Where to Begin? Surveying Anticipation in Neuroscience: An Essential Roadmapping Toolkit

Labra-Spröhnle, Fabián

doi:10.1007/978-3-319-31737-3_19-1

Cited by 2 publications

(2 citation statements)

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“…Moreover, the increasing attention to dynamics measures such as reaction time variability in ADHD during EF task, is also an illustrative example of another convergent trends in ADHD research (Kofler et al, 2013(Kofler et al, , 2018 Notwithstanding, an important epistemological caveat must be placed here to avoid misunderstandings, the "ratio cognoscendi " shall not be confused with the "ratio essendi " (Piaget, 2006) of the phenomena described and analysed by using multiscaling techniques, including those advocated in this work . It is important to bear in mind what Labra-Spröhnle (2017) and described about the complex epistemological dialectic between tools and theories and their explanatory limitations due to their mutual constructive entanglement.…”

Section: Discussionmentioning

confidence: 99%

“…In particular, the second chapter is a translational science, meta-theoretical exercise, devoted to developing tools and strategies to establish a bird's-eye view of some fundamental landmarks and grounding notions, directly related to the concept of "cognitive anticipation" in neuroscience. This chapter was published as; Labra-Spröhnle, F. (2017). Where to Begin?…”

Section: A Guided Synopsismentioning

confidence: 99%

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The Dynamic Patterns Of Thinking In Attention-Deficit/Hyperactivity Disorder (ADHD): Diagnostic Accuracy Of Euclidean, Multifractal And Lacunarity Measures

Labra-Spröhnle¹

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Background: Attention Deficit/Hyperactivity disorder (ADHD) is one of the most common and challenging childhood neurodevelopmental disorders, with an overall pooled prevalence rate of 7.2%. This condition is characterised by chronic, age-inappropriate levels of hyperactivity, inattention, and impulsivity. To this date the exact aetiology of ADHD remains unknown and controversial. Moreover, ADHD is a major diagnostic challenge for clinicians, since no useful bio-markers or “gold standard” diagnostic tests are available at present. Given this scenario, a translating research program is needed to identify robust bio-markers which would aid the future development of a test to assist in the screening, diagnosis and monitoring of ADHD. Objective: The main objective of this thesis is twofold. The first one is a translational science objective and it is aimed to devise, set, perform and report the strategies and translational steps required to render basic neuroscientific knowledge clinically operational for establishing a testing paradigm, and a set of biomarkers that could permit the assessment of executive function (EF) disorders, specifically ADHD. The second one is a translational research objective, aimed to carry-out a diagnostic accuracy study, phases I and II, by evaluating a new testing paradigm and a set of multiscale geometric and kinematic measures that could serve as biomarkers for ADHD, and that could in the future be implemented in a screening, diagnostic and monitoring test. Method: This work encompasses theoretical and empirical procedures. The variety of these procedures express the many dimensions of the translational tasks undertaken. The theoretical methods employed, include: conceptual analysis, critical analysis, theoretical systematisation and the epistemological assessment of EF, ADHD, and their associated notions. The empirical methods include those used in predictive modelling and also those employed in phases I and II of a diagnostic accuracy study. Results: The results of the conceptual analysis and of the theoretical systematisation of EF yielded a new theoretical definition of EF and a dynamic model of the inferential processes of thinking. Based on these a new testing paradigm was created to assess EF in ADHD children. This paradigm was implemented using a problem-solving task, which is a computer version of the board game called “Battleships”. The full task includes eight individual games, each one defined by a standard template with the positions of the ships. For phase I, the results showed that the mean of most of the multi-scale measures differed between the ADHD group and the control group at a 0.05 significance level. In regards to phase II, the fitted models using multi-scale measures provided very robust classifications. At the level of separate games, for a classifier using a naive logistic regression, the following values were obtained from the training dataset: Accuracy = 0.8692, p-value <2e-16, 95% confidence interval (CI)[0.846 to 0.951]; Sensitivity = 86.63%, CI [85.44% to 89.54%]; Specificity = 87.21%, CI [85.95% to 89.98%]; ROC AUC=0.935, CI [0.925 - 0.945]. At the level of the subject, summarising the classifier’s probabilities from the eight games played by each individual 100% classification accuracy was achieved. For the testing dataset, at the instance level, the values obtained were: Accuracy = 0.95, p-value = 0.003, CI [ 0.875 to 1.00]; Sensitivity = 100.00%, CI: [90.97% to 100.00%]; Specificity = 90.00%, CI [76.34% to 97.21%]. ROC AUC = 0.99, CI [0.992 - 1.00]. At the level of the subject, 100% classification accuracy was achieved. Conclusions: The outcomes from each translational step undertaken in this research support the strategies and procedures pursued to fulfil the translational science and translational research objectives of this thesis. There is a robust trend in the results which is compatible with the hypotheses of the clinical trial performed. Under similar conditions of testing these results seem, prima facie, to be an improvement in accuracy, sensitivity and specificity over any known objective test proposed to assist in the diagnosis of ADHD. The method presented here is a promising candidate to further develop a test for ADHD. Notwithstanding, the method in its actual form, is not ready to be used routinely in a clinical scenario. Before any clinical inception of this test, Phase III and IV diagnostic accuracy studies should be performed.

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Section: Discussionmentioning

confidence: 99%

Section: A Guided Synopsismentioning

confidence: 99%

The Dynamic Patterns Of Thinking In Attention-Deficit/Hyperactivity Disorder (ADHD): Diagnostic Accuracy Of Euclidean, Multifractal And Lacunarity Measures

Labra-Spröhnle¹

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Predictive Modelling of The Dynamic Patterns of Thinking in Attention-Deficit/Hyperactivity Disorder: Diagnostic Accuracy of Spatiotemporal Fractal Measures

Labra-Spröhnle¹,

Smith

Ahammer

et al. 2018

Preprint

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Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental condition characterized by executive function (EF) dynamics disturbances.Notwithstanding, current advances in translational neuroscience, no ADHD objective, clinically useful, diagnostic marker is available to date. Objectives: Using a customized definition of EF and a new clinical paradigm, we performed a prospective diagnostic accuracy trial to assess the diagnostic value of several fractal measures from the thinking processes or inferences in a cohort of ADHD children and typically developing controls. Method: We included children from age five to twelve diagnosed with a reference standard based on case history, physical and neurological examination, Conners 3 rd Edition, and DSM-V TM . The index test consisted of a computer-based inference task with a set of eight different instances of the "Battleships" game to be solved. A consecutive series of 18 cases and 18 controls (n = 36) recruited at the primary paediatrics service from the Nelson Marlborough Health in New Zealand underwent the reference standard and the index test. Several fractal measures were obtained from the inference task to produce supervised classification models. Results: Notably, the summarized logistic regression's predicted probabilities from the eight games played by each children yielded a 100% classification accuracy, sensitivity and specificity in both a training and an independent testing/validating cohort. Conclusions: From a translational vantage point the expeditious method and the robust results make this technique a promising candidate to develop a screening, diagnostic and monitoring system for ADHD, and may serve to assess other EF disturbances.

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Where to Begin? Surveying Anticipation in Neuroscience: An Essential Roadmapping Toolkit

Cited by 2 publications

References 31 publications

The Dynamic Patterns Of Thinking In Attention-Deficit/Hyperactivity Disorder (ADHD): Diagnostic Accuracy Of Euclidean, Multifractal And Lacunarity Measures

The Dynamic Patterns Of Thinking In Attention-Deficit/Hyperactivity Disorder (ADHD): Diagnostic Accuracy Of Euclidean, Multifractal And Lacunarity Measures

Predictive Modelling of The Dynamic Patterns of Thinking in Attention-Deficit/Hyperactivity Disorder: Diagnostic Accuracy of Spatiotemporal Fractal Measures

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