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What are neurodevelopmental conditions? - Coggle Diagram
What are neurodevelopmental conditions?
What is a neurodevelopmental condition?
Conditions in which the development of the central nervous system is altered in some way (typically the brain)
Conditions of a biological, environmental or multifactorial origin which affect one or more major developmental systems
-> This includes social, motor, emotional, language and cognition
Apparent early in childhood (Riby & Van Herwegen., 2015) - consistent factors in all disorders, as NDCs are usually noted when a child does not reach typical developmental milestones
Diagnostic manuals - examples of NDCs:
Autism
ADHD
Intellectual disability (unknown origin, genetic disorders associated include Fragile X and Downs Syndrome)
Cerebral palsy
Tic disorders
Motor disorders
Conduct disorders
DSM-5 - Onset in the developmental period:
Range of developmental deficits from specific limitations to global impairments
Co-occurrence (ASD as an intellectual disability, ADHD as a specific learning disorder)
Symptoms of excess as well as deficits and delays
ICD-10 - Onset in infancy or childhood:
Developmental deficits pr delay linked to biological development of the nervous system
No remissions or relapse
Common causes (etiology) of NDCs
Biological - Known genetic differences in one or more genes:
Numerical chromosome variations - trisomy 21 (DS), Klinefelter's syndrome is trisomy of sex chromosomes (XXY) and Turner's syndrome is monosome (XO)
Structural chromosome variations - deletions, translocations and duplications
-> Cri du Chat syndrome, Prader Willi syndrome and Fragile X
Other non-genetic causes are also included in this
Environmental -
Prenatal - drug and alcohol use
Fetal Alcohol Spectrum Disorder (2% of births with FASD; McCarthy et al., 2017) - high co-ocurrence with ADHD and ADD (Weyrauch et al., 2017), but also with a range of NDCs
Perinatal - premature birth or oxygen deprivation during birth
Intellectual disability in children aged less than seven years born moderately and late preterm compared with very preterm and term-born children - 140 per 1000 v 10 per 1000 (22 v 43 weeks)
-> Hirovonen et al., 2017 - not enough time for brain to develop
-> ID prevalence decreases with gestational age
-> Male sex and born small for age also predicted increased risk
-> Also associated with intracranial haemorrhage, along with low umbilical artery pH, and smoking
-> No data on SES and educational level, and no information about viruses in vitro (could have confounded results
Cerebral palsy
Intellectual Disability in children aged less than seven years born moderately and late preterm compared with preterm and term-born children (nationwide birth cohort study) - Hirvonen et al., 2017
Multifactorial - no clear causal model, includes NDCs such as ASD and ADHD, which appear to have biological, neural and environmental causes
Medical v social causal models - Botterma-Beutel et al., 2021
Medical model -
Dichotomizes people as typical v atypical, and disabled v non-disabled
Differences to be evidence of deficits
Assumption that disability is inherently inferior to non-disability (advocates for cures via intervention where the individual is the centre of the condition)
Social model -
Socially valued differences in functioning or appearance, and disabilities
-> Environmentally mediated - emphasises loss of opportunity to participate in society
Focus on efforts to remove barriers to participation - society is the issue
-> Acknowledge impact of social barriers which do not explain all aspects of disability and recognise individual contributions in the context of a disabling society
-> Disabilities can be celebrated while still recognising differences and support needs
Terminology - Bottema-Beutel et al., 2021; Monk et al., 2022):
Avoiding Ableist Language: (Bottema-Beutel et al., 2020)
Language inherently makes people infer autism as a negative condition that needs curing
Language shifts -
-> Autism as a puzzle - part of neurodiversity
-> Autism as an epidemic - increasingly recognised / diagnosed
-> Prioritising passing - prioritising acceptance and embracing autistic identities
Ableist language in research presents a bias towards results, and represents a power structure - autistic input on wording means research is created to support the autistic community rather than portray it in a discriminative light
Small percentages of the autistic community, those with autistic relatives and healthcare professionals endorse the use of previous discriminatory terms
Not full consensus on some terminology such as identity v person first language, and so the preference of the individual must be focused on
Participatory research is recommended to involve autistic individuals in research to remove bias and increase inclusivity
Condition rather than disorder - removal of deficit language
Difference v dysfunction / deficit - thinking about strength-based approaches
Identity first language over person-first - can depend on population preference
Use of language in autism research: Monk, Whitehouse & Waddington (2022)
In the 1940s, autism was conceptualised as an atypical or abnormal behavioural pattern, leading to a medical model that saw it as curable or fixable
Challenged by self-advocacy and neurodiversity movements - autism seen as part of identity and natural human diversity
Focus on interactions between social barriers and autism - characterising as a neurological difference over a disorder creates more inclusive environments to enhance wellbeing and quality of life
Autistic scholars have argued for identity first language in research to erase negative associations
ASD -> autism, autistic; disorder is medicalised term
Person first -> identity first - autism is part of identity
-Autism symptoms and impairments -> experiences and characteristics
At risk of autism -> may have autism
Co-morbidity -> co-occuring
Functioning and severity -> specific support needs
Cure, treatment, intervention -> support
Restricted interests and obsessions -> specialised, focused or intense interests
Normal person -> allistic or non-autistic
These changes provide a more accurate description of the autistic experience and how to support autistic people more effectively:
Allows support such as different communication methods and upskilling people around them to remove social barriers
Avoidance in research of comparing autistic behaviour to animal models, because it does not correlate to the complex expression of autism
Terminology is highly individual in preference
Why do we need to research NDCs?
MQ Mental Health 2019 - neurodevelopmental conditions only get 13.6% of research grant funding in the UK
It helps us to have a clear understanding of diagnosis, etiology and understanding conditions, but the biggest need comes from translating research into application and support
Research improves our understanding of NDCs, making diagnosis more accurate and improving support
Increase in prevalence of autism (20 cases per 1000 to around 120) - no increase in incidence, but increase in ability to diagnose and understand it
Improve institutional care - 64,000 individuals were in care in the 1960s
-> This actually was historical segregation of people with learning disabilities (1940s-1970s) - poor quality of care, little integration, poor treatment and lack of support - eventually closed and people were reintegrated
It is fundamental to challenge misconceptions, raising awareness and improving integration and inclusivity - it should not be up to the parents to fight for support, their children should be entitled to it
Health inequalities - 2012 report from MENCAP found the NHS was still unsafe for people with a learning disability
Fetuses with Down Syndrome could still be terminated up until birth in 2021
DNRs given to those with learning disabilities at a higher rate during COVID (Guardian)
Williamson et al., 2021 - higher prevalence of deaths and admissions from COVID in those with learning disabilities
-> Risks of covid-19 admission and death for people with LD - cohort study (Williamson et al., 2021)
Issues with early death, inappropriate care at home and in healthcare
Research highlights these issues, identifies areas of support needed and evidences what good support looks like
Solves postcode lottery on support
Health Inequalities and people with learning disabilities in the UK (Emerson & Baines., 2011) -
High rate of unmet physical and mental health needs, higher mortality rate in early life, higher rates of some type of cancer, increased risk of fatal coronary heart disease (particularly in DS) along with respiratory disease
36% of children have an associated psychiatric disorder
Dementia risk is higher (22% v 6%), along with 20 times the risk of epilepsy
8-200 times as likely to have a visual impairment, 40% have a hearing impairment and those with DS are more likely to be at risk of vision and hearing loss (Carvill, 2001)
-> Those in home environments are less likely to have had an eye examination than those with living with paid support staff
-> Carers frequently fail to identity sensory impairments (Kerr et al., 2003; Warburg, 2001)
Higher likelihood of low oral and physical health, increased risk of dysphagia (Chadwick & Jollife, 2009)
More likely to have GORD and osteoporosis, endocrine disorders and diabetes
Those with learning disabilities are at significantly more risk of physical health issues - also increased constipation rates
Raising awareness and understanding in the community - SEND code of practice in 2015 made a legal right to mainstream education:
SEND white paper (2026) - emphasis on inclusion, by embedding support for SEND mainstream education
-> Issue - access to therapies?
-> Lack of funding to make this possible
-> Erases impact of possible early intervention for some needs e.g. speech and language
Advance and challenge our understanding of theoretical approaches to neurotypical development and neurodiversity
Modelling neurodevelopmental conditions -
Biological cause -> neurophysical difference -> cognitive endophenotype (e.g. social cognition) -> behavioural phenotype (e.g. autistic traits)
Last two moderated by environment
Criticisms of this approach (Pearson et al., 2021)
-> Medical / deficit model
-> Cognition is noted as a central cause - this is not always the case (discussion about cause - if there is no cure, is establishing a cause more important than support?)
-> It is possible the nature of the condition impacts the need to establish cause e.g. ASD has little physical symptoms associated compared to CdLS
-> Failure to address other areas of need
-> Translation to functional differences
(ISSUE) Challenges to causal models - Need more research to understand what typical development looks like, such as the formation of certain core systems (Spelke & Kinzler, 2007):
Number development - 6 month old infants can discriminate between large numerosities using an approximate number system, and this predicts mathematical ability later in life
Memory systems
Understanding this allows subtle differences to be spotted - for example, those with WS perform better on verbal number tasks, but worse on magnitude or approximate number system tasks; this is the opposite pattern to those with DS (Ansari et al, 2006)
Karmiloff e tal., 2012 - WS could not discriminate large numerosities, but infants with DS could; this predicted higher mathematical ability later in life
-> Therefore, this shows what typical development looks like and how intervention and training can be targeted to support different NDCs
(ISSUE) Changing from categories to scales - Most research is focused on mature adult brains and focuses on double dissociations (e.g. Absence of intellectual impairment where there is language impairment - SLI; the opposite pattern to WS - Pinker, 1999)
Recent research suggests it is framed as relative proficiencies and deficits
(ISSUE) - Better approaches needed - Cognitive ability studies show an atypical developmental pathway - typical infants point before words, WS children point after speaking (Laing et al, 2002)
Less clear how the infant brain is structured and how the endstate is the result of developmental processes (Karmiloff-Smith, Scerif & Ansari, 2003)
Specialisation of brain structures comes from interaction with the environment, genes, brain and behaviour (Thomas, 2003)
Research should favour developmental and neuroconstructivist approaches as a result due to brain plasticity
Develop improved intervention and support pathways for individuals and their families
Cornelia de Lange Syndrome - highlighted by research, more awareness and support available
Hall et al., 2008 - showed high incidence of ear, eye, dental and GI problems
Led to development of international guidelines (Kline, Moss & Selicorni et al., 2018) for diagnosing and managing it - using acid reflux treatment to help GI, noted as the cause of the SIB
Need for accurate diagnosis, issues of variability and comorbidity:
Some studies use different developmental cutoffs for conditions e.g. motor percentiles in DCD
Diagnostic criteria is updated constantly - autism diagnosis now has two instead of three areas of difficulty (communication and social interaction + restrictive behaviours)
-> Issues with comparing studies before and after diagnostic change - see Worley & Mason., 2012
-> Have both clinical and causal framework implications
Despite knowledge about genetic influence, there is still variation in the amount of deletion or it can be due to different sets of mutations
-> DS can sometimes have other mutations other than trisomy on chromosome 21
-> Still some breakage and deletion in typical individuals also - means disorders are less likely t be purely genetic
Variability:
Deciding if wide variation between a start and end point is normal or not for a condition (e.g. autism)
Large variability in cognitive and behavioural outcomes in NDCs such as ADHD, as not all have attentional control issues (Nigg et al., 2005)
SLI has a range of subgroups of ability that can change over time in the same individual (Conti-Ramsden & Botting, 1999)
Variability results in conflicting evidence and exists in TD population - cannot be solved by use of large sample as this is not always possible
Still need to investigate the source of variability its interaction between environment and genetic, and how variability affects diagnosis (argument for scales over categories)
Often phenotypical overlap between NDCs e.g. memory is involved in DS, but in older individuals it is unclear if it is Alzheimer’s onset or DS
Most individuals end up with dual diagnoses as a result, but although DS and CdLS individuals share behavioural characteristics with ASD, there are subtle differences
Need better theoretical knowledge in order to provide better interventions
Failure of cognitive ability could be cumulative, and theories of autism for example may explain deficit for one individual but not the other
Also need to take environmental factors into account
Translating research into practice
Bjork and Solomon (2013) - takes about 14 months for psychological papers to be published, and they often take a while to write and submit to peer review
Process of research is also slow, and often psychological papers would also need further study to confirm all areas of hypothesis
Research needs to be translated more efficiently e.g. by family support groups, conferences and podcasts to show research before it is officially published
Lay summaries are therefore accessible and vital to this - all people at these conferences, including individuals and families, need to understand the findings
Equally, it makes application quicker if information is communicated in this form
Better research design (issues facing this)
Recent studies involve wider age ranges, tracing development back and using narrow age matched group design
Also, basing on chronological age often underestimates the disorder group - mental age provides better results on a standardised task that are more valid
Longitudinal studies are the best but are often expensive and time consuming (recruitment hard due to rarity)
Cross-sectional preferred
-> Developmental trajectory has been criticised as well as cross-sectional for having outcomes different to longitudinal studies
They only provide snapshots of different groups, and thus individual differences can confound results
Have to be validated by a longitudinal study as a result
Also need wide age range to avoid ceiling and floor effects
Heterogeneity - not all people with a disorder follow the trajectory in the same way (co-occurrence!)
(ISSUE) - Focus on domain general activities:
Different disorders cause atypical use of domain-specific and domain-general mechanisms, such as WS using local processing for face recognition, compared to general processing used by NTs
Equally, domain-general performance may not be consistent across standardised tasks - a task for NTs and WS may not work for DS (Van Herwegen, Farran & Annaz, 2011)
-> Have to assess the ability being tested, and more understanding is needed regarding the impact of domain-general activities that may confound task results and make those tasks impossible to match or compare with
However, it is not always possible to identify which domain general abilities present early in life will have an impact later in life due to some disorders being harder to diagnose in early life (ASD, ADHD - behaviour driven diagnosis)
More research needed for at-risk children (such as siblings) to understand how genetic and environmental factors impact executive functioning
Little focus on brain plasticity - due to these populations struggling to access fMRI studies because of sensory or hyperactivity needs
EEG is the prominent method used, but there is poor spatial resolution for pinpointing areas of specialisation
Functional Near Infrared Spectroscopy is a bridging technique between these two which could help
Have to be hypothesis driven
Causal models of some NDCs (see notes for models
Characteristics of ASD in CdLS (Moss et al., 2026):
ASD related characteristics are common in CdLS with 3 in 5 individuals showing traits
Broad similarities but subtle differences, particularly in anxiety and repetitive behaviour
Differences are important in regard to intervention
Executive functioning in CdLS (Reid et al., 2017):
Greater working memory differences and flexible thinking compared to those with Down Syndrome - can explain heightened anxiety
Less memory for future events and change in day to day life
Age can affect this
Prevalence of ASD symptomatology and related behavioural characteristics in persons with Down Syndrome (Moss et al., n.d.)
ASD characteristics occur in 1 in 5 individuals with DS
Show different levels of ability and behavioural characteristics when conditions cooccur compared to those with DS who do not have ASD
Individuals with both have similar characteristics to those with ASD - subtle difference in some areas of behaviour
Angelman syndrome
Physical phenotype - hypermotoric and ataxic movement, epilepsy onset before 3, abnormal electroencephalography and distinct dysmorphic facial features (Van Buggenhout & Fryns, 2009)
Deletional AS has hypopigmentation also (Smith et al., 1996)
Neonatal - feeding difficulties and hypertonia are common
Microcephaly
Insensitivity to pain and UTIs
Social phenotype - strong drive for adult attention, high laughing and smiling and social approach to familiar and unfamiliar adults
Meet much of the ASD criteria, but have significantly higher social motivation and enjoyment compared to CdLS and higher than ASD
Cognitive phenotype - significant impairment in all aspects, particularly expressive language and this increases in deletion groups
Behavioural phenotype - drive for adult attention, hyperactivity, inattentive behaviour, high impulsivity, strong preference for sensory stimuli such as water and shiny / reflective objects
Attention - kinship theory; in AS the mother’s allele for maternal survival are not expressed (paternal allele is for offspring survival at cost to maternal survival), and thus this predicts higher demand on the mother such as adult attention, sleeping problems and high activity to increase gain for the child
Aggression three times as common - pulling or grabbing by the hair
Sleep disorders reported frequently, linked to the epilepsy in this population (limited intervention success)
Causal model - not established and mostly researched in infancy:
Genetics / biological cause
(gene and chromosome deletion on 15q11-q13) and physical phenotype - lack of expression of maternal UBE3A gene, leading to widespread white matter abnormalities (Harting et al., 2009), particularly the arcuate fasciculus, linked to language
-> Changes to cerebellum function and structure - linked to sleep laughing and smiling, as well as linked to thalamocortical projections and hippocampal long-term potentiation
LEADS TO
- Cognitive phenotype of poor language, dysregulation and emotion / impulsivity could be causal for behaviours of smiling, aggression, sleep, contact and attention to promote survival of paternal genes
-> Favourable theory due to the decrease in this with age, as need for resources to survive decreases
-
LEADS TO
- Smiling and laughing behaviours to preserve attention
-> Environment - High parental stress, need to communicate, attention reinforces this
Cornelia de Lange Syndrome
Physical phenotype - low birth weight, delayed growth, upper limb abnormalities, excessive hair growth and small head circumference, distinct facial characteristics, as well as gastrointestinal issues
Heart and kidney issues, hearing loss, vision issues, dental problems
Social phenotype - poor social relatedness, compromised social interaction autistic-like characteristics, social withdrawal
Cognitive phenotype - most have an ID, moderate IQ range
Behavioural phenotype - SIB, hyperactivity, autistic-like repetitive behaviours, low mood and impulsivity
Pain and discomfort associated with gastrointestinal disorders in CdLS have shown to impact on SIB (Luzzani et al., 2003)
Substantial improvement in rate and severity of SIB after intervention to help health problems - self-injury intends to remove perceived external causes of pain
Environmental impact on SIB - after SIB established by pain event, environment and conditioning leads to reinforcement of the behaviour
Low research on cognitive pathways underpinning social phenotypes which bear resemblance to autism, particularly on ToM tasks - greater impairment on memory, executive function tasks
This explains behaviours such as mood, challenging behaviour and social withdrawal
Preference for routine could therefore be a compensatory mechanism for anxiety and act as coping strategy in these environments
Outbursts are linked to sudden change, as this challenges executive functioning skills
Genetic mutations causing abnormality -> Compromised function of cohesin pathway and malformation of the gut and oesophagus -> cognitive and behavioural changes (downregulation of proteins leads to stress) including SIB
Also leads to pruning changes which impact cognition, and thus produce behaviours socially and give autism-like characteristics, such as deficits in ToM and executive functioning skills
Impaired neural repair also linked to EF, and this leads to behaviours favouring routine, sameness and social withdrawal
Environment then impacts these behaviours by influencing anxiety and this introduces challenging behaviours where the individual dislikes unpredictability and thus the behaviour is an escape mechanism
Smith-Magenis Syndrome
Physical phenotype - flat head, heavy brows, prominent forehead, heavy jaw, vision and hearing problems, infantile scoliosis and hypotonia
Social phenotype - attention seeking with a favourite person, strong social preferences, little interest in peers, aggression if no individualised adult attention
Some association with ASD characteristics
Cognitive phenotype - Moderate ID range, weakness in short term and sequential processing, and strengths in LTM and visual attention
Communication impairments such as speech delay - weakness in expressive over receptive language
Behavioural phenotype - SIB, aggression, elevated impulsivity and stereotyped behaviours, universal sleep disturbance, stereotyped repetitive behaviour
High caregiver stress from high rate of challenging behaviours
Strong humour and affectionate personality
Causal model -
Biological - peripheral neuropathy causes unpleasant feelings in extremities and reduced pain perception, leading to SIB, meaning physical discomfort is the driving function of this behaviour
-> Reduced pain awareness also means they are unaware of the cost of SIB
-> Aggression also has a communicative function over SIB
-> Environmental link to SIB - parental response to this is reinforcing the behaviour (similar to AS)
Biological - impairment in EF and neurotransmitters -> repetitive behaviours, no inhibition (observed in AS also)
Biological - inverted melatonin release and circadian rhythms -> sleep disturbance (clock gene disturbance)
Biological - lack of inhibition and inability to delay gratification lead to emotional aversion to waiting, and ventral striatum impact relates to impulsive behaviour
-> Also acts a risk factor for aggression
-> Daytime sleep may lead to disruptive behaviours
-> Environment - caregiver stress contributes to sleep-related behaviours
Biological - loss of RA11 functioning leads to health problems and physical impairments which produce challenging behaviour (aggression, SIB etc)
-> Possible cognitive endophenotype as cognitive pathways affected by this induce behaviour linked to lack of inhibition
Reciprocal environment effects from caregivers - behaviours induce stress in caregivers, but the response from caregivers also encourages behaviours that seek attention or gratification
-> Language deficits also lead to behaviours that express frustration due to lack of understanding and attention
Prader-Willi Syndrome
Physical - hypotonia, characteristic facial features, obesity, deficient growth hormones, excessive tiredness, scoliosis
Social - lower social competence, lack of facial emotion recognition, lack of understanding of social intent
Lack of oxytocin linked to this
Cognitive - normal IQ, but mild to moderate ID is common
Specifically STM and mathematical deficits, along with EF deficits
Different deletions can result in visual processing and verbal IQ differences, due to dorsal processing impairment and ventral processing depending on deletion
Behavioural - excessive eating, high repetitive behaviours (different profile to ASD and OCD) such as skin-picking, questions, sameness, and risk of low-mood disorders, temper outbursts linked to change
Challenges of causal modelling in autism (John Wiley & Sons, 2008)
Less variation at a cognitive level compared to biological - hard to start at biological level
Circularity in explanation - links to language in autism could contribute to other behaviours, or other causes could induce language impairment (varied language impairment across individuals also)
Circularity also seen with disturbance of affective contact - autism is defined by this, but also causes social disturbance
This induced the causal model which represents these circular instances
Biological origin -
Brain dysfunction at physiological and neurochemical levels - fMRI, cerebral spinal fluid investigations, brain stem potentials, presence of epilepsy etc
-> Unclear which damage is responsible, but those with autism have increased risk of diverse medical conditions
-> Indirect evidence of brain damage, such as ID - suggested that there is a specific brain system for normal development, and disturbing this results in autism
-> Basic causal model suggests there is an origin point of autism resulting in two different forms of brain damage, one of which causes the behavioural signs of autism (imagination, communication and repetition) and one which has consequences but no impact on behaviour
Biological causes are likely heterogenous (twin and family study evidence) and from developmental history
-> Strong genetic cause (Rutter et al, 1990; Rutter, 2000)
-> Viral disease also linked
This advances the causal model to include three biological origins, resulting in a number of brain abnormalities, affecting brain functioning, which then causes behaviours (multiple cortical systems contribute to behavioural profile)
However, final form includes a cognitive level - leading to a biological starting point, collating into a cognitive disturbance, producing separate defined behaviours
Causal models are not determinate, as most disorders result from differing combinations of the same pool of genes even though behaviours are consistent in appearance (not always in severity)
Causal models must accommodate core features and associated features - it also primarily focuses on primary features, rather than secondary features
For example, anxiety in autism is induced by behaviours such as resistance to change or misunderstanding of social cues
In autism, the cognitive element has long been theorised as this becomes the core source of the behaviour in the causal model
As a result, autism has variations in its causal model as it has developed and changed with assimilation of new theories
Debated if this is to do with mentalising (second-order) - Frith et al., 1991 (double-empathy problem to be considered)
However, it has since been suggested there are multiple cognitive deficits such as central coherence, EF and ToM as not all behaviours in autism can be explained by mentalising issues (repetitive behaviours for example)
Shah and Frith (1983) - superiority in hidden figures test, means mentalising does not explain all features of autism
This makes the causal model as follows - biological -> weak central coherence (leading to) + mentalising (cognitive) -> behavioural
Other models may have CC and mentalising on same level
Yoshkova, Moss & Farran (2026) - some observation of atypical gait in children with Williams Syndrome, more research needed to identify subtle cues of motor difficulty