Differential activation of frontal and parietal regions during visual word recognition: an optical topography study

Cortical cognitive processing during reading captured using functional-near infrared spectroscopy

Neuroimaging studies using functional magnetic resonance imaging (fMRI) have provided unparalleled insights into the fundamental neural mechanisms underlying human cognitive processing, such as high-level linguistic processes during reading. Here, we build upon this prior work to capture sentence reading comprehension outside the MRI scanner using functional near infra-red spectroscopy (fNIRS) in a large sample of participants (n = 82). We observed increased task-related hemodynamic responses in prefrontal and temporal cortical regions during sentence-level reading relative to the control condition (a list of non-words), replicating prior fMRI work on cortical recruitment associated with high-level linguistic processing during reading comprehension. These results lay the groundwork towards developing adaptive systems to support novice readers and language learners by targeting the underlying cognitive processes. This work also contributes to bridging the gap between laboratory findings and more real-world applications in the realm of cognitive neuroscience.

The most fundamental and popular literature on functional near-infrared spectroscopy: a bibliometric analysis of the top 100 most cited articles

Background

Functional near infrared spectroscopy (fNIRS) has developed rapidly in recent years, and there are more and more studies on fNIRS. At present, there is no bibliometric analysis of the top 100 most cited articles on fNIRS research.

Objective

To identify the top 100 most cited articles on fNIRS and analyze those most fundamental and popular articles through bibliometric research methods.

Methods

The literature on fNIRS of web of science from 1990 to 2023 was searched and the top 100 most cited articles were identified by citations. Use the bibliometrix package in R studio and VOSviewer for data analysis and plotting to obtain the output characteristics and citation status of these 100 most cited articles, and analyze research trends in this field through keywords.

Results

A total of 9,424 articles were retrieved from web of science since 1990. The average citation number of the 100 articles was 457.4 (range from 260 to 1,366). Neuroimage published the most articles (n = 31). Villringer, A. from Leipzig University had the largest number of top 100 papers. Harvard University (n = 22) conducted most cited articles. The United States, Germany, Japan, and the United Kingdom had most cited articles, respectively. The most common keywords were near-infrared spectroscopy, activation, cerebral-blood-flow, brain, newborn-infants, oxygenation, cortex, fMRI, spectroscopy. The fund sources mostly came from National Institutes of Health Unitd States (NIH) and United States Department of Health Human Services (n = 28).

Conclusion

Neuroimage was the most popular journal. The top countries, institutions, and authors were the United States, Harvard University, and Villringer, A., respectively. Researchers and institutions from North America and Europe contributed the most. Near-infrared spectroscopy, activation, cerebral-blood-flow, brain, newborn-infants, oxygenation, cortex, fmri, spectroscopy, stimulation, blood-flow, light-propagation, infants, tissue comprise the future research directions and potential topic hotspots for fNIRS.

Neurovascular coupling dysfunction in high myopia patients: Evidence from a multi-modal magnetic resonance imaging analysis

BACKGROUND AND PURPOSE

To investigate neurovascular coupling dysfunction in high myopia (HM) patients.

MATERIALS AND METHODS

A total of 37 HM patients and 36 healthy controls were included in this study. Degree centrality (DC), regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF) maps were employed to represent neuronal activity. Cerebral blood perfusion was characterized by cerebral blood flow (CBF). The correlation coefficient was calculated to reflect the relationship between neuronal activity and cerebral blood perfusion. Pearson partial correlation analysis was utilized to evaluate the association between HM dysfunction and clinical indicators.

RESULTS

HM patients exhibited significant alterations in neurovascular coupling across 37 brain regions compared to healthy controls. The brain regions with marked changes varied among the four neurovascular coupling patterns, including the middle frontal gyrus, superior occipital gyrus, middle occipital gyrus, and fusiform gyrus. Additionally, the superior frontal gyrus orbital part, medial superior frontal gyrus, inferior occipital gyrus, and dorsolateral superior frontal gyrus displayed significant changes in three coupling patterns. In HM patients, the ReHo-CBF changes in the inferior frontal gyrus orbital part were positively correlated with best-corrected visual acuity (BCVA) and refractive diopter changes. Similarly, the ALFF-CBF changes in the inferior frontal gyrus orbital part showed a positive correlation with refractive diopter changes. ReHo-CBF and ALFF-CBF alterations in the paracentral lobule were positively correlated with BCVA and refractive diopter changes.

CONCLUSION

Our findings underscore the abnormal alterations in neurovascular coupling across multiple brain regions in HM patients. These results suggest that neurovascular dysfunction in HM patients may be associated with an aberrant visual regulation mechanism.

Application of pseudocontinuous arterial spin labeling perfusion imaging in children with autism spectrum disorders

Introduction

Pseudocontinuous Arterial Spin Labeling (pCASL) perfusion imaging allows non-invasive quantification of regional cerebral blood flow (CBF) as part of a multimodal magnetic resonance imaging (MRI) protocol. This study aimed to compare regional CBF in autism spectrum disorders (ASD) individuals with their age-matched typically developing (TD) children using pCASL perfusion imaging.

Materials and methods

This cross-sectional study enrolled 17 individuals with ASD and 13 TD children. All participants underwent pCASL examination on a 3.0 T MRI scanner. Children in two groups were assessed for clinical characteristics and developmental profiles using Autism Behavior Checklist (ABC) and Gesell development diagnosis scale (GDDS), respectively. We compared CBF in different cerebral regions of ASD and TD children. We also assessed the association between CBF and clinical characteristics/developmental profile.

Results

Compared with TD children, individuals with ASD demonstrated a reduction in CBF in the left frontal lobe, the bilateral parietal lobes, and the bilateral temporal lobes. Within the ASD group, CBF was significantly higher in the right parietal lobe than in the left side. Correlation analysis of behavior characteristics and CBF in different regions showed a positive correlation between body and object domain scores on the ABC and CBF of the bilateral occipital lobes, and separately, between language domain scores and CBF of the left frontal lobe. The score of the social and self-help domain was negatively correlated with the CBF of the left frontal lobe, the left parietal lobe, and the left temporal lobe.

Conclusion

Cerebral blood flow was found to be negatively correlated with scores in the social and self-help domain, and positively correlated with those in the body and object domain, indicating that CBF values are a potential MRI-based biomarker of disease severity in ASD patients. The findings may provide novel insight into the pathophysiological mechanisms of ASD.

Analysis of Brain Functional Connectivity Neural Circuits in Children With Autism Based on Persistent Homology

Autism spectrum disorder (ASD) is a complex neuropsychiatric disorder with a complex and unknown etiology. Statistics demonstrate that the number of people diagnosed with ASD is increasing in countries around the world. Currently, although many neuroimaging studies indicate that ASD is characterized by abnormal functional connectivity (FC) patterns within brain networks rather than local functional or structural abnormalities, the FC characteristics of ASD are still poorly understood. In this study, a Vietoris-Rips (VR) complex filtration model of the brain functional network was established by using resting-state functional magnetic resonance imaging (fMRI) data of children aged 6–13 years old [including 54 ASD patients and 52 typical development (TD) controls] from the Autism Brain Imaging Data Exchange (ABIDE) public database. VR complex filtration barcodes are calculated by using persistent homology to describe the changes in the FC neural circuits of brain networks. The number of FC neural circuits with different length ranges at different threshold values is calculated by using the barcodes, the different brain regions participating in FC neural circuits are discussed, and the connectivity characteristics of brain FC neural circuits in the two groups are compared and analyzed. Our results show that the number of FC neural circuits with lengths of 8–12 is significantly decreased in the ASD group compared with the TD control group at threshold values of 0.7, 0.8 and 0.9, and there is no significant difference in the number of FC neural circuits with lengths of 4–7 and 13–16 and lengths 16. When the thresholds are 0.7, 0.8, and 0.9, the number of FC neural circuits in some brain regions, such as the right orbital part of the superior frontal gyrus, the left supplementary motor area, the left hippocampus, and the right caudate nucleus, involved in the study is significantly decreased in the ASD group compared with the TD control group. The results of this study indicate that there are significant differences in the FC neural circuits of brain networks in the ASD group compared with the TD control group.

Data Processing in Functional Near-Infrared Spectroscopy (fNIRS) Motor Control Research

FNIRS pre-processing and processing methodologies are very important-how a researcher chooses to process their data can change the outcome of an experiment. The purpose of this review is to provide a guide on fNIRS pre-processing and processing techniques pertinent to the field of human motor control research. One hundred and twenty-three articles were selected from the motor control field and were examined on the basis of their fNIRS pre-processing and processing methodologies. Information was gathered about the most frequently used techniques in the field, which included frequency cutoff filters, wavelet filters, smoothing filters, and the general linear model (GLM). We discuss the methodologies of and considerations for these frequently used techniques, as well as those for some alternative techniques. Additionally, general considerations for processing are discussed.

Decoding of semantic categories of imagined concepts of animals and tools in fNIRS

Objective.Semantic decoding refers to the identification of semantic concepts from recordings of an individual's brain activity. It has been previously reported in functional magnetic resonance imaging and electroencephalography. We investigate whether semantic decoding is possible with functional near-infrared spectroscopy (fNIRS). Specifically, we attempt to differentiate between the semantic categories of animals and tools. We also identify suitable mental tasks for potential brain-computer interface (BCI) applications.Approach.We explore the feasibility of a silent naming task, for the first time in fNIRS, and propose three novel intuitive mental tasks based on imagining concepts using three sensory modalities: visual, auditory, and tactile. Participants are asked to visualize an object in their minds, imagine the sounds made by the object, and imagine the feeling of touching the object. A general linear model is used to extract hemodynamic responses that are then classified via logistic regression in a univariate and multivariate manner.Main results.We successfully classify all tasks with mean accuracies of 76.2% for the silent naming task, 80.9% for the visual imagery task, 72.8% for the auditory imagery task, and 70.4% for the tactile imagery task. Furthermore, we show that consistent neural representations of semantic categories exist by applying classifiers across tasks.Significance.These findings show that semantic decoding is possible in fNIRS. The study is the first step toward the use of semantic decoding for intuitive BCI applications for communication.

A Narrative Review on Clinical Applications of fNIRS

Functional near-infrared spectroscopy (fNIRS) is a relatively new imaging modality in the functional neuroimaging research arena. The fNIRS modality non-invasively investigates the change of blood oxygenation level in the human brain utilizing the transillumination technique. In the last two decades, the interest in this modality is gradually evolving for its real-time monitoring, relatively low-cost, radiation-less environment, portability, patient-friendliness, etc. Including brain-computer interface and functional neuroimaging research, this technique has some important application of clinical perspectives such as Alzheimer's disease, schizophrenia, dyslexia, Parkinson's disease, childhood disorders, post-neurosurgery dysfunction, attention, functional connectivity, and many more can be diagnosed as well as in some form of assistive modality in clinical approaches. Regarding the issue, this review article presents the current scopes of fNIRS in medical assistance, clinical decision making, and future perspectives. This article also covers a short history of fNIRS, fundamental theories, and significant outcomes reported by a number of scholarly articles. Since this review article is hopefully the first one that comprehensively explores the potential scopes of the fNIRS in a clinical perspective, we hope it will be helpful for the researchers, physicians, practitioners, current students of the functional neuroimaging field, and the related personnel for their further studies and applications.

Fixation-related NIRS indexes retinotopic occipital processing of parafoveal preview during natural reading

While word frequency and predictability effects have been examined extensively, any evidence on interactive effects as well as parafoveal influences during whole sentence reading remains inconsistent and elusive. Novel neuroimaging methods utilize eye movement data to account for the hemodynamic responses of very short events such as fixations during natural reading. In this study, we used the rapid sampling frequency of near-infrared spectroscopy (NIRS) to investigate neural responses in the occipital and orbitofrontal cortex to word frequency and predictability. We observed increased activation in the right ventral occipital cortex when the fixated word N was of low frequency, which we attribute to an enhanced cost during saccade planning. Importantly, unpredictable (in contrast to predictable) low frequency words increased the activity in the left dorsal occipital cortex at the fixation of the preceding word N-1, presumably due to an upcoming breach of top-down modulated expectation. Opposite to studies that utilized a serial presentation of words (e.g. Hofmann et al., 2014), we did not find such an interaction in the orbitofrontal cortex, implying that top-down timing of cognitive subprocesses is not required during natural reading. We discuss the implications of an interactive parafoveal-on-foveal effect for current models of eye movements.

Literacy acquisition: Reading development

Reading is a complex, multifactorial, and dynamic skill. Most of what we currently know about neural correlates underlying reading comes from studies carried out with adults. However, considering that adults are skilled readers, findings from these studies cannot be generalized to children who are still learning to read. The advancement of neuroimaging techniques allowed researchers to investigate the developmental fingerprints and neurocircuitry involved in reading in children. To highlight the contribution of neuroimaging in understanding reading development, we look at both reading components, namely, word identification and reading comprehension. This chapter covers the three literacy periods-emergent, early, and conventional literacy-to better understand how reading acquisition affects neural networks. Further, we discuss our findings in light of different cognitive reading models. Although it is important to consider both spatial and temporal measurements to provide a holistic account of reading-related brain activity, the current chapter focuses on the functional activation and connectivity of reading-related areas in typically developing children.

Feature Extraction and Classification Methods for Hybrid fNIRS-EEG Brain-Computer Interfaces

In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) patients is investigated. Brain tasks, channel selection methods, and feature extraction and classification algorithms available in the literature are reviewed. First, we categorize various types of patients with cognitive and motor impairments to assess the suitability of BCI for each of them. The prefrontal cortex is identified as a suitable brain region for imaging. Second, the brain activity that contributes to the generation of hemodynamic signals is reviewed. Mental arithmetic and word formation tasks are found to be suitable for use with LIS patients. Third, since a specific targeted brain region is needed for BCI, methods for determining the region of interest are reviewed. The combination of a bundled-optode configuration and threshold-integrated vector phase analysis turns out to be a promising solution. Fourth, the usable fNIRS features and EEG features are reviewed. For hybrid BCI, a combination of the signal peak and mean fNIRS signals and the highest band powers of EEG signals is promising. For classification, linear discriminant analysis has been most widely used. However, further research on vector phase analysis as a classifier for multiple commands is desirable. Overall, proper brain region identification and proper selection of features will improve classification accuracy. In conclusion, five future research issues are identified, and a new BCI scheme, including brain therapy for LIS patients and using the framework of hybrid fNIRS-EEG BCI, is provided.

A supplementary functional connectivity microstate attached to the default mode network in depression revealed by resting-state magnetoencephalography

Default mode network (DMN) has discernable involvement in the representation of negative, self-referential information in depression. Both increased and decreased resting-state functional connectivity between the anterior and posterior DMN have been observed in depression. These conflicting connectivity differences necessitated further exploration of the resting-state DMN dysfunction in depression. Hence, we investigated the time-varying dynamic interactions within the DMN via functional connectivity microstates in a sub-second level. 25 patients with depression and 25 matched healthy controls were enrolled in the MEG analysis. Spherical K-means algorithms embedded within an iterative optimization frame were applied to sliding windowed correlation matrices, resulting in sub-second alternations of two functional connectivity microstates for groups and highlighting the presence of functional variability. In the power dominant state, depressed patients showed a transient decreased pattern that reflected inter/intra-subnetwork deregulation. A supplementary negatively correlated state simultaneously presented with increased connectivity between the ventromedial prefrontal cortex (vmPFC) and the posterior cingulate cortex (PCC), two core nodes for the anterior and posterior DMN respectively. Additionally, depressed patients stayed longer in the supplementary microstate compared to healthy controls. During the time spent in the supplementary microstate, an attempt to compensate for the aberrant effect of vmPFC on PCC across DMN subnetworks was possibly made to balance the self-related processes disturbed by the dominant pattern. The functional compensation mechanism of the supplementary microstate attached to the dominant disrupted one provided a possible explanation to the existing inconsistent findings between the anterior and posterior DMN in depression.

The role of the putamen in language: a meta-analytic connectivity modeling study

The putamen is a subcortical structure that forms part of the dorsal striatum of basal ganglia, and has traditionally been associated with reinforcement learning and motor control, including speech articulation. However, recent studies have shown involvement of the left putamen in other language functions such as bilingual language processing (Abutalebi et al. 2012) and production, with some authors arguing for functional segregation of anterior and posterior putamen (Oberhuber et al. 2013). A further step in exploring the role of putamen in language would involve identifying the network of coactivations of not only the left, but also the right putamen, given the involvement of right hemisphere in high order language functions (Vigneau et al. 2011). Here, a meta-analytic connectivity modeling technique was used to determine the patterns of coactivation of anterior and bilateral putamen in the language domain. Based on previous evidence, we hypothesized that left putamen coactivations would include brain regions directly associated with language processing, whereas right putamen coactivations would encompass regions involved in broader semantic processes, such as memory and visual imagery. The results showed that left anterior putamen coactivated with clusters predominantly in left hemisphere, encompassing regions directly associated with language processing, a left posterior putamen network spanning both hemispheres, and cerebellum. In right hemisphere, coactivations were in both hemispheres, in regions associated with visual and orthographic processing. These results confirm the differential involvement of right and left putamen in different language components, thus highlighting the need for further research into the role of putamen in language.

Exploring effective multiplicity in multichannel functional near-infrared spectroscopy using eigenvalues of correlation matrices

Recent advances in multichannel functional near-infrared spectroscopy (fNIRS) allow wide coverage of cortical areas while entailing the necessity to control family-wise errors (FWEs) due to increased multiplicity. Conventionally, the Bonferroni method has been used to control FWE. While Type I errors (false positives) can be strictly controlled, the application of a large number of channel settings may inflate the chance of Type II errors (false negatives). The Bonferroni-based methods are especially stringent in controlling Type I errors of the most activated channel with the smallest [Formula: see text] value. To maintain a balance between Types I and II errors, effective multiplicity ([Formula: see text]) derived from the eigenvalues of correlation matrices is a method that has been introduced in genetic studies. Thus, we explored its feasibility in multichannel fNIRS studies. Applying the [Formula: see text] method to three kinds of experimental data with different activation profiles, we performed resampling simulations and found that [Formula: see text] was controlled at 10 to 15 in a 44-channel setting. Consequently, the number of significantly activated channels remained almost constant regardless of the number of measured channels. We demonstrated that the [Formula: see text] approach can be an effective alternative to Bonferroni-based methods for multichannel fNIRS studies.

A functional near-infrared spectroscopy study of lexical decision task supports the dual route model and the phonological deficit theory of dyslexia

The dual route model (DRM) of reading suggests two routes of reading development: the phonological and the orthographic routes. It was proposed that although the two routes are active in the process of reading; the first is more involved at the initial stages of reading acquisition, whereas the latter needs more reading training to mature. A number of studies have shown that deficient phonological processing is a core deficit in developmental dyslexia. According to the DRM, when the Lexical Decision Task (LDT) is performed, the orthographic route should also be involved when decoding words, whereas it is clear that when decoding pseudowords the phonological route should be activated. Previous functional near-infrared spectroscopy (fNIR) studies have suggested that the upper left frontal lobe is involved in decision making in the LDT. The current study used fNIR to compare left frontal lobe activity during LDT performance among three reading-level groups: 12-year-old children, young adult dyslexic readers, and young adult typical readers. Compared to typical readers, the children demonstrated lower activity under the word condition only, whereas the dyslexic readers showed lower activity under the pseudoword condition only. The results provide evidence for upper left frontal lobe involvement in LDT and support the DRM and the phonological deficit theory of dyslexia.

Beyond the N400: complementary access to early neural correlates of novel metaphor comprehension using combined electrophysiological and haemodynamic measurements

The simultaneous application of different neuroimaging methods combining high temporal and spatial resolution can uniquely contribute to current issues and open questions in the field of pragmatic language perception. In the present study, comprehension of novel metaphors was investigated using near-infrared spectroscopy (NIRS) combined with the simultaneous acquisition of electroencephalography (EEG)/event-related potentials (ERPs). For the first time, we investigated the effects of figurative language on early electrophysiological markers (P200, N400) and their functional relationship to cortical haemodynamic responses within the language network (Broca's area, Wernicke's area). To this end, 20 healthy subjects judged 120 sentences with respect to their meaningfulness, whereby phrases were either literal, metaphoric, or meaningless. Our results indicated a metaphor-specific P200 reduction and a linear increase of N400 amplitudes from literal over metaphoric to meaningless sentences. Moreover, there were metaphor related effects on haemodynamic responses accessed with NIRS, especially within the left lateral frontal cortex (Broca's area). Significant correlations between electrophysiological and haemodynamic responses indicated that P200 reductions during metaphor comprehension were associated with an increased recruitment of neural activity within left Wernicke's area, indicating a link between variations in neural activity and haemodynamic changes within Wernicke's area. This link may reflect processes related to interindividual differences regarding the ability to classify novel metaphors. The present study underlines the usefulness of simultaneous NIRS measurements in language paradigms - especially for investigating the functional significance of neurophysiological markers that have so far been rarely examined - as these measurements are easily and efficiently realizable and allow for a complementary examination of neural activity and associated metabolic changes in cortical areas.

Statistical analysis of high density diffuse optical tomography

High density diffuse optical tomography (HD-DOT) is a noninvasive neuroimaging modality with moderate spatial resolution and localization accuracy. Due to portability and wear-ability advantages, HD-DOT has the potential to be used in populations that are not amenable to functional magnetic resonance imaging (fMRI), such as hospitalized patients and young children. However, whereas the use of event-related stimuli designs, general linear model (GLM) analysis, and imaging statistics are standardized and routine with fMRI, such tools are not yet common practice in HD-DOT. In this paper we adapt and optimize fundamental elements of fMRI analysis for application to HD-DOT. We show the use of event-related protocols and GLM de-convolution analysis in un-mixing multi-stimuli event-related HD-DOT data. Statistical parametric mapping (SPM) in the framework of a general linear model is developed considering the temporal and spatial characteristics of HD-DOT data. The statistical analysis utilizes a random field noise model that incorporates estimates of the local temporal and spatial correlations of the GLM residuals. The multiple-comparison problem is addressed using a cluster analysis based on non-stationary Gaussian random field theory. These analysis tools provide access to a wide range of experimental designs necessary for the study of the complex brain functions. In addition, they provide a foundation for understanding and interpreting HD-DOT results with quantitative estimates for the statistical significance of detected activation foci.

Autoregressive model based algorithm for correcting motion and serially correlated errors in fNIRS

Systemic physiology and motion-induced artifacts represent two major sources of confounding noise in functional near infrared spectroscopy (fNIRS) imaging that can reduce the performance of analyses and inflate false positive rates (i.e., type I errors) of detecting evoked hemodynamic responses. In this work, we demonstrated a general algorithm for solving the general linear model (GLM) for both deconvolution (finite impulse response) and canonical regression models based on designing optimal pre-whitening filters using autoregressive models and employing iteratively reweighted least squares. We evaluated the performance of the new method by performing receiver operating characteristic (ROC) analyses using synthetic data, in which serial correlations, motion artifacts, and evoked responses were controlled via simulations, as well as using experimental data from children (3-5 years old) as a source baseline physiological noise and motion artifacts. The new method outperformed ordinary least squares (OLS) with no motion correction, wavelet based motion correction, or spline interpolation based motion correction in the presence of physiological and motion related noise. In the experimental data, false positive rates were as high as 37% when the estimated p-value was 0.05 for the OLS methods. The false positive rate was reduced to 5-9% with the proposed method. Overall, the method improves control of type I errors and increases performance when motion artifacts are present.

A working memory deficit among dyslexic readers with no phonological impairment as measured using the n-back task: an fNIR study

Data indicated that dyslexic individuals exhibited difficulties on tasks involving Working Memory (WM). Previous studies have suggested that these deficits stem from impaired processing in the Phonological Loop (PL). The PL impairment was connected to poor phonological processing. However, recent data has pointed to the Central Executive (CE) system as another source of WM deficit in dyslexic readers. This opened a debate whether the WM deficit stems solely from PL or can also be seen as an outcome of poor CE processing. In an attempt to verify this question, the current study compared adult skilled and compensated dyslexic readers with no impairment of phonological skills. The participants' PL and CE processing were tested by using the fNIR device attached to the frontal lobe and measured the changes in brain oxygen values when performing N-back task. As it was previously suggested, the N = 0 represented PL and N = 1 to 3 represent CE processing. It was hypothesized that dyslexic readers who show non-impaired phonological skills will exhibit deficits mainly in the CE subsystem and to a lesser extent in the PL. Results indicated that the two reading level groups did not differ in their accuracy and reaction times in any of the N-Back conditions. However, the dyslexic readers demonstrated significant lower maximum oxyHb values in the upper left frontal lobe, mainly caused due to a significant lower activity under the N = 1 condition. Significant task effects were found in the medial left hemisphere, and the high medial right hemisphere. In addition, significant correlations between fNIR-features, reading performance and speed of processing were found. The higher oxyHb values, the better reading and speed of processing performance obtained. The results of the current study support the hypothesis that at least for the group of dyslexics with non-impaired PL, WM deficit stems from poor CE activity.

Functional near-infrared spectroscopy for the assessment of overt reading

Functional near-infrared spectroscopy (fNIRS) has become increasingly established as a promising technique for monitoring functional brain activity. To our knowledge, no study has yet used fNIRS to investigate overt reading of irregular words and nonwords with a full coverage of the cerebral regions involved in reading processes. The aim of our study was to design and validate a protocol using fNIRS for the assessment of overt reading. Twelve healthy French-speaking adults underwent one session of fNIRS recording while performing an overt reading of 13 blocks of irregular words and nonwords. Reading blocks were separated by baseline periods during which participants were instructed to fixate a cross. Sources (n = 55) and detectors (n = 16) were placed bilaterally over frontal, temporal, parietal, and occipital regions. Two wavelengths were used: 690 nm, more sensitive to deoxyhemoglobin (HbR) concentration changes, and 830 nm, more sensitive to oxyhemoglobin (HbO) concentration changes. For all participants, total hemoglobin (HbT) concentrations (HbO + HbR) were significantly higher than baseline for both irregular word and nonword reading in the inferior frontal gyri, the middle and superior temporal gyri, and the occipital cortices bilaterally. In the temporal gyri, although the difference was not significant, [HbT] values were higher in the left hemisphere. In the bilateral inferior frontal gyri, higher [HbT] values were found in nonword than in irregular word reading. This activation could be related to the grapheme-to-phoneme conversion characterizing the phonological pathway of reading. Our findings confirm that fNIRS is an appropriate technique to assess the neural correlates of overt reading.

Functional near-infrared spectroscopy for the assessment of speech related tasks

Over the past years functional near-infrared spectroscopy (fNIRS) has substantially contributed to the understanding of language and its neural correlates. In contrast to other imaging techniques, fNIRS is well suited to study language function in healthy and psychiatric populations due to its cheap and easy application in a quiet and natural measurement setting. Its relative insensitivity for motion artifacts allows the use of overt speech tasks and the investigation of verbal conversation. The present review focuses on the numerous contributions of fNIRS to the field of language, its development, and related psychiatric disorders but also on its limitations and chances for the future.

A brief review on the use of functional near-infrared spectroscopy (fNIRS) for language imaging studies in human newborns and adults

Upon stimulation, real time maps of cortical hemodynamic responses can be obtained by non-invasive functional near-infrared spectroscopy (fNIRS) which measures changes in oxygenated and deoxygenated hemoglobin after positioning multiple sources and detectors over the human scalp. The current commercially available transportable fNIRS systems have a time resolution of 1-10 Hz, a depth sensitivity of about 1.5 cm, and a spatial resolution of about 1cm. The goal of this brief review is to report infants, children and adults fNIRS language studies. Since 1998, 60 studies have been published on cortical activation in the brain's classic language areas in children/adults as well as newborns using fNIRS instrumentations of different complexity. In addition, the basic principles of fNIRS including features, strengths, advantages, and limitations are summarized in terms that can be understood even by non specialists. Future prospects of fNIRS in the field of language processing imaging are highlighted.

The human execution/observation matching system investigated with a complex everyday task: a functional near-infrared spectroscopy (fNIRS) study

The investigation of brain areas involved in the human execution/observation matching system (EOM) has been limited to restricted motor actions when using common neuroimaging techniques such as functional magnetic resonance imaging (fMRI). A method which overcomes this limitation is functional near-infrared spectroscopy (fNIRS). In the present study, we explored the cerebral responses underlying action execution and observation during a complex everyday task. We measured brain activation of 39 participants during the performance of object-related reaching, grasping and displacing movements, namely setting and clearing a table, and observation of the same task from different perspectives. Observation of the table-setting task activated parts of a network matching those activated during execution of the task. Specifically, observation from an egocentric perspective led to a higher activation in the inferior parietal cortex than observation from an allocentric perspective, implicating that the viewpoint also influences the EOM during the observation of complex everyday tasks. Together these findings suggest that fNIRS is able to overcome the restrictions of common imaging methods by investigating the EOM with a naturalistic task.

Spatial sensitivity of acousto-optic and optical near-infrared spectroscopy sensing measurements

Near-infrared spectroscopy (NIRS) is a popular sensing technique to measure tissue oxygenation noninvasively. However, the region of interest (ROI) is often beneath a superficial layer, which affects its accuracy. By applying focused ultrasound in the ROI, acousto-optic (AO) techniques can potentially minimize the effect of physiological changes in the superficial layer. Using absorption perturbation experiments in both transmission and reflection modes, we investigated the spatial sensitivity distributions and mean penetration depths of an AO system based on a digital correlator and two popular NIRS systems based on i. intensity measurements using a single source and detector configuration, and ii. spatially resolved spectroscopy. Our results show that for both transmission and reflection modes, the peak relative sensitivities of the two NIRS systems are near to the superficial regions, whereas those of the AO technique are near to the ROIs. In the reflection mode, when the ROI is deeper than 14 mm, the AO technique has a higher absolute mean sensitivity than the two NIRS techniques. As the focused ultrasound is moved deeper into the turbid medium, the mean penetration depth increases accordingly. The focused ultrasound can shift the peak relative sensitivity of the AO measurement toward its focused region.

The developmental trajectory of brain-scalp distance from birth through childhood: implications for functional neuroimaging

Measurements of human brain function in children are of increasing interest in cognitive neuroscience. Many techniques for brain mapping used in children, including functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG), magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS), use probes placed on or near the scalp. The distance between the scalp and the brain is a key variable for these techniques because optical, electrical and magnetic signals are attenuated by distance. However, little is known about how scalp-brain distance differs between different cortical regions in children or how it changes with development. We investigated scalp-brain distance in 71 children, from newborn to age 12 years, using structural T1-weighted MRI scans of the whole head. Three-dimensional reconstructions were created from the scalp surface to allow for accurate calculation of brain-scalp distance. Nine brain landmarks in different cortical regions were manually selected in each subject based on the published fNIRS literature. Significant effects were found for age, cortical region and hemisphere. Brain-scalp distances were lowest in young children, and increased with age to up to double the newborn distance. There were also dramatic differences between brain regions, with up to 50% differences between landmarks. In frontal and temporal regions, scalp-brain distances were significantly greater in the right hemisphere than in the left hemisphere. The largest contributors to developmental changes in brain-scalp distance were increases in the corticospinal fluid (CSF) and inner table of the cranium. These results have important implications for functional imaging studies of children: age and brain-region related differences in fNIRS signals could be due to the confounding factor of brain-scalp distance and not true differences in brain activity.

Exploring the Neural Basis of Real-Life Joint Action: Measuring Brain Activation during Joint Table Setting with Functional Near-Infrared Spectroscopy

Many every-day life situations require two or more individuals to execute actions together. Assessing brain activation during naturalistic tasks to uncover relevant processes underlying such real-life joint action situations has remained a methodological challenge. In the present study, we introduce a novel joint action paradigm that enables the assessment of brain activation during real-life joint action tasks using functional near-infrared spectroscopy (fNIRS). We monitored brain activation of participants who coordinated complex actions with a partner sitting opposite them. Participants performed table setting tasks, either alone (solo action) or in cooperation with a partner (joint action), or they observed the partner performing the task (action observation). Comparing joint action and solo action revealed stronger activation (higher [oxy-Hb]-concentration) during joint action in a number of areas. Among these were areas in the inferior parietal lobule (IPL) that additionally showed an overlap of activation during action observation and solo action. Areas with such a close link between action observation and action execution have been associated with action simulation processes. The magnitude of activation in these IPL areas also varied according to joint action type and its respective demand on action simulation. The results validate fNIRS as an imaging technique for exploring the functional correlates of interindividual action coordination in real-life settings and suggest that coordinating actions in real-life situations requires simulating the actions of the partner.

Single-trial classification of antagonistic oxyhemoglobin responses during mental arithmetic

Near-infrared spectroscopy (NIRS) is a non-invasive optical technique that can be used for brain-computer interfaces (BCIs) systems. A common challenge for BCIs is a stable and reliable classification of single-trial data, especially for cognitive (mental) tasks. With antagonistic activation pattern, recently found for mental arithmetic (MA) tasks, an improved online classification for optical BCIs using MA should become possible. For this investigation, we used the data of a previous study where we found antagonistic activation patterns (focal bilateral increase of [oxy-Hb] in the dorsolateral prefrontal cortex in parallel with a [oxy-Hb] decrease in the medial area of the anterior prefrontal cortex) in eight subjects. We used the [oxy-Hb] responses to search for the best antagonistic feature combination and compared it to individual features from the same regions. In addition, we investigated the use of antagonistic [deoxy-Hb], total hemoglobin [Hbtot] and pairs of [oxy-Hb] and [deoxy-Hb] features as well as the existence of a group-related feature set. Our results indicate that the use of the antagonistic [oxy-Hb] features significantly increases the classification accuracy from 63.3 to 79.7%. These results support the hypothesis that antagonistic hemodynamic response patterns are a suitable control strategy for optical BCI, and that only two prefrontal NIRS channels are needed for good performance.

The role of orbitofrontal cortex in processing empathy stories in 4- to 8-year-old children

This study investigates the neuronal correlates of empathic processing in children aged 4–8 years, an age range discussed to be crucial for the development of empathy. Empathy, defined as the ability to understand and share another person's inner life, consists of two components: affective (emotion-sharing) and cognitive empathy (Theory of Mind). We examined the hemodynamic responses of preschool and school children (N = 48), while they processed verbal (auditory) and non-verbal (cartoons) empathy stories in a passive following paradigm, using functional Near-Infrared Spectroscopy. To control for the two types of empathy, children were presented blocks of stories eliciting either affective or cognitive empathy, or neutral scenes which relied on the understanding of physical causalities. By contrasting the activations of the younger and older children, we expected to observe developmental changes in brain activations when children process stories eliciting empathy in either stimulus modality toward a greater involvement of anterior frontal brain regions. Our results indicate that children's processing of stories eliciting affective and cognitive empathy is associated with medial and bilateral orbitofrontal cortex (OFC) activation. In contrast to what is known from studies using adult participants, no additional recruitment of posterior brain regions was observed, often associated with the processing of stories eliciting empathy. Developmental changes were found only for stories eliciting affective empathy with increased activation, in older children, in medial OFC, left inferior frontal gyrus, and the left dorsolateral prefrontal cortex. Activations for the two modalities differ only little, with non-verbal presentation of the stimuli having a greater impact on empathy processing in children, showing more similarities to adult processing than the verbal one. This might be caused by the fact that non-verbal processing develops earlier in life and is more familiar.

Sound to language: different cortical processing for first and second languages in elementary school children as revealed by a large-scale study using fNIRS

A large-scale study of 484 elementary school children (6-10 years) performing word repetition tasks in their native language (L1-Japanese) and a second language (L2-English) was conducted using functional near-infrared spectroscopy. Three factors presumably associated with cortical activation, language (L1/L2), word frequency (high/low), and hemisphere (left/right), were investigated. L1 words elicited significantly greater brain activation than L2 words, regardless of semantic knowledge, particularly in the superior/middle temporal and inferior parietal regions (angular/supramarginal gyri). The greater L1-elicited activation in these regions suggests that they are phonological loci, reflecting processes tuned to the phonology of the native language, while phonologically unfamiliar L2 words were processed like nonword auditory stimuli. The activation was bilateral in the auditory and superior/middle temporal regions. Hemispheric asymmetry was observed in the inferior frontal region (right dominant), and in the inferior parietal region with interactions: low-frequency words elicited more right-hemispheric activation (particularly in the supramarginal gyrus), while high-frequency words elicited more left-hemispheric activation (particularly in the angular gyrus). The present results reveal the strong involvement of a bilateral language network in children's brains depending more on right-hemispheric processing while acquiring unfamiliar/low-frequency words. A right-to-left shift in laterality should occur in the inferior parietal region, as lexical knowledge increases irrespective of language.

Quantitative evaluation of high-density diffuse optical tomography: in vivo resolution and mapping performance

Despite the unique brain imaging capabilities and advantages of functional near-infrared spectroscopy (fNIRS), including portability and comprehensive hemodynamic measurement, widespread acceptance in the neuroimaging community has been hampered by low spatial resolution and image localization errors. While recent technical developments such as high-density diffuse optical tomography (HD-DOT) have, in principle, been shown to have superior in silico image quality, the majority of optical imaging studies are still conducted with sparse fNIRS arrays, perhaps partially because the performance increases of HD-DOT appear incremental. Without a quantitative comparative analysis between HD-DOT and fNIRS, using both simulation and in vivo neuroimaging, the implications of the new HD-DOT technology have been difficult to judge. We present a quantitative comparison of HD-DOT and two commonly used fNIRS geometries using (1) standard metrics of image quality, (2) simulated brain mapping tasks, and (3) in vivo visual cortex mapping results in adult humans. The results show that better resolution and lower positional errors are achieved with HD-DOT and that these improvements provide a substantial advancement in neuroimaging capability. In particular, we demonstrate that HD-DOT enables detailed phase-encoded retinotopic mapping, while sparse arrays are limited to imaging individual block-design visual stimuli.

Pseudohomophone effects provide evidence of early lexico-phonological processing in visual word recognition

Previous research using event-related brain potentials (ERPs) suggested that phonological processing in visual word recognition occurs rather late, typically after semantic or syntactic processing. Here, we show that phonological activation in visual word recognition can be observed much earlier. Using a lexical decision task, we show that ERPs to pseudohomophones (PsHs) (e.g., ROZE) differed from well-matched spelling controls (e.g., ROFE) as early as 150 ms (P150) after stimulus onset. The PsH effect occurred as early as the word frequency effect suggesting that phonological activation occurs early enough to influence lexical access. Low-resolution electromagnetic tomography analysis (LORETA) revealed that left temporoparietal and right frontotemporal areas are the likely brain regions associated with the processing of phonological information at the lexical level. Altogether, the results show that phonological processes are activated early in visual word recognition and play an important role in lexical access.

Does familiarity or conflict account for performance in the word-stem completion task? Evidence from behavioural and event-related-potential data

The conflict monitoring theory (CMT) assumes that word-stems associated with several completions should lead to crosstalk and conflict due to underdetermined responding situation (Botvinick et al. in Psychol Rev 108(3):624-652, 2001). In contrast, the Multiple-Read-Out-Model (MROM) of Jacobs and Grainger (J Exp Psychol 20(6): 1311-1334, 1994) predicts a high level of general lexical activity (GLA) for word-stems with many completions, indicating a higher stimulus familiarity because these stems are more probable to be read. We compared word-stems with several completions against word-stems with one possible completion while measuring response times and electrophysiological recordings. Slowest response times and a distinct FN400 component, which has previously been related to the concept of familiarity (Curran in Memory Cogn 28(6):923-938, 2000), were apparent for word-stems that could only be associated with a single response. These findings support the claims of the MROM. Furthermore, the lack of the N2-component for word-stems with several completions continues to challenge the EEG-extension of the CMT (Yeung et al. in Psychol Rev 111(4):2004).