, we develop an extended targeting assessment framework for proxy means testing that accounts for societal sensitivity to targeting errors. Using a social welfare framework, we weight targeting errors based on their position in the welfare distribution and adjust for different levels of societal inequality aversion. While this approach provides a more comprehensive assessment of targeting performance, our two case studies show that bias in the data, particularly in the form of label bias and unstable proxy means testing weights, leads to a substantial underestimation of welfare losses, disadvantaging some groups more than others.

Comparative Analysis of Interactive Modalities for Intuitive Endovascular Interventions.

Endovascular intervention is a minimally invasive method for treating cardiovascular diseases. Although fluoroscopy, known for real-time catheter visualization, is commonly used, it exposes patients and physicians to ionizing radiation and lacks depth perception due to its 2D nature. To address these limitations, a study was conducted using teleoperation and 3D visualization techniques. This in-vitro study involved the use of a robotic catheter system and aimed to evaluate user performance through both subjective and objective measures. The focus was on determining the most effective modes of interaction. Three interactive modes for guiding robotic catheters were compared in the study: 1) Mode GM, using a gamepad for control and a standard 2D monitor for visual feedback; 2) Mode GH, with a gamepad for control and HoloLens providing 3D visualization; and 3) Mode HH, where HoloLens serves as both control input and visualization device. Mode GH outperformed other modalities in subjective metrics, except for mental demand. It exhibited a median tracking error of 4.72 mm, a median targeting error of 1.01 mm, a median duration of 82.34 s, and a median natural logarithm of dimensionless squared jerk of 40.38 in the in-vitro study. Mode GH showed 8.5%, 4.7%, 6.5%, and 3.9% improvements over Mode GM and 1.5%, 33.6%, 34.9%, and 8.1% over Mode HH for tracking error, targeting error, duration, and dimensionless squared jerk, respectively. To sum up, the user study emphasizes the potential benefits of employing HoloLens for enhanced 3D visualization in catheterization. The user study also illustrates the advantages of using a gamepad for catheter teleoperation, including user-friendliness and passive haptic feedback, compared to HoloLens. To further gauge the potential of using a more traditional joystick as a control input device, an additional study utilizing the Haption VirtuoseTM robot was conducted. It reveals the potential for achieving smoother trajectories, with a 38.9% reduction in total path length compared to a gamepad, potentially due to its larger range of motion and single-handed control.

A method for positioning multiple weak magnetic target signals under the interference of strong magnetic sources

When locating multiple magnetic targets, the interference between each magnetic dipole is often ignored, we propose a method to detect and locate multiple weak magnetic target signals under the interference of strong magnetic sources. First, under different burial depths, the influence of shallow magnetic sources and deep magnetic sources on each other was studied and the conclusion was drawn that shallow targets are less affected by deep targets, while deep targets have the opposite effect; and the normalized source strength (NSS) is introduced into the concept of magnetic inclination in the terrain field, this simultaneously utilizes the insensitivity of magnetic inclination to burial depth and the isotropy of NSS to amplify the signal characteristics of submerged deep targets, and initially obtains the horizontal position of the measured target; the idea of locating shallow targets first, removing the interference of shallow targets, and then locating deep targets is proposed, The results of positioning were fitted and optimized by moth Moth-Flame Optimization (MFO), and the accuracy of positioning was improved. In the simulation, compared with the total magnetic field intensity (TMI), the root mean square error (RMSE) of the positioning results of the three measured targets after using the proposed method is reduced from 0.2820, 0.1831 and 0.3972 to 0.0112, 0.0145 and 0.0326, the positioning error of deep target is greatly reduced, which proves the feasibility of the proposed method, in the actual experiment, the positioning accuracy of the deep measured magnetic source is also improved.

Dosimetric effects of rotational errors for single isocenter multiple targets in HyperArc plans: A phantom and retrospective imaging analysis study.

This study uses a phantom to investigate the dosimetric impact of rotational setup errors for Single Isocenter Multiple Targets (SIMT) HyperArc plans. Additionally, it evaluates intra-fractional rotational setup errors in patients treated with Encompass immobilization system. The Varian HyperArc system (Varian Medical systems) was used to create plans targeting spherical PTVs with diameters of 5, 10, and 15mm and with offsets of 1.3-5.3cm from the isocenter. Dosimetric parameters, including mean and maximum dose, D99% and D95% were evaluated for various rotational setup errors ranging from 0.5° to 2° for the PTVs and certain CTVs created within PTVs. These rotational errors were applied in an order and direction that resulted in the maximum displacement of targets. The rotation was applied both uniformly around all three axes and individually around each axis. Furthermore, to link the findings to actual treatment scenarios, the intra-fractional rotational setup errors were obtained for stereotactic cranial patients treated with the Encompass system using CBCT images acquired during treatments. The maximum displacement of 2.7mm was observed for targets located at 4.4 and 4.5cm from the isocenter with rotational setup errors of 2°. The dose reduction for D99% values corresponding to this displacement were about 50%, 40%, and 30% for PTVs with diameters of 5, 10, and 15mm, respectively. Both D99% and D95% showed a consistent trend of dose reduction across various rotational errors and PTV volumes. While the maximum dose remained consistent for different targets with various rotational errors, the mean dose decreased by approximately 25%, 12%, and 6% for PTVs with diameters of 5, 10, and 15cm, respectively, with rotational errors of 2°. In addition, by analyzing CBCT images, the absolute mean rotational setup errors obtained during treatment with Encompass for pitch, roll, and yaw were 0.17°±0.13°, 0.11°±0.10°, and 0.12°±0.10° respectively. This data, combined with existing studies, suggest that a 0.5° rotational setup error is a safe choice to consider for calculating additional PTV margin to ensure adequate CTV coverage. Therefore, the assessment of maximum displacement and dosimetric parameters in this study, for a 0.5° rotational error, highlights the need for an additional 0.7mm PTV margin for targets positioned at distances of 4.4cm or greater from the isocenter. For SIMT Plans, a 0.5° rotational setup error is recommended as a basis for calculating additional PTV margins to ensure adequate CTV coverage when using the Encompass system.

Upper extremity kinematics: development of a quantitative measure of impairment severity and dissimilarity after stroke.

Strokes are a leading cause of disability worldwide, with many survivors experiencing difficulty in recovering upper extremity movement, particularly hand function and grasping ability. There is currently no objective measure of movement quality, and without it, rehabilitative interventions remain at best informed estimations of the underlying neural structures' response to produce movement. In this article, we utilize a novel modification to Procrustean distance to quantify curve dissimilarity and propose the Reach Severity and Dissimilarity Index (RSDI) as an objective measure of motor deficits. All experiments took place at the Medstar National Rehabilitation Hospital; persons with stroke were recruited from the hospital patient population. Using Fugl-Meyer (FM) scores and reach capacities, stroke survivors were placed in either mild or severe impairment groups. Individuals completed sets of reach-to-target tasks to extrapolate kinematic metrics describing motor performance. The Procrustes method of statistical shape analysis was modified to identify reaching sub-movements that were congruous to able-bodied sub-movements. Movement initiation proceeds comparably to the reference curve in both two- and three-dimensional representations of mild impairment movement. There were significant effects of the location of congruent segments between subject and reference curves, mean velocities, peak roll angle, and target error. These metrics were used to calculate a preliminary RSDI score with severity and dissimilarity sub-scores, and subjects were reclassified in terms of rehabilitation goals as Speed Emphasis, Strength Emphasis, and Combined Emphasis. The modified Procrustes method shows promise in identifying disruptions in movement and monitoring recovery without adding to patient or clinician burden. The proposed RSDI score can be adapted and expanded to other functional movements and used as an objective clinical tool. By reducing the impact of stroke on disability, there is a significant potential to improve quality of life through individualized rehabilitation.

End-to-end validation of fiducial tracking accuracy in robotic radiosurgery using MRI-only simulation imaging.

Image-guided radiation-therapy (IGRT)-based robotic radiosurgery using magnetic resonance imaging (MRI)-only simulation could allow for improved target definition with highly conformal radiotherapy treatments. Fiducial marker (FM)-based alignment is used with robotic radiosurgery treatments of sites such as the prostate because it aids in accurate target localization. Synthetic CT (sCT) images are generated in the MRI-only workflow but FMs used for IGRT appear as signal voids in MRIs and do not appear in MR-generated sCTs, hindering the ability to use sCTs for fiducial-based IGRT. In this study we evaluate the fiducial tracking accuracy for a novel artificial fiducial insertion method in sCT images that allows for fiducial marker tracking in robotic radiosurgery, using MRI-only simulation imaging (MRI-only workflow). Artificial fiducial markers were inserted into sCT images at the site of the real marker implantation as visible in MRI. Two phantoms were used in this study. A custom anthropomorphic pelvis phantom was designed to validate the tracking accuracy for a variety of artificial fiducials in an MRI-only workflow. A head phantom containing a hidden target and orthogonal film pair inserts was used to perform end-to-end tests of artificial fiducial configurations inserted in sCT images. The setup and end-to-end targeting accuracy of the MRI-only workflow were compared to the computed tomography (CT)-based standard. Each phantom had six FMs implanted with a minimum spacing of 2cm. For each phantom a bulk-density sCT was generated, and artificial FMs were inserted at the implantation location. Several methods of FM insertion were tested including: (1) replacing HU with a fixed value (10000HU) (voxel-burned); (2) using a representative fiducial image derived from a linear combination of fiducial templates (composite-fiducial); (3) computationally simulating FM signal voids using a digital phantom containing FMs and inserting the corresponding signal void into sCT images (simulated-fiducial). All tests were performed on a CyberKnife system (Accuray, Sunnyvale, CA). Treatment plans and digital-reconstructed-radiographs were generated from the original CT and sCTs with embedded fiducials and used to align the phantom on the treatment couch. Differences in the initial phantom alignment (3D translations/rotations) and tracking parameters between CT-based plans and sCT-based plans were analyzed. End-to-end plans for both scenarios were generated and analyzed following our clinical protocol. For all plans, the fiducial tracking algorithm was able to identify the fiducial locations. The mean FM-extraction uncertainty for the composite and simulated FMs was below 48% for fiducials in both the anthropomorphic pelvis and end-to-end phantoms, which is below the 70% treatment uncertainty threshold. The total targeting error was within tolerance (<0.95mm) for end-to-end tests of sCT images with the composite and head-on simulated FMs (0.26, 0.44, and 0.35mm for the composite fiducial in sCT, head-on simulated fiducial in sCT, and fiducials in original CT, respectively. MRI-only simulation for robotic radiosurgery could potentially improve treatment accuracy and reduce planning margins. Our study has shown that using a composite-derived or simulated FM in conjunction with sCT images, MRI-only workflow can provide clinically acceptable setup accuracy in line with CT-based standards for FM-based robotic radiosurgery.

Accuracy-based proficiency testing for estradiol measurements

ObjectivesAccuracy of estradiol measurements is important but conventional proficiency testing (PT) cannot assess accuracy when possibly non-commutable samples are used and method peer-group means are the targets. Accuracy-based assessment of estradiol measurements is needed. Design and MethodsFive serum samples were prepared from single donors, frozen, and distributed overnight to 76 New York State Department of Health (NYSDOH)-certified laboratories. Participants analyzed samples for estradiol. The biases of group means were assessed against the Centers for Disease Control and Prevention (CDC)-defined targets, evaluated using the Hormone Standardization Program (HoSt) E2 performance criterion of ±12.5 %. Each laboratory’s performance was evaluated using total allowable error (acceptance limits) of target ±25 % or ±15 pg/mL (55 pmol/L) (whichever was greater, NYSDOH), target ±30 % (Clinical Laboratory Improvement Amendments [CLIA]), and target ±26 % (minimal limit based on biological variation [BV]). ResultsThe biases (range) were 34 % (−17 % to 175 %), 40 % (−33 % to 386 %), 16 % (−45 % to 193 %), 5 % (−27 % to 117 %), and −4% (−31 % to 21 %), for samples at estradiol of 24.1, 28.4, 61.7, 94.1, and 127 pg/mL, or 89, 104, 227, 345, and 466 pmol/L, respectively. Large positive method/analytical systematic biases were revealed for 9 commonly used method/analytical systems in the United States at low estradiol concentrations. Of the 9 analytical systems, 0, 0, 3, 7 and 6 met the HoSt criterion for the samples with estradiol at the five respective concentrations. PT evaluation showed that 59 %, 69 % and 87 % of laboratories would receive a PT event passing (satisfactory) score when the CDC-defined target and a criterion of NYSDOH, CLIA or BV was used, respectively. However, >95 % laboratories would obtain PT passing score if method peer-group means were used as targets regardless of the criterion used. ConclusionsImprovement in accuracy of estradiol measurements is needed, particularly at low estradiol concentrations. Accuracy-based PT provides unambiguous information about the accuracy of methods/analytical systems.

A New Minimax Theorem for Randomized Algorithms

The celebrated minimax principle of Yao says that for any Boolean-valued function f with finite domain, there is a distribution μ over the domain of f such that computing f to error ε against inputs from μ is just as hard as computing f to error ε on worst-case inputs. Notably, however, the distribution μ depends on the target error level ε: the hard distribution which is tight for bounded error might be trivial to solve to small bias, and the hard distribution which is tight for a small bias level might be far from tight for bounded error levels. In this work, we introduce a new type of minimax theorem which can provide a hard distribution μ that works for all bias levels at once. We show that this works for randomized query complexity, randomized communication complexity, some randomized circuit models, quantum query and communication complexities, approximate polynomial degree, and approximate logrank. We also prove an improved version of Impagliazzo’s hardcore lemma. Our proofs rely on two innovations over the classical approach of using Von Neumann’s minimax theorem or linear programming duality. First, we use Sion’s minimax theorem to prove a minimax theorem for ratios of bilinear functions representing the cost and score of algorithms. Second, we introduce a new way to analyze low-bias randomized algorithms by viewing them as “forecasting algorithms” evaluated by a certain proper scoring rule. The expected score of the forecasting version of a randomized algorithm appears to be a more fine-grained way of analyzing the bias of the algorithm. We show that such expected scores have many elegant mathematical properties—for example, they can be amplified linearly instead of quadratically. We anticipate forecasting algorithms will find use in future work in which a fine-grained analysis of small-bias algorithms is required.

A fatigue crack growth prediction method on small datasets based on optimized deep neural network and Delaunay data augmentation

The neural network-based prediction method has shown great potential in the field of fatigue crack growth prediction due to its powerful nonlinear processing and generalization capabilities. However, traditional deep neural network-based methods often encounter problems such as overfitting, underfitting, and instability when predicting FCG rates on small datasets. To address these issues, this study proposes a SA-DNN prediction method for metal fatigue crack growth by introducing Delaunay data augmentation and simulated annealing algorithm into the basic DNN framework. The proposed SA-DNN model is then used to predict the fatigue crack growth process of AM60B magnesium alloy and 7055 Al alloy, and the intrinsic and extrinsic generalization abilities of the model are evaluated. In both the evaluation of intrinsic and extrinsic generalization abilities, the mean squared errors of the training, validation, and testing sets rapidly converge to the target error in various epochs. The lowest mean squared errors achieved are 1.07 e-5 and 1.241 e-5, respectively. Moreover, the results also indicate that the proposed model can accurately predict the fatigue crack growth process of metal materials with varying degrees of nonlinearity.

Augmented Reality Registration System for Visualization of Skull Landmarks

BackgroundAugmented reality (AR) is an emerging technology in neurosurgery with the potential to become a strategic tool in the delivery of care and education for trainees. Advances in the technology have demonstrated promising use for improving visualization and spatial awareness of critical neuroanatomical structures. In this report, we employ a novel AR registration system for the visualization and targeting of skull landmarks. MethodsA markerless AR system was used to register 3D reconstructions of suture lines onto the head via a head mounted display. Participants were required to identify craniometric points with and without AR assistance. Targeting error was measured as the Euclidian distance between the user-defined location and the true craniometric point on the subjects’ head. ResultsAll participants successfully registered 3D reconstructions onto the subjects’ head. Targeting accuracy was significantly improved with AR (3.59 ± 1.29 mm) . Across all target points, AR increased accuracy by an average of 19.96 ± 3.80 mm. Post-test surveys revealed that participants felt the technology increased their confidence in identifying landmarks (4.6/5) and that the technology will be useful for clinical care (4.2/5). ConclusionsWhile several areas of improvement and innovation can further enhance the use of AR in neurosurgery, this report demonstrates the feasibility of a markerless headset-based AR system for visualizing craniometric points on the skull. As the technology continues to advance, AR is expected to play an increasingly significant role in neurosurgery, transforming how surgeries are performed and improving patient care.

Application of Bayesian network and genetic algorithm in construction safety evaluation

Developing a safety evaluation model for construction is of utmost importance due to the increasing prevalence of safety issues on construction sites in a rapidly growing sector. Consequently, this research integrates a clonal genetic algorithm (CGA) and a Bayesian network (BN) into the current building information modelling technology for building construction to establish a comprehensive safety evaluation model for building construction. To develop a framework for assessing building safety, this study initially filters the factors impacting building safety through an advanced evolutionary algorithm. Subsequently, a BN is employed to understand the structure and parameters of the model. When compared with both a back-propagation neural network (BPNN) model and a genetic-algorithm-optimised neural network model, the CGA–BPNN model shows a network training error of approximately 0.09%. Additionally, the target error value is observed to be around 0.02%, and the genetic cross-over probability of the CGA–BPNN model amounts to 0.6629. These results indicate the small algorithm error and appropriate training time of the model, as well as higher accuracy. The CGA–BPNN model filters the evaluation indexes in the BN and assigns appropriate weights to assess accurately the safety status of the construction project.

The effects of periodic and noisy tendon vibration on a kinesthetic targeting task.

Tendon vibration is used extensively to assess the role of peripheral mechanoreceptors in motor control, specifically, the muscle spindles. Periodic tendon vibration is known to activate muscle spindles and induce a kinesthetic illusion that the vibrated muscle is longer than it actually is. Noisy tendon vibration has been used to assess the frequency characteristics of proprioceptive reflex pathways during standing; however, it is unknown if it induces the same kinesthetic illusions as periodic vibration. The purpose of the current study was to assess the effects of both periodic and noisy tendon vibration in a kinesthetic targeting task. Participants (N = 15) made wrist extension movements to a series of visual targets without vision of the limb, while their wrist flexors were either vibrated with periodic vibration (20, 40, 60, 80, and 100Hz), or with noisy vibration which consisted of filtered white noise with power between ~ 20 and 100Hz. Overall, our results indicate that both periodic and noisy vibration can induce robust targeting errors during a wrist targeting task. Specifically, the vibration resulted in an undershooting error when moving to the target. The findings from this study have important implications for the use of noisy tendon vibration to assess proprioceptive reflex pathways and should be considered when designing future studies using noisy vibration.

Training &amp; prompting pre-service teachers’ noticing in a standardized classroom simulation – a mobile eye-tracking study

Numerous events happening in classrooms require a teacher to select important and filter out irrelevant information. This crucial and challenging skill is referred to as noticing. For noticing classroom management events pre-service teachers have a smaller knowledge base and little teaching experience compared to expert teachers. Supporting pre-service teachers in developing their classroom management knowledge and noticing skill is, thus, of great importance for teacher education. Previous research finds positive effects of interventions on teachers’ noticing during video observation. To our knowledge, no studies depict noticing during teaching. We examined N = 46 pre-service teachers’ noticing with regard to classroom management during classroom teaching in a quasi-experimental between-subjects design. Pre-service teachers’ took part in a standardized classroom simulation after a classroom management training, with one group receiving prompting regarding evidence-based classroom management strategies before and during the classroom simulation and one group receiving only training. We also included a control group without classroom management training. To assess differences in pre-service teachers’ noticing, the classroom simulation elicited comparable conditions, including standardized classroom management events and student behavior. Mobile eye-tracking as well as retrospective video observations were used to explore teachers’ event-related and global noticing. Event-related noticing was assessed via count and accuracy of noticed classroom management events. Global noticing included objective parameters of teachers eye movements (visit/fixation counts and duration) onto the students in the standardized classroom simulation. The results show that training and prompting significantly affected pre-service teachers’ event-related noticing, with both experimental groups making fewer target and time errors compared to the control group. No significant differences were found with regard to global noticing. This includes fixation and visit count and duration on students. Correlational analysis showed a positive association between higher noticing accuracy and share of fixations on students. This study expands upon previous empirical research using mobile eye-tracking to obtain objective measures of teachers’ noticing. It sheds light on the relevance of knowledge for teachers’ noticing during teaching. It also takes a first step toward understanding how pre-service teachers’ noticing during classroom teaching can be promoted through fostering knowledge about classroom management through a training.

MNI2CPC: A probabilistic cortex-to-scalp mapping for non-invasive brain stimulation targeting

BackgroundSynthesis of neural imaging information from many studies is valuable for identifying stable cortical targets for non-invasive brain stimulation (NIBS). Typically, these targets are specified in Montreal Neurological Institute (MNI) standard brain space. However, in practical NIBS applications, localizing MNI cortical targets often relies on the International 10–20 system or heuristic scalp approaches, which often lacks precision or applies only to specific targets. Objective/hypothesisWe aim to establish a probabilistic mapping from any cortical target in MNI space to continuous proportional coordinate (CPC) standard scalp space (MNI2CPC) and assess the performance of this mapping for NIBS targeting. MethodsThe MNI2CPC mapping was calculated based on a large MRI dataset (n = 114). Its targeting error was evaluated via cross-individual validation using a leave-one-out approach, as well as through independent validation across race (n = 27) and across patient (n = 58) cohorts. ResultsThe cross-individual validation demonstrated targeting errors of 4.03 ± 0.69 mm on the scalp and 3.30 ± 0.59 mm in the cortex. For independent cohorts, targeting errors were 4.71 ± 0.81 mm (scalp) and 3.85 ± 0.64 mm (cortex) across race, and 4.66 ± 0.77 mm (scalp) and 3.77 ± 0.61 mm (cortex) across patient. We publish a free online tool to enable querying of the CPC coordinate for any given MNI cortical target. The resulting CPC coordinates enable rapid and accurate manual localization on the scalp in a user-friendly manner. ConclusionsThe MNI2CPC mapping developed in this study allows for manual localization of any MNI cortical target, which improves the accessibility and ease of application of NIBS in diverse settings.

85 Performance Consistency on a Measure of Sustained and Selective Attention

Objective:Attention concerns, particularly difficulties with focusing and regulating attention, are reported in diverse clinical contexts. The Ruff 2&amp;7 Selective Attention Test (Ruff 2&amp;7; Ruff &amp; Allen, 1996) is a measure of sustained and selective attention that assesses automatic detection and effortful processing. The goal of this study was to create an internal consistency metric within this test and to determine cognitive predictors by evaluating associations with executive control of attention and other cognitive skills. It was hypothesized that those who are more consistent across Ruff 2&amp;7 performance would have more robust executive functioning skills, particularly those related to regulating and directing attention and the planning and utilization of cognitive resources.Participants and Methods:The current study examined a clinical sample of 98 United States veterans with a history of mild traumatic brain injury. After excluding invalid cases (n=24), the final sample consisted of 74 veterans (Age=38.5 (8.9) years old; 13.9 (2.2) years of education; 78% male; 82% white, 7% Black, 8% Hispanic, 2% Asian). A consistency score was defined as the absolute value of the intertrial change in target hits plus errors across each pair of trials of the same stimulus type (Automatic Detection, AD, and Controlled Search, CS). Hierarchical linear regression modeling was used to evaluate the relative contributions of memory and executive functions (Rey Auditory Verbal Learning Test, Delis-Kaplan Executive Function System Tower Test, phonemic fluency, Trail Making Test B) and subjective symptom report (PTSD Checklist for DSM-5, Barkley Adult ADHD Rating Scale for DSM-IV).Results:The mean deviation scores for the two trial types were similar (AD mean=13.6, SD=5.9; CS mean=13.6, SD=5.3). In predicting consistency across AD trials, delayed recall contributed 11% unique variance (p=.013), while no other block was statistically significant. For CS trials, self-reported PTSD and inattention symptoms contributed a combined 20% of unique variance to the model (p=.007), while there were no statistically significant cognitive predictors in this model.Conclusions:Contrary to expectation, executive function measures did not explain statistically significant variance in performance across either trial type. Less consistent performance on AD trials was associated with weaker verbal memory. Less consistent performance on CS trials, which theoretically require greater executive control, was not associated with any cognitive scores, but was associated with more severe self-reported psychological and inattention symptoms. These findings buttress the conceptual distinction between AD and CS trial types, and they point to both cognitive and non-cognitive underpinnings of performance consistency.

Frameless robot-assisted stereoelectroencephalography-guided radiofrequency: methodology, results, complications and stereotactic application accuracy in pediatric hypothalamic hamartomas

ObjectiveWe aimed to investigate the methodology, results, complications and stereotactic application accuracy of electrode implantation and its explanatory variables in stereoelectroencephalography-guided radiofrequency thermocoagulation (SEEG-RFTC) for pediatric hypothalamic hamartoma.MethodsChildren with hypothalamic hamartoma who underwent robot-assisted SEEG-RFTC between December 2017 and November 2021 were retrospectively analyzed. The methodology, seizure outcome, complications, in vivo accuracy of electrode implantation and its explanatory variables were analyzed.ResultsA total of 161 electrodes were implanted in 28 patients with 30 surgeries. Nine electrodes not following the planned trajectories due to intraoperative replanning were excluded, and the entry point and target point errors of 152 electrodes were statistically analyzed. The median entry point error was 0.87 mm (interquartile range, 0.50–1.41 mm), and the median target point error was 2.74 mm (interquartile range, 2.01–3.63 mm). Multifactor analysis showed that whether the electrode was bent (b = 2.16, p &amp;lt; 0.001), the length of the intracranial electrode (b = 0.02, p = 0.049), and the entry point error (b = 0.337, p = 0.017) had statistically significant effects on the target error. During follow-up (mean duration 31 months), 27 of 30 (90%) procedures were seizure-free. The implantation-related complication rate was 2.6% (4/152), and the major complication rate in all procedures was 6.7% (2/30).ConclusionRobot-assisted SEEG-RFTC is a safe, effective and accurate procedure for pediatric hypothalamic hamartoma. Explanatory variables significantly associated with the target point localization error at multivariate analysis include whether the intracranial electrode is bent, the intracranial electrode length and the entry point error.