Multimodal measurement approach to identify individuals with mild cognitive impairment: study protocol for a cross-sectional trial

Bernhard Grässler, Fabian Herold, Milos Dordevic, Tariq Ali Gujar, Sabine Darius, Irina Böckelmann, Notger G Müller, Anita Hökelmann, Bernhard Grässler, Fabian Herold, Milos Dordevic, Tariq Ali Gujar, Sabine Darius, Irina Böckelmann, Notger G Müller, Anita Hökelmann

Abstract

Introduction: The diagnosis of mild cognitive impairment (MCI), that is, the transitory phase between normal age-related cognitive decline and dementia, remains a challenging task. It was observed that a multimodal approach (simultaneous analysis of several complementary modalities) can improve the classification accuracy. We will combine three noninvasive measurement modalities: functional near-infrared spectroscopy (fNIRS), electroencephalography and heart rate variability via ECG. Our aim is to explore neurophysiological correlates of cognitive performance and whether our multimodal approach can aid in early identification of individuals with MCI.

Methods and analysis: This study will be a cross-sectional with patients with MCI and healthy controls (HC). The neurophysiological signals will be measured during rest and while performing cognitive tasks: (1) Stroop, (2) N-back and (3) verbal fluency test (VFT). Main aims of statistical analysis are to (1) determine the differences in neurophysiological responses of HC and MCI, (2) investigate relationships between measures of cognitive performance and neurophysiological responses and (3) investigate whether the classification accuracy can be improved by using our multimodal approach. To meet these targets, statistical analysis will include machine learning approaches.This is, to the best of our knowledge, the first study that applies simultaneously these three modalities in MCI and HC. We hypothesise that the multimodal approach improves the classification accuracy between HC and MCI as compared with a unimodal approach. If our hypothesis is verified, this study paves the way for additional research on multimodal approaches for dementia research and fosters the exploration of new biomarkers for an early detection of nonphysiological age-related cognitive decline.

Ethics and dissemination: Ethics approval was obtained from the local Ethics Committee (reference: 83/19). Data will be shared with the scientific community no more than 1 year following completion of study and data assembly.

Trial registration number: ClinicalTrials.gov, NCT04427436, registered on 10 June 2020, https://ichgcp.net/clinical-trials-registry/NCT04427436.

Keywords: cardiology; dementia; mental health; neurophysiology; physiology.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

Figures

Figure 1
Figure 1
Description of the Stroop paradigm. C, congruent condition; In, incongruent condition; M, mixed condition; s, seconds.
Figure 2
Figure 2
Description of N-back paradigm. 0, 0-back; 1, 1-back; 2, 2-back; s, seconds.
Figure 3
Figure 3
Description of verbal fluency test paradigm. s, seconds.
Figure 4
Figure 4
Visualization of the positions of the EEG electrodes and fNIRS optodes. IZ, inion; LPA, left preauricular point; NZ, nasion; RPA, right preauricular point.
Figure 5
Figure 5
EEG data processing pipeline. ICA, independent component analysis; Loreta, low-resolution electromagnetic tomography analysis.

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Source: PubMed

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