eeg use during dbs

Electroencephalography Use During Deep Brain Stimulation

California Polytechnic State University - San Luis Obispo

Adam Aslam Charles Aylward

Sara Wier

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Introduction- Project Goal- The goal of this project was to investigate electroencephalography use during deep brain stimulation through the testing and observation of signal patterns in healthy subjects. Project Aims- The aims of this project were to research, select and purchase, and start human subject testing all with the focus on electroencephalography and deep brain stimulation as it applies to Parkinson’s Disease. The emphasis of research was to look into what causes the signals picked up by the EEG, the dominant signals associated with EEG, current literature of EEG use especially associated with Parkinson’s Disease, and a general knowledge of deep brain stimulation and its applications. In order to select an EEG system several criteria were generated from previous studies. The criteria focused on electrode type, number of channels, sampling rate, and price. From the criteria, a system was selected. Subject testing was not investigated this year, but will extend into next year as the project continues. Background Research- The Brain- The Lobes of the Brain and Their Functions: The frontal lobe, located in the anterior part of the brain, is mainly responsible for emotional control, forming our personality, and influencing our decisions. Other functions of the frontal lobe include cognition, problem solving, speech, motor skill development, impulse control, regulating sexual urges, and planning. The parietal lobe, which mainly functions in processing sensory information for cognitive processes and spatial reasoning, is located posteriorly to the frontal lobe. More specifically, the parietal lobe senses pain, pressure, and touch, regulates and processes the body’s five senses, movement, visual orientation, and speech. The temporal lobes are located on each side of the brain and mainly process auditory sounds. Other functions of the temporal lobes include helping to form long-term memories and process new information, formation of visual and verbal memories, and interpret smells and sounds. The occipital lobe is located at the very back of the brain and is mainly responsible for visual processing. Other functions of the occipital lobe include movement and color recognition (“Lobes of the Brain”).

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Figure 1. Left: each lobe is differentiated by color and location (“Lobes of the Brain”); Right: the subthalamic nucleus is located beneath the thalamus (Leisman).

Motor Function Control Centers: The subthalamic nucleus is a component of the basal ganglia and is part of the diencephalon (Temel). Basal ganglia are collections of neuron cell bodies that receive input from the cerebral cortex and participate in the organization and guidance of complex motor functions. The basal ganglia consist of three structures: the caudate, the putamen, and the globus pallidus (Figure 2). The basal ganglia also transmit signals to other parts of the brain (Figure 2). The basal ganglia are mainly responsible for initiating and stopping skeletal movements (Purves).

Figure 2. Left: The anatomy and location of the basal ganglia are shown as well as the substantia nigra in the midbrain. Shown also are the signal transmission pathways. Right: Also shows signal transmission pathways, but

more clearly shows the inputs and outputs of the caudate and putamen of the basal ganglia (Purves). The cerebral cortex and the lobes of the brain are further broken down into 3 areas that control nearly all movement. The primary motor cortex is responsible for conscious control of precise skeletal muscle movements. The premotor cortex controls learned and repetitious motor skills and helps plan movements. Broca’s area is located in the left hemisphere of the brain usually and directs the muscles responsible for speech production.

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Figure 3. The locations of the primary motor cortex (red), premotor cortex (blue), and Broca’s area (purple) are shown (Motor areas of the brain).

Neuron Behavior- Neuron potentials: There are three different levels of membrane potentials. The first is the resting potential, which maintains a value of -70mV while nothing perturbs the cell. The threshold potential, -55mV, is the value the potential difference of the neuron must reach in order for an action potential to occur. An action potential is the period in which the cell potential rises and falls quickly to propagate a neural signal. The peak potential during this time is approximately 30 mV and is the maximum value the potential reaches during depolarization. The change in potential from resting to peak depolarization is always approximately 100mV (Shields, “Action Potentials”). There are two different types of potentials that occur at the post-synaptic cleft or the region between the axon terminal of one neuron and the dendrites of another neuron. The first type is known as an excitatory postsynaptic potential (EPSP) and is when the net influx of sodium ions is greater than net influx of potassium ions and a depolarization occurs that leads to an action potential. The second type is an inhibitory postsynaptic potential (IPSP) in which channels open for potassium and chlorine ions making the inside of the neuron more negative which inhibits the formation of an action potential (Shields, “The Synapse”). Potentials can also interact with one another in three ways. Temporal summation occurs when EPSPs close in time add together resulting in one excitatory postsynaptic potential of greater value. A spatial summation occurs when simultaneous stimulations at two different locations can cause EPSPs that add together also resulting in an excitatory postsynaptic potential of greater value. EPSPs and IPSPs can also summate and cancel each other out resulting in no change in cellular potential (Shields, “The Synapse”).

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Figure 4. Diagram showing the potential changes during depolarization of a neuron (Aqra).

Signal speed: The speed of signal is influenced by axon diameter and the amount of myelin a neuron possesses. The larger the diameter of the axon, the less resistance to local current flow there will be, which results in faster signal conduction. Myelin is a sheath that surrounds certain types of axons. More myelin results in faster conduction because the signal jumps over the myelin sheaths to gaps between the sheaths called Nodes of Ranvier, which shortens the distance the signal has to travel and thus cutting the time it takes for the signal to reach its destination. This is known as saltatory conduction (Shields, “Histology of Nervous Tissue”). Depolarization: While each neuron is resting, they maintain a cell potential of -70mV with a more negative interior than exterior. This potential is regulated by passive or leaky potassium ion channels if left by themselves would create a resting potential of -90mV. To establish the normal resting potential the neurons also utilize sodium-potassium pumps, which use energy in the form of ATP to pump three sodium ions out of the cell and two potassium ions into the cell. The process of depolarization begins with a stimulus, which could come from a conformational change in a peripheral neuron receptor or from the transmission and reception of neurotransmitters within the brain. This stimulation could also be caused by an applied electrical stimulus as with DBS. Once the stimulus reaches a neuron, the chemically gated sodium channels open up on the pre-synaptic dendritic endings of the neuron allowing sodium ions to flood into the cell. This is called a graded potential, which travels down the dendrites through the cell body to the beginning of the axon known as the axon hillock. The influx of sodium raises the potential. If the potential does not reach -55mV at this point, the cell only experiences the graded potential, an impulse that travels a smaller distance and does not stimulate any other neurons. However, if the cell potential reaches -55mV or above, an action potential propagates and is known as depolarization. This propagation occurs as the sodium ions increase the amount of positive charge within the cell and as the positive charge travels down the cell from the axon hillock, it causes the opening

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of more sodium channels. Once the cell reaches its maximum potential of 30 mV, potassium ion channels begin to open to allow the flux of potassium from within the cell. This begins to lower the potential of the cell to return it to resting potential after the impulse has travelled by the axon hillock and has begun to propagate down the axon. Hyperpolarization occurs when the membrane potential becomes more negative than the resting potential. This happens because the voltage gated sodium channels along the axon become inactivated when the impulse passes them and the potassium ion channels remain open and close more slowly. This is also called the absolute refractory period, which ensures that the signal only propagates in one direction. This allows more positively charged potassium ions to leave the cell than can enter through the only available leaky potassium ion channel thus causing the charge within the cell to drop and the charge outside the cell to increase. Once the potassium ion channels close, the voltage gated sodium channels reset and the resting membrane potential is reestablished through leaky potassium ion channels and the sodium potassium pump (Shields, “Action Potentials”). After the signal travels through the axon, it reaches the terminal dendritic endings of the neuron or what is known as the post-synaptic cleft. When the action potential propagates to this area, voltage gated calcium channels open and synaptic vesicles release the neurotransmitter by exocytosis. This neurotransmitter travels across the gap between the postsynaptic cleft of this one neuron to the pre-synaptic cleft of another neuron where the neurotransmitters bind to chemically gated sodium receptors and start another action potential (Shields, “The Synapse”).

Movement Disorders and Treatment- Movement Disorders are conditions that can be disabling and very difficult to manage. The most common movement disorder is ET. ET is a progressive disease that is often inherited and begins later in adulthood. Patients experience tremors due to the brain sending abnormal signals to muscles. The areas of the brain that the signals move through before reaching muscles are the cerebellum, nucleus ruber, globus pallidus interna (GPi), thalamus, and cortex (Types of Movement Disorders). Another common movement disorder is PD. Patients can suffer from tremors, muscle rigidity, bradykinesia, and depression among other symptoms. The cause of PD is unknown, but the symptoms are known to be caused by the loss of cells in the substantia nigra. This area produces the neurotransmitter dopamine, which is involved with muscle movement and motivation (Types of Movement Disorders). When the substantia nigra is deteriorated, the subthalamic nucleus (STN) becomes overactive, which affects the GPi. The GPi being overstimulated leads to thalamic inhibition, thus tremor. When the GPi is slowed, motion and rigidity begins to shut down (Espay). ET patients sometimes choose to take medications such as Primidone or Propranolol. Most medications that PD patients use aim to replace lost dopamine. Physical therapy and exercises have been known to improve symptoms as well (Types of Movement Disorders).

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Deep brain stimulation is a relatively recently developed technology that has had a drastic effect on the symptoms of many PD and ET patients. In DBS, a lead is implanted in the brain, usually in the thalamus, STN, or the GPi (Browner), which is then connected to an implanted pulse generator that contains the battery and circuitry required to generate the stimulation pulses. The generator is implanted beneath the skin in the upper portion of the chest and connected by wire subcutaneously to the DBS lead in the brain.

Figure 5. From left to right: Thalamus implantation of DBS stimulator, GPi implantation of DBS stimulator, and

STN implantation of DBS stimulator (Browner).

Components of an EEG System- EEG systems are comprised of electrodes, amplifiers, filters, analog to digital converter, and a recording device. Data flows from activity within the brain to the electrodes placed on the scalp in the microvolt range. Amplifiers and filters boost the signal to a range that can be accurately converted to digital data. The analog to digital converter then converts the signal to be read and displayed by a recording device, such as a personal computer. Neural activity in the brain results in changing potentials measured between a signal electrode and reference electrode. A third electrode (placement irrelevant) is used to ground the system. This general configuration of electrode is referred to as a montage. There are two types of montages: bipolar and referential. In the bipolar montage there are two electrodes used per channel. One electrode is used to perceive the potential difference and the other is used as a reference electrode. The referential montage uses one common reference electrode for all channels (EEG: Introduction). The electrodes are critical in obtaining high quality data for interpretation. Types of electrodes include disposable electrodes (often used with gel), reusable disc electrodes (gold, silver, stainless steel or tin), headbands/electrode caps, saline-based electrodes, and needle electrodes. Multi-channel EEG analysis favors the electrode cap as it places electrodes all around the surface of the scalp. Electrodes in the cap are commonly made of 1-3 mm diameter Ag or AgCl disks with a long flexible lead to connect to an amplifier. AgCl electrodes provide accurate recording in very slow changes in potential. Needle electrodes penetrate

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through the scalp, which can cause irritation or pain for the user and are thus best used only for long duration readings. Skin preparation prior to mounting the electrodes involves cleaning the skin surface of dried parts and oils. The space between the electrodes and the skin should be filled with a conductive paste to lower the impedance between the skin and electrodes as well as help the electrodes stick. Cap systems often provide small holes to inject the conductive paste (EEG: Introduction). In some systems, dry electrodes are used for convenience. These do not require the use of conductive paste, which minimizes preparation and clean up time. The performance of these systems has been shown to be as effective as commercially available wet electrodes (Taheri). Due to the low amplitude of the signals naturally created in the brain, amplifiers are required to gain the signals to levels usable by devices such as converters and displays. Specific characteristics of amplification must be met to selectively acquire the physiological systems and reject noise. Overwhelming interference can damage other components as the gain may boost the signals (surge) past maximum ratings. Biopotential amplification must meet several basic requirements to preserve the natural signal and protect the monitored patient. There must be protection for the system components and patient to prevent harm from surges or high input voltages. The physiological process must not be influenced in any way by the amplification and the signal must not be distorted. During measurements, the amplifier will pick up signals from the desired biopotential, undesired biopotentials, power line interference signal or 60 Hz (and harmonics), interference signals generated by the skin-electrode interface, and noise. Proper design eliminates the majority of the interference signals (EEG: Introduction). Important EEG System Specifications: Frequency bandwidth: Approximately 1Hz to 50 Hz. This range would capture the range of useful EEG, from beta waves to gamma waves (Malmivuo). Sampling Rate: The rate of data acquisition ranges from 20Hz to 20,000Hz depending on the system. Faster sampling rates allow for the analysis of high frequency signals and more accurate readings of ERPs or event related potentials. Number of channels: Depending on the application, the number of necessary channels can range from 2 to 256. A study looking into effective numbers of channels found that in a 256 electrode cap, on average only 125 gave useful results due to movement artifacts and poor electrode to scalp connections (Lau). Studies involving motion have been successful looking at as few as 2 strategically placed electrodes.

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Standard filters: Less than 1 Hz (high pass filter) and 50 Hz (low pass filter) (EEG: Introduction). Electrode Material: Ag/AgCl is a commonly used material in many clinical EEG applications. Electrode placement: Standard locations such as 10/20, 10/10, or 10/5 placement (EEG: Introduction). The first number refers to the front-to-back electrodes being placed with 10% of the total length in between each other. The second number refers to the side-to-side percentages of total length. The standard 10/20 placement has been improved upon in the 10/10 and 10/5 placements, which have more electrodes (Oostenveld and Praamstra). Impedance (resistance to current flow): 100 ohms to 5000 ohms (EEG: Introduction). .

Figure 6. 10/20 placement of electrodes on the scalp. Each letter preceding the numbers indicates the lobe of the

brain on which the electrode is placed. The number refers to the location (odd numbers being on the left side of the brain, even numbers on the right). Also shown are the placement of two reference electrodes, in this case, on the

ears (A1 and A2) (EEG: Introduction).

EEG Signals- EEG shows a graphical representation of voltage differences between two cerebral locations over time. The majority of the contribution to EEG is from synaptic voltages. This means the summation of both EPSP’s and IPSP’s between cortical neurons are included in the EEG (Olejniczak). There are five classifications of EEG signals. From lowest frequency to highest frequency, the waves are as follows: delta, theta, alpha, beta, and gamma waves. Delta waves have a frequency less than or equal to 3 Hz and dominant rhythms that occur in infants and in stages three and four of sleep. These waves occur frontally in adults and posteriorly in children. Theta waves have a frequency between 3.5 and 7.5 Hz. These waves are abnormal in people who are awake and over the age of 13. Alpha waves have a frequency of 7.5 to 13 Hz. They are best observed

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in posterior regions of adults and are higher in amplitude on the dominant side. These waves are present during relaxation periods such as closing of the eyes. Beta waves have a frequency greater than 14 Hz and they occur equally on both sides of the brain in the frontal region. These waves are dominant in people who are alert, anxious, or have their eyes open (EEG: Introduction). A fifth category, Gamma waves, has a frequency between 30 Hz and 50 Hz (Jirayucharoensak). Although gamma waves are commonly seen in EEG, there is speculation as to whether they can be distinguished from artifact using an EEG machine. Artifact due to eye or limb movement can be easily mistaken for brain activity in the gamma frequency range (Whitham).

Figure 7. Amplitude over a period of about 2 seconds for each major wave frequency class (EEG:

Introduction).

Epilepsy, PD, DBS, and EEG Systems- EEG systems have been mostly used for diagnosis of Epilepsy and other seizure causing disorders, even for seizures caused by aneurysm (Selvaraj). EEGs have also been used to study anxiety disorders, depressive disorders, co-morbid addiction, attention-deficit/hyperactivity disorder, and brain injury (Simkin). EEG devices have been utilized along with electrooculography, and electromyography (EMG) devices to diagnose sleeping disorders (Kaplan). One study used EEG to monitor effects of transcranial direct current stimulation (tDCS) and investigate the feasibility of using both the EEG system and the tDCS system simultaneously. tDCS is a non-invasive form of DBS and applies stimulation to the skull and more specifically in this study to the left sensorimotor cortex (Roy). EEG systems are also being used to diagnose patients with frontotemporal lobar degeneration (FTLD), a form of dementia characterized by alteration in personality and social behaviors and is associated with atrophy in the frontal and temporal brain regions. Before this study was done, FTLD was difficult to diagnose with the pre-existing algorithms to interpret the EEG wave activity, but through this study, non-linear algorithms were developed that led to more determinate diagnosis (Carlino). PD is caused by the degradation of dopamine releasing neurons, which deprives the basal nuclei of dopamine causing them to become overactive in turn causing tremors at rest and slow movements. PD causes a degradation of the area of the midbrain known as the substantia nigra. The substantia nigra acts as a source of input information into the caudate and putamen of the basal ganglia. The caudate and putamen then transmit the signal to the subthalamic nucleus (Purves).

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DBS is usually applied at a frequency of around 130Hz and has two methods of administering stimulation. The first, known as closed loop stimulation delivers electrical pulses in the pattern of firing neurons. The second method was known as open loop stimulation, which delivered normal, continuous, high voltage stimulation to the brain. Both methods were tested first on primates, and then on humans. Closed loop stimulation used the presence of beta bursts, or high frequency beta waves, to determine when and how long the stimulation should occur. When a beta burst was detected, the device delivered stimulation until the beta waves dropped below the trigger frequency, after which stimulation stopped. The study reported that this method of DBS reduced stimulation time by 56% and clinical improvement increased by 30% (Little). The beta wave frequency was determined directly from the DBS electrode. This particular study did not focus on the alteration of beta waves due to DBS, but focused on the frequency of beta waves to determine when to administer DBS stimulation with the closed loop system. (Little). EEG Systems Used in Relevant Studies- In a study used to relate brain waves during painful stimulation to waves during non-painful stimulation, a 19-channel EEG system was used using the 10/20 standard placement of electrodes. Referential montage was also used with reference electrodes on the earlobes and a sampling rate of 500 Hz (Chien). As of 2011, there was no way to record EEG during DBS treatment because of stimulation artifact overlapping with useful EEG. A common practice for collecting data during DBS stimulation was to record EEG just after DBS was shut off, and observe the patient’s transient response. It was found that by Hampel filtering, the artifact could be separated out. This filter uses the fast Fourier transform (FFT) to replace outliers in the frequency domain with interpolated values, then using the inverse FFT to transform back into the time domain. This allows EEG to be recorded during DBS by reducing stimulation artifact. EEG in this study was observed using a 72 channel “EasyCap” using 10/20 placement. Collection of EEG was made with a Neuroscan SynAmps sampling at 1 kHz and processed in Matlab (Allen). Dr. Harrison Walker of the University of Alabama studies DBS applied to PD, dystonia, and ET. A 16 or 24 channel Nihon Kohden EEG system was initially used, with a sampling rate of 10 kHz. To obtain better readings, Dr. Walker has switched to a Brain Vision device with 64 channels and active electrodes, which means that the amplifier is built into the electrode, minimizing artifact noise and improving signal quality. An important aspect of an EEG device is the capacity to sample at a fast rate. Slower sampling rates amplify the size of the noise, producing worse quality EEG signals. The study by Dr. Walker is especially relevant due to its similarity to the topic of this review. Dr. Walker used EEG to observe cortical response to DBS in multiple patients. Dr. Walker originally removed DBS artifact by reversing the anode and

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cathode on the DBS electrode, which inverted artifact and was then removed. Dr. Walker has since moved onto using bipolar pairings to eliminate DBS artifact. This means adjacent EEG electrodes are compared to each other, effectively eliminating DBS signal. Sampling at about 10 times the highest frequency observed is enough, unless looking at latency or to minimize DBS artifact. His experiment was successful in determining that “effective high frequency subthalamic DBS for PD is associated with synchronization of cortical neurons at the stimulation frequency or one of its subharmonics” (Walker). Specifically, it was found that neurons in cerebral cortex discharge at one millisecond after the stimulus pulse (Walker). It is important to note that use of EEG in DBS patients can result in skewed data. Since there is a hole in the head of the patient, changes in ERPs and EEG must be accounted for. This has successfully been done, and is seen in studies using EEG (Oostenveld and Oostendorp). Another study found that by using a simple mean squared error, DBS artifact could be removed from useful EEG. This study described different methods that have been used to separate DBS from useful EEG, such as an offline low pass filter or a bandpass filter online and a low pass filter offline (Sun). The evoked potentials of PD patients are often slowed, meaning neurons take longer to respond to stimuli. This was shown in a study in which patients responded to auditory signals. EEG was taken both with DBS on and off and the time it took the brain to respond to the 70 dB trigger was recorded. The study used a 64 channel EasyCap with active electrodes. The BrainAmp amplifier sampled at 1 kHz and signal was processed using Matlab, EEGLAB, and FieldTrip software. Seven electrodes, side-to-side with the Cz electrode were used for analysis because cable movement, blinking, swallowing, or muscle artifact didn’t largely affect them. A bandpass filter of .016 to 250 Hz was used (Gulberti). Beta waves have been studied as they relate to PD and the effect of DBS on such patients. Beta frequencies, which are centered around 20 Hz are recorded as normal activity for healthy people. Stronger beta waves occur when neural activity becomes synchronized over time and signals summate to produce a larger amplitude beta wave. One study has related beta waves to movement and has supported the mechanistic role of beta waves in the pathophysiology of PD. Beta waves in the study were shown to represent neural firing due to movements. The firing was suppressed due to warning cues predicting upcoming action and beta waves were higher and augmented by the holding of movements and by stopping pre-planned movements. Beta waves were classified as being responsible for slowing of spontaneous movements and postural correction or also maintaining status quo. Patients with PD, especially those who were taken off of dopaminergic medications, were seen to have much higher amplitude beta wave activity which limits information coding capacity so that novel processing is impaired and the status quo formed over new movements resulting in bradykinesia, which is the slowing of movements or

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the inability to adjust the body’s position. Because of this, beta waves are thought to be controlled by the level of dopaminergic activity in response to internal and external cues and serve to modulate the stability of the current motor state (Little). In a study involving finger movement, the C3 and C4 electrodes on healthy subjects were analyzed. Asking subjects to keep their eyes closed and to be as relaxed as possible without falling asleep minimized artifact and unwanted results. In this study, only two of the electrodes out of the 41-electrode cap were crucial for observation A BrainScope EEG was used, sampling at 256 Hz. An Isotrak II 3D scanner helped to place the electrodes at the desired locations (Stastný). Another study looked into the possible use of DBS in the pedunculopontine nucleus for PD patients. They found useful results from ankle and wrist movements by analyzing the Fp1, Fz, Cz, C3, C4, CP3, and CP4 electrodes and sampling at 1 kHz. Two frequency bands, theta (6–10 Hz) and beta (14–30 Hz), contributed to changes in movement in the C3/CP3-C4/CP4 and Fz-Cz range (Tsang).

System Selection- System Requirements-

Requirement Value Active electrodes The system must have active electrodes to minimize the

noise artifact Fast Sampling Rate ≥ 2000 Hz MatLab Compatible It would be nice if the system were compatible with

MatLab for signal analysis Price ≤ $20,000 Channels ≥ 32 channels

Table I. The above system requirements were generated based off of other EEG systems used in other relevant

studies. The requirements were developed from recommendations taken from other relevant studies as well as from a well-known researcher, Harrison Walker, who is familiar with EEG systems. Active electrodes, as recommended by Walker, minimize the noise artifact in the acquired data signal by possessing a second amplifier within them. A faster sampling rate allows for analysis of higher frequency signals and a more accurate reading of action potentials. The higher number of channels allows for a more accurate reading of the exact location of ERPs by covering a larger surface area of the head. And since the team is familiar with MatLab, it would be best to get a system compatible with that software in order to easily analyze the data.

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Some systems that met the majority of our requirements were: NeuroScan- Synamps 2 RT/64, Biosemi- ActiveTwo, Brain Products- ActiCHamp, Cognionics- Wireless 64, ANT Neuro- Asalab 64, and EGI- Geodesic 400. Some less expensive amplifiers were also explored, but with these systems, the cap had to be purchased separately. Some of the amplifiers considered were: Mitsar- 202-31, BrainMaster- Discovery 24E, Advanced Brain Monitoring- B-Alert X24, and Natus- Nicolet v32. Some of the stand-alone caps considered were: ANT Neuro- Waveguard, BrainMaster- ElectroCap, Brain Products- Acticap, BrainVision- BrainCap, and Easycap- eascycap Active. All systems were compared using the requirements above:

Brain Products BioSemi Cognionics Neuroscan

ANT

Neuro EGI

Model ActiCHamp ActiveTwo Wireless 64

Synamps 2/RT

64 Asalab 64 Geodesic 400

Sampling Rate (Hz) 25000 8192 500 20000 4000 8000

Active Electrodes Yes Yes Yes No Yes No

Gel/Dry Gel Gel Dry Gel Gel Gel

MATLAB Yes Yes Yes Yes Yes Yes

Channels 64 64 64 64 64 64

Electrode Layout 10/20 10/20 10/20 10/20 10/20 10/20

Price ($) 39900 32000 40445 -- 28K-56K --

Table II. The systems all evaluated above include both an amplifier and cap. All systems with missing pricing information indicate that pricing information was unavailable.

Amplifiers Mitsar BrainMaster Advanced Brain Monitoring Natus

Model Mitsar 202 31 Discovery

24E B-Alert X24 Nicolet v32 Sampling Rate (Hz) 2000 512 256 12000

MATLAB Yes Yes Yes Yes Channels 32 24 24 32 Price ($) 10500 5800 -- --

Table III. The systems above only consist of an amplifier. If the amplifier is listed without pricing information that

means that pricing information was unavailable for that product.

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Table IV. The products listed above are all electrode caps for EEG. If the price is not listed for the cap the pricing

information was unavailable for that product.

All of the systems in Table I were listed in tier 1, which classified them as being all encompassing systems, but also the most expensive systems. The next two tables layout cheaper systems, but Table II only contains amplifiers and Table III only contains electrode caps. All systems follow the 10/20 electrode placement guidelines. Most systems require conductive gel for the electrodes and are MatLab compatible. The selected EEG system consisted of the Mitsar 202-31 amplifier and the Brain Products actiCAP electrodes and cap. We selected this combination of devices because they met the majority of our requirements. Major considerations when choosing these two devices were the use of active electrodes and MatLab compatibility. The sampling rate was not quite as high as desired, but for our applications, the sampling rate of 2000 Hz seemed sufficient. Another major component was the cost. The MatLab compatibility turned out to be a great thing because this allowed for the incorporation of EEGLab and WinEEG data analysis software.

Protocol- Objective- This study involves the use of an electroencephalography (EEG) system to measure brain signal data from healthy subjects. Our interest is to analyze this EEG while subjects perform tasks that are difficult for patients with movement disorders such as Parkinson's Disease. Our hope is that results can then be used to give more insight on the function of deep brain stimulation in movement disorder patients. Materials- EEG systems consist of a cap, electrodes, recording circuitry, and connecting wires. We will be using the Mitsar-EEG 202-31 system with a 10/10 layout, which has 31 channels and a 2000 Hz sampling rate. This system includes the amplifier, a USB cable, a power supply unit, and WINEEG data analysis software. The cap and electrode system used will be a 32-channel BrainProducts actiCAP with active electrodes. This also comes with the SuperVisc gel that is used to increase conductivity at the electrode. An external device such as a camera or accelerometer will be used simultaneously with the experiment in order to mark the time of the

Caps ANT Neuro BrainMaster Brain Products BrainVision Easycap Model Waveguard ElectroCap actiCAP BrainCap Easycap Active

Active Electrodes Yes No Yes No Yes Electrode Layout 10/20 10/20 10/20 10/20 10/20

Price ($) -- 475 -- -- --

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action on the signal. For use in our tests seen in the Methods section, we will use paper cups, pencils, and binder paper. Methods- The 18-24 year old students being studied will be asked for basic demographic information, including age, sex, race, and relevant health history. Before testing begins, the subject will be asked to review and sign the informed consent form, and any questions that he or she has about the study will be addressed. The subject will be told that they have the option to opt out of the study at any time. The study will take approximately 1 hour to complete. The first step is EEG system setup, which includes placement of the EEG cap and will take 10-15 minutes total to complete. The camera will be set up to view the subject's upper body, head, and the table in front of him/her. At this time, an optional accelerometer may also be set up in the appropriate location. The setup of the EEG includes adjusting the electrode cap to fit the user’s head and injecting the conductive gel. The subjects will then be asked to relax and sit still for 2 minutes. Each test will have the subject wait for a verbal cue to begin the indicated activity. A research supervisor will begin a timer at the start of each test. During each test, subjects will be asked to avoid blinking or moving, other than that required for the test. 1. Pencil Pickup Test The first test has the subject reach for an object placed on a table within arm’s reach. The subject will be asked to sit comfortably with his/her arms resting on the table. Then he/she will reach for a pencil on the table, pick it up, and place it back on the table. This test will be repeated five times by each subject with 20 seconds between each test. 2. Writing/Drawing Test This test looks into writing/drawing. The subject will be given a pencil and binder paper to write their name repeatedly for 30 seconds and then stop for 10 seconds. The subject will then be asked to draw an outwardly expanding spiral for 10 seconds. This will be repeated 3 times with 20 seconds between each test. 3. Swallow Test This test has the subject take sips of water from a paper cup. We are looking at the swallowing action, so the subject will be asked to remain still with a small amount of water in their mouth for 2 seconds before swallowing. This will be repeated 5 times with 20 seconds between tests. 4. Stand Test This test has the subject stand up. He/she will be asked to stand up for 5 seconds after being verbally prompted. We will attempt to keep all wires and other parts stationary

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since we expect noise to interfere with our signal. We will ask the subject to perform this task 5 times with 20 seconds between each test.

5. Postural Tremor Test

This test has the patient hold their dominant arm parallel to the floor and pause for 5 seconds. With their arm held out, the subject proceeds to rotate their wrist alternating between facing the hand up and down for 10 seconds. This test will be repeated 5 times with 20 seconds between each test.

6. Bradykinesia Test

This test has the subject place their arm on a table and tap their thumb to their index finger. The subject will sit at rest with their arm resting on the table. Once verbally prompted, the subject taps their thumb to their index finger 10 times at 1-second intervals using a stopwatch for assistance. This test will be repeated 5 times with 20 seconds between each test.

Once the testing is finished, the cap will be removed, which will take roughly 5 minutes. Subjects will be advised to wash out the conductive gel using water and shampoo.

Each measurement will begin with the subject at rest and continue through the duration of the exercise. A new sample is recorded for each test including repeated tests. The aim of the recordings at different conditions is to determine characteristics of the EEG while the subject is at rest, and changes that occur with typical voluntary motions or actions. These tests represent the control group, which serves as a baseline for the tasks performed. Data that will later be conducted on patients with Parkinson's Disease can be compared to this control group.

Data Interpretation-

The 32-channel EEG being used will follow the standard 10/10 electrode layout. The number of electrodes acquiring signals provides sufficient freedom to observe responses in different sections of the brain during the tests. The focus of the tests performed in the experiment procedure will be on movement related activity. The corresponding electrodes used for analysis will be primarily in the C, F and P regions of the 10/10 scheme and will vary depending on the activity performed by the subject.

The EEG manufacturer software will manage the signal acquisition from the EEG electrodes. Raw signals will be analyzed using Matlab with the EEGLAB Toolbox. The acquisition software provided by the EEG manufacturer, EEGStudio, provides filtering of common noise signals including the power frequency (50Hz). EEGStudio also provides adjustment of individual electrode sensitivity and filtering. The preprocessed data obtained from EEGStudio can then be exported to a Matlab compatible file format for extended analysis. EEG signals existing in the time domain will be converted to the frequency domain using Fast Fourier Transform techniques provided by the EEGLAB software to observe the power spectra produced by each activity. The power spectra will be observed to identify signal peaks of interest associated with each movement related activities. Subject data will then be compared to find peak frequencies common to multiple subjects. Further analysis will include spatial filtering to produce a scalp map of peak signals during the activities with the help of the EEGLAB software.

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Data for each subject will be stored anonymously using the following format: “EEG15A” to represent EEG data from subject ‘A’ taken in the year 2015. Any publication or distribution of the data will not reveal name or any identifying information about any of the subjects.

Discussion and Future Considerations- System Limitations and Challenges- Several issues arose once we received the EEG system. The first was that the amplifier only possessed a European outlet plug. We were able to solve this issue quickly, however when we realized that the Acticap had 32 electrodes with one reference and the Mitsar amplifier only had 31 channels with two references, our biggest issue started to take shape (Figure 8). Because the cap was discovered to follow a 10/10 layout instead of a 10/20 layout, the electrode labels on the cap also did not match up with the labels on the amplifier. We did our best to make sense of the product differences in order to take recordings from our first subject, but once we looked into the electrode placement a second time we realized we needed to reconfigure the montage within the software as well as the electrode order plugged into the amplifier.

Figure 8. Left: the 31-channel Mitsar EEG amplifer system (Mitsar EEG 202 32 Channel). Each electrode from the cap has a connector that should correspond and plug into one of the channels on the amplifier. Right: the electrodes

on the actiCAP and their corresponding locations (Downloads AcitCAP). Our problem originated because the labels on both systems don’t match up and the cap has more electrodes than the amplifier has channels.

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We used online literature as well as the layout charts provided with the cap to create a montage that conceptually matched the electrode placements on the scalp. This process consisted of calculating each angle for which each electrode was placed in terms of two separate angles, θ and Φ. θ being the angle of counter clockwise rotation with Cz representing the origin. Φ is the elevation of each electrode with respect to the z-axis through Cz as well (Figure 9). Through this process we were able to create a new montage to analyze data. We also replaced the A1 and A2 reference electrodes, which are usually placed on the ears, with two actively recording electrodes, which were considered to be the two mandible electrodes, TP9 and TP10. With this issue mostly solved we hoped to shift the focus of the project to testing on human subjects.

Figure 9. Shown is a representation of the reference angles, θ and Φ, which were used to correctly locate each

electrode on the acitCAP in order to create our custom montage (EMEGS).

Future Directions- As the year closes out, the main focus for this project for the future is to collect a large amount of data from human subjects. The data will then be analyzed and observed for the presence of any patterns. Looking far into the future, the EEG system and protocol could also be utilized to test subjects with Parkinson’s Disease and/or Deep Brain Stimulators.

Φ (phi)

θ (theta)

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Jirayucharoensak, Suwicha, Setha Pan-Ngum, and Pasin Israsena. “EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation.” The Scientific World Journal 2014 (2014). doi:10.1155/2014/627892. Kaplan, Richard F, Ying Wang, Kenneth A Loparo, Monica R Kelly, and Richard R Bootzin. “Performance Evaluation of an Automated Single-Channel Sleep-Wake Detection Algorithm.” Nature and Science of Sleep 6 (October 15, 2014): 113–22. doi:10.2147/NSS.S71159. Lau T., Gwin, J. and D. Ferris, "How Many Electrodes Are Really Needed for EEG-Based Mobile Brain Imaging?," Journal of Behavioral and Brain Science, Vol. 2 No. 3, 2012, pp. 387-393. doi:10.4236/jbbs.2012.23044. Leisman, Gerry, Robert Melillo, and Frederick R. “Clinical Motor and Cognitive Neurobehavioral Relationships in the Basal Ganglia.” In Basal Ganglia - An Integrative View, edited by Fernando A. Barrios. InTech, 2013. http://www.intechopen.com/books/basal-ganglia-an-integrative-view/clinical-motor- and-cognitive-neurobehavioral-relationships-in-the-basal-ganglia. Little, Simon, and Peter Brown. “The Functional Role of Beta Oscillations in Parkinson’s Disease.” Parkinsonism & Related Disorders, Proceedings of XX World Congress on Parkinson’s Disease and Related Disorders, 20, Supplement 1 (January 2014): S44–48. doi:10.1016/S1353-8020(13)70013-0. "Lobes of the Brain." MDhealth.com. 7 Jan. 2015. Web. 7 Jan 2015. <www.md-health.com>. Malmivuo, Jaakko, and Robert Plonsey. "Electroencephalography." Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields. Oxford: Oxford UP, 1995. 257-264. Print. “Mitsar EEG 202 32 Channel.” Stens Corporation. Epiphanet, 2015. Web. 9 June 2015. Motor Areas of the Brain. Digital image. StudyBlue. N.p., 02 July 2014. Web. 20 Jan. 2015. <https://www.studyblue.com/notes/note/n/neuroanatomy-1/deck/11548824>. Olejniczak, Piotr. “Neurophysiologic Basis of EEG”. American Clinical Neurophysiology Society. 20 Dec 2014. Web.3 June 2006. </www.ncbi.nlm.nih.gov>.

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Oostenveld, Robert and Peter . "The Five Percent Electrode System for High-resolution EEG and ERP Measurements". Clinical Neurophysiology. 6 Nov 2000. 112:713- 719.doi:10.1016/S1388- 2457(00)00527- 7. Oostenveld, Robert and Thom Oostendorp. “Validating the Boundary Element Method for Forward and Inverse EEG Computations in the Presence of a Hole in the Skull”. Department of Medical Physics, University of Nijmegen, Nijmegen, The Netherlands. Human Brain Mapping (Impact Factor: 6.92). 11/2002; 17(3):179-92. DOI: 10.1002/hbm.10061. Purves, Dale. "Modulation of Movement by the Basal Ganglia and Cerebellum." Neuroscience. 2nd ed. Sunderland, MA: Sinauer Associates, 1997. 20,21, 329-341. Print. Roy, A., B. Baxter, and Bin He. “High-Definition Transcranial Direct Current Stimulation Induces Both Acute and Persistent Changes in Broadband Cortical Synchronization: A Simultaneous tDCS #x2013;EEG Study.” IEEE Transactions on Biomedical Engineering 61, no. 7 (July 2014): 1967–78. doi:10.1109/TBME.2014.2311071. Selvaraj, Thomas George, Balakrishnan Ramasamy, Stanly Johnson Jeyaraj, and Easter Selvan Suviseshamuthu. “EEG Database of Seizure Disorders for Experts and Application Developers.” Clinical EEG and Neuroscience 45, no. 4 (October 1, 2014): 304–9. doi:10.1177/1550059413500960. Shields, Cameron K. “Action Potentials.” Zoo 331 Class Lecture. Science 52 Room E27, San Luis Obispo. 21 Apr. 2014. Lecture. Shields, Cameron K. "Histology of Nervous Tissue." Zoo 331 Class Lecture. Science 52 Room E27, San Luis Obispo. 16 Apr. 2014. Lecture. Shields, Cameron K. “The Synapse.” Zoo 331 Class Lecture. Science 52 Room E27, San Luis Obispo. 28 Apr. 2014. Lecture. Simkin, Deborah R., Robert W. Thatcher, and Joel Lubar. “Quantitative EEG and Neurofeedback in Children and Adolescents: Anxiety Disorders, Depressive Disorders, Comorbid Addiction and Attention- /hyperactivity Disorder, and Brain Injury.” Child and Adolescent Psychiatric Clinics of North America 23, no. 3 (July 2014): 427–64. doi:10.1016/j.chc.2014.03.001. Stastný J, Sovka P. "High-resolution Movement EEG Classification". Comput Intell Neurosci. 2007;:54925.

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Sun Y, Farzan F, Garcia dominguez L, et al. “A Novel Method for Removal of Deep Brain Stimulation Artifact from Electroencephalography”. J Neurosci Methods. 2014;237:33- 40. Taheri BA, Knight RT, Smith RL. “A Dry Electrode for EEG Recording”. Electroencephalogr Clin Neurophysiol. 1994;90(5):376-83. Temel, Yasin, Arjan Blokland, Harry W. M. Steinbusch, and Veerle Visser-Vandewalle. “The Functional Role of the Subthalamic Nucleus in Cognitive and Limbic Circuits.” Progress in Neurobiology 76, no. 6 (August 2005): 393–413. doi:10.1016/j.pneurobio.2005.09.005. Teplan, M. "FUNDAMENTALS OF EEG MEASUREMENT." MEASUREMENT SCIENCE REVIEW 2nd ser. 2 (202): n. pag. Measurement. Institute of Measurement Science, Slovak Academy of Sciences, 2002. (Dec 2014). Tsang EW, Hamani C, Moro E, et al. "Involvement of the Human Pedunculopontine Nucleus Region in Voluntary Movements". Neurology. 2010;75(11):950-9. “Types of Movement Disorders”. John Hopkins Medicine. <www.HopkinsMedicine.org>. Walker Harrison, Huang He, Gonzalez Christopher, et al. “Short Latency Activation of Cortex During Clinically Effective Subthalamic DBS for Parkinson Disease”. Movement disorders  : official journal of the Movement Disorder Society 2012;27(7):864-873. doi:10.1002/mds.25025. Weiss D, Klotz R, Govindan RB, et al. “Subthalamic Stimulation Modulates Cortical Motor Network Activity and Synchronization in Parkinson's Disease”. Brain. 2015. Whitham, Emma M. et al. “Thinking Activates EMG in Scalp Electrical Recordings”. Clinical Neurophysiology, Volume 119 , Issue 5 , 1166 - 1175.

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Appendix: IRB Forms-

Informed Consent Form INFORMED CONSENT TO PARTICIPATE IN A RESEARCH PROJECT, "Electroencephalography Measurement During Motor Tasks" Adam Aslam, Charlie Aylward, and Sara Wier, students in the Department of Biomedical Engineering at Cal Poly, San Luis Obispo, under the supervision of Dr. Kristen Cardinal, are conducting a research project studying brain signals in healthy subjects. The purpose of the study is to measure brain activity in healthy individuals performing daily motor tasks, in order to observe relationships between brain activity and movement. You are being asked to take part in this study by allowing the researchers listed above to record brain signals while you perform daily tasks such as lifting a pencil or holding your arms in certain positions. You will be asked to wear an electroencephalography (EEG) recording cap, which is placed on your head like a helmet and is connected by wires to recording equipment in order to measure brain activity. The EEG merely collects the electrical activity produced by your brain and then displays this on output devices. Conducting gel will be added between the cap and your hair or scalp to improve signal quality. Your participation will take approximately 1 to 1 ½ hours. Please be aware that you are not required to participate in this research and you may discontinue your participation at any time without penalty. The possible risks associated with participation in this study include minor discomfort due to the electrode cap or the conducting gel, and a very minor risk of low voltage electric shock due to static electricity. If you should experience any discomfort or emotional distress, please be aware that you may contact the Cal Poly Health Center at (805) 756-1211 or Cal Poly Counseling Services at (805) 756-2511 at any time for assistance. Your confidentiality will be protected by maintaining restricted access to each subject’s personal information and study data. Also, an anonymous patient identifier will be used in place of your name or any other identifying information in study documents. Your name will not be used in any reports of this research without your permission. Your participation may help contribute to an understanding of brain function. In addition, you will be offered $25 at the end of the data collection period. If you have questions regarding this study, please feel free to contact Charlie Aylward, Adam Aslam, or Sara Wier at [email protected] or at (805) 756-2675. If you have concerns regarding the manner in which the study is conducted, you may contact Dr. Steve Davis, Chair of the Cal Poly Human Subjects Committee, at (805) 756-2754,

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[email protected], or Dr. Dean Wendt, Dean of Research, at (805) 756-1508, [email protected]. If you agree to voluntarily participate in this research project as described, please indicate your agreement by signing below. Please keep one copy of this form for your reference, and thank you for your participation in this research.

____________________________________ ________________ Signature of Volunteer Date

____________________________________ ________________ Signature of Researcher Date

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HUMAN SUBJECTS PROTOCOL APPROVAL FORM Cal Poly, San Luis Obispo All Cal Poly faculty, staff, and student research with human subjects, as well as other research involving human subjects that is conducted at Cal Poly, must be reviewed by the Cal Poly Human Subjects Committee for the protection of human subjects, the researchers, and the University. Human subjects research is defined as any systematic investigation of living human subjects that is designed to develop or contribute to generalizable knowledge. While the ethical guidelines for research are applicable to classroom activities, demonstrations, and assignments, the Human Subjects Committee does not review classroom activities unless data will be collected and used in a systematic investigation. Researchers should complete all items on this approval form and submit it, along with a research protocol (containing the information detailed in Guidelines for Human Subjects Research Protocol), to the Office of Research and Economic Development (Debbie Hart, Bldg. 38, Room 154). Please feel free to attach an additional page if your responses to any of the items require more space. Your answers to the items on this form, as well as the research protocol, should be typed. The Committee will make every effort to respond to your submission within two to four weeks. Committee approval should be received prior to contacting prospective subjects and collecting data. Please read carefully Cal Poly's Policy for the Use of Human Subjects in Research prior to completing this application.

If you require assistance in completing this form, contact the Office of Research and Economic Development at (805) 756-1508.

February 4, 2015 3. Type of Research: 1.

Date: Senior project 2. Title of Research Project: Master’s thesis

Faculty research X Other:

Electroencephalography measurement during motor tasks

please explain: MEDITEC Research Project

4. Name(s) of Researcher(s) Principal Investigator: Charlie Aylward

Department or other affiliation:

Computer Engineering

Phone: (530) 774-6696 Email: [email protected]

Position:

Faculty X Student

Other: Please explain

Additional Researcher:

Adam Aslam

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Mechanical Engineering


Position:

Faculty X Student


Additional Researcher:

Sara Wier


Biomedical Engineering


Position:

Faculty X Student


Any additional researchers involved in the project should be listed with the descriptive information requested above on a separate sheet.

5. Faculty Advisor (if applicable)

Name:

Dr. Kristen Cardinal Email:

[email protected]


Biomedical Engineering Department

Phone:

(805) 756-2675

Other thesis committee members if the research is a thesis:

Name:

Email:


Phone:

Name:

Email:


Phone:

Name:

Email:


Phone:

6. Is there an external funding source for the project: X Yes, and the source St. Jude Medical and MEDITEC budget

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is:

No

7. Is this a modification of a project previously reviewed by Cal Poly’s Human Subjects Committee?

Yes, and the approximate date of the last review was:

X No

8. Estimated duration of the project: Starting date: 3/15/2015 Completion

date: 3/15/2016

9. Describe any risks (physical, psychological, social, or economic) that may be involved. See Specific Ethical Criterion #1 in Policy for the Use of Human Subjects in Research for a description of the types of risks.

1) There is a slight risk of discomfort due to wearing the EEG electrode cap and conductive gel.

2) There is a very minor risk of possible low voltage electric shock generated by the EEG measurement hardware or from static electricity.

10. Indicate what measures will be taken to minimize risks. See Specific Ethical Criterion #1 in Policy for the Use of Human Subjects in Research for a discussion of strategies for minimizing risks.

1) The EEG system safety guidelines specified by the system manual will be precisely followed.

2) EEG system setup and operation will be practiced prior to conducting research on subjects. 3) Subjects will be asked periodically about any discomfort that they are experiencing, and

measures will be taken to try to mitigate any discomfort.

11. Explain how subjects' confidentiality will be protected. See Specific Ethical Criterion #5 in Policy for the Use of Human Subjects in Research for a discussion of strategies for minimizing risks. 1) The confidentiality of the test subjects will be protected by replacing patient names with an

anonymous unique identifier consisting of a letter followed by the year that the subject participated in the study (e.g. A15, B15, etc.). Any study documents and publications will refer to patients by anonymous identifier only.

2) Although demographic information and EEG tracings may be published along with findings from the study, the identity of subjects participating in the study will not be disclosed.

3) Paper copies of research paperwork, consent forms, and data with subjects’ information will be stored in a locked cabinet.

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12. Describe any incentives for participation that will be used. See Specific Ethical Criterion #2 in Policy for the Use of Human Subjects in Research for a discussion of the use of incentives in research. Subjects who participate will be offered $25 from the MEDITEC budget to be used for purchase of a meal.

13. Will deception of subjects be involved in the research procedures? Yes* X No

*If so, explain the deception and how it will be handled. See Specific Ethical Criterion #3 in Policy for the Use of Human Subjects in Research for a discussion of the use of deception in research:

14. Type of review requested: Exempt from further review* X Expedited review Full review See Types of Review in Policy for the Use of Human Subjects in Research for a discussion of the criteria for exempt, expedited, and full reviews.

*The research protocol submitted for a project presumed to be exempt may be abbreviated but should contain sufficient information to support the conclusion that the project meets the criteria for exemption.

15. Signatures: Your signature below indicates that the information presented in this application (the approval form and research protocol) is accurate and that you have read, understand, and agree to follow the Policy for the Use of Human Subjects in Research. Name of Primary Researcher:

Charlie Aylward

Signature:

Cal Poly Faculty Advisor's Signature (Required if this is student research) I have reviewed this research proposal, which has been prepared by my advisee(s) in accordance with the Guidelines for Obtaining Human Subjects Approval. Name of Faculty Advisor: Kristen Cardinal Signature

Return to the Human Subjects Committee homepage.

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