Name: conducting concurrent electroencephalography and functional near-infrared spectroscopy recordings with a flanker task
Uploaded: 2020-05-24T12:30:00.000+00:00
Duration: 13 min 18 s
Description: Watch this Scientific Journal Video about Conducting Concurrent Electroencephalography and Functional Near-Infrared Spectroscopy Recordings with a Flanker Task at JoVE.com

This work was performed in part at the high performance computing cluster (HPCC), which is supported by information and communication technology office (ICTO) of the University of Macau. This study was supported by MYRG2019-00082-FHS and MYRG 2018-00081-FHS grants from the University of Macau in Macau, and also funded by The Science and Technology Development Fund, Macau SAR (FDCT 0011/2018/A1 and FDCT 025/2015/A1).

Prior to the experimental tests, all participants signed informed consent documents. The protocol for the present study was approved by the Ethics Committee of the University of Macau.
1. Hardware and software setting for concurrent EEG and fNIRS recordings
<ol>
	<li>Construct a head cap for concurrent EEG-fNIRS recordings.
	<ol>
		<li>Select the appropriate cap size according to the head circumference of participants. In this study, use a medium-size cap since it is suitable for most adolescent and adult participants.</li>
		<li>Design the layout of fNIRS optodes along with the EEG cap in the prefrontal cortex (Figure 1).
		<ol>
			<li>Place EEG electrodes in the middle section of the fNIRS optodes to ensure the measurement of the same brain region by the two techniques19,30. However, due to the low spatial resolution of both EEG and fNIRS neuroimaging methods, place the electrodes in the corresponding brain area covered by fNIRS optodes rather than the exact locations of fNIRS channels.</li>
			<li>Make 22 holes inside the EEG cap to hold the fNIRS optodes in line with the specific layout in the prefrontal cortex. Identify and mark the locations of fNIRS optodes according to the designed layout of the head cap and then punch holes inside the cap to place and fix the optodes.</li>
			<li>Place 21 or 71 EEG electrodes along the surface of the EEG cap (see&#160;Table of Materials) according to the 10-20 International System and mount the grids for the optodes.</li>
		</ol>
		</li>
		<li>Set the distance between each source-detector pair as 3 cm and then fix the optodes, in which the blue optodes denote the light detectors while the red ones represent the laser sources.</li>
	</ol>
	</li>
	<li>Set the EEG and fNIRS ports in the software.</li>
	<li>Use the time triggers generated through the parallel port and serial port to ensure the synchronization of two different signals.
	<ol>
		<li>Set the parallel port (e.g., H378 in this study) for the EEG system (see&#160;Table of Materials).</li>
		<li>Set the serial port (e.g., 6 9600 in this study) for the fNIRS system (see&#160;Table of Materials). 
		NOTE: The port type and number should be modified regarding various EEG and fNIRS setups. Please contact the manufacturers for more information.</li>
	</ol>
	</li>
</ol>
2. Experimental preparation
<ol>
	<li>Warm up the fNIRS system with lasers switched on for 30 min.</li>
	<li>Set all necessary operation parameters for the fNIRS measurement system.</li>
	<li>Show the fused experimental setup including the EEG and fNIRS measurement systems to participants.</li>
	<li>Measure and mark the Cz point according to the 10-20 International System. Identify the electrode position of Cz at half of the distance between the inion and nasion and half of the distance between the left and right inter-aural indentations.</li>
	<li>Place the front part of the cap along the participant&#8217;s forehead first and then pull down the back section of the cap towards the neck.</li>
	<li>Validate the positions.
	<ol>
		<li>Measure the distance between the Cz and inion and nasion again with a soft ruler, and double-check whether it is located at the midpoint. Likewise, measure the distance between the Cz and left and right inter-aural, and double-check whether the Cz is located at the midpoint.</li>
	</ol>
	</li>
	<li>Prepare for the EEG recordings. 
	NOTE: It is highly recommended that the EEG electrodes be set up first and then the fNIRS optodes. If EEG conductive gel covers the holes for the placement of fNIRS optodes, it should be cleaned to prevent the contamination of optodes.
	<ol>
		<li>Fill conductive gel by inserting a blunt needle through the holes of the EEG electrode grid.</li>
		<li>Place all electrodes into the EEG electrode grid according to the labels.</li>
		<li>Open the EEG software and inspect the signal quality of EEG electrodes.</li>
		<li>Readjust the electrode by refilling conductive gel if the signal quality is not good enough to meet the requirements (40 mV).</li>
		<li>Readjust the electrode by refilling conductive gel if the impedance could not meet the requirements.</li>
	</ol>
	</li>
	<li>Prepare for the fNIRS recordings. 
	Caution: Do not expose participants&#8217; eyes to the laser beam of fNIRS sources directly.
	<ol>
		<li>Place the optical fibers along the holder arms attached to the fNIRS measurement system as well as the holder. Ensure that the fibers are neat and tidy.</li>
		<li>Insert the optical sources and detectors into the holes according to the layout.</li>
		<li>Test the signal quality. If a channel does not have a high-level signal-to-noise ratio (i.e., if the channel is marked in yellow), gently inspect the participant&#8217;s hair surrounding the optical probes to ensure that nothing exists between the optical probe and scalp.</li>
		<li>If step 2.8.3 cannot improve the signal quality, turn up the signal intensity. If there is too much signal (i.e., if the channel is marked in red), turn down the signal intensity.</li>
	</ol>
	</li>
</ol>
3. Run the experiment
<ol>
	<li>Start the experiment when the signals are stable with excellent signal-to-noise ratio and participants are familiar with the experiment instructions. Use the classic Flanker paradigm for the experimental test29,31.</li>
	<li>After the experiment, save and export the data from both EEG and fNIRS.</li>
	<li>Remove EEG electrodes and fNIRS optical probes carefully.</li>
</ol>
4. Measurement of three-dimensional (3D) MNI coordinates of fNIRS optodes with 3D digitizer
<ol>
	<li>Let participants sit in a chair and wear the glasses with the sensor.</li>
	<li>Open the digitizer software on the computer. Ensure that the 3D digitizer system is in connection with the computer through an appropriate COM port.</li>
	<li>Load the layout of the optodes setting file.</li>
	<li>Move the 3D digitizer stylus across the key positions (Nz, Iz, left ear, right ear, Cz) along with the screen and press the button on the stylus.</li>
	<li>Localize the optical sources and detectors</li>
	<li>Export the 3D coordinates files.</li>
</ol>
5. Data analysis
<ol>
	<li>fNIRS data analysis
	<ol>
		<li>Process the 3D MNI coordinates data by using the registration option in NIRS-SPM with MATLAB 2019. Select: stand-alone spatial registration | With 3D Digitize. Choose the previously saved others and origin text files and then select Registration.</li>
		<li>Pre-process fNIRS signals with Homer2 software32.
		<ol>
			<li>Convert the raw data to optical density changes for different wavelengths and further convert to the concentration changes of HbO at different time points using a modified Beer-Lambert Law. Generally, the typically differential path length factor (DPF) value affected by the age, gender, and wavelength, and the distance between the source and decetor33,34 is 6, which is similar to the average&#160;DPF from previous studies34,35.</li>
			<li>Use the spline motion artifacts detection algorithm from the Homer2 fNIRS processing package for motion correction. Please select the appropriate methods of motion correction based on literature36.</li>
			<li>Process the raw hemoglobin continuous data by a low-pass filter of 0.2 Hz and subsequently a high-pass filter of 0.015 Hz.</li>
			<li>Normalize hemodynamic signal amplitude by dividing the averaged values.</li>
			<li>Generate the fNIRS data for each channel based on the 3D digitizer information. Select the channels that have a registration probability of 100% or more in the superior frontal cortex (SFC)according to the regression calculation of the NIRS-SPM for further analysis.</li>
			<li>Export the peak values of oxygen hemoglobin (HbO) concentration changes. 
			NOTE: In this study, only HbO signals were analyzed due to their high signal-to-noise ratio. The peak values of run-averaged HbO data were extracted for each channel from each participant for further analysis.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>EEG data processing 
	NOTE: Offline EEG data analysis was performed with the EEGLAB. Only N200 at Fz was the interesting component for the present study. All electrodes were subjected to an automatic artifact correction to remove eye movements by using an internal model of artifact topographies. Continuous EEG data were then segmented into different trials according to target and nontarget stimuli, in which the epoch for each trial lasted 2500 ms, involving a pre-stimulus period of 500 ms (baseline epoch) and a post-stimulus period of 2000 ms (task epoch).
	<ol>
		<li>Load the raw EEG data folder into the EEGLAB by using the plugins. Choose the BIOSIG plugin for the BDF file in this study. 
		NOTE: Please choose a suitable plugin according to the EEG data file format.</li>
		<li>Set the channel location information for EEGLAB37. Load the corresponding location file of the cap.</li>
		<li>Re-reference electrodes in the ERPLAB, which is one plugin of EEGLAB. Choose the channels placed in the mastoids as reference electrodes.</li>
		<li>Extract EEG data epochs based on the event and bin files in the ERPLAB37.</li>
		<li>Filter the EEG data segments in the ERPLAB by using the FIR filter by filtering the low frequencies with a cutoff of 30Hz and by filtering the high frequencies with a cutoff of 0.1 Hz.</li>
		<li>Remove ocular EEG artifacts with the Independent Component Analysis in EEGLAB.</li>
		<li>Reject EEG data segments with amplitude values exceeding &#177; 100 &#181;V at any channel in ERPLAB.</li>
		<li>Average the EEG data segments in ERPLAB. 
		NOTE: These are the generally used data analysis method and the software for processing EEG and the fNIRS data. There are numerous processing software and methods available.</li>
	</ol>
	</li>
	<li>Correlation calculation
	<ol>
		<li>Generate the relationship between fNIRS and EEG recordings by using Pearson correlation analysis.</li>
	</ol>
	</li>
</ol>

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J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ERPLAB:+an+open-source+toolbox+for+the+analysis+of+event-related+potentials.">ERPLAB: an open-source toolbox for the analysis of event-related potentials.</a> Frontiers in Human Neuroscience. 8, 213 (2014).</li></ol>

The authors have nothing to disclose.&#8195;

In this protocol, combined EEG and fNIRS recordings were performed to examine the brain activation patterns involving an event-related Flanker paradigm by recording the neural signals of the whole brain and concurrent hemodynamic responses of the prefrontal cortex. The ERP results showed that N200 at Fz was able to significantly distinguish the congruent and incongruent conditions (P=0.037). Meanwhile, the HbO signals in SFC (channels 21) also exhibited a significant difference between the congruent and incongruent condi...

This study aims to develop a working protocol to reveal the neural activation pattern underlying the Flanker task by using fused EEG and fNIRS neuroimaging techniques. Interestingly, the concurrent fNIRS-EEG recordings allow for the inspection of the relationship between the hemodynamic signals in the prefrontal cortex and various event-related potential (ERP) components of the whole brain associated with the Flanker task.
The integration of various noninvasive neuroimaging modalities including functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI) is essential to improve the understanding of where and when information processing is taking place in the brain1,2,3. Additionally, there is the potential to combine fNIRS and EEG to examine the relationship between local neural activity and subsequent changes in hemodynamic responses, in which EEG and fNIRS can be complementary in revealing the neural mechanism of human brain cognitive function. fNIRS is a vascular-based functional neuroimaging technique that relies on the hemodynamic responses to infer brain activation. fNIRS measures the relative oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) concentration changes in the cerebral cortex, which plays an important role in the study of cognitive processing3,4,5,6,7. According to the neurovascular and neurometabolic coupling mechanism8, the change of local neural activity associated with cognitive processing is generally accompanied by subsequent alterations in the local blood flow and blood oxygen with a delay of 4-7 seconds. It is shown that the neurovascular coupling is likely a power transducer, which integrates the fast dynamics of neural activity into the vascular input of slow hemodynamics9. Specifically, fNIRS is mostly used for inspecting the neurovascular activity in the frontal lobe, especially the prefrontal cortex that is responsible for high cognitive functions, such as executive functions10,11,12, reasoning and planning13, decision making14, and social cognition and moral judgment15. However, the hemodynamic responses measured by fNIRS only indirectly capture the neural activity with a low temporal resolution, whereas EEG can offer temporally fine and direct measures of neural activities. Consequently, the combination of EEG and fNIRS recording can identify more features and reveal more information associated with the functioning of the brain.
More importantly, the multi-modal acquisition of EEG and fNIRS signals has been conducted to inspect the brain activation underlying various cognitive tasks16,17,18,19,20,21,22 or brain-computer interface23,24. In particular, concurrent ERP (event-related potential) and fNIRS recordings were carried out based on the event-related auditory oddball paradigm1, in which fNIRS can identify the hemodynamic changes in the frontotemporal cortex several seconds after the appearance of P300 component. Horovitz et al. also demonstrated the simultaneous measurements of fNIRS signals and the P300 component during a semantic processing task25. Interestingly, previous studies based on simultaneous EEG and fNIRS recordings showed that P300 during oddball stimuli exhibited a significant correlation with fNIRS signals26. It was discovered that the multi-modal measures have the potential to reveal the comprehensive cognitive neural mechanism based on the event-related paradigm26. Besides the oddball task, the Flanker task associated with ERP component N200 is also an important paradigm, which can be used for the investigation of cognitive ability detection and evaluation with healthy controls and patients with various disorders. Specifically, N200 was a negative component that peaks 200-350 ms from the anterior cingulated cortex frontal27 and superior temporal cortex28. Although previous studies examined the relationship between the superior frontal cortex and alpha oscillation in the Flanker task29, the correlation between the N200 amplitude and the hemodynamic responses during the Flanker task has not been explored.
In this protocol, a home-made EEG/fNIRS patch based on standard EEG cap was utilized for the concurrent EEG and fNIRS recordings. The arrangements of optodes/electrodes with support were achieved through the placement of fNIRS optodes fused into the EEG cap. The simultaneous EEG and fNIRS data acquisitions were carried out with the same stimuli tasks generated by E-prime software. We hypothesize that ERP components associated with the Flanker task can exhibit a significant correlation with the hemodynamic responses in the prefrontal cortex. Meanwhile, the combined ERP and fNIRS recordings can extract multiple signal indicators to identify the brain activation patterns with enhanced accuracy. To test the hypothesis, the fNIRS setup and EEG machine were integrated to reveal the complex neural cognition mechanism corresponding to the event-related Flanker task.

<table><tbody><tr><td>EEG cap</td><td>EASYCAP GmbH</td><td>-</td><td>-</td></tr><tr><td>EEG system</td><td>BioSemi</td><td>-</td><td>-</td></tr><tr><td>fNIRS system</td><td>TechEn</td><td>-</td><td>CW6 System</td></tr></tbody></table>

conducting concurrent electroencephalography and functional near-infrared spectroscopy recordings with a flanker task

Concurrent EEG and fNIRS recordings offer an excellent opportunity to gain a full understanding of the neural mechanism of cognitive processing by inspecting the relationship between the neural and hemodynamic signals. EEG is an electrophysiological technology that can measure the rapid neuronal activity of the cortex, whereas fNIRS relies on the hemodynamic responses to infer brain activation. The combination of EEG and fNIRS neuroimaging techniques can identify more features and reveal more information associated with the functioning of the brain. In this protocol, fused EEG-fNIRS measurements were performed for concurrent recordings of evoked-electrical potentials and hemodynamic responses during a Flanker task. In addition, the critical steps for setting up the hardware and software system as well as the procedures for data acquisition and analysis were provided and discussed in detail. It is expected that the present protocol can pave a new avenue for improving the understanding of the neural mechanisms underlying various cognitive processes by using the EEG and fNIRS signals.

Figure 2 shows the HbO signals for all channels while Figure 3 displays the ERPs at Fz and FCz for the two conditions of the Flanker task. Figure 4 illustrated the Pearson correlation analysis results showed that the fNIRS signals in SFC exhibited a significant correlation with the ERP N200 component at Fz for the incongruent condition (P&#60;0.05). However, this is not the case for the congruent condit...

Watch this Scientific Journal Video about Conducting Concurrent Electroencephalography and Functional Near-Infrared Spectroscopy Recordings with a Flanker Task at JoVE.com

Conducting Concurrent Electroencephalography and Functional Near-Infrared Spectroscopy Recordings with a Flanker Task

The present protocol describes how to perform concurrent EEG and fNIRS recordings and how to inspect the relationship between the EEG and fNIRS data.&#160;

Concurrent EEG and fNIRS recordings offer an excellent opportunity to gain a full understanding of the neural mechanism of cognitive processing by ...

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7.6K Views.  University of Macau. The present protocol describes how to perform concurrent EEG and fNIRS recordings and how to inspect the relationship between the EEG and fNIRS data. 

Video: Conducting Concurrent Electroencephalography and Functional Near-Infrared Spectroscopy Recordings with a Flanker Task

Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks

There are several advantages that functional near-infrared spectroscopy (fNIRS) presents in the study of the neural control of human movement. It is relatively flexible with respect to participant positioning and allows for some head movements during tasks. Additionally, it is inexpensive, light weight, and portable, with very few contraindications to its use. This presents a unique opportunity to study functional brain activity during motor tasks in individuals who are typically developing, as well as those with movement disorders, such as cerebral palsy. An additional consideration when studying movement disorders, however, is the quality of actual movements performed and the potential for additional, unintended movements. Therefore, concurrent monitoring of both blood flow changes in the brain and actual movements of the body during testing is required for appropriate interpretation of fNIRS results. Here, we show a protocol for the combination of fNIRS with muscle and kinematic monitoring during motor tasks. We explore gait, a unilateral multi-joint movement (cycling), and two unilateral single-joint movements (isolated ankle dorsiflexion, and isolated hand squeezing). The techniques presented can be useful in studying both typical and atypical motor control, and can be modified to investigate a broad range of tasks and scientific questions.

Monitoring brain activity during upright motor tasks is of great value when investigating the neural source of movement disorders. Here, we demonstrate a protocol that combines functional near infrared spectroscopy with continuous monitoring of muscle and kinematic activity during 4 types of motor tasks.

There are several advantages that functional near-infrared spectroscopy (fNIRS) presents in the study of the neural control of human movement. It is ...

Behavior

Using Fiberless, Wearable fNIRS to Monitor Brain Activity in Real-world Cognitive Tasks

Functional Near Infrared Spectroscopy (fNIRS) is a neuroimaging technique that uses near-infrared light to monitor brain activity. Based on neurovascular coupling, fNIRS is able to measure the haemoglobin concentration changes secondary to neuronal activity. Compared to other neuroimaging techniques, fNIRS represents a good compromise in terms of spatial and temporal resolution. Moreover, it is portable, lightweight, less sensitive to motion artifacts and does not impose significant physical restraints. It is therefore appropriate to monitor a wide range of cognitive tasks (e.g., auditory, gait analysis, social interaction) and different age populations (e.g., new-borns, adults, elderly people). The recent development of fiberless fNIRS devices has opened the way to new applications in neuroscience research. This represents a unique opportunity to study functional activity during real-world tests, which can be more sensitive and accurate in assessing cognitive function and dysfunction than lab-based tests. This study explored the use of fiberless fNIRS to monitor brain activity during a real-world prospective memory task. This protocol is performed outside the lab and brain haemoglobin concentration changes are continuously measured over the prefrontal cortex while the subject walks around in order to accomplish several different tasks.

Monitoring brain activity outside the lab without physical constraints presents methodological challenges. A fiberless, wearable functional Near Infrared Spectroscopy (fNIRS) system was used to measure brain activity during an ecological prospective memory task. It was demonstrated that this system could be used to monitor brain activity during non-lab based experiments.

Functional Near Infrared Spectroscopy (fNIRS) is a neuroimaging technique that uses near-infrared light to monitor brain activity. Based on neurovascular ...

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

In spite of the success in applying non-invasive electroencephalography (EEG), magneto-encephalography (MEG) and functional magnetic resonance imaging (fMRI) for extracting crucial information about the mechanism of the human brain, such methods remain insufficient to provide information about physiological processes reflecting cognitive and emotional functions at the subcortical level. In this respect, modern invasive clinical approaches in humans, such as deep brain stimulation (DBS), offer a tremendous possibility to record subcortical brain activity, namely local field potentials (LFPs) representing coherent activity of neural assemblies from localized basal ganglia or thalamic regions. Notwithstanding the fact that invasive approaches in humans are applied only after medical indication and thus recorded data correspond to altered brain circuits, valuable insight can be gained regarding the presence of intact brain functions in relation to brain oscillatory activity and the pathophysiology of disorders in response to experimental cognitive paradigms. In this direction, a growing number of DBS studies in patients with Parkinson&#39;s disease (PD) target not only motor functions but also higher level processes such as emotions, decision-making, attention, memory and sensory perception. Recent clinical trials also emphasize the role of DBS as an alternative treatment in neuropsychiatric disorders ranging from obsessive compulsive disorder (OCD) to chronic disorders of consciousness (DOC). Consequently, we focus on the use of combined invasive (LFP) and non-invasive (EEG) human brain recordings in assessing the role of cortical-subcortical structures in cognitive and emotional processing trough experimental paradigms (e.g. speech stimuli with emotional connotation or paradigms of cognitive control such as the Flanker task), for patients undergoing DBS treatment.

The present protocol aims at assessing cognitive-emotional functions in the basal ganglia by simultaneous neurophysiological recording of local field potentials and non-invasive brain cortical activity (EEG). The procedure is exemplified by the use of paradigms involving speech stimuli with emotional connotation or the Flanker task involving cognitive control.

In spite of the success in applying non-invasive electroencephalography (EEG), magneto-encephalography (MEG) and functional magnetic resonance imaging ...

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), magnetoencephalography or functional magnetic-resonance imaging. These techniques have either inherently low temporal or low spatial resolution, and suffer from low signal-to-noise ratio and/or poor high-frequency sensitivity. Thus, they are suboptimal for exploring the short-lived spatio-temporal dynamics of many of the underlying brain processes. In contrast, the invasive technique of electrocorticography (ECoG) provides brain signals that have an exceptionally high signal-to-noise ratio, less susceptibility to artifacts than EEG, and a high spatial and temporal resolution (i.e., &lt;1 cm/&lt;1 millisecond, respectively). ECoG involves measurement of electrical brain signals using electrodes that are implanted subdurally on the surface of the brain. Recent studies have shown that ECoG amplitudes in certain frequency bands carry substantial information about task-related activity, such as motor execution and planning1, auditory processing2 and visual-spatial attention3. Most of this information is captured in the high gamma range (around 70-110 Hz). Thus, gamma activity has been proposed as a robust and general indicator of local cortical function1-5. ECoG can also reveal functional connectivity and resolve finer task-related spatial-temporal dynamics, thereby advancing our understanding of large-scale cortical processes. It has especially proven useful for advancing brain-computer interfacing (BCI) technology for decoding a user's intentions to enhance or improve communication6 and control7. Nevertheless, human ECoG data are often hard to obtain because of the risks and limitations of the invasive procedures involved, and the need to record within the constraints of clinical settings. Still, clinical monitoring to localize epileptic foci offers a unique and valuable opportunity to collect human ECoG data. We describe our methods for collecting recording ECoG, and demonstrate how to use these signals for important real-time applications such as clinical mapping and brain-computer interfacing. Our example uses the BCI2000 software platform8,9 and the SIGFRIED10 method, an application for real-time mapping of brain functions. This procedure yields information that clinicians can subsequently use to guide the complex and laborious process of functional mapping by electrical stimulation.
Prerequisites and Planning:
Patients with drug-resistant partial epilepsy may be candidates for resective surgery of an epileptic focus to minimize the frequency of seizures. Prior to resection, the patients undergo monitoring using subdural electrodes for two purposes: first, to localize the epileptic focus, and second, to identify nearby critical brain areas (i.e., eloquent cortex) where resection could result in long-term functional deficits. To implant electrodes, a craniotomy is performed to open the skull. Then, electrode grids and/or strips are placed on the cortex, usually beneath the dura. A typical grid has a set of 8 x 8 platinum-iridium electrodes of 4 mm diameter (2.3 mm exposed surface) embedded in silicon with an inter-electrode distance of 1cm. A strip typically contains 4 or 6 such electrodes in a single line. The locations for these grids/strips are planned by a team of neurologists and neurosurgeons, and are based on previous EEG monitoring, on a structural MRI of the patient's brain, and on relevant factors of the patient's history. Continuous recording over a period of 5-12 days serves to localize epileptic foci, and electrical stimulation via the implanted electrodes allows clinicians to map eloquent cortex. At the end of the monitoring period, explantation of the electrodes and therapeutic resection are performed together in one procedure.
In addition to its primary clinical purpose, invasive monitoring also provides a unique opportunity to acquire human ECoG data for neuroscientific research. The decision to include a prospective patient in the research is based on the planned location of their electrodes, on the patient's performance scores on neuropsychological assessments, and on their informed consent, which is predicated on their understanding that participation in research is optional and is not related to their treatment. As with all research involving human subjects, the research protocol must be approved by the hospital's institutional review board. The decision to perform individual experimental tasks is made day-by-day, and is contingent on the patient's endurance and willingness to participate. Some or all of the experiments may be prevented by problems with the clinical state of the patient, such as post-operative facial swelling, temporary aphasia, frequent seizures, post-ictal fatigue and confusion, and more general pain or discomfort.
At the Epilepsy Monitoring Unit at Albany Medical Center in Albany, New York, clinical monitoring is implemented around the clock using a 192-channel Nihon-Kohden Neurofax monitoring system. Research recordings are made in collaboration with the Wadsworth Center of the New York State Department of Health in Albany. Signals from the ECoG electrodes are fed simultaneously to the research and the clinical systems via splitter connectors. To ensure that the clinical and research systems do not interfere with each other, the two systems typically use separate grounds. In fact, an epidural strip of electrodes is sometimes implanted to provide a ground for the clinical system. Whether research or clinical recording system, the grounding electrode is chosen to be distant from the predicted epileptic focus and from cortical areas of interest for the research. Our research system consists of eight synchronized 16-channel g.USBamp amplifier/digitizer units (g.tec, Graz, Austria). These were chosen because they are safety-rated and FDA-approved for invasive recordings, they have a very low noise-floor in the high-frequency range in which the signals of interest are found, and they come with an SDK that allows them to be integrated with custom-written research software. In order to capture the high-gamma signal accurately, we acquire signals at 1200Hz sampling rate-considerably higher than that of the typical EEG experiment or that of many clinical monitoring systems. A built-in low-pass filter automatically prevents aliasing of signals higher than the digitizer can capture. The patient's eye gaze is tracked using a monitor with a built-in Tobii T-60 eye-tracking system (Tobii Tech., Stockholm, Sweden). Additional accessories such as joystick, bluetooth Wiimote (Nintendo Co.), data-glove (5th Dimension Technologies), keyboard, microphone, headphones, or video camera are connected depending on the requirements of the particular experiment.
Data collection, stimulus presentation, synchronization with the different input/output accessories, and real-time analysis and visualization are accomplished using our BCI2000 software8,9. BCI2000 is a freely available general-purpose software system for real-time biosignal data acquisition, processing and feedback. It includes an array of pre-built modules that can be flexibly configured for many different purposes, and that can be extended by researchers' own code in C++, MATLAB or Python. BCI2000 consists of four modules that communicate with each other via a network-capable protocol: a Source module that handles the acquisition of brain signals from one of 19 different hardware systems from different manufacturers; a Signal Processing module that extracts relevant ECoG features and translates them into output signals; an Application module that delivers stimuli and feedback to the subject; and the Operator module that provides a graphical interface to the investigator.
A number of different experiments may be conducted with any given patient. The priority of experiments will be determined by the location of the particular patient's electrodes. However, we usually begin our experimentation using the SIGFRIED (SIGnal modeling For Realtime Identification and Event Detection) mapping method, which detects and displays significant task-related activity in real time. The resulting functional map allows us to further tailor subsequent experimental protocols and may also prove as a useful starting point for traditional mapping by electrocortical stimulation (ECS).
Although ECS mapping remains the gold standard for predicting the clinical outcome of resection, the process of ECS mapping is time consuming and also has other problems, such as after-discharges or seizures. Thus, a passive functional mapping technique may prove valuable in providing an initial estimate of the locus of eloquent cortex, which may then be confirmed and refined by ECS. The results from our passive SIGFRIED mapping technique have been shown to exhibit substantial concurrence with the results derived using ECS mapping10.
The protocol described in this paper establishes a general methodology for gathering human ECoG data, before proceeding to illustrate how experiments can be initiated using the BCI2000 software platform. Finally, as a specific example, we describe how to perform passive functional mapping using the BCI2000-based SIGFRIED system.

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

We present a method for collecting electrocorticographic signals for research purposes from humans who are undergoing invasive epilepsy monitoring. We show how to use the BCI2000 software platform for data collection, signal processing and stimulus presentation. Specifically, we demonstrate SIGFRIED, a BCI2000-based tool for real-time functional brain mapping.

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), ...

Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent

Although electroencephalography (EEG) is widely used as a non-invasive technique for recording neural activities of the brain, our understanding of the neurogenesis of EEG is still very limited. Local field potentials (LFPs) recorded via a multi-laminar microelectrode can provide a more detailed account of simultaneous neural activity across different cortical layers in the neocortex, but the technique is invasive. Combining EEG and LFP measurements in a pre-clinical model can greatly enhance understanding of the neural mechanisms involved in the generation of EEG signals, and facilitate the derivation of a more realistic and biologically accurate mathematical model of EEG. A simple procedure for acquiring concurrent and co-localized EEG and multi-laminar LFP signals in the anesthetized rodent is presented here. We also investigated whether EEG signals were significantly affected by a burr hole drilled in the skull for the insertion of a microelectrode. Our results suggest that the burr hole has a negligible impact on EEG recordings.

This protocol describes a simple method for concurrent recording of co-localized electroencephalography (EEG) and multi-laminar local field potential in an anesthetized rat. A burr hole drilled in the skull for the insertion of a microelectrode is shown to produce negligible distortion of the EEG signal.

Although electroencephalography (EEG) is widely used as a non-invasive technique for recording neural activities of the brain, our understanding of the ...

Conducting Hyperscanning Experiments with Functional Near-Infrared Spectroscopy

Concurrent brain recordings of two or more interacting persons, an approach termed hyperscanning, are gaining increasing importance for our understanding of the neurobiological underpinnings of social interactions, and possibly interpersonal relationships. Functional near-infrared spectroscopy (fNIRS) is well suited for conducting hyperscanning experiments because it measures local hemodynamic effects with a high sampling rate and, importantly, it can be applied in natural settings, not requiring strict motion restrictions. In this article, we present a protocol for conducting fNIRS hyperscanning experiments with parent-child dyads and for analyzing brain-to-brain synchrony. Furthermore, we discuss critical issues and future directions, regarding the experimental design, spatial registration of the fNIRS channels, physiological influences and data analysis methods. The described protocol is not specific to parent-child dyads, but can be applied to a variety of different dyadic constellations, such as adult strangers, romantic partners or siblings. To conclude, fNIRS hyperscanning has the potential to yield new insights into the dynamics of the ongoing social interaction, which possibly go beyond what can be studied by examining the activities of individual brains.

The present protocol describes how to conduct fNIRS hyperscanning experiments and analyze brain-to-brain synchrony. Further, we discuss challenges and possible solutions.

Concurrent brain recordings of two or more interacting persons, an approach termed hyperscanning, are gaining increasing importance for our understanding ...

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG (good temporal resolution) and fMRI (good spatial resolution) to measure neuronal activity during an electrographic event, through hemodynamic responses known as blood-oxygen-level-dependent (BOLD) changes. It is a non-invasive research tool that is utilized in neuroscience research and is highly beneficial to the clinical community, especially for the management of neurological diseases, provided that proper equipment and protocols are administered during data acquisition. Although recording EEG-fMRI is apparently straightforward, the correct preparation, especially in placing and securing the electrodes, is not only important for safety but is also critical in ensuring the reliability and analyzability of the EEG data obtained. This is also the most experience-demanding part of the preparation. To address these issues, a straightforward protocol that ensures data quality was developed. This article provides a step-by-step guide for acquiring reliable EEG data during EEG-fMRI using this protocol that utilizes readily available medical products. The presented protocol can be adapted to different applications of EEG-fMRI in research and clinical settings, and may be beneficial to both inexperienced and expert operators.

This article provides a straightforward protocol for acquiring good quality electroencephalography (EEG) data during simultaneous EEG and functional magnetic resonance imaging by utilizing readily available medical products.

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG ...

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Functional near-infrared spectroscopy (fNIRS) is a portable neuroimaging methodology, more robust to motion and more cost-effective than functional magnetic resonance imaging (fMRI), which makes it highly suitable for conducting naturalistic studies of brain function and for use with developmental and clinical populations. Both fNIRS and fMRI methodologies detect changes in cerebral blood oxygenation during functional brain activation, and prior studies have shown high spatial and temporal correspondence between the two signals. There is, however, no quantitative comparison of the two signals collected simultaneously from the same subjects with whole-head fNIRS coverage. This comparison is necessary to comprehensively validate area-level activations and functional connectivity against the fMRI gold standard, which in turn has the potential to facilitate comparisons of the two signals across the lifespan. We address this gap by describing a protocol for simultaneous data collection of fMRI&#160;and fNIRS signals that: i) provides whole-head fNIRS coverage; ii) includes short-distance measurements for regression of the non-cortical, systemic physiological signal; and iii) implements two different methods for optode-to-scalp co-registration of fNIRS measurements. fMRI and fNIRS data from three subjects are presented, and recommendations for adapting the protocol to test developmental and clinical populations are discussed. The current setup with adults allows scanning sessions for an average of approximately 40 min, which includes both functional and structural scans. The protocol outlines the steps required to adapt the fNIRS equipment for use in the magnetic resonance (MR) environment, provides recommendations for both data recording and optode-to-scalp co-registration, and discusses potential modifications of the protocol to fit the specifics of the available MR-safe fNIRS system. Representative subject-specific responses from a flashing-checkerboard task illustrate the feasibility of the protocol to measure whole-head fNIRS signals in the MR environment. This protocol will be particularly relevant for researchers interested in validating fNIRS signals against fMRI across the lifespan.

We present a method for simultaneously collecting fMRI and fNIRS signals from the same subjects with whole-head fNIRS coverage. The protocol has been tested with three young adults and can be adapted for data collection for developmental studies and clinical populations.

Functional near-infrared spectroscopy (fNIRS) is a portable neuroimaging methodology, more robust to motion and more cost-effective than functional ...

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two of the fundamental noninvasive methods for identifying brain activity. Multimodal methods have sought to combine the high temporal resolution of EEG with the spatial precision of fMRI, but the complexity of this approach is currently in need of improvement. The protocol presented here describes the recently developed spatiotemporal fMRI-constrained EEG source imaging method, which seeks to rectify source biases and improve EEG-fMRI source localization through the dynamic recruitment of fMRI sub-regions. The process begins with the collection of multimodal data from concurrent EEG and fMRI scans, the generation of 3D cortical models, and independent EEG and fMRI processing. The processed fMRI activation maps are then split into multiple priors, according to their location and surrounding area. These are taken as priors in a two-level hierarchical Bayesian algorithm for EEG source localization. For each window of interest (defined by the operator), specific segments of the fMRI activation map will be identified as active to optimize a parameter known as model evidence. These will be used as soft constraints on the identified cortical activity, increasing the specificity of the multimodal imaging method by reducing cross-talk and avoiding erroneous activity in other conditionally active fMRI regions. The method generates cortical maps of activity and time-courses, which may be taken as final results, or used as a basis for further analyses (analyses of correlation, causation, etc.) While the method is somewhat limited by its modalities (it will not find EEG-invisible sources), it is broadly compatible with most major processing software, and is suitable for most neuroimaging studies.

An EEG-fMRI multimodal imaging method, known as the spatiotemporal fMRI-constrained EEG source imaging method, is described here. The presented method employs conditionally-active fMRI sub-maps, or priors, to guide EEG source localization in a manner that improves spatial specificity and limits erroneous results.

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two of the fundamental noninvasive methods for identifying brain ...

Biology

Recording Cortical and Subcortical Neuronal Activity Using Electrode Systems

Source: Trenado, C., et al. <a href="https://app.jove.com/v/53466">Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans.</a> J. Vis. Exp. (2016).
This video demonstrates the process of recording cortical and subcortical neuronal activity using electroencephalography (EEG) and deep brain stimulation (DBS) electrodes during an attention-based visual stimulation test.

All procedures involving human participants have been performed in compliance with the institutional, national, and international guidelines for human ...