Pietro Scatturin

Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data

Motion artifacts are a significant source of noise in many functional near-infrared spectroscopy (fNIRS) experiments. Despite this, there is no well-established method for their removal. Instead, functional trials of fNIRS data containing a motion artifact are often rejected completely. However, in most experimental circumstances the number of trials is limited, and multiple motion artifacts are common, particularly in challenging populations. Many methods have been proposed recently to correct for motion artifacts, including principle component analysis, spline interpolation, Kalman filtering, wavelet filtering and correlation-based signal improvement. The performance of different techniques has been often compared in simulations, but only rarely has it been assessed on real functional data. Here, we compare the performance of these motion correction techniques on real functional data acquired during a cognitive task, which required the participant to speak aloud, leading to a low-frequency, low-amplitude motion artifact that is correlated with the hemodynamic response. To compare the efficacy of these methods, objective metrics related to the physiology of the hemodynamic response have been derived. Our results show that it is always better to correct for motion artifacts than reject trials, and that wavelet filtering is the most effective approach to correcting this type of artifact, reducing the area under the curve where the artifact is present in 93% of the cases. Our results therefore support previous studies that have shown wavelet filtering to be the most promising and powerful technique for the correction of motion artifacts in fNIRS data. The analyses performed here can serve as a guide for others to objectively test the impact of different motion correction algorithms and therefore select the most appropriate for the analysis of their own fNIRS experiment.

Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study.

In the task-switching paradigm, reaction time is longer and accuracy is worse in switch trials relative to repetition trials. This so-called switch cost has been ascribed to the engagement of control processes required to alternate between distinct stimulus-response mapping rules. Neuroimaging studies have reported an enhanced activation of the human lateral prefrontal cortex and the superior frontal gyrus during the task-switching paradigm. Whether neural activation in these regions is dissociable and associated with separable cognitive components of task switching has been a matter of recent debate. We used multi-channel near-infrared spectroscopy (fNIRS) to measure brain cortical activity in a task-switching paradigm designed to avoid task differences, order predictability, and frequency effects. The results showed a generalized bilateral activation of the lateral prefrontal cortex and the superior frontal gyrus in both switch trials and repetition trials. To isolate the activity selectively associated with the task-switch, the overall activity recorded during repetition trials was subtracted from the activity recorded during switch trials. Following subtraction, the remaining activity was entirely confined to the left portion of the superior frontal gyrus. The present results suggest that factors associated with load and maintenance of distinct stimulus-response mapping rules in working memory are likely contributors to the activation of the lateral prefrontal cortex, whereas only activity in the left superior frontal gyrus can be linked unequivocally to switching between distinct cognitive tasks.

A new method based on ICBM152 head surface for probe placement in multichannel fNIRS

We propose a new probe placement method for multichannel functional Near Infrared Spectroscopy (fNIRS) based on the ICBM152 template, the most commonly used reference brain for neuroimaging. Our method is based on the use of a physical model of the ICBM152 head surface as reference scalp and its validity is supported by previous investigations of cranio-cerebral correlation. The method, intended for fNIRS group studies, dispenses with the use of individual MRI scan and digitizing procedure for each participant. The present approach offers a fast, simple, reproducible and straightforward method to place the probes on the head surface according to the MNI coordinates of the regions of interest with an average measurement error similar to those of previous methods. This ensures that fNIRS results can be readily compared within the neuroimaging community, both across studies and techniques.

A reference-channel based methodology to improve estimation of event-related hemodynamic response from fNIRS measurements

Functional near-infrared spectroscopy (fNIRS) uses near-infrared light to measure cortical concentration changes in oxygenated (HbO) and deoxygenated hemoglobin (HbR) held to be correlated with cognitive activity. Providing a parametric depiction of such changes in the classic form of stimulus-evoked hemodynamic responses (HRs) can be attained with this technique only by solving two problems. One problem concerns the separation of informative optical signal from structurally analogous noise generated by a variety of spurious sources, such as heart beat, respiration, and vasomotor waves. Another problem pertains to the inherent variability of HRs, which is notoriously contingent on the type of experiment, brain region monitored, and human phenotype. A novel method was devised in the present context to solve both problems based on a two-step algorithm combining the treatment of noise-only data extrapolated from a reference-channel and a Bayesian filter applied on a per-trial basis. The present method was compared to two current methods based on conventional averaging, namely, a typical averaging method and an averaging method implementing the use of a reference-channel. The result of the comparison, carried out both on artificial and real data, revealed a sensitive accuracy improvement in HR estimation using the present method relative to each of the other methods.

Are the neural correlates of subitizing and estimation dissociable? An fNIRS investigation

Human performance in visual enumeration tasks typically shows two distinct patterns as a function of set size. For small sets, usually up to 4 items, numerosity judgments are extremely rapid, precise and confident, a phenomenon known as subitizing. When this limit is exceeded and serial counting is precluded, exact enumeration gives way to estimation: performance becomes error-prone and more variable. Surprisingly, despite the importance of subitizing and estimation in numerical cognition, only few neuroimaging studies have examined whether the neural activity related to these two phenomena can be dissociated. In the present work, we used multi-channel near-infrared spectroscopy (fNIRS) to measure hemodynamic activity of the bilateral parieto-occipital cortex during a visual enumeration task. Participants had to judge the numerosity of dot arrays and indicate it by means of verbal response. We observed a different hemodynamic pattern in the parietal cortex, both in terms of amplitude modulation and temporal profile, for numerosities below and beyond the subitizing range. Crucially, the neural dissociation between subitizing and estimation was strongest at the level of right IPS. The present findings confirm that fNIRS can be successfully used to detect subtle temporal differences in hemodynamic activity and to produce inferences on the neural mechanisms underlying cognitive functions.

An exploratory fNIRS study with immersive virtual reality: a new method for technical implementation

For over two decades Virtual Reality (VR) has been used as a useful tool in several fields, from medical and psychological treatments, to industrial and military applications. Only in recent years researchers have begun to study the neural correlates that subtend VR experiences. Even if the functional Magnetic Resonance Imaging (fMRI) is the most common and used technique, it suffers several limitations and problems. Here we present a methodology that involves the use of a new and growing brain imaging technique, functional Near-infrared Spectroscopy (fNIRS), while participants experience immersive VR. In order to allow a proper fNIRS probe application, a custom-made VR helmet was created. To test the adapted helmet, a virtual version of the line bisection task was used. Participants could bisect the lines in a virtual peripersonal or extrapersonal space, through the manipulation of a Nintendo Wiimote ® controller in order for the participants to move a virtual laser pointer. Although no neural correlates of the dissociation between peripersonal and extrapersonal space were found, a significant hemodynamic activity with respect to the baseline was present in the right parietal and occipital areas. Both advantages and disadvantages of the presented methodology are discussed.

A hemodynamic correlate of lateralized visual short-term memories.

Neuroimaging studies attempting to isolate the neural substrate of visual short-term memory in humans have concentrated on the behavior of neurons populating the posterior part of the parietal cortex as a possible source of visual short-term memory capacity limits. Using a standard change-detection task, fMRI studies have shown that maintenance of bilaterally encoded objects elicited bilateral increases of hemodynamic activation in the intra-parietal and intra-occipital sulci (IPS-IOS) proportional to the number of objects retained in visual short-term memory. We used a spatially cued variant of the change-detection task to record hemodynamic responses to unilaterally encoded objects using functional near-infrared spectroscopy (fNIRS). Electrophysiological studies that employed this task have shown that maintenance of unilaterally encoded objects elicited posterior unilateral (contralateral) increase in event-related negativity proportional to the number of objects retained in visual short-term memory. We therefore examined whether contralateral increases in oxy-hemoglobin concentration correlated with the number of retained objects. Contrary to the idea that bilateral increases in BOLD responses and unilateral increases in event-related negativity may be different reflections of the same underlying neural/functional processing, memory-related increases in oxy-hemoglobin concentration were found bilaterally even when objects had to be encoded unilaterally. The present findings suggest that EEG and fMRI/fNIRS techniques reveal distinct neural signatures of the mechanisms supporting visual short-term memory.

Bayesian filtering of human brain hemodynamic activity elicited by visual short-term maintenance recorded through functional near-infrared spectroscopy (fNIRS).

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that measures changes in oxy-hemoglobin (ΔHbO) and deoxy-hemoglobin (ΔHbR) concentration associated with brain activity. The signal acquired with fNIRS is naturally affected by disturbances engendering from ongoing physiological activity (e.g., cardiac, respiratory, Mayer wave) and random measurement noise. Despite its several drawbacks, the so-called conventional averaging (CA) is still widely used to estimate the hemodynamic response function (HRF) from noisy signal. One such drawback is related to the number of trials necessary to derive stable HRF functions adopting the CA approach, which must be substantial (N >> 50). In this work, a pre-processing procedure to remove artifacts followed by the application of a non-parametric Bayesian approach is proposed that capitalizes on a priori available knowledge about HRF and noise. Results with the proposed Bayesian approach were compared with CA and with a straightforward band-pass filtering approach. On simulated data, a five times lower estimation error on HRF was obtained with respect to that obtained by CA, and 2.5 times lower than that obtained by band pass filtering. On real data, the improvement achieved by the present method was attested by an increase in the contrast to noise ratio (CNR) and by a reduced variability in single trial estimation. An application of the present Bayesian approach is illustrated that was optimized to monitor changes in hemodynamic activity reflecting variations in visual short-term memory load in humans, which are notoriously hard to detect using functional magnetic resonance imaging (fMRI). In particular, statistical analyses of HRFs recorded during a memory task established with high reliability the crucial role of the intraparietal sulcus and the intra-occipital sulcus in posterior areas of the human brain in visual short-term memory maintenance.

A methodology to improve estimation of stimulus-evoked hemodynamic response from fNIRS measurements

Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical neuroimaging method used to investigate functional activity of the cerebral cortex evoked by cognitive, visual, auditory and motor tasks, detecting regional changes of oxy- and deoxy-hemoglobin concentration. Accurate estimation of the stimulus-evoked hemodynamic response (HR) from fNIRS signals in order to quantitatively investigate cognitive functions requires to cope with several noise components. Some of them appear as random disturbances (typically tackled through averaging techniques), while others are due to physiological sources, such as heart beat, respiration, vasomotor waves, and are particularly challenging to be dealt with because they lie in the same frequency band of HR. In this work we present a new two-steps methodology for the HR estimation from fNIRS data. The first step is a pre-processing stage where physiological trends in fNIRS data are reduced by exploiting a mathematical model identified from the signal of a reference channel. In the second step, the pre-processed data of the other channels are filtered with a recently presented non-parametric Bayesian approach (Scarpa et al., Optics Express, 2010). The presented method for HR estimation is compared with widely used methods: conventional averaging, band-pass filtering and principal component analysis (PCA). Results on simulated data reveal the ability of the proposed method to improve the accuracy of the estimates of the functional hemodynamic response, as well as the estimate of peak amplitude and latency. Encouraging preliminary results in a representative real data set showing an improvement of contrast to noise ratio are also reported.

Altered social attention in anorexia nervosa during real social interaction.

The capacity to devote attentional resources in response to body-related signals provided by others is still largely unexplored in individuals with Anorexia Nervosa (AN). Here, we tested this capacity through a novel paradigm that mimics a social interaction with a real partner. Healthy individuals (Experiment 1) and individuals with AN (Experiment 2) completed a task with another person which consisted in performing, alternatively, rapid aiming movements to lateralised targets. Generally, this task leads to a form of Inhibition of Return (IOR), which consists of longer reaction times when an individual has to respond to a location previously searched by either himself (individual IOR) or by the partner (social IOR) as compared to previously unexplored locations. IOR is considered as an important attentional mechanism that promotes an effective exploration of the environment during social interaction. Here, healthy individuals displayed both individual and social IOR that were both reliable and of the same magnitude. Individuals with AN displayed a non-significant individual IOR but a reliable social IOR that was also significantly stronger than individual IOR. These results suggest the presence of a reduced sensitivity in processing body-related stimuli conveyed by oneself in individuals with AN which is reflected in action-based attentional processes.