CAP Sleep Database

The Cyclic Alternating Pattern (CAP) of EEG Activity During Sleep

The Cyclic Alternating Pattern (CAP) is a periodic EEG activity occurring during NREM sleep. It is characterized by cyclic sequences of cerebral activation (phase A) followed by periods of deactivation (phase B) which separate two successive phase A periods with an interval <1 min. A phase A period and the following phase B period define a CAP cycle, and at least two CAP cycles are required to form a CAP sequence.

See CAP-sequence.jpg for an example of cyclic alternating pattern (CAP) in sleep stage 2. A CAP cycle is defined as a phase A period followed by a phase B period lasting a minute or less. Two or more adjacent CAP cycles define a CAP sequence.

Phase A periods are subdivided into three subtypes:

• Subtype A1: synchronized events with low impact on autonomic and somatomotor activities;
• Subtype A2: mixed synchronized–desynchronized EEG events with an intermediate influence on the autonomic and somatomotor activities; and
• Subtype A3: predominantly desynchronized EEG events with heavy effects on the autonomic and somatomotor activities.

A detailed description and definition of CAP is reported in [1]. For a complete review of the history and significance of CAP, see [2].

Despite being a physiological phenomenon, CAP is also a marker of sleep instability and can be correlated with several sleep-related pathologies. In fact, on one hand CAP can reflect a reaction of the sleeping brain to any endogenous or exogenous disturbance; on the other hand, the A phase of CAP has been interpreted as a kind of gate through which pathological events more easily occur [3]. Increased amounts of CAP are often observed in sleep-disordered breathing (SDB), as well as in insomnia [4], sleep movement disorders (periodic leg movements, or PLM [5], restless leg syndrome (RLS) [6], parasomnias like REM behavior disorder (RBD), and epileptic diseases such as nocturnal frontal lobe epilepsy (NFLE) [7]. Pathological amounts of CAP can also be found in hypersomnias of central origin such as narcolepsy [8].

The ratio between NREM CAP sleep and total NREM sleep (CAP-rate), and the different distributions of CAP A phases with respect to sleep stages can be measured in sleep centers to characterize such pathologies. These indexes can be valuable as measures of sleep quality, but the time needed to determine them has been an obstacle to their adoption in routine clinical practice, since visual scoring of CAP phases A for an entire night of sleep recording requires expertise and lengthy, attentive analysis. The development of software capable of increasingly accurate and efficient automated analysis of CAP is beginning to result in wider clinical use of CAP indexes for diagnosis of sleep pathologies and assessment of the efficacy of therapeutic interventions.

The CAP Sleep Database

The CAP Sleep Database is a collection of 108 polysomnographic recordings registered at the Sleep Disorders Center of the Ospedale Maggiore of Parma, Italy. The waveforms (contained in the .edf files of the database) include at least 3 EEG channels (F3 or F4, C3 or C4 and O1 or O2, referred to A1 or A2), EOG (2 channels), EMG of the submentalis muscle, bilateral anterior tibial EMG, respiration signals (airflow, abdominal and thoracic effort and SaO2) and EKG. Additional traces include EEG bipolar traces, according to the 10-20 international system (Fp1-F3, F3-C3, C3-P3, P3-O1 and/or Fp2-F4, F4-C4, C4-P4, P4-O2).

The 16 healthy subjects included in the study did not present any neurological disorders and were free of drugs affecting the central nervous system. The 92 pathological recordings include 40 recordings of patients diagnosed with NFLE, 22 affected by RBD, 10 with PLM, 9 insomniac, 5 narcoleptic, 4 affected by SDB and 2 by bruxism. The age and gender of the subjects are reported in a spreadsheet (gender-age.xlsx).

The recordings are named according to the subjects' pathology:

Annotations

Expert neurologists trained at the Sleep Center provided the scoring of the sleep macrostructure, according to the Rechtschaffen & Kales rules [9], while the CAP was detected in agreement with Terzano’s reference atlas of rules [10]. All the signals were visualized and the scorings were performed using REMlogic™ software (Embla).

The scores for each recording are provided as .txt files in REMlogic report format, and also as .st files in PhysioBank-compatible format. The .txt score files have the following fields:

• Sleep stage (W=wake, S1-S4=sleep stages, R=REM, MT=body movements)
• Body position (Left, Right, Prone, or Supine; not recorded in some subjects)
• Time of day [hh:mm:ss]
• Event (either a sleep stage (SLEEP-S0..S4, REM, MT), or a phase A of CAP)
• Duration (in seconds)
• Location (the signal(s) in which the event can be observed)

A Matlab script is provided for reading the .txt score files easily. By launching ScoringReader.m, an array containing the scoring of the macrostructure, and three arrays containing the starting time of the CAP A phases, their duration and their subtype, are generated. The hypnogram is reported as 0 for wake, 1 to 4 for the sleep stages, according to R&K rules, and 5 for REM. The Matlab function CAP.m computes, starting from these variables, the CAP time and CAP rate according to Terzano’s rules.

The .st score files can be read using the PhysioBank ATM and other software that reads PhysioBank-compatible annotation files. These files contain the same information as the .txt files; times are encoded as for other annotation files, and each annotation's aux string contains the associated event, duration, sleep stage, location, and (where available) body position.

Applications for this database

This database is intended to provide a useful number of carefully annotated examples of CAP in a representative variety of pathophysiologic contexts, for development and evaluation of automated CAP analyzers, as well as to support basic studies of the dynamics of CAP.

Several efforts have been made to develop a reliable automatic CAP-scoring algorithm [11]. Most of these methods rely on the extraction of spectral features from the EEG and on the application of machine-learning algorithms. Although all these methods achieve good results, none of them is yet applied to clinical practice since they either require some amount of clinician intervention or do not achieve a sufficient accuracy in the classification to support the clinical diagnosis. Some recordings from this database have been used for studies on features related to CAP phase A [12-16] and for training automatic CAP detection algorithms [17].

Acknowledgements

The CAP Sleep Database was contributed to PhysioNet by Professor Mario Giovanni Terzano, MD and Professor Liborio Parrino, MD. The team of sleep experts of the Sleep Disorders Center of the Ospedale Maggiore of Parma, Italy, who performed the scoring includes Andrea Grassi, MD, Fernando De Paolis, MD, Giulia Milioli, MD, Silvia Riccardi, MD, Nicoletta Azzi, BSc, and Valentina Rosso, BSc. The BIOSIP group at the Bioengineering Department of Politecnico di Milano, Italy contributed to the organization of the database and implemented the Matlab scripts.

PhysioNet also gratefully acknowledges the contributions of BIOSIP group member Sara Mariani, MSc, who coordinated the preparation of the database for public release and its documentation and related software as a PhysioNetWorks project during her visit to MIT.

Bibliography

1. MG Terzano, D Mancia, MR Salati, G Costani, A Decembrino, L Parrino. The cyclic alternating pattern as a physiologic component of normal NREM sleep. Sleep 1985;8(2):137-145.
2. L Parrino, R Ferri, O Bruni, M. G. Terzano. Cyclic alternating pattern (CAP): The marker of sleep instability. Sleep Med Rev 2012 Feb;16(1):27-45
3. L Parrino, P Halasz, CA Tassinari, MG Terzano.C CAP, epilepsy and motor events during sleep: the unifying role of arousal. Sleep Med Rev 2006 Aug;10(4):267-285.
4. MG Terzano, L Parrino, MC Spaggiari, V Palomba, M Rossi, A Smerieri. CAP variables and arousals as sleep electroencephalogram markers for primary insomnia. Clin Neurophysiol 2003 Sep;114(9):1715-1723.
5. L Parrino, M Boselli, GP Buccino, MC Spaggiari, G Di Giovanni, MG Terzano. The cyclic alternating pattern plays a gate-control on periodic limb movements during non-rapid eye movement sleep. J Clin Neurophysiol 1996 Jul;13(4):314-323.
6. W Hening. The clinical neurophysiology of the restless legs syndrome and periodic limb movements. Part I: diagnosis, assessment, and characterization. Clin Neurophysiol 2004 Sep;115(9):1965-1974.
7. T Kato, JY Montplaisir, F Guitard, BJ Sessle, JP Lund, GJ Lavigne. Evidence that experimentally induced sleep bruxism is a consequence of transient arousal. J Dent Res 2003 Apr;82(4):284-288.
8. M Zucconi, L Ferini-Strambi. NREM parasomnias: arousal disorders and differentiation from nocturnal frontal lobe epilepsy. Clin Neurophysiol 2000 Sep;111 Suppl 2:S129-S135.
9. R Poryazova, E Werth, L Parrino, MG Terzano, CL Bassetti. Cyclic alternating pattern in narcolepsy patients and healthy controls after partial and total sleep deprivation. Clin Neurophysiol 2011 Sep;122(9):1788-1793.
10. A Rechtscahffen, A. Kales. A manual of standardized terminology, techniques and scoring system for sleep stages in human subjects. National Institutes of Health, Neurological Information Network, Publication 204, 1968.
11. MG Terzano, L Parrino, A Sherieri, R Chervin, S Chokroverty, C Guilleminault, M Hirshkowitz, M Mahowald, H Moldofsky, A Rosa, R Thomas, A Walters. Atlas, rules, and recording techniques for the scoring of cyclic alternating pattern (CAP) in human sleep. Sleep Med 2001 Nov;2(6):537-553.
12. U Barcaro, E Bonanni, M Maestri, L Murri, L Parrino, MG Terzano. A general automatic method for the analysis of NREM sleep microstructure. Sleep Med 2004 Nov;5(6):567-576.
13. R Largo, C Munteanu, A Rosa. CAP event detection by wavelets and GA tuning. Proc 2005 IEEE International Workshop on Intelligent Signal Processing 2005, pp. 44-48.
14. R Ferri, O Bruni, S Miano, A Smerieri, K Spruyt, MG Terzano. Inter-rater reliability of sleep cyclic alternating pattern (CAP) scoring and validation of a new computer-assisted CAP scoring method. Clin Neurophysiol 2005 Mar;116(3):696-707.
15. S Mariani, AM Bianchi, E Manfredini, V Rosso, MO Mendez, L Parrino, M Matteucci, A Grassi, S Cerutti, MG Terzano. Automatic detection of A phases of the cyclic alternating pattern during sleep. Proc IEEE Eng Med Biol Soc 2010;5085-5088.
16. C Navona, U Barcaro, E Bonanni, F Di Martino, M Maestri, L Murri. An automatic method for the recognition and classification of the A-phases of the cyclic alternating pattern. Clin Neurophysiol 2002 Nov;113(11):1826-1831.
17. S Mariani, E Manfredini, V Rosso, MO Mendez, AM Bianchi, M Matteucci, MG Terzano, S Cerutti, L Parrino. Characterization of A phases during the Cyclic Alternating Pattern of sleep. Clin Neurophysiol 2011 Oct;122(10):2016-2024.