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1
Rebello, Keila, Luciana M. Moura, Walter H. L. Pinaya, Luis A. Rohde, and João R. Sato. "Default Mode Network Maturation and Environmental Adversities During Childhood." Chronic Stress 2 (January 2018): 247054701880829. http://dx.doi.org/10.1177/2470547018808295.
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Default mode network (DMN) plays a central role in cognition and brain disorders. It has been shown that adverse environmental conditions impact neurodevelopment, but how these conditions impact in DMN maturation is still poorly understood. This article reviews representative neuroimaging functional studies addressing the interactions between DMN development and environmental factors, focusing on early life adversities, a critical period for brain changes. Studies focused on this period of life offer a special challenge: to disentangle the neurodevelopmental connectivity changes from those related to environmental conditions. We first summarized the literature on DMN maturation, providing an overview of both typical and atypical development patterns in childhood and early adolescence. Afterward, we focused on DMN changes associated with chronic exposure to environmental adversities during childhood. This summary suggests that changes in DMN development could be a potential allostatic neural feature associated with an embodiment of environmental circumstances. Finally, we discuss about some key methodological issues that should be considered in paradigms addressing environmental adversities and open questions for future investigations.
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Lee, Junghan, Deokjong Lee, Kee Namkoong, and Young-Chul Jung. "Aberrant posterior superior temporal sulcus functional connectivity and executive dysfunction in adolescents with internet gaming disorder." Journal of Behavioral Addictions 9, no. 3 (October 12, 2020): 589–97. http://dx.doi.org/10.1556/2006.2020.00060.
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AbstractBackground and aimsThe clinical significance of Internet gaming disorder (IGD) is spreading worldwide, but its underlying neural mechanism still remains unclear. Moreover, the prevalence of IGD seems to be the highest in adolescents whose brains are in development. This study investigated the functional connectivity between large-scale intrinsic networks including default mode network, executive control network, and salience network. We hypothesized that adolescents with IGD would demonstrate different functional connectivity patterns among large-scale intrinsic networks, implying neurodevelopmental alterations, which might be associated with executive dysfunction.MethodsThis study included 17 male adolescents with Internet gaming disorder, and 18 age-matched male adolescents as healthy controls. Functional connectivity was examined using seed-to-voxel analysis and seed-to-seed analysis, with the nodes of large-scale intrinsic networks used as region of interests. Group independent component analysis was performed to investigate spatially independent network.ResultsWe identified aberrant functional connectivity of salience network and default mode network with the left posterior superior temporal sulcus (pSTS) in adolescents with IGD. Furthermore, functional connectivity between salience network and pSTS correlated with proneness to Internet addiction and self-reported cognitive problems. Independent component analysis revealed that pSTS was involved in social brain network.Discussion and conclusionsThe results imply that aberrant functional connectivity of social brain network with default mode network and salience network was identified in IGD that may be associated with executive dysfunction. Our results suggest that inordinate social stimuli during excessive online gaming leads to altered connections among large-scale networks during neurodevelopment of adolescents.
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Van den Bergh, Bea R. H., Robert Dahnke, and Maarten Mennes. "Prenatal stress and the developing brain: Risks for neurodevelopmental disorders." Development and Psychopathology 30, no. 3 (August 2018): 743–62. http://dx.doi.org/10.1017/s0954579418000342.
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AbstractThe prenatal period is increasingly considered as a crucial target for the primary prevention of neurodevelopmental and psychiatric disorders. Understanding their pathophysiological mechanisms remains a great challenge. Our review reveals new insights from prenatal brain development research, involving (epi)genetic research, neuroscience, recent imaging techniques, physical modeling, and computational simulation studies. Studies examining the effect of prenatal exposure to maternal distress on offspring brain development, using brain imaging techniques, reveal effects at birth and up into adulthood. Structural and functional changes are observed in several brain regions including the prefrontal, parietal, and temporal lobes, as well as the cerebellum, hippocampus, and amygdala. Furthermore, alterations are seen in functional connectivity of amygdalar–thalamus networks and in intrinsic brain networks, including default mode and attentional networks. The observed changes underlie offspring behavioral, cognitive, emotional development, and susceptibility to neurodevelopmental and psychiatric disorders. It is concluded that used brain measures have not yet been validated with regard to sensitivity, specificity, accuracy, or robustness in predicting neurodevelopmental and psychiatric disorders. Therefore, more prospective long-term longitudinal follow-up studies starting early in pregnancy should be carried out, in order to examine brain developmental measures as mediators in mediating the link between prenatal stress and offspring behavioral, cognitive, and emotional problems and susceptibility for disorders.
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Missault, Stephan, Cynthia Anckaerts, Soumaya Ahmadoun, Ines Blockx, Michaël Barbier, Kenny Bielen, Disha Shah, et al. "Hypersynchronicity in the default mode-like network in a neurodevelopmental animal model with relevance for schizophrenia." Behavioural Brain Research 364 (May 2019): 303–16. http://dx.doi.org/10.1016/j.bbr.2019.02.040.
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Picon, Felipe Almeida, João Ricardo Sato, Maurício Anés, Leonardo Modesti Vedolin, Alessandro André Mazzola, Bruna Bressan Valentini, Renata Basso Cupertino, et al. "Methylphenidate Alters Functional Connectivity of Default Mode Network in Drug-Naive Male Adults With ADHD." Journal of Attention Disorders 24, no. 3 (December 10, 2018): 447–55. http://dx.doi.org/10.1177/1087054718816822.
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Objective: This study evaluated the hypothesis that methylphenidate immediate release (MPH-IR) treatment would improve Default Mode Network (DMN) within-connectivity. Method: Resting-state functional connectivity of the main nodes of DMN was evaluated in a highly homogeneous sample of 18 drug-naive male adult participants with ADHD. Results: Comparing resting-state functional connectivity functional magnetic resonance imaging (R-fMRI) scans before and after MPH treatment focusing exclusively on within-DMN connectivity, we evidenced the strengthening of functional connectivity between two nodes of the DMN: posterior cingulate cortex (PCC) and left lateral parietal cortex (LLP). Conclusion: Our results contribute to the further understanding on how MPH affects functional connectivity within DMN of male adults with ADHD and corroborate the hypothesis of ADHD being a delayed neurodevelopmental disorder.
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Wang, Kai, Mingyu Xu, Yiting Ji, Lingli Zhang, Xiujuan Du, Jijun Li, Qiang Luo, and Fei Li. "Altered social cognition and connectivity of default mode networks in the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder." Australian & New Zealand Journal of Psychiatry 53, no. 8 (March 7, 2019): 760–71. http://dx.doi.org/10.1177/0004867419836031.
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Objective: As two common neurodevelopmental disorders, autistic spectrum disorder and attention deficit hyperactivity disorder frequently occur together. Until now, only a few studies have investigated the co-occurrence of attention deficit hyperactivity disorder and autistic spectrum disorder, this is due to restrictions associated with previous Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. Most previous research has focused on the developmental trajectories for autistic spectrum disorder and attention deficit hyperactivity disorder separately, while the neural mechanisms underpinning the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder remain largely unknown. Methods: We studied 162 autistic spectrum disorder individuals (including 79 co-attention deficit hyperactivity disorder and 83 non-attention deficit hyperactivity disorder patients) and 177 typical developing individuals using resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange II, an aggregated magnetic resonance imaging dataset from 19 centers. Independent component analysis was used to extract sub-networks from the classic resting-state networks. Functional connectivity values within (intra-iFC) and between (inter-iFC) these networks were then determined. Subsequently, we compared the ASD_coADHD group with the ASD_nonADHD group in relation to the abnormal intra-iFC and inter-iFC of autistic spectrum disorder group relative to the typical developing group. Results: The ASD_coADHD group showed more severe social impairment and decreased intra-iFC in the bilateral posterior cingulate cortex of the default mode network (independent component 17) and increased inter-iFC between the default mode network (independent component 8) and the somatomotor networks (independent component 2) compared to the ASD_nonADHD group. In addition, the strength of the intra-iFC in the default mode network was associated with the severity of autistic traits across the entire autistic spectrum disorder group and particularly the ASD_coADHD group. Conclusion: Our results showed that dysfunction of the default mode network is a central feature in the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder, including connectivity within the default mode network as well as between the default mode network and the somatomotor networks, thus supporting the existence of a clinically combined phenotype (autistic spectrum disorder + attention deficit hyperactivity disorder).
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Hilger, Kirsten, and Christian J. Fiebach. "ADHD symptoms are associated with the modular structure of intrinsic brain networks in a representative sample of healthy adults." Network Neuroscience 3, no. 2 (January 2019): 567–88. http://dx.doi.org/10.1162/netn_a_00083.
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Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders with significant and often lifelong effects on social, emotional, and cognitive functioning. Influential neurocognitive models of ADHD link behavioral symptoms to altered connections between and within functional brain networks. Here, we investigate whether network-based theories of ADHD can be generalized to understanding variations in ADHD-related behaviors within the normal (i.e., clinically unaffected) adult population. In a large and representative sample, self-rated presence of ADHD symptoms varied widely; only 8 out of 291 participants scored in the clinical range. Subject-specific brain network graphs were modeled from functional MRI resting-state data and revealed significant associations between (nonclinical) ADHD symptoms and region-specific profiles of between-module and within-module connectivity. Effects were located in brain regions associated with multiple neuronal systems including the default-mode network, the salience network, and the central executive system. Our results are consistent with network perspectives of ADHD and provide further evidence for the relevance of an appropriate information transfer between task-negative (default-mode) and task-positive brain regions. More generally, our findings support a dimensional conceptualization of ADHD and contribute to a growing understanding of cognition as an emerging property of functional brain networks.
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Leveque, Yohana, Baptiste Fauvel, Mathilde Groussard, Anne Caclin, Philippe Albouy, Hervé Platel, and Barbara Tillmann. "Altered intrinsic connectivity of the auditory cortex in congenital amusia." Journal of Neurophysiology 116, no. 1 (July 1, 2016): 88–97. http://dx.doi.org/10.1152/jn.00663.2015.
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Congenital amusia, a neurodevelopmental disorder of music perception and production, has been associated with abnormal anatomical and functional connectivity in a right frontotemporal pathway. To investigate whether spontaneous connectivity in brain networks involving the auditory cortex is altered in the amusic brain, we ran a seed-based connectivity analysis, contrasting at-rest functional MRI data of amusic and matched control participants. Our results reveal reduced frontotemporal connectivity in amusia during resting state, as well as an overconnectivity between the auditory cortex and the default mode network (DMN). The findings suggest that the auditory cortex is intrinsically more engaged toward internal processes and less available to external stimuli in amusics compared with controls. Beyond amusia, our findings provide new evidence for the link between cognitive deficits in pathology and abnormalities in the connectivity between sensory areas and the DMN at rest.
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Pereira, V., P. de Castro-Manglano, and C. Soutullo Esperon. "Brain development in attention deficit hyperactivity disorder: A neuroimaging perspective review." European Psychiatry 33, S1 (March 2016): S357. http://dx.doi.org/10.1016/j.eurpsy.2016.01.1277.
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IntroductionAttention deficit hyperactivity disorder (ADHD) is a challenge in child and adolescent psychiatry. In the recent decades many studies with longitudinal designs have used neuroimaging with ADHD patients, suggesting its neurodevelopmental origin.ObjectivesStudy the findings of neuroimaging (MRI, fMRI, DTI, PET) techniques on ADHD patients from a longitudinal point of view, looking also for the potential influence of treatments and other predictors (i.e. genetics).AimsTo provide a global perspective of all the recent findings on ADHD patients with the neuroimaging technics, focusing on longitudinal measurements of the changes in brain development.MethodsWe conducted a review of the literature in the databases Pubmed and ScienceDirect (terms ADHD, neuroimaging, MRI, fMRI, DTI, PET, functional connectivity, metilphenidate and cortical thickness). We focused on studies using neuroimaging techniques with ADHD patients, looking at their populations, methodologies and results.ResultsThe studies found abnormalities in the structure of grey matter, activity and brain connectivity in many neural networks, with particular involvement of the fronto-parietal and Default Mode Network. There is also convergent evidence for white matter pathology and disrupted anatomical connectivity in ADHD. In addition, dysfunctional connectivity during rest and during cognitive tasks has been demonstrated.ConclusionsThis evidence describe ADHD as a brain development disorder, with delays and disruptions in the global development of the central nervous system that compromises grey and white matters, most evident in the prefrontal cortex, parietal and posterior cingulate cortices, as well as basal ganglia, damaging activity and structural and functional connectivity of various brain networks, especially the fronto-striato-parietal and default mode network.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Pereira, V., and P. de Castro-Manglano. "The Effects of Medication on Default Mode Network (DMN) Connectivity in Attention Deficit/hyperactivity Disorder (ADHD): Bibliographic Review." European Psychiatry 41, S1 (April 2017): S629. http://dx.doi.org/10.1016/j.eurpsy.2017.01.1022.
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IntroductionADHD is a neurodevelopmental disorder comprising brain structural and functional alterations, especially in default mode network (DMN), as MRI studies have recently shown. However, it is not clear in which extent medication for ADHD may influence the activity of these networks.ObjectivesThe main purpose is to look up published evidence about the effects of ADHD medication on the connectivity of DMN in patients as measured with functional-MRI.MethodsA review was conducted with Pubmed, using search terms ‘default mode network’+ ‘ADHD’ + ‘medication’/‘methylphenidate’/‘atomoxetine’/‘stimulant’/‘lisdexanfetamine’. Original research studies in English using f-MRI to assess DMN connectivity in ADHD patients were included in a more comprehensive review.ResultsThe searches found 124 articles, 8 meeting the review criteria. A total size of 146 ADHD patients was comprised (mean size: 18.25 patients). Three studies used specific resting-state f-MRI. Seven were drug trials, 3 of them short-term, randomized and controlled ones. Six included methylphenidate, 2 atomoxetine, 1 lisdexanfetamine and 3 amphetamines. Two also assessed drugs clinical effects. Evidence seems heterogeneous, but mostly consistent with normalizing drug effects on DMN in patients (in some studies also compared with healthy controls), associated with a measured clinical improvement in one study with amphetamines and one with atomoxetine. One trial found little differences on DMN activity.ConclusionsPsychostimulant drugs and atomoxetine are clinically effective medications; DMN connectivity may partially explain their action mechanisms and constitute a potential response predictor. Further f-MRI studies might more deeply assess the imaging-clinical relationships for each drug.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Ilves, Nigul, Pilvi Ilves, Rael Laugesaar, Julius Juurmaa, Mairi Männamaa, Silva Lõo, Dagmar Loorits, et al. "Resting-State Functional Connectivity and Cognitive Impairment in Children with Perinatal Stroke." Neural Plasticity 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/2306406.
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Perinatal stroke is a leading cause of congenital hemiparesis and neurocognitive deficits in children. Dysfunctions in the large-scale resting-state functional networks may underlie cognitive and behavioral disability in these children. We studied resting-state functional connectivity in patients with perinatal stroke collected from the Estonian Pediatric Stroke Database. Neurodevelopment of children was assessed by the Pediatric Stroke Outcome Measurement and the Kaufman Assessment Battery. The study included 36 children (age range 7.6–17.9 years): 10 with periventricular venous infarction (PVI), 7 with arterial ischemic stroke (AIS), and 19 controls. There were no differences in severity of hemiparesis between the PVI and AIS groups. A significant increase in default mode network connectivity (FDR 0.1) and lower cognitive functions (p<0.05) were found in children with AIS compared to the controls and the PVI group. The children with PVI had no significant differences in the resting-state networks compared to the controls and their cognitive functions were normal. Our findings demonstrate impairment in cognitive functions and neural network profile in hemiparetic children with AIS compared to children with PVI and controls. Changes in the resting-state networks found in children with AIS could possibly serve as the underlying derangements of cognitive brain functions in these children.
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Azaryah, Hatim, Juan Verdejo-Román, Cristina Martin-Pérez, José Antonio García-Santos, Cristina Martínez-Zaldívar, Francisco J. Torres-Espínola, Daniel Campos, et al. "Effects of Maternal Fish Oil and/or 5-Methyl-Tetrahydrofolate Supplementation during Pregnancy on Offspring Brain Resting-State at 10 Years Old: A Follow-Up Study from the NUHEAL Randomized Controlled Trial." Nutrients 12, no. 9 (September 4, 2020): 2701. http://dx.doi.org/10.3390/nu12092701.
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Recent studies have shown that maternal supplementation with folate and long-chain polyunsaturated fatty acids (LC-PUFAs) during pregnancy may affect children’s brain development. We aimed at examining the potential long-term effect of maternal supplementation with fish oil (FO) and/or 5-methyl-tetrahydrofolate (5-MTHF) on the brain functionality of offspring at the age of 9.5–10 years. The current study was conducted as a follow-up of the Spanish participants belonging to the Nutraceuticals for a Healthier Life (NUHEAL) project; 57 children were divided into groups according to mother’s supplementation and assessed through functional magnetic resonance imaging (fMRI) scanning and neurodevelopment testing. Independent component analysis and double regression methods were implemented to investigate plausible associations. Children born to mothers supplemented with FO (FO and FO + 5-MTHF groups, n = 33) showed weaker functional connectivity in the default mode (DM) (angular gyrus), the sensorimotor (SM) (motor and somatosensory cortices) and the fronto-parietal (FP) (angular gyrus) networks compared to the No-FO group (placebo and 5-MTHF groups, n = 24) (PFWE < 0.05). Furthermore, no differences were found regarding the neuropsychological tests, except for a trend of better results in an object recall (memory) test. Considering the No-FO group, the aforementioned networks were associated negatively with attention and speed-processing functions. Mother’s FO supplementation during pregnancy seems to be able to shape resting-state network functioning in their children at school age and appears to produce long-term effects on children´s cognitive processing.
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Easson, Amanda K., Zainab Fatima, and Anthony R. McIntosh. "Functional connectivity-based subtypes of individuals with and without autism spectrum disorder." Network Neuroscience 3, no. 2 (January 2019): 344–62. http://dx.doi.org/10.1162/netn_a_00067.
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Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder, characterized by impairments in social communication and restricted, repetitive behaviors. Neuroimaging studies have shown complex patterns and functional connectivity (FC) in ASD, with no clear consensus on brain-behavior relationships or shared patterns of FC with typically developing controls. Here, we used a dimensional approach to characterize two distinct clusters of FC patterns across both ASD participants and controls using k-means clustering. Using multivariate statistical analyses, a categorical approach was taken to characterize differences in FC between subtypes and between diagnostic groups. One subtype was defined by increased FC within resting-state networks and decreased FC across networks compared with the other subtype. A separate FC pattern distinguished ASD from controls, particularly within default mode, cingulo-opercular, sensorimotor, and occipital networks. There was no significant interaction between subtypes and diagnostic groups. Finally, a dimensional analysis of FC patterns with behavioral measures of IQ, social responsiveness, and ASD severity showed unique brain-behavior relations in each subtype and a continuum of brain-behavior relations from ASD to controls within one subtype. These results demonstrate that distinct clusters of FC patterns exist across ASD and controls, and that FC subtypes can reveal unique information about brain-behavior relationships.
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Marshall, Emily, Jason S. Nomi, Bryce Dirks, Celia Romero, Lauren Kupis, Catie Chang, and Lucina Q. Uddin. "Coactivation pattern analysis reveals altered salience network dynamics in children with autism spectrum disorder." Network Neuroscience 4, no. 4 (January 2020): 1219–34. http://dx.doi.org/10.1162/netn_a_00163.
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Brain connectivity studies of autism spectrum disorder (ASD) have historically relied on static measures of functional connectivity. Recent work has focused on identifying transient configurations of brain activity, yet several open questions remain regarding the nature of specific brain network dynamics in ASD. We used a dynamic coactivation pattern (CAP) approach to investigate the salience/midcingulo-insular (M-CIN) network, a locus of dysfunction in ASD, in a large multisite resting-state fMRI dataset collected from 172 children (ages 6–13 years; n = 75 ASD; n = 138 male). Following brain parcellation by using independent component analysis, dynamic CAP analyses were conducted and k-means clustering was used to determine transient activation patterns of the M-CIN. The frequency of occurrence of different dynamic CAP brain states was then compared between children with ASD and typically developing (TD) children. Dynamic brain configurations characterized by coactivation of the M-CIN with central executive/lateral fronto-parietal and default mode/medial fronto-parietal networks appeared less frequently in children with ASD compared with TD children. This study highlights the utility of time-varying approaches for studying altered M-CIN function in prevalent neurodevelopmental disorders. We speculate that altered M-CIN dynamics in ASD may underlie the inflexible behaviors commonly observed in children with the disorder.
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Jung, Minyoung, Yiheng Tu, Joel Park, Kristen Jorgenson, Courtney Lang, Wenwen Song, and Jian Kong. "Surface-based shared and distinct resting functional connectivity in attention-deficit hyperactivity disorder and autism spectrum disorder." British Journal of Psychiatry 214, no. 06 (November 28, 2018): 339–44. http://dx.doi.org/10.1192/bjp.2018.248.
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BackgroundBoth attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental disorders with a high prevalence. They are often comorbid and both exhibit abnormalities in sustained attention, yet common and distinct neural patterns of ASD and ADHD remain unidentified.AimsTo investigate shared and distinct functional connectivity patterns in a relatively large sample of boys (7- to 15-year-olds) with ADHD, ASD and typical development matched by age, gender and IQ.MethodWe applied machine learning techniques to investigate patterns of surface-based brain resting-state connectivity in 86 boys with ASD, 83 boys with ADHD and 125 boys with typical development.ResultsWe observed increased functional connectivity within the limbic and somatomotor networks in boys with ASD compared with boys with typical development. We also observed increased functional connectivity within the limbic, visual, default mode, somatomotor, dorsal attention, frontoparietal and ventral attention networks in boys with ADHD compared with boys with ASD. In addition, using a machine learning approach, we were able to discriminate typical development from ASD, typical development from ADHD and ASD from ADHD with accuracy rates of 76.3%, 84.1%, and 79.3%, respectively.ConclusionsOur results may shed new light on the underlying mechanisms of ASD and ADHD and facilitate the development of new diagnostic methods for these disorders.Declaration of interestJ.K. holds equity in a startup company, MNT.
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Eggebrecht, Adam T., Jed T. Elison, Eric Feczko, Alexandre Todorov, Jason J. Wolff, Sridhar Kandala, Chloe M. Adams, et al. "Joint Attention and Brain Functional Connectivity in Infants and Toddlers." Cerebral Cortex 27, no. 3 (January 7, 2017): 1709–20. http://dx.doi.org/10.1093/cercor/bhw403.
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Abstract Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development.
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Supekar, K., S. Ryali, R. Yuan, D. Kumar, C. De Los Angeles, and V. Menon. "Identification of robust and interpretable brain signatures of autism and clinical symptom severity using a dynamic time-series deep neural network." European Psychiatry 64, S1 (April 2021): S145. http://dx.doi.org/10.1192/j.eurpsy.2021.397.
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IntroductionAutism spectrum disorder (ASD) is among the most common and pervasive neurodevelopmental disorders. Yet, despite decades of research, the neurobiology of ASD is still poorly understood, as inconsistent findings preclude the identification of robust and interpretable neurobiological markers and predictors of clinical symptoms.ObjectivesIdentify robust and interpretable dynamic brain markers that distinguish children with ASD from typically-developing (TD) children and predict clinical symptom severity.MethodsWe leverage multiple functional brain imaging cohorts (ABIDE, Stanford; N = 1004) and exciting recent advances in explainable artificial intelligence (xAI), to develop a novel multivariate time series deep neural network model that extracts informative brain dynamics features that accurately distinguish between ASD and TD children, and predict clinical symptom severity.ResultsOur model achieved consistently high classification accuracies in cross-validation analysis of data from the ABIDE cohort. Crucially, despite the differences in symptom profiles, age, and data acquisition protocols, our model also accurately classified data from an independent Stanford cohort without additional training. xAI analyses revealed that brain features associated with the default mode network, and the human voice/face processing and communication systems, most clearly distinguished ASD from TD children in both cohorts. Furthermore, the posterior cingulate cortex emerged as robust predictor of the severity of social and communication deficits in ASD in both cohorts.ConclusionsOur findings, replicated across two independent cohorts, reveal robust and neurobiologically interpretable brain features that detect ASD and predict core phenotypic features of ASD, and have the potential to transform our understanding of the etiology and treatment of the disorder.DisclosureNo significant relationships.
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Nakayama, Takahiro, Toshiyuki Fukutomi, Yasuo Terao, and Kimio Akagawa. "Syntaxin 1A Gene Is Negatively Regulated in a Cell/Tissue Specific Manner by YY1 Transcription Factor, Which Binds to the −183 to −137 Promoter Region Together with Gene Silencing Factors Including Histone Deacetylase." Biomolecules 11, no. 2 (January 23, 2021): 146. http://dx.doi.org/10.3390/biom11020146.
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The HPC-1/syntaxin 1A (Stx1a) gene, which is involved in synaptic transmission and neurodevelopmental disorders, is a TATA-less gene with several transcription start sites. It is activated by the binding of Sp1 and acetylated histone H3 to the −204 to +2 core promoter region (CPR) in neuronal cell/tissue. Furthermore, it is depressed by the association of class 1 histone deacetylases (HDACs) to Stx1a–CPR in non-neuronal cell/tissue. To further clarify the factors characterizing Stx1a gene silencing in non-neuronal cell/tissue not expressing Stx1a, we attempted to identify the promoter region forming DNA–protein complex only in non-neuronal cells. Electrophoresis mobility shift assays (EMSA) demonstrated that the −183 to −137 OL2 promoter region forms DNA–protein complex only in non-neuronal fetal rat skin keratinocyte (FRSK) cells which do not express Stx1a. Furthermore, the Yin-Yang 1 (YY1) transcription factor binds to the −183 to −137 promoter region of Stx1a in FRSK cells, as shown by competitive EMSA and supershift assay. Chromatin immunoprecipitation assay revealed that YY1 in vivo associates to Stx1a–CPR in cell/tissue not expressing Stx1a and that trichostatin A treatment in FRSK cells decreases the high-level association of YY1 to Stx1a-CPR in default. Reporter assay indicated that YY1 negatively regulates Stx1a transcription. Finally, mass spectrometry analysis showed that gene silencing factors, including HDAC1, associate onto the −183 to −137 promoter region together with YY1. The current study is the first to report that Stx1a transcription is negatively regulated in a cell/tissue-specific manner by YY1 transcription factor, which binds to the −183 to −137 promoter region together with gene silencing factors, including HDAC.
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Qiao, Chen, Bin Gao, Lu-Jia Lu, Vince D. Calhoun, and Yu-Ping Wang. "Two-Step Feature Selection for Identifying Developmental Differences in Resting fMRI Intrinsic Connectivity Networks." Applied Sciences 9, no. 20 (October 12, 2019): 4298. http://dx.doi.org/10.3390/app9204298.
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Functional connectivity derived from functional magnetic resonance imaging (fMRI) is used as an effective way to assess brain architecture. There has been a growing interest in its application to the study of intrinsic connectivity networks (ICNs) during different brain development stages. fMRI data are of high dimension but small sample size, and it is crucial to perform dimension reduction before pattern analysis of ICNs. Feature selection is thus used to reduce redundancy, lower the complexity of learning, and enhance the interpretability. To study the varying patterns of ICNs in different brain development stages, we propose a two-step feature selection method. First, an improved support vector machine based recursive feature elimination method is utilized to study the differences of connectivity during development. To further reduce the highly correlated features, a combination of F-score and correlation score is applied. This method was then applied to analysis of the Philadelphia Neurodevelopmental Cohort (PNC) data. The two-step feature selection was randomly performed 20 times, and those features that showed up consistently in the experiments were chosen as the essential ICN differences between different brain ages. Our results indicate that ICN differences exist in brain development, and they are related to task control, cognition, information processing, attention, and other brain functions. In particular, compared with children, young adults exhibit increasing functional connectivity in the sensory/somatomotor network, cingulo-opercular task control network, visual network, and some other subnetworks. In addition, the connectivity in young adults decreases between the default mode network and other subnetworks such as the fronto-parietal task control network. The results are coincident with the fact that the connectivity within the brain alters from segregation to integration as an individual grows.
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Wang, Emily, and Rose Mary Xavier. "M24. NETWORK STRUCTURE OF PSYCHOPATHOLOGY SYMPTOMS IN A COMMUNITY SAMPLE OF YOUTH." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S142—S143. http://dx.doi.org/10.1093/schbul/sbaa030.336.
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Abstract Background The field of network psychometrics has developed into a promising alternative to the common cause theory and depicts mental health disorders as arising from the interactions between individual symptoms. Currently, major depressive disorder and post-traumatic stress disorder have been the two main disorders studied using network models. In this study, we aimed to examine the network structure of psychopathology symptoms in a community youth sample to detect the most influential symptoms. We also identify influential bridge symptoms which may lead to comorbidities. Methods The sample (n = 2875) was taken from the Philadelphia Neurodevelopmental Cohort and comprised of youth between the ages of 11–21. 112 variables corresponding to 17 psychopathology symptom groups were used to build the network model. We estimated the network structure using a mixed graphical model. Edges were estimated using a pairwise weighted adjacency matrix with EBIC regularization at a default gamma level of 0.25. The relative influence of each node was determined using predictability and centrality measurements including node strength, closeness, and betweenness. A network was similarly created to detect the most influential bridge symptoms using community clusters. Results The network generated from 17 psychopathology symptom domains (comprising ADD, agoraphobia, conduct disorder, depression, generalized anxiety disorder, mania, OCD, ODD, panic disorder, phobia, psychosis, PTSD, general probes, separation anxiety, psychosis prodromal symptoms, social anxiety and suicide) had several distinct cluster regions and two independent psychosis prodromal symptom nodes. No negative associations were observed in the network. The strongest edge regression coefficient (1.593) was detected between a general screening probe asking whether the subject had received previous treatment and a psychosis variable related to hallucination. An OCD item eliciting subject’s fear over accidentally doing something bad had the greatest average centrality measurement (2.317) followed closely by a conduct disorder item eliciting if the subject had ever threatened someone (2.254). Two depression items - irritability (2.228) and depressive mood (1.825) had the largest average bridge centrality values. History of inpatient treatment (0.997), fear of traveling in a car (0.989) and compulsive checking (0.989) had the largest predictability values, suggesting they could potentially be effective intervention targets. Discussion OCD and conduct disorder symptoms had the largest centrality values and are influential symptoms that could potentially be used to more effectively screen youth for mental health disorders. Depression symptoms had the largest bridge centrality values and should be targeted to prevent comorbidity of associated symptoms. Understanding psychopathology symptom networks could potentially lead to greater insights for prevention and individualizing treatments.
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Ilzarbe, Daniel, Inmaculada Baeza, Elena De la Serna, Mireia Rosa, Olga Puig-Navarro, Mireia Masias, Jose Pariente, et al. "T138. ADOLESCENT ONSET OF PSYCHOSIS IMPACTS SEGREGATION OF CORTICO-SUBCORTICAL NETWORKS DURING DEVELOPMENT." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S283. http://dx.doi.org/10.1093/schbul/sbaa029.698.
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Abstract Background Functional connectivity (FC) during the resting-state is reduced in schizophrenia, especially within the Default Mode Network (DMN) (Dong 2018), and between the hippocampus, striatum and ventral tegmental area (VTA), which together conform a Midbrain Network (Gangadin 2019). Cross-sectional studies in adult samples have reported altered FC between dopamine synthesizing centers in midbrain and cortical areas in schizophrenia (Martino 2018). Conceptualizing schizophrenia as a neurodevelopmental disorder, we hypothesize that these changes may take place in early ages, prior to the clinical onset of psychosis. Therefore, we aim to examine FC of the DMN and Midbrain networks longitudinally in adolescents at increased risk of developing psychosis compared with youth with early onset psychosis and healthy volunteers (HV). Methods This longitudinal case-control study encompassed adolescents (12.6–18.9 years old) with psychosis risk syndrome (PRS; n=47), first episode of psychosis (FEP; n=59), and age and sex-matched HV (n=34). Fourteen out of the 30 PRS with follow-up assessment developed psychosis (t-PRS). Resting-state fMRI data was available for 88 subjects at baseline and follow-up [no significant differences in relation to drop-outs]: 10 t-PRS re-scanned at 3–12 months (at transition), and 14 PRS who did not transited (nt-PRS), 35 FEP; and 29 HV re-scanned at 10–36 month follow-up. After exclusion due to poor acquisition or excess movement, the final sample encompassed: 27 FEP, 9 t-PRS, 12 nt-PRS and 28 HV. Individual time series were extracted from Regions of Interest (ROI): for the DMN, the medial Prefrontal Cortex (mPFC), precuneus (PC), and bilateral temporo-parietal junction (Schilbach 2016); and for the Midbrain Network, the associative and limbic striatum, VTA and subiculum (Gangadin 2019). The orthogonal parameters of movement, white matter and cerebrospinal fluid (and their derivatives) and head motion scrubbing regressors were regressed out before performing the correlations. Multivariate mixed-effect models were estimated, including group (4), time and group by time interaction as fixed effects; and time and individual variability as random effects. Results There were no significant differences within-network FC. There was a significant group by time interaction in FC between the two networks (p = .02), driven by VTA-PC (pFDR = .02) and VTA-mPFC (pFDR = .04). Post-hoc analyses showed a significant reduction in FC in nt-PRS over time (psFDR ≤ .03), with FEP and t-PRS showing an opposite pattern (psFDR ≤ .01) in both networks. There was a trend-level reduction in FC over time in HV (ps ≤ .09), which showed significant differences relative to FEP (ps ≤ .04) in the VTA-PC and VTA-mPFC, and with t-PRS in the VTA-PC (p = .02). There was no significant difference between HV and nt-PRS. Cumulative dose of antipsychotics was negatively correlated with FC between mPFC-VTA in FEP at follow-up (r = -.41; p = .04); yet group by time effects survived when used as covariable. Sex, socio-economic status or global intelligence quotient did not exert significant effects. Discussion Our findings suggest that the onset of psychosis during adolescence impacts on the age-normative reduction of FC between the DMN and Midbrain networks, characteristic of the network segregation which takes place during typical brain functional development (Satterthwaite 2013). Antipsychotic medication on cortico-subcortical FC appear to have a reversing effect on these findings, although longitudinal group differences in network connectivity persist despite controlling for this effect. Our data sheds light on the changes in the organization of brain function taking place in the early stages of psychosis, coinciding with a key developmental period.
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Rakesh, Divyangana, Nicholas B. Allen, and Sarah Whittle. "Longitudinal changes in within-salience network functional connectivity mediate the relationship between childhood abuse and neglect, and mental health during adolescence." Psychological Medicine, August 25, 2021, 1–13. http://dx.doi.org/10.1017/s0033291721003135.
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Abstract Background Understanding the neurobiological underpinnings of childhood maltreatment is vital given consistent links with poor mental health. Dimensional models of adversity purport that different types of adversity likely have distinct neurobiological consequences. Adolescence is a key developmental period, during which deviations from normative neurodevelopment may have particular relevance for mental health. However, longitudinal work examining links between different forms of maltreatment, neurodevelopment, and mental health is limited. Methods In the present study, we explored associations between abuse, neglect, and longitudinal development of within-network functional connectivity of the salience (SN), default mode (DMN), and executive control network in 142 community residing adolescents. Resting-state fMRI data were acquired at age 16 (T1; M = 16.46 years, s.d. = 0.52, 66F) and 19 (T2; mean follow-up period: 2.35 years). Mental health data were also collected at T1 and T2. Childhood maltreatment history was assessed prior to T1. Results Abuse and neglect were both found to be associated with increases in within-SN functional connectivity from age 16 to 19. Further, there were sex differences in the association between neglect and changes in within-DMN connectivity. Finally, increases in within-SN connectivity were found to mediate the association between abuse/neglect and lower problematic substance use and higher depressive symptoms at age 19. Conclusions Our findings suggest that childhood maltreatment is associated with altered neurodevelopmental trajectories, and that changes in salience processing may be linked with risk and resilience for the development of depression and substance use problems during adolescence, respectively. Further work is needed to understand the distinct neurodevelopmental and mental health outcomes of abuse and neglect.
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Guassi Moreira, João F., Katie A. McLaughlin, and Jennifer A. Silvers. "Characterizing the Network Architecture of Emotion Regulation Neurodevelopment." Cerebral Cortex, May 5, 2021. http://dx.doi.org/10.1093/cercor/bhab074.
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Abstract The ability to regulate emotions is key to goal attainment and well-being. Although much has been discovered about neurodevelopment and the acquisition of emotion regulation, very little of this work has leveraged information encoded in whole-brain networks. Here we employed a network neuroscience framework to parse the neural underpinnings of emotion regulation skill acquisition, while accounting for age, in a sample of children and adolescents (N = 70, 34 female, aged 8–17 years). Focusing on three key network metrics—network differentiation, modularity, and community number differences between active regulation and a passive emotional baseline—we found that the control network, the default mode network, and limbic network were each related to emotion regulation ability while controlling for age. Greater network differentiation in the control and limbic networks was related to better emotion regulation ability. With regards to network community structure (modularity and community number), more communities and more crosstalk between modules (i.e., less modularity) in the control network were associated with better regulatory ability. By contrast, less crosstalk (i.e., greater modularity) between modules in the default mode network was associated with better regulatory ability. Together, these findings highlight whole-brain connectome features that support the acquisition of emotion regulation in youth.
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Duy, Phan Q., Pasko Rakic, Seth L. Alper, Stephanie M. Robert, Adam J. Kundishora, William E. Butler, Christopher A. Walsh, et al. "A neural stem cell paradigm of pediatric hydrocephalus." Cerebral Cortex, September 12, 2022. http://dx.doi.org/10.1093/cercor/bhac341.
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Abstract Pediatric hydrocephalus, the leading reason for brain surgery in children, is characterized by enlargement of the cerebral ventricles classically attributed to cerebrospinal fluid (CSF) overaccumulation. Neurosurgical shunting to reduce CSF volume is the default treatment that intends to reinstate normal CSF homeostasis, yet neurodevelopmental disability often persists in hydrocephalic children despite optimal surgical management. Here, we discuss recent human genetic and animal model studies that are shifting the view of pediatric hydrocephalus from an impaired fluid plumbing model to a new paradigm of dysregulated neural stem cell (NSC) fate. NSCs are neuroprogenitor cells that comprise the germinal neuroepithelium lining the prenatal brain ventricles. We propose that heterogenous defects in the development of these cells converge to disrupt cerebrocortical morphogenesis, leading to abnormal brain–CSF biomechanical interactions that facilitate passive pooling of CSF and secondary ventricular distention. A significant subset of pediatric hydrocephalus may thus in fact be due to a developmental brain malformation leading to secondary enlargement of the ventricles rather than a primary defect of CSF circulation. If hydrocephalus is indeed a neuroradiographic presentation of an inborn brain defect, it suggests the need to focus on optimizing neurodevelopment, rather than CSF diversion, as the primary treatment strategy for these children.
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Jiang, Weixiong, Stephanie L. Merhar, Zhuohao Zeng, Ziliang Zhu, Weiyan Yin, Zhen Zhou, Li Wang, Lili He, Jennifer Vannest, and Weili Lin. "Neural alterations in opioid-exposed infants revealed by edge-centric brain functional networks." Brain Communications, May 5, 2022. http://dx.doi.org/10.1093/braincomms/fcac112.
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Abstract Prenatal opioid exposure has been linked to adverse effects spanning multiple neurodevelopmental domains, including cognition, motor development, attention, and vision. However, the neural basis of these abnormalities is largely unknown. A total of 49 infants, including 21 opioid-exposed and 28 controls, were enrolled and underwent MR imaging (43 ± 6 days old) after birth, including resting state functional MRI. Edge-centric functional networks based on dynamic functional connections were constructed and machine-learning methods were employed to identify neural features distinguishing opioid-exposed infants from unexposed controls. An accuracy of 73.6% (sensitivity 76.25% and specificity 69.33%) was achieved using 10 times ten-fold cross-validation, which substantially outperformed those obtained using conventional static functional connections (accuracy 56.9%). More importantly, we identified that prenatal opioid exposure preferentially affects inter- rather than intra-network dynamic functional connections, particularly with the visual, subcortical and default mode networks. Consistent results at the brain regional and connection levels were also observed, where the brain regions and connections associated with visual and higher order cognitive functions played pivotal roles in distinguishing opioid-exposed infants from controls. Our findings support the clinical phenotype of infants exposed to opioids in utero and may potentially explain the higher rates of visual and emotional problems observed in this population. Finally, our findings suggested that edge-centric networks could better capture the neural differences between opioid-exposed infants and controls by abstracting the intrinsic co-fluctuation along edges, which may provide a promising tool for future studies focusing on investigating the effects of prenatal opioid exposure on neurodevelopment.
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Talishinsky, Aleksandr, Jonathan Downar, Petra E. Vértes, Jakob Seidlitz, Katharine Dunlop, Charles J. Lynch, Heather Whalley, et al. "Regional gene expression signatures are associated with sex-specific functional connectivity changes in depression." Nature Communications 13, no. 1 (September 28, 2022). http://dx.doi.org/10.1038/s41467-022-32617-1.
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AbstractThe neural substrates of depression may differ in men and women, but the underlying mechanisms are incompletely understood. Here, we show that depression is associated with sex-specific patterns of abnormal functional connectivity in the default mode network and in five regions of interest with sexually dimorphic transcriptional effects. Regional differences in gene expression in two independent datasets explained the neuroanatomical distribution of abnormal connectivity. These gene sets varied by sex and were strongly enriched for genes implicated in depression, synapse function, immune signaling, and neurodevelopment. In an independent sample, we confirmed the prediction that individual differences in default mode network connectivity are explained by inferred brain expression levels for six depression-related genes, including PCDH8, a brain-specific protocadherin integral membrane protein implicated in activity-related synaptic reorganization. Together, our results delineate both shared and sex-specific changes in the organization of depression-related functional networks, with implications for biomarker development and fMRI-guided therapeutic neuromodulation.
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Ilomäki, Miro, Jallu Lindblom, Viljami Salmela, Marjo Flykt, Mervi Vänskä, Juha Salmi, Tuija Tolonen, Kimmo Alho, Raija-Leena Punamäki, and Patrik Wikman. "Early life stress is associated with the default mode and fronto-limbic network connectivity among young adults." Frontiers in Behavioral Neuroscience 16 (September 23, 2022). http://dx.doi.org/10.3389/fnbeh.2022.958580.
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Exposure to early life stress (ELS) is associated with a variety of detrimental psychological and neurodevelopmental effects. Importantly, ELS has been associated with regional alterations and aberrant connectivity in the structure and functioning of brain regions involved in emotion processing and self-regulation, creating vulnerability to mental health problems. However, longitudinal research regarding the impact of ELS on functional connectivity between brain regions in the default mode network (DMN) and fronto-limbic network (FLN), both implicated in emotion-related processes, is relatively scarce. Neuroimaging research on ELS has mostly focused on single nodes or bi-nodal connectivity instead of functional networks. We examined how ELS is associated with connectivity patterns within the DMN and FLN during rest in early adulthood. The participants (n = 86; 47 females) in the current functional magnetic resonance imaging (fMRI) study were young adults (18–21 years old) whose families had participated in a longitudinal study since pregnancy. ELS was assessed both prospectively (parental reports of family relationship problems and mental health problems during pregnancy and infancy) and retrospectively (self-reported adverse childhood experiences). Inter-subject representational similarity analysis (IS-RSA) and multivariate distance matrix regression (MDMR) were used to analyze the association between ELS and the chosen networks. The IS-RSA results suggested that prospective ELS was associated with complex alterations within the DMN, and that retrospective ELS was associated with alterations in the FLN. MDMR results, in turn, suggested that that retrospective ELS was associated with DMN connectivity. Mean connectivity of the DMN was also associated with retrospective ELS. Analyses further showed that ELS-related alterations in the FLN were associated with increased connectivity between the prefrontal and limbic regions, and between different prefrontal regions. These results suggest that exposure to ELS in infancy might have long-lasting influences on functional brain connectivity that persist until early adulthood. Our results also speak for the importance of differentiating prospective and retrospective assessment methods to understand the specific neurodevelopmental effects of ELS.
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Kelsey, Caroline M., Katrina Farris, and Tobias Grossmann. "Variability in Infants' Functional Brain Network Connectivity Is Associated With Differences in Affect and Behavior." Frontiers in Psychiatry 12 (June 9, 2021). http://dx.doi.org/10.3389/fpsyt.2021.685754.
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Variability in functional brain network connectivity has been linked to individual differences in cognitive, affective, and behavioral traits in adults. However, little is known about the developmental origins of such brain-behavior correlations. The current study examined functional brain network connectivity and its link to behavioral temperament in typically developing newborn and 1-month-old infants (M [age] = 25 days; N = 75) using functional near-infrared spectroscopy (fNIRS). Specifically, we measured long-range connectivity between cortical regions approximating fronto-parietal, default mode, and homologous-interhemispheric networks. Our results show that connectivity in these functional brain networks varies across infants and maps onto individual differences in behavioral temperament. Specifically, connectivity in the fronto-parietal network was positively associated with regulation and orienting behaviors, whereas connectivity in the default mode network showed the opposite effect on these behaviors. Our analysis also revealed a significant positive association between the homologous-interhemispheric network and infants' negative affect. The current results suggest that variability in long-range intra-hemispheric and cross-hemispheric functional connectivity between frontal, parietal, and temporal cortex is associated with individual differences in affect and behavior. These findings shed new light on the brain origins of individual differences in early-emerging behavioral traits and thus represent a viable novel approach for investigating developmental trajectories in typical and atypical neurodevelopment.
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Chahal, Rajpreet, Jonas G. Miller, Justin P. Yuan, Jessica L. Buthmann, and Ian H. Gotlib. "An exploration of dimensions of early adversity and the development of functional brain network connectivity during adolescence: Implications for trajectories of internalizing symptoms." Development and Psychopathology, January 31, 2022, 1–15. http://dx.doi.org/10.1017/s0954579421001814.
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Abstract Different dimensions of adversity may affect mental health through distinct neurobiological mechanisms, though current supporting evidence consists largely of cross-sectional associations between threat or deprivation and fronto-limbic circuitry. In this exploratory three-wave longitudinal study spanning ages 9–19 years, we examined the associations between experiences of unpredictability, threat, and deprivation with the development of functional connectivity within and between three brain networks implicated in psychopathology: the salience (SAL), default mode (DMN), and fronto-parietal (FPN) networks, and tested whether network trajectories moderated associations between adversity and changes in internalizing symptoms. Connectivity decreased with age on average; these changes differed by dimension of adversity. Whereas family-level deprivation was associated with lower initial levels and more stability across most networks, unpredictability was associated with stability only in SAL connectivity, and threat was associated with stability in FPN and DMN-SAL connectivity. In youth exposed to higher levels of any adversity, lower initial levels and more stability in connectivity were related to smaller increases in internalizing symptoms. Our findings suggest that whereas deprivation is associated with widespread neurodevelopmental differences in cognitive and emotion processing networks, unpredictability is related selectively to salience detection circuitry. Studies with wider developmental windows should examine whether these neurodevelopmental alterations are adaptive or serve to maintain internalizing symptoms.
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Dengsø, Mads J. "Wrong Brains at the Wrong Time? Understanding ADHD Through the Diachronic Constitution of Minds." Advances in Neurodevelopmental Disorders, March 14, 2022. http://dx.doi.org/10.1007/s41252-022-00244-y.
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Abstract Objectives The purpose of this theoretical analysis of current research on ADHD is to provide an account integrating executive functional profiles with its broader structural neurodevelopmental profile. Methods Comparative theoretical analyses between executive functional deficit disorder models of ADHD and results from default mode network fMRI data. This was followed by an analysis of the temporal profile of ADHD and phase synchronous neural assemblies. Results Comparative analyses suggest disparities within executive functional deficit disorder models and discontinuities between executive functional and structural profiles of ADHD. Analysis of the temporal signature of ADHD provides a potential avenue for integrating different profiles by means of anchoring executive functions within inherent diachronic neurocognitive organization. Conclusions The analyses provided suggest that executive functional deficits in ADHD arise from much broader idiosyncrasies, rooted within the inherent diachronic organization of neurocognitive function, and whose challenges must be understood in conjunction with socio cultural environmental factors.
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Choi, Hongyoon, Yoori Choi, Kyu Wan Kim, Hyejin Kang, Do Won Hwang, E. Edmund Kim, June-Key Chung, and Dong Soo Lee. "Maturation of metabolic connectivity of the adolescent rat brain." eLife 4 (November 27, 2015). http://dx.doi.org/10.7554/elife.11571.
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Neuroimaging has been used to examine developmental changes of the brain. While PET studies revealed maturation-related changes, maturation of metabolic connectivity of the brain is not yet understood. Here, we show that rat brain metabolism is reconfigured to achieve long-distance connections with higher energy efficiency during maturation. Metabolism increased in anterior cerebrum and decreased in thalamus and cerebellum during maturation. When functional covariance patterns of PET images were examined, metabolic networks including default mode network (DMN) were extracted. Connectivity increased between the anterior and posterior parts of DMN and sensory-motor cortices during maturation. Energy efficiency, a ratio of connectivity strength to metabolism of a region, increased in medial prefrontal and retrosplenial cortices. Our data revealed that metabolic networks mature to increase metabolic connections and establish its efficiency between large-scale spatial components from childhood to early adulthood. Neurodevelopmental diseases might be understood by abnormal reconfiguration of metabolic connectivity and efficiency.
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Elumalai, Pavithra, Yasharth Yadav, Nitin Williams, Emil Saucan, Jürgen Jost, and Areejit Samal. "Graph Ricci curvatures reveal atypical functional connectivity in autism spectrum disorder." Scientific Reports 12, no. 1 (May 18, 2022). http://dx.doi.org/10.1038/s41598-022-12171-y.
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AbstractWhile standard graph-theoretic measures have been widely used to characterize atypical resting-state functional connectivity in autism spectrum disorder (ASD), geometry-inspired network measures have not been applied. In this study, we apply Forman–Ricci and Ollivier–Ricci curvatures to compare networks of ASD and typically developing individuals (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We find brain-wide and region-specific ASD-related differences for both Forman–Ricci and Ollivier–Ricci curvatures, with region-specific differences concentrated in Default Mode, Somatomotor and Ventral Attention networks for Forman–Ricci curvature. We use meta-analysis decoding to demonstrate that brain regions with curvature differences are associated to those cognitive domains known to be impaired in ASD. Further, we show that brain regions with curvature differences overlap with those brain regions whose non-invasive stimulation improves ASD-related symptoms. These results suggest the utility of graph Ricci curvatures in characterizing atypical connectivity of clinically relevant regions in ASD and other neurodevelopmental disorders.
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Dorfschmidt, Lena, Richard A. Bethlehem, Jakob Seidlitz, František Váša, Simon R. White, Rafael Romero-García, Manfred G. Kitzbichler, et al. "Sexually divergent development of depression-related brain networks during healthy human adolescence." Science Advances 8, no. 21 (May 27, 2022). http://dx.doi.org/10.1126/sciadv.abm7825.
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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.
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Jin, Zhishuai, Sizhu Huyang, Lichen Jiang, Yajun Yan, Ming Xu, Jinyu Wang, Qixiong Li, and Daxing Wu. "Increased Resting-State Interhemispheric Functional Connectivity of Posterior Superior Temporal Gyrus and Posterior Cingulate Cortex in Congenital Amusia." Frontiers in Neuroscience 15 (April 30, 2021). http://dx.doi.org/10.3389/fnins.2021.653325.
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Interhemispheric connectivity of the two cerebral hemispheres is crucial for a broad repertoire of cognitive functions including music and language. Congenital amusia has been reported as a neurodevelopment disorder characterized by impaired music perception and production. However, little is known about the characteristics of the interhemispheric functional connectivity (FC) in amusia. In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to investigate the interhemispheric FC of the whole brain in amusia at resting-state. Thirty amusics and 29 matched participants underwent a resting-state functional magnetic resonance imaging (fMRI) scanning. An automated VMHC approach was used to analyze the fMRI data. Compared to the control group, amusics showed increased VMHC within the posterior part of the default mode network (DMN) mainly in the posterior superior temporal gyrus (pSTG) and posterior cingulate cortex (PCC). Correlation analyses revealed negative correlations between the VMHC value in pSTG/PCC and the music perception ability among amusics. Further ROC analyses showed that the VMHC value of pSTG/PCC showed a good sensibility/specificity to differentiate the amusics from the controls. These findings provide a new perspective for understanding the neural basis of congenital amusia and imply the immature state of DMN may be a credible neural marker of amusia.
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Shanmugan, Sheila, Jakob Seidlitz, Zaixu Cui, Azeez Adebimpe, Danielle S. Bassett, Maxwell A. Bertolero, Christos Davatzikos, et al. "Sex differences in the functional topography of association networks in youth." Proceedings of the National Academy of Sciences 119, no. 33 (August 8, 2022). http://dx.doi.org/10.1073/pnas.2110416119.
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Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy ( P < 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent results. Furthermore, transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography were spatially correlated with the expression of genes on the X chromosome. These results highlight the role of sex as a biological variable in shaping functional topography.
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Uribe, Carme, Carme Junque, Esther Gómez-Gil, María Díez-Cirarda, and Antonio Guillamon. "Brain connectivity dynamics in cisgender and transmen people with gender incongruence before gender affirmative hormone treatment." Scientific Reports 11, no. 1 (October 26, 2021). http://dx.doi.org/10.1038/s41598-021-00508-y.
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AbstractLarge-scale brain network interactions have been described between trans- and cis-gender binary identities. However, a temporal perspective of the brain's spontaneous fluctuations is missing. We investigated the functional connectivity dynamics in transmen with gender incongruence and its relationship with interoceptive awareness. We describe four states in native and meta-state spaces: (i) one state highly prevalent with sparse overall connections; (ii) a second with strong couplings mainly involving components of the salience, default, and executive control networks. Two states with global sparse connectivity but positive couplings (iii) within the sensorimotor network, and (iv) between salience network regions. Transmen had more dynamical fluidity than cismen, while cismen presented less meta-state fluidity and range dynamism than transmen and ciswomen. A positive association between attention regulation and fluidity and meta-state range dynamism was found in transmen. There exist gender differences in the temporal brain dynamism, characterized by distinct interrelations of the salience network as catalyst interacting with other networks. We offer a functional explanation from the neurodevelopmental cortical hypothesis of a gendered-self.
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Pode-Shakked, Ben, Ortal Barel, Amihood Singer, Miriam Regev, Hana Poran, Aviva Eliyahu, Yael Finezilber, et al. "A single center experience with publicly funded clinical exome sequencing for neurodevelopmental disorders or multiple congenital anomalies." Scientific Reports 11, no. 1 (September 27, 2021). http://dx.doi.org/10.1038/s41598-021-98646-w.
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AbstractExome sequencing (ES) is an important diagnostic tool for individuals with neurodevelopmental disorders (NDD) and/or multiple congenital anomalies (MCA). However, the cost of ES limits the test's accessibility for many patients. We evaluated the yield of publicly funded clinical ES, performed at a tertiary center in Israel, over a 3-year period (2018–2020). Probands presented with (1) moderate-to-profound global developmental delay (GDD)/intellectual disability (ID); or (2) mild GDD/ID with epilepsy or congenital anomaly; and/or (3) MCA. Subjects with normal chromosomal microarray analysis who met inclusion criteria were included, totaling 280 consecutive cases. Trio ES (proband and parents) was the default option. In 252 cases (90.0%), indication of NDD was noted. Most probands were males (62.9%), and their mean age at ES submission was 9.3 years (range 1 month to 51 years). Molecular diagnosis was reached in 109 probands (38.9%), mainly due to de novo variants (91/109, 83.5%). Disease-causing variants were identified in 92 genes, 15 of which were implicated in more than a single case. Male sex, families with multiple-affected members and premature birth were significantly associated with lower ES yield (p < 0.05). Other factors, including MCA and coexistence of epilepsy, autism spectrum disorder, microcephaly or abnormal brain magnetic resonance imaging findings, were not associated with the yield. To conclude, our findings support the utility of clinical ES in a real-world setting, as part of a publicly funded genetic workup for individuals with GDD/ID and/or MCA.
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Eryilmaz, Hamdi, Melissa Pax, Alexandra G. O’Neill, Mark Vangel, Ibai Diez, Daphne J. Holt, Joan A. Camprodon, Jorge Sepulcre, and Joshua L. Roffman. "Network hub centrality and working memory performance in schizophrenia." Schizophrenia 8, no. 1 (September 23, 2022). http://dx.doi.org/10.1038/s41537-022-00288-y.
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AbstractCognitive impairment, and working memory deficits in particular, are debilitating, treatment-resistant aspects of schizophrenia. Dysfunction of brain network hubs, putatively related to altered neurodevelopment, is thought to underlie the cognitive symptoms associated with this illness. Here, we used weighted degree, a robust graph theory metric representing the number of weighted connections to a node, to quantify centrality in cortical hubs in 29 patients with schizophrenia and 29 age- and gender-matched healthy controls and identify the critical nodes that underlie working memory performance. In both patients and controls, elevated weighted degree in the default mode network (DMN) was generally associated with poorer performance (accuracy and reaction time). Higher degree in the ventral attention network (VAN) nodes in the right superior temporal cortex was associated with better performance (accuracy) in patients. Degree in several prefrontal and parietal areas was associated with cognitive performance only in patients. In regions that are critical for sustained attention, these correlations were primarily driven by between-network connectivity in patients. Moreover, a cross-validated prediction analysis showed that a linear model using a summary degree score can be used to predict an individual’s working memory accuracy (r = 0.35). Our results suggest that schizophrenia is associated with dysfunctional hubs in the cortical systems supporting internal and external cognition and highlight the importance of topological network analysis in the search of biomarkers for cognitive deficits in schizophrenia.
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Feng, Yu, Xiaodong Kang, Hesong Wang, Jing Cong, Wenwen Zhuang, Kaiqing Xue, Fali Li, Dezhong Yao, Peng Xu, and Tao Zhang. "The relationships between dynamic resting-state networks and social behavior in autism spectrum disorder revealed by fuzzy entropy–based temporal variability analysis of large-scale network." Cerebral Cortex, March 17, 2022. http://dx.doi.org/10.1093/cercor/bhac100.
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Abstract Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by a core deficit in social processes. However, it is still unclear whether the core clinical symptoms of the disorder can be reflected by the temporal variability of resting-state network functional connectivity (FC). In this article, we examined the large-scale network FC temporal variability at the local region, within-network, and between-network levels using the fuzzy entropy technique. Then, we correlated the network FC temporal variability to social-related scores. We found that the social behavior correlated with the FC temporal variability of the precuneus, parietal, occipital, temporal, and precentral. Our results also showed that social behavior was significantly negatively correlated with the temporal variability of FC within the default mode network, between the frontoparietal network and cingulo-opercular task control network, and the dorsal attention network. In contrast, social behavior correlated significantly positively with the temporal variability of FC within the subcortical network. Finally, using temporal variability as a feature, we construct a model to predict the social score of ASD. These findings suggest that the network FC temporal variability has a close relationship with social behavioral inflexibility in ASD and may serve as a potential biomarker for predicting ASD symptom severity.
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Wang, Zhengning, Yuhang Xu, Dawei Peng, Jingjing Gao, and Fengmei Lu. "Brain functional activity-based classification of autism spectrum disorder using an attention-based graph neural network combined with gene expression." Cerebral Cortex, December 30, 2022. http://dx.doi.org/10.1093/cercor/bhac513.
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Abstract Autism spectrum disorder (ASD) is a complex brain neurodevelopmental disorder related to brain activity and genetics. Most of the ASD diagnostic models perform feature selection at the group level without considering individualized information. Evidence has shown the unique topology of the individual brain has a fundamental impact on brain diseases. Thus, a data-constructing method fusing individual topological information and a corresponding classification model is crucial in ASD diagnosis and biomarker discovery. In this work, we trained an attention-based graph neural network (GNN) to perform the ASD diagnosis with the fusion of graph data. The results achieved an accuracy of 79.78%. Moreover, we found the model paid high attention to brain regions mainly involved in the social-brain circuit, default-mode network, and sensory perception network. Furthermore, by analyzing the covariation between functional magnetic resonance imaging data and gene expression, current studies detected several ASD-related genes (i.e. MUTYH, AADAT, and MAP2), and further revealed their links to image biomarkers. Our work demonstrated that the ASD diagnostic framework based on graph data and attention-based GNN could be an effective tool for ASD diagnosis. The identified functional features with high attention values may serve as imaging biomarkers for ASD.
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Lin, Pingting, Shiyi Zang, Yi Bai, and Haixian Wang. "Reconfiguration of Brain Network Dynamics in Autism Spectrum Disorder Based on Hidden Markov Model." Frontiers in Human Neuroscience 16 (February 8, 2022). http://dx.doi.org/10.3389/fnhum.2022.774921.
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Autism spectrum disorder (ASD) is a group of complex neurodevelopment disorders characterized by altered brain connectivity. However, the majority of neuroimaging studies for ASD focus on the static pattern of brain function and largely neglect brain activity dynamics, which might provide deeper insight into the underlying mechanism of brain functions for ASD. Therefore, we proposed a framework with Hidden Markov Model (HMM) analysis for resting-state functional MRI (fMRI) from a large multicenter dataset of 507 male subjects. Specifically, the 507 subjects included 209 subjects with ASD and 298 well-matched health controls across 14 sites from the Autism Brain Imaging Data Exchange (ABIDE). Based on the HMM, we can identify the recurring brain function networks over time across ASD and healthy controls (HCs). Then we assessed the dynamical configuration of the whole-brain networks and further analyzed the community structure of transitions across the brain states. Based on the 19 HMM states, we found that the global temporal statistics of the specific HMM states (including fractional occupancies and lifetimes) were significantly altered in ASD compared to HCs. These specific HMM states were characterized by the activation pattern of default mode network (DMN), sensory processing networks [including visual network, auditory network, and sensory and motor network (SMN)]. Meanwhile, we also find that the specific modules of transitions between states were closely related to ASD. Our findings indicate the temporal reconfiguration of the brain network in ASD and provide novel insights into the dynamics of the whole-brain networks for ASD.
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Peng, Liling, Xiao Liu, Di Ma, Xiaofeng Chen, Xiaowen Xu, and Xin Gao. "The Altered Pattern of the Functional Connectome Related to Pathological Biomarkers in Individuals for Autism Spectrum Disorder Identification." Frontiers in Neuroscience 16 (May 6, 2022). http://dx.doi.org/10.3389/fnins.2022.913377.
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ObjectiveAutism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by the development of multiple symptoms, with incidences rapidly increasing worldwide. An important step in the early diagnosis of ASD is to identify informative biomarkers. Currently, the use of functional brain network (FBN) is deemed important for extracting data on brain imaging biomarkers. Unfortunately, most existing studies have reported the utilization of the information from the connection to train the classifier; such an approach ignores the topological information and, in turn, limits its performance. Thus, effective utilization of the FBN provides insights for improving the diagnostic performance.MethodsWe propose the combination of the information derived from both FBN and its corresponding graph theory measurements to identify and distinguish ASD from normal controls (NCs). Specifically, a multi-kernel support vector machine (MK-SVM) was used to combine multiple types of information.ResultsThe experimental results illustrate that the combination of information from multiple connectome features (i.e., functional connections and graph measurements) can provide a superior identification performance with an area under the receiver operating characteristic curve (ROC) of 0.9191 and an accuracy of 82.60%. Furthermore, the graph theoretical analysis illustrates that the significant nodal graph measurements and consensus connections exists mostly in the salience network (SN), default mode network (DMN), attention network, frontoparietal network, and social network.ConclusionThis work provides insights into potential neuroimaging biomarkers that may be used for the diagnosis of ASD and offers a new perspective for the exploration of the brain pathophysiology of ASD through machine learning.
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Tang, Biqiu, Wenjing Zhang, Shikuang Deng, Jiang Liu, Na Hu, Qiyong Gong, Shi Gu, and Su Lui. "Age-associated network controllability changes in first episode drug-naïve schizophrenia." BMC Psychiatry 22, no. 1 (January 10, 2022). http://dx.doi.org/10.1186/s12888-021-03674-5.
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Abstract Background Recent neuroimaging studies revealed dysregulated neurodevelopmental, or/and neurodegenerative trajectories of both structural and functional connections in schizophrenia. However, how the alterations in the brain’s structural connectivity lead to dynamic function changes in schizophrenia with age remains poorly understood. Methods Combining structural magnetic resonance imaging and a network control theory approach, the white matter network controllability metric (average controllability) was mapped from age 16 to 60 years in 175 drug-naïve schizophrenia patients and 155 matched healthy controls. Results Compared with controls, the schizophrenia patients demonstrated the lack of age-related decrease on average controllability of default mode network (DMN), as well as the right precuneus (a hub region of DMN), suggesting abnormal maturational development process in schizophrenia. Interestingly, the schizophrenia patients demonstrated an accelerated age-related decline of average controllability in the subcortical network, supporting the neurodegenerative model. In addition, compared with controls, the lack of age-related increase on average controllability of the left inferior parietal gyrus in schizophrenia patients also suggested a different pathway of brain development. Conclusions By applying the control theory approach, the present study revealed age-related changes in the ability of white matter pathways to control functional activity states in schizophrenia. The findings supported both the developmental and degenerative hypotheses of schizophrenia, and suggested a particularly high vulnerability of the DMN and subcortical network possibly reflecting an illness-related early marker for the disorder.
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van Oort, Jasper, Indira Tendolkar, Rose Collard, Dirk E. M. Geurts, Janna N. Vrijsen, Fleur A. Duyser, Nils Kohn, Guillén Fernández, Aart H. Schene, and Philip F. P. van Eijndhoven. "Neural correlates of repetitive negative thinking: Dimensional evidence across the psychopathological continuum." Frontiers in Psychiatry 13 (July 22, 2022). http://dx.doi.org/10.3389/fpsyt.2022.915316.
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Repetitive negative thinking (RNT) captures an important transdiagnostic factor that predisposes to a maladaptive stress response and contributes to diverse psychiatric disorders. Although RNT can best be seen as a continuous symptom dimension that cuts across boundaries from health to various psychiatric disorders, the neural mechanisms underlying RNT have almost exclusively been studied in health and stress-related disorders, such as depression and anxiety disorders. We set out to study RNT from a large-scale brain network perspective in a diverse population consisting of healthy subjects and patients with a broader range of psychiatric disorders. We studied 46 healthy subjects along with 153 patients with a stress-related and/or neurodevelopmental disorder. We focused on three networks, that are associated with RNT and diverse psychiatric disorders: the salience network, default mode network (DMN) and frontoparietal network (FPN). We investigated the relationship of RNT with both network connectivity strength at rest and with the stress-induced changes in connectivity. Across our whole sample, the level of RNT was positively associated with the connectivity strength of the left FPN at rest, but negatively associated with stress-induced changes in DMN connectivity. These findings may reflect an upregulation of the FPN in an attempt to divert attention away from RNT, while the DMN result may reflect a less flexible adaptation to stress, related to RNT. Additionally, we discuss how our findings fit into the non-invasive neurostimulation literature. Taken together, our results provide initial insight in the neural mechanisms of RNT across the spectrum from health to diverse psychiatric disorders.
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Holz, Nathalie E., Dorothea L. Floris, Alberto Llera, Pascal M. Aggensteiner, Seyed Mostafa Kia, Thomas Wolfers, Sarah Baumeister, et al. "Age-related brain deviations and aggression." Psychological Medicine, April 22, 2022, 1–10. http://dx.doi.org/10.1017/s003329172200068x.
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Abstract Background Disruptive behavior disorders (DBD) are heterogeneous at the clinical and the biological level. Therefore, the aims were to dissect the heterogeneous neurodevelopmental deviations of the affective brain circuitry and provide an integration of these differences across modalities. Methods We combined two novel approaches. First, normative modeling to map deviations from the typical age-related pattern at the level of the individual of (i) activity during emotion matching and (ii) of anatomical images derived from DBD cases (n = 77) and controls (n = 52) aged 8–18 years from the EU-funded Aggressotype and MATRICS consortia. Second, linked independent component analysis to integrate subject-specific deviations from both modalities. Results While cases exhibited on average a higher activity than would be expected for their age during face processing in regions such as the amygdala when compared to controls these positive deviations were widespread at the individual level. A multimodal integration of all functional and anatomical deviations explained 23% of the variance in the clinical DBD phenotype. Most notably, the top marker, encompassing the default mode network (DMN) and subcortical regions such as the amygdala and the striatum, was related to aggression across the whole sample. Conclusions Overall increased age-related deviations in the amygdala in DBD suggest a maturational delay, which has to be further validated in future studies. Further, the integration of individual deviation patterns from multiple imaging modalities allowed to dissect some of the heterogeneity of DBD and identified the DMN, the striatum and the amygdala as neural signatures that were associated with aggression.
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Miklowitz, David J., Marc J. Weintraub, Patricia D. Walshaw, Christopher D. Schneck, Kiki D. Chang, John Merranko, Amy S. Garrett, and Manpreet K. Singh. "Early Family Intervention for Youth at Risk for Bipolar Disorder: Psychosocial and Neural Mediators of Outcome." Current Neuropharmacology 21 (January 11, 2023). http://dx.doi.org/10.2174/1570159x21666230111120817.
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Background: The impairing neurodevelopmental course of bipolar disorder (BD) suggests the importance of early intervention for youth in the beginning phases of the illness. Objective: We report the results of a 3-site randomized trial of family-focused therapy for youth at high-risk (FFT-HR) for BD, and explore psychosocial and neuroimaging variables as mediators of treatment effects. Methods: High-risk youth (<18 years) with major depressive disorder or other specified BD, active mood symptoms, and a family history of BD were randomly assigned to 4 months of FFT- HR (psychoeducation, communication and problem-solving skills training) or 4 months of enhanced care psychoeducation. Adjunctive pharmacotherapy was provided by study psychiatrists. Neuroimaging scans were conducted before and after psychosocial treatments in eligible participants. Independent evaluators interviewed participants every 4-6 months over 1-4 years regarding symptomatic outcomes. Results: Among 127 youth (mean 13.2+2.6 years) over a median of 98 weeks, FFT-HR was associated with longer intervals prior to new mood episodes and lower levels of suicidal ideation than enhanced care. Reductions in perceived family conflict mediated the effects of psychosocial interventions on the course of mood symptoms. Among 34 participants with pre- /post-treatment fMRI scans, youth in FFT-HR had (a) stronger resting state connectivity between ventrolateral PFC and anterior default mode network, and (b) increased activity of dorsolateral and medial PFC in emotion processing and problem-solving tasks, compared to youth in enhanced care. Conclusion: FFT-HR may delay new mood episodes in symptomatic youth with familial liability to BD. Putative treatment mechanisms include neural adaptations suggestive of improved emotion regulation.
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Looden, Tristan, Dorothea L. Floris, Alberto Llera, Roselyne J. Chauvin, Tony Charman, Tobias Banaschewski, Declan Murphy, et al. "Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project." Molecular Autism 13, no. 1 (December 27, 2022). http://dx.doi.org/10.1186/s13229-022-00529-y.
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Abstract Background Autism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioral, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterize heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks. Methods All analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism (n = 282) and typically developing (TD) controls (n = 221) between 6 and 30 years of age. We employed a novel task potency approach which combines the unique aspects of both resting state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioral data. Results Deviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p < 0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p < 0.002). The CCA identified significant and robust brain-behavior covariation between functional connectivity atypicality and autism-related behavioral features. Conclusions Individuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show how sophisticated modeling methods such as task potency and normative modeling can be used toward unravelling complex heterogeneous conditions like autism.
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Moradimanesh, Z., R. Khosrowabadi, M. Eshaghi Gordji, and G. R. Jafari. "Altered structural balance of resting-state networks in autism." Scientific Reports 11, no. 1 (January 21, 2021). http://dx.doi.org/10.1038/s41598-020-80330-0.
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AbstractWhat makes a network complex, in addition to its size, is the interconnected interactions between elements, disruption of which inevitably results in dysfunction. Likewise, the brain networks’ complexity arises from interactions beyond pair connections, as it is simplistic to assume that in complex networks state of a link is independently determined only according to its two constituting nodes. This is particularly of note in genetically complex brain impairments, such as the autism spectrum disorder (ASD), which has a surprising heterogeneity in manifestations with no clear-cut neuropathology. Accordingly, structural balance theory (SBT) affirms that in real-world signed networks, a link is remarkably influenced by each of its two nodes’ interactions with the third node within a triadic interrelationship. Thus, it is plausible to ask whether ASD is associated with altered structural balance resulting from atypical triadic interactions. In other words, it is the abnormal interplay of positive and negative interactions that matters in ASD, besides and beyond hypo (hyper) pair connectivity. To address this question, we explore triadic interactions based on SBT in the weighted signed resting-state functional magnetic resonance imaging networks of participants with ASD relative to healthy controls (CON). We demonstrate that balanced triads are overrepresented in the ASD and CON networks while unbalanced triads are underrepresented, providing first-time empirical evidence for the strong notion of structural balance on the brain networks. We further analyze the frequency and energy distributions of different triads and suggest an alternative description for the reduced functional integration and segregation in the ASD brain networks. Moreover, results reveal that the scale of change in the whole-brain networks’ energy is more narrow in the ASD networks during development. Last but not least, we observe that energy of the salience network and the default mode network are lower in ASD, which may be a reflection of the difficulty in dynamic switching and flexible behaviors. Altogether, these results provide insight into the atypical structural balance of the ASD brain (sub) networks. It also highlights the potential value of SBT as a new perspective in functional connectivity studies, especially in the case of neurodevelopmental disorders.
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Nilchian, Parsa, and Aaron T. Mattfeld. "Increased RTV in ADHD: A Novel Approach to Detect Inattention [Florida International University]." Journal of Student Research, April 24, 2019. http://dx.doi.org/10.47611/jsr.vi.660.
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Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder and the second most common mental condition in U.S. children, affecting more than 6.1 million individuals between the ages of 2-17 years. Defined by two behavioral features - inattention and hyperactivity - identifying and studying ADHD, especially related periods of inattention, a defining feature, poses an important limitation. Recent studies have identified elevated reaction time variability (RTV) as a reliable feature of ADHD, that may be related to periods of inattention. However, the neural mechanisms behind RTV, and thereby inattention, are not well understood. The default mode network (DMN) is a functional brain system responsible for internally-directed mental processes, that is active when not engaged in cognitively demanding externally directed tasks. Activation of the DMN during active states, thus, could disrupt externally directed behavior and related neurobiological mechanisms – perhaps acting as an internal distraction. We predicted that activation in the DMN during an externally directed task will be elevated during periods of increased RTV. Further, we anticipated DMN activation to precede abnormally slow responses. We used blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) while participants with and without ADHD performed a standard sustained attention to response (SART) task. We then examined the activation of the DMN during episodes of aberrant RTV, defined as reaction times more than two standard deviations from the preceding measure of variability, to ascertain the nature of the aforementioned association. The neurobiological mechanisms that are related to the attention-deficit in ADHD must be better understood to aid in diagnosis and treatment. This study aims to be the first to provide comprehensive evidence of the neural underpinnings behind increased RTV and thereby inattention in individuals with ADHD. The current system to diagnose ADHD in children is based on potentially subjective behavioral observations by parents and teachers. Identifying increased RTV as a behavioral marker of ADHD with a well-characterized neurobiological mechanism may enable a more effective and objective method of diagnosis, resulting in more successful treatment outcomes and decreased costs of care for families of children with the disorder.
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Voruz, Philippe, Alexandre Cionca, Isabele Jacot de Alcântara, Anthony Nuber-Champier, Gilles Allali, Lamyae Benzakour, Marine Thomasson, et al. "Functional connectivity underlying cognitive and psychiatric symptoms in post-COVID-19 syndrome: is anosognosia a key determinant?" Brain Communications 4, no. 2 (March 1, 2022). http://dx.doi.org/10.1093/braincomms/fcac057.
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Abstract Lack of awareness of cognitive impairment (i.e. anosognosia) could be a key factor for distinguishing between neuropsychological post-COVID-19 condition phenotypes. In this context, the 2-fold aim of the present study was to (i) establish the prevalence of anosognosia for memory impairment, according to the severity of the infection in the acute phase and (ii) determine whether anosognosic patients with post-COVID syndrome have a different cognitive and psychiatric profile from nosognosic patients, with associated differences in brain functional connectivity. A battery of neuropsychological, psychiatric, olfactory, dyspnoea, fatigue and quality-of-life tests was administered 227.07 ± 42.69 days post-SARS-CoV-2 infection to 102 patients (mean age: 56.35 years, 65 men, no history of neurological, psychiatric, neuro-oncological or neurodevelopmental disorder prior to infection) who had experienced either a mild (not hospitalized; n = 45), moderate (conventional hospitalization; n = 34) or severe (hospitalization with intensive care unit stay and mechanical ventilation; n = 23) presentation in the acute phase. Patients were first divided into two groups according to the presence or absence of anosognosia for memory deficits (26 anosognosic patients and 76 nosognosic patients). Of these, 49 patients underwent an MRI. Structural images were visually analysed, and statistical intergroup analyses were then performed on behavioural and functional connectivity measures. Only 15.6% of patients who presented mild disease displayed anosognosia for memory dysfunction, compared with 32.4% of patients with moderate presentation and 34.8% of patients with severe disease. Compared with nosognosic patients, those with anosognosia for memory dysfunction performed significantly more poorly on objective cognitive and olfactory measures. By contrast, they gave significantly more positive subjective assessments of their quality of life, psychiatric status and fatigue. Interestingly, the proportion of patients exhibiting a lack of consciousness of olfactory deficits was significantly higher in the anosognosic group. Functional connectivity analyses revealed a significant decrease in connectivity, in the anosognosic group as compared with the nosognosic group, within and between the following networks: the left default mode, the bilateral somatosensory motor, the right executive control, the right salient ventral attention and the bilateral dorsal attention networks, as well as the right Lobules IV and V of the cerebellum. Lack of awareness of cognitive disorders and, to a broader extent, impairment of the self-monitoring brain system, may be a key factor for distinguishing between the clinical phenotypes of post-COVID syndrome with neuropsychological deficits.