Stress estimation by the prefrontal cortex asymmetry: Study on fNIRS signals

sure the brain hemodynamic activity in applications to evaluate affective disorders and stress. Using two wavelengths of light, it is possible to monitor relative changes in the concentrations of oxyhemoglobin and deoxyhemoglobin. Besides, the spatial asymmetry in the prefrontal cortex activity has been correlated with the brain response to stressful situations. Methods: We measured prefrontal cortex activity with a NIRS multi-distance device during a baseline period, under stressful conditions (e.g., social stress), and after a recovery phase. We calculated a laterality index for the contaminated brain signal and for the brain signal where we removed the influence of extracerebral hemodynamic activity by using a short channel. Results: There was a significant right lateralization during stress when using the contaminated signals, consistent with previous investigations, but this significant difference disappeared using the corrected signals. Indeed, exploration of the susceptibility to contamination of the different channels showed non-homogeneous spatial patterns, which would hint at detection of stress from extracerebral activity from the forehead. Limitations: There was no recovery phase between the social and the arithmetic stressor, a cumulative effect was not considered. Conclusions: Extracerebral hemodynamic activity provided insights into the pertinence of short channel corrections in fNIRS studies dealing with emotions. It is important to consider this issue in clinical applications including modern monitoring systems based on fNIRS technique to assess emotional states in affective disorders

Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic

Functional near-infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task-evoked and spontaneous hemodynamic oscillations of non-cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task-evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency-resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi-channel and multi-distance recordings. We found significant task-related fluctuations for oxy-and deoxy-hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non-cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro-visceral link

Interchangeable Sensor Device for a functional near-infrared spectroscopy system

El objeto de la presente invención es un dispositivo sensor intercambiable no invasivo para un sistema de espectroscopia funcional de infrarrojo cercano (fNIR) destinado a detectar cambios en la concentración de especies de hemoglobinas en una superficie corporal cualquiera.The invention relates to an interchangeable sensor device for a functional near-infrared spectroscopy system (fNIRS) which is a non-invasive device intended to detect changes in the concentration of haemoglobin species on any body surface area.Peer reviewedUniversidad Miguel Hernández, Consejo Superior de Investigaciones Científicas (España)A1 Solicitud de patente con informe sobre el estado de la técnic

Dispositivo sensor intercambiable

Peer reviewedUniversidad Miguel Hernández, Consejo Superior de Investigaciones Científicas (España)U Solicitud de modelo de utilida

Stress estimation by the prefrontal cortex asymmetry: Study on fNIRS signals

[Background]: Functional near-infrared spectroscopy (fNIRS) is a non-invasive technique frequently used to measure the brain hemodynamic activity in applications to evaluate affective disorders and stress. Using two wavelengths of light, it is possible to monitor relative changes in the concentrations of oxyhemoglobin and deoxyhemoglobin. Besides, the spatial asymmetry in the prefrontal cortex activity has been correlated with the brain response to stressful situations.[Methods]: We measured prefrontal cortex activity with a NIRS multi-distance device during a baseline period, under stressful conditions (e.g., social stress), and after a recovery phase. We calculated a laterality index for the contaminated brain signal and for the brain signal where we removed the influence of extracerebral hemodynamic activity by using a short channel.[Results]: There was a significant right lateralization during stress when using the contaminated signals, consistent with previous investigations, but this significant difference disappeared using the corrected signals. Indeed, exploration of the susceptibility to contamination of the different channels showed non-homogeneous spatial patterns, which would hint at detection of stress from extracerebral activity from the forehead.[Limitations]: There was no recovery phase between the social and the arithmetic stressor, a cumulative effect was not considered.[Conclusions]: Extracerebral hemodynamic activity provided insights into the pertinence of short channel corrections in fNIRS studies dealing with emotions. It is important to consider this issue in clinical applications including modern monitoring systems based on fNIRS technique to assess emotional states in affective disorders.Spanish Ministry of Science, Innovation and University, grant number PID2019-107304RB-I00, in which Dr. Carmen Tabernero is principal investigator.Peer reviewe

Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic

Functional near-infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task-evoked and spontaneous hemodynamic oscillations of non-cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task-evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency-resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi-channel and multi-distance recordings. We found significant task-related fluctuations for oxy- and deoxy-hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non-cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro-visceral link.Peer reviewe

Identifying ADHD boys by very-low frequency prefrontal fNIRS fluctuations during a rhythmic mental arithmetic task

Objective. Computer-aided diagnosis of attention-deficit/hyperactivity disorder (ADHD) aims to provide useful adjunctive indicators to support more accurate and cost-effective clinical decisions. Deep- and machine-learning (ML) techniques are increasingly used to identify neuroimaging-based features for objective assessment of ADHD. Despite promising results in diagnostic prediction, substantial barriers still hamper the translation of the research into daily clinic. Few studies have focused on functional near-infrared spectroscopy (fNIRS) data to discriminate ADHD condition at the individual level. This work aims to develop an fNIRS-based methodological approach for effective identification of ADHD boys via technically feasible and explainable methods. Approach. fNIRS signals recorded from superficial and deep tissue layers of the forehead were collected from 15 clinically referred ADHD boys (average age 11.9 years) and 15 non-ADHD controls during the execution of a rhythmic mental arithmetic task. Synchronization measures in the time-frequency plane were computed to find frequency-specific oscillatory patterns maximally representative of the ADHD or control group. Time series distance-based features were fed into four popular ML linear models (support vector machine, logistic regression (LR), discriminant analysis and naïve Bayes) for binary classification. A ‘sequential forward floating selection’ wrapper algorithm was adapted to pick out the most discriminative features. Classifiers performance was evaluated through five-fold and leave-one-out cross-validation (CV) and statistical significance by non-parametric resampling procedures. Main results. LR and linear discriminant analysis achieved accuracy, sensitivity and specificity scores of near 100% (p < .001) for both CV schemes when trained with only three key wrapper-selected features, arising from surface and deep oscillatory components of very low frequency. Significance. We provide preliminary evidence that very-low frequency fNIRS fluctuations induced/modulated by a rhythmic mental task accurately differentiate ADHD boys from non-ADHD controls, outperforming other similar studies. The proposed approach holds promise for finding functional biomarkers reliable and interpretable enough to inform clinical practice