Neurophysiological assessment of brain function and maturation II. A measure of brain dysmaturity in healthy preterm neonates

ELSEVI

ER

evie

healthy

prcterm

infants.

Pediatr

IW‘7: I (,:X7-295. -_---

5X term intidnts born between 38 an pretcrm inlllnt received monthly m

0 1997 by Elsevier Science PI1 SO887-8994(96)00009-X

Inc. All rights reserved. 0 0887~8994/97/s 17.00

Qher:

Rrain

Dymlaturity

in Preterm

Neonate\

287

Table 1. Thirty-two EEC-sleep variables submitted to discrhniuant analysis EEG spectral energies (5): Total EEG energy. delta band energy. theta band energy. dpllil band energy. beta band energy:‘: EMG spectral energy ( 1) Cardiorespiratory measures ( 12): Rate. variance. mean frequency. bandwidth. spectral edge. and ratio of harmonics for both cardiac and respiratory signals Event marker observations ( IO): crying. eyes opened or closed, patting/rocking; movements-large body, small body, head. and .1 events--electrode adjustment, blood drawing facial; environme! Visually scored phasic and continuity measures (4): Arousal number and duration. REM, and total body movements ‘i: EEG

frequencies

in the delta.

theta.

alpha,

and beta ranges.

Abbreviations: EEG = electrorncephalographic EMG = elecrromyographic REMS = rapid eye movements hkilll frequency Specific !3ptXtKll measures ot physiologic Spectral edge aiglida [ 81. Ratio of harmonics I Reprinted with permission from Sleep 1996; 19: I X-25.

tal outcome 191. Neurophysiologic differences also persist into infancy between cohorts [ 101, but correlations with social/environmental factors need to be assessed in future studies.

Wilh iikc ot’ discriminunt analysi.4, active, quiet. and awake states wcrc prcdictcd by comparing 34 phyk&@c Irchaviors on Vislli~l/digitill lXC.i-slcCl9 stiiclics (‘l‘uhlc I ) IHI. Thirteen 01’ the 34 mcasurcs I9cst prcdic~lccl xtatc li~i both cohorts (Tahlc 2) [Xl, The first three mc;~rcs wcrc identical for cadi groiil9 in ;I specific hcclucncc 1ix.. I’ill9itl eye movements (REM); rcsl9iriktory ratio ol’ harmonics, which is il spectral IlltXSlII’L of respiriitory regularity; and spectral delta EEG energiesI. owever, a change in the order of significance was o erved between neonatal cohorts for the remaining IO of I3 measures (Table 2). This alteration in the order of measures that define EEC-sleep state reflects brain adaptation to conditions of prematurity and undcrscorcs our conceptual framework ot brain dysmaturity in preterm neonates. Seventeen EEG-sleep architecture and continuity measures were compared between cohorts (Table 3) I I]. Polysomnographic analyses indicated that the preterm group had longer sleep cycles with ;I greater l9crccntagc ot c per tninutc. quiet slop, t’cwtx and shortor arous~Is body movements per minute. and fewer R With quantitative digital analyses 12.71 spectral EEG energies also dis guished the neonatal cohorts; differences in spectral EG energies were reduced for the preterm group dut different EEG-sleep . and these differences were specific to the EEC

288 PEDIATRIC NEUROLOGY

Vol.

I6 No. 4

err of significance of EEG-sleep variables for the function

discrimiuant

3 3

5 6 7 8 9 IO II I2 I3

Term

Preterm at term

REM RR ratio Delta energy EEG energy EMG energy Beta energy RR variance Theta energy Alpha energy HR ratio RR HR HR variance

REM RR ratio Delta energy Beta energy HR ratio EEG energy HR HR variance EMG energy RR variance RR Theta energy Alpha energy

Both REM RR ratio Delta energy Beta energy RR variance EEG energy HR variance EMG energy HR ratio HR Theta energy Alpha energy RR

Abbreviations: EEG = electroencephalographic EMG =- electromyographic = Heart rate HR Ratio = Ratio of harmonics (a spectral measure of regularity) REM = rapid eye movements RR = Respiratory rate Reprinted with permi\
frequency bandwidth. Finally, higher spectral EEG correlations, which measure the concordance between homologous brain regions, were also observed in the preterm group 171. Autonomic behaviors also dift’ercd between cohorts during specific EEG-sleep states (Fig I ) 15,7]. Spectral c~~rdiorespirato1.y measures were less well regulated for the prcternl group at conccptic~nill term ages. Crudiac regular-

ElX~-hl~Xp

stiltc‘ ilrcllilcctWC

Mi xcd frcqucncy High VOllil~C slOW TracC alternant

Low

voltage

irrcgulilr

Indetcrminatc Waking Cycle Icnglh

(min)

Stiltl! continuity Ar~~usals Sleep liltcncy Sleep cfficicnc> Spontaneous EWhCd

Phaxic cvcntx Facc/\uch t IC,Kl Small I Alp? REM

(body

nio\ cnicnt4)

Abhrcviutions: FEG a = clcctroenccphll(~~raphic REM = Rapid eye movements

Preterm 0.974

-

0.972

-

0 970

-

0.966

-

0.966

-

0.964

i

0 962 L 0.960

/ 1

/

0.956

/

0.956

/

0.954

k

0.952

i

/

Mixed Frequency

High Voltage Slow

Trace Aitemant

Low Voltage lnegular

SLEEPSTATE

ity, for example. was less during quiet sleep. The przterm cohort also had less well-developed state-dependent changes in rectal temperature between the first and second halves of the sleep cycle [Sl. Preterm inf‘lrnts also had higher rectal temperatures than their term counterparts throughout the ultradian sleep cycle, with significant differences for average and variance of rectal temperatures during all four EEG-sleep sLates [ I 11. Therefore, despite the absence of medical illnesses, differences in EEG-sleep organization for the preterm cohort reflect adaptive strategies during brain development. Some measures were accelerated as compared with those of term infants: longer sleep cycle:;, f.ragmcntation (i-e .. lowor arousaIs and motility), higher quiet sleep pcrr*c-,ntages,and higher spectrai EEG corrclalions. which arc expcctcd fi)r older inf’anrs (Table 3). Othcl mca5urc:> wcrc dclaycd. longer periods of EEG di\continuity during quiet ~kcp. h)\Y spcclral ilIt?hii ;lllcl hCt;I E energies, higher mean cardiorcspiratory rates and rectal temperature values, and less regulated cardiorespiratory behavior during quiet sleep. which would have been expected for pretcrm neonates at younger conceptional ages (CA) before term. These seemingly contradictory expressions of neurophysiologic behavior nonetheless reflect adaptive strategies which lead to brain dysmaturity; both accelerated and delayed EEG-sleep behaviors may be expressed in the same preterm cohort.

v ort of healthy pretcrm infants. month1 ey reached conce ep behaviors betw term ages to document and 43 weeks CA /12,13J; visu analyses of EEG-sleep -cterm cohort failed to stud& for this asymptomatic document evolving brain disorders during the 8 to 10 weeks of extrauterine life in the neonatal intensive care

unit NCIJ). In a subset of these healthy the first EEG-sleep study at app demonstrated neurophysiologic with their prenatal maturational fetal sonography [ 14,151. Specific regional EEG patterns changed in brain location and neurophysiologic expression in a manner that was unique to the preterm child at increasing CA: temporal theta. positive temporal sharp waves, and sharp wave transients were all expressed differently by this preterm cohort as compared with the term group [3,4]. We also described maturational trends for specific physiologic measures which comprise EEG-sleep with increasing conceptional term ages [ 131: efore 36 weeks CA, a continuous EEG pattern became increasingly abundant, while percentage of discontinuous EEG or trace discontinue decreased. The length of neonatal sleep cycle increased from 8 to 36 minutes, with greater numbers of and more prolonged electrographic arousals with increasing CA. Decreases in mean heart and respiratory rates were evident with increasing CA. Before 36 weeks CA, spectral EEC analyses indicated increasing trends for both total spectral EEG energies and delta EEG cznergies; the former was more prominent Luring active, and the latter was more prominent during quiet for spectral alpha and beta EE observed. No changes in the spectral theta energies were apparent before 36 weeks CA. After 36 weeks CA. different t~lat~~at~~~ observed in the healthy preterm cohort. Low voltage irregular active sleep appeared after ing in percentage by a conception

cfuclions

in the avcragc heart and rcspiraiory

la0626 30 32

36 Camctsd

Age

(wksl

than 36 weeks PCA. Unlike in those of the younger preterm group, no changes were observed in the total spectral EEG energies or spectral delta EEG energies in the older preterm neonates after 36 weeks CA. Spectral theta energies now increased in abundance, while spectral alpha and beta EEG energies paradoxically decreased (Fig. 2). What is more, the spectral measure of respiratory regularity (i.e., ratio of harmonics) paradoxically decreased, which was unexpected for infants advancing to older CA. These two paradoxical trends in the maturation of two sleep behaviors for the older preterm infants are contrary to what is expected-greater spectral EEG energics at higher frequency bandwidths (i.e., alpha and beta ranges). as well as a greater regularity of cardiorespiratory behavior---should be expressed at older CA. Decreases in these spectral measures are dysmature expressions of brain function of infants who adapted to conditions of prematurity, independent of medical illnesses. Specific EEG-sleep behaviors rcprcscnt a larger inventory 01’ t~curophysiological mcasurcs for brain maturation at spcci t‘ic CA intervals. From 35 behaviors, 4 EEG-sleep mcihures that t9csl I~IU~I~~ I’unctional brain nkiluruhm wcrc xclcctcd l9y rcgrcssion analysts. One 01’ four WilS il llOlkXlVl~l2lI IllCiISlI~C, RI :M, which IX%1 l*Ul’l&YCcl hl’ilill maturation bct’orc 36 weeks CA; the other ~hrcc wcrc c~tdral IlICi\stIt*Cs.Aft~t* 36 weeks CA, oxclusivcly ccrc1JlXI nicasurcs (i.e. tOlilt spoctrul k3X.i cncrgics illltl SI9c’C@al theta. alpha, and beta EEG energies) best represented brain maturation in prctcrm nconatcs between 36 and 40 weeks CA. Similirrly. a short list of only 4 of 20 EEG-sleep measures predicted state organi/.ation at any particular CA range for prctcrm neonates at approximately 36 weeks CA 1161. Spectral theta EEG cncrgics. REM per minute. arousals per minute. and facial movements per minute predicted changes in EEG discontinuity, as an expression of prctcrm sleep state. In summary. specific EEG-sleep hchaviors best represent the highly complex processes rcsponsiblc for the expression of brain function at diffcrcnt StilgCS

porated into a ncurophysiologic index of brain dysmaturity to represent physiologic behaviors for different groups of high risk infants [ 171; we initially selected seven measures, which include spectral beta range EEG energies, spectral EEG correlation (i.e., T3C3/T4C4), spectral respiratory regularity (i.e., ratio of harmonics), sleep cycle length, arousal number, REM, and percentage of quiet sleep; these measures express either delayed or accelerated EEG-sleep behaviors as compared with those of a term cohort. In Figure 3A,B, plots locate the unique positions for a preterm infant in multidimensional space that differentiate their sleep behaviors from those of term subjects. A preterm infant’s dysmature EEG-sleep behaviors occupy different physiologic “spaces” than those of their term counterparts. One analytic procedure, Mahalanobis distance, was applied to compare multivariate normal distributions of data sets [ 171. This calculation determined a neonate’s unique dysmaturity index at a given CA; a revised dysmatbrity index will be calculated at each CA interval. based on the seven EEG-sleep behaviors obtained at that age. The use of Mahalanobis distance is geometric and avoids the cancellation that can occur with simple Fummation of values. Each infant is represented in multidimensional space by those physiologic parameters (Figure ): for term infants, the representation tends to cluster tightly around the location that depends on CA, sex, and/or race. For preterm infants, on the other hand, representation is more dispersed and probably centers around a different location. The Mahalanobis distance is the distance between the preterm child’s vector and the ccntor of the cluster of term infants with the same conceptional age. It dift’ers from the conventional Euclidunt the correlations can distance in that it takes int illlltlll~ inl’inl scores li)r lhc 11111 ,EG-Slccp measures that arc used to dcf’inc this dysmaturity index. Figure 3A.B illustrates how II gl’ciltcr number 01’mcasurcs hcttcr difl‘ercntiatcs neonatal groups. This accounting makes it a commonly used metric l’or assessing statistical differences; in particular. there is a I: I relation between the Mnhalanobis distance of a point for the mean, and the probability of observing that value, when one assumes a multivariate normal distribution. For a particular CA range, each EEG-sleep measure will contribute in a unique way to the dysmaturity index which physiologically represents the adaptive processes of the child during maturation, as expressed by EEG-sleep behaviors.

Ol‘ tlCVlJl~~~lII~llt.

An inventory of EEG-sleep measures is being investigated for the healthy pretcrm cohort which can be incor-

Three hundred twenty-two EEG-sleep studies recorded from X7 preterm and term infants until and including 7 months of age were analyzed with respect to ontogeny of sleep behaviors. Our preliminary analyses compared each of the seven EEG-sleep measures which co

-I-I-lVar

7

-I-

o.oor

+ I

0.009

I +

-‘-,----+----+----I----‘----~~~.~,-...,....,..~., 38

41

4 17

---,----,----+----t----+----,I,‘,

54

58

r,?

66

BETA 0 015

;

0.013

+

0.011

+ I

P

dysmaturity index already described; these EEG-sleep measure\; evolve in ;I ma r that is comrno children but that also distin ishes each neon& Changing trends for two spectral EEG-sleep measures, beta range EE6 energies and EEG correlations, exemplify these maturational characteristics 1IO]. Decreasing spect energies w iF observed for both te 3s (Fig ilk!, erm

with advancmg ages beyond

Scher:

Brain

Dysmsturity

in Preterm

Neonate\

291

group, specifically between 38 and 45 wl:ek! CA. The brackets in Figure 4B indicate that there is no overlap in confidence intervals (Cl) between the groups. T;lis similar decrease in spectral beta EEG energies for both preterm and term cohorts suggests that a biologic:.lly determined adaptive process exists, whether the child is reared in an intrauterine or extrauterine environment. However, a more rapid decrease in spectral beta EEG energies occurred for the preterm study group approximately between 38 and 45 weeks CA, which implies an altered rate of brain adaptation. Both neonatal groups are programmed to remodel functional neuronal aggregates during late fetal, neonatal, and early infancy periods; however, the preterm cohort has adapted to conditions of prematurity by a more accelerated process of preprogrammed brain remodelling, during the end of the neonatal period (until 1 month post-term CA). The second EEG-sleep measure, spectra! EEG correlation between the T3C31T4C4 regions L&O demonstrates both similar and dissimilar maturational characteristics between cohorts (Fig SA,B). Both neonatal groups demnen+..r.,x.,l~I~;LIIILLUI~L c.:,P.%:ciP.n..* * ,,-,.ce,l I-l-!P VL~JL~~LLU iKiCX2Siii~ tKiidS iii 3pLLLndn ecu correlations during fetal, neonatal, and early infancy periods. This increase in spectral correlations began in utero after 36 weeks CA, and continued beyond conceptional term ages. There was, however, a more rapid increase in spectral correlations approximately between 38 and 45 weeks CA for the preterm group (i.e., the CI between cohorts did not overlap during this age range, as with spectral beta EEG energies). The preterm cohort adapted to conditions of prematurity by more accelerated intercortical connections between homologous brain regions approximately 4-5 weeks post-term CA. Both decreasing spectral beta EEG energies dnd increasing spectral EEG correlations represent regressive processes in the developin g brain: an increased rate of preprogrammed brain remodelling (i.e., decreasing spectral EEG beta energies) despite an increased rate of intercortical connections (i.e., increasing spectral EEG correlations) reflect two types of adaptive processes during ontogeny. Although the same two regressive phenomena exist biologically for both preterm and term groups, the preterm cohort exhibits age-specific “brain dysmaturity”, extending from 38 to 45 weeks CA. turity in the preterm cohort is expressed as I beta energies, or a greater reduction in neuronal activities red with those of term infants during this age gher spectra! EEG correlations, on the other hand represent an acceleration in intercortical connections for the preterm cohort. as compared with those of the term group during the same a$Te range. These findings underscore the use of our preciously described dysmaturity index, which will monitor the ontogeny of each measure of EEG-sleep behavior, both individually and as part of a collective physiologic expression of state development.

292

PEDIATRIC

NE’JROLOGY

Vol.

ih No. 4

PAIR 0.325

+ I I

0.300

: I

0.275

:

0.250

I

0.22s

1 I I

0.200

I I

0.175

I +

0.150

I +

0.175

1 I

0.050

:

I I I

I

I ---+----+----+----+----+---t----~---)-~ 30

42

46

50 AGEGPP

0.3::

54

50

62

66

(WEEKS)

I i I

I 0.300

1

0.275

:

0.250

:

0.225

:

I

I I I

0.175 1 0.150

: I

0.125

I + I I

0.100

: I I

0 075 1 I

0.050 1 I ---+

---_

38

.*----+----,----+----+----+----+--C--+--

+----+----,--~-,----‘----+---l--

42

46

50

54

58

62

56

AGEGRP (WEEKS)

We recently reported that our healthy preterm cohort. de\pitc the lack of medical illnesses. had comparatively lower Bayley Mental and Motor Scales at 12 and 24 months of age before correction for prematurity 191. Age-equivalency (i.e., correction foi* prematurity) is required until age 2 years for the preterm cohort. since brain function has not yet “caught up” to that of the term cohort. Although this has been a common assulrrption of devel-

able 5. egmssion results predicting selected neonatal EEG-sleep ~tlwwe~

Bayley

Coef?‘kient F-value P-value

8

Adjusted I?

Age

12 months (n = 25) Unadjusted* No. of arousals REM Adjusted’

Beta Latency .4ge 24 months (n = 28) Unadjusted Beta SES Adjusted Beta Latency

+57.3526 + I.8454 + I ,089.3 +dU3

19.406

.oooI

.6382

.6053

6.279

.0070

.3634

.305s

+2.617.1 +O.3916

7.54 I

.0027

.3763

.3264

+ 1.351.2 -0.2272

2.635

.0915

.I741

.I080

Latency = Sleep latency to first mixed frequency * Unadjusted = No age correction for prematurity. ’ Adjusted = Age correction for prematurity.

active

sleep period.

~A&,p\+,~;nn~-.UL,“...T.

Beta = REM = SES = Reprinted

Spectral beta energies during mixed frequency sleep Spectral eye movements per minute during active sleep Socioeconomic class. with permission from Pediatr Neural 1996; I 1: 12 1

likely to experience compromised neurodevelopmental outcome, as predicted by greater degrees of EEG-sleep dysmaturity. EEG-slep? studies during i~fa~cy need to be conducted, at which time infants w 0 remain at higher risk can be documented in terms of persistent neu~o~hysio~ogic dysmaturity at older ages.

EEG sleep is an active neurologic pocess that involves many interrelated neuronal networks [ 18,191. Maturatiorr of sleep processes [20] further modif;:: the expression and function of these networks. Major maturational changes in the brain occur over a relatively short developmental timespan during the first year of life, which are expressed rofound changes in EEG-sleep organization. eep reorganization during early infancy involves reordering of sleep architecture and continuity measures ]2 1,223; discontinuity of quiet EEG sleep in the neonate (i.e., trace alternant) IS replaced by a sequence of conti uous EEG-sleep stages traditionally defined as non-RE (NREI’v¶) sleep by 2 months of a tion occurs (i.e., arousals) during as compared with interrupted e 24-h period in infants; naptimes generally cons ly two daytime nap al are evident during ates and young infants s, 30 to 70 minutes, t~~~atio~of digitally waking states also

de of 75 to 9

between homolo-

ature neona-

ications or enviro

social stresses are

similar between prete

Scher:

Brain

Dysmnturity

in Preterm

Neonates

293

sequential order of sleep cycle segments, the predominance of active sleep, and abundance of arousals, other preterm sleep behaviors may be accelerated or delayed. Yet developmental discordance or “unevenness” [ 291 among multiple physiologic behaviors also exists during sleep for premature infants, representing ontogenetic adaptation; different neuronal networks which subserve brain function respond to stress by altered maturational rates, despite the absence of a severe neonatal encephalopathy. These differences in EEG-sleep organization may persist during infancy for certain high risk infants, reflecting continued brain dysmaturity. Our recent findings of lower spectral beta EEG energies and higher spectral EEG correlations for a healthy preterm cohort to 45 weeks CA as compared with those of a term cohort are two examples of persistent brain dysmaturity [lo]. Can one assume that brain circuitry which subserves sleep also conttibutes to cognitive activities? Do dysmature neonatal tiEG-sleep behaviors then predetermine both later neurophysiologic and neurodevelopmental performance‘?

This work was supported RR00084 to MSS. Scaife

Linking Sleep Disorganization utcome in Children

PEDIATRIC

NEUROLOGY

Vol.

in part by grants Family Foundation,

NSOI I IO. NS26793. and the Twenty-five Club of

Magee-Womens Hospital. the Cradle Roll Auxiliary, Womens Hospital Research Fund. Ms. Margie Phillips

For the past 25 years, certain studies have dealt with the role of sleep in memory consolidation and cognitive/ attentional tasks [ 35,361. Physiologic processes responsible for REM and NREM behaviors during sleep play important roles in cognitive processes during the waking state. Adult animal and human populations, rather than immature subjects, however have been the focus of most of these investigations. Pediatricians clinically associate developmental stages of sleep maturation with neurodevelopmental progress in children: delays in sleep maturation have traditionally been associated with children with slower developmental progress. Combined investigations of sleep ontogeny and neurologic performance during infancy, comparing low and high risk neonatal survivors, will provide insights into the brain’s ongoin g adaptation to stress and help predict which vulnerable neonates remain at greater risk for both sleep and developmental disorders at older ages. Although severe brain disorders are expressed in a minority of neonates by severe EEG-sleep disturbances, most convalescent or asymptomatic neonates alternatively express brain dysfunction as more subtle alterations in EEG-sleep maturation dnd organization. One method to quantify brain dysfunction is use of a brain dysmaturity index, based on selected physiologic measurements which represent EEG-sleep state. We demonstrated that an asymptomatic preterm cohort expressed dysmature EEGsleep organization and maturation despite the absence of medical complications. Furthermore, for a combined cohort of healthy preterm and term infants, dysmature EEG-sleep behaviors were associated with lower developmental performances at 12 and 24 months of age. medical complications and environmental influences wi]]

194

interact with gestational maturity to alter brain function further at progressively older ages remains to be determined. Does dysmature neonatal EEG sleep influence sleep ontogeny during infancy and, if so, how does ongoing brain dysfunction at older ages interact with environmental/social influences’! Can documentation of EEG-sleep dysmaturity at older ages predict neurodevelopmental performance more accurately than neonatal physiologic assessments? Establishing such associations will greatly aid the clinician who must otherwise rely on a limited clinical repertoire of the neonate and young infant to target children with emerging static encephalopathies. EEG-sleep studies represents a neurophysiologic screening procedure by which neonates with a subclinical presentation of a static encephalopathy can be followed into infancy, at which time environmental/social factors become more influential. Earlier identification of such high risk children will allow more effective interventional strategies by both parents and professionals.

16 No. 4

tarial

and the provided

Mageesecre-

assistance.

lRefererlces [I] Scher Comparisons infants [2] parisons

MS, Steppe of EEC-sleep

DA. Dahl RE. Asthena S, Guthrie RD. measures in healthy fullterm and preterm

of matched conceptional ages. Sleep 1993: IS:342-8. Scher MS. Sun M. Steppe DA. Guthrie RD. Sclabas\i of EEG spectral

and correlation

measures

between

RJ. Cornhealthy

term

and preterm infants. Pediatr Neurol 1994; IO: IO-I-X. ]3] Scher MS, Bova JM. Dokianakis SG, Steppe DA. Positive temporal sharp waves on EEG recordings of healthy neonates: A benign of dysmuturity

pilt Cll

L’,lectloetlccpli~ll[~~r

in prcterm

infant\

at po4tconceptionaI

C’lin Ncurophy\lol

199-!:90:

]J] Scher MS, Nova JM. Dokianaki\ significance of sharp wave transient> pretcrm

and

fullterm

I994;90: I 79-85. [5] Scher MS. Sclabassi fullterm Neural

neonates. Dokianakis

preterm ]&I Sclabassi neonates

Steppe

Neurophysiol

DA,

Guthrie

RD.

1994;10:191-4.

neonates

I994;36:738-44. [7] Scher parisons

Sun M.

Clin

changes during sleep state transitions in at postconceptional term ages. Pediatr

161 Scher MS. Steppe DA, Sclabassi RJ. Cardiorespiratory preterm

ages.

SG. Steppe DA. Physiological EEG recordings of healthy

Electroencephalogr SG.

RJ. Rectal temperature and preterm neonates

on

term

173-K

at comparable

Scher

postconceptional

MS. Sun M, Steppe

of EEG-state infants

Dohianakis SG. behavior during

specific

DA. Guthrie

spectral

values

Sun M. Guthrie sleep in fullterm term

RD.

Sclabassi

in healthy

of matched conceptional ages. Sleep MS, Dokianakis SG. Sun M, Steppe

RJ. Computer

classification

of sleep

ages. Pediatr

RD. and Re\

RJ. Comfullterm

and

1994; 1747-S I, DA. Guthrie RD.

in preterm

and fullterm

at similar postconceptional term ages. Sleep 1996; I9 I X-25. er MS, Steppe DA. Bank\ 0L. Prediction of lower neurode-

velopmental performances measures. Pediatr Neurol

of healthy neonates 1996: 14: 137-44.

by neonatal

EEG-sleep

[IO] Scher MS. Steppe DA, Sun M. Sclabassi RJ. A study of brain adaptation from neonatal to infancy periods using spectral EEG-sleep analyses. Presented at the Fourth thesda, MD, June 2.1-26. 1996.

1111

Scher

MS,

Steppe

DA,

SIDS Salerno

International DG,

Beggarly

Conference. ME.

Bank\

BeDL.

Skin

and rectal

temperatures

during

EEG-sleep

neonates at matched postconceptional Annual Meeting. Washington, DC,

I121 ifcheF MS. Steppe DA. Dokianakis of phasic and continuity measures during Pediatr Res 1994;36:732-7.

Scher

[13]

MS,

Steppe

DA,

for fullterm

ages. Presented May 30. 1996.

Banks

and preterm

at the APSS

10th

SG. Guthrie RD. Maturation sleep in preterm neonates.

DL.

Guthrie

Maturational trends of EEG-sleep measures neonate. Pediatr Neurol 1995:12:314-22.

RD.

in the

Sclabassi

healthy

RJ.

pretcrm

Busby

[23]

K. Pivik

RT. Auditory

arousal

thresholds

sleepin

during

hyperkinetic children. Sleep I985;8:332-4 I. 1241 Bell MA. Fox NA. The relations between frontal brain electrical activity and cognitive development during infancy. Child Dev l992;63: 1142-63. 1251 Thatcher childhood. Brain

RW. Cyclic cortical Cogn 1992;20:24-50.

[26] Anders TF. Keener .slcepwake patterns in full-term

reorganization

during

cariy

M. Developmental course of nighttime and premature infant\ during the first year

[14] S&es MS. !vlartin J, Steppe DA. Bank5 DL. Comparative estimates of neonatal gestational maturity by electrographic and fetal ultrasonographic criteria. Pediatr Neurol 1994; I I :2 14-8.

of life. 1. Sleep 1985:8: 173-92. 1271 Ungerer JA. Sigman M. Beckwith L, Cohen SE. Parmelee AH. Sleep behavior of preterm children at three years of age. Dev Med Child

[IS] estimates

Neurol [28]

Scher MS. of neonatal

Martin J. Steppe gestational maturity

DA. Banks in neonates

DL. Comparative by EEG and fetal

sonographic

criteria. Ann Ncurol 1994;36:523. [I61 Scher MS, Dokianakis SG. Steppe DA, Bauks DL, Sclabassi JR. Computer classification of state in healthy preterm neonates. Sleep 1996; in press. [l7] Scher

MS, Steppe DA,

Banks

DL.

from EEG-sleep analysts to document prematurity. Presented at the Fourth Bethesda.

A dysmaturity

June 23-26. 1996. obson JA. Lydic R, Baghdoyan HA. WI From brain centers to sleep cycle generation: Behav Brain Sci 1986;9:37 I. [19] 32(

index

MD.

Colebras A. ed. The pi 6): i -94. Corner MA. Ontogeny

1 DJ, Drucker-Colin

R, Morrison

neurology of brain

of

Evolving neuronal

sleep.

sleep mechanisms.

A. Parmeggiani

1221

A review 105-55. Scher

Maturational Beckerman Disorders 1992:89-I

of normal MS,

and abnormal

Guthtie

R.

Krieger

findings.

and

Children.

Baltimore:

M.

and premature

Sclabassi

RJ.

early childhood. In: Respiratory Control William>

of sleep

1301

Whitney

MP.

Thoman

infants are differentially related Behav Prdiatr 1993; l4:7 I-80. [31] Be&with L, Parmelee home

environment,

EB.

Early

sleep

patterns

to later developmental AH Jr. EEG patterns

of premature

disabilities.

J Dev

of preterm

and later IQ. Child Dev 198657~777-89. JR. Lee AFS, Morelock S. The relationship

infants. between

n infant death. Ann NY Acad Sci 1988:00:62-77. FH. Alc H, McAnulty GB. Behavioral and electrophy+ nc; for gestational age effects in healthy preterm and full-term

infants

studied

two

weeks

after

expected

due date. Child

Dev

i 990:h 1: I 27 I -86.

J Clin Neurophysiol

ID. Sun

and stability

1987:20:25-38.

1992;

Mecha-

KT. The organization

states in fullterm, preterm. and small-for-gestational age infants: A comparative study. Dev Psychobiol 1985: I 8: I5 1-62. [29] Davis DH, Thoman EB. Behavioral states of premature infants: Implications for netlral and behavioral development. Dev Psychobiol

In: McGinty

PH. eds. Brain

aspects of sleep from birth through RC. Brollillette RT, Hunt CE. eds. in Infants I I.

concepts of populations.

Neurology

nisms of Sleep. New York: Raven Press. 1985. [21] Lornibroso CT. Neonatal polygraphy in full-term infants: 1985;2:

derived

brain adaptation to conditions of SIDS international Conference.

1983:X:297-304. Watt JE, Strongman

&

Wilhinh.

ler DM. Als H, Dufb FH. McAnulty GB, Liederman J. Effectiveness of individualized developmental care for low-risk preterm infants: Behavioral and electrophysiologic evidence. Pediatrics l995;96:

923-32. [Sr;] \leep

rg VS. Sleep and memory sta

1361 mans.

emery. Neurosci Biobehav de&erg VS. Sleep and memory

Neurosci

Biobehav

Scher:

Rev

Brain

I: The innuencc

of different

Rev 1992; 16:497-502. II: lnvestigatic:n\ on hu-

I992; 16:503-S.

Dysmaturity

in Preterm

Neonates

295