Assessment of learning in simulator-based arthroscopy training with the diagnostic arthroscopy skill score (DASS) and neurophysiological measures.

PURPOSE: Virtual arthroscopic training has become increasingly popular. However, there is a lack of efficiency-based tracking of the trainee, which may be critical for determining the specifics of training programs and adapting them for the needs of each trainee. This study aims to evaluate and compare the measures obtained with a non-invasive neurophysiological method with The Diagnostic Arthroscopy Skill Score (DASS), a commonly used assessment tool for evaluating arthroscopic skills. METHODS: The study collected simulator performance scores, consisting of "Triangulation Right Hand", "Triangulation Left Hand", "Catch the Stars" and "Three Rings" and DASS scores from 22 participants (11 novices, 11 experts). These scores were obtained while participants underwent a structured program of exercises for the fundamentals of arthroscopic surgery training (FAST) and knee module using a simulator-based arthroscopy device. During the evaluation, data on oxy-hemoglobin and deoxy-hemoglobin levels in the prefrontal cortex were collected using the Functional Near-Infrared Spectroscopy (fNIRS) imaging system. Performance scores, DASS scores, and fNIRS data were subsequently analyzed to determine any correlation between performance and cortex activity. RESULTS: The simulator performance scores and the DASSPart2 scores were significantly higher in the expert group compared to the novice group (200.1 ± 28.5 vs 172.5 ± 48.9, p = 0.04 and 9.4 ± 5.6 vs. 5.4 ± 5.6 p = 0.02). In the expert group, fNIRS data showed a significantly lower prefrontal cortex activation during fundamental tasks in the FAST module, indicating significantly more efficient mental resource use. CONCLUSION: The analysis of cognitive workload changes during simulation-based arthroscopy training revealed a significant correlation between the trainees' DASS scores and fNIRS data. This correlation suggests the potential use of fNIRS data and DASS scores as additional metrics to create adaptive training protocols for each participant. By incorporating these metrics, the training process can be optimized, leading to more efficient arthroscopic training and better preparedness for clinical operations. LEVEL OF EVIDENCE: III.

Differences in time-frequency characteristics between healthy controls and TBI patients during hypercapnia assessed via fNIRS.

Damage to the cerebrovascular network is a universal feature of traumatic brain injury (TBI). This damage is present during different phases of the injury and can be non-invasively assessed using functional near infrared spectroscopy (fNIRS). fNIRS signals are influenced by partial arterial carbon dioxide (PaCO2), neurogenic, Mayer waves, respiratory and cardiac oscillations, whose characteristics vary in time and frequency and may differ in the presence of TBI. Therefore, this study aims to investigate differences in time-frequency characteristics of these fNIRS signal components between healthy controls and TBI patients and characterize the changes in their characteristics across phases of the injury. Data from 11 healthy controls and 21 TBI patients were collected during the hypercapnic protocol. Results demonstrated significant differences in low-frequency oscillations between healthy controls and TBI patients, with the largest differences observed in Mayer wave band (0.06 to 0.15 Hz), followed by the PaCO2 band (0.012 to 0.02 Hz). The effects within these bands were opposite, with (i) Mayer wave activity being lower in TBI patients during acute phase of the injury (d = 0.37 [0.16, 0.57]) and decreasing further during subacute (d = 0.66 [0.44, 0.87]) and postacute (d = 0.75 [0.50, 0.99]) phases; (ii) PaCO2 activity being lower in TBI patients only during acute phase of the injury (d = 0.36 [0.15, 0.56]) and stabilizing to healthy levels by the subacute phase. These findings demonstrate that TBI patients have impairments in low frequency oscillations related to different mechanisms and that these impairments evolve differently over the course of injury.

An Examination of the Effects of Virtual Reality Training on Spatial Visualization and Transfer of Learning.

Spatial visualization ability (SVA) has been identified as a potential key factor for academic achievement and student retention in Science, Technology, Engineering, and Mathematics (STEM) in higher education, especially for engineering and related disciplines. Prior studies have shown that training using virtual reality (VR) has the potential to enhance learning through the use of more realistic and/or immersive experiences. The aim of this study was to investigate the effect of VR-based training using spatial visualization tasks on participant performance and mental workload using behavioral (i.e., time spent) and functional near infrared spectroscopy (fNIRS) brain-imaging-technology-derived measures. Data were collected from 10 first-year biomedical engineering students, who engaged with a custom-designed spatial visualization gaming application over a six-week training protocol consisting of tasks and procedures that varied in task load and spatial characteristics. Findings revealed significant small (Cohen's d: 0.10) to large (Cohen's d: 2.40) effects of task load and changes in the spatial characteristics of the task, such as orientation or position changes, on time spent and oxygenated hemoglobin (HbO) measures from all the prefrontal cortex (PFC) areas. Transfer had a large (d = 1.37) significant effect on time spent and HbO measures from right anterior medial PFC (AMPFC); while training had a moderate (d = 0.48) significant effect on time spent and HbR measures from left AMPFC. The findings from this study have important implications for VR training, research, and instructional design focusing on enhancing the learning, retention, and transfer of spatial skills within and across various VR-based training scenarios.

Individual differences in skill acquisition and transfer assessed by dual task training performance and brain activity.

Assessment of expertise development during training program primarily consists of evaluating interactions between task characteristics, performance, and mental load. Such a traditional assessment framework may lack consideration of individual characteristics when evaluating training on complex tasks, such as driving and piloting, where operators are typically required to execute multiple tasks simultaneously. Studies have already identified individual characteristics arising from intrinsic, context, strategy, personality, and preference as common predictors of performance and mental load. Therefore, this study aims to investigate the effect of individual difference in skill acquisition and transfer using an ecologically valid dual task, behavioral, and brain activity measures. Specifically, we implemented a search and surveillance task (scanning and identifying targets) using a high-fidelity training simulator for the unmanned aircraft sensor operator, acquired behavioral measures (scan, not scan, over scan, and adaptive target find scores) using simulator-based analysis module, and measured brain activity changes (oxyhemoglobin and deoxyhemoglobin) from the prefrontal cortex (PFC) using a portable functional near-infrared spectroscopy (fNIRS) sensor array. The experimental protocol recruited 13 novice participants and had them undergo three easy and two hard sessions to investigate skill acquisition and transfer, respectively. Our results from skill acquisition sessions indicated that performance on both tasks did not change when individual differences were not accounted for. However inclusion of individual differences indicated that some individuals improved only their scan performance (Attention-focused group), while others improved only their target find performance (Accuracy-focused group). Brain activity changes during skill acquisition sessions showed that mental load decreased in the right anterior medial PFC (RAMPFC) in both groups regardless of individual differences. However, mental load increased in the left anterior medial PFC (LAMPFC) of Attention-focused group and decreased in the Accuracy-focused group only when individual differences were included. Transfer results showed no changes in performance regardless of grouping based on individual differences; however, mental load increased in RAMPFC of Attention-focused group and left dorsolateral PFC (LDLPFC) of Accuracy-focused group. Efficiency and involvement results suggest that the Attention-focused group prioritized the scan task, while the Accuracy-focused group prioritized the target find task. In conclusion, training on multitasks results in individual differences. These differences may potentially be due to individual preference. Future studies should incorporate individual differences while assessing skill acquisition and transfer during multitask training.

Functional near-infrared spectroscopy to assess pain in neonatal circumcisions.

INTRODUCTION: Pain assessment is challenging in neonates. Behavioral and physiological pain scales do not assess neocortical nociception, essential to pain encoding and central pain pathway development. Functional near-infrared spectroscopy (fNIRS) can assess neocortical activation to noxious stimuli from changes in oxy-(HbO) and total-hemoglobin concentrations (HbT). This study aims to assess fNIRS nociceptive functional activation in the prefrontal cortex of neonates undergoing circumcision through changes in HbO and HbT, and the correlation between changes in fNIRS and Neonatal Infant Pain Scale (NIPS), a behavioral pain assessment scale. METHODS: In healthy term neonates, HbO, HbT, and NIPS were recorded during sequential circumcision events 1-Prep before local anesthetic injection; 2-Local anesthetic injection; 3-Prep before incision; 4-Oral sucrose; 5-Incision; 6-Gomco (hemostatic device) attached; 7-Gomco twisted on; and 8-Gomco removed. fNIRS and NIPS changes after each event were assessed with Wilcoxon signed-rank test and summarized as median and interquartile range (IQR). Changes in fNIRS vs. NIPS were correlated with Spearman coefficient. RESULTS: In 31 neonates fNIRS increased (median [IQR] µmol/L) with noxious events: Local injection (HbO: 1.1 [0.5, 3.1], p < .001; HbT: 2.3 [0.2, 7.6], p < .001), Gomco attached (HbO: 0.7 [0.1, 1.7], p = .002; HbT: 0.7 [-0.2, 2.9], p = .02), and Gomco twisted on (HbO: 0.5 [-0.2, 1.7], p = .03; HbT: 0.8 [-0.1, 3.3], p = .02). fNIRS decreased with non-noxious event: Prep before incision (HbO: -0.6 [-1.2, -0.2] p < .001; HbT: -1 [-1.8, -0.4], p < .001). Local anesthetic attenuated fNIRS increases to subsequent sharp stimuli. NIPS increased with subsequent sharp stimuli despite local anesthetic. Although fNIRS and NIPS changed in the same direction, there was not a strong correlation between them. CONCLUSIONS: During neonatal circumcision, changes in fNIRS differed between different types of painful stimuli, which was not the case for NIPS, suggesting that fNIRS may complement NIPS to assess the quality of pain.

Evaluation of fNIRS signal components elicited by cognitive and hypercapnic stimuli.

Functional near infrared spectroscopy (fNIRS) measurements are confounded by signal components originating from multiple physiological causes, whose activities may vary temporally and spatially (across tissue layers, and regions of the cortex). Furthermore, the stimuli can induce evoked effects, which may lead to over or underestimation of the actual effect of interest. Here, we conducted a temporal, spectral, and spatial analysis of fNIRS signals collected during cognitive and hypercapnic stimuli to characterize effects of functional versus systemic responses. We utilized wavelet analysis to discriminate physiological causes and employed long and short source-detector separation (SDS) channels to differentiate tissue layers. Multi-channel measures were analyzed further to distinguish hemispheric differences. The results highlight cardiac, respiratory, myogenic, and very low frequency (VLF) activities within fNIRS signals. Regardless of stimuli, activity within the VLF band had the largest contribution to the overall signal. The systemic activities dominated the measurements from the short SDS channels during cognitive stimulus, but not hypercapnic stimulus. Importantly, results indicate that characteristics of fNIRS signals vary with type of the stimuli administered as cognitive stimulus elicited variable responses between hemispheres in VLF band and task-evoked temporal effect in VLF, myogenic and respiratory bands, while hypercapnic stimulus induced a global response across both hemispheres.

Studying Brain Activation during Skill Acquisition via Robot-Assisted Surgery Training.

Robot-assisted surgery systems are a recent breakthrough in minimally invasive surgeries, offering numerous benefits to both patients and surgeons including, but not limited to, greater visualization of the operation site, greater precision during operation and shorter hospitalization times. Training on robot-assisted surgery (RAS) systems begins with the use of high-fidelity simulators. Hence, the increasing demand of employing RAS systems has led to a rise in using RAS simulators to train medical doctors. The aim of this study was to investigate the brain activity changes elicited during the skill acquisition of resident surgeons by measuring hemodynamic changes from the prefrontal cortex area via a neuroimaging sensor, namely, functional near-infrared spectroscopy (fNIRS). Twenty-four participants, who are resident medical doctors affiliated with different surgery departments, underwent an RAS simulator training during this study and completed the sponge suturing tasks at three different difficulty levels in two consecutive sessions/blocks. The results reveal that cortical oxygenation changes in the prefrontal cortex were significantly lower during the second training session (Block 2) compared to the initial training session (Block 1) (p < 0.05).

Examining Mental Workload in a Spatial Navigation Transfer Game via Functional near Infrared Spectroscopy.

The goal of this study was to examine the effects of task-related variables, such as the difficulty level, problem scenario, and experiment week, on performance and mental workload of 27 healthy adult subjects during problem solving within the spatial navigation transfer (SNT) game. The study reports task performance measures such as total time spent on a task (TT) and reaction time (RT); neurophysiological measures involving the use of functional near-infrared spectroscopy (fNIRS); and a subjective rating scale for self-assessment of mental workload (NASA TLX) to test the related hypotheses. Several within-subject repeated-measures factorial ANOVA models were developed to test the main hypothesis. The results revealed a number of interaction effects for the dependent measures of TT, RT, fNIRS, and NASA TLX. The results showed (1) a decrease in TT and RT across the three levels of difficulty from Week 1 to Week 2; (2) an increase in TT and RT for high and medium cognitive load tasks as compared to low cognitive load tasks in both Week 1 and Week 2; (3) an overall increase in oxygenation from Week 1 to Week 2. These findings confirmed that both the behavioral performance and mental workload were sensitive to task manipulations.

Single-Trial Recognition of Video Gamer's Expertise from Brain Haemodynamic and Facial Emotion Responses.

With an increase in consumer demand of video gaming entertainment, the game industry is exploring novel ways of game interaction such as providing direct interfaces between the game and the gamers' cognitive or affective responses. In this work, gamer's brain activity has been imaged using functional near infrared spectroscopy (fNIRS) whilst they watch video of a video game (League of Legends) they play. A video of the face of the participants is also recorded for each of a total of 15 trials where a trial is defined as watching a gameplay video. From the data collected, i.e., gamer's fNIRS data in combination with emotional state estimation from gamer's facial expressions, the expertise level of the gamers has been decoded per trial in a multi-modal framework comprising of unsupervised deep feature learning and classification by state-of-the-art models. The best tri-class classification accuracy is obtained using a cascade of random convolutional kernel transform (ROCKET) feature extraction method and deep classifier at 91.44%. This is the first work that aims at decoding expertise level of gamers using non-restrictive and portable technologies for brain imaging, and emotional state recognition derived from gamers' facial expressions. This work has profound implications for novel designs of future human interactions with video games and brain-controlled games.

Early diagnosis of traumatic intracranial hematomas.

Timing of the intervention for intracranial hematomas is critical for its success, specifically since expansion of the hemorrhage can result in debilitating and sometimes fatal outcomes. Led by Britton Chance, we and an extended team from University of Pennsylvania, Baylor and Drexel universities developed a handheld brain hematoma detector for early triage and diagnosis of head trauma victims. After obtaining de novo Food and Drug Administration clearance, over 200 systems are deployed in all Marine battalion aid stations around the world. Infrascanner, a handheld brain hematoma detection system, is based on the differential near-infrared light absorption of the injured versus the noninjured part of brain. About 12 independent studies have been conducted in the USA, Canada, Spain, Italy, the Netherlands, Germany, Russia, Poland, Afghanistan, India, China, and Turkey. Here, we outline the background and design of the device as well as clinical studies with a total of 1293 patients and 203 hematomas. Infrascanner demonstrates high sensitivity (adults: 92.5% and children: 93%) and specificity (adults: 82.9% and children: 86.5%) in detecting intracranial hematomas >3.5 mL in volume and <2.5 cm from the surface of the brain. Infrascanner is a clinically effective screening solution for head trauma patients in prehospital settings where timely triage is critical.

Performance Monitoring via Functional Near Infrared Spectroscopy for Virtual Reality Based Basic Life Support Training.

The use of serious game tools in training of medical professions is steadily growing. However, there is a lack of reliable performance assessment methods to evaluate learner's outcome. The aim of this study is to determine whether functional near infrared spectroscopy (fNIRS) can be used as an additional tool for assessing the learning outcome of virtual reality (VR) based learning modules. The hypothesis is that together with an improvement in learning outcome there would be a decrease in the participants' cerebral oxygenation levels measured from the prefrontal cortex (PFC) region and an increase of participants' serious gaming results. To test this hypothesis, the subjects were recruited and divided into four groups with different combinations of prior virtual reality experience and prior Basic Life Support (BLS) knowledge levels. A VR based serious gaming module for teaching BLS and 16-Channel fNIRS system were used to collect data from the participants. Results of the participants' scores acquired from the serious gaming module were compared with fNIRS measures on the initial and final training sessions. Kruskal Wallis test was run to determine any significant statistical difference between the groups and Mann-Whitney U test was utilized to obtain pairwise comparisons. BLS training scores of the participants acquired from VR based serious game's the learning management system and fNIRS measurements revealed decrease in use of resources from the PFC, but increase in behavioral performance. Importantly, brain-based measures can provide an additional quantitative metric for trainee's expertise development and can assist the medical simulation instructors.

Investigation of optical neuro-monitoring technique for detection of maintenance and emergence states during general anesthesia.

The American Society of Anesthesiologist recommends peripheral physiological monitoring during general anesthesia, which offers no information regarding the effects of anesthetics on the brain. Since no "gold standard" method exists for this evaluation, such a technique is needed to ensure patient comfort, procedure quality and safety. In this study we investigated functional near infrared spectroscopy (fNIRS) as possible monitor of anesthetic effects on the prefrontal cortex. Anesthetic drugs, such as sevoflurane, suppress the cerebral metabolism and alter the cerebral blood flow. We hypothesize that fNIRS derived features carry information on the effects of anesthetics on the prefrontal cortex (PFC) that can be used for the classification of the anesthetized state. In this study, patients were continuously monitored using fNIRS, BIS and standard monitoring during surgical procedures under sevoflurane general anesthesia. Maintenance and emergence states were identified and fNIRS features were identified and compared between states. Linear and non-linear machine learning algorithms were investigated as methods for the classification of maintenance/emergence. The results show that changes in oxygenated (HbO2) and deoxygenated hemoglobin (HHb) concentration and blood volume measured by fNIRS were associated with the transition between maintenance and emergence that occurs as a result of sevoflurane washout. We observed that during maintenance the signal is relatively more stable than during emergence. Maintenance and emergence states were classified with 94.7% accuracy with a non-linear model using the locally derived mean total hemoglobin, standard deviation of HbO2, minimum and range of HbO2 and HHb as features. These features were found to be correlated with the effects of sevoflurane and to carry information that allows real time and automatic classification of the anesthetized state with high accuracy.

Investigation of data-driven optical neuromonitoring approach during general anesthesia with sevoflurane.

Anesthesia monitoring currently needs a reliable method to evaluate the effects of the anesthetics on its primary target, the brain. This study focuses on investigating the clinical usability of a functional near-infrared spectroscopy (fNIRS)-derived machine learning classifier to perform automated and real-time classification of maintenance and emergence states during sevoflurane anesthesia. For 19 surgical procedures, we examine the entire continuum of the maintenance-transition-emergence phases and evaluate the predictive capability of a support vector machine (SVM) classifier during these phases. We demonstrate the robustness of the predictions made by the SVM classifier and compare its performance with that of minimum alveolar concentration (MAC) and bispectral (BIS) index-based predictions. The fNIRS-SVM investigated in this study provides evidence to the usability of the fNIRS signal for anesthesia monitoring. The method presented enables classification of the signal as maintenance or emergence automatically as well as in real-time with high accuracy, sensitivity, and specificity. The features local mean HbTotal, std [Formula: see text], local min Hb and [Formula: see text], and range Hb and [Formula: see text] were found to be robust biomarkers of this binary classification task. Furthermore, fNIRS-SVM was capable of identifying emergence before movement in a larger number of patients than BIS and MAC.

Near-infrared spectroscopy for the evaluation of anesthetic depth.

The standard-of-care guidelines published by the American Society of Anesthesiologists (ASA) recommend monitoring of pulse oximetry, blood pressure, heart rate, and end tidal CO2 during the use of anesthesia and sedation. This information can help to identify adverse events that may occur during procedures. However, these parameters are not specific to the effects of anesthetics or sedatives, and therefore they offer little, to no, real time information regarding the effects of those agents and do not give the clinician the lead-time necessary to prevent patient "awareness." Since no "gold-standard" method is available to continuously, reliably, and effectively monitor the effects of sedatives and anesthetics, such a method is greatly needed. Investigation of the use of functional near-infrared spectroscopy (fNIRS) as a method for anesthesia or sedation monitoring and for the assessment of the effects of various anesthetic drugs on cerebral oxygenation has started to be conducted. The objective of this paper is to provide a thorough review of the currently available published scientific studies regarding the use of fNIRS in the fields of anesthesia and sedation monitoring, comment on their findings, and discuss the future work required for the translation of this technology to the clinical setting.

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.

Molecular concentration of deoxyHb in human prefrontal cortex predicts the emergence and suppression of consciousness.

This is the first study to use fNIRS to explore anaesthetic depth and awakening during surgery with general anaesthesia. A 16 channel continuous wave (CW) functional near-infrared system (fNIRS) was used to monitor PFC activity. These outcomes were compared to BIS measures. The results indicate that deoxyHb concentration in the PFC varies during the suppression and emergence of consciousness. During suppression, deoxyHb levels increase, signalling the deactivation of the PFC, while during emergence, deoxyHb concentration drops, initiating PFC activation and the recovery of consciousness. Furthermore, BIS and deoxyHb concentrations in the PFC display a high negative correlation throughout the different anaesthetic phases. These findings suggest that deoxyHb could be a reliable marker for monitoring anaesthetic depth, and that the PFC intervenes in the suppression and emergence of consciousness.

Functional near-infrared spectroscopy for the measurement of propofol effects in conscious sedation during outpatient elective colonoscopy.

Endoscopic procedures performed in the United States routinely involve the use of conscious sedation as standard of care. The use of sedation reduces patient discomfort and anxiety while improving the technical quality of the procedure, and as a result, over 98% of clinicians have adopted the practice. The tremendous benefits of sedation are offset by heightened costs, increased patient discharge time, and cardiopulmonary complication risks. The inherent liabilities of putting patients under sedation have necessitated a large number of physiological monitoring systems in order to ensure patient comfort and safety. Currently American Society of Anesthesiologist (ASA) guidelines recommend monitoring of pulse oximetry, blood pressure, heart rate, and end-tidal CO2; although important safeguards, these physiological measurements do not allow for the reliable assessment of patient sedation. Proper monitoring of patient state ensures procedure quality and patient safety; however no "gold-standard" is available to determine the depth of sedation which is comparable to the anesthesiologist's professional judgment. Developments in functional near-infrared spectroscopy (fNIRS) over the past two decades have introduced cost-effective, portable, and non-invasive neuroimaging tools which measure cortical hemodynamic activity as a correlate of neural functions. Anesthetic drugs, such as propofol, operate by suppressing cerebral metabolism. fNIRS imaging methods have the ability to detect these drug related effects as well as neuronal activity through the measurement of local cerebral hemodynamic changes. In the present study, 41 patients were continuously monitored using fNIRS while undergoing outpatient elective colonoscopy with propofol sedation. The preliminary results indicated that oxygenated hemoglobin changes in the dorsolateral prefrontal cortex, as assessed by fNIRS were correlated with changes in response to bolus infusions of propofol, whereas other standard physiological measures were not significantly associated.

Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development.

Functional near infrared spectroscopy (fNIRS) is a non-invasive, safe, and portable optical neuroimaging method that can be used to assess brain dynamics during skill acquisition and performance of complex work and everyday tasks. In this paper we describe neuroergonomic studies that illustrate the use of fNIRS in the examination of training-related brain dynamics and human performance assessment. We describe results of studies investigating cognitive workload in air traffic controllers, acquisition of dual verbal-spatial working memory skill, and development of expertise in piloting unmanned vehicles. These studies used conventional fNIRS devices in which the participants were tethered to the device while seated at a workstation. Consistent with the aims of mobile brain imaging (MoBI), we also describe a compact and battery-operated wireless fNIRS system that performs with similar accuracy as other established fNIRS devices. Our results indicate that both wired and wireless fNIRS systems allow for the examination of brain function in naturalistic settings, and thus are suitable for reliable human performance monitoring and training assessment.

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.

Frontal lobe role in simple arithmetic calculations: an fNIR study.

This study aimed to affirm the use of functional near-infrared spectroscopy (fNIR) in examining frontal lobe role during automatic (i.e., requires retrieval from long-term memory) and method-based (i.e., requires calculation) arithmetic processing. Adult university students (math difficulties [MD] and control) performed simple arithmetic calculations while monitored using an fNIR system designed to image regions within the frontal cortices. Addition and subtraction problems presented on a computer screen belonged to one of three categories: triples "under 10" (e.g., 2+3=?, 5-3=?), triples that "break 10" (e.g., 5+8=?, 13-5=?), or triples "including 10" (e.g., 10+7=?, 17-10=?). fNIR recordings indicated significant interactions between type of triple, operation, and group over left frontal lobe, and between type of triple and group over right frontal lobe. Within-group differences among controls were found in the "break 10" triples with higher DeOxyHb level recorded during subtraction processing. Between-group differences were found in the "break 10" and "including 10" triples for subtraction with higher levels of DeOxyHb recorded among controls. Results imply that among adults frontal lobe is still involved during simple mathematical processing and fNIR recordings can differentiate its role in adults of varying mathematical ability.