Best practices for fNIRS publications

Neurophotonics, Год журнала: 2021, Номер 8(01)

Опубликована: Янв. 7, 2021

The application of functional near-infrared spectroscopy (fNIRS) in the neurosciences has been expanding over last 40 years. Today, it is addressing a wide range applications within different populations and utilizes great variety experimental paradigms. With rapid growth diversification research methods, some inconsistencies are appearing way which methods presented, can make interpretation replication studies unnecessarily challenging. Society for Functional Near-Infrared Spectroscopy thus motivated to organize representative (but not exhaustive) group leaders field build consensus on best practices describing utilized fNIRS studies. Our paper designed provide guidelines help enhance reliability, repeatability, traceability reported encourage throughout community. A checklist provided guide authors preparation their manuscripts assist reviewers when evaluating papers.

Язык: Английский

---

Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

Journal of Neural Engineering, Год журнала: 2018, Номер 15(3), С. 036028 - 036028

Опубликована: Фев. 15, 2018

Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous system a device. BCI was historically performed using electroencephalography (EEG). In last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex outcomes. These performances achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall performances, we investigated capabilities fNIRS recordings state-of-the-art deep procedures. Approach. We guided left right hand motor imagery task on 15 subjects fixed response time 1 s experiment length 10 min. Left versus accuracy DNN in multi-modal recording modality estimated it compared standalone classifiers. Main results. At group level increase performance when considering classifier synergistic effect. Significance. can be significantly improved employing provide electrical hemodynamic activity information, combination advanced non-linear

Язык: Английский

---

Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review

Sensors, Год журнала: 2022, Номер 22(15), С. 5865 - 5865

Опубликована: Авг. 5, 2022

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better resolution, though it is constrained by its One important merit shared the that both modalities have favorable portability could be integrated into compatible experimental setup, providing compelling ground development of multimodal fNIRS-EEG integration analysis approach. Despite growing number studies using concurrent designs reported in recent years, methodological reference past remains unclear. To fill this knowledge gap, review critically summarizes status methods currently used studies, an up-to-date overview guideline future projects to conduct studies. A literature search was conducted PubMed Web Science through 31 August 2021. After screening qualification assessment, 92 involving data recordings analyses were included final review. Specifically, three categories analyses, including EEG-informed fNIRS-informed parallel identified explained with detailed description. Finally, we highlighted current challenges potential directions research.

Язык: Английский

---

A Mini-Review on Functional Near-Infrared Spectroscopy (fNIRS): Where Do We Stand, and Where Should We Go?

Photonics, Год журнала: 2019, Номер 6(3), С. 87 - 87

Опубликована: Авг. 1, 2019

This mini-review is aimed at briefly summarizing the present status of functional near-infrared spectroscopy (fNIRS) and predicting where technique should go in next decade. quotes 33 articles on different fNIRS basics technical developments 44 reviews applications published last eight years. The huge number review about a wide spectrum topics field cognitive social sciences, neuroimaging research, medicine testifies to maturity achieved by this non-invasive optical vascular-based technique. Today, has started be utilized healthy subjects while moving freely naturalistic settings. Further instrumental are expected done near future fully satisfy latter important aspect. In addition, procedures, including correction methods for strong extracranial interferences, need standardized before using as clinical tool individual patients. New research avenues such interactive neurosciences, cortical activation modulated type sport performance, during neurofeedback training highlighted.

Язык: Английский

---

Systemic physiology augmented functional near-infrared spectroscopy: a powerful approach to study the embodied human brain

Neurophotonics, Год журнала: 2022, Номер 9(03)

Опубликована: Июль 11, 2022

In this Outlook paper, we explain why an accurate physiological interpretation of functional near-infrared spectroscopy (fNIRS) neuroimaging signals is facilitated when systemic activity (e.g., cardiorespiratory and autonomic activity) measured simultaneously by employing physiology augmented (SPA-fNIRS). The rationale for SPA-fNIRS twofold: (i) enables a more complete understanding the fNIRS at head since they contain components originating from neurovascular coupling sources. with can be used regressing out confounding in signals. Misinterpretations thus minimized. (ii) to study embodied brain linking state entire body, allowing novel insights into their complex interplay. We envisage approach will become increasingly important future.

Язык: Английский

---

Mental workload assessment by monitoring brain, heart, and eye with six biomedical modalities during six cognitive tasks

Frontiers in Neuroergonomics, Год журнала: 2024, Номер 5

Опубликована: Март 12, 2024

Introduction The efficiency and safety of complex high precision human-machine systems such as in aerospace robotic surgery are closely related to the cognitive readiness, ability manage workload, situational awareness their operators. Accurate assessment mental workload could help preventing operator error allow for pertinent intervention by predicting performance declines that can arise from either work overload or under stimulation. Neuroergonomic approaches based on measures human body brain activity collectively provide sensitive reliable training environments. Methods In this study, we developed a new six-cognitive-domain task protocol, coupling it with six biomedical monitoring modalities concurrently capture correlates across longitudinal multi-day investigation. Utilizing two distinct each aspect cardiac (ECG PPG), ocular (EOG eye-tracking), (EEG fNIRS), 23 participants engaged four sessions over 4 weeks, performing tasks associated working memory, vigilance, risk assessment, shifting attention, situation awareness, inhibitory control. Results results revealed varying levels sensitivity within modality. While certain exhibited consistency tasks, neuroimaging modalities, particular, unveiled meaningful differences between conditions domains. Discussion This is first comprehensive comparison these brain-body multiple days findings underscore potential wearable sensing methods evaluating workload. Such neuroergonomic inform development next generation neuroadaptive interfaces more efficient interaction skill acquisition.

Язык: Английский

---

Prediction of epileptic seizures with convolutional neural networks and functional near-infrared spectroscopy signals

Computers in Biology and Medicine, Год журнала: 2019, Номер 111, С. 103355 - 103355

Опубликована: Июль 10, 2019

Язык: Английский

---

fNIRS improves seizure detection in multimodal EEG-fNIRS recordings

Journal of Biomedical Optics, Год журнала: 2019, Номер 24(05), С. 1 - 1

Опубликована: Фев. 7, 2019

In the context of epilepsy monitoring, electroencephalography (EEG) remains modality choice. Functional near-infrared spectroscopy (fNIRS) is a relatively innovative that cannot only characterize hemodynamic profiles seizures but also allow for long-term recordings. We employ deep learning methods to investigate benefits integrating fNIRS measures seizure detection. designed recurrent neural network with long short-term memory units and subsequently validated it using CHBMIT scalp EEG database—a compendium 896 h surface After validating our EEG, fNIRS, multimodal data comprising corpus 89 from 40 refractory epileptic patients was used as model input evaluate integration measures. Following heuristic hyperparameter optimization, EEG-fNIRS provide superior performance metrics (sensitivity specificity 89.7% 95.5%, respectively) in detection task, low generalization errors loss. False rates are generally low, 11.8% 5.6% data, respectively. Employing neuroimaging, particularly EEG-fNIRS, patients, can enhance performance. Furthermore, proposed characterized herein offers promising framework future investigations prediction.

Язык: Английский

---

Toward Neuroscience of the Everyday World (NEW) using functional near-infrared spectroscopy

Current Opinion in Biomedical Engineering, Год журнала: 2021, Номер 18, С. 100272 - 100272

Опубликована: Фев. 6, 2021

Язык: Английский

---

Motion artifacts removal and evaluation techniques for functional near-infrared spectroscopy signals: A review

Frontiers in Neuroscience, Год журнала: 2022, Номер 16

Опубликована: Окт. 3, 2022

With the emergence of an increasing number functional near-infrared spectroscopy (fNIRS) devices, significant deterioration in measurement caused by motion artifacts has become essential research topic for fNIRS applications. However, a high requirement mathematics and programming limits related researches. Therefore, here we provide first comprehensive review artifact removal aiming to (i) summarize latest achievements, (ii) present solutions evaluation metrics from perspective application reproduction, (iii) predict future topics field. The synthesizes information fifty-one journal articles (screened according three criteria). Three hardware-based nine algorithmic are summarized, their requirements (compatible signal types, availability online applications, limitations) extensions discussed. Five noise suppression two distortion were synthesized evaluate methods. Moreover, highlight deficiencies existing research: balance between use auxiliary hardware that solution is not clarified; few studies mention filtering delay solutions, robustness stability under extreme conditions

Язык: Английский

---