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Applied Neuropsychology: Child
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/hapc20
From gifted to high potential and twice
exceptional: A state-of-the-art meta-review
Tatiana Desvaux, J. Danna, J.-L. Velay & A. Frey
To cite this article: Tatiana Desvaux, J. Danna, J.-L. Velay & A. Frey (04 Sep 2023): From gifted to
high potential and twice exceptional: A state-of-the-art meta-review, Applied Neuropsychology:
Child, DOI: 10.1080/21622965.2023.2252950
To link to this article: https://doi.org/10.1080/21622965.2023.2252950
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REVIEW ARTICLE
From gifted to high potential and twice exceptional: A state-of-the-art
meta-review
Tatiana Desvaux
a
, J. Danna
b
, J.-L. Velay
a
, and A. Frey
a,c
a
CNRS, Laboratoire de Neurosciences Cognitives, Aix-Marseille University, UMR 7291, Marseille, France;
b
CLLE, Universit
e de Toulouse, CNRS,
Toulouse, France;
c
INSPE of Aix-Marseille University, Marseille, France
ABSTRACT
Despite the abundant literature on intelligence and high potential individuals, there is still a lack
of international consensus on the terminology and clinical characteristics associated to this popu-
lation. It has been argued that unstandardized use of diagnosis tools and research methods make
comparisons and interpretations of scientific and epidemiological evidence difficult in this field. If
multiple cognitive and psychological models have attempted to explain the mechanisms underly-
ing high potentiality, there is a need to confront new scientific evidence with the old, to uproot a
global understanding of what constitutes the neurocognitive profile of high-potential in gifted
individuals. Another particularly relevant aspect of applied research on high potentiality concerns
the challenges faced by individuals referred to as “twice exceptional”in the field of education and
in their socio-affective life. Some individuals have demonstrated high forms of intelligence
together with learning, affective or neurodevelopmental disorders posing the question as to
whether compensating or exacerbating psycho-cognitive mechanisms might underlie their
observed behavior. Elucidating same will prove relevant to questions concerning the possible
need for differential diagnosis tools, specialized educational and clinical support. A meta-review of
the latest findings from neuroscience to developmental psychology, might help in the conception
and reviewing of intervention strategies.
KEYWORDS
Gifted; giftedness; high
potential; intelligence;
learning disorders; twice
exceptional
Aim and scope
The aim of this meta-review is to report and synthesize
important findings in the field of high intelligence research
putting into light their contribution to culture and termin-
ology shifts. In the first part of this paper, we report the dif-
ferent subtending models of high potentiality, notably the
behavioral models such as the psychometric and multidi-
mensional models and the anatomo-functional models such
as the cognitive and network models and discuss their con-
tribution to scientific terminology and culture related per-
ceptions. We then attempt to align the neural correlates of
this singular ability to epidemiological evidence on develop-
mental trajectories and discuss the implications of model
framework selection on research on high intelligence as well
as the gap to be breached to establish an overall picture on
the phenomenon of high potentiality.
In the light of the current rise in media interest regarding
the prevalence of high potential individuals facing academic
distress and soliciting professional and clinical assistance,
the second part of this review attempts to address the accu-
mulated epidemiological and scientific evidence available to
date on the specificities and neuro-cognitive mechanisms
underlying the co-occurrence of high potential and neurode-
velopmental disorders impacting learning.
Literature search strategy
For each section, reviews which were relevant to the topic of
interest and which were cited more than twenty times, were
identified from google scholar and Summon database with
selected filters and keywords as listed in the Appendix.
From there, sub-articles were selected for each section of the
paper, narrowing down the search to specific topics through
a secondary choice of keywords entered with conjunctions
“and”and “Or.”Only articles published in English and
French, cited more than twenty times and falling with the
limits of the first hundred listed articles were selected.
Where fields of research became highly specific, articles
cited more than 15 times were selected. Articles published
between 2000 and 2022 were selected except where historical
papers were cited. Our threshold for high intelligence in the
selection of articles was set at an FSIQ score 130 ± 5 on
the Wechsler scale for children or adults, although we took
into consideration, where applicable, variation in the inclu-
sion range for certain papers (for example in the case of het-
erogeneous profiles as defined by a difference of at least 23
points between the higher and the lower index score).
Articles were retrieved from November 2021 to August
2022, with review and editing in 2023.
CONTACT Tatiana DESVAUX Marie-christine.desvaux@etu.univ-amu.fr Laboratoire de Neurosciences Cognitives (LNC) –Aix-Marseille Universit
e, 3, place
Victor-Hugo, Marseille, Cedex 3 13331, France.
ß2023 Taylor & Francis Group, LLC
APPLIED NEUROPSYCHOLOGY: CHILD
https://doi.org/10.1080/21622965.2023.2252950
From gifted to high potential: a review of terms,
models and neural correlates
Definition and terminologies
Several definitions have been used to designate people with
exceptional abilities and historically, the terms “gifted”and
“talented”were used indistinctively to describe individuals
with outstanding skills in academic or nonacademic
domains (Carman, 2013; Ziegler, 2009; Ziegler & Raul,
2000). Galton (1869) is considered amongst the early investi-
gators of giftedness with his work on heritability of intelli-
gence traits. Several years later, the term “gifted”was used
for the first time by Terman (1925) in his longitudinal study
of children with high intellectual abilities. The upsurge of
psychometric testing and factorial analysis (e.g., Spearman,
1904; Wechsler, 1939) made “giftedness”synonymous to a
high intellectual capacity as demonstrated by elevated psy-
chometric test score results while the term “talent”became
by opposition ascribed to exceptional aptitudes that were
“non-IQ measured”(Gagn
e, 1985). Spearman’s conception
of a broad ability or general component of intelligence that
acts as a dominant latent variable for multiple cognitive
skills was challenged by Thurstone’s factor-analysis approach
(Thurstone, 1931,1975), segregating intelligence into seven
primary latent factors including reasoning, spatial visualiza-
tion, number facility, verbal comprehension, word fluency,
perceptual speed and associative memory. Cattell Horn-
Carroll’s model (CHC model) (Carroll, 1995) pushed the
cognitive model further with their three stratum theory of
intelligence, stratifying the third-factor general intelligence,
“g,”into a number of lower influencing second order-factors
of broad intelligence such as fluid intelligence, crystallized
intelligence, short-term memory (Gsm) and processing
speed (Gs) and the last stratum of minor or narrow ability
factors representing individual differences as measured by
cognitive tests. The stratification of general intelligence in
different aspects gave rise to a multidirectional conception
of intelligence, with aspects such as fluid or crystallized
intelligence subsequently shown to have different develop-
mental trajectories (Kent, 2017) with debated influence on
each other (Au et al., 2015; Unsworth et al., 2014).
While the CHC model advocates for an underlying gen-
eral ability, critics of “g-factor”have argued intelligence
should be perceived as being multi-dimensional rather than
being fruit of a general broad ability. Renowned models
include Sternberg’s triad for analytical, synthetic and prac-
tical intelligence or Gardner’s multiple intelligence models
(Gardner, 1993; Sternberg, 1985). Such theories proposed a
more encompassing approach to “high-abilities”including
dimensions such as creativity or socio-affective abilities and
have led the way to new conceptions of intelligence. Gagn
e’s
differentiated model of giftedness (Gagn
e, 2004,2010,2013)
has acknowledged the role of environmental factors and
chance in the process of converting an individual’s potential
into a developed skill and Renzulli’s three-ring conception
of giftedness (Renzulli, 1988) has recognized the importance
of motivation or commitment and creativity in the construc-
tion of gifted behavior. His model distinguished between
school-house giftedness characterized by high skills in test
taking and creative-productive house giftedness demon-
strated by individuals highly capable of producing original
material and products (Renzulli, 2011). By highlighting the
role and effect of learning, practice, motivation and of envir-
onmental factors on intelligence, their models contributed to
a terminology shift from “giftedness”to “high potential”on
the basis that exceptional “natural abilities”have the poten-
tial to turn into “talents”by the mediation of internal and
external factors (Stoeger et al., 2018) and by the interference
of socioenvironmental catalysts. Accordingly, “talent”soon
became perceived as the actualization of “high innate
potential”into “high performance”or “competence”such
that one could be of high potential without being talented,
while the opposite would be impossible (Nijs et al., 2014).
Such models allowed for the innate (nature) versus acquired
(culture) debate and contextualized the distinction between
subgroups of “high potential individuals”which could be
then end up to be “academically talented”or who could also
present disabilities in attentional, emotional or language
tasks such as reading and writing. These models, considered
to be more ecological to child development and education
have been adopted by many educational policies all over the
word, notably in North America and Australia (Heuser
et al., 2017).
In parallel, developmental research on the emergence of
differences in intelligence in high potential individuals have
taken into account the time dimension by showing that
mental processes and functions form quantitatively and
qualitatively as the individual transition through various
stages of cognitive development (Vraive-Douret, 2011;
Steiner & Carr, 2003; Reis & Renzulli, 2004). Such theories
have opened horizons to new integrative models attempting
to align stages of biological development of brain architec-
ture with the development of cognitive skills. Based on psy-
chomotor and linguistic evidence from longitudinal studies,
giftedness was soon associated with a precocious form of
ability development (Vraive-Douret, 2011) bringing the
terms “precocious children”to the jargon. Developmental
models have highly influenced the educational realm, where
precocious talking, reading, or walking was assimilated as an
indicator of giftedness.
These 21st century models have taken a complete over-
turn challenging the notion of general ability, interpreting
“g”as an emergent property arising from positive correla-
tions between test scores rather than a latent causal variable
(Conway & Kovacs, 2015). The Process Overlap Theory by
Kovacs and Conway (2019a,2020), presents g as a formative
construct that arises because cognitive tests are designed in
such a way that there could be an overlap of executive proc-
esses during tasks, that is they require the individual to tap
both into domain-general executive processes, such as atten-
tion control (Frischkorn & Schubert, 2018), as well as
domain-specific processes involved in specific tasks. This
paradigm shift has certain implications for the diagnosis of
high intelligence, where psychometric g has reigned for dec-
ades as the standard diagnosis tool. Novel theories argue
that IQ scores are merely weighted sum scores (Van der
2 T. DESVAUX ET AL.
Maas et al., 2014) and its utility should rather rely in the
separate indices which could provide an interpretation of
specific cognitive skills (Kovacs & Conway, 2019b).
The continuous evolution of models of intelligence has
brought not only new terminology, but has altered the con-
ception of what high intelligence or potential means. New
models of high intelligence have enriched psychological
diagnosis with supplementary evaluation tools, although
Psychometric g remains to date the official diagnosis tool of
giftedness (OMS), due to its empirical robustness (Deary
et al., 2010). As perceptions of high potentiality are cultur-
ally-influenced, these new models also seem to have directly
impacted the identification procedures, the direction and
philosophy of educational programs and interventions for
high potential children across countries (Pfeiffer, 2012).
Neural correlates of high intellectual potential (HIP):
from localized to distributed approaches
Perceptions on intelligence and models have also greatly
shaped functional and anatomical research. Highly intelli-
gent individuals are known to demonstrate higher levels of
performance in tasks requiring cognitive flexibility, inhibi-
tory control, working memory and planning (Fiske &
Holmboe, 2019; Vaivre-Douret, 2011). Under the postulate
of a broad general ability laying the foundation for intelli-
gence, research in neuroanatomy investigated the fronto-
parietal regions, already implicated from lesion studies in
the control of superior cognitive functions (Barbey et al.,
2012). Such studies have associated IQ scores with structural
correlates such as cortical thickness, gyrification, grey and
white matter volume and density in the fronto-parietal lobes
with correlation coefficient varying from 0.3 to 0.60 (Bajaj
et al., 2018; Choi et al., 2008; Ryman et al., 2016).
Functional studies have also demonstrated the implication of
the lateral prefrontal cortex in g-related tasks (Barbey et al.,
2013; Choi et al., 2008).
With the accumulation of neuroimaging evidence for a
distributed network of cortical regions involved in g-related
tasks and the rise of the CHC model emphasizing the con-
tributive role of secondary broad abilities such as working
memory, and processing speed, the localizationist approach
gradually gave way to the network approach to high intelli-
gence. The Parietal-Frontal Integration Theory (P-FIT)
(Barbey et al., 2012; Jung & Haier, 2007); a network media-
ting the integration of information between the frontal and
parietal cortices came of interest and was correlated to fluid,
crystallized, and spatial intelligence (Colom et al., 2009).
A central feature of the P-FIT model is the role of sub-
cortical connections, in particular white-matter fiber tracks
(WM)—an important contributor of processing speed and
working memory performance- in enabling efficient inter-
cortical region communication. Greater intra- and inter-
hemispheric connections in the fronto-parietal regions as
well as increase in myelination in the corpus callosum is
thought to contribute to the superior processing speed abil-
ity demonstrated by high IQ individuals (Luders et al.,
2007). Recently, diffusion tensor imaging carried out on a
population of children with high intellectual abilities demon-
strated a correlation of WM fiber-bundles as well as density
and homogeneity of WM brain networks with high intelli-
gence scores (Basten et al., 2015; Ryman et al., 2016;
Suprano et al., 2019).
Today, it is known that high IQ related tasks are sup-
ported by communications distributed across widespread
cortical regions, that include but does not limit itself to the
prefrontal and parietal areas but also interactions with basal
ganglia, between dorsal attention and default model net-
works (Gl€
ascher et al., 2010; Hearne et al., 2016; Jiang et al.,
2020; Santarnecchi et al., 2017). Research has also extended
its interest to structural differences memory systems of HIP
children and has shown that they are differently sized and
connected compared to the brains of typically developing
children (Amat et al., 2008). Such differences are thought to
contribute to superior working memory, differential learning
strategies and superior language capacity (Goriounova &
Mansvelder, 2019). Other scholars (Alnæs et al., 2018) have
veered their interests in the cortico-striatal-thalamic-cortical
circuit, suggesting that superior connections observed in
high IQ individuals could account for their higher anticipa-
tion and sensitivity to reward, henceforth altering their
learning abilities. Yet others (Pezoulas et al., 2017), have
investigated the cerebellum which bears numerous connec-
tions with the pre-frontal and posterior parietal brain lobes.
Recently, with the rise of advances in neural networks,
biological correlates of intelligence were sought in network
topology and efficiency. Under the network efficiency the-
ory, the brain needs to minimize the cost of information
processing by balancing competing constraints for local and
global efficiency. Local efficiency is supported in networks
by high spatial proximity of nodes as the reduction in aver-
age length of axonal projections conserves space and mater-
ial. This leads to higher signal transmission speed.
Conversely, long-distance connections cater for global, sys-
tem-wide function. Structural and functional studies have
linked intelligence to small world architecture which consists
of high local clustering as well as long-distance connections
of shortest path length to promote global information proc-
essing (Hilger, 2017; Kocevar et al., 2019; Suprano, 2019).
Sol
e-Casals (2019) found gifted children to have a more
integrated brain network topology as compared to chrono-
logically paired neuro-typical controls. Pezoulas et al. (2017)
compared resting state cerebellar functional networks
between high and low-IQ individuals and found them to be
more efficient in high IQ individuals. Interestingly papers
have also revealed gender differences in the organization of
brain networks (Allen et al., 2011; Szalkai et al., 2015;
Tomasi & Volkow, 2012). In their meta-analysis Hill et al.
(2014) argued that men tended to have a more distributed
gender specific network supporting working memory tasks
including regions of the cerebellum, portions of the superior
parietal lobe, and bilateral thalamus. Jiang et al. (2020),
demonstrated that in female subjects, functional connectivity
nodes (FC) in P-FIT regions as well as regions of the visual
word form area, implicated in low-level processes of letters
identification and high-level processes of word meaning
APPLIED NEUROPSYCHOLOGY: CHILD 3
were found to be better predictors of IQ in females, whereas
FC nodes in the lingual gyrus and subcortical areas such as
the basal ganglia, and thalamus (known to participate in
procedural leaning- a core component implicated in math-
ematical skills and spatial mnemonic processing), had a
more contributing power to IQ in males. Based on their
observations they discussed the possibility of males and
females capitalizing their most efficient cognitive processes
to induce their respective superiority in cognitive domains.
Lastly, global network dynamics approaches from the
field of network neuroscience are starting to investigate the
capacity of the brain to transition between functional net-
work states (rest or active) to enable rapid information
exchange. Barbey (2018) postulated that such phenomenon
could account for individual differences in information
processing and reflect general intelligence. Research in this
area falls into the framework of reflective models of “g”
such as the process overlap theory of intelligence, which
assumes that reflective “g”arises from the overlapping of
networks and from the modulation of its system-wide
dynamic states.
Recently Girn et al. (2019) and Langer et al. (2012) dem-
onstrated that the capacity to flexibly transition between
functional network states accounted for individual differen-
ces in crystallized and fluid intelligence. Schultz and Cole
(2016) who studied how functional connectivity (the tem-
poral correlation of activity between distinct locations in the
brain) was reconfigured from rest to an activated-task
related state, found that the efficiency of these updates in
brain network organization is positively related to general
intelligence. Individuals with higher scores of general intelli-
gence tended to have less brain network reconfigurations
between resting states and task related states and that this
association held for various cognitive networks except for
the motor system. This suggests that HIP individuals have
an intrinsic network architecture that can answer more effi-
ciently to various cognitive demands.
This network neuroscience approach to intelligence tran-
scends past attempts at explaining individual differences in
general intelligence with localized functional brain regions,
networks or the overlap among specific networks, but pro-
vides a basis for general intelligence that relies on the ability
of the brain to reorganize flexibly its intrinsic connectivity
networks, i.e., neuroplasticity. Undoubtedly, the novel
approach of investigating intelligence will shed the light to
new specificities in individual differences in human intelli-
gence and challenge our understanding of its neural bases.
Neurodevelopmental and cognitive trajectories of high
intelligence
While imaging and network studies confer a time-specific
capture of the structural and functional characteristics of the
high IQ brain, it must be pointed out that on a neurodeve-
lopmental perspective, the cognitive advantage of high IQ
children is thought to arise from a differential long term
dynamic process. In their longitudinal neuroimaging study
of cortical development in 300 children and adolescents,
Shaw et al. (2006) showed that if cortices of high-IQ group
started off as thinner at the younger age compared to con-
trols, by the time adolescence was reached, they had thick-
ened rapidly and significantly outgrew those the average-IQ
children, especially the prefrontal cortex. Same was demon-
strated by Navas-S
anchez et al. (2014), who found that
math-gifted adolescents presented thinner cortices that
chronologically-aged average IQ peers and large surface
areas in fronto-parietal regions, a phenomenon postulated
by them to be attributed by an above-age neural maturation.
Yet, one must not forget that in a population reported to be
highly inclined to invest themselves in training selectively in
areas of excellence structural divergences observed with con-
trols might reflect a combination of intrinsic (genetic) and
extrinsic factors (training). Takeuchi et al. (2011) for
instance demonstrated that mental calculation training could
impact grey matter in the frontal and parietal region.
The same follows for the development of processing
speed as might be conferred by differential development of
myelination. Early histological studies have shown that mye-
lination of neuronal axons follow a specific spatiotemporal
pattern throughout development and these have been corre-
lated to the evolution of cognitive and behavioral ability by
functional neuroimaging studies (Deoni et al., 2016; Nagy
et al., 2004). Although longitudinal studies investigated the
correlation between white matter myelination and structural
network development as a function of age in neurotypical
infants (Dai et al., 2019), same is difficult to explore in high
IQ individuals, due to the late nature of the diagnosis.
Further, one must take into account that myelination tends
to be activity dependent (Fields, 2015), which is difficult to
take into account during a punctual imaging study. If eluci-
dating the similarities of differences in the time-dynamic
differential trajectory of myelination in high potential indi-
viduals is of interest, especially in refining any sensitive win-
dows of development, the fact that intelligence is a complex
dynamic process influenced by socio-environmental, genetic
and molecular factors makes generalizations on the struc-
tural and functional neurodevelopment HIP population dif-
ficult if not impossible to make. The enterprise is even more
complicated by difficulties faced by researchers to gather
data early in development.
Indeed, scientific studies on the maturation of cognitive
functions in high potential infants and toddlers are scarce
and has for long been subjected to the bias of retrospectives
questionnaires as diagnosis typically comes in after language
acquisition. Yet, recent works on the contribution of infant
and early childhood competence in terms of attention and
executive function as predictors of adult cognitive abilities
and IQ scores builds in optimism that childhood measure-
ments could also provide sound grounds for elucidating the
developmental trajectory of high IQ individuals from
infancy (Blankenship et al., 2019; Wu et al., 2017). Rose
et al. (2012) for instance found that psychomotor speed,
attention, information encoding measurements in infancy
contribute to later competence at 11 years of age. If such
works support the early differentiation hypothesis, caution is
hence in order in discussing the chronological acquisition of
4 T. DESVAUX ET AL.
any cognitive advantage in the context of high potentiality,
especially considering that a study on HIP kinder-garden
children has shown that great variability prevails in meas-
ures of cognitive, and executive functioning at this age
(Hern
andez Finch et al., 2014).
Methodology-wise, it is also known that studying the cog-
nitive advantages conferred by the substrates of high intelli-
gence is delicate and requires careful task selection. For
instance in early studies high IQ individuals could some-
times not process sensory stimuli at an increased speed
compared to controls, and it was shown that results were
confounded by attentional resources (Bates & Stough, 1997).
In those studies where high IQ individuals did in fact dis-
play an advantage at processing sensory stimuli, Melnick
et al. (2013) have argued that only a relatively small propor-
tion of the variance in individuals IQ was explained by the
results. Using a low-level visual task, they demonstrated that
both processing speed and perceptual suppression strongly
correlated with IQ and that individuals with high IQ,
although faster at perceiving small objects, exhibited large
deficits in motion perception as stimulus size increased. By
conjecturing that not only information processing speed but
sensory suppressive processes constituted key bottlenecks in
both perception and intelligence, their study is one amongst
other that exemplify the complex nature of brain processing
systems involved in testing procedures and how difficult it is
to study same in children where the systems involved still
follow the course of typical or atypical developmental
trajectories.
Past studies by Jensen and Munro (1979), replicated by
Carlson and Jensen (1982), demonstrated negative correla-
tions between movement time (MT) and scores to the Raven
test in a test requiring participants to turn off a series of
lights as fast as possible. If such results suggest that high
potential children outperform controls in terms of overall
movement time little is known as to whether this advantage
is being conferred by globally more efficient functional net-
works subtending information processing and movement exe-
cution or if this advantage could be subtended by the
investment of superior cognitive processes directed at opti-
mizing procedural learning strategies. Interestingly, Spit and
Rispens (2019) found no significant difference in procedural
memory between high IQ children aged 8 to 13 and controls
at a serial reaction time task involving visuospatial sequence
learning. Further investigation in the area is needed, particu-
larly as to whether the advantage in Movement time of HIP
children persists in adults in tasks requiring different levels of
complexity of movement execution would prove informative.
Further, there is also little evidence as to whether high poten-
tial individuals bear differences in movement preparation and
execution as compared to age-related peers. Unfortunately
this lack of investigation possibly reflects the fact that models
of intelligence consider high motor performance, such that
those reached by high level athletes as not IQ-related talents.
The investigation of the cognitive advantages or bottlenecks
that might arise in HIP children during movement planning,
execution and automation is however not only relevant to the
field of physical education but also takes in importance in the
linguistic and educational realm, where handwriting is an
essential competency defining academic success (Dinehart,
2015). Understanding the developmental trajectory of sensori-
motor systems in young HIP children might shed the light
on how handwriting acquisition is automated in this
population.
Contrary to motor performance, executive function per-
formance and development in high potential individuals
have also been greatly studied, considered a possible con-
tributor to their superior performance in information proc-
essing and cognitive regulation. Authors have argued that
high performance at executive function contribute to aca-
demic success which has in turn fueled massive research on
the topic (Brock et al., 2009; McClelland & Cameron, 2019).
Categorized into three high order cognitive group of skills
(Diamond, 2013), namely, Working Memory—involved in
the recovery and processing of previous acquired knowledge,
Inhibitory Control—including both cognitive and behavioral
inhibition, and lastly Cognitive Flexibility comprising the
ability to evaluate, select and adapt multiple cognitive strat-
egies to achieve a purpose, executive functions have been
showed to develop prematurely in gifted individuals
(Bildiren, 2018; Vaivre-Douret, 2011). Johnson et al. (2003)
found high IQ children aged between six and eleven to score
higher on mental-attentional tasks and significantly demon-
strated higher effortful inhibition capacity during interfer-
ence loaded tasks. In their meta-analysis of 17 articles
comparing executive functions in gifted versus non-gifted
Rodr
ıguez-Naveiras et al. (2019) supported the verbal and
visual working memory superiority hypothesis in the high
potential group, yet warned against the effect of sample size
and WM testing tools. Such effects could yet again explain
the discrepancies in results.
Metacognitive and emotional profiles of high potential
individuals
Aside from information processing, executive control, and
regulation skills, research has also focused on metacognition
and emotional regulation and control of children with high
potential. Metacognition, as defined by the fields and neuro-
psychological and educational science, denotes one’s ability
to reflect on his or her cognitive processes and to adjust the
behavioral outcome accordingly. Many studies have demon-
strated that HIP children outperform average peers in meta-
cognition strategies (Berkowitz & Cicchelli, 2004; Oppong
et al., 2019; Snyder et al., 2011). Development-wise, research
has accumulated evidence that gifted individuals demon-
strate superior metacognitive skills as from the age of seven
(Annevirta & Vauras, 2006), although some argue that meta-
cognitive awareness might already appear in the HIP child
as early as in the preschool age (Barfurth et al., 2009).
As for the development of emotional skills and profiles of
HIP individual, there is still to date, no clear consensus on
how emotional intelligence (EI) should modeled, measured
and how it is correlated to cognitive intelligence (Zeidner &
Matthews, 2017; Zeidner et al., 2003). Currently, there exists
two main models of EI: one ability-based measured by
APPLIED NEUROPSYCHOLOGY: CHILD 5
performance tests at perceiving, assimilating, understanding
and managing emotions (e.g., Mayer–Salovey–Caruso EI
Test (MSCEIT); Mayer et al., 2003), and another perspective
conceptualizing EI as a non-cognitive attribute, encompass-
ing affective, motivational and personality traits and best
measured by self-reports such as the Schutte Self-Report
Inventory (SSRI) (Murphy & Janeke, 2009).
Under the first model, EI being a cognitive trait should
demonstrate a positive manifold and correlate with other
psychometric measures of intelligence, while being distinct
from other sub-factors of g. One study, proposed by
MacCann (2010) reported that EI could indeed measure a
kind of intelligence by constituting a latent factor distinct
from fluid and crystallized intelligence (Gc, Gf). Yet its
strong correlation with “Gc”(Gc/EI: r ¼.71) posed the
question as to whether the abilities measured constitute a
new form of intelligence or whether they could be consid-
ered a different for “Gc.”On the same trend, authors have
postulated that EI should be related to both crystallized ver-
bal ability, in that it relies on the accurate identification and
naming of emotions for the establishment of a coping strat-
egy, and on fluid ability of reasoning in the implementation
of self-regulation mechanisms in the face of new emotionally
loaded situations (Kong, 2014; Zeidner et al., 2005). Yet evi-
dence of same is lacking (Zeidner & Matthews, 2017), and
Zeidner et al. (2005) demonstrated that individual differen-
ces in EI are measure dependent, gifted students scoring
higher on MSCEIT tests when compared to controls but
lower on the SSRI tests. To date, there is no consensus as to
whether being intellectually gifted provides a cognitive
advantage at emotional intelligence.
To make matters more complex, mass media has nour-
ished the stereotype that high intelligence is associated with
emotional and social difficulties. The gifted child is por-
trayed as the bearer of intense emotion, hypersensitive and
aloof in his social relations, some even arguing that such
constitutes the psychological profiles of the gifted popula-
tion. While scholars today tend to agree that high potential
individuals do not present emotional deficits (Ogurlu, 2021),
results from studies focusing on the emotional and social
behaviors of this population vary greatly mostly due to
methodology. Peyre et al. (2016) found no significant differ-
ences in sensitivity analyses between their 23 gifted pre-
school children aged from 5 to 6 years compared to
controls. Conversely, Gere et al. (2009) stipulated that based
on the responses of parents to the Dunn’s(1999) Sensory
Profile questionnaire, gifted children group demonstrated
heightened emotional responses and sensitivity to their
environment. The same issue arises in studies on anxiety in
gifted children, some authors reporting increased anxiety
among gifted children presumably because of their height-
ened sensitivity and hyper-acuity, others found reduced anx-
iety levels, attributed to protective factors such as better
coping mechanisms (Chuderski, 2015; Zeidner & Shani-
Zinovich, 2011), and yet others found no link (Gu
enol
e
et al., 2013).
Considering the rise of reports of depression and social
isolation in gifted children, it is not surprising that the
psychological well-being of the population is thoroughly
investigated, though yet again literature on psycho-cognitive
profiles of HIP individuals has a long history of conflicting
evidence. The perpetuation of the scientific blur on the psy-
cho-cognitive profiles of gifted individuals despite giftedness
being one of the most investigated topics in cognitive and
neuropsychology is astounding. Indeed, recent authors have
attempted to explain the contrasted data by possible meth-
odological biases brought about by small sample sizes,
unclear high potential definitions and non-validated assess-
ment tools in past publications. As discussed below, it is
important hence that future research attempts to account for
those artifacts if progress on the topic is not to be hindered
by false interpretations.
Identification of high potential individuals: threshold
issues, heterogeneous sub profiles and sampling bias
The discrepancy observed in literature with regards to stud-
ies on high potential individuals has engendered much ques-
tioning about the identification and inclusion methods used
in the scientific publications. Despite, international consen-
sus for HIP diagnosis to be defined by a minimum score of
130 on the Wechsler’s scale, identification tools for high
potential individuals in scientific research vary as some
authors argue for the superiority of other intelligence tests
related to their robustness against cultural and educational
influence (Pfeiffer & Blei, 2008; Renzulli, 2012; Sternberg,
2003,2016). Others, have questioned the varying strategies
applied to sample inclusion and exclusion scores in research
methods, as some scholars prefer to set the threshold inclu-
sion limit below an FSIQ of 130 to account for the margin
of error (Silverman, 2018).
Another confounding factor includes high variability
between indices of the IQ test scores. If a dispersion of 12
points between the highest and the lowest index is consid-
ered a frequent phenomenon (40% of the general popula-
tion), a difference of 23 points is only reached by 8% to
18% of the population and is considered to constitute a het-
erogeneous profile. Some authors have argued that children
with heterogeneous profiles could be part of a distinct sub-
group of HP population displaying distinct vulnerabilities
and risks (Gu
enol
e et al., 2015). Vaivre-Douret (2011)
argued for instance that precocious maturation of sensori-
motor functions would appear between the ages of 0 and
36 months in HP individuals with homogeneous IQ profile,
whereas psychomotor asynchrony, as described by Terrassier
(1979) would more likely appear in heterogeneous profiles.
Boschi et al.’s study (2016) found that the homogeneous
HIP children outperformed the heterogeneous HIP children
in memory and motor skills at school age. Nusbaum et al.
(2017) showed that neural substrates differed homogeneous
high IQ and heterogeneous high IQ individuals, with a left
hemispheric lateralization distinctive of heterogeneous high
IQ individuals who frequently demonstrate high verbal indi-
ces. Suprano et al. (2019) who used graph theory to com-
pare brain networks of HP children also found differences
in network topology between the two sub profiles of
6 T. DESVAUX ET AL.
homogenous and heterogeneous IQs (based on verbal com-
prehension index and perceptual reasoning index).
While evidence is accumulating in favor of a distinctive
cognitive profile for HP-heterogeneous the question arises as
to the possible risk factors it could constitute to academic
achievement. If underachievement occurs across all academic
populations, gifted or not; gifted underachievers are for their
part operationally defined by negative deviations on the
regression of school achievement on general intelligence
(Gilar-Corbi et al., 2019). Counselors as well have argued
that HP children in academic distress tend to demonstrate
negative attitudes toward learning and school, a negative
self-concept as well as emotional and behavioral problems
(Blaas, 2014). Of course, the underlying mechanisms of
underachievement in gifted population are complex and
multidimensional yet it is interesting to note that individual-
based risk factors such as motivation and self-regulation are
implicated in gifted students’learning and well-being (Al-
Dhamit & Kreishan, 2016). Knowing that a more heteroge-
neous IQ-profile puts high potential children at greater the
risk of adaptation and learning difficulties, it is hence legit-
imate to question the prevalence of such profiles in aca-
demic underachievers.
This would prove to be ultimately critical if the same
population ended up seeking clinical help for diagnosis and
intervention. Already, many have warned against the sam-
pling bias and perception bias that could occur in studying
HP individuals known to therapists and extrapolating obser-
vations to the general HP population. More often than not
HP individuals who come to be known to relevant
authorities also present confounding comorbidities such as
neurodevelopmental disorders (dyslexia, developmental
coordination disorders—DCD and/or ADHD) or socio-
affective disorders (autism, depression) and their close rela-
tives (parents, teachers) are already sensitized, desperate or
burdened by their behavior making rating surveys and ques-
tionnaires difficult to interpret objectively (Pfeiffer, 2015).
Also, little is known to date on the relative prevalence of
homogenous versus heterogeneous profiles of HP individuals
known to clinical support systems and such investigations
should be carried out to eliminate risks of over extrapolating
specific cognitive attributes of a subgroup to the general HP
population.
Twice exceptional HIP children
Over the past decades a subgroup of the gifted population,
has been the subject of increased attention from educators
and practitioners: the “twice-exceptional”or 2E. The term
designates individuals who simultaneously possess a high
ability and a learning, emotional, physical, sensory and/or
developmental disability (Foley-Nicpon et al., 2011; Foley-
Nicpon et al., 2013). While consensus on the term is not yet
reached in research, it is widely used in education as the
label “exceptional”was already used to designate children
with exceptional ‘strengths’or exceptional “weaknesses.”If
research has for long focused on “learning disabilities,”leav-
ing other forms of disabilities (emotional, sensory, physical
and developmental) pending, works from Foley Nicpon
et al. (2011) and Foley-Nicpon et al. (2013) have shown that
giftedness in students could be paralleled with deficits in
attention, social awareness, thereby encompassing autism
spectrum disorders (ASD), specific learning disabilities
(SLD), attention deficit hyperactivity disorder (ADHD), and
emotional disturbances (ED) in the 2e group. According to
Ronksley-Pavia (2015), an extensive research gap in the lit-
erature is still to be breached regarding children with other
exceptionalities.
If in the field of education, the prevalence of 2E is now-
adays internationally recognized, in what ways does the cog-
nitive functioning and do the neural substrates of 2E differ
or resemble those of purely gifted individual (or those with
the isolated disability) is still debated, given the difficulty of
assessing the comorbidity effect (Foley-Nicpon et al., 2010).
Further, the occurrence of 2E puts at test current models of
intelligence and reliance on medical models fail to provide a
clear boundary between gifted/non-gifted and disabled/non-
disabled. Indeed, the spearman’s model of a broad ability
(1904) cannot account for gifted individuals having intellec-
tual disabilities. While models such as Gardner’s(1983,1993)
or Gagn
e’s(1995) tend to be more accommodating since
high ability in one area does not imply corresponding abil-
ities in others, dynamic models considering the spectrum of
possible interactions at the interface between giftedness and
disability are scarce.
For long, the observation and diagnosis of twice-excep-
tional children was difficult, as high abilities were thought
to compensate for the expression of the disability and con-
versely that disabilities could be hidden by giftedness. This
interplay between cognitive “strengths”and “weaknesses,”
referred to as the “masking effect (Assouline et al., 2010),
has been speculated to be an underlying mechanism explain-
ing the differentiated performance of the 2E population
compared to the gifted or disabled under certain tasks.
Currently opposite views argue that 2E individuals display
distinct cognitive profiles from gifted individuals or disabled
individuals that is not the result of a simple additive or sub-
tractive effect. Same will be discussed with regards to spe-
cific learning and neurodevelopmental disorders.
Dyslexia and high potential
Dyslexia is a learning disability which arises in 7% of chil-
dren across cultures (Goswami, 2022) which is characterized
by difficulties in reading fluently despite normal intelligence
and in the absence of sensory deficits in vision or hearing
(American Psychiatric Association, 2000). Phonological skills
which include various abilities such as phonological memory
(verbal short-term memory or VSTM), rapid automatized
naming (RAN) or phonological awareness (PA), are now-
adays known to participate considerably in the acquisition
of literacy (Ara
ujo & Fa
ısca, 2019; Norton & Wolf, 2012)
and that deficits in such skills underlie the difficulties pre-
sented by dyslexia (Goswami, 2011; Ramus et al., 2003).
According to Tallal’s theory (1980) on the mechanisms of
dyslexia as was supported by numerous subsequent studies,
APPLIED NEUROPSYCHOLOGY: CHILD 7
children with dyslexia present deficits in the temporal proc-
essing of speech at the basic auditory level which is due to
an inability to assimilate sensory information delivered
rapidly.
A more recent theory, “temporal sampling theory”
(Goswami, 2011) argues that the successful representation of
the different temporal rates and amplitude modulation of
complex speech signals requires the efficient sampling of the
speech stream by auditory cortical networks. These are
mediated by the emergence of specific cortical networks
oscillatory frequencies operating at different time scales
(Giraud & Poeppel, 2012; Leong & Goswami, 2014; Poeppel,
2003). According to the theory, children with dyslexia could
present difficulties in specifying linguistic units such as sylla-
bles, because of atypical oscillatory sampling at one or more
temporal rates. Further, some authors (Casini et al., 2018);
Gori & Facoetti, 2015; have postulated that temporal sam-
pling deficits might extend to the visual modality based on
studies relating dyslexia to impairments in the magnocellu-
lar-dorsal (M-D) pathway (Gori et al., 2014,2016) known to
be sensitive to rapidly changing information. From their
results showing that children with dyslexia exhibit a larger
perceptual variability when doing temporal tasks involving
both the auditory and visual modality, Casini et al. (2018)
argued that time perception could be implicated in dyslexia
with an atypical functioning of the ‘internal clock’of dys-
lexic children.
The investigation of the impact of high potentiality on
dyslexia is quite new, yet two theories prevail. The first pre-
sumes that the core deficits in phonological processing asso-
ciated with dyslexia are unaffected by intelligence.
According to the core-deficit view, high ability in more gen-
eral skills cannot compensate for deficits in the phonological
processes underlying word reading, although they are prob-
ably beneficial for reading comprehension (Van Viersen
et al., 2015). Under this hypothesis, high potential individu-
als would hence demonstrate comparable deficits in core
processes such as phonological awareness (PA), verbal short-
term memory (VSTM), and rapid automatized naming
(RAN) to those by non-HP dyslexics. Tanaka et al. (2011)
compared differences in brain activations during a phono-
logical processing between poor readers with high IQ and
low IQ and found that both groups showed reduced activa-
tion in brain areas such as left parieto-temporal and occi-
pito-temporal regions, suggesting that phonological deficit
could be independent of IQ.
Proponents of the opposite theory argue that the presence
of an intelligence-related cognitive strength relevant for liter-
acy (e.g., working memory demonstrated by Alloway et al.
(2009) as a factor of academic progress in the acquisition of
literacy) can provoke or stimulate the emergence of com-
pensatory mechanisms that could help circumvent underly-
ing dyslexia-related deficits or subdue their negative effect
on literacy development (Van Viersen et al., 2016). Indeed
within the framework of the “deficit in temporal processing
of speech at the basic auditory level model”of dyslexia, it
could be that compensatory mechanisms related to superior
sensory information processing skills are at plays in HIP
individuals. Van Viersen et al., 2017 investigated same and
found HP individuals with dyslexia to perform in between
children with dyslexia and TD children, with deficits in PA
and RAN but strengths in VSTM, WM suggesting that a
compensating mechanism might indeed occur. Berninger
and Abbott (2013) found that this compensation could yet
again be dependent on HP profiles as twice exceptional stu-
dents with average verbal reasoning and dyslexia demon-
strated significantly lower reading, spelling, morphological,
and syntactic skills than students with high verbal reasoning
and dyslexia. In the framework of “temporal sampling the-
ory of dyslexia,”little is also known as to whether the mech-
anisms underlying the temporal sampling of speech are
preserved or deteriorated in individuals with high IQ.
Developmental coordination disorder (DCD) and high
potential
Conferring to the DSM-5, DCD is a neurodevelopmental
disorder that induces deficits in the acquisition and execu-
tion of coordinated fine and gross motor skills compared to
age-related peers. With a prevalence of that 5–6% in school
aged children and about half of the early diagnoses persist-
ing through adulthood, DCD, can considerably impairs
quality of life depending on the severity of the symptoms
(Biotteau et al., 2019; Kirby et al., 2014). Children with
DCD frequently display handwriting difficulties which
impairs academic life (c). Poor c has been shown to be a
risk factor for obesity and depression (Karras et al., 2019).
Unfortunately, the prevalence of DCD in gifted children has
not been investigated much. In children who have portrayed
as typically preferring intellectual tasks and having reduced
interest in motor-related activities, little is known as to
whether the effect of reduced practice, motivation is detri-
mental or even influential in the case of DCD.
Functional neuroimaging works have started to investi-
gate the neural bases of DCD: Zwicker et al. (2011) demon-
strated that children with DCD showed reduced bold signals
in cortical regions associated with skilled motor practice
amongst which the bilateral inferior parietal lobules, right
lingual, middle and middle-frontal gyri, the left fusiform
gyrus and cerebellar areas compared to non DCD controls.
Fuelscher et al. (2018) showed a differentiated activation
pattern of brain areas in manual dexterity tasks. Yet no such
works exist to clarify the influence of IQ or what possible
compensation mechanisms, if any, that high cognitive func-
tion might infer.
While studies have shown the correlation of motor impair-
ment severity and IQ in the context of Autism (Kaur et al.,
2018; Surgent et al., 2021), few studies have investigated same
in the context of DCD. One of the few, carried out by
Vaivre-Douret et al. (2020) found slightly less severe DCD
symptoms in certain areas, notably ideomotor and Visio-
Spatial/Constructive tasks in high IQ groups with DCD
compared to controls. The cognitive functioning of high IQ
children with DCD was found to vary from controls, with a
better performance executive functioning and visio-spatial
skills but lesser performance in auditory attention and
8 T. DESVAUX ET AL.
memory tasks. Recently, He et al. (2018) demonstrated that
interhemispheric M1 cortical inhibition is impaired in a small
sample group of eight adults with DCD compared to controls
while intrahemispheric M1 inhibition is preserved. It would
be interesting to know if such mechanisms are preserved in
HP- DCD groups who are known to have enhanced interhe-
mispheric frontal connectivity between the dorsolateral pre-
frontal and premotor cortex (Prescott et al., 2010). Today
little is known as to whether the sensorimotor processing
advantages typically displayed by HIP individuals compensate
for deficits brought about by DCD.
Attention deficit-hyperactivity disorder (ADHD) and high
potential
Defined by the DSM-V attention deficit-hyperactivity dis-
order (ADHD) is a neurodevelopmental disorder that affects
between 2% and 7% of individuals in their childhood (Sayal
et al., 2018). Established as a risk factor for other mental
health disorders, and correlated to negative outcomes in life
such as academic underachievement, poor employability,
social distress and criminality, diagnosis and intervention on
ADHD has raised many concerns over the past decades. The
diagnosis is based on the observations of 18 symptoms cate-
gorized into two main focal groups of inattention (IA) and
hyperactivity-impulsivity (HI). There are three subtypes of
ADHD: the predominantly inattentive type, the predomin-
antly hyperactive/impulsivity type, and the combined type.
For long, the validity of the diagnosis of ADHD in gifted
children has not been recognized, as proponents of the
Da˛browski’s theory (1967) had assimilated giftedness with
five types of over excitability, of which a psychomotor over
excitability making them hyperactive, impulsive, and inatten-
tive by nature, rather than being due to ADHD symptoms.
Other authors argued that gifted children displayed ADHD-
like symptoms at school only due to boredom. Today, sev-
eral reviews and works (Minahim & Rohde, 2015; Mullet &
Rinn, 2015) have provided empirical evidence that ADHD
can coexist with high intelligence. As for the particularities
of being both ADHD and HIP, research is now focusing on
elucidating the protective vs. risk factors, or similarities vs.
differences to ADHD in the gifted population. Two hypothe-
ses have prevailed: the twice-exceptional theory in this line
of work (Budding & Chidekel, 2012) postulated that gifted
children would be at greater risk for more severe IA and HI
symptoms, based on the over excitability theory mentioned
above, while the cognitive reserve concept whereby high IQ
would act as a protective factor and reduce the severity of
ADHD symptoms (Minahim & Rohde, 2015). A recent
study by Gomez et al. (2020) found that for most ADHD
symptoms, the results did not uniformly support either the-
ory. Indeed, aside from the observation of significant differ-
ences in a few HI symptoms, severity was not different
across ADHD-gifted or ADHD-non gifted groups, putting
the twice exceptional theory into perspective. In the same
vein, while inattention was less prominent in gifted ADHD
children when compared to non-gifted ADHD controls
same was not observed across all symptoms, thereby not
fully supporting the cognitive reserve concept. The authors
suggested that specificities between ADHD gifted children
and non-ADHD gifted children might not be generalized
but would appear solely on specific HP behaviors (verbal
and motor activity modulation and reflective capacity on
questions) which would act as a basis for adapted diagnosis
in the ADHD-gifted population.
High functioning autism and high potential
High functioning Autism (HFA) is a developmental disorder
that forms part of the autism spectrum disorder (ASD), with
specific deficits in social interactions and the demonstration
of restricted or repetitive interests or behavior without
impairment in language, adaptive skills and cognitive func-
tioning (American Psychiatric Association, 2000). Decades
ago, authors who have investigated the scoring patterns of
HFA-Gifted population to psychometric tests such as
Wechsler Adult Intelligence Scale–Third Edition (WAIS-III)
have found that the population tended to exhibit distinct
characteristics, notably weaknesses in graphomotor and
processing speeds as demonstrated by lower scores to the
Digit-Symbol Coding and Symbol Search subtests and visual
and verbal reasoning strengths as showed by higher scores
to the Perceptual Reasoning Index (PRI), verbal comprehen-
sion index (VCI) Information and Matrix Reasoning subtest
(Foley-Nicpon et al., 2012; Mayes & Calhoun, 2008). These
variabilities across test scores have been argued to impact
significantly final IQ scores, such that the use of the General
Ability Index (GAI), calculated from VCI and PRI scores
was proposed as a more adapted measure of IQ in HFA and
individuals with ASD in general (Foley-Nicpon et al., 2012).
Considering the possible protective or risk factors that gift-
edness might bring into light in the context of HFA, very
few studies exist to date. Pe~
nuelas-Calvo et al. (2021)
showed that in HFA, intelligence quotient positively corre-
lates social cognition as measured by the ‘Reading the Mind
in the Eyes’Test. The authors have postulated that compen-
satory mechanisms might arise from shared above-average
functional cerebral resources between social recognition and
high intelligence or that high ability in problem-solving in
gifted individuals might be at play to compensate for lack of
facial expression recognition. For instance, it is known that
while neurotypical individuals activate their amygdala in
facial expression recognition tasks, individuals with ASD
seem to compensate with higher activation of frontotempo-
ral regions (Baron-Cohen et al., 2000). Conversely, Dempsey
et al. (2021) who compared patterns of age-related declines
in adaptive functioning between groups of ASD-gifted and
ASD non-gifted found no protective effect of giftedness.
Longitudinal Functional Neuroimaging studies comparing
HFA gifted and HFA non-gifted might prove to be interest-
ing to infer whether such mechanisms are at play.
Conclusion
In this meta-review, we have attempted to portrait a global
picture of what is known to date pertaining to the singular
APPLIED NEUROPSYCHOLOGY: CHILD 9
cognitive, behavioral and developmental profiles of HP indi-
viduals. New investigation techniques are now questioning a
long history of epidemiological evidence on HIP and provid-
ing new frameworks of interpretation the cognitive mecha-
nisms underlying high intelligence. Conceptions of HIP,
research methods and terminology must hence evolve
accordingly, focusing on scientific evidence rather than years
of culturally influenced presumptions.
In reality, despite decades of investigation, there are still
numerous limits to our understanding on HP which could
be explained by many factors, including small-scale observa-
tional studies with small sample size, unstandardized meth-
ods of sample selection and sample selection bias with
access to individuals diagnosed with confounding co-mor-
bidities. HP individuals recruited in studies are often part of
a cohort of patients followed by clinicians for co-existing
confounding affective and learning disorders. Responses to
retrospective surveys used in developmental research are
often confounded by parents and teachers already sensitized
to the condition, a bias likely to be exacerbated by the cur-
rent rise in media coverage.
It is imperative that future investigations seek out to
widen sample selection to HP individuals unknown of prac-
ticing that have remained under the professionals’radar.
Further, it appears that sub profiles of HP with extreme var-
iations on the Weschler’s scale (homogenous and heteroge-
neous profiles) might need to be taken into account
regarding the neurofunctional evidence of differential neural
bases subtending their cognitive processes. With regards to
the co-occurrence of attention, learning or affective disor-
ders with HP, one must not be duped by the term "twice
exceptional”as little is known about the potential cognitive
mechanisms at play in each respective situation. It hence fol-
lows, the fruit of such investigations would prove crucial in
determining if the present support system provided to them,
academically or clinically, would be efficient as is or would
need to be adapted to their HP condition.
Disclosure statement
No potential conflict of interest was reported by the author(s).
ORCID
Tatiana Desvaux http://orcid.org/0000-0001-9286-1016
A. Frey http://orcid.org/0000-0002-0110-8633
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