scholarly journals Using machine learning-based lesion behavior mapping to identify anatomical networks of cognitive dysfunction: spatial neglect and attention

2019 ◽  
Author(s):  
Daniel Wiesen ◽  
Christoph Sperber ◽  
Grigori Yourganov ◽  
Christopher Rorden ◽  
Hans-Otto Karnath
Keyword(s):  
Statistical Power ◽  
Spatial Neglect ◽  
Support Vector ◽  
Lesion Volume ◽  
Right Brain ◽  
Anatomical Basis ◽  
Lesion Mapping ◽  
Mapping Techniques ◽  
Subcortical Regions ◽  
Univariate Analyses

AbstractPrevious lesion behavior studies primarily used univariate lesion behavior mapping techniques to map the anatomical basis of spatial neglect after right brain damage. These studies led to inconsistent results and lively controversies. Given these inconsistencies, the idea of a widespread network that might underlie spatial orientation and neglect has been pushed forward. In such case, univariate lesion behavior mapping methods might have been inherently limited in uncover the presumed network in a single study due to limited statistical power. By using multivariate lesion-mapping based on support vector regression, we aimed to validate the network hypothesis directly in a large sample of 203 newly recruited right brain damaged patients. In a single analysis, this method identified a network of parietal, temporal, frontal, and subcortical regions, which also included white matter tracts connecting these regions. The results were compared to univariate analyses of the same patient sample using different combinations of lesion volume correction and statistical thresholding. The comparison revealed clear benefits of multivariate lesion behavior mapping in identifying brain networks.

scholarly journals Structural white-matter connections mediating distinct behavioral components of spatial neglect in right brain-damaged patients

Cortex ◽  
2016 ◽  
Vol 77 ◽  
pp. 54-68 ◽  
Author(s):  
Maarten J. Vaessen ◽  
Arnaud Saj ◽  
Karl-Olof Lovblad ◽  
Markus Gschwind ◽  
Patrik Vuilleumier
Keyword(s):  
White Matter ◽  
Spatial Neglect ◽  
Right Brain

scholarly journals G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Florent Le Borgne ◽  
Arthur Chatton ◽  
Maxime Léger ◽  
Rémi Lenain ◽  
Yohann Foucher
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Statistical Power ◽  
Small Sample ◽  
Causal Effects ◽  
Small Samples ◽  
Support Vector ◽  
Sample Sizes ◽  
Super Learner ◽  
Small Sample Sizes

AbstractIn clinical research, there is a growing interest in the use of propensity score-based methods to estimate causal effects. G-computation is an alternative because of its high statistical power. Machine learning is also increasingly used because of its possible robustness to model misspecification. In this paper, we aimed to propose an approach that combines machine learning and G-computation when both the outcome and the exposure status are binary and is able to deal with small samples. We evaluated the performances of several methods, including penalized logistic regressions, a neural network, a support vector machine, boosted classification and regression trees, and a super learner through simulations. We proposed six different scenarios characterised by various sample sizes, numbers of covariates and relationships between covariates, exposure statuses, and outcomes. We have also illustrated the application of these methods, in which they were used to estimate the efficacy of barbiturates prescribed during the first 24 h of an episode of intracranial hypertension. In the context of GC, for estimating the individual outcome probabilities in two counterfactual worlds, we reported that the super learner tended to outperform the other approaches in terms of both bias and variance, especially for small sample sizes. The support vector machine performed well, but its mean bias was slightly higher than that of the super learner. In the investigated scenarios, G-computation associated with the super learner was a performant method for drawing causal inferences, even from small sample sizes.

scholarly journals Defining reperfusion post endovascular therapy in ischemic stroke using MR-dynamic contrast enhanced perfusion

2020 ◽  
Vol 93 (1116) ◽  
pp. 20190890
Author(s):  
Christopher D d’Esterre ◽  
Rani Gupta Sah ◽  
Zarina Assis ◽  
Aron S. Talai ◽  
Andrew M. Demchuk ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Predictive Model ◽  
Volume Change ◽  
Endovascular Therapy ◽  
Support Vector ◽  
Lesion Volume ◽  
Mr Perfusion ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Acute Infarct

Objectives Cerebral blood flow (CBF) measurements after endovascular therapy (EVT) for acute ischemic stroke are important to distinguish early secondary injury related to persisting ischemia from that related to reperfusion when considering clinical response and infarct growth. Methods We compare reperfusion quantified by the modified Thrombolysis in Cerebral Infarction Score (mTICI) with perfusion measured by MRI dynamic contrast-enhanced perfusion within 5 h of EVT anterior circulation stroke. MR perfusion (rCBF, rCBV, rTmax, rT0) and mTICI scores were included in a predictive model for change in NIHSS at 24 h and diffusion-weighted imaging (DWI) lesion growth (acute to 24 h MRI) using a machine learning RRELIEFF feature selection coupled with a support vector regression. Results For all perfusion parameters, mean values within the acute infarct for the TICI-2b group (considered clinically good reperfusion) were not significantly different from those in the mTICI <2b (clinically poor reperfusion). However, there was a statistically significant difference in perfusion values within the acute infarct region of interest between the mTICI-3 group versus both mTICI-2b and <2b (p = 0.02). The features that made up the best predictive model for change in NIHSS and absolute DWI lesion volume change was rT0 within acute infarct ROI and admission CTA collaterals respectively. No other variables, including mTICI scores, were selected for these best models. The correlation coefficients (Root mean squared error) for the cross-validation were 0.47 (13.7) and 0.51 (5.7) for change in NIHSS and absolute DWI lesion volume change. Conclusion MR perfusion following EVT provides accurate physiological approach to understanding the relationship of CBF, clinical outcome, and DWI growth. Advances in knowledge MR perfusion CBF acquired is a robust, objective reperfusion measurement providing following recanalization of the target occlusion which is critical to distinguish potential therapeutic harm from the failed technical success of EVT as well as improve the responsiveness of clinical trial outcomes to disease modification.

Structural integrity of white matter tracts as a predictor of acute ischemic stroke outcome

2020 ◽  
Vol 15 (9) ◽  
pp. 965-972
Author(s):  
Deepthi Rajashekar ◽  
Pauline Mouchès ◽  
Jens Fiehler ◽  
Bijoy K Menon ◽  
Mayank Goyal ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Support Vector Regression ◽  
Support Vector ◽  
Stroke Severity ◽  
Lesion Volume ◽  
White Matter Tract ◽  
Support Vector Regression Model ◽  
White Matter Tracts

Background and purpose Clinical assessment scores in acute ischemic stroke are only moderately correlated with lesion volume since lesion location is an important confounding factor. Many studies have investigated gray matter indicators of stroke severity, but the understanding of white matter tract involvement is limited in the early phase after stroke. This study aimed to measure and model the involvement of white matter tracts with respect to 24-h post-stroke National Institutes of Health Stroke Scale (NIHSS). Material and methods A total of 96 patients (50 females, mean age 66.4 ± 14.0 years, median NIHSS 5, interquartile range: 2–9.5) with follow-up fluid-attenuated inversion recovery magnetic resonance imaging data sets acquired one to seven days after acute ischemic stroke onset due to proximal anterior circulation occlusion were included. Lesions were semi-automatically segmented and non-linearly registered to a common reference atlas. The lesion overlap and tract integrity were determined for each white matter tract in the AALCAT atlas and used to model NIHSS outcomes using a supervised linear-kernel support vector regression method, which was evaluated using leave-one-patient-out cross validation. Results The support vector regression model using the tract integrity and tract lesion overlap measurements predicted the 24-h NIHSS score with a high correlation value of r = 0.7. Using the tract overlap and tract integrity feature improved the modeling accuracy of NIHSS significantly by 6% (p < 0.05) compared to using overlap measures only. Conclusion White matter tract integrity and lesion load are important predictors for clinical outcome after an acute ischemic stroke as measured by the NIHSS and should be integrated for predictive modeling.

Relations of Singing Talent with Voice Onset Time of Trained and Untrained Female Singers

2007 ◽  
Vol 105 (1) ◽  
pp. 133-142
Author(s):  
Christopher R. McCrea ◽  
Christopher Watts
Keyword(s):  
Statistical Power ◽  
Voice Onset Time ◽  
Onset Time ◽  
The Other ◽  
Effect Sizes ◽  
Perceptual Judgments ◽  
Significant Difference ◽  
Female Singers ◽  
Univariate Analyses

This study examined phonatory-articulatory timing during sung productions by trained and untrained female singers with and without singing talent. 31 untrained female singers were divided into two groups (talented or untalented) based on the perceptual judgments of singing talent by two experienced vocal instructors. In addition to the untrained singers, 24 trained female singers were recorded singing America the Beautiful, and voice onset time was measured for selected words containing /p, b, g, k/. Univariate analyses of variance indicated that phonatory-articulatory timing, as measured with voice onset time, was different among the three groups for /g/, with the untrained-untalented singers displaying longer voice onset time than the trained singers. No other significant differences were observed across the other phonemes. Despite a significant difference observed, relatively small effect sizes and statistical power make it difficult to draw any conclusions regarding the usefulness of voice onset time as an indicator of singing talent.

Small numbers in the right brain: Evidence from patients without and with spatial neglect

Cortex ◽  
2013 ◽  
Vol 49 (1) ◽  
pp. 348-351 ◽  
Author(s):  
Marilena Aiello ◽  
Sheila Merola ◽  
Fabrizio Doricchi
Keyword(s):  
Spatial Neglect ◽  
Right Brain ◽  
The Right

scholarly journals Measuring Gaze and Arrow Cuing Effects With a Short Test Adapted to Brain Damaged Patients With Unilateral Spatial Neglect: A Preliminary Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Rindra Narison ◽  
Marie de Montalembert ◽  
Andrew Bayliss ◽  
Laurence Conty
Keyword(s):  
Older Patients ◽  
Brain Lesion ◽  
Brain Lesions ◽  
Spatial Neglect ◽  
Short Version ◽  
Unilateral Spatial Neglect ◽  
Right Brain ◽  
Short Test ◽  
Preliminary Study ◽  
Healthy Participants

People with left unilateral spatial neglect (USN) following a right brain lesion show difficulty in orienting their attention toward stimuli presented on the left. However, cuing the stimuli with gaze direction or a pointing arrow can help some of them to compensate for this difficulty. In order to build a tool that helps to identify these patients, we needed a short version of the paradigm classically used to test gaze and arow cuing effects in healthy adults, adapted to the capacities of patients with severe attention deficit. Here, we tested the robustness of the cuing effects measured by such a short version in 48 young adult healthy participants, 46 older healthy participants, 10 patients with left USN following a right brain lesion (USN+), and 10 patients with right brain lesions but no USN (USN–). We observed gaze and arrow cuing effects in all populations, independently of age and presence or absence of a right brain lesion. In the neglect field, the USN+ group showed event greater cuing effect than older healthy participants and the USN– group. We showed that gaze and arrow cuing effects are powerful enough to be detected in a very short test adapted to the capacities of older patients with severe attention deficits, which increases their applicability in rehabilitation settings. We further concluded that our test is a suitable basis to develop a tool that will help neuropsychologists to identify USN patients who respond to gaze and/or arrow cuing in their neglect field.

Sign in / Sign up

Export Citation Format

Share Document