Anna C. Merzagora

Prefrontal hemodynamic changes produced by anodal direct current stimulation.

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that has been investigated for the treatment of many neurological or neuropsychiatric disorders. Its main effect is to modulate the cortical excitability depending on the polarity of the current applied. However, understanding the mechanisms by which these modulations are induced and persist is still an open question. A possible marker indicating a change in cortical activity is the subsequent variation in regional blood flow and metabolism. These variations can be effectively monitored using functional near-infrared spectroscopy (fNIRS), which offers a noninvasive and portable measure of regional blood oxygenation state in cortical tissue. We studied healthy volunteers at rest and evaluated the changes in cortical oxygenation related to tDCS using fNIRS. Subjects were tested after active stimulation (12 subjects) and sham stimulation (10 subjects). Electrodes were applied at two prefrontal locations; stimulation lasted 10 min and fNIRS data were then collected for 20 min. The anodal stimulation induced a significant increase in oxyhemoglobin (HbO(2)) concentration compared to sham stimulation. Additionally, the effect of active 10-min tDCS was localized in time and lasted up to 8-10 min after the end of the stimulation. The cathodal stimulation manifested instead a negligible effect. The changes induced by tDCS on HbO(2), as captured by fNIRS, agreed with the results of previous studies. Taken together, these results help clarify the mechanisms underlying the regional alterations induced by tDCS and validate the use of fNIRS as a possible noninvasive method to monitor the neuromodulation effect of tDCS.

Wavelet analysis for EEG feature extraction in deception detection.

Deception detection has important clinical and legal implications. However, the reliability of methods for the discrimination between truthful and deceptive responses is still limited. Efforts to improve reliability have examined measures of central nervous system function such as EEG. However, EEG analyses based on either time- or frequency-domain parameters have had mixed results. Because EEG is a nonstationary signal, the use of joint time-frequency features may yield more reliable results for detecting deception. The goal of this study was to investigate the feasibility of deception detection based on EEG features extracted through wavelet transformation. EEG was recorded from 4 electrode sites (F3, F4, F7, F8) during a modified version of the Guilty Knowledge Test (GKT) in 5 subjects. Wavelet analysis revealed significant differences between deceptive and truthful responses. These differences were detected in features whose frequency range roughly corresponds to the EEG beta rhythm and within a time window which coincides with the P300 component. These preliminary results indicate that joint time-frequency EEG features extracted through wavelet analysis may provide a more reliable method for detecting deception than standard ERPs

THE EVOLUTION OF FIELD DEPLOYABLE fNIR SPECTROSCOPY FROM BENCH TO CLINICAL SETTINGS

In the late 1980s and early 1990s, Dr. Britton Chance and his colleagues, using picosecond-long laser pulses, spearheaded the development of time-resolved spectroscopy techniques in an effort to obtain quantitative information about the optical characteristics of the tissue. These efforts by Chance and colleagues expedited the translation of near-infrared spectroscopy (NIRS)-based techniques into a neuroimaging modality for various cognitive studies. Beginning in the early 2000s, Dr. Britton Chance guided and steered the collaboration with the Optical Brain Imaging team at Drexel University toward the development and application of a field deployable continuous wave functional near-infrared spectroscopy (fNIR) system as a means to monitor cognitive functions, particularly during attention and working memory tasks as well as for complex tasks such as war games and air traffic control scenarios performed by healthy volunteers under operational conditions. Further, these collaborative efforts led to various clinical applications, including traumatic brain injury, depth of anesthesia monitoring, pediatric pain assessment, and brain–computer interface in neurology. In this paper, we introduce how these collaborative studies have made fNIR an excellent candidate for specified clinical and research applications, including repeated cortical neuroimaging, bedside or home monitoring, the elicitation of a positive effect, and protocols requiring ecological validity. This paper represents a token of our gratitude to Dr. Britton Chance for his influence and leadership. Through this manuscript we show our appreciation by contributing to his commemoration and through our work we will strive to advance the field of optical brain imaging and promote his legacy.

FUNCTIONAL NEAR-INFRARED SPECTROSCOPY–BASED ASSESSMENT OF ATTENTION IMPAIRMENTS AFTER TRAUMATIC BRAIN INJURY

A frequent consequence of traumatic brain injury (TBI) is cognitive impairment, which results in significant disruption of an individuals everyday living. To date, most clinical rehabilitation interventions still rely on behavioral observation, with little or no quantitative information about physiological changes produced at the brain level. Functional brain imaging has been extensively used in the study of cognitive impairments following TBI. However, its applications to rehabilitation have been limited. This is due in part to the expensive or invasive nature of these modalities. The objective of this study is to apply functional near-infrared spectroscopy (fNIR) to the assessment of attention impairments following TBI. fNIR provides a localized measure of prefrontal hemodynamic activation, which is susceptible to TBI, and it does so in a noninvasive, affordable and wearable way, thus partially overcoming the limitations of other modalities. Participants included 5 TBI subjects and 11 healthy controls....

Multimodal analysis of a sustained attention protocol: continuous performance test assessed with near infrared spectroscopy and EEG.

The aim of this work is to describe, using functional imaging techniques, the spatial and temporal distribution of neural activations ensuing from execution of cognitive functions and to find correlation in data coming from analysis modalities related to different physical properties. A 10-mm continuous performance test (CPT) was administered to a group of healthy subjects as measure of sustained attention. Images of electroencephalography (EEG) and of near infrared spectroscopy (NIRS) were recorded during the task. cerebral activations measure is obtained from the recording of quantities linked with electrical neural activity for the EEG and with change in blood oxygenation for the NIRS system. Good agreement was found between the two modalities, both showing higher activation in the middle upper frontal region and similar temporal trend. A further understanding of the superior central nervous system behavior can be achieved from combined use of both imaging modalities

Single trial somatosensory evoked potential extraction with ARX filtering for a combined spinal cord intraoperative neuromonitoring technique

BackgroundWhen spinal cord functional integrity is at risk during surgery, intraoperative neuromonitoring is recommended. Tibial Single Trial Somatosensory Evoked Potentials (SEPs) and H-reflex are here used in a combined neuromonitoring method: both signals monitor the spinal cord status, though involving different nervous pathways. However, SEPs express a trial-to-trial variability that is difficult to track because of the intrinsic low signal-to-noise ratio. For this reason single trial techniques are needed to extract SEPs from the background EEG.MethodsThe analysis is performed off line on data recorded in eight scoliosis surgery sessions during which the spinal cord was simultaneously monitored through classical SEPs and H-reflex responses elicited by the same tibial nerve electrical stimulation. The single trial extraction of SEPs from the background EEG is here performed through AutoRegressive filter with eXogenous input (ARX). The electroencephalographic recording can be modeled as the sum of the background EEG, which can be described as an autoregressive process not related to the stimulus, and the evoked potential (EP), which can be viewed as a filtered version of a reference signal related to the stimulus. The choice of the filter optimal orders is based on the Akaike Information Criterion (AIC). The reference signal used as exogenous input in the ARX model is a weighted average of the previous SEPs trials with exponential forgetting behavior.ResultsThe moving average exponentially weighted, used as reference signal for the ARX model, shows a better sensibility than the standard moving average in tracking SEPs fast inter-trial changes. The ability to promptly detect changes allows highlighting relations between waveform changes and surgical maneuvers. It also allows a comparative study with H-reflex trends: in particular, the two signals show different fall and recovery dynamics following stressful conditions for the spinal cord.ConclusionThe ARX filter showed good performances in single trial SEP extraction, enhancing the available information concerning the current spinal cord status. Moreover, the comparison between SEPs and H-reflex showed that the two signals are affected by the same surgical maneuvers, even if they monitor the spinal cord through anatomically different pathways.

Verbal working memory impairments following traumatic brain injury: an fNIRS investigation

The construct of working memory and its reliance on dorsolateral prefrontal cortex (DLPFC) have been the focus of many studies in healthy subjects and in clinical populations. However, transfer of knowledge gained from cognitive science studies to clinical applications can be a challenging goal. This scarce cross-dissemination may be partially due to the use of ‘tools’ that are limited in their ability to generate meaningful information about impairments in clinical groups. To this end, this paper investigates the use of functional near-infrared spectroscopy (fNIRS), which offers unique opportunities for recording neuroactivation. Specifically, we examine measures of the DLPFC hemodynamic response during a working memory task in adults with traumatic brain injury (TBI) and healthy controls. Analysis of hemodynamic measures showed significant differences between the two groups, even without differences in behavioral performance. Additional subtle disparities were linked to levels of performance in TBI and healthy subjects. fNIRS hemodynamic measures may therefore provide novel information to existing theories and knowledge of the working memory construct. Future studies may further define these subtle differences captured by fNIRS to help identify which components affect inter-individual variations in performance and could play a contributing role in the choice and planning of neurorehabilitation interventions targeting working memory.

Applications of functional near infrared imaging: casestudy on UAV ground controller

Functional Near-Infrared (fNIR) spectroscopy is an emerging optical brain imaging technology that enables assessment of brain activity through the intact skull in human subjects. fNIR systems developed during the last decade allow for a rapid, non-invasive method of measuring the brain activity of a subject while conducting tasks in realistic environments. This paper introduces underlying principles and various fNIR designs currently applied to real-time settings, such as monitoring Unmanned Aerial Vehicle (UAV) operators expertise development and cognitive workload during simulated missions.

Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach

Although neuroimaging has greatly expanded our knowledge about the brain-behavior relation, combining multiple neuroimaging modalities with complementing strengths can overcome some limitations encountered when using a single modality. Valuable candidates for a multimodal approach are functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). fNIRS is an imaging technology that localizes hemodynamic changes within the cortex. However, hemodynamic activation is an intrinsically slow process. On the other hand, EEG has excellent time resolution by directly measuring the manifestation of the brain electrical activity at the scalp. Based on their complementary strengths, the integration of fNIRS and EEG may provide higher spatiotemporal resolution than either method alone. In this effort, we integrate fNIRS and EEG to evaluate the behavioral performance of six healthy adults in a working memory task. To this end, features extracted from fNIRS and EEG were used separately, as well as in combination, and their performances were compared against each other.

Non-invasive neuroimaging: Generalized Linear Models for interpreting functional Near Infrared Spectroscopy signals

Cognitive activity is related to important changes in the local blood flow level and in the oxygenation of the blood. These two effects lead to a modification of the optical properties of the cerebral cortex. With the aid of the functional near infrared spectroscopy (fNIRS) technique it is possible, through optical measures, to achieve information about the hemodynamic features of the brain activation. The aim of this study was to find a method to identify and to map the cerebral areas activated during a sustained attention task (Conners continuous performance test - CPT) in a group of healthy subjects. This information will be of fundamental interest for a following study on a group of patients that will be administered the same examination. We propose a new analysis method based on the theory of generalized linear model (GLM) in order to obtain intuitive cerebral activation maps during the performing of cognitive tasks