Estimation of partial optical path length in the brain in subject-specific head models for near-infrared spectroscopy

Nakamura, Kotaro; Kurihara, Kazuki; Kawaguchi, Hiroshi; Obata, Takayuki; Ito, Hiroshi; Okada, Eiji

doi:10.1007/s10043-016-0179-9

Cited by 9 publications

(7 citation statements)

References 20 publications

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“…Such individual anatomical difference is illustrated by evidence that each individual subject exhibits unique scalp and skull thickness, CSF distributions and cortical folding patterns (Hasan et al, 2007; H. Li, Ruan, Xie, Wang, & Liu, 2007). Moreover, a recent study provided direct evidence supporting our findings, because the partial optical pathlength in the brain decreases with an increase in the scalp‐brain distance varying with individuals and across brain regions (Nakamura et al, 2016).…”

Section: Discussionsupporting

confidence: 88%

“…Several studies have shown that the anatomical structure affects the sensitivity of the fNIRS signal by using realistic 3D head models (Custo, Wells, Barnett, Hillman, & Boas, 2006; Fukui, Ajichi, & Okada, 2003; Hoshi, Shimada, Sato, & Iguchi, 2005; Strangman et al, 2003). In particular, by constructing subject‐specific head models, Nakamura et al found that variability of the partial optical pathlength in the brain was very high between subjects and between fiducial points, and that partial optical pathlength was strongly associated with the depth of the brain surface (Nakamura et al, 2016). Moreover, the partial optical pathlength of the fNIRS probe pair depends not only on the individual's head structure, but also on the local head structure to which the probe is attached, even for the same individual subject.…”

Section: Introductionmentioning

confidence: 99%

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Targeting brain regions of interest in functional near‐infrared spectroscopy—Scalp‐cortex correlation using subject‐specific light propagation models

Cai

Nitta

Yokota

et al. 2021

Human Brain Mapping

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Targeting specific brain regions of interest by the accurate positioning of optodes (emission and detection probes) on the scalp remains a challenge for functional near‐infrared spectroscopy (fNIRS). Since fNIRS data does not provide any anatomical information on the brain cortex, establishing the scalp‐cortex correlation (SCC) between emission‐detection probe pairs on the scalp and the underlying brain regions in fNIRS measurements is extremely important. A conventional SCC is obtained by a geometrical point‐to‐point manner and ignores the effect of light scattering in the head tissue that occurs in actual fNIRS measurements. Here, we developed a sensitivity‐based matching (SBM) method that incorporated the broad spatial sensitivity of the probe pair due to light scattering into the SCC for fNIRS. The SCC was analyzed between head surface fiducial points determined by the international 10–10 system and automated anatomical labeling brain regions for 45 subject‐specific head models. The performance of the SBM method was compared with that of three conventional geometrical matching (GM) methods. We reveal that the light scattering and individual anatomical differences in the head affect the SCC, which indicates that the SBM method is compulsory to obtain the precise SCC. The SBM method enables us to evaluate the activity of cortical regions that are overlooked in the SCC obtained by conventional GM methods. Together, the SBM method could be a promising approach to guide fNIRS users in designing their probe arrangements and in explaining their measurement data.

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Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Targeting brain regions of interest in functional near‐infrared spectroscopy—Scalp‐cortex correlation using subject‐specific light propagation models

Cai

Nitta

Yokota

et al. 2021

Human Brain Mapping

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“…The usage of constant DPF values seems less-than-ideal because DPF values vary largely across individuals [122,123,193,194] and depend on (i) the wavelength used [122,123,192,194], (ii) the cortical area measured [122,123,190,192,195,196], (iii) the participants’ age [122,123,192,197], (iv) the size of the detector area [189], and (v) the source–detector separation [189]. Furthermore, as recently observed, the DPF can also change during the experiment [198].…”

Section: Discussionmentioning

confidence: 99%

Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging in Exercise–Cognition Science: A Systematic, Methodology-Focused Review

Herold

Wiegel

Scholkmann

et al. 2018

JCM

304

307

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For cognitive processes to function well, it is essential that the brain is optimally supplied with oxygen and blood. In recent years, evidence has emerged suggesting that cerebral oxygenation and hemodynamics can be modified with physical activity. To better understand the relationship between cerebral oxygenation/hemodynamics, physical activity, and cognition, the application of state-of-the art neuroimaging tools is essential. Functional near-infrared spectroscopy (fNIRS) is such a neuroimaging tool especially suitable to investigate the effects of physical activity/exercises on cerebral oxygenation and hemodynamics due to its capability to quantify changes in the concentration of oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb) non-invasively in the human brain. However, currently there is no clear standardized procedure regarding the application, data processing, and data analysis of fNIRS, and there is a large heterogeneity regarding how fNIRS is applied in the field of exercise–cognition science. Therefore, this review aims to summarize the current methodological knowledge about fNIRS application in studies measuring the cortical hemodynamic responses during cognitive testing (i) prior and after different physical activities interventions, and (ii) in cross-sectional studies accounting for the physical fitness level of their participants. Based on the review of the methodology of 35 as relevant considered publications, we outline recommendations for future fNIRS studies in the field of exercise–cognition science.

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“…None of the sixteen reviewed studies investigating the effect of ageing on fNIRS activity reported the DPF values used. The depth of the cortex will also affect the DPF, with considerable intersubject variability and differences between scalp locations having been reported (Nakamura et al, 2016). The effect of age related cortical thinning and grey matter atrophy may increase the cortical depth in addition to increasing the amount of cerebrospinal fluid in the subarachnoid space which would affect light attenuation (Purdon et al, 2015).…”

Section: Influence Of Ageing and Pdmentioning

confidence: 99%

“…The values of DPF are both age and wavelength dependent and display high intersubject variability (Duncan et al, 1996;Duncan et al, 1995). The mean optical path length also varies spatially and increases with depth of the brain surface (Nakamura et al, 2016). Another factor is what outcome measures are selected for statistical analysis, for example HbO 2 , HbR, total haemoglobin or a combination.…”

Section: Introductionmentioning

confidence: 99%

fNIRS response during walking — Artefact or cortical activity? A systematic review

Vitório

Stuart

Rochester

et al. 2017

Neuroscience & Biobehavioral Reviews

126

134

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This systematic review aims to (i) evaluate functional near infrared spectroscopy (fNIRS) walking study design in young adults, older adults and people with Parkinson's disease (PD); (ii) examine signal processing techniques to reduce artefacts and physiological noise in fNIRS data; and (iii) provide evidence-based recommendations for fNIRS walking study design and signal analysis techniques. An electronic search was undertaken. The search request detailed the measurement technique, cohort and walking task. Thirty-one of an initial yield of 73 studies satisfied the criteria. Protocols and methods for removing artefacts and noise varied. Differences in fNIRS signals between studies were found in rest vs. walking, speed of walking, usual vs. complex walking and easy vs. difficult tasks. In conclusion, there are considerable technical and methodological challenges in conducting fNIRS studies during walking which can introduce inconsistencies in study findings. We provide recommendations for the construction of robust methodologies and suggest signal processing techniques implementing a theoretical framework accounting for the physiology of haemodynamic responses.

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Estimation of partial optical path length in the brain in subject-specific head models for near-infrared spectroscopy

Cited by 9 publications

References 20 publications

Targeting brain regions of interest in functional near‐infrared spectroscopy—Scalp‐cortex correlation using subject‐specific light propagation models

Targeting brain regions of interest in functional near‐infrared spectroscopy—Scalp‐cortex correlation using subject‐specific light propagation models

Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging in Exercise–Cognition Science: A Systematic, Methodology-Focused Review

fNIRS response during walking — Artefact or cortical activity? A systematic review

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