Cognitive Deficits in Spina Bifida - DiVA portal

Bachelor Degree Project in Cognitive Neuroscience

Basic level 15 ECTS Spring term 2015

Camilla Stenson

Supervisor: Björn Persson Examiner: Paavo Pylkkänen

Cognitive Deficits in Spina Bifida

COGNITIVE DEFICITS IN SPINA BIFIDA 1

Abstract

Spina bifida myelomeningocele (SBM) is the most common and severe type of spina bifida

which is a neural tube defect (NTD). Additionally to the defect of the spinal cord most cases of

SBM develop an Arnold-Chiari-II malformation, which is the main reason behind the common

development of hydrocephalus. Children with SBM have a rather different cognitive profile than

typically developing children. Hence, this thesis reviews the neurological impact on the cognitive

profile and its relation to the social impairments found for this population. The Arnold-Chiari-II

malformation is a malformation of the hindbrain which affects structures of the hindbrain,

midbrain, ventricular system and subcortical gray matter. These deficits lead to impairments in

the cognitive domains of executive functioning, visual-spatial working memory, intelligence,

language, and learning. The consequences of these cognitive deficits are often on the social

aspects of life. Two aspects affected are education and work, projecting in less academic success

and a higher rate of unemployment. By clarifying the relationship between all of these aspects

there is hope to improve the life of these individuals, especially on an educational basis.

Keywords: spina bifida myelomeningocele, Arnold-Chiari-II malformation, cognition,

neuroscience, social


Table of contents

Cognitive Deficits in Spina Bifida .................................................................................... 3

Theoretical background .................................................................................................... 4

Spina Bifida Occulta .................................................................................................... 5

Spina Bifida Cystica ..................................................................................................... 5

What are the causes? .................................................................................................... 6

Neurological implications and Arnold-Chiari-II malformation ......................................... 9

Cognitive profile ............................................................................................................ 13

Visual-Spatial deficits ................................................................................................ 14

Executive deficits ....................................................................................................... 15

Learning deficits ........................................................................................................ 18

Language deficits ....................................................................................................... 19

Intelligence ................................................................................................................ 20

Social impairments......................................................................................................... 22

Discussion ..................................................................................................................... 24

References ..................................................................................................................... 31


Cognitive Deficits in Spina Bifida

Spina bifida is a type of neural tube defect (NTD) which affect 1 to 2 infants per 1000

births (Bassuk & Kibar, 2009). Spina bifida occurs when the neural tube does not close correctly

during embryogenesis and can be of different severity (Bassuk & Kibar, 2009). One of the

subtypes of spina bifida is spina bifida myelomeningocele (SBM) which is characterized by a

protrusion of the spinal cord, nerve roots and cerebrospinal fluid (CSF) through the back

(Northrup & Volcik, 2000). When this occur it may force the cerebellum and midbrain down

towards the brainstem causing an Arnold-Chiari-II malformation (Stevenson, 2004). Almost all

cases of SBM is affected by this malformation and it is only to be found when SBM is present

(Stevenson, 2004; Vinck, Maassen, Mullaart, & Rotteveel, 2006). Arnold-Chiari-II malformation

is a congenital malformation of the hindbrain affecting structures such as cerebellum as well as

several midbrain structures and subcortical gray matter (Stevenson, 2004; Ware et al., 2014).

Many children with SBM develop hydrocephalus as a consequence of the malformation

(Northrup & Volcik, 2000; Stevenson, 2004). All of this together creates a rather different

cognitive profile, which in turn affects the social life of these individuals (Holmbeck et al., 2003;

Rose & Holmbeck, 2007; van Mechelen, Verhoef, van Asbeck, & Post, 2008).

While many studies and reviews on spina bifida do not differentiate clearly between the

subtypes of this condition, the focus in this paper will be on SBM. The reasons behind focusing

on SBM is that it is the most common and most severe subtype of spina bifida (Northrup &

Volcik, 2000). The severity lies in the higher level lesion and the neurological impact which is

not found in other subtypes (Verhoef et al., 2006).

The aim of this paper is to highlight the cognitive deficits and social impairments of

SBM. This aim will be approached by describing the neurological underpinnings of SBM as well


as going through the cognitive deficits of executive functions, learning, language and intelligence

and presenting the findings regarding the social impairments of this population.

Firstly a theoretical background will be presented about the different types of spina bifida

and the possible causes of the defect. After this, findings regarding the neurological basis of SBM

will be presented as well as theories and findings concerning Arnold-Chiari-II malformation.

Then the cognitive profile in SBM, divided in several domains will be presented, followed by

findings of the social impairment presented in the literature. In the discussion, the link between

all aspects of spina bifida will be discussed, key findings concluded, limitations of these findings

presented and future direction and implications of these findings will be discussed.

Theoretical Background

Spina bifida is a form of neural tube defect (NTD) in which the neural tube does not close

correctly or not at all during embryogenesis, which occurs early during pregnancy. This defect

can occur at different levels of the neural tube resulting in different defects (Bassuk & Kibar,

2009). If the neural tube closure is affected at the lower parts, spina bifida can emerge. NTDs can

be open or close which, as the name suggests, mean that the defect is either covered by skin or

the nervous tissues are exposed (Bassuk & Kibar, 2009). NTDs are the most common structural

malformations of the central nervous system in human beings and, as mentioned, affect 1 to 2

infants per 1000 births (Bassuk & Kibar, 2009). The open NTD’s are the most common and

include SBM (Bassuk & Kibar, 2009). 15% to 20% of NTD’s are covered with skin which is the

case for meningocele (Northrup & Volcik, 2000). As briefly mentioned earlier, spina bifida

comes in several types which vary in severity. The types are normally divided into two main

groups; spina bifida occulta (SBO) and spina bifida cystica (SBC); Northrup & Volcik, 2000).


Spina Bifida Occulta

The mildest form of spina bifida is SBO. The word “occulta” means hidden which is a

good description of the defect. In SBO, the spinal cord and meninges is within the vertebral canal

but it results from a gap in at least one vertebral arch. This might manifest in a small cavity

between two neighboring vertebrae, indicating that the vertebrae have not been fused together

properly. This might show as a birthmark or a small dimple of hair on the patient’s lower back.

When there are only one vertebra that have failed to fuse together and the spinal cord and nerves

are normal, neurological symptoms are normally absent and the patient have no clinical

symptoms. If more than one vertebra is involved patients might develop bowel, bladder or motor

problems (Northrup & Volcik, 2000). However, in approximately 10% of otherwise healthy

people, SBO occur in the lower lumbar or sacral vertebrae and is thus regarded as a normal

variation in the population (Northrup & Volcik, 2000).

Spina Bifida Cystica

SBC are the umbrella term for spina bifida when a defect in the vertebral arch causes a

cyst like sac on the back. This sac is filled with cerebrospinal fluid (CSF) and the spinal cord,

meninges, and spinal nerves may protrude out into the sac. One type of SBC is meningocele

which is a closed NTD. In the case of meningocele the spinal cord and spinal root are in their

normal position but there is a sac at the location of the defect on the vertebral arch containing

cerebrospinal fluid and meninges. Despite that the spinal cord is at its normal location there can

be spinal cord abnormalities due to this malformation (Northrup & Volcik, 2000).

A more common and severe type of SBC is characterized further by a protrusion of the

spinal cord and/or nerve roots through the vertebral arch defect into the sac. This is referred to as

myelomeningocele or meningomyelocele which is an open NTD. Only 1% of children born with

an open NTD are free of handicap (Northrup & Volcik, 2000). The interruption of the spinal cord


in myelomeningocele generally causes anesthesia of the skin and paralysis of the legs,

incontinence of urine and feces, and abnormalities in the hips, feet and knees, all depending on

the level of the lesion on the spinal cord. The level of the lesion may also be an indicator for the

degree of abnormalities in the brain as well as neurobehavioral outcomes (Fletcher et al., 2005).

When a child is born with myelomeningocele it will need multiple surgeries and invasive

procedures. The first surgery is needed within 24 to 48 hours after birth in order to close the

opening in the back to reduce the risk of infection, only 20% of infants who don’t get the surgery

will survive to the age of two years. Approximately 80% of children born with

myelomeningocele, have a presence of hydrocephalus at birth, probably caused by an Arnold-

Chiari type II malformation, but not exclusively (Northrup & Volcik, 2000). The prevalence for

hydrocephalus is greater for higher level lesions (Verhoef et al., 2006).

What are the causes?

There are several theories about the origins of NTD’s and Spina bifida, ranging from tea

consumption (Yazdy, Tinker, Mitchell, Demmer, & Werler, 2012) to folic acid levels (Wald,

Law, Morris, & Wald, 2001), and genetic components (Detrait et al., 2005). The recurrence risk

for siblings of patients with NTDs without other syndromes are 2% to 5%, suggesting a genetic

component (Detrait et al., 2005). In a group of families there was a history of NTDs in 8.5% of

the cases. Although parent-child pairs are rare, pairs related at second or third degree are the most

affected, suggesting that a small number of genes are involved (Detrait et al., 2005). One big

question to account for when discussing recurrence rates within families with NTDs is whether

the different levels of NTDs, which represent different defects, remain constant within the

affected family. This would imply that a family can be affected with a lower NTD like spina

bifida, and not inherit various versions of NTDs (Detrait et al., 2005). NTD inheritance tends to

be exactly that, constant, although 30 to 40% of recurrences include an NTD phenotype, meaning


an NTD at a different level and another defect. The theories for the reasons behind this

occurrence are many, including: if it is one common underlying gene, or in families with different

phenotypic presentations it may be due to several different underlying genes (Detrait et al., 2005).

It might be due to timing on key environmental exposures, or could it even be the result of

random chance (Detrait et al., 2005). Furthermore, NTDs are often associated with various

chromosome rearrangements, such as trisomy 13 and 18, which refers to a triple set of

chromosomes 13 and 18 instead of the normal two (Detrait et al., 2005). In 5 to 17% of cases

with NTDs, chromosome abnormalities are found, especially aneuploidy (any variation in the

number of chromosomes that involves individual chromosomes rather than entire sets of

chromosomes; Detrait et al., 2005).

Folic acid is known to reduce the prevalence of NTD pregnancies if folic acid

consumption is raised around the time of conception, thus raising the serum folate concentration

in the blood (Wald et al., 2001). In 1992 the U.S Public Health Service (USPHS) started a

program to increase folic acid consumption by improving dietary habits, fortifying foods with

folic acid, and recommending all women capable of becoming pregnant to consume 0.4 mg folic

acid per day. All in an attempt to decline the number of NTD affected pregnancies in the U.S

(Service & States, 2004). The number of NTD affected pregnancies in the US were about 4000

(2490 cases of spina bifida specifically) in the period 1995 to 1996, and about 3000 (1640 cases

of spina bifida specifically) in the period 1999 to 2000 (Service & States, 2004). This decline of

about 27% highlights the partial success of the U.S folic acid fortification program (Service &

States, 2004). Wald et al (2001) found that a dosage of 0.2 mg/day reduces the risk for NTDs by

about 20%, 0.4mg/day, 36%, 1mg/day, 57%, 5mg/day, 85% (Wald et al., 2001). With regard to

these findings it would be reasonable to suggest that the recommended dose of folic acid

supplements should be 5mg/day instead of about 0.2mg/day, that is the level of the U.S folic acid


fortification and the recommendations in the United Kingdom (0.24mg) today (Wald et al.,

2001). However, blood folate concentration varies from person to person, meaning that the intake

of folic acid depends on the initial serum folate concentration the woman have. Women with

higher initial levels may get a lower effect of the same dose of folic acid than women with a

lower initial levels, meaning that the risk reduction for a dosage of 0.4mg/day can range from

23% to 52% depending on initial levels of serum folate concentration (Wald et al., 2001).

Another nutrient that may be essential for neural tube closure is vitamin B12. Suarez, Hendricks,

Felkner, and Gunter (2003) studied 343 Mexican-American women of which 157 case-women

who have had NTD affected pregnancies and 186 controls with normal pregnancies. 5-6 weeks

postpartum the women were interviewed and blood samples were taken. They collected data of

dietary intake of b12 and serum b12 levels and measured and controlled for age, years of education,

body mass index (BMI), dietary intake of folate, multivitamin intake, and serum folate levels.

They found that women with the lowest vitamin B12 levels showed a strong risk effect for having

a NTD birth, about three times higher than the risk for women with the highest vitamin B12

levels.

Among other theories about the cause of NTDs, diabetes and glucose levels constitute one

theory. This has been shown in several mouse models where elevated glucose levels, associated

with diabetes, can be a factor for NTDs (Fine, Horal, Chang, Fortin, & Loeken, 1999; Hiramatsu

et al., 2002). Another may be the body mass index (BMI) of the mother since obese women, with

a BMI over 29, seems to have almost twice the risk of having a child with a NTD (Rasmussen,

Chu, Kim, Schmid, & Lau, 2008; Shaw, Todoroff, Schaffer, & Selvin, 2000; Watkins,

Rasmussen, Honein, Botto, & Moore, 2003). Regarding tea consumption, the theory was

developed from the notion that catechin (an antioxidant found in tea) reduces the uptake of folate.


However, tea consumption does not seem to be associated with a higher risk for a spina bifida

affected pregnancy (Yazdy et al., 2012).

Neurological implications and Arnold-Chiari-II malformation

Alongside the physical disabilities mentioned before, several studies have shown that

children with SBM often suffer from several cognitive disabilities. The brain abnormities

regarding SBM are varied and several factors have an impact on the cognitive profile of these

children. Almost all of the cases of SBM are affected by an Arnold-Chiari-II malformation

(Vinck, Maassen, Mullaart, & Rotteveel, 2006), and thus are the primary source of the brain

abnormalities found in children with SBM. Arnold-Chiari-II malformation is a unique hindbrain

herniation (i.e., misplacement due to pressure) which only occurs in the presence of SBM

(Stevenson, 2004). This malformation is also the main reason behind the origin of hydrocephalus

in these patients. The degree of anatomical disturbance, due to Arnlond-Chiari-II malformation,

is varied from child to child (Stevenson, 2004).

The theory that most efficiently explain the development of Arnold-Chiari-II

malformation is a unified theory by McLone and Knepper (1989). This theory combines features

from several other theories that do not manage to explain the origin of the malformation

thoroughly. This theory points out that ventricular distension (i.e., a dilation of the ventricles) is

crucial for both neural development and development of the skull. In SBM the open neural tube

defect as well as incomplete spinal occlusion makes cerebrospinal fluid (CSF) drain through the

central canal, thus it is not maintained in the ventricular system. Without this ventricular

distention the posterior fossa never fully develops. Alongside with growth of the hindbrain this

forces the cerebellum both cephalad and caudad along with the brainstem. This lack of

ventricular distention produce several other anomalies and malformations such as polygyria

(malformation characterized by an excessive number of small gyri), enlargement of massa


intermedia (seemingly functionless mass of grey matter in the midline of the third ventricle), and

base of skull anomalies (Stevenson, 2004). It was earlier believed that the hydrocephalus

associated with SBM was the cause of the Arnold-Chiari-II malformation. This is not the case

since prenatal imaging has shown the development of Arnlod-Chiari-II malformation before any

signs of hydrocephalus. Additionally 10-15% of children with SBM with Arnold-Chiari-II

malformation do not develop hydrocephalus (Rekate, 1984). McLone and Knepper (1989)

explain that the development of hydrocephalus may be due to an impaction of posterior fossa

brain matter on the foramen magnum. This blocks or impairs the outflow of CSF at the foramen

of Luchka and Magendie which are openings in the fourth ventricle, resulting in progressive

ventriculomegaly, a brain condition occurring when the lateral ventricles become dilated.

Arnold-Chiari-II malformation makes the cerebellar vermis invariably displaced below

the foramen magnum. It takes the appearance of a “peg” and can be placed really low. The

cerebellum is abnormally located and as a whole it is small and seems thin. The gyri of the

cerebellum are small and numerous, called polygyria. The posterior fossa is smaller as well

which makes it seem crowded even though the cerebellum is smaller (Stevenson, 2004).

Furthermore abnormalities in cortical thickness, white matter integrity (Ware et al., 2014), as well

as multiple ventricular anomalies are found in these patients (Stevenson, 2004). The fourth

ventricle is frequently displaced and the third ventricle may take on a different shape, commonly

referred to as “shark tooth deformity”. The lateral ventricle varies in appearance from nearly

normal to severely deformed and the occipital horns are unduly enlarged (Stevenson, 2004).

About one-third of these patients has partial or total absence of the corpus callosum which is

referred to as agenesis of the corpus callosum. Untreated symptomatic Arnold-Chiari-II

malformation is the leading cause of death in children with SBM under the age of two years

(Stevenson, 2004).


Ware and colleagues (2014) studied gray matter volume in subcortical structures in

children with SBM by using anatomical and diffusion magnetic resonance imaging (MRI). The

structures examined were basal ganglia structures (caudate, pallidum, putamen), hippocampus,

amygdala, and thalamus. They found a significant reduction of volume of the hippocampus as

well as a significant enlargement of the putamen. Additionally they studied the mean diffusivity

(MD) and the fractional anisotropy (FA) in these subcortical structures. Both of these are

measured by diffusion magnetic resonance imaging (dMRI) which makes it possible to identify

the diffusion process of molecules (e.g., water). MD is the measure of the total diffusion within a

voxel. FA is a value that describes the degree of anisotropy (i.e., water molecules being directed

in a matter that is predetermined by the tissue structure) of a diffusion process. Overall, the MD

values were higher for SBM group compared to controls with exceptions for the putamen which

had lower MD values and, amygdala and pallidum which had similar MD values to the controls.

Regarding FA values they were overall higher for the SBM group than for controls with

exception for the hippocampus (Ware et al., 2014). The mechanical effects of hydrocephalus

may answer to the increased MD and FA values which in turn suggests lower density and cellular

degeneration of these structures (Ware et al., 2014).

It is common in children with SBM to have abnormalities in the midbrain tectum

(Williams et al., 2013). The superior colliculus is a part of the midbrain tectum and consists of

two layers: the superficial layer and the intermediate layer. The superficial layer receives direct

input from primary sensory regions and its outputs projects to visuomotor and motor neurons

located in the more inferior intermediate layer which converge and integrates the information

(Merker, 2007). The midbrain tectum is considered to be critical to spatial attention since it is a

component of the posterior attentional network (Dennis et al., 2005). The Arnold-Chiari-II

malformation can cause a fusion of the colliculi which forms a single mass called tectal beaking


(Stevenson, 2004). Tectal beaking is associated with indices of white matter integrity of both

frontal and parietal tectocortical pathways in these children compared to typically developing

peers as well as other children with SBM that do not have this tectal beaking (Williams et al.,

2013). These findings suggest a change in the tectocortical pathways which are not due to the

mechanical effects of hydrocephalus (Williams et al., 2013). Furthermore, children with SBM

display a significant decrease of tectal volume compared to typically developing controls

regardless of the presence of tectal beaking (Williams et al., 2013). Decreased FA values in the

posterior but not anterior tectocortical white matter pathways suggests damage to the posterior

pathways, probably caused by hydrocephalus, but relatively intact anterior pathways (Williams et

al., 2013). Limbic fiber abnormalities found in children with SBM and Arnold-Chiari-II

malformation may account for deficits in learning and memory functions (Vachha, Adams, &

Rollins, 2006).

Other variables that may contribute to the brain abnormalities are the insertion of a shunt

as a treatment for the hydrocephalus, complications of the shunt, and epilepsy and its treatment

(Ramsundhar & Donald, 2014). The most common reason behind shunt revisions is a blockage of

the shunt, this blockage may lead to raised intracranial pressure (Hunt, Oakeshott, & Kerry,

1999). Insertion of a shunt, as well as revision of the shunt, seems to be indicators of several

achievements at adult age (Hunt, Oakeshott, & Kerry, 1999). Achievement is specified by Hunt

and colleagues (1999) as independent living, driving a car, and having a job. In a group of

patients with spina bifida who have had a shunt inserted but no revisions after the insertion, 68%

were classified as achievers. In another group of patients with spina bifida who have had a shunt

inserted and shunt revisions only 28% were classified as achievers. Only 18% of patients who

had have shunt revisions after the age of two were classified as achievers (Hunt et al., 1999).


Cognitive profile

This section will discuss several aspects of the cognitive profile in children with spina

bifida, which have been frequently studied. Abnormal development of subcortical gray matter

may account for disruptions in higher order cognition for children with SBM (Ware et al., 2014).

For instance, abnormalities in thalamus and certain basal ganglia nuclei (particularly the caudate

and putamen) are shown to be involved in working memory and attentional control, domains that

are impaired in SBM children which will be clarified subsequently (Baier et al., 2010;

Burmeister et al., 2005; Mammarella, Cornoldi, & Donadello, 2003; Rose & Holmbeck, 2007;

Vachha et al., 2006; Vachha & Adams, 2005; Wiedenbauer & Jansen-Osmann, 2006).

It is important to study the cognitive deficits these children have since they are many and

varied and may affect the life of these children further regarding education and employment (van

Mechelen et al., 2008). The unemployment rate for young adults (16-25 years of age) with spina

bifida of 53% is far higher than the 8% in the general population (15-24 years of age) in the

Netherlands, and is especially low for individuals with spina bifida cystica with a higher level

lesion and hydrocephalus (Barf et al., 2009). The same study found a relationship between the

same variables and educational level (Barf et al., 2009). Educational level might be affected by

cognitive impairments that seem to project to disabilities with math (Barnes et al., 2006; Dennis

& Barnes, 2002; Mayes & Calhoun, 2006) as well as difficulties in some areas of language

(Fletcher, Barnes, & Dennis, 2002). Van Mechelen and colleagues (2008) stress the importance

of educational support for these children since level of education was the only significant

predictor of work participation in general for this population in their study. Furthermore,

impairment in executive functions such as planning, problem solving and attention as well as

impairment in navigation might contribute to educational, job-related, social, and personal

restriction (Burmeister et al., 2005; Dennis et al., 2005; Rose & Holmbeck, 2007; Snow, 1999;


Wiedenbauer & Jansen-Osmann, 2006). Therefore, knowledge about the cognitive profile in

children with spina bifida is crucial.

Visual-Spatial deficits

The visuospatial working memory is a temporary store within the general working

memory system proposed by Baddeley and Hitch (1974) which has the role of processing and

maintenance of visuospatial information from sensory perception or from long term storage.

Spatial knowledge can be divided into three domains: landmark knowledge (i.e., the knowledge

of certain objects in the environment), route knowledge (i.e., knowledge of routes between these

objects), and survey knowledge (i.e., overviewing representations which entail spatial relations

and metric information; Wiedenbauer & Jansen-Osmann, 2006). The meaning of landmarks is

twofold and refers to either landmarks as reference locus that decide the localization of other loci

in the environment, or landmarks as perceived and remembered visual objects (Wiedenbauer &

Jansen-Osmann, 2006). Furthermore, perception models propose two different kinds of spatial

relations between objects and observers: categorical perception and coordinate perception.

Categorical perception specifies spatial relationships of visual primitives that may be described

by categories, feature groupings and/or verbal locatives. Coordinate perception specify how

things relate to each other in space (e.g., the line and the dot are 3 cm apart). Whereas children

with SBM do not seem to have problems with categorical perception, they seem to have an

impaired coordinate perception (Dennis & Barnes, 2011). Although children with spina bifida

(shunted for hydrocephalus) managed to point out fewer (but not significantly fewer) landmarks

on the correct location in a study by Wiedenbauer and Jansen-Osmann (2006), these children do

not have substantial deficits in their landmark knowledge. However, they seem to have severely

limited route knowledge compared to healthy peers (Wiedenbauer & Jansen-Osmann, 2006).

When matching participants for age, gender, verbal- and performance IQ children with spina


bifida needed more trials in a virtual maze before reaching the learning criterion as they made

more incorrect turns and errors compared to controls. These findings indicate that an environment

with more landmarks is crucial for the navigation of these individuals (Wiedenbauer & Jansen-

Osmann, 2006).

Mammarella and colleagues (2003) showed that visuospatial working memory can be

divided into an active and a passive component. The active component involves a greater active

storage and processing of information, used when you, for example, have to actively remember

both the sequential order and the visual representation of a visual stimuli. The passive

component, however, is based on a passive manipulation of information used when you mainly

need to sustain the recognition of the visual stimuli. Their study showed that children with spina

bifida (shunted for hydrocephalus) were as good as controls in tasks that required an active

component of visuospatial working memory but failed in tasks that required passive, and

especially visual, functions of the visuospatial working memory (Mammarella et al., 2003).

Executive deficits

Executive functions are a set of high-level cognitive processes such as attention, planning,

self-regulation, and goal-directed behavior. Several studies have found that children or

adolescents with spina bifida have impaired executive functioning (Riddle, Morton, Sampson,

Vachha, & Adams, 2005; Rose & Holmbeck, 2007; Snow, 1999), especially regarding planning,

problem solving, mental flexibility (Snow, 1999), and attention (Rose & Holmbeck, 2007). One

way of measuring executive function is by using the Behavior Rating Inventory of Executive

Function (BRIEF; Gioia & Isquith, 2011), which is a parent and teacher rating scale that

measures executive functions as displayed in the child’s everyday environment. The BRIEF scale

is divided into nine domains: initiate, sustain, inhibit, shift, organize, plan, self-monitor, working-

memory and emotional control. Burmeister and colleagues (2005) found that children with SBM


were rated with greater difficulties on all the BRIEF scale measures compared to healthy

controls.

Rose and Holmbeck (2007) found a significant impairment of the domains initiate (i.e.,

the ability to initiate an activity and produce problem solving strategies or ideas independently),

and working-memory, but were using a sample with varying types of spina bifida although the

majority (71 %) was shunted for hydrocephalus. However, the varying types of spina bifida in

this sample gives an indication that the effects of hydrocephalus (and/or shunt surgery) may be a

major factor for the cognitive disabilities found. Within the spina bifida sample, shunt status

(whether or not a participant have required shunting for hydrocephalus) was a significant

predictor of both the Cognitive Assessment System (CAS; Naglieri & Das, 1997) and BRIEF

performance (Rose & Holmbeck, 2007).

This study by Rose and Holmbeck (2007) found impairments regarding planning on one

of the test used. Children with spina bifida were impaired on the planning sub-tests of the

performance-based CAS but did not show any impairments on the BRIEF questionnaire (which is

answered by parents and teachers). The two tests measure different types of planning. CAS

measure the ability to develop and rapidly execute problem solving strategies, whereas BRIEF

measures the social and behavioral manifestations of planning ability. The difference between the

outcomes of these two tests may be an indication for the type of planning which is impaired.

Meaning that children with spina bifida may have an reduced ability with rapid and efficient

development of problem solving strategies but do not have difficulties in their ability to plan for

and anticipate consequences in their daily activities (Rose & Holmbeck, 2007).

Regarding attention, children with spina bifida do not seem to have impaired sustained

attention (i.e., the ability to maintain a consistent behavioral response and to detect unpredictably

occurring signals over a long period of time), but are impaired when it comes to focused attention


(i.e., the ability to response separately to a specific stimuli; Rose & Holmbeck, 2007). However,

the results might be affected by the use of two different types of tests for sustain and focused

attention in this study. Sustain attention were measured using the parent/teacher BRIEF

questionnaire, whereas focused attention were measured by the performance-based CAS (Rose &

Holmbeck, 2007).

In orientation of attention we can either shift attention by overt movements of the head,

body or eyes, or covert, meaning a shift of attention without moving our head, body or eyes.

Furthermore overt orientation of attention can be automatic, as in orienting towards salient

information, and can be tested using exogenous cues, or effortful, as in voluntary shifts of

attention towards something we find interesting and can be tested by using endogenous cues

(Dennis et al., 2005). Children with SBM seem to have a slowed covert orientation, compared to

matched controls, on both exogenous and endogenous cues that concern attention disengagement

(Dennis et al., 2005). This may be due to the dysmorphology (i.e., abnormal development of

tissue form) of the midbrain and thinning of the posterior cortex that these children display due to

Arnold-Chiari-II malformation, regions that are associated with the control of covert orienting

(Dennis et al., 2005). Furthermore, among children with SBM the prevalence rate for Attention

Deficit Hyperactive Disorder (ADHD), based on parent rating scales, is higher (31%) than for the

general child population (5%) as presented in the Diagnostic and Statistical Manual of Mental

Disorder, fifth edition (DSM-V; Burmeister et al., 2005; American Psychiatric Association,

2013). The parent rating scales used by Burmeister and colleagues (2005) were based on the

DSM-V criteria. The group of children with SBM and ADHD did not differ in number of shunt

revisions compared with the group of children with SBM, without ADHD (Burmeister et al.,

2005).


Learning deficits

Mayes and Calhoun (2006) studied the frequency of learning disabilities in children with

clinical disorders among which one of the groups were children with spina bifida. They found

that 60% of the children in the spina bifida group (with normal intelligence i.e. IQ > 80; mean IQ:

89) had learning disabilities and mainly disabilities with math and written expression (i.e., the

ability to express oneself in writing). 33% of the spina bifida group had learning disabilities in

math, and 40% had learning disabilities in written expression. The two other learning disabilities

studied; reading and spelling, did not seem to be disabled in this group.

Regarding math and numeracy young adults with SBM seem to have poorer computation

accuracy (which was related to the working memory of numbers), computation speed, problem

solving, and functional numeracy than expected for their age and those skills are furthermore

poorer than their own level of reading decoding (Dennis & Barnes, 2002). The compromised

functional numeracy was related to the number of lifetime shunt revisions (Dennis & Barnes,

2002). For these individuals it seems that poor math problem solving skills in their childhood

may translate into poor problem solving and numeracy further on in adulthood (Dennis & Barnes,

2002). These difficulties are likely to limit the academic achievement, vocational success and

functional independence for individuals with SBM (Dennis & Barnes, 2002). Overall children

with this condition have less mastery of math facts (basic facts in addition, subtraction,

multiplication, and addition, i.e., 3+3=6; Barnes et al., 2006). Many have hypothesized a link

between deficits in visual-spatial working memory, visual memory, and visual-spatial

functioning, and disabilities in mathematics (McLean & Hitch, 1999; Rourke, 1993; Share,

Moffitt, & Silva, 1988). Barnes and colleagues (2006) did not find this link and furthermore

found that visual-spatial errors in multi-digit arithmetic were not elevated in children with SBM.


Furthermore, these children seem to have problems with remembering a long list of

words, due to impairment in memory span (Vachha & Adams, 2005). In a memory task they had

to remember a long list of words, some words (fruits) were of higher value than other words

(animals). Children with SBM remembered significantly fewer words than controls. This study

also suggests that children with SBM are impaired in their ability to use the most efficient

strategy in learning items of different value in order to achieve a higher score. The majority, 65%,

of the SBM group reported that they tried to remember all the words, whereas 85% of controls

reported that they tried to remember the items with the higher value (Vachha & Adams, 2005).

The ability to remember information of relevance among less relevant information is an

important skill for success in school, something that children with SBM seem to have problems

with (Vachha & Adams, 2005). Children with SBM seem to reach poorer educational success.

One-third of the children in a study of young adults with spina bifida had need for special

education or had not reached education beyond primary school and only 16% of the sample had

higher level education (Barf et al., 2009). They also found a link between lower education and

having spina bifida cystica, a higher level lesion and the occurrence of hydrocephalus (Barf et al.,

2009).

Language deficits

Regarding language most children with SBM have a good vocabulary (Horn, Lorch, &

Culatta, 1985) and comprehension of grammar seem to improve more with age (for children with

hydrocephalus) compared to healthy controls (Dennis, Hendrick, Hoffman, & Humphreys, 1987)

However they seem to have difficulties in other areas of language (Fletcher et al., 2002). Their

difficulties are mainly in construction of meaning and in pragmatic communication (social

communication).


Many children with SBM (who are in the intellectually average range) show the core

feature of the “cocktail party syndrome” which produces a language that lacks content and

essence, and fails to deliver the central information of a subject. Thus, their language tends to be

verbose and complicated (Dennis, Jacennik, & Barnes, 1994). The term “cocktail party

syndrome” is described by Tew (1979) in five steps: (1) preservation of response, with repetition

of an earlier statement made by the child, (2) Excessive use of social phrases in conversation, (3)

An over-familiarity in manner, not normally expected in a child, (4) Introduction of personal

experience into the conversation, usually in an irrelevant and inappropriate context, and (5)

Fluent and well-articulated speech. Thus, the “cocktail party syndrome” is used to describe

language that within a conversation is contextually aimless, irrelevant and inappropriate, despite

that it is articulate and coherently expressive (Tew, 1979). However to describe these differences

in language as a syndrome might be misleading (Dennis et al., 1994).

Construction of meaning and in pragmatic communication require flexible language

processing in real time which seems to be impaired due to brain abnormalities caused by the

Arnold-Chiari-II malformation (Fletcher et al., 2002)

Intelligence

It has been commonly reported that hydrocephalic children are more impaired on

performance IQ than verbal IQ (Berker, Goldstein, Lorber, Priestley, & Smith, 1992; Dennis et

al., 1981; Donders, Rourke, & Canady, 1991; Fletcher et al., 1992). Similar results have been

found when comparing children with SBM and children with spina bifida without cerebral

malformations (Vinck et al., 2010). In this study by Vinck and colleagues (2010) they used the

Wechsler Intelligence Scale for Children – III (WISC-III; Wechsler, 1991) which was

administered to measure general intelligence in children aged 6-16 years of age. The WISC-III

are divided into verbal IQ (VIQ), performance IQ (PIQ), and full scale IQ (FSIQ). Although


scores on VIQ were similar (SBM: 94, spina bifida: 98), scores on PIQ (SBM: 77 spina bifida:

98) and FSIQ (SBM: 85, spina bifida: 100) differed significantly (Vinck et al., 2010). However,

when comparing children with SBM with healthy controls Jacobs, Northam, and Anderson

(2001) found that children with SBM performed significantly poorer on all intelligence tests in

the WISC-III including VIQ (SBM: 84,5, controls: 105,7), PIQ (SMB: 79,3, controls: 106,8), and

FSIQ (SMB: 80,8, controls: 106,7; Jacobs et al., 2001). In an older test on intelligence among

these children (Tew, 1977) using an older version of the WISC, similar scores were presented.

Barf and colleagues (2003) studied the cognitive status of young adults (16-25 years of age) with

spina bifida cystica either with or without hydrocephalus and used the Standard progressive

matrices (Raven, 1996) to measure general intelligence (mean IQ is 100). A group mean of 83 for

the hydrocephalus group and 93 for the group without hydrocephalus was presented and one fifth

on the hydrocephalic group had an IQ under 70 (Barf et al., 2003). In addition to general

intelligence, memory, verbal learning, executive function and reaction time was tested, and IQ

significantly correlated with all but one of the other cognitive scores (Barf et al., 2003).

Holler, Fennell, Crosson, Boggs and Mickle (1995) as well as Barf and colleagues (2003)

present that malformation of the corpus callosum appear to be negatively related to intelligence,

whereas Ralph, Moylan, Canady, Simmons (2000) contradicting finding suggested that the

number of shunt revisions was a possible answer to why some children with SBM may have a

lower IQ, which goes in line with the findings of Barf and colleagues (2003). Both studies found

that five or more shunt revisions had a negative effect on IQ (Ralph et al., 2000; Barf et al.,

2003). Furthermore, there may be a relationship between impaired performance IQ and

performance in the attention and executive domain (Riddle et al., 2005).


Whereas mean intelligence is generally known to be set at 100, the mean scores of

children with SBM is generally lower and seems to be due to cerebral malformation including

hydrocephalus (Barf et al., 2003; Jacobs et al., 2001; Tew, 1977; Vinck et al., 2010).

Social impairments

Children with spina bifida (age 8-9) exhibit lower levels of psychosocial adjustment

compared with healthy peers (Holmbeck et al., 2003). They seem to be more socially immature

and are more dependent on adults for direction and guidance. They are less likely to initiate social

contact and to make independent decisions. Furthermore, they seem more passive and less

engaged when observed during family interaction (Holmbeck et al., 2003). As a result of this,

children with spina bifida tend to have fewer social contacts outside of school compared to

healthy peers (Holmbeck et al., 2003). These impairments may be linked to their deficit regarding

pragmatic communication mentioned before (Fletcher et al., 2002; Holmbeck et al., 2003).

Furthermore, the deficits in attention and executive function found in children with spina bifida

have been found to be predictive of these social adjustment difficulties (Rose & Holmbeck,

2007). Holmbeck and colleagues (2003) hypothesize that the social difficulties experienced in

childhood may make them more likely to experience depressive affect during adolescence.

Adolescents with spina bifida have been found to be at greater risk for having depressive

symptoms such as depressive mood, low self-worth, and suicidal ideation compared to able-

bodied peers (Appleton et al., 1997).

When asking adolescents (12-21 years of age) about the future they reported that they felt

less positive about being able to go out on dates, being treated the same as other kids, and job

opportunities (Sawin, Brei, Buran, & Fastenau, 2002). As mentioned before, employment seems

to be a major issue for individuals with spina bifida, with only 47% of 92 participants who had


finished their education having a regular job (Barf et al., 2009). In other another sample (of 179

participants), 62.5% worked at least for one hour per week, of which 22.4% worked in a sheltered

workplace. Sex, educational level, and self-care independence were significant predictors of full

time employment, and for paid work only level of education was a significant predictor. When

trying to find work, the most common problem reported (stated by 57% of the sample) was an

unwilling attitude among the employees (van Mechelen et al., 2008). Furthermore, lower scores

on VIQ, PIQ, and functional math skills have been found to be associated with unemployed

status. For hydrocephalic children with spina bifida there seems to be significantly more

problems when it comes to out of school activities compared to children with spina bifida without

hydrocephalus (Cate, Kennedy, & Stevenson, 2002).

Whereas intelligence, memory, and word production do not seem to be related to

subjective quality of life (SQoL) in young adults with spina bifida and hydrocephalus, executive

function seems to be (Barf, Post, Verhoef, Gooskens, & Prevo, 2010). Scores on executive

functioning was a stronger determinant of SQoL than functional independence in a study by Barf

and colleagues (2010). The authors of this particular study suggests that the reason behind why

executive functioning is related to SQoL might be due to a more direct or more substantial impact

of executive function on daily activities as they interfere with more complicated or more

articulated activities. This indicates that disadvantages in planning, mental flexibility or attention

can affect independent functioning, especially in new situations, for children with hydrocephalic

spina bifida (Barf et al., 2010). Hetherington, Dennis, Barnes, Drake and Gentili (2006) found a

relationship between functional math skills and overall quality of life.

When studying resilience in adults with spina bifida, Hayter and Dorstyn (2013) found a

significant positive correlation between resilience, self-esteem, and self-compassion as well as an

significant negative correlation between resilience and depression, anxiety, and stress.


Furthermore, this psychological distress was associated with lower levels of self-esteem and self-

compassion. The authors suggest that the cumulative medical stressors that are experienced by

individuals with spina bifida (in addition to physical disability) have a negative impact on

psychological functioning (Hayter & Dorstyn, 2013). Lastly, although an minority, it is important

to highlight that more than one-fifth of a sample of 97 adults with spina bifida had experienced

social isolation and bullying as a consequence of their disability (Hayter & Dorstyn, 2013).

Discussion

Spina bifida is a lower level NTD which comes in different variations at different levels

of severity (Bassuk & Kibar, 2009; Northrup & Volcik, 2000). SMB is the most severe type of

spina bifida which often is accompanied by neurological deficits such as Arnold-Chiari-II

malformation and hydrocephalus (Stevenson, 2004). The causes behind NTD and spina bifida are

not determined, and several theories and findings may yield some answers. Perhaps there is a

network of aspects underlying the cause of NTD and spina bifida. Some of the components

behind the cause may be genetic components (Detrait et al., 2005), folic acid levels (Wald et al.,

2001), vitamin b12 levels (Suarez et al., 2003), diabetes and glucose levels (Fine et al., 1999), and

BMI (Watkins et al., 2003).

The aim of this paper was to highlight the cognitive deficits and social impairments of

SBM. To fully understand the cognitive deficits and their social implications, the neurological

basis of SBM needs to be reviewed. Several factors implement the neurological aspect of SBM.

One is the occurrence of hydrocephalus, the other is the Arnold-Chiari-II malformation which

also is the main cause of hydrocephalus. However, hydrocephalus can be present in this

population without Arnold-Chiari-II malformation, and the Arnold-Chiari-II malformation can be

present without hydrocephalus. Arnold-Chiari-II malformation primarily affects structures of the


hindbrain and midbrain. The cerebellum is severely deformed and the ventricular system of the

brain affected, partly because of a blockage caused by a displacement of the cerebellum

(Stevenson, 2004). Differences in the volume of gray matter may explain many of the cognitive

deficits. Reduction in volume of the hippocampus as well as enlargement of the putamen (Ware

et al., 2014), which are structures that are involved in learning, may give some answers regarding

the disabilities in this area. Furthermore, abnormalities in limbic fibers may contribute to the

learning and memory disabilities (Vachha et al., 2006). The presence of tectal beaking may be

linked to deficits in covert orientation of attention, and damage to posterior tectocortical white

matter pathways as well as decreased tectal volume may be a cause of attention deficits (Williams

et al., 2013).

The cognitive profile for children with SMB differs between individuals, although some

aspects have been suggested to correlate with the population with spina bifida. In the visual-

spatial domain children with SBM or spina bifida with hydrocephalus seems to be impaired on

coordinate perception, have severely limited route knowledge, and impairments on passive

functions of visual-spatial working memory (Dennis & Barnes, 2011; Mammarella et al., 2003;

Wiedenbauer & Jansen-Osmann, 2006). The knowledge of landmarks does not seem to be

impaired in these individuals which implies that an environment with more landmarks would be

beneficial for the navigation of individuals with hydrocephalic spina bifida. The findings

regarding active and passive components of visual-spatial working memory seem to contradict

the findings concerning landmarks. One would assume that landmarks would be a passive

stimulus and route knowledge an active stimulus. However, if landmarks are sequentially

memorized it could imply the use of an active component. Thus, future studies on the difference

between memorization of a single landmark and sequentially presented landmarks would add

clarity to this issue.


Problems regarding executive functions such as planning, problem solving, mental

flexibility and attention have been found. In planning, Rose and Holmbeck (2007) presented a

difference between two types of planning which were measured with two different scales. One

scale measured the social and behavioral manifestation of planning ability whereas the other

measured the ability to develop and rapidly execute problem solving strategies. However, this

statement is problematic since one of the measures also require problem solving skills. Problem

solving, by itself, has been found to be impaired in this population (Snow, 1999), for example

when testing problem solving in math and on the BRIEF scale (Dennis & Barnes, 2002; Rose &

Holmbeck, 2007). Children with hydrocephalic spina bifida have an impaired ability to respond

separately to a specific stimulus which is called focused attention (Rose & Holmbeck, 2007).

However, they do not seem to be impaired when it comes to the ability to maintain attention. This

later finding needs to be addressed further since it was found by using a questionnaire answered

by parents and teachers of the child and were thus not measured by actually testing the child’s

ability of sustained attention.

Concerning the learning disabilities which have been found to be present in 60% of the

sample in a study by Mayes and Calhoun (2006). It is interesting to note that the mean IQ was 89

and IQ was further controlled to be over 80, meaning that the sample were divided into two

groups based on having an IQ score over or under 80. The group with an IQ under 80 were not

included when studying learning disabilities in this study. The rather high prevalence of 60% may

be severely affected by the small sample of 23 children. Further studies should study the

prevalence of learning disabilities for this group, but with a larger sample, and include all

participants, and control for IQ but not exclude children with IQ under 80. Regarding IQ and

intelligence, PIQ is often reported to be impaired whereas VIQ and FSIQ are in the normal range

(Berker et al., 1992; Dennis et al., 1981; Donders, Rourke, & Canady, 1991; Fletcher et al., 1992;


Vinck et al., 2010). However, many of these findings are rather on hydrocephaly than on SBM

per se. Conversely, studies have found impairments on all three IQ measures when studying

children with SBM. This may imply that impairments on solely PIQ are associated with

hydrocephalus whereas the neurological deficits of SBM may affect VIQ and FSIQ as well.

Impairments of several aspects of social life for this population have been observed.

Children with spina bifida tend to have fewer contacts outside of school. This may be attributed

to their lower levels of psychosocial adjustments which are manifested in that these children

seem to be more socially immature, depend more on adults, do not initiate social contact as much

and are less engaged in social situations compared to healthy peers (Holmbeck et al., 2003).

Additionally, there might be a relationship between social difficulties in childhood and depressive

symptoms in adolescence (Holmbeck et al., 2003). Higher risk for depressive symptoms has been

found for adolescents with spina bifida (Appleton et al., 1997), thus making the relationship

probable.

This may be due to the cognitive deficits of pragmatic (or social) language (Fletcher et

al., 2002) and deficits in attention and executive functions (Rose & Holmbeck, 2007) which in

turn may be attributed to deficits in tectum and white matter connectivity (Williams et al., 2013).

Furthermore, a study demonstrates a relationship between SQoL and executive functioning (Barf

et al., 2010). The authors provide a discussion about this relationship, suggesting that

disadvantages in functions such as planning, attention or mental flexibility may affect social

situations where independent functioning is crucial. This especially regards new situations where

these children cannot rely on previously learned experiences (Barf et al., 2010).

The social domains of work and education seem to be severely affected by spina bifida in

several ways. It can be partly due to negative attitudes towards disabled individuals that still exist

in our society such as bullying, social isolation (Hayter & Dorstyn, 2013) or negative attitudes


from employers (van Mechelen et al., 2008). Relationships between level of education and

prevalence of paid work have been found, indicating that educational support is important (van

Mechelen et al., 2008). Unemployment seems to be associated with lower scores on VIQ, PIQ

and math skill which supports the previous statement. Several cognitive deficits might affect the

educational success of children with spina bifida, such as planning, problem solving, attention

and learning deficits. Regarding learning these children need extra support when it comes to

acquiring the basic math knowledge (Dennis & Barnes, 2002) as well as when it comes to sifting

out relevant information from less relevant information (Vachha & Adams, 2005). Limbic fiber

abnormalities may account for some of the learning deficits (Vachha et al., 2006). Children with

SBM may as well benefit from having support with planning of their studies. Furthermore,

deficits in written expression may imply a need for rethinking the way knowledge is tested in

these children. However, a sufficient way in testing knowledge in this population needs to be

studied. Written exams may be affected by deficits in written expression, multiple-choice may be

affected by deficits in sifting out information, and oral exams may be affected by deficits in

language.

Resilience seems to be negatively affected by medical stressors that come with this

condition (e.g., surgeries). Psychological distress may decrease levels of self-esteem and self-

compassion. However, higher levels of self-esteem and self-compassion are positively correlated

with higher levels of resilience (Hayter & Dorstyn, 2013). These finding may imply a need for

active work with self-esteem and self-compassion for individuals who have gone through several

medical stressors. Additionally, self-esteem may affect educational and vocational success as

well as social situations overall.

All findings in this thesis imply a link between SBM and the impaired social situation of

these individuals by describing the neurological deficits and its impact on cognitive functions.


However, there are some limitations of the studies on spina bifida that complicates their findings.

The terminology in this field is somewhat confusing with several terms for the same concept,

which makes it difficult to differentiate the types of spina bifida and what deficits are caused by

what. Some studies use the term spina bifida with hydrocephalus which do not differentiate

children with the occurrence of Arnold-Chiari-II malformation from those without. It is known

that Arnold-Chiari-II malformation is the main cause of hydrocephalus, but that there are cases of

spina bifida with hydrocephalus without this malformation although it is less common. That

hydrocephaly impairs cognition is known, but the effects of solely Arnold-Chiari-II malformation

is still scarcely studied. Further research on this subject should try to differentiate the

neurological deficits to find the specific profile for SBM. Furthermore, there are studies with

samples of various forms of spina bifida where no differentiation is made. It is important to be

cautious when drawing conclusions about the cognitive profile of spina bifida when some display

damages to the brain and some do not.

Conclusion

In conclusion, children and adolescents with SBM have, as a consequence of the neural

tube defect and Arnold-Chiari-II malformation, cognitive deficits that affect their social life and

education. Regarding education the cognitive deficits affect school related domains such as

learning. However, there are other aspects to educational success that these children need support

with. These domains concern planning, sifting information, problem solving and attention.

Therefore, knowledge about the whole picture of spina bifida is important to be able to provide

the best educational support for these children and adolescents. By developing an educational

support in the form of a mentor or coach that will meet with the child or adolescent once a week,

many of these weaknesses in school might be resolved. The coach can, for example, help the


child with planning and structure of their studies as well as being a support in the school

environment.


References

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders

(5th ed.). Washington, DC: American Psychiatric Publishing

Appleton, P. L., Ellis, N. C., Minchom, P. E., Lawson, V., Böll, V., & Jones, P. (1997).

Depressive symptoms and self-concept in young people with spina bifida. Journal of

Pediatric Psychology, 22(5), 707–722. doi:10.1093/jpepsy/22.5.707

Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of learning and

motivation, 8, 47-89.

Baier, B., Karnath, H. O., Dieterich, M., Birklein, F., Heinze, C., & Müller, N. G. (2010).

Keeping memory clear and stable – the contribution of human basal ganglia and prefrontal

cortex to working memory. The Journal of Neuroscience,30(29), 9788-9792.

Barf, H. A., Post, M. W. M., Verhoef, M., Gooskens, R. H. J. M., & Prevo, A. J. H. (2010). Is

cognitive functioning associated with subjective quality of life in young adults with spina

bifida and hydrocephalus? Journal of Rehabilitation Medicine : Official Journal of the

UEMS European Board of Physical and Rehabilitation Medicine, 42(1), 56–59.

doi:10.2340/16501977-0481

Barf, H. A., Post, M. W. M., Verhoef, M., Jennekens-Schinkel, A., Gooskens, R. H. J. M., &

Prevo, A. J. H. (2009). Restrictions in social participation of young adults with spina bifida.

Disability and Rehabilitation, 31(11), 921–927. doi:10.1080/09638280802358282

Barf, H. A., Verhoef, M., Jennekens-Schinkel, A., Post, M. W. M., Gooskens, R. H. J. M., &

Prevo, A. J. H. (2003). Cognitive status of young adults with spina bifida. Developmental

Medicine and Child Neurology, 45, 813–820. doi:10.1017/S0012162203001518

Barnes, M. A., Wilkinson, M., Khemani, E., Boudesquie, A., Dennis, M., & Fletcher, J. M.

(2006). Arithmetic processing in children with spina bifida: Calculation accuracy, strategy


use, and fact retrieval fluency. Journal of Learning Disabilities, 39(2), 174–187.

doi:10.1177/00222194060390020601

Bassuk, A. G., & Kibar, Z. (2009). Genetic Basis of Neural Tube Defects. Seminars in Pediatric

Neurology, 16(3), 101–110. doi:10.1016/j.spen.2009.06.001

Berker, E., Goldstein, G., Lorber, J., Priestley, B., & Smith, A. (1992). Reciprocal neurological

developments of twins discordant for hydrocephalus. Developmental Medicine and Child

Neurology.

Burmeister, R., Hannay, H. J., Copeland, K., Fletcher, J. M., Boudousquie, A., & Dennis, M.

(2005). Attention problems and executive functions in children with spina bifida and

hydrocephalus. Child Neuropsychology : A Journal on Normal and Abnormal Development

in Childhood and Adolescence, 11, 265–283. doi:10.1080/092970490911324

Cate, I. M. P., Kennedy, C., & Stevenson, J. (2002). Disability and quality of life in spina bifida

and hydrocephalus. Developmental Medicine and Child Neurology, 44(2000), 317–322.

doi:10.1017/S0012162201002146

Dennis, M., & Barnes, M. (2002). Math and numeracy in young adults with spina bifida and

hydrocephalus. Developmental Neuropsychology, 21(2), 141–155.

doi:10.1207/S15326942DN2102_2

Dennis, M., & Barnes, M. A. (2011). The Cognitive Phenotype Of Spina Bifida

Meningomyelocele NIH Public Access. Research in Developmental Disabilities, 16(1), 31–

39. doi:10.1002/ddrr.89.The

Dennis, M., Edelstein, K., Copeland, K., Frederick, J., Francis, D. J., Hetherington, R., Vinck, J.

M. (2005). Covert orienting to exogenous and endogenous cues in children with spina

bifida. Neuropsychologia, 43, 976–987. doi:10.1016/j.neuropsychologia.2004.08.012


Dennis, M., Fitz, C. R., Netley, C. T., Sugar, J., Harwood-Nash, D. C., Hendrick, E. B., &

Humphreys, R. P. (1981). The intelligence of hydrocephalic children. Archives of

Neurology, 38(10), 607-615.

Dennis, M., Hendrick, E. B., Hoffman, H. J., & Humphreys, R. P. (1987). Language of

hydrocephalic children and adolescents. Journal of Clinical and Experimental

Neuropsychology, 9(5), 593-621.

Dennis, M., Jacennik, B., & Barnes, M. A. (1994). The content of narrative discourse in children

and adolescents after early-onset hydrocephalus and in normally developing age

peers. Brain and Language, 46(1), 129-165.

Detrait, E. R., George, T. M., Etchevers, H. C., Gilbert, J. R., Vekemans, M., & Speer, M. C.

(2005). Human neural tube defects: Developmental biology, epidemiology, and genetics.

Neurotoxicology and Teratology, 27, 515–524. doi:10.1016/j.ntt.2004.12.007

Donders, J., Rourke, B. P., & Canady, A. I. (1991). Neuropsychological functioning of

hydrocephalic children. Journal of clinical and experimental neuropsychology, 13(4), 607-

613.

Fine, E. L., Horal, M., Chang, T. I., Fortin, G., & Loeken, M. R. (1999). Evidence that elevated

glucose causes altered gene expression, apoptosis, and neural tube defects in a mouse model

of diabetic pregnancy. Diabetes, 48, 2454–2462. doi:10.2337/diabetes.48.12.2454

Fletcher, J. M., Barnes, M., & Dennis, M. (2002). Language development in children with spina

bifida. Seminars in Pediatric Neurology, 9(3), 201–208.

Fletcher, J. M., Bohan, T. P., Brandt, M. E., Brookshire, B. L., Beaver, S. R., Francis, D. J., &

Miner, M. E. (1992). Cerebral white matter and cognition in hydrocephalic

children. Archives of neurology, 49(8), 818-824.


Fletcher, J. M., Copeland, K., Frederick, J. A., Blaser, S. E., Kramer, L. A., Northrup, H., …

Dennis, M. (2005). Spinal lesion level in spina bifida: a source of neural and cognitive

heterogeneity. Journal of Neurosurgery, 102(Pediatrics 3), 268–279.

doi:10.3171/ped.2005.102.3.0268

Gioia, G. A., & Isquith, P. K. (2011). Behavior Rating Inventory for Executive Functions (pp.

372-376). Springer New York.

Hayter, M. R., & Dorstyn, D. S. (2013). Resilience, self-esteem and self-compassion in adults

with spina bifida. Spinal Cord, 52, 167–171. doi:10.1038/sc.2013.152

Hetherington, R., Dennis, M., Barnes, M., Drake, J., & Gentili, F. (2006). Functional outcome in

young adults with spina bifida and hydrocephalus.Child's Nervous System, 22(2), 117-124.

Hiramatsu, Y., Sekiguchi, N., Hayashi, M., Isshiki, K., Yokota, T., King, G. L., & Loeken, M. R.

(2002). Diacylglycerol production and protein kinase C activity are increased in a mouse

model of diabetic embryopathy. Diabetes, 51, 2804–2810. doi:10.2337/diabetes.51.9.2804

Holler, K. A., Fennell, E. B., Crosson, B., Boggs, S. R., & Mickle, J. P. (1995).

Neuropsychological and adaptive functioning in younger versus older children shunted for

early hydrocephalus. Child Neuropsychology, 1(1), 63-73.

Holmbeck, G. N., Westhoven, V. C., Phillips, W. S., Bowers, R., Gruse, C., Nikolopoulos, T., …

Davison, K. (2003). A multimethod, multi-informant, and multidimensional perspective on

psychosocial adjustment in preadolescents with spina bifida. Journal of Consulting and

Clinical Psychology, 71(4), 782–796. doi:10.1037/0022-006X.71.4.782

Horn, D. G., Lorch, E. P., & Culatta, B. (1985). Distractibility and vocabulary deficits in children

with spina bifida and hydrocephalus. Developmental Medicine & Child Neurology, 27(6),

713-720.


Hunt, G. M., Oakeshott, P., & Kerry, S. (1999). Link between the CSF shunt and achievement in

adults with spina bifida. Journal of Neurology, Neurosurgery, and Psychiatry, 67, 591–595.

doi:10.1136/jnnp.68.6.800

Jacobs, R., Northam, E., & Anderson, V. (2001). Cognitive Outcome in Children with

Myelomeningocele and Perinatal Hydrocephalus: A Longitudinal Perspective. Journal of

Developmental and Physical Disabilities, 13(4), 389–405. doi:10.1023/A:1012289513829

Naglieri, J. A., & Das, J. P. (1997). Cognitive Assessment System.

Mammarella, N., Cornoldi, C., & Donadello, E. (2003). Visual but not spatial working memory

deficit in children with spina bifida. Brain and Cognition, 53, 311–314. doi:10.1016/S0278-

2626(03)00132-5

Mayes, S. D., & Calhoun, S. L. (2006). Frequency of reading, math, and writing disabilities in

children with clinical disorders. Learning and Individual Differences, 16, 145–157.

doi:10.1016/j.lindif.2005.07.004

McLean, J. F., & Hitch, G. J. (1999). Working memory impairments in children with specific

arithmetic learning difficulties. Journal of Experimental Child Psychology, 74, 240–260.

doi:10.1006/jecp.1999.2516

McLone, D., & Knepper, P. A. (1989). The cause of Chiari II malformation: a unified

theory. Pediatric Neurosurgery, 15(1), 1-12.

Merker, B. (2007). Consciousness without a cerebral cortex: a challenge for neuroscience and

medicine. The Behavioral and Brain Sciences, 30, 63–81; discussion 81–134.

doi:10.1017/S0140525X07000891

Northrup, H., & Volcik, K. A. (2000). Spina bifida and other neural tube defects. Current

Problems in Pediatrics, 30, 313–332. doi:10.1067/mpp.2000.112052


Ralph, K., Moylan, P., Canady, A., & Simmons, S. (2000). The effects of multiple shunt

revisions on neuropsychological functioning and memory. Neurological research, 22(1),

131-136

Ramsundhar, N., & Donald, K. (2014). An approach to the developmental and cognitive profile

of the child with spina bifida. South African Medical Journal, 104(3), 221.

doi:10.7196/SAMJ.8048

Rasmussen, S. A., Chu, S. Y., Kim, S. Y., Schmid, C. H., & Lau, J. (2008). Maternal obesity and

risk of neural tube defects: a metaanalysis. American Journal of Obstetrics and Gynecology,

198, 611–619. doi:10.1016/j.ajog.2008.04.021

Raven, J. C. (1996) Standard Progressive Matrices. Oxford: Oxford Psychologists Press.

Rekate, H. L. (1984). To shunt or not to shunt: hydrocephalus and dysraphism.Clinical

neurosurgery, 32, 593-607.

Riddle, R., Morton, A., Sampson, J. D., Vachha, B., & Adams, R. (2005). Performance on the

NEPSY among children with spina bifida. Archives of Clinical Neuropsychology, 20, 243–

248. doi:10.1016/j.acn.2004.07.004

Rose, B. M., & Holmbeck, G. N. (2007). Attention and executive functions in adolescents with

spina bifida. Journal of Pediatric Psychology, 32(8), 983–994. doi:10.1093/jpepsy/jsm042

Rourke, B. P. (1993). Arithmetic disabilities, specific and otherwise: a neuropsychological

perspective. Journal of Learning Disabilities. doi:10.1177/002221949302600402

Sawin, K. J., Brei, T. J., Buran, C. F., & Fastenau, P. S. (2002). Factors Associated With Quality

of Life in Adolescents With Spina Bifida. Journal of Holistic Nurcing, 20(3), 279–304.

Service, P. H., & States, U. (2004). Spina bifida and anencephaly before and after folic acid

mandate--United States, 1995-1996 and 1999-2000. MMWR. Morbidity and Mortality

Weekly Report, 53, 362–365. doi:10.1001/jama.292.3.325


Share, D. L., Moffitt, T. E., & Silva, P. A. (1988). Factors associated with arithmetic-and-reading

disability and specific arithmetic disability. Journal of Learning Disabilities, 21, 313–320.

doi:10.1177/002221948802100515

Shaw, G. M., Todoroff, K., Schaffer, D. M., & Selvin, S. (2000). Maternal height and

prepregnancy body mass index as risk factors for selected congenital anomalies. Paediatric

and Perinatal Epidemiology, 14, 234–239. doi:10.1046/j.1365-3016.2000.00274.x

Snow, J. H. (1999). Executive Processes for Children With Spina Bifida. Children’s Health Care.

doi:10.1207/s15326888chc2803_3

Stevenson, K. L. (2004). Chiari type II malformation: past, present, and future. Neurosurgical

Focus, 16(2), 1–7.

Suarez, L., Hendricks, K., Felkner, M., & Gunter, E. (2003). Maternal serum B 12 levels and risk

for neural tube defects in a Texas-Mexico border population. Annals of epidemiology, 13(2),

81-88.

Tew, B. (1977). Spina bifida children's scores on the Wechsler Intelligence Scale for

Children. Perceptual and motor skills, 44(2), 381-382

Tew, B. (1979). The “cocktail party syndrome” in children with hydrocephalus and spina

bifida. International Journal of Language & Communication Disorders, 14(2), 89-101.

Vachha, B., & Adams, R. C. (2005). Memory and selective learning in children with spina bifida-

myelomeningocele and shunted hydrocephalus: a preliminary study. Cerebrospinal Fluid

Research, 2, 10. doi:10.1186/1743-8454-2-10

Vachha, B., Adams, R. C., & Rollins, N. K. (2006). Limbic tract anomalies in pediatric

myelomeningocele and Chiari II malformation: anatomic correlations with memory and

learning--initial investigation. Radiology, 240(1), 194–202. doi:10.1148/radiol.2401050674


Wald, N., Law, M., Morris, J., & Wald, D. (2001). Quantifying the effect of folic acid. The

Lancet, 358, 2069–2073. doi:10.1016/S0140-6736(01)07104-5

Van Mechelen, M. C., Verhoef, M., van Asbeck, F. W. A., & Post, M. W. M. (2008). Work

participation among young adults with spina bifida in the Netherlands. Developmental

Medicine and Child Neurology, 50, 772–777. doi:10.1111/j.1469-8749.2008.03020.x

Ware, A. L., Juranek, J., Williams, V. J., Cirino, P. T., Dennis, M., & Fletcher, J. M. (2014).

Anatomical and diffusion MRI of deep gray matter in pediatric spina bifida. YNICL, 5, 120–

127. doi:10.1016/j.nicl.2014.05.012

Watkins, M. L., Rasmussen, S. A., Honein, M. A., Botto, L. D., & Moore, C. A. (2003). Maternal

obesity and risk for birth defects. Pediatrics, 111(5), 1152–1158.

doi:10.1542/peds.111.5.S1.1152

Wechsler, D. (1991). WISC-III: Wechsler intelligence scale for children: Manual. Psychological

Corporation.

Verhoef, M., Barf, H. A., Post, M. W. M., van Asbeck, F. W. A., Gooskens, R. H. J. M., &

Prevo, A. J. H. (2006). Functional independence among young adults with spina bifida, in

relation to hydrocephalus and level of lesion. Developmental Medicine and Child

Neurology, 48, 114–119. doi:10.1017/S0012162206000259

Wiedenbauer, G., & Jansen-Osmann, P. (2006). Spatial knowledge of children with spina bifida

in a virtual large-scale space. Brain and Cognition, 62, 120–127.

doi:10.1016/j.bandc.2006.04.003

Williams, V. J., Juranek, J., Stuebing, K., Cirino, P. T., Dennis, M., & Fletcher, J. M. (2013).

Examination of frontal and parietal tectocortical attention pathways in spina bifida

meningomyelocele using probabilistic diffusion tractography. Brain Connectivity, 3(5), 512–

22. doi:10.1089/brain.2013.0171


Vinck, A., Maassen, B., Mullaart, R., & Rotteveel, J. (2006). Arnold-Chiari-II malformation and

cognitive functioning in spina bifida. Journal of Neurology, Neurosurgery, and Psychiatry,

77, 1083–1086. doi:10.1136/jnnp.2005.075887

Vinck, A., Nijhuis-van der Sanden, M. W. G., Roeleveld, N. J. A., Mullaart, R. A., Rotteveel, J.

J., & Maassen, B. A. M. (2010). Motor profile and cognitive functioning in children with

spina bifida. European Journal of Paediatric Neurology, 14(1), 86–92.

doi:10.1016/j.ejpn.2009.01.003

Yazdy, M. M., Tinker, S. C., Mitchell, A. A., Demmer, L. A., & Werler, M. M. (2012). Maternal

tea consumption during early pregnancy and the risk of spina bifida. Birth Defects Research

Part A: Clinical and Molecular Teratology, 94, 756–761. doi:10.1002/bdra.23025

Documents

Cognitive Deficits in Spina Bifida - DiVA portal