Assessing autism at its social and developmental roots: A review of Autism Spectrum Disorder studies using functional near-infrared spectroscopy

Liu, Tao; Liu, Xingchen; Yi, Li; Zhu, Chaozhe; Markey, Patrick S.; Pelowski, Matthew

doi:10.1016/j.neuroimage.2017.09.044

Cited by 46 publications

(26 citation statements)

References 127 publications

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“…Additionally, exciting research has been carried out in the study of atypical development, with a focus on executive and language dysfunctions, and neurodevelopmental disorders such as autism and attention‐deficit hyperactivity disorder that are difficult to investigate in tightly restrained environments as, for example, an fMRI scanner. In particular, the functional organization and the social brain within autism have been investigated both in children and adults, showing the ability of fNIRS to measure neurocognitive functions in these groups.…”

Section: Introductionmentioning

confidence: 99%

The present and future use of functional near‐infrared spectroscopy (fNIRS) for cognitive neuroscience

Pinti

Tachtsidis

Hamilton

et al. 2018

Annals of the New York Academy of Sciences

665

575

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The past few decades have seen a rapid increase in the use of functional near-infrared spectroscopy (fNIRS) in cognitive neuroscience. This fast growth is due to the several advances that fNIRS offers over the other neuroimaging modalities such as functional magnetic resonance imaging and electroencephalography/magnetoencephalography. In particular, fNIRS is harmless, tolerant to bodily movements, and highly portable, being suitable for all possible participant populations, from newborns to the elderly and experimental settings, both inside and outside the laboratory. In this review we aim to provide a comprehensive and state-of-the-art review of fNIRS basics, technical developments, and applications. In particular, we discuss some of the open challenges and the potential of fNIRS for cognitive neuroscience research, with a particular focus on neuroimaging in naturalistic environments and social cognitive neuroscience.

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Section: Introductionmentioning

confidence: 99%

The present and future use of functional near‐infrared spectroscopy (fNIRS) for cognitive neuroscience

Pinti

Tachtsidis

Hamilton

et al. 2018

Annals of the New York Academy of Sciences

665

575

View full text Add to dashboard Cite

show abstract

“…Functional nearinfrared spectroscopy (fNIRS) is non-invasive brain imaging technique that has relatively high temporal resolution, places few physical constraints, and is tolerant to motion artifact and electromagnetic noise (for review, see Scholkmann et al, 2014). Therefore, it is ideal for use with young children (Perlman et al, 2014;Liu et al, 2017). One recent study with fNIRS revealed that watching fantastical events performed by cartoon characters leads to increased activation in children's dlPFC relative to playing with them using a touch screen (Li et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Reality Status Judgments of Real and Fantastical Events in Children’s Prefrontal Cortex: An fNIRS Study

Liu

Woolley

et al. 2019

Front. Hum. Neurosci.

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The present study aimed to examine neural mechanisms underlying the ability to differentiate reality from fantasy. Using functional near-infrared spectroscopy (fNIRS), we measured prefrontal activations in children and adults while they performed a reality judgment task. Participants' task was to judge the reality status of events in fantastical and realistic videos. Behavioral data revealed that, although there was no accuracy difference, children showed significantly longer reaction times in making the judgments than did adults. The fNIRS data consistently revealed higher prefrontal activations in children than in adults when watching the videos and judging the reality of the events. These results suggest that when making judgments of event reality, children may require more cognitive resources and also mainly rely on their own personal experiences.

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“…There have also been reported some related, EEG-NIRS works in [58][59][60][61][62][63][64], where emotion diagnoses were investigated. As these works are out of the scope of the current paper, we omit a detailed description of these papers.…”

Section: Hybrid Bcimentioning

confidence: 99%

Deep recurrent–convolutional neural network for classification of simultaneous EEG–fNIRS signals

Ghonchi

Fateh

Abolghasemi

et al. 2020

IET signal process.

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Brain Computer Interface (BCI) is a powerful system for communicating between the brain and outside world. Traditional BCI systems work based on EEG signals only. Recently, researchers have used combination of EEG signals with other signals to improve the performance of BCI systems. Among these signals, the combination of EEG with fNIRS has achieved favorable results. In most studies, only EEGs or fNIRs have been considered as chain-like sequences, and do not consider complex correlations between adjacent signals, neither in time nor channel location. In this paper, a deep neural network model has been introduced to identify the exact objectives of the human brain by introducing temporal and spatial features. The proposed model incorporates spatial relationship between EEG and fNIRS signals. This could be implemented by transforming the sequences of these chain-like signals into hierarchical three-rank tensors. The tests show that the proposed model has a precision of 99.6%.

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Assessing autism at its social and developmental roots: A review of Autism Spectrum Disorder studies using functional near-infrared spectroscopy

Cited by 46 publications

References 127 publications

The present and future use of functional near‐infrared spectroscopy (fNIRS) for cognitive neuroscience

The present and future use of functional near‐infrared spectroscopy (fNIRS) for cognitive neuroscience

Reality Status Judgments of Real and Fantastical Events in Children’s Prefrontal Cortex: An fNIRS Study

Deep recurrent–convolutional neural network for classification of simultaneous EEG–fNIRS signals

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