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Neural interfacing non-invasive brain stimulation with NIRS-EEG joint imaging for closed-loop control of neuroenergetics in ischemic stroke

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Abstract

Stroke can be defined as a sudden onset of neurological deficits caused by a focal injury to the central nervous system from a vascular cause. In ischemic stroke (~87% of all strokes) and transient ischemic attack (TIA), the blood vessel carrying blood to the brain is blocked causing deficit in the glucose supply – the main energy source. Here, neurovascular coupling (NVC) mechanism links neural activity with the corresponding blood flow that supplies glucose and oxygen for neuronal energy. Brain accounts for about 25% of total glucose consumption while being 2% of the total body weight. Therefore, a deficit in glucose supply can quickly change brain's energy supply chain that can be transient (in TIA) or longer lasting (in stroke, vascular dementia). Here, implications of the failure of brain's energy supply chain can be dysfunctional brain networks in cerebrovascular diseases. Using near-infrared spectroscopy (NIRS) in conjunction with electroencephalography (EEG), a non-invasive, real-time and point of care method to monitor the neuroenergetic status of the cortical gray matter is proposed. Furthermore, we propose that NIRS-EEG joint-imaging can be used to dose non-invasive brain stimulation (NIBS) – transcranial direct current stimulation (tDCS) and photobiomodulation – which may be able to provide therapeutic options for patients with energetic insufficiency by modulating the cortical neural activity and hemodynamics.
AbstractStroke can be defined as a sudden onset of
neurological deficits caused by a focal injury to the central
nervous system from a vascular cause. In ischemic stroke (~87%
of all strokes) and transient ischemic attack (TIA), the blood
vessel carrying blood to the brain is blocked causing deficit in
the glucose supply the main energy source. Here,
neurovascular coupling (NVC) mechanism links neural activity
with the corresponding blood flow that supplies glucose and
oxygen for neuronal energy. Brain accounts for about 25% of
total glucose consumption while being 2% of the total body
weight. Therefore, a deficit in glucose supply can quickly
change brain’s energy supply chain that can be transient (in
TIA) or longer lasting (in stroke, vascular dementia). Here,
implications of the failure of brain’s energy supply chain can be
dysfunctional brain networks in cerebrovascular diseases. Using
near-infrared spectroscopy (NIRS) in conjunction with
electroencephalography (EEG), a non-invasive, real-time and
point of care method to monitor the neuroenergetic status of the
cortical gray matter is proposed. Furthermore, we propose that
NIRS-EEG joint-imaging can be used to dose non-invasive
brain stimulation (NIBS) transcranial direct current
stimulation (tDCS) and photobiomodulation – which may be
able to provide therapeutic options for patients with energetic
insufficiency by modulating the cortical neural activity and
hemodynamics.
I. INTRODUCTION
Ischemic stroke is caused due to obstruction of blood supply
to brain tissue resulting in corresponding neuronal necrosis
and loss of neurologic function. It constitutes an estimated
87 percent of all stroke cases [1]. Transient Ischemic Attack
(TIA) produces a transient episode of neurological
dysfunction similar to stroke due to transient obstruction or
reduced blood flow. However, those symptoms go away
when the blood flow is restored [2]. Nevertheless, 10%-15%
of TIA patients develop a stroke within 3 months [2].
Research was conducted within the context of the regional NUMEV
funding, Franco-German PHC-PROCOPE funding, and Franco-Indian
INRIA-DST funding.
A. von Lühmann is with the Machine Learning Department, Technische
Universität Berlin, Germany.
J. Addesa is with the Department of Biomedical Engineering, University
at Buffalo - SUNY, USA.
S. Chandra is with the Indian Institute of Technology Madras, Chennai,
India.
A. Das is with the AMRI Institute of Neurosciences, Kolkata, India.
M. Hayashibe is with the INRIA and Université de Montpellier,
Montpellier, France.
A. Dutta is with the Department of Biomedical Engineering, University
at Buffalo-SUNY, USA. (e-mail: adutta@ieee.org).
Furthermore, cognitive impairment and dementia can
develop due to vascular dysfunction [3], i.e., stroke/TIA and
dementia can be inter-related. Here, any deficits in brain’s
energy supply chain can be investigated under
neuroenergetics theory, i.e., energy barriers in the multistable
attractor dynamics of brain networks [4] resulting in acute as
well as chronic dysfunctional brain networks in
cerebrovascular diseases. Positron Emission Tomography
(PET) provides quantification of metabolic failure since it
allows estimation of cerebral blood flow (CBF), the regional
metabolic rate for oxygen (CMRO2), and the regional
oxygen extraction fraction (OEF). For the cortical gray
matter, broadband NIRS can also be used for the estimation
of CBF, CMRO2, and OEF [5], oxidative metabolism [6]),
and NVC in conjunction with EEG [7] however near-
infrared spectroscopy (NIRS) [8] [9] and
electroencephalography (EEG) [10] [11] is limited by ‘depth
penetration’ [12]. In this paper, we propose non-invasive
brain stimulation (NIBS) to ameliorate the energy demand-
supply ‘mismatch’ which is limited to the cortical gray
matter having ‘depth penetration’ comparable to NIRS-EEG
[13]. Therefore, a portable multi-modal brain computer
interface (BCI) involving NIRS-EEG is proposed to monitor
the neuroenergetic status of the cortical gray matter in
cerebrovascular diseases to dose NIBS to improve
cerebrovascular function [14].
Transcranial direct current stimulation (tDCS) is presented
as the NIBS technique that involves application of low
intensity direct current at the scalp for the modulation of
cortical excitability in humans [15] [16]. Anodal tDCS can
increase regional cerebral blood flow, while cathodal tDCS
may decrease it from pre-stimulus levels subsequent to
stimulation application [17]. Furthermore, tDCS affects the
downstream metabolic systems regulated by the brain [18]
where widespread effects of tDCS on human NVC,
vasomotor reactivity, and cerebral autoregulation has been
found [19][20][21]. Another NIBS technique,
photobiomodulation can improve the energy supply by
improving mitochondrial respiration [22] and prevent
mitochondrial breakdown [23]. This leads to a closed-loop
BCI where the cortical ischemic brain tissue at risk due to
energy-starved conditions can be targeted with NIBS (e.g.,
tDCS, photobiomodulation) under NIRS-EEG joint imaging
[13]. In principal accordance, we propose portable NIRS-
EEG joint imaging [24] of the neuroenergetic status of the
cortical gray matter under NIBS intervention that can guide
Neural interfacing non-invasive brain stimulation with NIRS-EEG
joint imaging for closed-loop control of neuroenergetics in ischemic
stroke
Alexander von Lühmann, Jessica Addesa, Sourav Chandra, Abhijit Das, Mitsuhiro Hayashibe-IEEE
Member, and Anirban Dutta, IEEE Member
individual dosing of tDCS (vis-à-vis its nonlinear dose
response [25]) and photobiomodulation [26] (vis-à-vis its
biphasic dose response [22]) in cerebrovascular diseases.
In our prior work, nineteen patients with acute ischemic
stroke (<1 month) localized to a single hemisphere (6
females; 42 to 71 years) were assessed for changes in
regional oxy-hemoglobin concentration (HbO2) in response
to anodal tDCS using a custom-made Continuous Wave-
NIRS + tDCS device [7]. The study was approved by the
institutional review board (IRB) of the Institute of
Neuroscience Kolkata, India and was conducted following
the declaration of Helsinki. Bipolar tDCS was conducted
according to the international 10–20 system with F3 (left
hemisphere) or F4 (right hemisphere) for cathodal and Cz
(interhemispheric on the vertex) for anodal stimulation
where F3/F4 overlies the watershed areas between the
anterior and of the middle cerebral arteries. These sites were
selected based on computational modeling (using
StimViewer, Neuroelectrics, Spain)[27] in order to target
primarily the outer convex brain territory (superficial
divisions). The hemispheres affected by acute stroke showed
significantly less variability in regional oxy-hemoglobin
concentrations than healthy hemispheres in response to
anodal tDCS (-0.67+/-0.28 vs. 3.57+/-0.86; p<0.01).
II. METHODS
A. NIRS-EEG joint imaging of noninvasive brain
stimulation-evoked response
In a first approach to closed-loop BCI, we designed and
evaluated a wireless modular and miniaturized instrument for
functional NIRS (fNIRS) acquisition including a new spring-
loaded optode concept for robust attachment to the head and
published this openNIRS technology for open access [28].
We have now integrated and improved the core parts of this
openNIRS technology into a new architecture for high
precision hybrid acquisition of multiple electrical and optical
biosignals, as needed in the application domain described
above: the hybrid Mobile, Modular, Multimodal Biosignal
Acquisition (M3BA) architecture ([24], see Figure 1). The
M3BA architecture offers a highly miniaturized
customizable wireless platform for simultaneous high
precision acquisition of electrophysiological (EEG, ECG)
and optical (fNIRS) signals. It provides an EEG input
referred noise (at 500 SPS) as low as 1.39 µV, a NIRS noise
equivalent power of NEP750nm = 5:92pWpp, NEP850nm =
4.77pWpp, full input linearity, lock-in amplification, driven
right leg circuitry, modularity, Bluetooth and low power
consumption. Each module provides up to 6
electrophysiological and 6 optical measurement channels and
a 3D accelerometer. The architecture allows flexible
biopotential reference setups (e.g., measuring EEG and ECG
with different references at once) and can be integrated in a
Wireless Body Area/Sensor Network (WBAN/WBSN).
Extensive performance characterization and in-vivo
experiments concluded the evaluation; the M3BA
architecture now facilitates custom designs for measuring
NVC, vasomotor reactivity, and cerebral autoregulation
under NIBS. The M3BA architecture is being tailored to a
head-gear for wearable multimodal non-invasive brain
sensor-stimulation in a BCI setup [29]. Here, broadband
NIRS-EEG can identify neurovascular and neurometabolic
dysfunction of the cortical gray matter related to
cerebrovascular diseases [30].
B. Autoregressive (ARX) model of the neurovascular
coupling
This study was conducted on 5 ischemic stroke survivors
in their chronic phase (1 female; age 68 to 76 years; ictus > 6
months; ischemic strokes again restricted to a single
hemisphere) [31]. PISTIM (Neuroelectrics, Spain) electrodes
were placed over F3 and F4 according the international 10-
20 EEG system and SPONSTIM-25 (Neuroelectrics, Spain)
electrodes were placed over Cz. F3 (F4 when monitoring the
right hemisphere) anodal and Cz cathodal tDCS at a current
density of 0.526A/m2 was turned ON for 30sec with 10sec
ramp-up and ramp-down, which was repeated 15 times in
random order with 30sec OFF periods in between for each
hemisphere. Eyes-open block-averaged resting-state NIRS
oximeter (INVOS Cerebral Oximeter Model 4100, USA)
measurements were conducted just above each eyebrow and
below the F3/F4 sites using SomaSensor (SAFB-SM,
INVOS, USA). In addition, eyes-open resting-state EEG
(StarStim, Neuroelectrics, Spain) was recorded at 500Hz
from the nearby electrodes F1, FC3, F5, F2, FC4, F6
(international 10-20 system) with CMS/DRL electrodes
placed in the left mastoid. Jindal et al. [31] further showed a
post-stimulation decrease from baseline of the log-
transformed mean-power of EEG within 0.5 Hz - 11.25 Hz
that corresponded with a post-tDCS increase in the
Figure 1. Hybrid M3BA module for joint EEG/EMG/ECG and NIRS
imaging (adapted from (Lühmann et al., 2016))
corticospinal excitability from baseline. Jindal et al. [31]
presented the signal processing for eyes-open resting state
EEG (StarStim, Neuroelectrics, Spain) which was recorded
at 500Hz from F3, F4, C3, Cz, C4, P3, P4 (international 10-
20 system) for roughly 3 mins with CMS/DRL electrodes
placed on the left mastoid. Specifically, pre-processing was
performed using EEGLAB functions [32] where artefactual
epochs ("non-stereotyped" or "paroxysmal" noise such as
those induced by generalized head and electrode movements,
tDCS voltage ramping epochs, high amplitude random
fluctuations in broadband
EEG activity near tDCS electrodes) were removed following
subsequent visual inspection of the data. Then, the percent
change in log-transformed mean-power of EEG within 0.5
Hz - 11.25 Hz frequency band was analyzed for both the
lesional and contralesional hemispheres - F3, C3, P3 were
averaged for left hemisphere and F4, C4, P4 were averaged
for the right hemisphere. This average power spectrum was
analyzed for 25 successive 4 sec artefact-free epochs (i.e.,
~100 sec immediately before and ~100 sec immediately after
tDCS) using Welch's averaged, modified periodogram
spectral estimation method (MATLAB function
“spectrum.welch”)[33].
Sood and colleagues [34] recently presented an online
approach to autoregressive (ARX) model to continuously
evaluate the degree of coupling between EEG band (0.5-
11.25 Hz) power and NIRS HbO2 dynamics in the slow
oscillation regime (<0.1 Hz) [35] during anodal tDCS in
healthy – see Figure 2. Here, EEG band (0.5-11.25 Hz)
power was used as the input signal and NIRS HbO2
dynamics was used as an output signal under the hypothesis
that tDCS-modulated vasodilation can affect the oscillations
in the slow oscillation regime (<0.1 Hz) [36]. Slow
oscillation regime (<0.1 Hz) is relevant also in spontaneous
brain activation [35]. In this study on 5 stroke subjects,
parameters of an ARX model were estimated using the
System Identification Toolbox in Matlab (The Mathworks
Inc., USA) to find the relation between anodal tDCS induced
cortical neural activity leading to changes in the EEG power
spectrum and oxy-hemoglobin rSO2 signals in the low
frequency (<0.1Hz) regime. Poles, which are associated with
the output side, have a direct influence on the dynamic
properties of the system.
III. RESULTS
Illustrative example of a healthy subject is shown in
Figure 2 where poles (a1, a2, a3, a4) of the transfer function
did not show significant transients during anodal tDCS
(Table 1 in [34] provides numerical values). However, the
percent change in the poles (a1, a2, a3, a4) of the transfer
function (roots of the denominator of the transfer function)
were found different for the contralesional and ipsilesional
hemispheres of the same subject in the stroke survivors as
shown in Table 1.
IV. DISCUSSION
Difference in ARX model parameters to evaluate the
degree of coupling between EEG band (0.5-11.25 Hz) power
and oxy-hemoglobin rSO2 signals in the slow oscillation
regime (<0.1 Hz) neuronal represents a laterality between the
contralesional and ipsilesional hemispheres of the same
stroke survivor, as shown in Table 1. This may be related to
the difference in neurovascular/neurometabolic coupling
status. In our prior work, we noted onset effects (so-called
“initial dip” due to rapid decrease in HbO2 [37]) of anodal
tDCS in four chronic (>6 months) ischemic stroke survivors
Figure 3. Brain State Dependent Electrotherapy using neurovascular
and neurometabolic coupling (NVC) model (adapted from (Dagar et
al., 2016)). NVC model adapted from (Banaji et al., 2010) for our
NIBS intervention under NIRS-EEG joint imaging. The NIBS
modalities are transcranial direct current stimulation (tDCS) and
photobiomodulation that directly affect different parts of the model
according to our hypothesis. The model inputs are in solid ovals while
the outputs are in dashed rectangles. The model inputs are mean
arterial blood pressure (ABP), changes in arterial O2 levels (SaO2),
and changes in arterial CO2 levels (PaCO2) besides functional
activation due to tDCS (estimated from EEG signal). The model
outputs are tissue oxygen saturation (TOS) and ΔoxCCO, along with
oxygen consumption rate (CMRO2) (estimated from broadband NIRS).
Figure 2. Top panel shows an illustrative example (healthy subject)
showing the EEG band (0.5-11.25 Hz) power as the input (in black),
NIRS HbO2 signal in the low frequency (<0.1Hz) regime that was
measured (in blue) during anodal tDCS as well as predicted by ARX
online tracking method (in dotted red). Bottom panel shows the
corresponding transients in the poles (a1, a2, a3, a4) of the ARX
transfer function (roots of the denominator of the transfer function).
(Dutta et al., 2015a) which may be related to the metabolic
demands [38] of excitability enhancing anodal tDCS. For
example, a high value for baseline oxygen extraction fraction
can accentuate the initial dip [39] which may be important
for excitability enhancing anodal tDCS intervention in
energy-starved conditions. In energy-starved conditions,
neurons use lactate [40] as an initial fuel for mitochondrial
respiration [41] until NVC processes take over [40]. In order
to capture this “initial dip” in the HbO2 time-series, Dutta
and colleagues [42] performed Empirical Mode
Decomposition (EMD) of the non-stationary HbO2 NIRS
resting-state time-series into a set of intrinsic mode functions
(IMFs) where the 8th IMF could capture it. We investigated
this onset effect of anodal tDCS on HbO2 NIRS based on the
role of NVC using simultaneous recording of NIRS and EEG
[42]. Here, the percent change in the mean rSO2 for the first
10 sec of anodal tDCS ON periods (i.e., onset effects)
relative to the first 10 sec of OFF periods mostly correlated
with the corresponding percent change in log-transformed
mean-power of EEG within 0.5Hz-11.25Hz frequency band
in five chronic (>6 months) ischemic stroke survivors [31].
Following ‘onset effects’ during anodal tDCS, possibly
related to the metabolic demands [38] and neuronal use of
lactate [40], it is postulated that NVC leads to an increase in
CBF and total hemoglobin concentration, Hbt a good
indicator of variations in regional cerebral blood volume
which can be derived as the sum of HbO2 and HbR
concentrations [42]. Anodal as well as cathodal tDCS has
been shown to increase regional CBF during stimulation
where anodal tDCS showed greater increase than cathodal
tDCS [17]. In this paper, it was shown that the effects of
neuronal excitation (with anodal tDCS) and neuronal
inhibition (with cathodal stimulation) on the hemodynamics
can be captured using NIRS-EEG joint imaging which offers
the possibility to not only study cortical gray matter
neuroenergetics and NVC in the patients with
cerebrovascular diseases, but it also allows individual dosing
of tDCS and photobiomodulation [26] in cerebrovascular
diseases with a BCI, as shown in Figure 3.
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... However, they are unable to establish causal relationships. The ability to interact with brain oscillations in a precisely-timed fashion to enhance or inhibit endogenous processes -using sensory [1], [2], [3], [4], electrical [5] or magnetic [6] stimulation -allows for their functional roles to be determined [7], and potentially for restoration of processes deteriorated by aging or pathology [8]. While there is a great deal of interest in closed-loop stimulation [7], [9], researchers lack flexible, powerful tools that are easily accessible. ...
... In [24], the authors developed a low-cost device limited to acquisition. Other portable devices enable closed-loop stimulation [2], [3], [4], some also based on low-cost hardware [25], but work with simple heuristics and are generally not sufficiently powerful for deep learning applications. Closed-loop stimulation has been used in the context of preventing drowsiness [2], enhancing attention and engagement [4], preventing strokes [3] and studying memory consolidation [1], [25], [26], [27]. ...
... Other portable devices enable closed-loop stimulation [2], [3], [4], some also based on low-cost hardware [25], but work with simple heuristics and are generally not sufficiently powerful for deep learning applications. Closed-loop stimulation has been used in the context of preventing drowsiness [2], enhancing attention and engagement [4], preventing strokes [3] and studying memory consolidation [1], [25], [26], [27]. Depending on the application, real-time constraints can vary from hundreds of ms [28] to a few seconds [4]. ...
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Electroencephalography (EEG) is a method of measuring the brain's electrical activity, using non-invasive scalp electrodes. In this article, we propose the Portiloop, a deep learning-based portable and low-cost device enabling the neuroscience community to capture EEG, process it in real time, detect patterns of interest, and respond with precisely-timed stimulation. The core of the Portiloop is a System on Chip composed of an Analog to Digital Converter (ADC) and a Field-Programmable Gate Array (FPGA). After being converted to digital by the ADC, the EEG signal is processed in the FPGA. The FPGA contains an ad-hoc Artificial Neural Network (ANN) with convolutional and recurrent units, directly implemented in hardware. The output of the ANN is then used to trigger the user-defined feedback. We use the Portiloop to develop a real-time sleep spindle stimulating application, as a case study. Sleep spindles are a specific type of transient oscillation ($\sim$2.5 s, 12-16 Hz) that are observed in EEG recordings, and are related to memory consolidation during sleep. We tested the Portiloop's capacity to detect and stimulate sleep spindles in real time using an existing database of EEG sleep recordings. With 71% for both precision and recall as compared with expert labels, the system is able to stimulate spindles within $\sim$300 ms of their onset, enabling experimental manipulation of early the entire spindle. The Portiloop can be extended to detect and stimulate other neural events in EEG. It is fully available to the research community as an open science project.
... In addition, the EEG and NIRS measuring devices are small and movable and the measuring process is noninvasive and nonradioactive. To some extent, they can replace the traditional biochemical test or imaging diagnosis method [26][27][28]. Fig. 1 depicts the EEG-NIRS device wearing method for acquisition equipment. Fig. 2 shows the division of NIRS channels and functional areas. ...
... In the left and right hemispheres, channels 14,15,16,29,30,31,32,46,47, and 48 were identified as gray areas. The yellow area of frontopolar prefrontal cortex was identified as channels 7,8,12,13,21,22,23,24,25,26,27,28,36,37,41, and 42. ...
Article
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There are two major research issues with regard to detoxification; one is pathological testing of drug users and the other is rehabilitation methods and techniques. Over the years, domestic and foreign researchers have done a lot of work on pathological changes in the brain and rehabilitation techniques for drug users. This article discusses the research status of these two aspects. At present, the evaluation of brain function in drug addicts is still dominated by a single electroencephalography (EEG), near-infrared spectroscopy (NIRS), or magnetic resonance imaging scan. The multimodal physiological data acquisition method based on EEG–NIRS technique is relatively advantageous for actual physiological data acquisition. The traditional drug rehabilitation method is based on medication and psychological counseling. In recent years, psychological correction (e.g., emotional ventilation, intelligent physical and mental decompression, virtual reality technique and drug addiction suppression system, sports training, and rehabilitation) and physical therapy (transcranial magnetic stimulation) have gradually spread. These rehabilitations focus on comprehensive treatment from the psychological and physical aspects. In recent years, new intervention ideas such as brain–computer interface technique have been continuously proposed. In this review, we have introduced multimodal brain function detection and rehabilitation intervention, which have theoretical and practical significance in drug rehabilitation research.
... In contrast, the zeros of the model exhibited variations across the subjects Table 3 during HD-tDCS that indicated modulation of the neurovascular coupling [35]. Here, simultaneous monitoring of the hemodynamic response is crucial for dosing tDCS due to its postulated role in neuromodulation action [8], which can lead to inter-and intra-subject variability in neuronal responses [49,123]-need for closed-loop dosing [124]. Furthermore, tDCS can be a promising method to evoke regional CBF [5] to ameliorate hypoperfusion in cerebrovascular diseases, including facilitating cognitive rehabilitation. ...
Article
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Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. Our study presents a grey-box linear model that was developed from a physiologically detailed multi-compartmental neurovascular unit model consisting of the vascular smooth muscle, perivascular space, synaptic space, and astrocyte glial cell. Then, model linearization was performed on the physiologically detailed nonlinear model to find appropriate complexity (Akaike information criterion) to fit functional near-infrared spectroscopy (fNIRS) based measure of blood volume changes, called cerebrovascular reactivity (CVR), to high-definition (HD) tDCS. The grey-box linear model was applied on the fNIRS-based CVR during the first 150 seconds of anodal HD-tDCS in eleven healthy humans. The grey-box linear models for each of the four nested pathways starting from tDCS scalp current density that perturbed synaptic potassium released from active neurons for Pathway 1, astrocytic transmembrane current for Pathway 2, perivascular potassium concentration for Pathway 3, and voltage-gated ion channel current on the smooth muscle cell for Pathway 4 were fitted to the total hemoglobin concentration (tHb) changes from optodes in the vicinity of 4x1 HD-tDCS electrodes as well as on the contralateral sensorimotor cortex. We found that the tDCS perturbation Pathway 3 presented the least mean square error (MSE, median
... The EEG can capture the changes in temporal activity. NIRS quantitatively analyzes the blood oxygen metabolism level of brain tissue via the spectral measurement method [7,8], the combination of the two marks the successful integration of EEG and cerebral blood oxygen metabolism level to positively quantify the degree of drug addiction [9][10][11]. ...
Article
Most studies on drug addiction degree are made based on statistical scales, addicts' account, and subjective judgement of rehabilitation doctors. No objective, quantified evaluation has been made. This paper uses devises the synchronous bimodal signal collection and experimentation paradigm with electroencephalogram (EEG) and forehead high-density near-infrared spectroscopy (NIRS) device. The drug addicts are classified into mild, moderate and severe groups with reference to the suggestions of researchers and medical experts. Data of 45 drug addicts (mild: 15; moderate: 15; and severe: 15) is collected, and then used to design an addiction degree testing algorithm based on decision fusion. The algorithm is used to classify mild, moderate and severe addiction. This paper pioneers to use two types of Convolutional Neural Network (CNN) to abstract the EEG and NIR data of drug addicts, and introduces batch normalization to CNN, thus accelerating training process, reducing parameter sensitivity, and enhancing system robustness. The characteristics output by two CNNs are transformed into dimensions. Two new characteristics are assigned with a weight of 50% each. The data is used for decision fusion. In the networks, 27 subjects are used as training sets, 9 as validation sets, and 9 as testing sets. The 3-class accuracy remains to be 63.15%, preliminarily justifying this method as an effective approach to measure drug addiction degree. And the method is ready to use, objective, and offers results in real time.
... Moreover, the use of transcranial NIR laser (810 nm) in low-level light therapy showed improvement in patients suffering from anxiety and depression [25]. Since increased oxygen consumption occurs during increased neural activity [26], which leads to increased CCO activity, so an assessment and modulation of CCO activity can open a pathway to monitor and modulate neuronal activity [27,28]. Here, redox state-dependent changes in the NIR spectrum is an essential tool for near-infrared spectroscopy of the oxidation state of CCO [2]. ...
Article
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Transcranial near-infrared stimulation (tNIRS) has been proposed as a tool to modulate cortical excitability. However, the underlying mechanisms are not clear where the heating effects on the brain tissue needs investigation due to increased near-infrared (NIR) absorption by water and fat. Moreover, the risk of localized heating of tissues (including the skin) during optical stimulation of the brain tissue is a concern. The challenge in estimating localized tissue heating is due to the light interaction with the tissues’ constituents, which is dependent on the combination ratio of the scattering and absorption properties of the constituent. Here, apart from tissue heating that can modulate the cortical excitability (“photothermal effects”); the other mechanism reported in the literature is the stimulation of the mitochondria in the cells which are active in the adenosine triphosphate (ATP) synthesis. In the mitochondrial respiratory chain, Complex IV, also known as the cytochrome c oxidase (CCO), is the unit four with three copper atoms. The absorption peaks of CCO are in the visible (420–450 nm and 600–700 nm) and the near-infrared (760–980 nm) spectral regions, which have been shown to be promising for low-level light therapy (LLLT), also known as “photobiomodulation”. While much higher CCO absorption peaks in the visible spectrum can be used for the photobiomodulation of the skin, 810 nm has been proposed for the non-invasive brain stimulation (using tNIRS) due to the optical window in the NIR spectral region. In this article, we applied a computational approach to delineate the “photothermal effects” from the “photobiomodulation”, i.e., to estimate the amount of light absorbed individually by each chromophore in the brain tissue (with constant scattering) and the related tissue heating. Photon migration simulations were performed for motor cortex tNIRS based on a prior work that used a 500 mW cm − 2 light source placed on the scalp. We simulated photon migration at 630 nm and 700 nm (red spectral region) and 810 nm (near-infrared spectral region). We found a temperature increase in the scalp below 0.25 °C and a minimal temperature increase in the gray matter less than 0.04 °C at 810 nm. Similar heating was found for 630 nm and 700 nm used for LLLT, so photothermal effects are postulated to be unlikely in the brain tissue.
... The combination of EEG and fNIRS enables new approaches in many domains related to neuroscience and neurotechnology. Among them are advanced diagnostic tools for medicine, e.g., toward the non-invasive real-time monitoring of the neuroenergetic status of cortical gray matter in ischemic strokes [vAC+17] These overall factors make EEG and fNIRS predestined for multimodal and hybrid integration into miniaturized and wearable non-invasive neuroimaging equipment, allowing comparably high usability. Consequently, EEG and fNIRS are the modalities of choice for the work in this thesis. ...
Thesis
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In neuroscience and related fields, progress in instrumentation, computational power, and signal processing methods continuously provide novel and increasingly powerful tools toward the investigation of brain activity in real-time and everyday environments. Research into real-life and application-oriented, non-invasive neurotechnology bears a number of multidisciplinary challenges which need to be addressed. Neurophysiological signals have to be measured subtly and safely while reliability and robustness have to be ensured. To this end, new approaches are explored in this thesis that deal with the simultaneous acquisition and utilization of multiple brain and body signals in mobile scenarios. They aim to reduce acquisition restraints for mobile neuroimaging, and at the same time increase the amount of information that is provided by hybrid acquisition equipment. This enables the exploitation of complementary and shared information in the measured modalities toward the development of methods that enhance robustness in the analysis and classification of brain signals. The first contribution of this work comprises the development of novel architectures and devices for the mobile measurement of brain and body signals. Here, the focus lies on functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) instruments. The primary result is M3BA, an architecture for Mobile, Modular, Multimodal Biosignal Acquisition. While miniaturized beyond previous approaches, M3BA offers hybrid and high-precision measurement of fNIRS, EEG, acceleration and other signals while allowing scalability and easy customization. The second contribution targets the generation of evoked multimodal neuroimaging data under realistic environmental but yet well-controlled movement conditions. Making use of M3BA modules in a lightweight wireless headset, a novel, bespoke n-back-based cognitive workload paradigm was designed and administered in a study with 17 freely moving subjects. Using this unique dataset, the third contribution consists of the development of a multimodal Blind-Source-Separation framework for the analysis of fNIRS signals and its application in BLISSA2RD, for the accelerometer-based rejection of movement induced artifacts. Employing it along with other state-of-the-art methods, we ultimately provide a proof of feasibility toward workload classification under challenging, realistic conditions. In this unique approach, and with strict rejection of artifacts, accuracies greater than 80% based on neurophysiological EEG-fNIRS markers is achieved.
Article
Face touch is an unconscious human habit. Frequent touching of sensitive/mucosal facial zones (eyes, nose, and mouth) increases health risks by passing pathogens into the body and spreading diseases. Furthermore, accurate monitoring of face touch is critical for behavioral intervention. Existing monitoring systems only capture objects approaching the face, rather than detecting actual touches. As such, these systems are prone to false positives upon hand or object movement in proximity to one's face (e.g., picking up a phone). We present FaceSense, an ear-worn system capable of identifying actual touches and differentiating them between sensitive/mucosal areas from other facial areas. Following a multimodal approach, FaceSense integrates low-resolution thermal images and physiological signals. Thermal sensors sense the thermal infrared signal emitted by an approaching hand, while physiological sensors monitor impedance changes caused by skin deformation during a touch. Processed thermal and physiological signals are fed into a deep learning model (TouchNet) to detect touches and identify the facial zone of the touch. We fabricated prototypes using off-the-shelf hardware and conducted experiments with 14 participants while they perform various daily activities (e.g., drinking, talking). Results show a macro-F1-score of 83.4% for touch detection with leave-one-user-out cross-validation and a macro-F1-score of 90.1% for touch zone identification with a personalized model.
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Multimodal measurements combining broadband near-infrared spectroscopy (NIRS) and phosphorus magnetic resonance spectroscopy ((31)P MRS) assessed associations between changes in the oxidation state of cerebral mitochondrial cytochrome-c-oxidase (Δ[oxCCO]) and (31)P metabolite peak-area ratios during and after transient cerebral hypoxia-ischemia (HI) in the newborn piglet.
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Objective: For the further development of the fields of telemedicine, neurotechnology and Brain-Computer Interfaces (BCI), advances in hybrid multimodal signal acquisition and processing technology are invaluable. Currently, there are no commonly available hybrid devices combining bio-electrical and bio-optical neurophysiological measurements (here Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS)). Our objective was the design of such an instrument, and that in a miniaturized, customizable and wireless form. Methods: We present here the design and evaluation of a Mobile, Modular, Multimodal Biosignal Acquisition architecture (M3BA) based on a high-performance analog front-end optimized for bio-potential acquisition, a microcontroller, and our openNIRS technology. Results: The designed M3BA modules are very small configurable high precision and low-noise modules (EEG input referred noise @ 500 SPS 1:39 Vpp, NIRS noise equivalent power NEP750nm = 5:92pWpp, NEP850nm = 4:77pWpp) with full input linearity, Bluetooth, 3D accelerometer and lowpower consumption. They support flexible, user-specified biopotential reference setups, and Wireless Body Area/Sensor Network (WBAN/WBSN) scenarios. Conclusion: Performance characterization and in-vivo experiments confirmed functionality and quality of the designed architecture. Significance: Telemedicine and assistive neurotechnology scenarios will increasingly include wearable multimodal sensors in the future. The M3BA architecture can significantly facilitate future designs for research in these and other fields that rely on customized mobile hybrid biosignal acquisition hardware.
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Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral haemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about -15sec was found after a cumulative 550 sec stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization.
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Transcranial electrical stimulation (tES), including transcranial direct and alternating current stimulation (tDCS, tACS) are non-invasive brain stimulation techniques increasingly used for modulation of central nervous system excitability in humans. Here we address methodological issues required for tES application. This review covers technical aspects of tES, as well as applications like exploration of brain physiology, modelling approaches, tES in cognitive neurosciences, and interventional approaches. It aims to help the reader to appropriately design and conduct studies involving these brain stimulation techniques, understand limitations and avoid shortcomings, which might hamper the scientific rigor and potential applications in the clinical domain.
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Brain-Computer Interfaces (BCIs) and neuroergonomics research have high requirements regarding robustness and mobility. Additionally, fast applicability and customization are desired. Functional Near-Infrared Spectroscopy (fNIRS) is an increasingly established technology with a potential to satisfy these conditions. EEG acquisition technology, currently one of the main modalities used for mobile brain activity assessment, is widely spread and open for access and thus easily customizable. fNIRS technology on the other hand has either to be bought as a predefined commercial solution or developed from scratch using published literature. To help reducing time and effort of future custom designs for research purposes, we present our approach toward an open source multichannel stand-alone fNIRS instrument for mobile NIRS-based neuroimaging, neuroergonomics and BCI/BMI applications. The instrument is low-cost, miniaturized, wireless and modular and openly documented on www.opennirs.org. It provides features such as scalable channel number, configurable regulated light intensities, programmable gain and lock-in amplification. In this paper, the system concept, hardware, software and mechanical implementation of the lightweight stand-alone instrument are presented and the evaluation and verification results of the instrument’s hardware and physiological fNIRS functionality are described. Its capability to measure brain activity is demonstrated by qualitative signal assessments and a quantitative mental arithmetic based BCI study with 12 subjects.
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Stroke instigates regenerative responses that reorganize connectivity patterns among surviving neurons. The new connectivity patterns can be suboptimal for behavioral function. This review summarizes current knowledge on post-stroke motor system reorganization and emerging strategies for shaping it with manipulations of behavior and cortical activity to improve functional outcome. ©2015 Int. Union Physiol. Sci./Am. Physiol. Soc.
Article
Background: Transcranial direct current stimulation (tDCS) has been shown to perturb both cortical neural activity and hemodynamics during (online) and after the stimulation, however mechanisms of these tDCS-induced online and after-effects are not known. Here, online resting-state spontaneous brain activation may be relevant to monitor tDCS neuromodulatory effects that can be measured using electroencephalography (EEG) in conjunction with near-infrared spectroscopy (NIRS). Method: We present a Kalman Filter based online parameter estimation of an autoregressive (ARX) model to track the transient coupling relation between the changes in EEG power spectrum and NIRS signals during anodal tDCS (2mA, 10min) using a 4×1 ring high-definition montage. Results: Our online ARX parameter estimation technique using the cross-correlation between log (base-10) transformed EEG band-power (0.5-11.25Hz) and NIRS oxy-hemoglobin signal in the low frequency (≤0.1Hz) range was shown in 5 healthy subjects to be sensitive to detect transient EEG-NIRS coupling changes in resting-state spontaneous brain activation during anodal tDCS. Conventional sliding window cross-correlation calculations suffer a fundamental problem in computing the phase relationship as the signal in the window is considered time-invariant and the choice of the window length and step size are subjective. Here, Kalman Filter based method allowed online ARX parameter estimation using time-varying signals that could capture transients in the coupling relationship between EEG and NIRS signals. Conclusion: Our new online ARX model based tracking method allows continuous assessment of the transient coupling between the electrophysiological (EEG) and the hemodynamic (NIRS) signals representing resting-state spontaneous brain activation during anodal tDCS.
Article
Objective: To investigate the clinical features of transient ischemic attack (TIA) to diagnose by new definition. Methods: The clinical date of 71 carotid artery TIA patients diagnosed by old diagnosis standard were analyzed. The patients were diagnosed again by the new definition of TIA from the American Heart Association/American Stroke Association Stroke Council, and the clinical date of new diagnosed TIA and cerebral infarction were compared with each other. Results: Depending on the new definition, 49 patients (69.0%) were diagnosed as TIA, while 22 patients (31.0%) were diagnosed as cerebral infarction. There were no significant differences in attack duration of TIA, age, gender, history of hypertension, DM and hyperlipidemia between the two groups (all P > 0.05). The rates of unilateral weaknessand and fibrillation atrial, CT showed subcortex ischemia or white matter rarefaction, ECG abnormal and carotid blood vessel abnormal examined by carotid color doppler ultrasonography in TIA group were significantly lower than those in the cerebral infarction group (P < 0.05-0.01). Conclusions: The new definition of TIA does not emphasize the duration of clinical symptom. The potential for TIA in the patient who with unilateral weakness, head CT, ECG and carotid blood vessel abnormal may offer important clue to the diagnosis of cerebral infarction.