Publications
21. Park, Bo-Yong; Paquola, Casey; Bethlehem, Richard A I; Benkarim, Oualid; Consortium, Neuroscience Psychiatry Network (NSPN); Mišić, Bratislav; Smallwood, Jonathan; Bullmore, Edward T; Bernhardt, Boris C
Adolescent development of multiscale structural wiring and
functional interactions in the human connectome Journal Article
In: Proc. Natl. Acad. Sci. U. S. A., vol. 119, no. 27, pp. e2116673119, 2022.
Abstract | BibTeX | Tags: brain development; connectome; cortical gradients; structure function
@article{Park2022-mh,
title = {Adolescent development of multiscale structural wiring and
functional interactions in the human connectome},
author = {Bo-Yong Park and Casey Paquola and Richard A I Bethlehem and Oualid Benkarim and Neuroscience Psychiatry Network (NSPN) Consortium and Bratislav Mišić and Jonathan Smallwood and Edward T Bullmore and Boris C Bernhardt},
year = {2022},
date = {2022-07-01},
journal = {Proc. Natl. Acad. Sci. U. S. A.},
volume = {119},
number = {27},
pages = {e2116673119},
publisher = {Proceedings of the National Academy of Sciences},
abstract = {Adolescence is a time of profound changes in the physical wiring
and function of the brain. Here, we analyzed structural and
functional brain network development in an accelerated longitudinal cohort spanning 14 to 25 y (n = 199). Core to our
work was an advanced in vivo model of cortical wiring
incorporating MRI features of corticocortical proximity,
microstructural similarity, and white matter tractography.
Longitudinal analyses assessing age-related changes in cortical
wiring identified a continued differentiation of multiple
corticocortical structural networks in youth. We then assessed
structure-function coupling using resting-state functional MRI
measures in the same participants both via cross-sectional
analysis at baseline and by studying longitudinal change between
baseline and follow-up scans. At baseline, regions with more
similar structural wiring were more likely to be functionally
coupled. Moreover, correlating longitudinal structural wiring
changes with longitudinal functional connectivity
reconfigurations, we found that increased structural
differentiation, particularly between sensory/unimodal and
default mode networks, was reflected by reduced functional
interactions. These findings provide insights into adolescent
development of human brain structure and function, illustrating
how structural wiring interacts with the maturation of
macroscale functional hierarchies.},
keywords = {brain development; connectome; cortical gradients; structure function},
pubstate = {published},
tppubtype = {article}
}
Adolescence is a time of profound changes in the physical wiring
and function of the brain. Here, we analyzed structural and
functional brain network development in an accelerated longitudinal cohort spanning 14 to 25 y (n = 199). Core to our
work was an advanced in vivo model of cortical wiring
incorporating MRI features of corticocortical proximity,
microstructural similarity, and white matter tractography.
Longitudinal analyses assessing age-related changes in cortical
wiring identified a continued differentiation of multiple
corticocortical structural networks in youth. We then assessed
structure-function coupling using resting-state functional MRI
measures in the same participants both via cross-sectional
analysis at baseline and by studying longitudinal change between
baseline and follow-up scans. At baseline, regions with more
similar structural wiring were more likely to be functionally
coupled. Moreover, correlating longitudinal structural wiring
changes with longitudinal functional connectivity
reconfigurations, we found that increased structural
differentiation, particularly between sensory/unimodal and
default mode networks, was reflected by reduced functional
interactions. These findings provide insights into adolescent
development of human brain structure and function, illustrating
how structural wiring interacts with the maturation of
macroscale functional hierarchies.22. Bedford, Saashi A; Seidlitz, Jakob; Bethlehem, Richard A I
Translational potential of human brain charts Journal Article
In: Clin. Transl. Med., vol. 12, no. 7, pp. e960, 2022.
BibTeX | Tags:
@article{Bedford2022-bx,
title = {Translational potential of human brain charts},
author = {Saashi A Bedford and Jakob Seidlitz and Richard A I Bethlehem},
year = {2022},
date = {2022-07-01},
journal = {Clin. Transl. Med.},
volume = {12},
number = {7},
pages = {e960},
publisher = {Wiley},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
23. Azevedo, Tiago; Campbell, Alexander; Romero-Garcia, Rafael; Passamonti, Luca; Bethlehem, Richard A I; Liò, Pietro; Toschi, Nicola
A deep graph neural network architecture for modelling
spatio-temporal dynamics in resting-state functional MRI data Journal Article
In: Med. Image Anal., vol. 79, no. 102471, pp. 102471, 2022.
Abstract | BibTeX | Tags: Deep learning; Graph neural networks; Rs-fMRI; Spatio-temporal dynamics; Temporal convolutional network; Time series; UK Biobank
@article{Azevedo2022-pn,
title = {A deep graph neural network architecture for modelling
spatio-temporal dynamics in resting-state functional MRI data},
author = {Tiago Azevedo and Alexander Campbell and Rafael Romero-Garcia and Luca Passamonti and Richard A I Bethlehem and Pietro Liò and Nicola Toschi},
year = {2022},
date = {2022-07-01},
journal = {Med. Image Anal.},
volume = {79},
number = {102471},
pages = {102471},
publisher = {Elsevier BV},
abstract = {Resting-state functional magnetic resonance imaging (rs-fMRI)
has been successfully employed to understand the organisation of
the human brain. Typically, the brain is parcellated into
regions of interest (ROIs) and modelled as a graph where each
ROI represents a node and association measures between
ROI-specific blood-oxygen-level-dependent (BOLD) time series are
edges. Recently, graph neural networks (GNNs) have seen a surge
in popularity due to their success in modelling unstructured
relational data. The latest developments with GNNs, however,
have not yet been fully exploited for the analysis of rs-fMRI
data, particularly with regards to its spatio-temporal dynamics.
In this paper, we present a novel deep neural network
architecture which combines both GNNs and temporal convolutional
networks (TCNs) in order to learn from both the spatial and
temporal components of rs-fMRI data in an end-to-end fashion. In
particular, this corresponds to intra-feature learning (i.e.,
learning temporal dynamics with TCNs) as well as inter-feature
learning (i.e., leveraging interactions between ROI-wise
dynamics with GNNs). We evaluate our model with an ablation
study using 35,159 samples from the UK Biobank rs-fMRI database,
as well as in the smaller Human Connectome Project (HCP)
dataset, both in a unimodal and in a multimodal fashion. We also
demonstrate that out architecture contains
explainability-related features which easily map to realistic
neurobiological insights. We suggest that this model could lay
the groundwork for future deep learning architectures focused on
leveraging the inherently and inextricably spatio-temporal
nature of rs-fMRI data.},
keywords = {Deep learning; Graph neural networks; Rs-fMRI; Spatio-temporal dynamics; Temporal convolutional network; Time series; UK Biobank},
pubstate = {published},
tppubtype = {article}
}
Resting-state functional magnetic resonance imaging (rs-fMRI)
has been successfully employed to understand the organisation of
the human brain. Typically, the brain is parcellated into
regions of interest (ROIs) and modelled as a graph where each
ROI represents a node and association measures between
ROI-specific blood-oxygen-level-dependent (BOLD) time series are
edges. Recently, graph neural networks (GNNs) have seen a surge
in popularity due to their success in modelling unstructured
relational data. The latest developments with GNNs, however,
have not yet been fully exploited for the analysis of rs-fMRI
data, particularly with regards to its spatio-temporal dynamics.
In this paper, we present a novel deep neural network
architecture which combines both GNNs and temporal convolutional
networks (TCNs) in order to learn from both the spatial and
temporal components of rs-fMRI data in an end-to-end fashion. In
particular, this corresponds to intra-feature learning (i.e.,
learning temporal dynamics with TCNs) as well as inter-feature
learning (i.e., leveraging interactions between ROI-wise
dynamics with GNNs). We evaluate our model with an ablation
study using 35,159 samples from the UK Biobank rs-fMRI database,
as well as in the smaller Human Connectome Project (HCP)
dataset, both in a unimodal and in a multimodal fashion. We also
demonstrate that out architecture contains
explainability-related features which easily map to realistic
neurobiological insights. We suggest that this model could lay
the groundwork for future deep learning architectures focused on
leveraging the inherently and inextricably spatio-temporal
nature of rs-fMRI data.24. Alexander-Bloch, Aaron; Huguet, Guillaume; Schultz, Laura M; Huffnagle, Nicholas; Jacquemont, Sebastien; Seidlitz, Jakob; Saci, Zohra; Moore, Tyler M; Bethlehem, Richard A I; Mollon, Josephine; Knowles, Emma K; Raznahan, Armin; Merikangas, Alison; Chaiyachati, Barbara H; Raman, Harshini; Schmitt, J Eric; Barzilay, Ran; Calkins, Monica E; Shinohara, Russel T; Satterthwaite, Theodore D; Gur, Ruben C; Glahn, David C; Almasy, Laura; Gur, Raquel E; Hakonarson, Hakon; Glessner, Joseph
Copy number variant risk scores associated with cognition,
psychopathology, and brain structure in youths in the
Philadelphia Neurodevelopmental Cohort Journal Article
In: JAMA Psychiatry, vol. 79, no. 7, pp. 699–709, 2022.
@article{Alexander-Bloch2022-uw,
title = {Copy number variant risk scores associated with cognition,
psychopathology, and brain structure in youths in the
Philadelphia Neurodevelopmental Cohort},
author = {Aaron Alexander-Bloch and Guillaume Huguet and Laura M Schultz and Nicholas Huffnagle and Sebastien Jacquemont and Jakob Seidlitz and Zohra Saci and Tyler M Moore and Richard A I Bethlehem and Josephine Mollon and Emma K Knowles and Armin Raznahan and Alison Merikangas and Barbara H Chaiyachati and Harshini Raman and J Eric Schmitt and Ran Barzilay and Monica E Calkins and Russel T Shinohara and Theodore D Satterthwaite and Ruben C Gur and David C Glahn and Laura Almasy and Raquel E Gur and Hakon Hakonarson and Joseph Glessner},
year = {2022},
date = {2022-07-01},
journal = {JAMA Psychiatry},
volume = {79},
number = {7},
pages = {699–709},
publisher = {American Medical Association (AMA)},
abstract = {Importance: Psychiatric and cognitive phenotypes have been
associated with a range of specific, rare copy number variants
(CNVs). Moreover, IQ is strongly associated with CNV risk scores
that model the predicted risk of CNVs across the genome. But the
utility of CNV risk scores for psychiatric phenotypes has been
sparsely examined. Objective: To determine how CNV risk scores,
common genetic variation indexed by polygenic scores (PGSs), and
environmental factors combine to associate with cognition and
psychopathology in a community sample. Design, Setting, and
Participants: The Philadelphia Neurodevelopmental Cohort is a
community-based study examining genetics, psychopathology,
neurocognition, and neuroimaging. Participants were recruited
through the Children's Hospital of Philadelphia pediatric
network. Participants with stable health and fluency in English
underwent genotypic and phenotypic characterization from
November 5, 2009, through December 30, 2011. Data were analyzed
from January 1 through July 30, 2021. Exposures: The study
examined (1) CNV risk scores derived from models of burden,
predicted intolerance, and gene dosage sensitivity; (2) PGSs
from genomewide association studies related to developmental
outcomes; and (3) environmental factors, including trauma
exposure and neighborhood socioeconomic status. Main Outcomes
and Measures: The study examined (1) neurocognition, with the
Penn Computerized Neurocognitive Battery; (2) psychopathology,
with structured interviews based on the Schedule for Affective
Disorders and Schizophrenia for School-Age Children; and (3)
brain volume, with magnetic resonance imaging. Results:
Participants included 9498 youths aged 8 to 21 years; 4906
(51.7%) were female, and the mean (SD) age was 14.2 (3.7)
years. After quality control, 18 185 total CNVs greater than 50
kilobases (10 517 deletions and 7668 duplications) were
identified in 7101 unrelated participants genotyped on Illumina
arrays. In these participants, elevated CNV risk scores were
associated with lower overall accuracy on cognitive tests (standardized β = 0.12; 95% CI, 0.10-0.14; P = 7.41
$times$ 10-26); lower accuracy across a range of cognitive
subdomains; increased overall psychopathology; increased
psychosis-spectrum symptoms; and higher deviation from a
normative developmental model of brain volume. Statistical
models of developmental outcomes were significantly improved
when CNV risk scores were combined with PGSs and environmental
factors. Conclusions and Relevance: In this study, elevated CNV
risk scores were associated with lower cognitive ability, higher
psychopathology including psychosis-spectrum symptoms, and
greater deviations from normative magnetic resonance imaging
models of brain development. Together, these results represent a
step toward synthesizing rare genetic, common genetic, and
environmental factors to understand clinically relevant outcomes
in youth.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Importance: Psychiatric and cognitive phenotypes have been
associated with a range of specific, rare copy number variants
(CNVs). Moreover, IQ is strongly associated with CNV risk scores
that model the predicted risk of CNVs across the genome. But the
utility of CNV risk scores for psychiatric phenotypes has been
sparsely examined. Objective: To determine how CNV risk scores,
common genetic variation indexed by polygenic scores (PGSs), and
environmental factors combine to associate with cognition and
psychopathology in a community sample. Design, Setting, and
Participants: The Philadelphia Neurodevelopmental Cohort is a
community-based study examining genetics, psychopathology,
neurocognition, and neuroimaging. Participants were recruited
through the Children's Hospital of Philadelphia pediatric
network. Participants with stable health and fluency in English
underwent genotypic and phenotypic characterization from
November 5, 2009, through December 30, 2011. Data were analyzed
from January 1 through July 30, 2021. Exposures: The study
examined (1) CNV risk scores derived from models of burden,
predicted intolerance, and gene dosage sensitivity; (2) PGSs
from genomewide association studies related to developmental
outcomes; and (3) environmental factors, including trauma
exposure and neighborhood socioeconomic status. Main Outcomes
and Measures: The study examined (1) neurocognition, with the
Penn Computerized Neurocognitive Battery; (2) psychopathology,
with structured interviews based on the Schedule for Affective
Disorders and Schizophrenia for School-Age Children; and (3)
brain volume, with magnetic resonance imaging. Results:
Participants included 9498 youths aged 8 to 21 years; 4906
(51.7%) were female, and the mean (SD) age was 14.2 (3.7)
years. After quality control, 18 185 total CNVs greater than 50
kilobases (10 517 deletions and 7668 duplications) were
identified in 7101 unrelated participants genotyped on Illumina
arrays. In these participants, elevated CNV risk scores were
associated with lower overall accuracy on cognitive tests (standardized β = 0.12; 95% CI, 0.10-0.14; P = 7.41
$times$ 10-26); lower accuracy across a range of cognitive
subdomains; increased overall psychopathology; increased
psychosis-spectrum symptoms; and higher deviation from a
normative developmental model of brain volume. Statistical
models of developmental outcomes were significantly improved
when CNV risk scores were combined with PGSs and environmental
factors. Conclusions and Relevance: In this study, elevated CNV
risk scores were associated with lower cognitive ability, higher
psychopathology including psychosis-spectrum symptoms, and
greater deviations from normative magnetic resonance imaging
models of brain development. Together, these results represent a
step toward synthesizing rare genetic, common genetic, and
environmental factors to understand clinically relevant outcomes
in youth.25. Dorfschmidt, Lena; Bethlehem, Richard A; Seidlitz, Jakob; Váša, František; White, Simon R; Romero-García, Rafael; Kitzbichler, Manfred G; Aruldass, Athina R; Morgan, Sarah E; Goodyer, Ian M; Fonagy, Peter; Jones, Peter B; Dolan, Ray J; Consortium, NSPN; Harrison, Neil A; Vértes, Petra E; Bullmore, Edward T
Sexually divergent development of depression-related brain
networks during healthy human adolescence Journal Article
In: Sci. Adv., vol. 8, no. 21, pp. eabm7825, 2022.
@article{Dorfschmidt2022-gu,
title = {Sexually divergent development of depression-related brain
networks during healthy human adolescence},
author = {Lena Dorfschmidt and Richard A Bethlehem and Jakob Seidlitz and František Váša and Simon R White and Rafael Romero-García and Manfred G Kitzbichler and Athina R Aruldass and Sarah E Morgan and Ian M Goodyer and Peter Fonagy and Peter B Jones and Ray J Dolan and NSPN Consortium and Neil A Harrison and Petra E Vértes and Edward T Bullmore},
year = {2022},
date = {2022-05-01},
journal = {Sci. Adv.},
volume = {8},
number = {21},
pages = {eabm7825},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Sexual differences in human brain development could be relevant
to sex differences in the incidence of depression during
adolescence. We tested for sex differences in parameters of normative brain network development using fMRI data on N = 298
healthy adolescents, aged 14 to 26 years, each scanned one to
three times. Sexually divergent development of functional
connectivity was located in the default mode network, limbic
cortex, and subcortical nuclei. Females had a more
``disruptive'' pattern of development, where weak functional
connectivity at age 14 became stronger during adolescence. This
fMRI-derived map of sexually divergent brain network development
was robustly colocated with i prior loci of reward-related brain
activation ii a map of functional dysconnectivity in major
depressive disorder (MDD), and iii an adult brain gene
transcriptional pattern enriched for genes on the X chromosome,
neurodevelopmental genes, and risk genes for MDD. We found
normative sexual divergence in adolescent development of a
cortico-subcortical brain functional network that is relevant to
depression.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sexual differences in human brain development could be relevant
to sex differences in the incidence of depression during
adolescence. We tested for sex differences in parameters of normative brain network development using fMRI data on N = 298
healthy adolescents, aged 14 to 26 years, each scanned one to
three times. Sexually divergent development of functional
connectivity was located in the default mode network, limbic
cortex, and subcortical nuclei. Females had a more
``disruptive'' pattern of development, where weak functional
connectivity at age 14 became stronger during adolescence. This
fMRI-derived map of sexually divergent brain network development
was robustly colocated with i prior loci of reward-related brain
activation ii a map of functional dysconnectivity in major
depressive disorder (MDD), and iii an adult brain gene
transcriptional pattern enriched for genes on the X chromosome,
neurodevelopmental genes, and risk genes for MDD. We found
normative sexual divergence in adolescent development of a
cortico-subcortical brain functional network that is relevant to
depression.26. Valk, Sofie L; Xu, Ting; Paquola, Casey; Park, Bo-Yong; Bethlehem, Richard A I; de Wael, Reinder Vos; Royer, Jessica; Masouleh, Shahrzad Kharabian; Bayrak, Şeyma; Kochunov, Peter; Yeo, B T Thomas; Margulies, Daniel; Smallwood, Jonathan; Eickhoff, Simon B; Bernhardt, Boris C
Genetic and phylogenetic uncoupling of structure and function in
human transmodal cortex Journal Article
In: Nat. Commun., vol. 13, no. 1, pp. 2341, 2022.
@article{Valk2022-rf,
title = {Genetic and phylogenetic uncoupling of structure and function in
human transmodal cortex},
author = {Sofie L Valk and Ting Xu and Casey Paquola and Bo-Yong Park and Richard A I Bethlehem and Reinder Vos de Wael and Jessica Royer and Shahrzad Kharabian Masouleh and Şeyma Bayrak and Peter Kochunov and B T Thomas Yeo and Daniel Margulies and Jonathan Smallwood and Simon B Eickhoff and Boris C Bernhardt},
year = {2022},
date = {2022-05-01},
journal = {Nat. Commun.},
volume = {13},
number = {1},
pages = {2341},
publisher = {Springer Science and Business Media LLC},
abstract = {Brain structure scaffolds intrinsic function, supporting
cognition and ultimately behavioral flexibility. However, it
remains unclear how a static, genetically controlled
architecture supports flexible cognition and behavior. Here, we
synthesize genetic, phylogenetic and cognitive analyses to
understand how the macroscale organization of structure-function
coupling across the cortex can inform its role in cognition. In
humans, structure-function coupling was highest in regions of
unimodal cortex and lowest in transmodal cortex, a pattern that
was mirrored by a reduced alignment with heritable connectivity
profiles. Structure-function uncoupling in macaques had a
similar spatial distribution, but we observed an increased
coupling between structure and function in association cortices
relative to humans. Meta-analysis suggested regions with the
least genetic control (low heritable correspondence and
different across primates) are linked to social-cognition and
autobiographical memory. Our findings suggest that genetic and
evolutionary uncoupling of structure and function in different
transmodal systems may support the emergence of complex forms of
cognition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Brain structure scaffolds intrinsic function, supporting
cognition and ultimately behavioral flexibility. However, it
remains unclear how a static, genetically controlled
architecture supports flexible cognition and behavior. Here, we
synthesize genetic, phylogenetic and cognitive analyses to
understand how the macroscale organization of structure-function
coupling across the cortex can inform its role in cognition. In
humans, structure-function coupling was highest in regions of
unimodal cortex and lowest in transmodal cortex, a pattern that
was mirrored by a reduced alignment with heritable connectivity
profiles. Structure-function uncoupling in macaques had a
similar spatial distribution, but we observed an increased
coupling between structure and function in association cortices
relative to humans. Meta-analysis suggested regions with the
least genetic control (low heritable correspondence and
different across primates) are linked to social-cognition and
autobiographical memory. Our findings suggest that genetic and
evolutionary uncoupling of structure and function in different
transmodal systems may support the emergence of complex forms of
cognition.27. Bowden-Jones, Henrietta; Hook, Roxanne W; Grant, Jon E; Ioannidis, Konstantinos; Corazza, Ornella; Fineberg, Naomi A; Singer, Bryan F; Roberts, Amanda; Bethlehem, Richard; Dymond, Simon; Romero-Garcia, Rafa; Robbins, Trevor W; Cortese, Samuele; Thomas, Shane A; Sahakian, Barbara J; Dowling, Nicki A; Chamberlain, Samuel R
Gambling disorder in the UK: key research priorities and the
urgent need for independent research funding Journal Article
In: Lancet Psychiatry, vol. 9, no. 4, pp. 321–329, 2022.
@article{Bowden-Jones2022-ns,
title = {Gambling disorder in the UK: key research priorities and the
urgent need for independent research funding},
author = {Henrietta Bowden-Jones and Roxanne W Hook and Jon E Grant and Konstantinos Ioannidis and Ornella Corazza and Naomi A Fineberg and Bryan F Singer and Amanda Roberts and Richard Bethlehem and Simon Dymond and Rafa Romero-Garcia and Trevor W Robbins and Samuele Cortese and Shane A Thomas and Barbara J Sahakian and Nicki A Dowling and Samuel R Chamberlain},
year = {2022},
date = {2022-04-01},
journal = {Lancet Psychiatry},
volume = {9},
number = {4},
pages = {321–329},
publisher = {Elsevier BV},
abstract = {Gambling in the modern era is pervasive owing to the variety of
gambling opportunities available, including those that use
technology (eg, online applications on smartphones). Although
many people gamble recreationally without undue negative
effects, a sizeable subset of individuals develop disordered
gambling, which is associated with marked functional impairment
including other mental health problems, relationship problems,
bankruptcy, suicidality, and criminality. The National UK
Research Network for Behavioural Addictions (NUK-BA) was
established to promote understanding of, research into, and
treatments for behavioural addictions including gambling
disorder, which is the only formally recognised behavioural
addiction. In this Health Policy paper, we outline the status of
research and treatment for disordered gambling in the UK
(including funding issues) and key research that should be
conducted to establish the magnitude of the problem,
vulnerability and resilience factors, the underlying
neurobiology, long-term consequences, and treatment
opportunities. In particular, we emphasise the need to: (1)
conduct independent longitudinal research into the prevalence of
disordered gambling (including gambling disorder and at-risk
gambling), and gambling harms, including in vulnerable and
minoritised groups; (2) select and refine the most suitable
pragmatic measurement tools; (3) identify predictors (eg,
vulnerability and resilience markers) of disordered gambling in
people who gamble recreationally, including in vulnerable and
minoritised groups; (4) conduct randomised controlled trials on
psychological interventions and pharmacotherapy for gambling
disorder; (5) improve understanding of the neurobiological basis
of gambling disorder, including impulsivity and compulsivity,
genetics, and biomarkers; and (6) develop clinical guidelines
based on the best contemporary research evidence to guide
effective clinical interventions. We also highlight the need to
consider what can be learnt from approaches towards mitigating
gambling-related harm in other countries.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Gambling in the modern era is pervasive owing to the variety of
gambling opportunities available, including those that use
technology (eg, online applications on smartphones). Although
many people gamble recreationally without undue negative
effects, a sizeable subset of individuals develop disordered
gambling, which is associated with marked functional impairment
including other mental health problems, relationship problems,
bankruptcy, suicidality, and criminality. The National UK
Research Network for Behavioural Addictions (NUK-BA) was
established to promote understanding of, research into, and
treatments for behavioural addictions including gambling
disorder, which is the only formally recognised behavioural
addiction. In this Health Policy paper, we outline the status of
research and treatment for disordered gambling in the UK
(including funding issues) and key research that should be
conducted to establish the magnitude of the problem,
vulnerability and resilience factors, the underlying
neurobiology, long-term consequences, and treatment
opportunities. In particular, we emphasise the need to: (1)
conduct independent longitudinal research into the prevalence of
disordered gambling (including gambling disorder and at-risk
gambling), and gambling harms, including in vulnerable and
minoritised groups; (2) select and refine the most suitable
pragmatic measurement tools; (3) identify predictors (eg,
vulnerability and resilience markers) of disordered gambling in
people who gamble recreationally, including in vulnerable and
minoritised groups; (4) conduct randomised controlled trials on
psychological interventions and pharmacotherapy for gambling
disorder; (5) improve understanding of the neurobiological basis
of gambling disorder, including impulsivity and compulsivity,
genetics, and biomarkers; and (6) develop clinical guidelines
based on the best contemporary research evidence to guide
effective clinical interventions. We also highlight the need to
consider what can be learnt from approaches towards mitigating
gambling-related harm in other countries.28. Grant, Jon E; Peris, Tara S; Ricketts, Emily J; Bethlehem, Richard A I; Chamberlain, Samuel R; O'Neill, Joseph; Scharf, Jeremiah M; Dougherty, Darin D; Deckersbach, Thilo; Woods, Douglas W; Piacentini, John; Keuthen, Nancy J
Reward processing in trichotillomania and skin picking disorder Journal Article
In: Brain Imaging Behav., vol. 16, no. 2, pp. 547–556, 2022.
Abstract | BibTeX | Tags: Imaging; Neurobiology; Reward; Skin picking disorder; Trichotillomania; fMRI
@article{Grant2022-lu,
title = {Reward processing in trichotillomania and skin picking disorder},
author = {Jon E Grant and Tara S Peris and Emily J Ricketts and Richard A I Bethlehem and Samuel R Chamberlain and Joseph O'Neill and Jeremiah M Scharf and Darin D Dougherty and Thilo Deckersbach and Douglas W Woods and John Piacentini and Nancy J Keuthen},
year = {2022},
date = {2022-04-01},
journal = {Brain Imaging Behav.},
volume = {16},
number = {2},
pages = {547–556},
publisher = {Springer Science and Business Media LLC},
abstract = {Trichotillomania (hair pulling disorder) and skin picking
disorder are common and often debilitating mental health
conditions, grouped under the umbrella term of body focused
repetitive behaviors (BFRBs). Although the pathophysiology of
BFRBs is incompletely understood, reward processing dysfunction
has been implicated in the etiology and sustention of these
disorders. The purpose of this study was to probe reward processing in BFRBs. 159 adults (125 with a BFRB [83.2% (n = 104) female] and 34 healthy controls [73.5% (n = 25) female])
were recruited from the community for a multi-center
between-group comparison using a functional imaging (fMRI)
monetary reward task. Differences in brain activation during
reward anticipation and punishment anticipation were compared
between BFRB patients and controls, with stringent correction
for multiple comparisons. All group level analyses controlled
for age, sex and scanning site. Compared to controls, BFRB
participants showed marked hyperactivation of the bilateral
inferior frontal gyrus (pars opercularis and pars triangularis)
compared to controls. In addition, BFRB participants exhibited
increased activation in multiple areas during the anticipation
of loss (right fusiform gyrus, parahippocampal gyrus,
cerebellum, right inferior parietal lobule; left inferior
frontal gyrus). There were no significant differences in the
win-lose contrast between the two groups. These data indicate
the existence of dysregulated reward circuitry in BFRBs. The
identified pathophysiology of reward dysfunction may be useful
to tailor future treatments.},
keywords = {Imaging; Neurobiology; Reward; Skin picking disorder; Trichotillomania; fMRI},
pubstate = {published},
tppubtype = {article}
}
Trichotillomania (hair pulling disorder) and skin picking
disorder are common and often debilitating mental health
conditions, grouped under the umbrella term of body focused
repetitive behaviors (BFRBs). Although the pathophysiology of
BFRBs is incompletely understood, reward processing dysfunction
has been implicated in the etiology and sustention of these
disorders. The purpose of this study was to probe reward processing in BFRBs. 159 adults (125 with a BFRB [83.2% (n = 104) female] and 34 healthy controls [73.5% (n = 25) female])
were recruited from the community for a multi-center
between-group comparison using a functional imaging (fMRI)
monetary reward task. Differences in brain activation during
reward anticipation and punishment anticipation were compared
between BFRB patients and controls, with stringent correction
for multiple comparisons. All group level analyses controlled
for age, sex and scanning site. Compared to controls, BFRB
participants showed marked hyperactivation of the bilateral
inferior frontal gyrus (pars opercularis and pars triangularis)
compared to controls. In addition, BFRB participants exhibited
increased activation in multiple areas during the anticipation
of loss (right fusiform gyrus, parahippocampal gyrus,
cerebellum, right inferior parietal lobule; left inferior
frontal gyrus). There were no significant differences in the
win-lose contrast between the two groups. These data indicate
the existence of dysregulated reward circuitry in BFRBs. The
identified pathophysiology of reward dysfunction may be useful
to tailor future treatments.29. Bethlehem, R A I; Seidlitz, J; White, S R; Vogel, J W; Anderson, K M; Adamson, C; Adler, S; Alexopoulos, G S; Anagnostou, E; Areces-Gonzalez, A; Astle, D E; Auyeung, B; Ayub, M; Bae, J; Ball, G; Baron-Cohen, S; Beare, R; Bedford, S A; Benegal, V; Beyer, F; Blangero, J; Cábez, M Blesa; Boardman, J P; Borzage, M; Bosch-Bayard, J F; Bourke, N; Calhoun, V D; Chakravarty, M M; Chen, C; Chertavian, C; Chetelat, G; Chong, Y S; Cole, J H; Corvin, A; Costantino, M; Courchesne, E; Crivello, F; Cropley, V L; Crosbie, J; Crossley, N; Delarue, M; Delorme, R; Desrivieres, S; Devenyi, G A; Biase, M A Di; Dolan, R; Donald, K A; Donohoe, G; Dunlop, K; Edwards, A D; Elison, J T; Ellis, C T; Elman, J A; Eyler, L; Fair, D A; Feczko, E; Fletcher, P C; Fonagy, P; Franz, C E; Galan-Garcia, L; Gholipour, A; Giedd, J; Gilmore, J H; Glahn, D C; Goodyer, I M; Grant, P E; Groenewold, N A; Gunning, F M; Gur, R E; Gur, R C; Hammill, C F; Hansson, O; Hedden, T; Heinz, T.; Rodrigue, A; Rollins, C K; Romero-Garcia, R; Ronan, L; Rosenberg, M D; Rowitch, D H; Salum, G A; Satterthwaite, T D; Schaare, H L; Schachar, R J; Schultz, A P; Schumann, G; Schöll, M; Sharp, D; Shinohara, R T; Skoog, I; Smyser, C D; Sperling, R A; Stein, D J; Stolicyn, A; Suckling, J; Sullivan, G; Taki, Y; Thyreau, B; Toro, R; Traut, N; Tsvetanov, K A; Turk-Browne, N B; Tuulari, J J; Tzourio, C; Vachon-Presseau, É; Valdes-Sosa, M J; Valdes-Sosa, P A; Valk, S L; Amelsvoort, T; Vandekar, S N; Vasung, L; Victoria, L W; Villeneuve, S; Villringer, A; Vértes, P E; Wagstyl, K; Wang, Y S; Warfield, S K; Warrier, V; Westman, E; Westwater, M L; Whalley, H C; Witte, A V; Yang, N; Yeo, B; Yun, H; Zalesky, A; Zar, H J; Zettergren, A; Zhou, J H; Ziauddeen, H; Zugman, A; Zuo, X N; 3R-BRAIN,; AIBL,; Initiative, Alzheimer's Disease Neuroimaging; Investigators, Alzheimer's Disease Repository Without Borders; Team, CALM; Cam-CAN,; CCNP,; COBRE,; cVEDA,; Group, ENIGMA Developmental Brain Age Working; Project, Developing Human Connectome; FinnBrain,; Study, Harvard Aging Brain; IMAGEN,; KNE96,; Aging, Mayo Clinic Study; NSPN,; POND,; Group, PREVENT-AD Research; VETSA,; Bullmore, E T; Alexander-Bloch, A F
Brain charts for the human lifespan Journal Article
In: Nature, vol. 604, no. 7906, pp. 525–533, 2022.
@article{Bethlehem2022-sf,
title = {Brain charts for the human lifespan},
author = {R A I Bethlehem and J Seidlitz and S R White and J W Vogel and K M Anderson and C Adamson and S Adler and G S Alexopoulos and E Anagnostou and A Areces-Gonzalez and D E Astle and B Auyeung and M Ayub and J Bae and G Ball and S Baron-Cohen and R Beare and S A Bedford and V Benegal and F Beyer and J Blangero and M Blesa Cábez and J P Boardman and M Borzage and J F Bosch-Bayard and N Bourke and V D Calhoun and M M Chakravarty and C Chen and C Chertavian and G Chetelat and Y S Chong and J H Cole and A Corvin and M Costantino and E Courchesne and F Crivello and V L Cropley and J Crosbie and N Crossley and M Delarue and R Delorme and S Desrivieres and G A Devenyi and M A Di Biase and R Dolan and K A Donald and G Donohoe and K Dunlop and A D Edwards and J T Elison and C T Ellis and J A Elman and L Eyler and D A Fair and E Feczko and P C Fletcher and P Fonagy and C E Franz and L Galan-Garcia and A Gholipour and J Giedd and J H Gilmore and D C Glahn and I M Goodyer and P E Grant and N A Groenewold and F M Gunning and R E Gur and R C Gur and C F Hammill and O Hansson and T Hedden and T ... Heinz and A Rodrigue and C K Rollins and R Romero-Garcia and L Ronan and M D Rosenberg and D H Rowitch and G A Salum and T D Satterthwaite and H L Schaare and R J Schachar and A P Schultz and G Schumann and M Schöll and D Sharp and R T Shinohara and I Skoog and C D Smyser and R A Sperling and D J Stein and A Stolicyn and J Suckling and G Sullivan and Y Taki and B Thyreau and R Toro and N Traut and K A Tsvetanov and N B Turk-Browne and J J Tuulari and C Tzourio and É Vachon-Presseau and M J Valdes-Sosa and P A Valdes-Sosa and S L Valk and T Amelsvoort and S N Vandekar and L Vasung and L W Victoria and S Villeneuve and A Villringer and P E Vértes and K Wagstyl and Y S Wang and S K Warfield and V Warrier and E Westman and M L Westwater and H C Whalley and A V Witte and N Yang and B Yeo and H Yun and A Zalesky and H J Zar and A Zettergren and J H Zhou and H Ziauddeen and A Zugman and X N Zuo and 3R-BRAIN and AIBL and Alzheimer's Disease Neuroimaging Initiative and Alzheimer's Disease Repository Without Borders Investigators and CALM Team and Cam-CAN and CCNP and COBRE and cVEDA and ENIGMA Developmental Brain Age Working Group and Developing Human Connectome Project and FinnBrain and Harvard Aging Brain Study and IMAGEN and KNE96 and Mayo Clinic Study Aging and NSPN and POND and PREVENT-AD Research Group and VETSA and E T Bullmore and A F Alexander-Bloch},
year = {2022},
date = {2022-04-01},
journal = {Nature},
volume = {604},
number = {7906},
pages = {525–533},
publisher = {Springer Science and Business Media LLC},
abstract = {Over the past few decades, neuroimaging has become a ubiquitous
tool in basic research and clinical studies of the human brain.
However, no reference standards currently exist to quantify
individual differences in neuroimaging metrics over time, in
contrast to growth charts for anthropometric traits such as
height and weight1. Here we assemble an interactive open
resource to benchmark brain morphology derived from any current
or future sample of MRI data ( http://www.brainchart.io/ ). With
the goal of basing these reference charts on the largest and
most inclusive dataset available, acknowledging limitations due
to known biases of MRI studies relative to the diversity of the
global population, we aggregated 123,984 MRI scans, across more
than 100 primary studies, from 101,457 human participants
between 115 days post-conception to 100 years of age. MRI
metrics were quantified by centile scores, relative to
non-linear trajectories2 of brain structural changes, and rates
of change, over the lifespan. Brain charts identified previously
unreported neurodevelopmental milestones3, showed high stability
of individuals across longitudinal assessments, and demonstrated
robustness to technical and methodological differences between
primary studies. Centile scores showed increased heritability
compared with non-centiled MRI phenotypes, and provided a
standardized measure of atypical brain structure that revealed
patterns of neuroanatomical variation across neurological and
psychiatric disorders. In summary, brain charts are an essential
step towards robust quantification of individual variation
benchmarked to normative trajectories in multiple, commonly used
neuroimaging phenotypes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Over the past few decades, neuroimaging has become a ubiquitous
tool in basic research and clinical studies of the human brain.
However, no reference standards currently exist to quantify
individual differences in neuroimaging metrics over time, in
contrast to growth charts for anthropometric traits such as
height and weight1. Here we assemble an interactive open
resource to benchmark brain morphology derived from any current
or future sample of MRI data ( http://www.brainchart.io/ ). With
the goal of basing these reference charts on the largest and
most inclusive dataset available, acknowledging limitations due
to known biases of MRI studies relative to the diversity of the
global population, we aggregated 123,984 MRI scans, across more
than 100 primary studies, from 101,457 human participants
between 115 days post-conception to 100 years of age. MRI
metrics were quantified by centile scores, relative to
non-linear trajectories2 of brain structural changes, and rates
of change, over the lifespan. Brain charts identified previously
unreported neurodevelopmental milestones3, showed high stability
of individuals across longitudinal assessments, and demonstrated
robustness to technical and methodological differences between
primary studies. Centile scores showed increased heritability
compared with non-centiled MRI phenotypes, and provided a
standardized measure of atypical brain structure that revealed
patterns of neuroanatomical variation across neurological and
psychiatric disorders. In summary, brain charts are an essential
step towards robust quantification of individual variation
benchmarked to normative trajectories in multiple, commonly used
neuroimaging phenotypes.30. Choe, Katrina Y; Bethlehem, Richard A I; Safrin, Martin; Dong, Hongmei; Salman, Elena; Li, Ying; Grinevich, Valery; Golshani, Peyman; DeNardo, Laura A; Peñagarikano, Olga; Harris, Neil G; Geschwind, Daniel H
Oxytocin normalizes altered circuit connectivity for social
rescue of the Cntnap2 knockout mouse Journal Article
In: Neuron, vol. 110, no. 5, pp. 795–808.e6, 2022.
Abstract | BibTeX | Tags: autism; brain network; fMRI; functional connectivity; iDISCO; mouse model; nucleus accumbens; oxytocin; paraventricular nucleus; social behavior
@article{Choe2022-ld,
title = {Oxytocin normalizes altered circuit connectivity for social
rescue of the Cntnap2 knockout mouse},
author = {Katrina Y Choe and Richard A I Bethlehem and Martin Safrin and Hongmei Dong and Elena Salman and Ying Li and Valery Grinevich and Peyman Golshani and Laura A DeNardo and Olga Peñagarikano and Neil G Harris and Daniel H Geschwind},
year = {2022},
date = {2022-03-01},
journal = {Neuron},
volume = {110},
number = {5},
pages = {795–808.e6},
publisher = {Elsevier BV},
abstract = {The neural basis of abnormal social behavior in autism spectrum
disorders (ASDs) remains incompletely understood. Here we used
two complementary but independent brain-wide mapping approaches,
mouse resting-state fMRI and c-Fos-iDISCO+ imaging, to construct
brain-wide activity and connectivity maps of the Cntnap2
knockout (KO) mouse model of ASD. At the macroscale level, we
detected reduced functional coupling across social brain regions
despite general patterns of hyperconnectivity across major brain
structures. Oxytocin administration, which rescues social
deficits in KO mice, strongly stimulated many brain areas and
normalized connectivity patterns. Notably, chemogenetically
triggered release of endogenous oxytocin strongly stimulated the
nucleus accumbens (NAc), a forebrain nucleus implicated in
social reward. Furthermore, NAc-targeted approaches to activate
local oxytocin receptors sufficiently rescued their social
deficits. Our findings establish circuit- and systems-level
mechanisms of social deficits in Cntnap2 KO mice and reveal the
NAc as a region that can be modulated by oxytocin to promote
social interactions.},
keywords = {autism; brain network; fMRI; functional connectivity; iDISCO; mouse model; nucleus accumbens; oxytocin; paraventricular nucleus; social behavior},
pubstate = {published},
tppubtype = {article}
}
The neural basis of abnormal social behavior in autism spectrum
disorders (ASDs) remains incompletely understood. Here we used
two complementary but independent brain-wide mapping approaches,
mouse resting-state fMRI and c-Fos-iDISCO+ imaging, to construct
brain-wide activity and connectivity maps of the Cntnap2
knockout (KO) mouse model of ASD. At the macroscale level, we
detected reduced functional coupling across social brain regions
despite general patterns of hyperconnectivity across major brain
structures. Oxytocin administration, which rescues social
deficits in KO mice, strongly stimulated many brain areas and
normalized connectivity patterns. Notably, chemogenetically
triggered release of endogenous oxytocin strongly stimulated the
nucleus accumbens (NAc), a forebrain nucleus implicated in
social reward. Furthermore, NAc-targeted approaches to activate
local oxytocin receptors sufficiently rescued their social
deficits. Our findings establish circuit- and systems-level
mechanisms of social deficits in Cntnap2 KO mice and reveal the
NAc as a region that can be modulated by oxytocin to promote
social interactions.31. Stauffer, Eva-Maria; Bethlehem, Richard A I; Warrier, Varun; Murray, Graham K; Romero-Garcia, Rafael; Seidlitz, Jakob; Bullmore, Edward T
Grey and white matter microstructure is associated with
polygenic risk for schizophrenia Journal Article
In: Mol. Psychiatry, vol. 26, no. 12, pp. 7709–7718, 2021.
@article{Stauffer2021-el,
title = {Grey and white matter microstructure is associated with
polygenic risk for schizophrenia},
author = {Eva-Maria Stauffer and Richard A I Bethlehem and Varun Warrier and Graham K Murray and Rafael Romero-Garcia and Jakob Seidlitz and Edward T Bullmore},
year = {2021},
date = {2021-12-01},
journal = {Mol. Psychiatry},
volume = {26},
number = {12},
pages = {7709–7718},
publisher = {Springer Science and Business Media LLC},
abstract = {Recent discovery of approximately 270 common genetic variants
associated with schizophrenia has enabled polygenic risk scores
(PRS) to be measured in the population. We hypothesized that
normal variation in PRS would be associated with magnetic
resonance imaging (MRI) phenotypes of brain morphometry and
tissue composition. We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy
controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (Nmax = 29,878) who had multiple
micro- and macrostructural MRI metrics measured at each of 180
cortical areas, seven subcortical structures, and 15 major white
matter tracts. Linear mixed-effect models were used to
investigate associations between PRS and brain structure at
global and regional scales, controlled for multiple comparisons.
Polygenic risk was significantly associated with reduced neurite
density index (NDI) at global brain scale, at 149 cortical
regions, five subcortical structures, and 14 white matter
tracts. Other microstructural parameters, e.g., fractional
anisotropy, that were correlated with NDI were also
significantly associated with PRS. Genetic effects on multiple
MRI phenotypes were co-located in temporal, cingulate, and
prefrontal cortical areas, insula, and hippocampus. Post-hoc
bidirectional Mendelian randomization analyses provided
preliminary evidence in support of a causal relationship between
(reduced) thalamic NDI and (increased) risk of schizophrenia.
Risk-related reduction in NDI is plausibly indicative of reduced
density of myelinated axons and dendritic arborization in
large-scale cortico-subcortical networks. Cortical, subcortical,
and white matter microstructure may be linked to the genetic
mechanisms of schizophrenia.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent discovery of approximately 270 common genetic variants
associated with schizophrenia has enabled polygenic risk scores
(PRS) to be measured in the population. We hypothesized that
normal variation in PRS would be associated with magnetic
resonance imaging (MRI) phenotypes of brain morphometry and
tissue composition. We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy
controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (Nmax = 29,878) who had multiple
micro- and macrostructural MRI metrics measured at each of 180
cortical areas, seven subcortical structures, and 15 major white
matter tracts. Linear mixed-effect models were used to
investigate associations between PRS and brain structure at
global and regional scales, controlled for multiple comparisons.
Polygenic risk was significantly associated with reduced neurite
density index (NDI) at global brain scale, at 149 cortical
regions, five subcortical structures, and 14 white matter
tracts. Other microstructural parameters, e.g., fractional
anisotropy, that were correlated with NDI were also
significantly associated with PRS. Genetic effects on multiple
MRI phenotypes were co-located in temporal, cingulate, and
prefrontal cortical areas, insula, and hippocampus. Post-hoc
bidirectional Mendelian randomization analyses provided
preliminary evidence in support of a causal relationship between
(reduced) thalamic NDI and (increased) risk of schizophrenia.
Risk-related reduction in NDI is plausibly indicative of reduced
density of myelinated axons and dendritic arborization in
large-scale cortico-subcortical networks. Cortical, subcortical,
and white matter microstructure may be linked to the genetic
mechanisms of schizophrenia.32. Romero-Garcia, Rafael; Hart, Michael G; Bethlehem, Richard A I; Mandal, Ayan; Assem, Moataz; Crespo-Facorro, Benedicto; Gorriz, Juan Manuel; Burke, G A Amos; Price, Stephen J; Santarius, Thomas; Erez, Yaara; Suckling, John
BOLD coupling between lesioned and healthy brain is associated
with glioma patients' recovery Journal Article
In: Cancers (Basel), vol. 13, no. 19, pp. 5008, 2021.
Abstract | BibTeX | Tags: brain tumours; cognitive recovery; functional MRI; global signal; neurosurgery
@article{Romero-Garcia2021-ol,
title = {BOLD coupling between lesioned and healthy brain is associated
with glioma patients' recovery},
author = {Rafael Romero-Garcia and Michael G Hart and Richard A I Bethlehem and Ayan Mandal and Moataz Assem and Benedicto Crespo-Facorro and Juan Manuel Gorriz and G A Amos Burke and Stephen J Price and Thomas Santarius and Yaara Erez and John Suckling},
year = {2021},
date = {2021-10-01},
journal = {Cancers (Basel)},
volume = {13},
number = {19},
pages = {5008},
publisher = {MDPI AG},
abstract = {Predicting functional outcomes after surgery and early adjuvant
treatment is difficult due to the complex, extended,
interlocking brain networks that underpin cognition. The aim of
this study was to test glioma functional interactions with the
rest of the brain, thereby identifying the risk factors of
cognitive recovery or deterioration. Seventeen patients with
diffuse non-enhancing glioma (aged 22-56 years) were
longitudinally MRI scanned and cognitively assessed before and
after surgery and during a 12-month recovery period (55 MRI
scans in total after exclusions). We initially found, and then
replicated in an independent dataset, that the spatial
correlation pattern between regional and global BOLD signals
(also known as global signal topography) was associated with
tumour occurrence. We then estimated the coupling between the
BOLD signal from within the tumour and the signal extracted from
different brain tissues. We observed that the normative global
signal topography is reorganised in glioma patients during the
recovery period. Moreover, we found that the BOLD signal within
the tumour and lesioned brain was coupled with the global signal
and that this coupling was associated with cognitive recovery.
Nevertheless, patients did not show any apparent disruption of
functional connectivity within canonical functional networks.
Understanding how tumour infiltration and coupling are related
to patients' recovery represents a major step forward in
prognostic development.},
keywords = {brain tumours; cognitive recovery; functional MRI; global signal; neurosurgery},
pubstate = {published},
tppubtype = {article}
}
Predicting functional outcomes after surgery and early adjuvant
treatment is difficult due to the complex, extended,
interlocking brain networks that underpin cognition. The aim of
this study was to test glioma functional interactions with the
rest of the brain, thereby identifying the risk factors of
cognitive recovery or deterioration. Seventeen patients with
diffuse non-enhancing glioma (aged 22-56 years) were
longitudinally MRI scanned and cognitively assessed before and
after surgery and during a 12-month recovery period (55 MRI
scans in total after exclusions). We initially found, and then
replicated in an independent dataset, that the spatial
correlation pattern between regional and global BOLD signals
(also known as global signal topography) was associated with
tumour occurrence. We then estimated the coupling between the
BOLD signal from within the tumour and the signal extracted from
different brain tissues. We observed that the normative global
signal topography is reorganised in glioma patients during the
recovery period. Moreover, we found that the BOLD signal within
the tumour and lesioned brain was coupled with the global signal
and that this coupling was associated with cognitive recovery.
Nevertheless, patients did not show any apparent disruption of
functional connectivity within canonical functional networks.
Understanding how tumour infiltration and coupling are related
to patients' recovery represents a major step forward in
prognostic development.33. Lombardo, Michael V; Eyler, Lisa; Pramparo, Tiziano; Gazestani, Vahid H; Hagler, Donald J Jr; Chen, Chi-Hua; Dale, Anders M; Seidlitz, Jakob; Bethlehem, Richard A I; Bertelsen, Natasha; Barnes, Cynthia Carter; Lopez, Linda; Campbell, Kathleen; Lewis, Nathan E; Pierce, Karen; Courchesne, Eric
Atypical genomic cortical patterning in autism with poor early
language outcome Journal Article
In: Sci. Adv., vol. 7, no. 36, pp. eabh1663, 2021.
@article{Lombardo2021-wn,
title = {Atypical genomic cortical patterning in autism with poor early
language outcome},
author = {Michael V Lombardo and Lisa Eyler and Tiziano Pramparo and Vahid H Gazestani and Donald J Jr Hagler and Chi-Hua Chen and Anders M Dale and Jakob Seidlitz and Richard A I Bethlehem and Natasha Bertelsen and Cynthia Carter Barnes and Linda Lopez and Kathleen Campbell and Nathan E Lewis and Karen Pierce and Eric Courchesne},
year = {2021},
date = {2021-09-01},
journal = {Sci. Adv.},
volume = {7},
number = {36},
pages = {eabh1663},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Cortical regionalization develops via genomic patterning along
anterior-posterior (A-P) and dorsal-ventral (D-V) gradients.
Here, we find that normative A-P and D-V genomic patterning of
cortical surface area (SA) and thickness (CT), present in
typically developing and autistic toddlers with good early
language outcome, is absent in autistic toddlers with poor early
language outcome. Autistic toddlers with poor early language
outcome are instead specifically characterized by a secondary
and independent genomic patterning effect on CT. Genes involved
in these effects can be traced back to midgestational A-P and
D-V gene expression gradients and different prenatal cell types
(e.g., progenitor cells and excitatory neurons), are
functionally important for vocal learning and human-specific
evolution, and are prominent in prenatal coexpression networks
enriched for high-penetrance autism risk genes. Autism with poor
early language outcome may be explained by atypical genomic
cortical patterning starting in prenatal development, which may
detrimentally affect later regional functional specialization
and circuit formation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cortical regionalization develops via genomic patterning along
anterior-posterior (A-P) and dorsal-ventral (D-V) gradients.
Here, we find that normative A-P and D-V genomic patterning of
cortical surface area (SA) and thickness (CT), present in
typically developing and autistic toddlers with good early
language outcome, is absent in autistic toddlers with poor early
language outcome. Autistic toddlers with poor early language
outcome are instead specifically characterized by a secondary
and independent genomic patterning effect on CT. Genes involved
in these effects can be traced back to midgestational A-P and
D-V gene expression gradients and different prenatal cell types
(e.g., progenitor cells and excitatory neurons), are
functionally important for vocal learning and human-specific
evolution, and are prominent in prenatal coexpression networks
enriched for high-penetrance autism risk genes. Autism with poor
early language outcome may be explained by atypical genomic
cortical patterning starting in prenatal development, which may
detrimentally affect later regional functional specialization
and circuit formation.34. Park, Shinwon; Haak, Koen V; Cho, Han Byul; Valk, Sofie L; Bethlehem, Richard A I; Milham, Michael P; Bernhardt, Boris C; Martino, Adriana Di; Hong, Seok-Jun
Atypical integration of sensory-to-transmodal functional systems
mediates symptom severity in autism Journal Article
In: Front. Psychiatry, vol. 12, pp. 699813, 2021.
Abstract | BibTeX | Tags: autism spectrum disoder; connectopic mapping; cortical hierarchy; high-order system; low-level sensory; subcortico-cortical connectivity
@article{Park2021-ml,
title = {Atypical integration of sensory-to-transmodal functional systems
mediates symptom severity in autism},
author = {Shinwon Park and Koen V Haak and Han Byul Cho and Sofie L Valk and Richard A I Bethlehem and Michael P Milham and Boris C Bernhardt and Adriana Di Martino and Seok-Jun Hong},
year = {2021},
date = {2021-08-01},
journal = {Front. Psychiatry},
volume = {12},
pages = {699813},
abstract = {A notable characteristic of autism spectrum disorder (ASD) is
co-occurring deficits in low-level sensory processing and
high-order social interaction. While there is evidence indicating
detrimental cascading effects of sensory anomalies on the
high-order cognitive functions in ASD, the exact pathological
mechanism underlying their atypical functional interaction across
the cortical hierarchy has not been systematically investigated.
To address this gap, here we assessed the functional organisation
of sensory and motor areas in ASD, and their relationship with
subcortical and high-order trandmodal systems. In a resting-state
fMRI data of 107 ASD and 113 neurotypical individuals, we applied
advanced connectopic mapping to probe functional organization of
primary sensory/motor areas, together with targeted seed-based
intrinsic functional connectivity (iFC) analyses. In ASD, the
connectopic mapping revealed topological anomalies (i.e.,
excessively more segregated iFC) in the motor and visual areas,
the former of which patterns showed association with the symptom
severity of restricted and repetitive behaviors. Moreover, the
seed-based analysis found diverging patterns of ASD-related
connectopathies: decreased iFCs within the sensory/motor areas
but increased iFCs between sensory and subcortical structures.
While decreased iFCs were also found within the higher-order
functional systems, the overall proportion of this anomaly tends
to increase along the level of cortical hierarchy, suggesting
more dysconnectivity in the higher-order functional networks.
Finally, we demonstrated that the association between low-level
sensory/motor iFCs and clinical symptoms in ASD was mediated by
the high-order transmodal systems, suggesting pathogenic
functional interactions along the cortical hierarchy. Findings
were largely replicated in the independent dataset. These results
highlight that atypical integration of sensory-to-high-order
systems contributes to the complex ASD symptomatology.},
keywords = {autism spectrum disoder; connectopic mapping; cortical hierarchy; high-order system; low-level sensory; subcortico-cortical connectivity},
pubstate = {published},
tppubtype = {article}
}
A notable characteristic of autism spectrum disorder (ASD) is
co-occurring deficits in low-level sensory processing and
high-order social interaction. While there is evidence indicating
detrimental cascading effects of sensory anomalies on the
high-order cognitive functions in ASD, the exact pathological
mechanism underlying their atypical functional interaction across
the cortical hierarchy has not been systematically investigated.
To address this gap, here we assessed the functional organisation
of sensory and motor areas in ASD, and their relationship with
subcortical and high-order trandmodal systems. In a resting-state
fMRI data of 107 ASD and 113 neurotypical individuals, we applied
advanced connectopic mapping to probe functional organization of
primary sensory/motor areas, together with targeted seed-based
intrinsic functional connectivity (iFC) analyses. In ASD, the
connectopic mapping revealed topological anomalies (i.e.,
excessively more segregated iFC) in the motor and visual areas,
the former of which patterns showed association with the symptom
severity of restricted and repetitive behaviors. Moreover, the
seed-based analysis found diverging patterns of ASD-related
connectopathies: decreased iFCs within the sensory/motor areas
but increased iFCs between sensory and subcortical structures.
While decreased iFCs were also found within the higher-order
functional systems, the overall proportion of this anomaly tends
to increase along the level of cortical hierarchy, suggesting
more dysconnectivity in the higher-order functional networks.
Finally, we demonstrated that the association between low-level
sensory/motor iFCs and clinical symptoms in ASD was mediated by
the high-order transmodal systems, suggesting pathogenic
functional interactions along the cortical hierarchy. Findings
were largely replicated in the independent dataset. These results
highlight that atypical integration of sensory-to-high-order
systems contributes to the complex ASD symptomatology.35. Gau, Rémi; Noble, Stephanie; Heuer, Katja; Bottenhorn, Katherine L; Bilgin, Isil P; Yang, Yu-Fang; Huntenburg, Julia M; Bayer, Johanna M M; Bethlehem, Richard A I; Rhoads, Shawn A; Vogelbacher, Christoph; Borghesani, Valentina; Levitis, Elizabeth; Wang, Hao-Ting; Bossche, Sofie Van Den; Kobeleva, Xenia; Legarreta, Jon Haitz; Guay, Samuel; Atay, Selim Melvin; Varoquaux, Gael P; Huijser, Dorien C; Sandström, Malin S; Herholz, Peer; Nastase, Samuel A; Badhwar, Amanpreet; Dumas, Guillaume; Schwab, Simon; Moia, Stefano; Dayan, Michael; Bassil, Yasmine; Brooks, Paula P; Mancini, Matteo; Shine, James M; O'Connor, David; Xie, Xihe; Poggiali, Davide; Friedrich, Patrick; Heinsfeld, Anibal S; Riedl, Lydia; Toro, Roberto; Caballero-Gaudes, César; Eklund, Anders; Garner, Kelly G; Nolan, Christopher R; Demeter, Damion V; Barrios, Fernando A; Merchant, Junaid S; McDevitt, Elizabeth A; Oostenveld, Robert; Craddock, R Cameron; Rokem, Ariel; Doyle, Andrew; Ghosh, Satrajit S; Nikolaidis, Aki; Stanley, Olivia W; Uruñuela, Eneko; Community, Brainhack
Brainhack: Developing a culture of open, inclusive,
community-driven neuroscience Journal Article
In: Neuron, vol. 109, no. 11, pp. 1769–1775, 2021.
Abstract | BibTeX | Tags: Brainhack; best practices; collaboration; community building; hackathon; inclusivity; neuroscience; open science; reproducibility; training
@article{Gau2021-lr,
title = {Brainhack: Developing a culture of open, inclusive,
community-driven neuroscience},
author = {Rémi Gau and Stephanie Noble and Katja Heuer and Katherine L Bottenhorn and Isil P Bilgin and Yu-Fang Yang and Julia M Huntenburg and Johanna M M Bayer and Richard A I Bethlehem and Shawn A Rhoads and Christoph Vogelbacher and Valentina Borghesani and Elizabeth Levitis and Hao-Ting Wang and Sofie Van Den Bossche and Xenia Kobeleva and Jon Haitz Legarreta and Samuel Guay and Selim Melvin Atay and Gael P Varoquaux and Dorien C Huijser and Malin S Sandström and Peer Herholz and Samuel A Nastase and Amanpreet Badhwar and Guillaume Dumas and Simon Schwab and Stefano Moia and Michael Dayan and Yasmine Bassil and Paula P Brooks and Matteo Mancini and James M Shine and David O'Connor and Xihe Xie and Davide Poggiali and Patrick Friedrich and Anibal S Heinsfeld and Lydia Riedl and Roberto Toro and César Caballero-Gaudes and Anders Eklund and Kelly G Garner and Christopher R Nolan and Damion V Demeter and Fernando A Barrios and Junaid S Merchant and Elizabeth A McDevitt and Robert Oostenveld and R Cameron Craddock and Ariel Rokem and Andrew Doyle and Satrajit S Ghosh and Aki Nikolaidis and Olivia W Stanley and Eneko Uruñuela and Brainhack Community},
year = {2021},
date = {2021-06-01},
journal = {Neuron},
volume = {109},
number = {11},
pages = {1769–1775},
publisher = {Elsevier BV},
abstract = {Brainhack is an innovative meeting format that promotes
scientific collaboration and education in an open, inclusive
environment. This NeuroView describes the myriad benefits for
participants and the research community and how Brainhacks
complement conventional formats to augment scientific progress.},
keywords = {Brainhack; best practices; collaboration; community building; hackathon; inclusivity; neuroscience; open science; reproducibility; training},
pubstate = {published},
tppubtype = {article}
}
Brainhack is an innovative meeting format that promotes
scientific collaboration and education in an open, inclusive
environment. This NeuroView describes the myriad benefits for
participants and the research community and how Brainhacks
complement conventional formats to augment scientific progress.36. Bertelsen, Natasha; Landi, Isotta; Bethlehem, Richard A I; Seidlitz, Jakob; Busuoli, Elena Maria; Mandelli, Veronica; Satta, Eleonora; Trakoshis, Stavros; Auyeung, Bonnie; Kundu, Prantik; Loth, Eva; Dumas, Guillaume; Baumeister, Sarah; Beckmann, Christian F; Bölte, Sven; Bourgeron, Thomas; Charman, Tony; Durston, Sarah; Ecker, Christine; Holt, Rosemary J; Johnson, Mark H; Jones, Emily J H; Mason, Luke; Meyer-Lindenberg, Andreas; Moessnang, Carolin; Oldehinkel, Marianne; Persico, Antonio M; Tillmann, Julian; Williams, Steve C R; Spooren, Will; Murphy, Declan G M; Buitelaar, Jan K; group, EU-AIMS LEAP; Baron-Cohen, Simon; Lai, Meng-Chuan; Lombardo, Michael V
Imbalanced social-communicative and restricted repetitive
behavior subtypes of autism spectrum disorder exhibit different
neural circuitry Journal Article
In: Commun. Biol., vol. 4, no. 1, pp. 574, 2021.
@article{Bertelsen2021-ky,
title = {Imbalanced social-communicative and restricted repetitive
behavior subtypes of autism spectrum disorder exhibit different
neural circuitry},
author = {Natasha Bertelsen and Isotta Landi and Richard A I Bethlehem and Jakob Seidlitz and Elena Maria Busuoli and Veronica Mandelli and Eleonora Satta and Stavros Trakoshis and Bonnie Auyeung and Prantik Kundu and Eva Loth and Guillaume Dumas and Sarah Baumeister and Christian F Beckmann and Sven Bölte and Thomas Bourgeron and Tony Charman and Sarah Durston and Christine Ecker and Rosemary J Holt and Mark H Johnson and Emily J H Jones and Luke Mason and Andreas Meyer-Lindenberg and Carolin Moessnang and Marianne Oldehinkel and Antonio M Persico and Julian Tillmann and Steve C R Williams and Will Spooren and Declan G M Murphy and Jan K Buitelaar and EU-AIMS LEAP group and Simon Baron-Cohen and Meng-Chuan Lai and Michael V Lombardo},
year = {2021},
date = {2021-05-01},
journal = {Commun. Biol.},
volume = {4},
number = {1},
pages = {574},
publisher = {Springer Science and Business Media LLC},
abstract = {Social-communication (SC) and restricted repetitive behaviors
(RRB) are autism diagnostic symptom domains. SC and RRB severity
can markedly differ within and between individuals and may be
underpinned by different neural circuitry and genetic
mechanisms. Modeling SC-RRB balance could help identify how
neural circuitry and genetic mechanisms map onto such phenotypic
heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC =
RRB, SC > RRB, and RRB > SC subtype predictions. Applying this
model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many
commonalities in terms of intrinsic functional connectivity,
they also show replicable differences within some networks
compared to a typically-developing group (TD). Specifically, the
somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and
anterior salience circuitry. Genes that are highly expressed
within these networks show a differential enrichment pattern
with known autism-associated genes, indicating that such
circuits are affected by differing autism-associated genomic
mechanisms. These results suggest that SC-RRB imbalance subtypes
share many commonalities, but also express subtle differences in
functional neural circuitry and the genomic underpinnings behind
such circuitry.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Social-communication (SC) and restricted repetitive behaviors
(RRB) are autism diagnostic symptom domains. SC and RRB severity
can markedly differ within and between individuals and may be
underpinned by different neural circuitry and genetic
mechanisms. Modeling SC-RRB balance could help identify how
neural circuitry and genetic mechanisms map onto such phenotypic
heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC =
RRB, SC > RRB, and RRB > SC subtype predictions. Applying this
model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many
commonalities in terms of intrinsic functional connectivity,
they also show replicable differences within some networks
compared to a typically-developing group (TD). Specifically, the
somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and
anterior salience circuitry. Genes that are highly expressed
within these networks show a differential enrichment pattern
with known autism-associated genes, indicating that such
circuits are affected by differing autism-associated genomic
mechanisms. These results suggest that SC-RRB imbalance subtypes
share many commonalities, but also express subtle differences in
functional neural circuitry and the genomic underpinnings behind
such circuitry.37. Chye, Yann; Suo, Chao; Romero-Garcia, Rafael; Bethlehem, Richard A I; Hook, Roxanne; Tiego, Jeggan; Goodyer, Ian; Jones, Peter B; Dolan, Ray; Bullmore, Edward T; Grant, Jon E; Yücel, Murat; Chamberlain, Samuel R
Examining the relationship between altered brain functional
connectome and disinhibition across 33 impulsive and compulsive
behaviours Journal Article
In: Br. J. Psychiatry, vol. 220, no. 2, pp. 1–3, 2021.
Abstract | BibTeX | Tags: Impulsivity; brain network; compulsivity; connectome; transdiagnostic
@article{Chye2021-rs,
title = {Examining the relationship between altered brain functional
connectome and disinhibition across 33 impulsive and compulsive
behaviours},
author = {Yann Chye and Chao Suo and Rafael Romero-Garcia and Richard A I Bethlehem and Roxanne Hook and Jeggan Tiego and Ian Goodyer and Peter B Jones and Ray Dolan and Edward T Bullmore and Jon E Grant and Murat Yücel and Samuel R Chamberlain},
year = {2021},
date = {2021-05-01},
journal = {Br. J. Psychiatry},
volume = {220},
number = {2},
pages = {1–3},
publisher = {Royal College of Psychiatrists},
abstract = {Impulsive and compulsive problem behaviours are associated with
a variety of mental disorders. Latent phenotyping indicates the
expression of impulsive and compulsive problem behaviours is
predominantly governed by a transdiagnostic 'disinhibition'
phenotype. In a cohort of 117 individuals, recruited as part of
the Neuroscience in Psychiatry Network (NSPN), we examined how
brain functional connectome and network properties relate to
disinhibition. Reduced functional connectivity within a
subnetwork of frontal (especially right inferior frontal gyrus),
occipital and parietal regions was linked to disinhibition.
Findings provide insights into neurobiological pathways
underlying the emergence of impulsive and compulsive disorders.},
keywords = {Impulsivity; brain network; compulsivity; connectome; transdiagnostic},
pubstate = {published},
tppubtype = {article}
}
Impulsive and compulsive problem behaviours are associated with
a variety of mental disorders. Latent phenotyping indicates the
expression of impulsive and compulsive problem behaviours is
predominantly governed by a transdiagnostic 'disinhibition'
phenotype. In a cohort of 117 individuals, recruited as part of
the Neuroscience in Psychiatry Network (NSPN), we examined how
brain functional connectome and network properties relate to
disinhibition. Reduced functional connectivity within a
subnetwork of frontal (especially right inferior frontal gyrus),
occipital and parietal regions was linked to disinhibition.
Findings provide insights into neurobiological pathways
underlying the emergence of impulsive and compulsive disorders.38. Park, Bo-Yong; Hong, Seok-Jun; Valk, Sofie L; Paquola, Casey; Benkarim, Oualid; Bethlehem, Richard A I; Martino, Adriana Di; Milham, Michael P; Gozzi, Alessandro; Yeo, B T Thomas; Smallwood, Jonathan; Bernhardt, Boris C
Differences in subcortico-cortical interactions identified from
connectome and microcircuit models in autism Journal Article
In: Nat. Commun., vol. 12, no. 1, pp. 2225, 2021.
@article{Park2021-ie,
title = {Differences in subcortico-cortical interactions identified from
connectome and microcircuit models in autism},
author = {Bo-Yong Park and Seok-Jun Hong and Sofie L Valk and Casey Paquola and Oualid Benkarim and Richard A I Bethlehem and Adriana Di Martino and Michael P Milham and Alessandro Gozzi and B T Thomas Yeo and Jonathan Smallwood and Boris C Bernhardt},
year = {2021},
date = {2021-04-01},
journal = {Nat. Commun.},
volume = {12},
number = {1},
pages = {2225},
publisher = {Springer Science and Business Media LLC},
abstract = {The pathophysiology of autism has been suggested to involve a
combination of both macroscale connectome miswiring and
microcircuit anomalies. Here, we combine connectome-wide
manifold learning with biophysical simulation models to
understand associations between global network perturbations and
microcircuit dysfunctions in autism. We studied neuroimaging and
phenotypic data in 47 individuals with autism and 37 typically
developing controls obtained from the Autism Brain Imaging Data
Exchange initiative. Our analysis establishes significant
differences in structural connectome organization in individuals
with autism relative to controls, with strong between-group
effects in low-level somatosensory regions and moderate effects
in high-level association cortices. Computational models reveal
that the degree of macroscale anomalies is related to atypical
increases of recurrent excitation/inhibition, as well as
subcortical inputs into cortical microcircuits, especially in
sensory and motor areas. Transcriptomic association analysis
based on postmortem datasets identifies genes expressed in
cortical and thalamic areas from childhood to young adulthood.
Finally, supervised machine learning finds that the macroscale
perturbations are associated with symptom severity scores on the
Autism Diagnostic Observation Schedule. Together, our analyses
suggest that atypical subcortico-cortical interactions are
associated with both microcircuit and macroscale connectome
differences in autism.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The pathophysiology of autism has been suggested to involve a
combination of both macroscale connectome miswiring and
microcircuit anomalies. Here, we combine connectome-wide
manifold learning with biophysical simulation models to
understand associations between global network perturbations and
microcircuit dysfunctions in autism. We studied neuroimaging and
phenotypic data in 47 individuals with autism and 37 typically
developing controls obtained from the Autism Brain Imaging Data
Exchange initiative. Our analysis establishes significant
differences in structural connectome organization in individuals
with autism relative to controls, with strong between-group
effects in low-level somatosensory regions and moderate effects
in high-level association cortices. Computational models reveal
that the degree of macroscale anomalies is related to atypical
increases of recurrent excitation/inhibition, as well as
subcortical inputs into cortical microcircuits, especially in
sensory and motor areas. Transcriptomic association analysis
based on postmortem datasets identifies genes expressed in
cortical and thalamic areas from childhood to young adulthood.
Finally, supervised machine learning finds that the macroscale
perturbations are associated with symptom severity scores on the
Autism Diagnostic Observation Schedule. Together, our analyses
suggest that atypical subcortico-cortical interactions are
associated with both microcircuit and macroscale connectome
differences in autism.39. Park, Bo-Yong; Bethlehem, Richard Ai; Paquola, Casey; Larivière, Sara; Rodríguez-Cruces, Raul; de Wael, Reinder Vos; Consortium, Neuroscience Psychiatry Network (NSPN); Bullmore, Edward T; Bernhardt, Boris C
An expanding manifold in transmodal regions characterizes
adolescent reconfiguration of structural connectome organization Journal Article
In: Elife, vol. 10, 2021.
Abstract | BibTeX | Tags: adolescence; connectome; human; longitudinal; multi-scale; neurodevelopment; neuroimaging; neuroscience
@article{Park2021-ap,
title = {An expanding manifold in transmodal regions characterizes
adolescent reconfiguration of structural connectome organization},
author = {Bo-Yong Park and Richard Ai Bethlehem and Casey Paquola and Sara Larivière and Raul Rodríguez-Cruces and Reinder Vos de Wael and Neuroscience Psychiatry Network (NSPN) Consortium and Edward T Bullmore and Boris C Bernhardt},
year = {2021},
date = {2021-03-01},
journal = {Elife},
volume = {10},
publisher = {eLife Sciences Publications, Ltd},
abstract = {Adolescence is a critical time for the continued maturation of
brain networks. Here, we assessed structural connectome
development in a large longitudinal sample ranging from
childhood to young adulthood. By projecting high-dimensional
connectomes into compact manifold spaces, we identified a marked
expansion of structural connectomes, with strongest effects in
transmodal regions during adolescence. Findings reflected
increased within-module connectivity together with increased
segregation, indicating increasing differentiation of
higher-order association networks from the rest of the brain.
Projection of subcortico-cortical connectivity patterns into
these manifolds showed parallel alterations in pathways centered
on the caudate and thalamus. Connectome findings were
contextualized via spatial transcriptome association analysis,
highlighting genes enriched in cortex, thalamus, and striatum.
Statistical learning of cortical and subcortical manifold
features at baseline and their maturational change predicted
measures of intelligence at follow-up. Our findings demonstrate
that connectome manifold learning can bridge the conceptual and
empirical gaps between macroscale network reconfigurations,
microscale processes, and cognitive outcomes in adolescent
development.},
keywords = {adolescence; connectome; human; longitudinal; multi-scale; neurodevelopment; neuroimaging; neuroscience},
pubstate = {published},
tppubtype = {article}
}
Adolescence is a critical time for the continued maturation of
brain networks. Here, we assessed structural connectome
development in a large longitudinal sample ranging from
childhood to young adulthood. By projecting high-dimensional
connectomes into compact manifold spaces, we identified a marked
expansion of structural connectomes, with strongest effects in
transmodal regions during adolescence. Findings reflected
increased within-module connectivity together with increased
segregation, indicating increasing differentiation of
higher-order association networks from the rest of the brain.
Projection of subcortico-cortical connectivity patterns into
these manifolds showed parallel alterations in pathways centered
on the caudate and thalamus. Connectome findings were
contextualized via spatial transcriptome association analysis,
highlighting genes enriched in cortex, thalamus, and striatum.
Statistical learning of cortical and subcortical manifold
features at baseline and their maturational change predicted
measures of intelligence at follow-up. Our findings demonstrate
that connectome manifold learning can bridge the conceptual and
empirical gaps between macroscale network reconfigurations,
microscale processes, and cognitive outcomes in adolescent
development.40. Romero-Garcia, Rafa; Hook, Roxanne W; Tiego, Jeggan; Bethlehem, Richard A I; Goodyer, Ian M; Jones, Peter B; Dolan, Ray; Grant, Jon E; Bullmore, Edward T; Yücel, Murat; Chamberlain, Samuel R
Brain micro-architecture and disinhibition: a latent phenotyping
study across 33 impulsive and compulsive behaviours Journal Article
In: Neuropsychopharmacology, vol. 46, no. 2, pp. 423–431, 2021.
@article{Romero-Garcia2021-kn,
title = {Brain micro-architecture and disinhibition: a latent phenotyping
study across 33 impulsive and compulsive behaviours},
author = {Rafa Romero-Garcia and Roxanne W Hook and Jeggan Tiego and Richard A I Bethlehem and Ian M Goodyer and Peter B Jones and Ray Dolan and Jon E Grant and Edward T Bullmore and Murat Yücel and Samuel R Chamberlain},
year = {2021},
date = {2021-01-01},
journal = {Neuropsychopharmacology},
volume = {46},
number = {2},
pages = {423–431},
publisher = {Springer Science and Business Media LLC},
abstract = {Impulsive and compulsive symptoms are common, tend to co-occur,
and collectively account for a substantive global disease
burden. Latent phenotyping offers a promising approach to
elucidate common neural mechanisms conferring vulnerability to
such symptoms in the general population. We utilised the
Neuroscience in Psychiatry Network (NSPN), a cohort of young
people (aged 18-29 years) in the United Kingdom, who provided
questionnaire data and Magnetic Resonance Imaging scans. Partial
Least Squares was used to identify brain regions in which
intra-cortical myelination (measured using Magnetisation
Transfer, MT) was significantly associated with a disinhibition
phenotype, derived from bi-factor modelling of 33 impulsive and
compulsive problem behaviours. The neuroimaging sample comprised
126 participants, mean 22.8 (2.7 SD) years old, being 61.1%
female. Disinhibition scores were significantly and positively
associated with higher MT in the bilateral frontal and parietal
lobes. 1279 genes associated with disinhibition-related brain
regions were identified, which were significantly enriched for
functional biological interactions reflecting receptor
signalling pathways. This study indicates common microstructural
brain abnormalities contributing to a multitude of related,
prevalent, problem behaviours characterised by disinhibition.
Such a latent phenotyping approach provides insights into common
neurobiological pathways, which may help to improve disease
models and treatment approaches. Now that this latent
phenotyping model has been validated in a general population
sample, it can be extended into patient settings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Impulsive and compulsive symptoms are common, tend to co-occur,
and collectively account for a substantive global disease
burden. Latent phenotyping offers a promising approach to
elucidate common neural mechanisms conferring vulnerability to
such symptoms in the general population. We utilised the
Neuroscience in Psychiatry Network (NSPN), a cohort of young
people (aged 18-29 years) in the United Kingdom, who provided
questionnaire data and Magnetic Resonance Imaging scans. Partial
Least Squares was used to identify brain regions in which
intra-cortical myelination (measured using Magnetisation
Transfer, MT) was significantly associated with a disinhibition
phenotype, derived from bi-factor modelling of 33 impulsive and
compulsive problem behaviours. The neuroimaging sample comprised
126 participants, mean 22.8 (2.7 SD) years old, being 61.1%
female. Disinhibition scores were significantly and positively
associated with higher MT in the bilateral frontal and parietal
lobes. 1279 genes associated with disinhibition-related brain
regions were identified, which were significantly enriched for
functional biological interactions reflecting receptor
signalling pathways. This study indicates common microstructural
brain abnormalities contributing to a multitude of related,
prevalent, problem behaviours characterised by disinhibition.
Such a latent phenotyping approach provides insights into common
neurobiological pathways, which may help to improve disease
models and treatment approaches. Now that this latent
phenotyping model has been validated in a general population
sample, it can be extended into patient settings.