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A NIRS-fMRI investigation of prefrontal cortex activity during a working memory task
Abstract
Near-infrared spectroscopy (NIRS) is commonly used for studying human brain function. However, several studies have shown that superficial hemodynamic changes such as skin blood flow can affect the prefrontal NIRS hemoglobin (Hb) signals. To examine the criterion-related validity of prefrontal NIRS-Hb signals, we focused on the functional signals during a working memory (WM) task and investigated their similarity with blood-oxygen-level-dependent (BOLD) signals simultaneously measured by functional magnetic resonance imaging (fMRI). We also measured the skin blood flow with a laser Doppler flowmeter (LDF) at the same time to examine the effect of superficial hemodynamic changes on the NIRS-Hb signals. Correlation analysis demonstrated that temporal changes in the prefrontal NIRS-Hb signals in the activation area were significantly correlated with the BOLD signals in the gray matter rather than those in the soft tissue or the LDF signals. While care must be taken when comparing the NIRS-Hb signal with the extracranial BOLD or LDF signals, these results suggest that the NIRS-Hb signal mainly reflects hemodynamic changes in the gray matter. Moreover, the amplitudes of the task-related responses of the NIRS-Hb signals were significantly correlated with the BOLD signals in the gray matter across participants, which means participants with a stronger NIRS-Hb response showed a stronger BOLD response. These results thus provide supportive evidence that NIRS can be used to measure hemodynamic signals originating from prefrontal cortex activation.
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“Research using these devices has demonstrated agreement between measurements obtained from fNIRS vs. the gold standard of functional magnetic resonance imaging (Mehagnoul-Schipper et al., 2002; Huppert et al., 2006; Sato et al., 2013; Moriguchi et al., 2017).”
From A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations (2018) · cites this paper as Sato et al., 2013
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Cites
Plum, F. (1960) · Archives of Neurology · doi:10.1001/archneur.1960.03840090124020 · Cited by 10,388
Cohen, J. (1992) · Psychological Bulletin · doi:10.1037//0033-2909.112.1.155 · Cited by 8,771
Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.24.9868 · Cited by 6,483
Thresholding of statistical maps in functional neuroimaging using the false discovery rate
Genovese, C. R., Lazar, N. A., & Nichols, T. (2002) · NeuroImage · doi:10.1006/nimg.2001.1037 · Cited by 4,923
Jöbsis, F. F. (1977) · Science · doi:10.1126/science.929199 · Cited by 3,899
Stereotaxic Display of Brain Lesions
Rorden, C., & Brett, M. (2000) · Behavioural Neurology · doi:10.1155/2000/421719 · Cited by 2,573
Taussig, M. (1991) · Routledge eBooks · doi:10.4324/9780203397244 · Cited by 2,403
Oxygenation‐sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields
Ogawa, S., Lee, T., Nayak, A. S., & Glynn, P. (1990) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910140108 · Cited by 2,269
Estimation of optical pathlength through tissue from direct time of flight measurement
Delpy, D. T., Cope, M., van der Zee, P., Arridge, S., Wray, S., & Wyatt, J. S. (1988) · Physics in Medicine and Biology · doi:10.1088/0031-9155/33/12/008 · Cited by 2,251
Fisher, R. A. (1915) · Biometrika · doi:10.1093/biomet/10.4.507 · Cited by 2,230
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Items 101–200 of 338
Funane, T., Sato, H. R., Yahata, N., Takizawa, R., Nishimura, Y., Kinoshita, A., Katura, T., Atsumori, H., Fukuda, M., Kasai, K., et al. (2015) · Neurophotonics · doi:10.1117/1.nph.2.1.015003 · Cited by 24
Self-citationYeung, M. K.-C., Lee, T., & Chan, A. S.-Y. (2019) · Autism Research · doi:10.1002/aur.2082 · Cited by 24
Noah, J. A., Dravida, S., Zhang, X., Yahil, S., & Hirsch, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0173525 · Cited by 24
Ayaz, H., & Dehais, F. (2021) · Wiley eBooks · doi:10.1002/9781119636113.ch31 · Cited by 26
Kawashima, C., Tanaka, Y., Inoue, A., Nakanishi, M., Okamoto, K., Maruyama, Y., Oshita, H., Ishitobi, Y., Aizawa, S., Masuda, K., et al. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.07.028 · Cited by 23
Tando, T., Kaga, Y., Ishii, S., 青柳, 閣., Sano, F., Kanemura, H., Sugita, K., & Aihara, M. (2014) · Brain and Development · doi:10.1016/j.braindev.2014.01.002 · Cited by 23
Photoneuromodulation makes a difficult cognitive task less arduous
Chan, A. S.-Y., Lee, T., Hamblin, M. R., & Cheung, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-93228-2 · Cited by 22
Skau, S., Helenius, O., Sundberg, K., Käll, L. B., & Kuhn, H. G. (2022) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2022.100180 · Cited by 26
Yang, C., Zhang, T., Huang, K., Xiong, M., Liu, H., Wang, P., & Zhang, Y. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1046849 · Cited by 22
Koch, J. K. L., Miguel, H. O., & Smiley‐Oyen, A. L. (2018) · Experimental Brain Research · doi:10.1007/s00221-018-5358-4 · Cited by 21
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Dashtestani, H., Zaragoza, R., Kermanian, R., Knutson, K. M., Halem, M., Casey, A., Karamzadeh, N. S., Anderson, A. A., Boccara, C., & Gandjbakhche, A. (2018) · Brain and Behavior · doi:10.1002/brb3.1116 · Cited by 24
Weyand, S., & Chau, T. T. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00536 · Cited by 21
Huang, C., Chou, P., Wei, H.-L., & Sun, C. (2015) · IEEE Journal of Selected Topics in Quantum Electronics · doi:10.1109/jstqe.2015.2503318 · Cited by 21
Zhou, G., Liu, J., Ding, X. P., Fu, G., & Lee, K. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00474 · Cited by 21
Anderson, A. A., Parsa, K., Geiger, S., Zaragoza, R., Kermanian, R., Miguel, H. O., Dashtestani, H., Chowdhry, F. A., Smith, E. G., Aram, S., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0198257 · Cited by 21
Berglund-Barraza, A., Tian, F., Basak, C., & Evans, J. L. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00433 · Cited by 27
Evaluation of neurocognitive function of prefrontal cortex in ornithine transcarbamylase deficiency
Anderson, A. A., Gropman, A. L., Mons, C. L., Stratakis, C. A., & Gandjbakhche, A. (2020) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2019.12.014 · Cited by 21
Ueda, S., Ota, T., Iida, J., Yamamuro, K., Yoshino, H., Kishimoto, N., & Kishimoto, T. (2018) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.12643 · Cited by 20
Uratani, M., Ota, T., Iida, J., Okazaki, K., Yamamuro, K., Nakanishi, Y., Kishimoto, N., & Kishimoto, T. (2019) · Child and Adolescent Psychiatry and Mental Health · doi:10.1186/s13034-019-0289-9 · Cited by 19
Interpersonal neural synchrony when predicting others’ actions during a game of rock-paper-scissors
Kayhan, E., Nguyen, T., Matthes, D., Langeloh, M., Michel, C., Jiang, J., & Hoehl, S. (2022) · Scientific Reports · doi:10.1038/s41598-022-16956-z · Cited by 18
Eleveld, N., Esquivel-Franco, D. C., Drost, G., Absalom, A. R., Zeebregts, C. J., de Vries, J. P. P. M., Elting, J. W. J., & Maurits, N. M. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12082776 · Cited by 20
You, Y., Liu, J., Yao, Z., Zhang, S., Chen, K., & Ma, X. (2023) · Sleep Medicine · doi:10.1016/j.sleep.2023.07.020 · Cited by 21
Shin, J. H., Kang, M. J., & Lee, S. A. (2024) · Human Brain Mapping · doi:10.1002/hbm.26619 · Cited by 18
Chou, P., Tang, K., Chen, Y., Sun, C., Huang, C., & Chen, D.-Y. (2018) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2018.01.030 · Cited by 20
Yoshiike, T., Honma, M., Yamada, N., Kim, Y., & Kuriyama, K. (2018) · Physiology & Behavior · doi:10.1016/j.physbeh.2018.06.015 · Cited by 21
Sutoko, S., Chan, Y. L., Obata, A. N., Sato, H. R., Maki, A., Numata, T., Funane, T., Atsumori, H., Kiguchi, M., Tang, T. B., et al. (2019) · Neurophotonics · doi:10.1117/1.nph.6.1.015001 · Cited by 19
Self-citationJiang, Y., Li, Z., Zhao, Y., Xiao, X. N., Zhang, Y., Sun, P., Yang, Y., & Zhu, C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116550 · Cited by 19
Future Applications of Real-World Neuroimaging to Clinical Psychology
Crum, J. E., II (2020) · Psychological Reports · doi:10.1177/0033294120926669 · Cited by 18
Schommartz, I., Dix, A., Passow, S., & Li, S. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.605190 · Cited by 20
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Pu, S., Nakagome, K., Yamada, T., Yokoyama, K., Matsumura, H., Mitani, H., Adachi, A., & Kaneko, K. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.06.052 · Cited by 18
Yeung, M. K.-C., Lee, T., & Chan, A. S.-Y. (2021) · Psychophysiology · doi:10.1111/psyp.13802 · Cited by 18
Prefrontal Hemodynamics in Toddlers at Rest: A Pilot Study of Developmental Variability
Anderson, A. A., Smith, E. G., Chowdhry, F. A., Thurm, A. E., Condy, E. E., Swineford, L. B., Manwaring, S. S., Amyot, F., Matthews, D., & Gandjbakhche, A. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00300 · Cited by 18
Prefrontal dysfunction in post-COVID-19 hyposmia: an EEG/fNIRS study
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Himichi, T., & Nomura, M. (2015) · Journal of Integrative Neuroscience · doi:10.1142/s0219635215500120 · Cited by 17
Kim, J.-Y., Kim, K.-I., Han, C. H., Lim, J., & Im, C. (2016) · Journal of Near Infrared Spectroscopy · doi:10.1255/jnirs.1242 · Cited by 20
Narita, Z. C., Noda, T., Setoyama, S., Sueyoshi, K., Inagawa, T., & Sumiyoshi, T. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2018.05.004 · Cited by 17
Yamazaki, H., Kanazawa, Y., & Omori, K. (2020) · Hearing Research · doi:10.1016/j.heares.2020.108024 · Cited by 17
Relaxing Effect Induced by Forest Sound in Patients with Gambling Disorder
Ochiai, H., Song, C., Jo, H., Oishi, M., Imai, M., & Miyazaki, Y. (2020) · Sustainability · doi:10.3390/su12155969 · Cited by 17
Memristor-Based CNNs for Detecting Stress Using Brain Imaging Signals
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Validation of a mobile fNIRS device for measuring working memory load in the prefrontal cortex
Boere, K., Hecker, K. G., & Krigolson, O. E. (2023) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2023.112275 · Cited by 17
Inamoto, K., Sakuma, S., Ariji, Y., Higuchi, N., Izumi, M., & Nakata, K. (2014) · Neuroscience Letters · doi:10.1016/j.neulet.2014.12.034 · Cited by 16
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Joshi, S., Weedon, B. D., Esser, P., Liu, Y.-C., Springett, D. N., Meaney, A., Inácio, M., Delextrat, A. A., Kemp, S., Ward, T. E., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-13966-9 · Cited by 15
Zhao, Q., Wang, Z., Yang, C., Han, C., Zhang, Y., Zeb, I., Wang, P., Wu, H., Xiao, Q., Xu, F., et al. (2024) · Psychophysiology · doi:10.1111/psyp.14564 · Cited by 15
Hemodynamic changes in the prefrontal cortex during working memory in essential hypertension
Grant, H., BHAMBHANI, Y. N., & Singhal, A. (2015) · Journal of the American Society of Hypertension · doi:10.1016/j.jash.2015.06.007 · Cited by 15
Tai Chi practice on prefrontal oxygenation levels in older adults: A pilot study
Tsang, W. W. N., Chan, K. K., Cheng, C. N., Hu, F. S. F., Mak, C. T. K., & Wong, J. W. C. (2018) · Complementary Therapies in Medicine · doi:10.1016/j.ctim.2018.11.005 · Cited by 15
Činčiūtė, S. (2019) · PeerJ · doi:10.7717/peerj.6621 · Cited by 18
Fujiwara, K., Shibata, M., Awano, Y., Shibayama, K., Iso, N., Matsuo, M., Nakashima, A., Moriuchi, T., Mitsunaga, W., & Higashi, T. (2021) · Neural Regeneration Research · doi:10.4103/1673-5374.313058 · Cited by 17
Ano, Y., Kobayashi, K., Hanyuda, M., & Kawashima, R. (2020) · Aging · doi:10.18632/aging.103951 · Cited by 15
Hernández‐Martín, E., & González–Mora, J. L. (2020) · Brain Science Advances · doi:10.26599/bsa.2020.9050014 · Cited by 15
Chou, P., Liu, W., Wang, S.-C., Lin, W.-H., Chung, Y.-L., Chang, C.-H., & Su, K. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1235713 · Cited by 15
Keshmiri, S., Sumioka, H., Yamazaki, R., & Ishiguro, H. (2018) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2018.00033 · Cited by 14
Mirbagheri, M., Hakimi, N., Ebrahimzadeh, E., & Setarehdan, S. K. (2019) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2019.100286 · Cited by 15
Pu, S., Nakagome, K., Yamada, T., Yokoyama, K., Matsumura, H., Nagata, I., & Kaneko, K. (2015) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2015.01.009 · Cited by 15
Siddiquee, M. R., Atri, R., Marquez, J. S., Hasan, S. M. S., Ramon, R., & Bai, O. (2020) · Sensors · doi:10.3390/s20185082 · Cited by 14
Wei, Y., Tang, X., Zhang, T., Su, W., Xu, L., Cui, H., Qian, Z., Zhang, T., & Wang, J. (2022) · General Psychiatry · doi:10.1136/gpsych-2021-100702 · Cited by 13
Zhang, B. B. B., Kan, R. L. D., Giron, C. G., Lin, T. T. Z., Yau, S., & Kranz, G. S. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1049130 · Cited by 14
Chou, P., Liu, W., Lin, W.-H., Hsu, C., Wang, S.-C., & Su, K. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.08.101 · Cited by 13
Kinoshita, A., Takizawa, R., Koike, S., Satomura, Y., Kawasaki, S., Kawakubo, Y., Marumo, K., Tochigi, M., Sasaki, T., Nishimura, Y., et al. (2015) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2015.04.006 · Cited by 13
Self-citationPrediction of epileptic seizures using fNIRS and machine learning
Guevara, E., Flores-Castro, J.-A., Peng, K., Nguyen, D. K., Lesage, F., Pouliot, P., & Rosas-Romero, R. (2019) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-190738 · Cited by 13
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Xiong, W., Ma, L., & Li, H. (2025) · Frontiers in Neuroscience · doi:10.3389/fnins.2025.1565848 · Cited by 13
Immink, M. A., Pointon, M., Wright, D. L., & Marino, F. E. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.644968 · Cited by 12
Ong, S., Husain, S. F., Wee, H. N., Ching, J., Kovalik, J., Cheng, M. S., Schwarz, H., Tang, T. B., & Ho, C. S. H. (2021) · Diagnostics · doi:10.3390/diagnostics11111978 · Cited by 12
Jeong, E., Ryu, H. B., Jo, G., & Jaehyeok, K. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15102075 · Cited by 12
Hosomi, F., Yanagi, M., Kawakubo, Y., Tsujii, N., Ozaki, S., & Shirakawa, O. (2019) · Scientific Reports · doi:10.1038/s41598-019-41739-4 · Cited by 15
The effects of exercise on mood and prefrontal brain responses to emotional scenes in smokers
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Fukumoto, Y., Todo, M., Bizen, H., Kimura, D., & Suzuki, T. (2022) · Neuroimage Reports · doi:10.1016/j.ynirp.2022.100083 · Cited by 12
Multimodal resting-state connectivity predicts affective neurofeedback performance
Trambaiolli, L. R., Cassani, R., Biazoli, C. E., Cravo, A. M., Sato, J. R., & Falk, T. H. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.977776 · Cited by 12
Tung, H., Lin, W.-H., Lan, T., Hsieh, P. F., Chiang, M., Lin, Y., & Peng, S. (2021) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2021.05.012 · Cited by 11
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Jeong, E., & Ryu, H. B. (2016) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2016.00134 · Cited by 11
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Liu, C., Xue, B., Yan, W., Rwei, A. Y., & Wu, C. (2022) · IEEE Open Journal of Nanotechnology · doi:10.1109/ojnano.2022.3226603 · Cited by 11
Hirao, K. (2014) · Journal of Educational Evaluation for Health Professions · doi:10.3352/jeehp.2014.11.24 · Cited by 11
Brain language networks and cognitive outcomes in children with frontotemporal lobe epilepsy
Hüsser, A. M., Vannasing, P., Tremblay, J., Osterman, B., Lortie, A., Diadori, P., Major, P., Rossignol, E., Roger, K., Fourdain, S., et al. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2023.1253529 · Cited by 11
Balconi, M., Allegretta, R. A., Acconito, C., Saquella, F., & Angioletti, L. (2025) · Sensors · doi:10.3390/s25061880 · Cited by 10
Wang, H., Ren, L., Yan, Z., Zhou, T., & Liang, Z. (2025) · npj Parkinson s Disease · doi:10.1038/s41531-025-01013-z · Cited by 10
Skau, S., Käll, L. B., Johansson, B., & Kuhn, H. G. (2021) · Neuroimage Reports · doi:10.1016/j.ynirp.2021.100038 · Cited by 12
Kamimura, H., Matsuoka, T., Okai, H., Shimizu, N., Harada, S., & Matsuo, K. (2022) · Scientific Reports · doi:10.1038/s41598-022-22345-3 · Cited by 12
Takahashi, T., Takikawa, Y., & Kawagoe, R. (2016) · Scientific Reports · doi:10.1038/srep20978 · Cited by 10
Keshmiri, S., Sumioka, H., Okubo, M., & Ishiguro, H. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00079 · Cited by 10
Diffuse Optical Tomography Using Bayesian Filtering in the Human Brain
Hernández‐Martín, E., & González–Mora, J. L. (2020) · Applied Sciences · doi:10.3390/app10103399 · Cited by 10
McKay, C., Shing, Y. L., Rafetseder, E., & Wijeakumar, S. (2021) · Developmental Science · doi:10.1111/desc.13094 · Cited by 10
Pu, S., Nakagome, K., Yamada, T., Matsumura, H., Yokoyama, K., Kaneko, K., & Kurosawa, Y. (2015) · PLoS ONE · doi:10.1371/journal.pone.0123972 · Cited by 10
Surface-based integration approach for fNIRS-fMRI reliability assessment
Bonilauri, A., Pirastru, A., Intra, F. S., Isernia, S., Cazzoli, M., Blasi, V., Baselli, G., & Baglio, F. (2023) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2023.109952 · Cited by 10
Pan, M., Zhao, M., Liu, L., Li, H., Wang, Y., & Qian, Q. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-037514 · Cited by 12
Katsumata, R., Hosokawa, T., Manabe, N., Mori, H., Wani, K., Ishii, K., Tanikawa, T., Urata, N., Ayaki, M., Nishino, K., et al. (2023) · Journal of Gastroenterology · doi:10.1007/s00535-023-02031-5 · Cited by 8
Cheering Enhances Inter‐Brain Synchronization Between Sensorimotor Areas of Player and Observer
Koide, T., & Shimada, S. (2018) · Japanese Psychological Research · doi:10.1111/jpr.12202 · Cited by 10
A Validation Study of a Middle Grades Reading Comprehension Assessment
Severino, L., DeCarlo, M. J. T., Sondergeld, T. A., İzzetoğlu, M., & Ammar, A. A. (2018) · RMLE Online · doi:10.1080/19404476.2018.1528200 · Cited by 9
Bronkhorst, M., Mukisa, R., Colier, W. N. J. M., Stothers, L. S., & Macnab, A. J. (2019) · Optical Sensors · doi:10.1117/12.2525240 · Cited by 9
Chong, J. S., Chan, Y. L., Ebenezer, E. G. M., Chen, H. Y., Kiguchi, M., Lu, C., & Tang, T. B. (2020) · Scientific Reports · doi:10.1038/s41598-020-79053-z · Cited by 9
Self-citationLim, L. G., Ung, W. C., Chan, Y. L., Lu, C., Funane, T., Kiguchi, M., & Tang, T. B. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2021.3062117 · Cited by 9
Self-citationPu, S., Nakagome, K., Miura, A., Iwata, M., Nagata, I., & Kaneko, K. (2016) · Scientific Reports · doi:10.1038/srep30685 · Cited by 9
Takeda, K., Sumiyoshi, T., Matsumoto, M., Murayama, K., Ikezawa, S., Matsumoto, K., & Nakagome, K. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00178 · Cited by 10
Katsumata, R., Hosokawa, T., & Kamada, T. (2023) · Cureus · doi:10.7759/cureus.49877 · Cited by 9
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Rabbani, M. H. R., & Islam, S. M. R. (2021) · International Conference on Electrical Engineering and Information Communication Technology · doi:10.1109/iceeict53905.2021.9667844 · Cited by 8
Matsubara, T., Chen, C., Hirotsu, M., Watanuki, T., Harada, K., Watanabe, Y., Matsuo, K., & Nakagawa, S. (2022) · Journal of Affective Disorders · doi:10.1016/j.jad.2022.08.025 · Cited by 8
Functional near-infrared spectroscopy in elderly patients with four types of dementia
Mei, X., Zou, C.-J., Hu, J., Liu, X., Zheng, C., & Zhou, D. (2023) · World Journal of Psychiatry · doi:10.5498/wjp.v13.i5.203 · Cited by 8
Single-trial classification of NIRS data from prefrontal cortex during working memory tasks
Ang, K. K., Yu, J., & Guan, C. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6944009 · Cited by 8
Matsuoka, J., Koike, S., Satomura, Y., Okada, N., Nishimura, Y., Sakakibara, E., Sakurada, H., Yamagishi, M., Takahashi, K., Takayanagi, Y., et al. (2020) · Schizophrenia · doi:10.1038/s41537-020-00118-z · Cited by 8
Self-citationFrequency‐domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic
Molina‐Rodríguez, S., Fructuoso, M. M., Martı́nez, L. M., & Ibáñez-Ballesteros, J. (2022) · Psychophysiology · doi:10.1111/psyp.14063 · Cited by 8
Li, C., Wong, Y., Langhammer, B., Huang, F., Du, X., Wang, Y., Zhang, H., & Zhang, T. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.907186 · Cited by 8
Gorniak, S. L., Wagner, V. E., Vaughn, K. A., Perry, J. W., Cox, L. G., Hibino, H., Montero-Hernandez, S. A., Hernández, A. E., & Pollonini, L. (2023) · Experimental Brain Research · doi:10.1007/s00221-023-06581-1 · Cited by 8
Metadata
- Authors
- Sato, H., Yahata, N., Funane, T., Takizawa, R., Katura, T., Atsumori, H., Nishimura, Y., Kinoshita, A., Kiguchi, M., Koizumi, H., Fukuda, M., & Kasai, K.
- Affiliations
- Hitachi (Japan) (JP)
- The University of Tokyo (JP)
- King's College London (GB)
- Gunma University (JP)
- Corresponding author
- Sato, Hiroki
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-12
- Volume
- 83
- Pages
- 158-173
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2046254753
- Cited by
- 339
- References
- 70
- Citations by year
- 2026: 12 · 2025: 24 · 2024: 15 · 2023: 23 · 2022: 19 · 2021: 48 · 2020: 33 · 2019: 20 · 2018: 38 · 2017: 25 · 2016: 26 · 2015: 31 · 2014: 19 · 2013: 5
- FWCI
- 20.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Education, Culture, Sports, Science and Technology
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- near-infrared spectroscopy, prefrontal cortex, working memory, BOLD signal, criterion validity, skin blood flow, laser Doppler flowmetry, hemodynamic response
- MeSH terms
- Adult, Brain Mapping, Female, Humans, Magnetic Resonance Imaging, Male, Memory, Short-Term, Middle Aged, Nerve Net, Oxygen Consumption, Sensitivity and Specificity, Task Performance and Analysis, Reproducibility of Results, Prefrontal Cortex, Spectroscopy, Near-Infrared
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