Sleep Research

Humans and animals have been extensively studied in the field of sleep research. Studies of sleeping animals have increased our knowledge of the basic mechanisms of sleep. Research with animal models has led to the understanding of many sleep disorders and has provided new insights that can enable us to understand human sleep and to develop effective treatments for sleep disorders.

Function of Sleep
One hypothesis is that sleep serves to reverse and/or restore biochemical and physiological processes that are progressively degraded during prior wakefulness. This classical view of sleep function has prevailed over competing hypotheses, largely because it is intuitively reasonable, and especially in light of the widespread and unfavorable psychological and behavioral effects that are experienced with sleep deprivation. Consistent with the restorative theory of sleep function are the increased amounts and intensity of sleep during a period of sleep recovery after 24 hours of sleep deprivation in humans and most other mammals.

Classification of Sleep
Sleep is a resting state characterized by reduced mobility, closed eyes, a reduced response to external stimuli, a characteristic sleep posture and reversible unconscious state. Sleep is determined by physiological changes in EEG (electroencephalogram – electrical signals from the brain), EMG (electromyogram – muscle movement), EOG (electrooculogram - eye movement) – see Figure 1, and other variables including temperature, blood pressure and neuroendocrine function.

 

Figure 1: Location of EEG, EOG and EMG electrodes in humans

 

 Figure 2: Location of rat EEG and mouse EEG electrodes.

 

 

Figure 3: Location of EMG electrodes in rodents.

1. splenius capitis   2. masseter   3. obicular ocular

EEG recordings are classified into four frequency bands:

  • Delta (0.5 to 4 Hz);
  • Theta (4 to 8 Hz);
  • Alpha (8 to11.5 Hz),
  • Beta1 (11.5 to 15 Hz) and Beta2 (15 to 35 Hz).
  • Gamma (30-100+ Hz)

The above list contains the most widely used definitions of the frequency bands. However, exact band limits may differ slightly between laboratories, species or protocols.

The most common frequency bands of EEG used to characterize the sleep cycle are:

  • Alpha - the approximately 10 Hz EEG rhythm characteristic of relaxed wakefulness, but also seen, generally at a somewhat slower frequency, during REM sleep.
  • Beta - An EEG frequency of between 15 and 30 Hz
  • Delta - A slow EEG rhythm, with a frequency of 3Hz or less with high voltage. Characteristic of Quiet Sleep or, as seen in humans and primates, sleep stages 3 and 4.  Most common in the mid-brain area, or just anterior of Lambda.
  • Theta waves - EEG wave forms of 4-6 Hz, most common in the parieto-temporal (frontal – or anterior of Bregma) areas and sometimes associated with emotional activity

Common transient EEG patterns used for sleep stage identification (primarily in humans and primates)

  • K-complexes - Sharp negative high voltage EEG waves that are followed by a slower positive component. In some species, K-complexes occur spontaneously during NREM sleep. They are also seen during SWS as evoked responses to external stimuli.
  • Spindles - A rhythmical, repetitive waveform of 12-14 Hz seen against a background of mixed EEG frequencies. Associated with stage 2 sleep (or SWS) in some species.

Wake EEG is dominated by the alpha rhythm, while the remainder of the EEG is characterized by lower voltage, irregular waveforms with a mixture of frequencies.

Human sleep comprises two physiological states:

  • NREM (non rapid eye movement) sleep and
  • REM (rapid eye movement) sleep, also known as paradoxical sleep (PS)

NREM sleep consists of four stages, each of which is characterized by progressively slower brain wave patterns, with slower patterns indicating deeper sleep (sleep spindles/delta oscillations). NREM makes up about 75% of total sleep time and gives way to the first REM episode of the night, which makes up approximately 25% of total sleep time.

A few examples of the work done in animal sleep research:

  • Studies with mice and dogs have offered insights on the cause of narcolepsy--the sleeping disorder characterized by sleepiness, muscle weakness and abnormal states of rapid eye movement (REM)--affecting more than one in every 2,000 Americans. Research has uncovered a genetic mutation that causes narcolepsy in dogs and mice. These findings have led sleep researchers to suspect the disorder might have similar roots in humans, providing an important link in treating the disorder in humans.
  • Research with rats has examined the amygdala's role in insomnia. These studies attempt to trace the amygdala's role in alertness and arousal during sleep. In rats that were subjected to fear conditioning, researchers detected suppressed REM sleep during subsequent sleep cycles. Researchers have concluded that fear-inducing stimuli suppress brain activity that should happen during REM and confirmed that the amygdala's activity can affect sleep patterns.
  • Researchers studying the relationship between thermoregulation and sleep regulation using rats that were sleep-deprived at different ambient temperatures have concluded that even brief sleep deprivation has major repercussions on recovery sleep.
  • Research has confirmed that dolphins, whales, birds and some other animals sleep with half of their brain--a phenomenon known as unihemispheric sleep. While humans do not have unihemispheric sleep, it is conceivable that the intensity of sleep may vary across different brain regions. These animal findings indicate that certain sleep characteristics have an ecological basis.

Sleep Research solutions from DSI
DSI has developed robust solutions for data acquisition and analysis in chronic sleep studies. Available monitoring solutions cover small to large animal species ranging from hardwired restrained techniques to industry leading fully implantable and wireless technology.

List of measured sleep parameters (but not limited to):

1)     Onset to slow-wave

2)     Onset to paradoxical (Small Animal)

3)     Onset to REM (Large Animal)

 

Implantable Telemetry    

                                                                                                               

DSI’s PhysioTel™ implants are designed for monitoring and collecting data from conscious, freely moving laboratory animals—providing stress-free data collection while eliminating percutaneous infections. PhysioTel implants are offered in different sizes to support a variety of research models ranging from mice and rats to dogs and non-human primates. The shape of DSI implants are designed to accommodate various surgical placements including subcutaneous and intraperitoneal placement.

DSI offers a variety of implant models to help researchers optimize data collection and simplify studies within this area of research.  Table 1 lists the devices developed for Sleep research.

 

 


Table 1.  Implantable devices for Sleep research.

 


Table 2. Channel bandwidth per device type.

               

Hardwire Solutions   

DSI’s hardwire solutions are a non-invasive method offering continuous measurement (EEG, EMG, EOG, etc.) during sleep studies with small animals.  Hardwired solutions allow the use of a tether solution to monitor up to 12 EEG/EMG channels with higher input bandwidths (0.5 Hz to 1 kHz).    

A setup would include use of an electrode (researcher’s choice) which would be the interface from the contact at the brain (EEG) or muscle (EMG) to the wire.  The other end of the wire would then be connected into one of DSI’s digital signal conditioners/amplifiers and partnered with DSI’s Ponemah™ software. 

 
Software Solutions

 At the core of every physiologic monitoring system is a data acquisition and analysis platform. DSI offers complete acquisition and analysis systems designed to turn physiologic signals into useable results with video integration as an option:

Acquisition software options:

  • PonemahTM
  • Dataquest A.R.T.TM

Analysis software:

  • NeuroScoreTM assists sleep studies by the following:
    • Manual sleep scoring
    • Automated sleep scoring – Small animal
      • Scoring based on the frequency content of the EEG and presence of EMG activity and movement
      • Stages include: Paradoxical Sleep, Slow Wave Sleep (SWS-1 and SWS-2), Wake and Active Wake
      • Automated sleep scoring – Large animal
        • Based on the American Academy of Sleep Medicine standards for human sleep scoring, this algorithm uses EEG, EMG, EOG and activity data
        • Stages include REM, Non-REM (N1, N2, N3), Wake and Active Wake
      • High throughput analysis using batch processing
      • Advanced frequency analysis tools
      • Video synchronization to data
      • Reporting tools for quick and consistent summaries

 

  

Figure 2a & 2b. Representation of NeuroScore sleep analysis – Short-term and Long-term.

DSI offers a complete solution for sleep research. Each solution consists of the recommended sensors, hardware, software, and accessories for reliable, accurate data collection and analysis of data.

Shown here are common, recommended system setup diagrams for DSI’s sleep solutions.

Hardwire solution with tethered monitoring

 

Unrestrained rodent monitoring with implantable telemetry (click on this heading for the schematic to appear as a pop-up)

 

Large Animal Implantable Telemetry System using DSI’s D70 series product (click on this heading for the schematic to appear as a pop-up)

 

 

DSI Bibliography

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Authier, S., et al. "Video-electroencephalography in conscious non human primate using radiotelemetry and computerized analysis: refinement of a safety pharmacology model." Journal of Pharmacological and Toxicological Methods, 60.1 (2009): 88-93.

Crofts, H. S., et al. "Investigation of the sleep electrocorticogram of the common marmoset (Callithrix jacchus) using radiotelemetry."
Clinical Neurophysiology, 112.12 (2001): 2265-2273.

Bastlund, Jesper F., et al. "Spontaneous epileptic rats show changes in sleep architecture and hypothalamic pathology."
Epilepsia 46.6 (2005): 934-938.

Datta, Subimal, and Robert Ross MacLean. "Neurobiological mechanisms for the regulation of mammalian sleep–wake behavior: reinterpretation of historical evidence and inclusion of contemporary cellular and molecular evidence." Neuroscience & Biobehavioral Reviews, 31.5 (2007): 775-824.

Hadjimarkou MM, Benham R, Schwarz JM, Holder MK, Mong JA.  Estradiol suppresses rapid eye movement sleep and activation of sleep-active neurons in the ventrolateral preoptic area.  European Journal of Neuroscience 2008; 27: 1780-1792.

Horner RL Brooks D Kozer LF Leung E Hamrahi H Render-Teixeira CL/ Makin H Kimoff RJ Phillipson EA Sleep architecture in a canine model of obstructive sleep apnea Journal of Sleep and Sleep Disorders Research 1998; 21: 791-934

Ivarsson M, Paterson LM, Hutson PH.  Antidepressants and REM sleep in Wistar-Kyoto and Sprague-Dawley rats.  European Journal of Pharmacology 2005; 522: 63-71.

Mavanji, Vijayakumar, et al. "Elevated sleep quality and orexin receptor mRNA in obesity-resistant rats." International Journal of Obesity 34.11 (2010): 1576-1588.

Morairty SR, Hedley L, Flores J,  Martin R, Kilduff TS.  Selective 5HT2A and 5HT6 Receptor Antagonists Promote Sleep in Rats. SLEEP 2008; 31: 34-44.

Morrow JD and Opp MR. Sleep-wake behavior and responses of interleukin-6-deficient mice to sleep deprivation. Brain, Behavior and Immunity 2005; 19 1: 28-39.

Olviadoti MD, Opp MR.  Effects of I.C.V. administration of interleukin-1 on sleep and body temperature of interleukin-6-deficient mice.  Neuroscience 2008; 153: 338-348.

Tang X, Sanford LD.  Telemetric Recording of Sleep and Home Cage Activity in Mice.  SLEEP 2002; 25: 677-685.

Wisor JP, Schmidt MA, Clegern WC. Cerebral microglia mediate sleep/wake and neuroinflammatory effects of methamphetamine. Brain, Behavior, and Immunity, 25 (2011) 767–776.

Wisor, JP., Schmidt, MA & Clegern WC. "Evidence for neuroinflammatory and microglial changes in the cerebral response to sleep loss."
Sleep 34.3 (2011): 261.

Wisor, JP., Schmidt, MA & Clegern WC. "Toll-like receptor 4 is a regulator of monocyte and electroencephalographic responses to sleep loss." Sleep, 34.10 (2011): 1335.



DSI Bibliography

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