**1. Introduction**

Telemetry technology allows remote measurement and recording of signals such as biopotentials. This technology offers the advantage of long-term EEG recordings without causing unnecessary distress, as happens in EEG systems where implanted leads connect to the recording device through a cable. The EEG recordings can be used to detect changes in the brain activity after a traumatic event. The use of telemetry for EEG acquisition is the most reliable option in experimental studies due to the reduction of animal stress. Besides its current disadvantages, such as a reduced number of channels when compared to tethered EEG, telemetry can allow us to distinguish oscillatory brain patterns that become pathological after a neurological injury. Normal brain oscillatory synchronization can be correlated with cognitive function and behavioral state. However, abnormal brain oscillations can be caused by pathologies characterized by dysfunction of the cholinergic system and trauma, leading to epilepsy. This phenomenon is the result of abnormal hypersynchronous firing in certain neuronal populations in the brain. Although not all kinds of brain injury can induce epilepsy, the spike/wave activity present during epileptic seizures is of special relevance, because severe brain injury can, in most cases, induce epilepsy.

The combination of EEG acquired through telemetry and video is widely used for assessment of epileptic focus, to distinguish epileptic seizures from psychogenic non-epileptic seizures, reassessment for potential surgery to treat epilepsy and to study animal models. Nevertheless, the assessment of the long-term EEG changes that occur after brain injury is a challenge, because a large amount of data is accumulated. Reducing the sampling rate and/or the recording schedule is not an option since each subject may respond differently to the injury and treatment. Furthermore, seizure-like events do not occur in pre-determined periods, therefore arbitrary sampling would compromise acquisition and analysis. In order to acquire reliable results, one requires a good estimation of duration and frequency of seizures and/or the duration of sleep stages. Several studies have addressed the need for analytical tools capable of optimally performing spectral analyses and, in this chapter, we evaluate the advantages and disadvantages of some available tools. The reduction and removal of artifacts in the acquired data, spectral decomposition of the signal using fast Fourier and wavelet transforms, and batch-processing will also be discussed. We will provide a view of the role of telemetric EEG technology in neuroscience, focusing on the study of brain injury induced by chemical means. Approaches to assess long-term EEG changes, choices of acquisition parameters, and tools to analyze the EEG data will be introduced.

Use of Telemetric EEG in Brain Injury 201

classification of seizures if monitored continuously. Meierkord (1992) used video-EEG telemetry to identify frontal lobe epilepsy and differentiate it from pseudo-seizures in patients. Overall, the seizure duration was short (up to 60 sec) and inter-ictal epileptiform EEG activity was identified as well as ictal abnormalities. In a similar effort, Raymond and colleagues (1999) were able to distinguish epileptic seizures from "non-epileptic" seizures. They described that even though it is unusual, some patients may display both epileptic seizures and "non-epileptic" seizures. They combined video-EEG telemetry and MRI (not simultaneous) to help in diagnosis and, interestingly, in 12 of 14 patients, the first seizure was "non-epileptic", suggesting that long-term monitoring is necessary to avoid pitfalls in the diagnosis. Moreover, there are situations when patients do not show structural anomalies in the MRI (Scott *et al*., 1999) but the EEG reveals epileptiform patterns. In these specific cases, although the telemetric EEG does not show a clear cut identification of the epileptogenic site (due to the spatial resolution limitation), it is still a valuable tool*.* In an attempt to increase the spatial resolution of the EEG, Gross and co-workers (2000) used closely spaced electrodes to study frontal lobe epilepsy (32-64 channels) and found abnormalities that were apparent with 10-20 electrodes. Nevertheless, independent of the number of channels, it is very important to precisely evaluate the video-EEG recordings and, if necessary, review it. In a re-assessment of data collected during 17 months from 121 patients (video-EEG telemetry), Alsaadi and colleagues (2004) changed the diagnosis of 24%

**2.2 The use of EEG telemetry to study behavior and detect seizures in animal models**  Telemetry has been shown to be extremely useful in animal models, allowing approaches that could be considered non-ethical in humans. Several studies were conducted specifically to verify the efficacy of new technologies that allow miniaturization of the telemetry system. Both the study of normal physiological events such as thermoregulation, sleep and circadian cycle (Herold *et al*., 1998) and the mechanisms of different neuropathologies can be explored through the use of telemetric EEG in animal models. Dimpfel and colleagues (1988) performed the implantation of bipolar electrodes in cortical and sub-cortical structures of rats to allow long-term recording of EEG after different drug treatments, such as amitriptyline, imipramine, amitriptylinoxide, amphetamine, diazepam, haloperidol and LSD. Cotugno and co-workers (1996) described a method to surgically implant telemetry transmitters in rats and record the EEG. The transmitter is implanted in a dorsal subcutaneous pocket and two stainless steel electrodes placed in the skull are connected to the transmitter through a subcutaneous tunnel. The EEG is then collected by an antenna

Fitzgerald and colleagues (2003) adapted a method to record EEG in rats through telemetry and perform real-time fast Fourier transform. They used a Data Sciences International system (DSI; St. Paul, Minn.) to send raw EEG of rats injected with atropine, caffeine, ketamine or pentobarbarbital to an oscilloscope (DataSys 7200, Gould Instrument Systems, Valley View, Ohio) with storage, fast Fourier transform (FFT) and averaging features. Then, they calculated the relative power peaks for atropine (< or =5 Hz), caffeine (7.5 Hz) and ketamine (induced a shift from 5 to 10 Hz to < 5 Hz). Bastlund and co-workers (2004) used telemetry to record cortical EEG, EMG, and temperature for long-term monitoring (5-8 weeks) of epileptiform activity in rats injected with either pentylenetetrazole or kainic acid. Weiergräber and colleagues (2005) while studying transgenic mouse models of epilepsy and sleep disorders, used EEG recorded through telemetry playing a crucial role in the

of the patients after re-analyzing the data.

located in a receiver positioned under the animal.

#### **2. Uses of telemetry technology**

The advance of remote recording of physiological data, such as biopotentials, by radio (Holter and Generelli, 1949) was a great advancement in the field of physiology. Telemetry has been used to assess physiological measures through the recording of biopotentials of subjects in remote locations for decades (Fischler & Frei, 1963; Hambrecht *et al*, 1963; Lee *et al*, 1964; Vreeland *et al*., 1963). The aerospace industry, NASA and the former USSR used telemetry to record electrocardiogram (ECG), electroencephalogram (EEG) and electromyogram (EMG) during different missions (Akulinichev & Baevskii, 1964; Blanc, Gravier, & Geier, 1967; Caldwell & Lewis, 1995; Frostjr *et al*, 1975; Helvey *et al*, 1964) with the objective to monitor pilots/astronauts, collecting information regarding changes in physiological parameters.

The technologies for recording of biopotentials remotely have been improving in parallel with different technologies. For example, the development of the transistor made possible the design of small and relatively power-efficient circuits, allowing small devices to be implanted (Jacobson and Mackay, 1957). Kamp (1984) described the use of a miniaturized 8-channel EEG amplifier combined with a standard radio transmitter/receiver system to record long-term EEG at the patient's residence. Van der Weide and Kamp (1984) created a system to record long-term home EEG in epileptic patients using radio telemetry transmitted over a regular telephone line. Wroe and co-workers (1987) combined telemetry and recording using a standard cassette system, allowing monitoring of epileptic patients in the clinic. Peng and colleagues (2001) used a regular telephone network to send data from a 20-channel EEG system to a monitoring center where the data could be stored and analyzed. Frequency resolution is very important when acquiring EEG signals and the use of frequency modulation (FM) technology allowed a higher sampling rate. Neihart & Harrison (2004) created an FM transmitter (433 MHz) powered by an inductive link (transcutaneous) to send biopotential data to a monopole antenna. A wireless multichannel recording system was designed by Mohseni and colleagues (2005) and featured integrated circuit AC amplification, DC input stabilization, time-division-multiplexing (each signal has a "timeslot") and wireless FM transmission (0.05-6 kHz)*.* Rizk and co-workers (2007) designed and implemented a singlechip to function as a 96-channel, brain-machine interface. The interface uses bidirectional communication, sampling the signals at 31.25 kHz and digitally suiting it for transmission, fulfilling the requirements for an implantable system. However, the newest existing techniques to implement brain-computer interfaces still face problems such as gliosis surrounding the implant and biocompatibility. Visual and auditory replacements and hand and limb prosthetics could revolutionize medicine, but there is still a long way to go (Rothschild, 2010). Finally, optical technology can potentially be used to transmit local field potential data (LFP) more accurately. Wei & Ziaie (2009) accomplished it designing a system composed of a printed circuit board (2.2 x 2.2 cm) to accommodate 4 amplifiers, 16 lightemitting diodes (LED) and a CCD camera to record the signal coming from the LED at 30 frames per second allowing reconstruction of a simulated LFP.

#### **2.1 The use of EEG telemetry to detect clinical seizures in patients**

The choice of what telemetry system to use in the clinic must be made according to the physician's expectations and requirements for an EEG system. The physician will determine the level of sophistication required for their EEG system (Schomer, 2006). In any case, although controversial, the EEG can be a potential marker to help in the diagnosis and

The advance of remote recording of physiological data, such as biopotentials, by radio (Holter and Generelli, 1949) was a great advancement in the field of physiology. Telemetry has been used to assess physiological measures through the recording of biopotentials of subjects in remote locations for decades (Fischler & Frei, 1963; Hambrecht *et al*, 1963; Lee *et al*, 1964; Vreeland *et al*., 1963). The aerospace industry, NASA and the former USSR used telemetry to record electrocardiogram (ECG), electroencephalogram (EEG) and electromyogram (EMG) during different missions (Akulinichev & Baevskii, 1964; Blanc, Gravier, & Geier, 1967; Caldwell & Lewis, 1995; Frostjr *et al*, 1975; Helvey *et al*, 1964) with the objective to monitor pilots/astronauts, collecting information regarding changes in

The technologies for recording of biopotentials remotely have been improving in parallel with different technologies. For example, the development of the transistor made possible the design of small and relatively power-efficient circuits, allowing small devices to be implanted (Jacobson and Mackay, 1957). Kamp (1984) described the use of a miniaturized 8-channel EEG amplifier combined with a standard radio transmitter/receiver system to record long-term EEG at the patient's residence. Van der Weide and Kamp (1984) created a system to record long-term home EEG in epileptic patients using radio telemetry transmitted over a regular telephone line. Wroe and co-workers (1987) combined telemetry and recording using a standard cassette system, allowing monitoring of epileptic patients in the clinic. Peng and colleagues (2001) used a regular telephone network to send data from a 20-channel EEG system to a monitoring center where the data could be stored and analyzed. Frequency resolution is very important when acquiring EEG signals and the use of frequency modulation (FM) technology allowed a higher sampling rate. Neihart & Harrison (2004) created an FM transmitter (433 MHz) powered by an inductive link (transcutaneous) to send biopotential data to a monopole antenna. A wireless multichannel recording system was designed by Mohseni and colleagues (2005) and featured integrated circuit AC amplification, DC input stabilization, time-division-multiplexing (each signal has a "timeslot") and wireless FM transmission (0.05-6 kHz)*.* Rizk and co-workers (2007) designed and implemented a singlechip to function as a 96-channel, brain-machine interface. The interface uses bidirectional communication, sampling the signals at 31.25 kHz and digitally suiting it for transmission, fulfilling the requirements for an implantable system. However, the newest existing techniques to implement brain-computer interfaces still face problems such as gliosis surrounding the implant and biocompatibility. Visual and auditory replacements and hand and limb prosthetics could revolutionize medicine, but there is still a long way to go (Rothschild, 2010). Finally, optical technology can potentially be used to transmit local field potential data (LFP) more accurately. Wei & Ziaie (2009) accomplished it designing a system composed of a printed circuit board (2.2 x 2.2 cm) to accommodate 4 amplifiers, 16 lightemitting diodes (LED) and a CCD camera to record the signal coming from the LED at 30

frames per second allowing reconstruction of a simulated LFP.

**2.1 The use of EEG telemetry to detect clinical seizures in patients** 

The choice of what telemetry system to use in the clinic must be made according to the physician's expectations and requirements for an EEG system. The physician will determine the level of sophistication required for their EEG system (Schomer, 2006). In any case, although controversial, the EEG can be a potential marker to help in the diagnosis and

**2. Uses of telemetry technology** 

physiological parameters.

classification of seizures if monitored continuously. Meierkord (1992) used video-EEG telemetry to identify frontal lobe epilepsy and differentiate it from pseudo-seizures in patients. Overall, the seizure duration was short (up to 60 sec) and inter-ictal epileptiform EEG activity was identified as well as ictal abnormalities. In a similar effort, Raymond and colleagues (1999) were able to distinguish epileptic seizures from "non-epileptic" seizures. They described that even though it is unusual, some patients may display both epileptic seizures and "non-epileptic" seizures. They combined video-EEG telemetry and MRI (not simultaneous) to help in diagnosis and, interestingly, in 12 of 14 patients, the first seizure was "non-epileptic", suggesting that long-term monitoring is necessary to avoid pitfalls in the diagnosis. Moreover, there are situations when patients do not show structural anomalies in the MRI (Scott *et al*., 1999) but the EEG reveals epileptiform patterns. In these specific cases, although the telemetric EEG does not show a clear cut identification of the epileptogenic site (due to the spatial resolution limitation), it is still a valuable tool*.* In an attempt to increase the spatial resolution of the EEG, Gross and co-workers (2000) used closely spaced electrodes to study frontal lobe epilepsy (32-64 channels) and found abnormalities that were apparent with 10-20 electrodes. Nevertheless, independent of the number of channels, it is very important to precisely evaluate the video-EEG recordings and, if necessary, review it. In a re-assessment of data collected during 17 months from 121 patients (video-EEG telemetry), Alsaadi and colleagues (2004) changed the diagnosis of 24% of the patients after re-analyzing the data.

#### **2.2 The use of EEG telemetry to study behavior and detect seizures in animal models**

Telemetry has been shown to be extremely useful in animal models, allowing approaches that could be considered non-ethical in humans. Several studies were conducted specifically to verify the efficacy of new technologies that allow miniaturization of the telemetry system. Both the study of normal physiological events such as thermoregulation, sleep and circadian cycle (Herold *et al*., 1998) and the mechanisms of different neuropathologies can be explored through the use of telemetric EEG in animal models. Dimpfel and colleagues (1988) performed the implantation of bipolar electrodes in cortical and sub-cortical structures of rats to allow long-term recording of EEG after different drug treatments, such as amitriptyline, imipramine, amitriptylinoxide, amphetamine, diazepam, haloperidol and LSD. Cotugno and co-workers (1996) described a method to surgically implant telemetry transmitters in rats and record the EEG. The transmitter is implanted in a dorsal subcutaneous pocket and two stainless steel electrodes placed in the skull are connected to the transmitter through a subcutaneous tunnel. The EEG is then collected by an antenna located in a receiver positioned under the animal.

Fitzgerald and colleagues (2003) adapted a method to record EEG in rats through telemetry and perform real-time fast Fourier transform. They used a Data Sciences International system (DSI; St. Paul, Minn.) to send raw EEG of rats injected with atropine, caffeine, ketamine or pentobarbarbital to an oscilloscope (DataSys 7200, Gould Instrument Systems, Valley View, Ohio) with storage, fast Fourier transform (FFT) and averaging features. Then, they calculated the relative power peaks for atropine (< or =5 Hz), caffeine (7.5 Hz) and ketamine (induced a shift from 5 to 10 Hz to < 5 Hz). Bastlund and co-workers (2004) used telemetry to record cortical EEG, EMG, and temperature for long-term monitoring (5-8 weeks) of epileptiform activity in rats injected with either pentylenetetrazole or kainic acid. Weiergräber and colleagues (2005) while studying transgenic mouse models of epilepsy and sleep disorders, used EEG recorded through telemetry playing a crucial role in the

Use of Telemetric EEG in Brain Injury 203

frequently affected areas, including the hippocampus, amygdala, pyriform cortex, and cortex (Turski *et al*., 1983b; Carpentier *et al*., 1990; Petras, 1994; Scremin *et al*., 1998; Shih *et al*., 2003). The situation becomes critical if the seizure is sustained for a prolonged period without significant interruption or recovery. When such an event takes place, the subject is experiencing *status epilepticus* (SE) and can years later display SRS. Under these circumstances, appropriate treatment is anticonvulsant therapy and monitoring (*i.e*. continuous video-EEG) in order to try to interrupt the process of epileptogenesis.

Various types of brain oscillations can be identified during the circadian cycle. A simplification of these types is exemplified in Fig. 1. Among normal function during the circadian cycle, sleep is of great importance and, obviously, sleep scoring or staging is fundamental as a tool in understanding normal and pathological situations. Gottesmann, (1992) described seven sleep-waking stages in the rat: 1 - attentive walking with dorsal hippocampus theta; 2 - quiet waking without theta pattern; 3 - sleep with cortical slow waves of increasing amplitude; 4 - deeper sleep with cortical spindles that progressively increase in number and amplitude; 5 - pre-paradoxal sleep events with high amplitude spindles that occur in parallel with thalamic sensory transmission to cortex; 6 - paradoxical sleep (eye movements are absent); 7 - paradoxical sleep with the characteristic rapid eye movements (REM). Since manual sleep scoring is laborious and time-consuming, several attempts have been made to automate this process. Gross and co-workers (2009) designed a MATLAB toolbox to perform semi-automated sleep scoring. The system is able to distinguish the states of waking, non-REM (NREM), transition-to-REM, and REM sleep if EEG and EMG are recorded simultaneously. Methods describing details for optimal EEG acquisition calibration, electrode application, signal filtering and power spectral analysis for

The search for the substrates of normal brain oscillations and its correlation with cognitive function, neurochemistry and behavioral states has been studied for several decades. Graf & Kastin, (1984) pointed that peptides can play a role, for example, in sleep, EEG and circadian patterns. Neurons that secrete orexins (excitatory neuropeptide hormones) are likely to be very important in promoting wakefulness during the circadian cycle and in controlling the transition to REM sleep. Also, hormones, like estradiol, can decrease sleep and increase locomotion (Mong *et al*., 2003). Among the neuroanatomical areas that play a role on sleep, the locus coeruleus is very important, generating brain states such as alertness. Its activation changes the EEG activity from typical non-alert patterns to alert patterns. The locus coeruleus also has a role in attention processes by changing the sensory responses of neocortical neurons and participating in orienting responses occurring in the forebrain that are closely linked to event-related potentials (Foote *et al*., 1991). EEG studies indicated that the noradrenergic connections from the locus coeruleus excite the upper brain areas, while activation of serotonergic pathways inhibits the same areas. A population of cholinergic neurons can induce and maintain paradoxical sleep and also induce a rapid and transient elevation of alertness (Kayama and Koyama, 1998). In other words projections from the locus coeruleus work as the arousal system. The suprachiasmatic nucleus located in the hypothalamus can also modulate sleep (Dijk and Duffy, 1999). The hypothalamic ventrolateral preoptic area and pons/basal forebrain can play a role on both arousing and sleep-inducing neuronal networks. The mentioned structures could play a role as an ON/OFF switch or transition from sleep to awake state and vice-versa. During sleep, one

**3.1 Normal brain oscillatory synchronization** 

sleep research were described by Campbell (2009).

neurological characterization of various transgenic mouse models and giving valuable information about epilepsies and sleep disorders in humans. They emphasized that without restraint from tethered EEG systems, the subjects can be observed without interference in their physiology.

Williams and co-workers (2006) used a three EEG channel system (DSI; St. Paul, Minn.) to record interictal spikes and epileptiform activity in the cortex and hippocampus of rats. They studied the model of kainic acid-induced seizures and long-term telemetric EEG recording to investigate epileptogenesis. According to them, although the chance to perform prolonged recordings is a great advantage, the cost, surgical complexity and frequency resolution of the system are listed as disadvantages. Obviously, collecting the data is just the first step, and throughout the use of the same system, White and colleagues (2006) tested different algorithms to process very large EEG data files acquired over 13 days. They concluded that the quality of the EEG and the type of analysis method employed can affect the positive predictive value (PPV, or true positives divided by the sum of true positives and false positives) and sensitivity (true positives divided by the sum of true positives and false negatives). In that sense, both implantation surgery accuracy and telemetry device integrity may be very important factors.

Lapray and colleagues (2008) presented a cost-effective and reusable telemetry system to record EEG in rats. The system allows a sampling rate of 500 Hz (bi-directional) and a range of up to 3 meters. The data transmission rate is roughly 115 kbps and the receiver connected to a computer through the USB port. The software developed by the group allows the recording of simultaneous video, opening the possibility to efficiently correlate behavior and EEG patterns. Finally, the study not only of EEG, but also action potentials during normal behavior, can be benefited by telemetry. It is known that the activity of place cells is highly correlated with the animal's spatial position (O'Keefe and Speakman, 1987; O'Keefe *et al*., 1998). A very innovative system was created by Chen and co-workers (2008) that used telemetry to record brain potentials in 3D mazes to investigate the role of hippocampal place cells in rats. The wireless technology used was Bluetooth which allowed a range of 5 meters and sampling at up to 10 kHZ, drastically increasing the frequency resolution and satisfying the conditions to have single unit recordings.
