@article{bed338146e3b420d91ca69f6828e0ca4,
title = "Locating Temporal Functional Dynamics of Visual Short-Term Memory Binding using Graph Modular Dirichlet Energy",
abstract = "Visual short-term memory binding tasks are a promising early marker for Alzheimer's disease (AD). To uncover functional deficits of AD in these tasks it is meaningful to first study unimpaired brain function. Electroencephalogram recordings were obtained from encoding and maintenance periods of tasks performed by healthy young volunteers. We probe the task's transient physiological underpinnings by contrasting shape only (Shape) and shape-colour binding (Bind) conditions, displayed in the left and right sides of the screen, separately. Particularly, we introduce and implement a novel technique named Modular Dirichlet Energy (MDE) which allows robust and flexible analysis of the functional network with unprecedented temporal precision. We find that connectivity in the Bind condition is less integrated with the global network than in the Shape condition in occipital and frontal modules during the encoding period of the right screen condition. Using MDE we are able to discern driving effects in the occipital module between 100-140 ms, coinciding with the P100 visually evoked potential, followed by a driving effect in the frontal module between 140-180 ms, suggesting that the differences found constitute an information processing difference between these modules. This provides temporally precise information over a heterogeneous population in promising tasks for the detection of AD.",
author = "Keith Smith and Benjamin Ricaud and Nauman Shahid and Stephen Rhodes and Starr, {John M.} and Augustin Ib{\'a}{\~n}ez and Parra, {Mario A.} and Javier Escudero and Pierre Vandergheynst",
note = "Funding Information: This study was partially supported by the Engineering and Physical Sciences Research Council (UK) via a DTP studentship to KS and the research project EP/N014421/1 to JE. KS was also awarded a JM Lessells Travel Scholarship from the Royal Society of Edinburgh to undertake collaborative research at EPFL. NS was supported by SNF grant 200021 154350/1 for the project {"}Towards signal processing on graphs{"}. AI is supported by CONICET, CONICYT/FONDECYT Regular (1130920), FONCyT-PICT 2012-0412, FONCyT-PICT 2012-1309, FONDAP 15150012, and INECO Foundation. MAP work was supported by Alzheimer's Society, Grant # ASR42303. This study was also supported by the MRC grant # MRC-R42552, awarded to MAP in collaboration with AI and JMS. We thank Jamie Crowther who assisted with data collection. We also acknowledge the support from the Alzheimer's Scotland Dementia Research and the Centre for Cognitive Ageing and Cognitive Epidemiology part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1) both from the University of Edinburgh. Publisher Copyright: {\textcopyright} 2017 The Author(s).",
year = "2017",
month = feb,
day = "10",
doi = "10.1038/srep42013",
language = "English",
volume = "7",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
}