Best practices for fNIRS publications

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

Simulating the cross-linguistic pattern of Optional Infinitive errors in children’s declaratives and Wh- questions

One of the most striking features of children’s early multi-word speech is their tendency to produce non-finite verb forms in contexts in which a finite verb form is required (Optional Infinitive [OI] errors, Wexler, 1994). MOSAIC is a computational model of language learning that simulates developmental changes in the rate of OI errors across several different languages by learning compound finite constructions from the right edge of the utterance (Freudenthal, Pine, Aguado-Orea, & Gobet, 2007; Freudenthal, Pine, & Gobet, 2006a, 2009). However, MOSAIC currently only simulates the pattern of OI errors in declaratives, and there are important differences in the cross-linguistic patterning of OI errors in declaratives and Wh- questions. In the present study, we describe a new version of MOSAIC that learns from both the right and left edges of the utterance. Our simulations demonstrate that this new version of the model is able to capture the cross-linguistic patterning of OI errors in declaratives in English, Dutch, German and Spanish by learning from declarative input, and the cross-linguistic patterning of OI errors in Wh- questions in English, German and Spanish by learning from interrogative input. These results show that MOSAIC is able to provide an integrated account of the cross-linguistic patterning of OI errors in declaratives and Wh- questions, and provide further support for the view, instantiated in MOSAIC, that OI errors are compound-finite utterances with missing modals or auxiliaries

An ERP study on L2 syntax processing: When do learners fail?

Event-related brain potentials (ERPs) can reveal online processing differences between native speakers and second language (L2) learners during language comprehension. Using the P600 as a measure of native-likeness, we investigated processing of grammatical gender agreement in highly proficient immersed Romance L2 learners of Dutch. We demonstrate that these late learners consistently fail to show native-like sensitivity to gender violations. This appears to be due to a combination of differences from the gender marking in their L1 and the relatively opaque Dutch gender system. We find that L2 use predicts the effect magnitude of non-finite verb violations, a relatively regular and transparent construction, but not that of gender agreement violations. There were no effects of age of acquisition, length of residence, proficiency or offline gender knowledge. Additionally, a within-subject comparison of stimulus modalities (written vs. auditory) shows that immersed learners may show some of the effects only in the auditory modality; in non-finite verb violations, an early native-like N400 was only present for auditory stimuli. However, modality failed to influence the response to gender. Taken together, the results confirm the persistent problems of Romance learners of Dutch with online gender processing and show that they cannot be overcome by reducing task demands related to the modality of stimulus presentation

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

Plasticity in bilateral superior temporal cortex: effects of deafness and cochlear implantation on auditory and visual speech processing

While many individuals can benefit substantially from cochlear implantation, the ability to perceive and understand auditory speech with a cochlear implant (CI) remains highly variable amongst adult recipients. Importantly, auditory performance with a CI cannot be reliably predicted based solely on routinely obtained information regarding clinical characteristics of the CI candidate. This review argues that central factors, notably cortical function and plasticity, should also be considered as important contributors to the observed individual variability in CI outcome. Superior temporal cortex (STC), including auditory association areas, plays a crucial role in the processing of auditory and visual speech information. The current review considers evidence of cortical plasticity within bilateral STC, and how these effects may explain variability in CI outcome. Furthermore, evidence of audio-visual interactions in temporal and occipital cortices is examined, and relation to CI outcome is discussed. To date, longitudinal examination of changes in cortical function and plasticity over the period of rehabilitation with a CI has been restricted by methodological challenges. The application of functional near-infrared spectroscopy (fNIRS) in studying cortical function in CI users is becoming increasingly recognised as a potential solution to these problems. Here we suggest that fNIRS offers a powerful neuroimaging tool to elucidate the relationship between audio-visual interactions, cortical plasticity during deafness and following cochlear implantation, and individual variability in auditory performance with a CI

Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network

The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing interest in characterizing the relationship between these measures in the distributed neural networks of the brain. In this study, we attempted an integration of structural and functional analyses of the human language circuits, including Wernicke's (WA), Broca's (BA) and supplementary motor area (SMA), using a combination of blood oxygen level dependent (BOLD) and diffusion tensor MRI.Functional connectivity was measured by low frequency inter-regional correlations of BOLD MRI signals acquired in a resting steady-state, and structural connectivity was measured by using adaptive fiber tracking with diffusion tensor MRI data. The results showed that different language pathways exhibited different structural and functional connectivity, indicating varying levels of inter-dependence in processing across regions. Along the path between BA and SMA, the fibers tracked generally formed a single bundle and the mean radius of the bundle was positively correlated with functional connectivity. However, fractional anisotropy was found not to be correlated with functional connectivity along paths connecting either BA and SMA or BA and WA. for use in diagnosing and determining disease progression and recovery

Recommendations for motion correction of infant fNIRS data applicable to data sets acquired with a variety of experimental designs and acquisition systems

Despite motion artifacts are a major source of noise in fNIRS infant data, how to approach motion correction in this population has only recently started to be investigated. Homer2 offers a wide range of motion correction methods and previous work on simulated and adult data suggested the use of Spline interpolation and Wavelet filtering as optimal methods for the recovery of trials affected by motion. However, motion artifacts in infant data differ from those in adults' both in amplitude and frequency of occurrence. Therefore, artifact correction recommendations derived from adult data might not be the optimal for infant data. We hypothesized that the combined use of Spline and Wavelet would outperform their individual use on data with complex profiles of motion artifacts. To demonstrate this, we first compared, on infant semi-simulated data, the performance of several motion correction techniques on their own and of the novel combined approach; then, we investigated the performance of Spline and Wavelet alone and in combination on real cognitive data from three datasets collected with infants of different ages (5, 7 and 10 months), with different tasks (auditory/visual and tactile) and with different NIRS systems. To quantitatively estimate and compare the efficacy of these techniques, we adopted four metrics: hemodynamic response recovery error, within-subject standard deviation, between-subjects standard deviation and number of trials that survived each correction method. Our results demonstrated that (i) it is always better correcting for motion artifacts than rejecting the corrupted trials; (ii) Wavelet filtering on its own and in combination with Spline interpolation seems to be the most effective approach in reducing the between- and the within-subject standard deviations. Importantly, the combination of Spline and Wavelet was the approach providing the best performance in semi-simulation both at low and high levels of noise, also recovering most of the trials affected by motion artifacts across all datasets, a crucial result when working with infant data. [Abstract copyright: Copyright © 2019. Published by Elsevier Inc.