Computation of measures of effect size for neuroscience data sets

Hentschke, Harald; Stüttgen, Maik C.

doi:10.1111/j.1460-9568.2011.07902.x

Cited by 388 publications

(340 citation statements)

References 58 publications

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“…The p-values were corrected using the False Discovery Rate (FDR), through the Benjamini and Hochberg linear-step up procedure, when there are multiple comparisons problems. Additionally, the effect size was computed, using the Matlab toolbox provided by Hentschke and Stüttgen [53], in different comparisons. For correlation analysis between clinical scales and neurophysiology, the Spearman rank order correlation was used.…”

Section: Discussionmentioning

confidence: 99%

Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer’s Disease Detected Using Quantitative Electroencephalography

Villa-Ochoa

Alonso

Duque

et al. 2017

JAD

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Background: Presenilin-1 (PSEN1) mutations are the most common cause of familial early onset Alzheimer's Disease (AD). The PSEN1 E280A (E280A) mutation has an autosomal dominant inheritance and is involved in the production of amyloid-β. In Antioquia, Colombia, there is the largest family group of carriers with E280A mutation. The study of mutation carriers provides an unique opportunity to identify brain changes in stages previous to AD. Electroencephalography (EEG) is a low cost and minimally invasiveness technique that enables the following of brain changes in AD.Objective: To examine how previous reported differences in EEG for Theta and Alpha-2 rhythms in E280A subjects are related to specific regions in cortex and could be tracked across different ages. Methods: EEG signals were acquired during resting state from non-carriers and carriers, asymptomatic and symptomatic, subjects from E280A kindred from Antioquia, Colombia. Independent Component Analysis and inverse solution methods were used to locate brain regions related to differences in Theta and Alpha-2 bands.Results: Independent Component Analysis helps to identify two components, mainly related to the Precuneus, were the differences in Theta and Alpha-2 exist simultaneously at asymptomatic and symptomatic stage. When a ratio between Theta and Alpha-2 is used significant correlations exist with age and a composite cognitive scale. Conclusion:Theta and Alpha-2 rhythms are altered in E280A subjects. The alterations are possible to track at Precuneus regions using EEG, ICA and inverse solution methods.

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Section: Discussionmentioning

confidence: 99%

Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer’s Disease Detected Using Quantitative Electroencephalography

Villa-Ochoa

Alonso

Duque

et al. 2017

JAD

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“…The percent-explained variance (o 2 ) reflects how much of the variance in a neuron's firing rates can be explained by the individual factors. The percent-explained variance for two factors was calculated using the MATLAB effect size measures toolbox 55 in a 300 ms-sliding window, advanced in steps of 20 ms. All statistical tests were carried out in MATLAB or R.…”

Section: Methodsmentioning

confidence: 99%

Abstract rule neurons in the endbrain support intelligent behaviour in corvid songbirds

2013

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Despite the lack of a layered neocortex and fundamental differences in endbrain organization in birds compared with mammals, intelligent species evolved from both vertebrate classes. Among birds, corvids show exceptional cognitive flexibility. Here we explore the neuronal foundation of corvid cognition by recording single-unit activity from an association area known as the nidopallium caudolaterale (NCL) while carrion crows make flexible rule-guided decisions, a hallmark of executive control functions. The most prevalent activity in NCL represents the behavioural rules, while abstracting over sample images and sensory modalities of the rule cues. Rule coding is weaker in error trials, thus predicting the crows' behavioural decisions. This suggests that the abstraction of general principles may be an important function of the NCL, mirroring the function of primate prefrontal cortex. These findings emphasize that intelligence in vertebrates does not necessarily rely on a neocortex but can be realized in endbrain circuitries that developed independently via convergent evolution.

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“…A value of d =0.2 to 0.3 shows a small effect size, d ≥ 0.5 shows medium effect size and a value of d ≥ 0.8 shows large effect size [30]. The effect size for a feature is a more reliable measure for classification and it complements the p value statistics when sample size changes [31]. All statistical calculations were carried out using the Statistical toolbox in MATLAB R2012b.…”

Section: E Roc and Statistical Analysismentioning

confidence: 99%

Detecting Subclinical Diabetic Cardiac Autonomic Neuropathy by Analyzing Ventricular Repolarization Dynamics

Imam

Karmakar

Jelinek

et al. 2016

IEEE J. Biomed. Health Inform.

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In this study, a linear parametric modeling technique was applied to model ventricular repolarization (VR) dynamics. Three features were selected from the surface ECG recordings to investigate the changes in VR dynamics in healthy and cardiac autonomic neuropathy (CAN) participants with diabetes including heart rate variability (calculated from RR intervals), repolarization variability (calculated from QT intervals), and respiration [calculated by ECG-derived respiration (EDR)]. Surface ECGs were recorded in a supine resting position from 80 age-matched participants (40 with no cardiac autonomic neuropathy (NCAN) and 40 with CAN). In the CAN group, 25 participants had early/subclinical CAN (ECAN) and 15 participants were identified with definite/clinical CAN (DCAN). Detecting subclinical CAN is crucial for designing an effective treatment plan to prevent further cardiovascular complications. For CAN diagnosis, VR dynamics was analyzed using linear parametric autoregressive bivariate (ARXAR) and trivariate (ARXXAR) models, which were estimated using 250 beats of derived QT, RR, and EDR time series extracted from the first 5 min of the recorded ECG signal. Results showed that the EDR-based models gave a significantly higher fitting value (p < 0.0001) than models without EDR, which indicates that QT-RR dynamics is better explained by respiratory-information-based models. Moreover, the QT-RR-EDR model fitting values gradually decreased from the NCAN group to ECAN and DCAN groups, which indicate a decoupling of QT from RR and the respiration signal with the increase in severity of CAN. In this study, only the EDR-based model significantly distinguished ECAN and DCAN groups from the NCAN group (p < 0.05) with large effect sizes (Cohen's d > 0.75) showing the effectiveness of this modeling technique in detecting subclinical CAN. In conclusion, the EDR-based trivariate QT-RR-EDR model was found to be better in detecting the presence and severity of CAN than the bivariate QT-RR model. This finding also establishes the importance of adding respiratory information for analyzing the gradual deterioration of normal VR dynamics in pathological conditions, such as diabetic CAN.

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Computation of measures of effect size for neuroscience data sets

Cited by 388 publications

References 58 publications

Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer’s Disease Detected Using Quantitative Electroencephalography

Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer’s Disease Detected Using Quantitative Electroencephalography

Abstract rule neurons in the endbrain support intelligent behaviour in corvid songbirds

Detecting Subclinical Diabetic Cardiac Autonomic Neuropathy by Analyzing Ventricular Repolarization Dynamics

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