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      Initial-Dip Existence and Estimation in Relation to DPF and Data Drift

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          Abstract

          Early de-oxygenation (initial dip) is an indicator of the primal cortical activity source in functional neuro-imaging. In this study, initial dip's existence and its estimation in relation to the differential pathlength factor (DPF) and data drift were investigated in detail. An efficient algorithm for estimation of drift in fNIRS data is proposed. The results favor the shifting of the fNIRS signal to a transformed coordinate system to infer correct information. Additionally, in this study, the effect of the DPF on initial dip was comprehensively analyzed. Four different cases of initial dip existence were treated, and the resultant characteristics of the hemodynamic response function (HRF) for DPF variation corresponding to particular near-infrared (NIR) wavelengths were summarized. A unique neuro-activation model and its iterative optimization solution that can estimate drift in fNIRS data and determine the best possible fit of HRF with free parameters were developed and herein proposed. The results were verified on simulated data sets. The algorithm is applied to free available datasets in addition to six healthy subjects those were experimented using fNIRS and observations and analysis regarding shape of HRF were summarized as well. A comparison with standard GLM is also discussed and effects of activity strength parameters have also been analyzed.

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          Most cited references 45

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          Statistical parametric maps in functional imaging: A general linear approach

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            Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions

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              Event-related fMRI: characterizing differential responses.

              We present an approach to characterizing the differences among event-related hemodynamic responses in functional magnetic resonance imaging that are evoked by different sorts of stimuli. This approach is predicated on a linear convolution model and standard inferential statistics as employed by statistical parametric mapping. In particular we model evoked responses, and their differences, in terms of basis functions of the peri-stimulus time. This facilitates a characterization of the temporal response profiles that has a high effective temporal resolution relative to the repetition time. To demonstrate the technique we examined differential responses to visually presented words that had been seen prior to scanning or that were novel. The form of these differences involved both the magnitude and the latency of the response components. In this paper we focus on bilateral ventrolateral prefrontal responses that show deactivations for previously seen words and activations for novel words.
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                Author and article information

                Contributors
                Journal
                Front Neuroinform
                Front Neuroinform
                Front. Neuroinform.
                Frontiers in Neuroinformatics
                Frontiers Media S.A.
                1662-5196
                11 December 2018
                2018
                : 12
                Affiliations
                Department of Opto-Mechatronics Engineering, Pusan National University , Busan, South Korea
                Author notes

                Edited by: Arjen van Ooyen, VU University Amsterdam, Netherlands

                Reviewed by: Noman Naseer, Air University, Pakistan; Tong Boon Tang, Universiti Teknologi Petronas, Malaysia

                *Correspondence: Myung-Yung Jeong myjeong@ 123456pusan.ac.kr
                10.3389/fninf.2018.00096
                6297380
                Copyright © 2018 Kamran, Naeem Mannan and Jeong.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Counts
                Figures: 13, Tables: 0, Equations: 15, References: 47, Pages: 13, Words: 6711
                Categories
                Neuroscience
                Original Research

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