Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2014 Nov 1.
Published in final edited form as: J Int Neuropsychol Soc. 2013 Aug 15;19(10):1065–1075. doi: 10.1017/S1355617713000891

Hippocampal Volume and Memory and Learning Outcomes at 7 Years in Children Born Very Preterm

Cristina Omizzolo 1,2, Deanne K Thompson 1,3, Shannon E Scratch 1, Robyn Stargatt 1,2, Katherine J Lee 1,4, Jeanie Cheong 1,5,6, Gehan Roberts 1,4,5, Lex W Doyle 1,4,5,6, Peter J Anderson 1,4
PMCID: PMC3964592  NIHMSID: NIHMS570976  PMID: 23947431

Abstract

Using magnetic resonance imaging, this study compared hippocampal volume between 145 very preterm children and 34 children born full term at 7 years of age. The relationship between hippocampal volume and memory and learning impairments at 7 years was also investigated. Manual hippocampal segmentation and subsequent 3D volumetric analysis revealed reduced hippocampal volumes in very preterm children compared with term peers. However, this relationship did not remain after correcting for whole brain volume and neonatal brain abnormality. Contrary to expectations, hippocampal volume in the very preterm cohort was not related to memory and learning outcomes. Further research investigating the effects of very preterm birth on more extensive networks in the brain that support memory and learning in middle childhood is needed.

Keywords: Neonatal, Hippocampal Formation Segmentation, Memory and Learning

Introduction

Over the past 20 years there has been a steady rise in preterm birth worldwide (World Health Organization, 2012). In 2010, an estimated 14.9 million babies were born preterm (<37 weeks’ gestational age), and approximately 20% of these are born very preterm (VPT), defined as birth prior to 32 weeks’ gestational age (GA; Goldenberg, Culhane, Iams, & Romero, 2008). Many VPT children experience later cognitive (Anderson & Doyle, 2003), academic (Aarnoudse-Moens, Weisglas-Kuperus, van Goudoever & Oosterlaan, 2009) and behavioral (Bhutta, Cleves, Casey, Cradock, & Anand, 2002) problems, and up to 60% will show diffuse and focal structural brain injury (Ment, Hirtz, & Huppi, 2009; Inder, Anderson, Spencer, Wells, & Volpe, 2003). In addition to high rates of brain injury, brain growth has been reported to be delayed in VPT infants and children (Thompson et al., 2008; Taylor et al., 2011). In particular, hippocampal volume has been found to be significantly reduced in VPT children compared with their term born counterparts (Gimenez et al., 2008; Thompson et al., 2008; Nosarti et al., 2002). The hippocampi have a well-established role in memory and learning (Moscovitch & Umilta, 1990; Nadel, Samsonovich, Ryan & Moscovitvh, 2000), and children born VPT often show impairments in these domains (Omizzolo et al., 2013; Rose, Feldman, & Jankowski, 2005; Taylor, Klein, Minich, & Hack, 2000; Woodward, Edgin, Thompson, & Inder 2005). This raises the question whether there may be a relationship between reduced hippocampal volume and memory and learning impairments.

The hippocampal formations comprise a group of several related brain areas within the left and right medial temporal lobes, including the dentate gyrus, hippocampus, subiculum, presubiculum, parasubiculum and entorhinal cortex (Amaral & Lavenex, 2007). They are known to be particularly vulnerable to many of the stressors and medical complications associated with VPT birth, including infection, hypoxia-ischemia, poor nutrition, hypoglycemia, hypothyroidism, and stress hormones (Gadian et al., 2000; Isaacs et al., 2000; Sizonenko et al., 2006; Khwaja & Volpe, 2008). These complications can result in reductions in gray matter volumes (Inder, Warfield, Wang, Huppi & Volpe, 2005; Volpe, 2009), including pyramidal cell death, a slowing of neural migration (Rees, Breen, Loeliger, McCrabb & Harding, 1999) and neuronal injury (Volpe, 2001) to the hippocampi.

In vivo measurement and volumetric analyses of the brain utilizing magnetic reasonance imaging (MRI) have become key components of neuroimaging research (Konrad et al., 2009). Manual segmentation and automated measures, such as voxel-based morphometry, have been used to investigate the hippocampal formation. However, manual segmentation is still considered the gold standard (Konrad et al., 2009), as voxel-based morphometry has been reported to produce significantly larger estimates of volume (Cherbuin, Anstey, Réglade-Meslin, & Sachdev, 2009). Most studies within the VPT literature have utilized manual segmentation, and have reported reduced hippocampal volume in VPT infants (Lodygensky et al., 2008; Thompson et al., 2008), children (Isaacs et al., 2000; Lodygensky et al., 2005), and adolescents (Abernethy, Palaniappan, & Cooke, 2002; Nosarti et al., 2002). Although fewer studies have employed voxel-based morphometry, reduced hippocampal volumes in adolescents (Gimenez et al., 2008) and young adults (Lawrence et al., 2010) born VPT have also been noted using this methodology.

Positron emission tomography (PET) studies indicate that the medial-temporal lobe, particularly the hippocampi, and the prefrontal cortex are vital for learning and long-term memory function (Cabeza & Nyberg, 2000). Memory is a complex system, involving the initial registration of information into immediate memory, followed by the manipulation of this information in working memory. Material is then transferred to long-term memory using processes such as articulatory rehearsal (Baddeley, 1996) and attentional refreshment (Barrouillet & Camos, 2001), where it is stored for later retrieval. Impairments to memory and learning have been reported in VPT infants as young as twelve months of age on a paradigm involving the reproduction of action sequences and recognition of pictures (Rose et al., 2005). Deficits to immediate/working memory in older VPT cohorts (Böhm, Smedler, & Forssberg, 2004; Vicari, Caravale, Carlesimo, Casadei, & Allemand 2004; Sansavini et al., 2006) and verbal list learning in very low birth-weight children (Taylor, et al., 2000) have also been reported.

A number of studies have investigated hippocampal volume and its relationship to general intellectual abilities and neurodevelopmental outcomes in preterm populations. Reduced hippocampal volumes in VPT neonates have been associated with poorer performance on the Mental Development and Psychomotor Development Indices of the Bayley Scale of Infant Development (BSID-II) at 2 years’ corrected age (Thompson et al., 2008). In VPT children at 8 years of age, reduced hippocampal volumes have been associated with poorer full scale IQ (Lodygensky et al., 2005; Peterson et al., 2000). Moreover, left hippocampal volume reduction at 15-16 years of age has been associated with low IQ in adolescents born with very low birth weight (VLBW; <1250 g) (Abernethy et al., 2002). Isaacs and colleagues (2004) also reported a relationship between reduced hippocampal volumes and poorer Performance IQ in a cohort of adolescents born VPT and/or VLBW. In contrast, Abernethy and colleagues (2004) found little evidence for a relationship between hippocampal volumes in VPT children at 7 years and full scale IQ.

Fewer studies have specifically examined the relationship between hippocampal volume and memory and learning in those born VPT, with published reports having a narrow focus. This is surprising given evidence for the important role of the hippocampi in memory and learning (Moscovitch & Umilta, 1990; Cabeza & Nyberg, 2000; Nadel et al., 2000). While the hippocampi have typically been related to episodic long-term memory function, evidence suggests that they may also play a significant role in immediate/working memory (Olson, Page, Moore, Chatterjee, & Verfaellie, 2006; Piekema, Kessels, Mars, Petersson, & Fernandez, 2006). In the VPT population, Beauchamp et al. (2008) found that reduced neonatal hippocampal volumes were associated with poorer visual working memory on a delayed alternation task in VPT 2 year olds. Reduced hippocampal volumes in adolescents aged 13 years who were born VPT/VLBW has been associated with poorer everyday memory (Isaacs et al., 2000; 2003), and left hippocampal volume reduction in those born VPT has been reported to correlate with reduced verbal recognition memory and learning performances at age 10-18 years (Giménez et al., 2004).

In summary, research investigating the association between hippocampal volume and multiple components of memory and learning in a large, representative and contemporary VPT cohort is needed. This is especially important given the significance of these skills for academic progress and success (Bull, Epsy, & Wiebe, 2008; Hornby & Woodward, 2009; Sansavini et al., 2006), highlighting the need for early detection and intervention. Using this framework, we recently reported that VPT children performed more poorly on measures of memory and learning in both verbal and visual domains compared with term controls at 7 years of age, with approximately 30% of the VPT group performing at least 1 SD below the control group mean (Omizzolo et al., 2013). Using children from the same cohort of VPT and term children, this study aims: 1) to compare hippocampal formation volume between VPT and term controls at age 7 years, and 2) to evaluate the association between hippocampal volume and memory and learning functioning in VPT children at 7 years.

Methods

Participants

Participants were part of the Victorian Infant Brain Studies (VIBeS) cohort, a prospective, longitudinal study examining brain abnormality and development in VPT children. Recruitment occurred from July 2001 to December 2003 at the Royal Women’s Hospital in Melbourne, Australia; 224 VPT infants with either a GA of <30 weeks or a birth weight of <1250 g were recruited. Infants with severe congenital abnormalities that would impair neurological function were excluded. A concurrent control group of 46 children born full term (37 to 42 weeks’ GA) and of normal birth weight (≥2500 g) was also recruited from the Royal Women’s Hospital. An MRI brain scan was conducted on all infants without sedation, and at term equivalent age for VPT subjects. Follow-up assessment occurred at ages 2, 5 and 7 years (corrected for prematurity). At the latest follow up at 7 years of age, 198 VPT (88%) and 43 (93%) term children had a neuropsychological assessment, and 160 VPT (81%) and 36 (84%) term children had a MRI brain scan. The main reasons children did not have imaging data at age 7 years were that they were too anxious or unsettled (VPT, n = 18; term, n = 3), did not consent (VPT, n = 6, term, n = 1) or were too impaired (VPT n = 6). Neuropsychological assessments and MRI brain scans were completed over two days. Of the 160 VPT and 36 term children with scans, 145 (91%) VPT and 34 (94%) term children had scans that were suitable for analysis after scans with movement artefact were excluded.

Procedure and Measures

This study was approved by the Human Research Ethics Committees of the Royal Women’s Hospital and the Royal Children’s Hospital. Parents gave written informed consent for their child to participate. MRI scanning took place at the Children’s MRI Centre at Melbourne’s Royal Children’s Hospital with a 3 Telsa Trio Siemens MRI machine (Siemens, Erlangen, Germany). Prior to the MRI scan, each child underwent a mock MRI scanning session that was aimed to familiarise the child with the scanning procedure. Scans were conducted without sedation or anesthesia, and both T1 (0.85mm sagittal slices, flip angle = 9°, repetition time = 1900ms, echo time = 2.27ms, field of view = 210 × 210mm, matrix= 256 × 256) and T2 weighted (0.90mm sagittal slices, repetition time = 3200ms, echo time = 447ms, field of view = 240 × 215mm, matrix = 256 × 230) structural images were acquired.

Hippocampal segmentation

A single operator (C.O.) manually outlined left and right hippocampal formations in the coronal view of the T1 scan using ITK-SNAP 2.2.0 (see Figure 1), and was blinded to all perinatal data (including to which birth group the images belonged). Tracing always proceeded from the posterior to anterior sections in a sequential manner (i.e. beginning at the hippocampal tail, and followed by the hippocampal body and head). Each slice of the hippocampal formation was traced from the superiomedial edge to the lateral edge, downwards to the inferior aspect, and finally to the medial edge. In general, anatomical boundaries proposed by Watson and colleagues (1992) and Pruessner and colleagues (2000) were followed, with reference to anatomical atlases by Woolsey, Hanaway and Gado, (2003). While tracing occurred in the coronal view, reference was made to the sagittal and horizontal views in order to provide more reliable identification of structural boundaries. The dentate gyrus, four cornu ammonis regions, alveus and the fimbria were included within the hippocampal formation measurement.

Figure 1.

Figure 1

T1 image showing left (green) and right (red) hippocampal boundaries as traced on (a) the coronal plane from anterior to posterior, (b) the axial plane, (c) the sagittal plane, and (d) the 3-dimensional representation.

Boundaries of the hippocampal tail

The most posterior slice of the hippocampal tail (HT) was defined as the slice where the crus of the fornix was clearly visible surrounding the hippocampus inferiomedially to the trigone of the lateral ventricle (TLV). Consistently, the lateral border was defined as the boundary between the white matter of the fimbria and the TLV. Medially, the border was where the quadrigeminal cistern met the hippocampal sulcus. Initially, an arbitrary border was used to help define the superior border of the HT. This arbitrary border was a horizontal line from the superior border of the quadrigeminal cistern to the TLV. This was to help define and separate the HT from the fasciolar gyrus, which sits above the HT. Further anteriorly, the fimbria was used as the superior border. The border between the hippocampus and the parahippocampal gyrus provided the inferior border (an upward slant medially). Although these procedures led to some exclusion of the medial and superior sections of the HT, this method appeared to produce the most consistent approach for defining the HT.

Boundaries of the hippocampal body

The fimbria formed the superior border of the hippocampal body (HB). The lateral border of the HB was defined by the inferior horn of the lateral ventricle, and the most visible inferiolateral grey matter was included. The medial border was where the subiculum joined with the hippocampal sulcus.

Boundaries of the hippocampal head

The hippocampal head (HH) can be identified as the most anterior portion of the hippocampal formation. The first coronal slice of the HH was defined when the uncal recess appeared in the superomedial portion of the hippocampus. This formed a distinct protuberance or “hook” which was used to identify the superomedial border. The inferior border was defined by the uncus, and the border between the entorhinal cortex and the hippocampus. When the grey matter at the superior part of the hippocampal formation became interspersed with amygdala, hippocampus, and basal ganglia (putamen and globus pallidus; Pruessner et al., 2000), the fimbria was used to separate the hippocampal formation from amygdala, evident as a line of white matter intermingling with CSF. The lateral border was the border between the alveus and the temporal horn of the lateral ventricle. Further anterior, the medial edge was the most medial point of the temporal lobe. The last slice was identified as the most anterior slice where the temporal horn of the lateral ventricle was still seen laterally to the hippocampus.

Repeat segmentations to assess intra-rater reliability were conducted 1 week apart on 10 subjects. Intra-class correlation coefficients were 0.97 (p<0.01) for the right and 0.96 (p<0.01) for the left hippocampal formations. Inter-rater reliability was carried out by an experienced operator (D.K.T) on 10 subjects. Intra-class correlation coefficients were 0.96 (p<0.01) for the right hippocampus and 0.97 (p<0.01) for the left hippocampus.

Neuropsychological assessment

Children underwent extensive neuropsychological assessment as part of the 7 year follow-up. Selected measures from the test battery were used to assess IQ as well as memory and learning within the verbal and visual modalities and are outlined below.

Wechsler Abbreviation Scale of Intelligence (WASI; Wechsler, 1999)

IQ was estimated using the 4-subtest version of the WASI.

Working Memory Test Battery for Children (WMTB-C; Pickering & Gathercole, 2001)

Three subsets from the WMTB-C were administered. Forward Digit Recall was used to assess immediate verbal memory and involved each child being read a series of numbers which they were required to recall in the same order. Number sequences began at 1 digit and increased to 9 digits (or until ceiling was reached), with 6 trials per sequence. Digits were read at a rate of 1 per second. Backward Digit Recall measured verbal working memory and had a similar process, although children were required to repeat sequences in the reverse order. Block Recall assessed immediate visual memory. The examiner tapped an array of three-dimensional blocks in a sequence (also at a rate of one per second), and participants were required to tap them in the same sequence. Responses on all tasks were scored 0 or 1 for each trial, and a total score reflected the number of trials completed correctly.

California Verbal Learning Test – Children’s Version (CVLT-C; Delis, Kramer, Kaplan & Ober, 1994)

The CVLT-C (Delis et al., 1994) was used to measure verbal memory and learning. Children were read a 15-item word list (List A) and asked to immediately recall the list. This was repeated 5 times, which in total derived a learning score. Next, a second or distracter list (List B, also of 15 words) was administered, which children were also required to immediately recall, followed by a short-delay recall of List A. After a 20 to 30 minute delay, long-delay recall and recognition trials of List A were administered. Outcome measures were immediate verbal memory (number of words recalled on trial 1 of list A), verbal learning (total number of words recalled across trials 1-5), and memory after short and long delays.

Dot locations subset from the Children’s Memory Scale (Cohen, 1997)

Dot locations was used to assess visual memory and learning. Children were presented with an array of 6 dots on a 3×3 grid and required to immediately recall their spatial location. This procedure was repeated two more times, and was followed by a second (or distractor) dot array. A short-delay recall of the original dot array was then administered, which was followed by a long-delay recall 20 to 30 minutes later. Outcome measures included immediate visual memory (trial 1), visual learning (total trials 1-3), and visual memory after short and long delays.

Neonatal Brain Abnormality Score

A neonatal neurologist rated cerebral abnormality on T1 and T2 structural scans using a system described by Kidokoro, Neil, & Inder (in press), which is an adaptation of a procedure applied previously (Inder et al., 2003; Woodward, Anderson, Austin, Howard, & Inder, 2006). This scoring system rates presence and severity of white matter abnormality (cystic lesions, signal abnormality, myelination delay, callosal thinning, lateral ventricular volume, white matter volume), cortical grey matter abnormality (extracerebral space, signal abnormality, gyral maturation), deep grey matter abnormality (signal abnormality, deep grey matter volume) and cerebellar abnormality (signal abnormality, cerebellar volume) on a scale from 0 to 4. These four subscales are summed to produce a global neonatal brain abnormality score (scores ranged from 0 to 40).

Social Risk

Social risk was defined as a high score on a parent questionnaire based on family structure, language spoken at home, education of primary caregiver, occupation and employment status of primary income earner, and maternal age at birth (overall score 0-12; Roberts et al., 2008).

Statistical Analyses

Data were analyzed using Stata 12 (StataCorp, 2011). Raw scores were used to report test results, and scores were recorded as “missing” when children were too impaired to complete tasks. Linear regression was used to examine differences between birth groups (VPT and term) in left and right hippocampal volumes (measured in cubic centimetres; cc), with separate models applied to each hemisphere. Each model was fitted using generalized estimating equations (GEEs) with an exchangeable correlations structure and robust standard errors to allow for correlations between twins/triplets in the study. Subsequent analyses controlled for gender, intracranial volume (ICV), and neonatal brain abnormality score.

Linear regression was also used to determine the relationships between left and right hippocampal volumes and memory and learning outcomes in the VPT cohort. Again, models were fitted with GEEs and robust standard errors. Secondary analyses adjusted for the effects of gender, ICV, and neonatal brain abnormality score.

Results

Sample Characteristics

Sample characteristics of the VPT and term cohorts are outlined in Table 1. ICV was smaller on average in the VPT group (6.3% reduction compared with term born peers, p<.01). Groups also differed on neonatal brain abnormality score (p<0.01), IQ (p<0.01), the percentage of singletons (p<0.01) and social risk (p<0.01). In contrast, there was little difference in gender, handedness, and age at assessment between the VPT and term groups.

Table 1.

Demographic and perinatal characteristics of the sample assessed at 7 years of age for the current study.

Very Preterm sample
n* = 145
Term sample
n* = 34
GA (weeks), M (SD) 27.5(1.9) 38.9(1.3)
Age at assessment (years), M (SD) 7.5(0.2) 7.5(0.2)
Birth Weight (g) 972(222) 3277(508)
IQ, M (SD) 98.8(13.1) 109.8(12.3)
Social risk, M (SD) 2.1(1.7) 1.2(1.6)
Intracranial volume, M (SD) 1325(118) 1414(99)
Neonatal brain abnormality score, M (SD) 5.6(3.4) 1.8(1.5)
Non right-handers, % 30.9 21.7
Small for gestational age, % 9.0 2.9
Male gender, % 49.7 50.0
Singleton, % 53.1 94.1
Antenatal corticosteroids, % 87.6 0
Postnatal corticosteroids, % 4.9 0
Bronchopulmonary dysplasia, % 29.7 0
Cystic periventricular leukomalacia, % 3.5 0
Intraventricular hemorrhage grades 3/4% 3.5 0
*

Some sample sizes are less than the total sample due to missing data (social risk [very preterm = 139, term = 33]. Intracranial volume [very preterm = 144], and postnatal corticosteroids [very preterm = 144].

M = mean

SD = standard deviation

GA = gestational age

IQ = general intellectual functioning

Table 2 displays the mean group differences for the VPT and term control groups on the memory and learning measures, and illustrates the generalized memory deficits of this VPT group.

Table 2.

Mean group differences on memory and leaming outcomes at age 7 years

Adjusted for age Adjusted for age, social risk,
excluding children with IQ<70

Outcome Mean group
difference (95%CI)
p Mean group
difference (95%CI)
p
Immediate Memory
 Digits Forward −1.26(−2.84, .31) .11 −.57(−2.13, .98) .47
 Block Recall −2.86(−4.44, −1.28) <.01 −2.87(−4.40, −1.34) <.01
Working Memory
 Digits Backward −2.21(−3.47, −.96) <.01 −1.98(−3.23, −.72) <.01
 CVLT-C Trial 1 −.34(−1.10, .42) .39 −.31(−1.09, .47) .44
Memory/Leaming
 CVLT-C
  Total Trials 1-5 −3.25(−7.55, 1.05) .14 −2.57(−6.94, 1.79) .25
  Short Delay −1.25(−2.19, −.31) <.01 −1.05(−2.03, −.08) .03
  Long Delay −.87(−1.94, .21) .11 −.59(−1.66, .49) .28
 Dot Locations
  Total Trials 1-3 −1.49(−2.29, −.69) <.01 −1.11(−1.92, −.30) <.01
  Short Delay −.80(−1.08, −.52) <.01 −.74(−1.03, −.44) <.01
  Long Delay −.56(−.91, −.22) <.01 −.49(−.84, −.14) <.01

Note: lower scores reflect poorer performance in the VPT group. N ranges from 179-164 depending on the outcome.

VPT = very preterm

CVLT-C = California Verbal Learning Test – Children’s Version

CI =confidence interval

Hippocampal Volume Analysis

Table 3 shows that VPT children had reduced right (p<0.01) and left (p<0.01) hippocampal volumes compared with term controls. The VPT group displayed a reduction of 5.9% to the right hippocampus, and 6.8% to the left hippocampus relative to mean hemispheric volume in the term controls. However, the evidence for these differences reduced for the right and left hippocampi when gender, ICV, and neonatal brain abnormality were added to the model (see Table 3). The proportion of variance (R2) accounted by birth group (i.e. VPT and term) was 4.8% for right hippocampal volume and 7.2% for left hippocampal volume. R2 increased to 10.3% for the right hippocampus and 14.1% for the left hippocampus when gender was added to the model, 23.1% (right hippocampus) and 25.4% (left hippocampus) when ICV was added, and 25.4% (right hippocampus) and 26.8% (left hippocampus) when neonatal brain abnormality was added. Of interest, there was little evidence that the association between group and hippocampal volume differed between genders (interaction; left hippocampal volume p=0.81, right hippocampal volume p=0.89).

Table 3.

Associations between birth group and hippocampal volume at 7 years

Unadjusted
n = 179
Adjusted for gender, ICV,
neonatal brain abnormality
n = 117

Volume
(cc)
VPT
M(SD)
Term M(SD) b(95%CI) p b(95% CI) p
Right 3.19(0.36) 3.39(0.31) −0.19(−0.31, −0.07) <0.01 −0.001(−0.13, 0.13) 0.98
Left 3.30(0.35) 3.54(0.32) −0.24(−0.36, −0.11) <0.01 −0.07(−0.20, 0.05) 0.26

VPT = very preterm

ICV = intracranial volume

M = mean

SD = standard deviation

CI = confidence interval

b = coefficient for group from the linear regression model representing the difference in means between the VPT and term groups

Hippocampal Volume as a Predictor of Memory and Learning Outcomes in Children Born VPT

Figure 2 displays the relationship between left (a) and right (b) hippocampal volumes and performance on memory and learning outcomes in the VPT group. Unadjusted and analyses adjusted for gender, ICV and neonatal brain abnormality score showed that neither left or right hippocampal volumes were associated with performance on our memory or learning outcomes. Right and left hippocampal volumes did not predict IQ in the VPT group in unadjusted or adjusted (i.e., gender, ICV and neonatal brain abnormality score) models (see Figure 2).

Figure 2.

Figure 2

Regression coefficients and 95% confidence intervals for the association between hippocampal volume and memory and IQ measures at 7 years of age in the VPT children for (a) the left hippocampus, and (b) the right hippocampus. Estimates represent the difference in outcome are per cc change in hippocampal volume from an unadjusted analysis (dotted lines) and an analysis adjusted for gender, ICV and neonatal brain abnormality (solid lines).

Discussion

This prospective, longitudinal study investigated hippocampal volume, and memory and learning outcomes in 7 year old children born VPT. Children born VPT had smaller hippocampi compared with their term peers, but not after adjusting for gender, ICV and neonatal brain abnormality. Contrary to expectation, we found little evidence of a relationship between hippocampal volume and memory or learning outcomes within the VPT group.

Previous research has reported hippocampal volume reductions in VPT and/or VLBW cohorts when compared to term born peers in the neonatal period as well as later childhood (Gimenez et al., 2004; Isaacs et al., 2000; Isaacs et al., 2003; Nosarti et al., 2002; Peterson et al., 2000; Thompson et al., 2008). Whilst some of these studies report that hippocampal volume reductions in these children persist after adjusting for overall brain size (Isaacs et al., 2003; Gimenez et al., 2004; Nosarti et al., 2002; Peterson et al., 2000), others do not (Isaacs et al., 2000; Thompson et al., 2008). Like previous studies, our unadjusted analyses showed reduced hippocampal volumes in the VPT group, however subsequent analyses indicated that these differences were largely related to overall smaller brain size (in the case of the right hippocampus) and neonatal brain injury (in the case of the left hippocampus). For example, hippocampal volume reductions in the VPT cohort (right = 5.8%, left = 6.8%) were similar in magnitude to whole brain volume reduction (ICV = 6.3%).

Although the hippocampi resemble adult morphology at approximately 5 years of age (Insausti, Cebada-Sanchez, & Marcos, 2010), they continue to grow with further organisation, dendritic branching, and myelination into adolescence (Insausti, et al., 2010). Given this study examined hippocampal volumes in VPT children at 7 years of age, the full effects of VPT birth on normal hippocampal growth may not be apparent until later in development. In support of this argument, studies examining hippocampal volumes in older children and adolescents born VPT show larger hippocampal reductions in comparison to whole brain volume (Gimenez et al., 2004; Isaacs et al., 2003; Nosarti et al., 2002; Peterson et al., 2000). For example, Nosarti and colleagues (2002) reported a 6.0% decrease in whole brain volume in a group of VPT 15 year olds compared with term controls, but found a 15.6% and 12.1% decrease in the right and left hippocampi respectively. Furthermore, Gimenez and colleagues (2004) reported a whole brain volume reduction of approximately 8% in their cohort of VPT children and adolescents aged 10-18 years compared with term controls, but found a 16.7% and 15.5% reduction in left and right hippocampal volumes respectively.

A number of methodological factors may help explain the differences in hippocampal volumes between our study and the aforementioned studies. Nosarti et al., (2002) recruited their VPT cohort during the late 1970s and early 1980s, whereas our cohort was recruited in the early 2000s. The substantial advances in perinatal care that have occurred over the past two decades, and particularly in the 1990s (Horbar et al., 2002), might have protective effects on the hippocampi. Further, Gimenez and colleagues (2004) utilized voxel-based morphometry for hippocampal analysis, whereas our study utilized manual segmentation, which is arguably a more precise and reliable estimate (Cherbuin et al., 2009).

Previous studies have shown that reduced neonatal hippocampal volume is associated with a number of intellectual and neurodevelopmental outcomes in VPT children and adolescents. For example, neonatal hippocampal volume reductions have been linked to developmental and motor delays at 2 years of age (Thompson et al., 2008), and reduced hippocampal volumes at 8 years of age has been associated with poorer full scale IQ (Lodygensky et al., 2005; Peterson et al., 2000). In this study we found no evidence for an association between hippocampi volume and IQ. Possible explanations for this discrepancy include the younger age of children in the current study, varying measures of IQ used across studies, and differences in segmentation protocols for hippocampal formations between studies.

Additionally, previous research has linked reduced hippocampal volumes during adolescent years to everyday memory impairment (Isaacs et al. 2000; 2003), and verbal learning and recognition memory impairment (Giménez et al., 2004) in VPT cohorts. Although VPT children in our study have been found to perform poorer than term controls in IQ and memory measures (Omizzolo et al., 2013), we were unable to associate memory functioning or IQ with hippocampal volumes measured at 7 years. Thus, our findings suggest that the effects of VPT birth on memory and learning at age 7 years are not confined to hippocampal volumes alone.

The VPT brain is not a typically developing brain. A recent account of functional localization suggests that when a task is sufficiently difficult, and therefore exceeds the resources of a particular brain area, other areas will be recruited to assist with the excess workload (Just, & Varma, 2007). When the development of a particular brain structure is altered during VPT birth, such as the hippocampi, resources in this area may be reduced and additional regions recruited (Lawrence et al., 2010). This theoretical account may explain why hippocampal volume itself was insufficient to explain memory and learning deficits in our VPT cohort, and suggests the involvement of more complex networks and neural systems.

The hippocampal formations have extensive connections across multiple brain regions (Rolls, 2000; Thierry, Gioanni, Degenetais, & Glowinski, 2000). Studies investigating neural networks underlying memory and learning highlight the important role of the prefrontal and parietal cortices (Cabeza & Nyberg, 2000), and show hippocampal-prefrontal interactions (Hasselmo, & Sarter, 2011). For example, the right anterior hippocampus and the right dorsolateral prefrontal cortex have been implicated with successful verbal memory processing in adults (Johnson, Saykin, Flashman, McAllister, & Sparling, 2001). Furthermore, prefrontal regions have been associated with general cognitive ability and memory in VPT children (Woodward et al., 2005). Early damage to the hippocampi associated with VPT birth, such as neonatal brain injury and the effects of corticosteroids, may secondarily influence memory and learning abilities by disrupting the underlying neural and functional circuitry of these areas.

The current study has a number of strengths. First, measures that assess multiple components of memory and learning were utilized to investigate the relationship with hippocampal volume in childhood. This contrasts previous literature that reports a limited number of neuropsychological measures. Second, each child participated in a mock MRI scan which exposed them to the scanning environment to ensure best quality images. Finally, our study was the first to have neonatal brain imaging in a VPT cohort, and therefore, allowed us to control for the effect of early neonatal brain abnormalities on later outcome.

While the current study provides insight into the integrity of the hippocampal formations following VPT birth, one methodological limitation remains to be addressed. Although manual tracing is considered the gold standard in measuring hippocampal volume (Konrad et al., 2009), it is prone to human error, especially when defining the boundaries of the hippocampal and entorhinal regions and the borders between the hippocampus and amygdala (Konrad et al., 2009). Furthermore, there are a large number of different anatomical protocols for delineating the hippocampal formation, which provide a possible source of variance and inconsistency in findings between studies and conditions (Geuze, Vermetten, & Bremner, 2005; Konrad et al., 2009; Van Leemput et al., 2009). In the current study, however, there was excellent intra-observer and inter-observer agreement in measurement of hippocampal volumes.

In conclusion, findings from this study demonstrate that hippocampal volume alone does not give sufficient insight into the role that this vital region plays in memory and learning in children born VPT at 7 years of age. Future research might examine whether particular regions of the hippocampus are more affected by VPT birth, and whether specific regions are more strongly associated with memory and learning outcomes. Research investigating the neural substrates and networks which foster memory and learning in this population are also needed, ideally using techniques such as tractography. Establishing the functional consequences of altered hippocampal development will help us understand and identify at-risk children early in their development.

Acknowledgements

We would like to acknowledge the input of the entire VIBeS research team, and all the families who participated in this study. This study was funded by Australia’s National Health & Medical Research Council (Project Grants (237117 & 491209), Early Career Award (1012236 to D.T.), Senior Research Fellowship (628371 to P.A.)), National Institutes of Health (HD058056), and the Victorian Government’s Operational Infrastructure Support Program. The information in this manuscript and the manuscript itself has never been published either electronically or in print, and there are no conflicts of interest.

Abbreviations

VPT

Very preterm

GA

Gestational age

References

  1. Aarnoudse-Moens CSH, Weisglas-Kuperus N, van Goudoever JB, Oosterlaan J. Meta-analysis of neurobehavioral outcomes in very preterm and/or very low birth weight children. Pediatrics. 2009;124(2):717–728. doi: 10.1542/peds.2008-2816. [DOI] [PubMed] [Google Scholar]
  2. Abernethy LJ, Cooke RWI, Foulder-Hughes L. Caudate and hippocampal volumes, intelligence, and motor impairment in 7-year-old children who were born preterm. Pediatric Research. 2004;55(5):884–893. doi: 10.1203/01.PDR.0000117843.21534.49. [DOI] [PubMed] [Google Scholar]
  3. Abernethy LJ, Palaniappan M, Cooke RW. Quantitative magnetic resonance imaging of the brain in survivors of very low birthweight. Achieves of Disease in Childhood. 2002;87:279–283. doi: 10.1136/adc.87.4.279. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Amaral D, Lavenex P. Hippocampal Neuroanatomy. In: Anderson P, Morris R, Amaral D, Bliss T, O’Keefe J, editors. The Hippocampus Book. Oxford University Press, Inc.; New York: 2007. 2007. pp. 37–114. [Google Scholar]
  5. Anderson PJ, Doyle LW. Neurobehavioral outcomes of school-age children born extremely low birth weight or very preterm in the 1990s. Journal of the American Medical Association. 2003;289(24):3264–3272. doi: 10.1001/jama.289.24.3264. [DOI] [PubMed] [Google Scholar]
  6. >Baddeley AD. The fractionation of working memory. Proceedings of the National Academy of Sciences. 1996;93:13468–13472. doi: 10.1073/pnas.93.24.13468. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Barrouillet P, Camos V. Developmental increase in working memory span: Resource sharing or temporal decay? Journal of Memory and Language. 2001;45:1–20. [Google Scholar]
  8. Beauchamp MH, Thompson DK, Howard K, Doyle LW, Egan GF, Inder TE, Anderson PF. Preterm infant hippocampal volumes correlate with later working memory deficits. Brain. 2008;131:2986–2994. doi: 10.1093/brain/awn227. [DOI] [PubMed] [Google Scholar]
  9. Bhutta AT, Cleves MA, Casey PH, Cradock MM, Anand KJ. Cognitive and behavioural outcomes of school-ages children who were born preterm: A meta-analysis. Journal of the American Medical Association. 2002;288(6):728–737. doi: 10.1001/jama.288.6.728. [DOI] [PubMed] [Google Scholar]
  10. Böhm B, Smedler AC, Forssberg H. Impulse control, working memory and other executive functions in preterm children when starting school. Acta Paediatrica. 2004;93:1363–1371. doi: 10.1080/08035250410021379. [DOI] [PubMed] [Google Scholar]
  11. Bull R, Espy KA, Wiebe SA. Short-term memory, working memory, and executive functioning in pre-schoolers: Longitudinal predictors of mathematical achievement at age 7 years. Developmental Neuropsychology. 2008;33(3):205–228. doi: 10.1080/87565640801982312. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Cabeza R, Nyberg L. Imaging cognition: An empirical review of PET studies with normal subjects. Journal of Cognitive Neuroscience. 2000;9:1–26. doi: 10.1162/jocn.1997.9.1.1. [DOI] [PubMed] [Google Scholar]
  13. Cherbuin N, Anstey KJ, Réglade-Meslin C, Sachdev PS. In vivo hippocampal measurement and memory: A comparison of manual tracing and automated segmentation in a large community-based sample. Plos One. 2009;4(4):e5265. doi: 10.1371/journal.pone.0005265. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Cohen MJ. Children’s Memory Scale. The Psychological Corporation; San Antonio: 1997. [Google Scholar]
  15. Delis DC, Kramer JH, Kaplan E, Ober BA. California Verbal Learning Test – Children’s Version (CVLT-C) Harcourt Assessment. 1994 [Google Scholar]
  16. Gadian DG, Aicardi J, Watkins KE, Porter DA, Mishkin M, Vargha-Khadem F. Developmental amnesia associated with early hypoxic-ischaemic injury. Brain. 2000;123:499–507. doi: 10.1093/brain/123.3.499. [DOI] [PubMed] [Google Scholar]
  17. Geuze E, Vermetten E, Bremner JD. MR-based in vivo hippocampal volumetrics: Review of methodologies currently employed. Molecular Psychiatry. 2005;10:147–159. doi: 10.1038/sj.mp.4001580. [DOI] [PubMed] [Google Scholar]
  18. Gimenéz M, Junqúe C, Narberhaus A, Caldú X, Salgago-Pineda P, Bargalló N, Botet F. Hippocampal gray matter reduction associates with memory deficits in adolescents with history of prematurely. Neuroimage. 2004;23:869–877. doi: 10.1016/j.neuroimage.2004.07.029. [DOI] [PubMed] [Google Scholar]
  19. Gimenez M, Soria-Pastor S, Junque C, Caldu X, Narberhaus A, Botet, Mercader JM. Proton magnetic resonance spectroscopy reveals medial temporal metabolic abnormalities in adolescnets with history of preterm birth. Pediatric Research. 2008;64(5):572–577. doi: 10.1203/PDR.0b013e3181841eab. [DOI] [PubMed] [Google Scholar]
  20. Goldenberg RL, Culhane JF, Iams JD, Romero R. Preterm birth 1: Epidemiology and causes of preterm birth. The Lancet. 2008;371(9606):75–84. doi: 10.1016/S0140-6736(08)60074-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Hasselmo ME, Sarter M. Modes and models of forebrain cholinergic neuromodulation of cognition. Neuropsychopharmacology. 2011;36(1):52–73. doi: 10.1038/npp.2010.104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Horbar JD, Badger GL, Carpenter JH, Fanaroff AA, Kilpatrick S, LaCorte M, Soll RF. Trends in mortality and morbidity for very low birth weight infants, 1991-1999. Pediatrics. 2002;10(1):143–151. doi: 10.1542/peds.110.1.143. [DOI] [PubMed] [Google Scholar]
  23. Hornby G, Woodward LJ. Educational needs of school-aged children born very and extremely preterm: A review. Educational Psychology Review. 2009;21:247–266. [Google Scholar]
  24. Inder TE, Anderson NJ, Spencer C, Wells S, Volpe JJ. White matter injury in the premature infant: A comparison between serial cranial sonographic and MR findings at term. American Journal of Neuroradiology. 2003;24(5):805–809. [PMC free article] [PubMed] [Google Scholar]
  25. Inder TE, Warfield SK, Wang H, Huppi PS, Volpe JJ. Abnormal cerebral structure is present at term in premature infants. Pediatrics. 2005;115(2):286–294. doi: 10.1542/peds.2004-0326. [DOI] [PubMed] [Google Scholar]
  26. Insausti R, Cebada-Sanchez S, Marcos P. Postnatal Development of the Human Hippocampal Formation. Springer; Heidelberg: 2010. 2010. [PubMed] [Google Scholar]
  27. Isaacs EB, Edmonds CJ, Chong WK, Lucas A, Morley R, Gadian DG. Brian morphometry and IQ measurements in preterm children. Brain. 2004;127:2595–2607. doi: 10.1093/brain/awh300. [DOI] [PubMed] [Google Scholar]
  28. Isaacs EB, Lucus A, Chong WK, Wood SJ, Johnson CL, Marshall, Gadian DG. Hippocampal volume and everyday memory in children of very low birth weight. Pediatric Research. 2000;47(6):713–720. doi: 10.1203/00006450-200006000-00006. [DOI] [PubMed] [Google Scholar]
  29. Isaacs EB, Vargha-Khadem F, Watkins KE, Lucas A, Mishkin M, Gadian DG. Developmental amnesia and its relationship to degree of hippocampal atrophy. Proceedings of the National Academy of Sciences. 2003;100(22):13060–13063. doi: 10.1073/pnas.1233825100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Johnson SC, Saykin AJ, Flashman LA, McAllister TW, Sparling MB. Brain activation on fMRI and verbal memory ability: Functional neuroanatomic correlates of CVLT performance. Journal of International Neuropsychological Society. 2001;7(1):55–62. doi: 10.1017/s135561770171106x. [DOI] [PubMed] [Google Scholar]
  31. Just MA, Varma S. The organization of thinking: What functional brain imaging reveals about the neuroarchitecture of complex cognition. Cognitive, Affective and Behavioral Neuroscience. 2007;7(3):153–191. doi: 10.3758/cabn.7.3.153. [DOI] [PubMed] [Google Scholar]
  32. Khwaja O, Volpe JJ. Pathogenesis of cerebral white matter injury of prematurity. Archives of Disease in Childhood. Fetal and Neonatal Edition. 2008;93(2):153–161. doi: 10.1136/adc.2006.108837. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Kidokoro H, Neil J, Inder T. A new assessment tool for brain abnormalities in very preterm infants on term MRI. American Journal of Neuroradiology. doi: 10.3174/ajnr.A3521. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Konrad C, Ukas T, Nebel. C, Arolt V, Toga AW, Narr KL. Defining the human hippocampus in cerebral magnetic resonance images – an overview of current segmentation protocols. Neuroimage. 2009;47:1185–1195. doi: 10.1016/j.neuroimage.2009.05.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Lawrence EJ, McGuire PK, Allin M, Walshe M, Giampietro V, Murray RM. The very preterm brain in young adulthood: The neural correlates of verbal paired associate learning. The Journal of Pediatrics. 2010;156:889–895. doi: 10.1016/j.jpeds.2010.01.017. [DOI] [PubMed] [Google Scholar]
  36. Lodygensky GA, Seghier ML, Warfield SK, Tolsa CB, Sizonenko S, Lazeyras F, Hüppi PS. Intrauterine growth restriction affects the preterm infant’s hippocampus. Pediatric Research. 2008;63(1):438–443. doi: 10.1203/PDR.0b013e318165c005. [DOI] [PubMed] [Google Scholar]
  37. Lodygensky GA, Rademaker K, Zimine S, Gex-Fabry M, Lieftink AF, Lazeyras F, Huppi PS. Structural and functional brain development after hydrocortisone treatment for neonatal chronic lung disease. Pediatrics. 2005;116(1):1–7. doi: 10.1542/peds.2004-1275. [DOI] [PubMed] [Google Scholar]
  38. Ment LR, Hirtz D, Huppi PS. Imaging biomarkers of out-come in the developing preterm brain. The Lancet Neurology. 2009;1:1042–1055. doi: 10.1016/S1474-4422(09)70257-1. [DOI] [PubMed] [Google Scholar]
  39. Moscovitch M, Umilta C. Modularity and neuropsychology: Modules and central processes in attention and memory. In: Schwartz MF, editor. Modular Deficits in Alzheimer’s Disease. MIT Press/Bradford; Cambridge, Mass: 1990. [Google Scholar]
  40. Nadel L, Samsonovitch A, Ryan L, Moscovitch M. Multiple trace theory of human memory: Computational, neuroimaging, and neuropsychological results. Hippocampus. 2000;10:352–268. doi: 10.1002/1098-1063(2000)10:4<352::AID-HIPO2>3.0.CO;2-D. [DOI] [PubMed] [Google Scholar]
  41. Nosarti C, Al-Asady MHS, Frangou S, Stewart AL, Rifkin L, Murray RM. Adolescents who were born very preterm have decreased brain volumes. Brain. 2002;125:1616–1623. doi: 10.1093/brain/awf157. [DOI] [PubMed] [Google Scholar]
  42. Olson IR, Page K, Moore KS, Chatterjee A, Verfaellie M. Working memory for conjunctions relies on the medial temporal lobe. The Journal of Neuroscience. 2006;26:4596–4601. doi: 10.1523/JNEUROSCI.1923-05.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Omizzolo C, Scratch SE, Stargatt R, Kidokoro H, Thompson DK, Lee K, Anderson PF. Neonatal brain abnormalities and memory and learning outcomes at 7 years in children born very preterm. Memory. 2013 doi: 10.1080/09658211.2013.809765. DOI:10.1080/ 09658211.2013.809765. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Peterson BS, Vohr B, Staib LH, Cannistraci CJ, Dolberg A, Schneider KC, Ment LR. Regional brain volume abnormalities and long-term cognitive outcome in preterm infants. Journal of the American Medical Association. 2000;284(15):1939–1947. doi: 10.1001/jama.284.15.1939. [DOI] [PubMed] [Google Scholar]
  45. Pickering S, Gathercole S. Working memory Test Battery for Children – Manual. The Psychological Corporation; London: 2001. [Google Scholar]
  46. Piekema C, Kessels RP, Mars RB, Petersson KM, Fernandez G. The right hippocampus participates in short-term memory maintenance of object-location associations. Neuroimage. 2006;33:374–382. doi: 10.1016/j.neuroimage.2006.06.035. [DOI] [PubMed] [Google Scholar]
  47. Pruessner JC, Li LM, Serles W, Pruessner M, Collins DL, Kabani K, Evans AC. Volumetry of hippocampus and amygdala with high-resolution MRI and three-dimensional analysis software: minimizing the discrepancies between laboratories. Cerebral Cortex. 2000;10:433–442. doi: 10.1093/cercor/10.4.433. [DOI] [PubMed] [Google Scholar]
  48. Rees S, Breen S, Loeliger M, McCrabb G, Harding R. Hypoxemia near mid-gestation has long-term effects on fetal brain development. Journal of Neuropathology & Experimental Neurology. 1999;58:932–945. doi: 10.1097/00005072-199909000-00004. [DOI] [PubMed] [Google Scholar]
  49. Roberts G, Howard K, Spittle AJ, Brown NC, Anderson PJ, Doyle LW. Rates of early intervention services in very preterm children with developmental disabilities at age 2 years. Journal of Paediatrics and Child Health. 2008;44:276–280. doi: 10.1111/j.1440-1754.2007.01251.x. [DOI] [PubMed] [Google Scholar]
  50. Rolls ET. Hippocampo-cortical and cortico-cortical backprojections. Hippocampus. 2002;10:380–388. doi: 10.1002/1098-1063(2000)10:4<380::AID-HIPO4>3.0.CO;2-0. [DOI] [PubMed] [Google Scholar]
  51. Rose SA, Feldman JF, Jankowski JJ. Recall memory in the first three years of life: A longitudinal study of preterm and term children. Developmental Medicine & Child Neurology. 2005;47(10):653–659. doi: 10.1017/S0012162205001349. [DOI] [PubMed] [Google Scholar]
  52. Sansavini A, Guarini A, Alessandroni R, Faldella G, Giovanelli G, Salviolo G. Are early grammatical and phonological working memory abilities affected by preterm birth? Journal of Communication Disorders. 2006;40:239–256. doi: 10.1016/j.jcomdis.2006.06.009. [DOI] [PubMed] [Google Scholar]
  53. Sizonenko SV, Borradori-Tolsa C, Bauthay DM, Lodygensky G, Lazeyras F, Huppi P. Impact of intrauterine growth restriction and glucocorticoids on brain development: Insights using advanced magnetic resonance imaging. Molecular and Cellular Endocrinology. 2006;254:163–171. doi: 10.1016/j.mce.2006.04.035. [DOI] [PubMed] [Google Scholar]
  54. StataCorp . Stata Statistical Software: Release 12. StataCorp LP; College Station, TX: 2011. [Google Scholar]
  55. Taylor GH, Filipek PA, Juranek J, Bangert B, Minich N, Hack M. Brain volumes in adolescents with very low birthweight: Effects on brain structure and associations with neuropsychological outcomes. Developmental Neuropsychology. 2011;36(1):96–117. doi: 10.1080/87565641.2011.540544. [DOI] [PubMed] [Google Scholar]
  56. Taylor HG, Klein N, Minich NM, Hack M. Verbal memory deficits in children with less than 750g birth weight. Child Neuropsychology. 2000;6(1):49–63. doi: 10.1076/0929-7049(200003)6:1;1-B;FT049. [DOI] [PubMed] [Google Scholar]
  57. Thierry AM, Gioanni Y, Degenetais E, Glowinski J. Hippocampo-prefontal cortex pathway: Anatomical and electrophysiological characteristics. Hippocampus. 2000;10:411–419. doi: 10.1002/1098-1063(2000)10:4<411::AID-HIPO7>3.0.CO;2-A. [DOI] [PubMed] [Google Scholar]
  58. Thompson DK, Wood. SJ, Doyle LW, Warfield SK, Lodygensky GA, Anderson PJ, Inder TE. Neonate hippocampal volumes: Prematurity, perinatal predictors, and 2-year outcome. Annals of Neurology. 2008;63:642–651. doi: 10.1002/ana.21367. [DOI] [PubMed] [Google Scholar]
  59. Van Leemput K, Bakkour A, Benner T, Wiggins G, Wald LL, Augustinack J, Fischl B. Automated segmentation of hippocampal subfields from ultra-high resolution in vivo MRI. Hippocampus. 2009;19:549–557. doi: 10.1002/hipo.20615. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Vicari S, Caravale B, Carlesimo GA, Casadei AM, Allemand F. Spatial working memory deficits in children at ages 3-4 who were low birth weight, preterm infants. Neuropsychology. 2004;18(4):673–678. doi: 10.1037/0894-4105.18.4.673. [DOI] [PubMed] [Google Scholar]
  61. Volpe JJ. Neurology of the Newborn. 4th W. B. Saunders; Philadelphia: 2001. [Google Scholar]
  62. Volpe JJ. Brain injury in premature infants: A complex amalgam of destructive and developmental disturbances. The Lancet Neurology. 2009;8:110–124. doi: 10.1016/S1474-4422(08)70294-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Watson C, Andermann F, Gloor P, Jones-Gotman M, Peters T, Evans A, Leroux G. Anatomic basis of amygdaloid and hippocampal volume measurement by magnetic resonance imaging. Neurology. 1992;42:1743–1750. doi: 10.1212/wnl.42.9.1743. [DOI] [PubMed] [Google Scholar]
  64. Wechsler D. Wechsler Abbreviated Scale of Intelligence (WASI) The Psychological Corporation; 1999. [Google Scholar]
  65. Woodward LJ, Anderson PJ, Austin NC, Howard K, Inder TE. Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. New England Journal of Medicine. 2006;355(7):685–694. doi: 10.1056/NEJMoa053792. [DOI] [PubMed] [Google Scholar]
  66. Woodward LJ, Edgin JO, Thompson D, Inder TE. Object working memory deficits predicted by early brain injury and development in the preterm infant. Brain. 2005;128:2578–2587. doi: 10.1093/brain/awh618. [DOI] [PubMed] [Google Scholar]
  67. Woolsey, Hanaway, Gado . The Brain Atlas: A Visual Guide to the Human Central Nervous System. 2nd Wiley; Great Britain: 2003. [Google Scholar]
  68. World Health Organisation Born Too Soon: The Global Action Report on Preterm Birth. 2012 Retrieved July 15th, 2012, from http://www.who.int/pmnch/media/news/2012/preterm_birth_report/en/index.html.

RESOURCES