Multiscale Entropy as a New Feature for EEG and fNIRS Analysis
The present study aims to apply multiscale entropy (MSE) to analyse brain activity in terms of brain complexity levels and to use simultaneous electroencephalogram and functional near-infrared spectroscopy (EEG/fNIRS) recordings for brain functional analysis. A memory task was selected to demonstrat...
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| Format: | Article |
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MDPI AG
2020-02-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/22/2/189 |
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| author | Thanate Angsuwatanakul Jamie O’Reilly Kajornvut Ounjai Boonserm Kaewkamnerdpong Keiji Iramina |
| author_facet | Thanate Angsuwatanakul Jamie O’Reilly Kajornvut Ounjai Boonserm Kaewkamnerdpong Keiji Iramina |
| author_sort | Thanate Angsuwatanakul |
| collection | DOAJ |
| description | The present study aims to apply multiscale entropy (MSE) to analyse brain activity in terms of brain complexity levels and to use simultaneous electroencephalogram and functional near-infrared spectroscopy (EEG/fNIRS) recordings for brain functional analysis. A memory task was selected to demonstrate the potential of this multimodality approach since memory is a highly complex neurocognitive process, and the mechanisms governing selective retention of memories are not fully understood by other approaches. In this study, 15 healthy participants with normal colour vision participated in the visual memory task, which involved the making the executive decision of remembering or forgetting the visual stimuli based on his/her own will. In a continuous stimulus set, 250 indoor/outdoor scenes were presented at random, between periods of fixation on a black background. The participants were instructed to make a binary choice indicating whether they wished to remember or forget the image; both stimulus and response times were stored for analysis. The participants then performed a scene recognition test to confirm whether or not they remembered the images. The results revealed that the participants intentionally memorising a visual scene demonstrate significantly greater brain complexity levels in the prefrontal and frontal lobe than when purposefully forgetting a scene; <i>p</i> < 0.05 (two-tailed). This suggests that simultaneous EEG and fNIRS can be used for brain functional analysis, and MSE might be the potential indicator for this multimodality approach. |
| first_indexed | 2024-04-13T00:46:16Z |
| format | Article |
| id | doaj.art-17544a6904bb417b95f332ea125b72e7 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-13T00:46:16Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-17544a6904bb417b95f332ea125b72e72022-12-22T03:10:00ZengMDPI AGEntropy1099-43002020-02-0122218910.3390/e22020189e22020189Multiscale Entropy as a New Feature for EEG and fNIRS AnalysisThanate Angsuwatanakul0Jamie O’Reilly1Kajornvut Ounjai2Boonserm Kaewkamnerdpong3Keiji Iramina4Graduate School of Systems Life Sciences, Kyushu University, Fukuoka 819-0395, JapanCollege of Biomedical Engineering, Rangsit University, Pathum Thani 12000, ThailandBiological Engineering Program, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, ThailandBiological Engineering Program, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, ThailandGraduate School of Systems Life Sciences, Kyushu University, Fukuoka 819-0395, JapanThe present study aims to apply multiscale entropy (MSE) to analyse brain activity in terms of brain complexity levels and to use simultaneous electroencephalogram and functional near-infrared spectroscopy (EEG/fNIRS) recordings for brain functional analysis. A memory task was selected to demonstrate the potential of this multimodality approach since memory is a highly complex neurocognitive process, and the mechanisms governing selective retention of memories are not fully understood by other approaches. In this study, 15 healthy participants with normal colour vision participated in the visual memory task, which involved the making the executive decision of remembering or forgetting the visual stimuli based on his/her own will. In a continuous stimulus set, 250 indoor/outdoor scenes were presented at random, between periods of fixation on a black background. The participants were instructed to make a binary choice indicating whether they wished to remember or forget the image; both stimulus and response times were stored for analysis. The participants then performed a scene recognition test to confirm whether or not they remembered the images. The results revealed that the participants intentionally memorising a visual scene demonstrate significantly greater brain complexity levels in the prefrontal and frontal lobe than when purposefully forgetting a scene; <i>p</i> < 0.05 (two-tailed). This suggests that simultaneous EEG and fNIRS can be used for brain functional analysis, and MSE might be the potential indicator for this multimodality approach.https://www.mdpi.com/1099-4300/22/2/189brain complexityelectroencephalogram (eeg)functional near-infrared spectroscopy (fnirs)multiscale entropy (mse) |
| spellingShingle | Thanate Angsuwatanakul Jamie O’Reilly Kajornvut Ounjai Boonserm Kaewkamnerdpong Keiji Iramina Multiscale Entropy as a New Feature for EEG and fNIRS Analysis Entropy brain complexity electroencephalogram (eeg) functional near-infrared spectroscopy (fnirs) multiscale entropy (mse) |
| title | Multiscale Entropy as a New Feature for EEG and fNIRS Analysis |
| title_full | Multiscale Entropy as a New Feature for EEG and fNIRS Analysis |
| title_fullStr | Multiscale Entropy as a New Feature for EEG and fNIRS Analysis |
| title_full_unstemmed | Multiscale Entropy as a New Feature for EEG and fNIRS Analysis |
| title_short | Multiscale Entropy as a New Feature for EEG and fNIRS Analysis |
| title_sort | multiscale entropy as a new feature for eeg and fnirs analysis |
| topic | brain complexity electroencephalogram (eeg) functional near-infrared spectroscopy (fnirs) multiscale entropy (mse) |
| url | https://www.mdpi.com/1099-4300/22/2/189 |
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