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Horata E, Ay H, Aslan D. Autistic-like behaviour and changes in thalamic cell numbers a rat model of valproic acid-induced autism; A behavioural and stereological study. Brain Res 2024; 1840:149047. [PMID: 38823508 DOI: 10.1016/j.brainres.2024.149047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Revised: 05/28/2024] [Accepted: 05/29/2024] [Indexed: 06/03/2024]
Abstract
The contribution of the thalamus to the development and behavioural changes in autism spectrum disorders (ASD), a neurodevelopmental syndrome, remains unclear. The aim of this study was to determine the changes in thalamic volume and cell number in the valproic acid (VPA)-induced ASD model using stereological methods and to clarify the relationship between thalamus and ASD-like behaviour. Ten pregnant rats were administered a single dose (600 mg/kg) of VPA intraperitoneally on G12.5 (VPA group), while five pregnant rats were injected with 5 ml saline (control group). Behavioural tests were performed to determine appropriate subjects and ASD-like behaviours. At P55, the brains of the subjects were removed. The sagittal sections were stained with cresyl violet and toluidine blue. The thalamic and hemispheric volumes with their ratios, the total number of thalamic cells, neurons and non-neuronal cells were calculated using stereological methods. Data were compared using a t-test and a Pearson correlation analysis was performed to examine the relationship between behaviour and stereological outcomes. VPA-treated rats had lower sociability and sociability indexes. There was no difference in social novelty preference and anxiety. The VPA group had larger hemispheric volume, lower thalamic volume, and fewer neurons. The highest percentage decrease was in non-neuronal cells. There was a moderate positive correlation between the number of non-neuronal cells and sociability, thalamic volume and the number of neurons as well as the time spent in the light box. The correlation between behaviour and stereological data suggests that the thalamus is associated with ASD-like behaviour.
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Affiliation(s)
- Erdal Horata
- Orthopedic Prosthesis Orthotics, Atatürk Health Services Vocational School, Afyonkarahisar Health Sciences University, Afyonkarahisar, Turkey.
| | - Hakan Ay
- Department of Anatomy, Faculty of Medicine, Eskişehir Osmangazi University, Eskişehir, Turkey
| | - Duygu Aslan
- Department of Anatomy, Faculty of Medicine, Kafkas University, Kars, Turkey
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2
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Huang S, Wang S, Che Z, Ge H, Yan Z, Fan J, Lu X, Liu L, Liu W, Zhong Y, Zou C, Rao J, Chen J. Brain-wide functional connectivity alterations and their cognitive correlates in subjective cognitive decline. Front Neurosci 2024; 18:1438260. [PMID: 39148525 PMCID: PMC11324595 DOI: 10.3389/fnins.2024.1438260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2024] [Accepted: 07/15/2024] [Indexed: 08/17/2024] Open
Abstract
Background Individuals with subjective cognitive decline (SCD) are at risk of developing Alzheimer's Disease (AD). Traditional seed-based analysis has shown biased functional connectivity (FC) in SCD individuals. To investigate unbiased altered FC by the brain-wide association study (BWAS) and to determine its association with cognition in SCD individuals. Methods Measure of association (MA) analysis was applied to detect significant voxels with FC changes. Based on these changes, we identified regions of interest (ROIs) and conducted ROI-wise FC analyses. Correlation analyses were then performed between these FC circuits and cognition. Results MA analysis identified 10 ROIs with significantly altered voxels. ROI-wise FC analyses revealed 14 strengthened FC, predominantly parietal-occipital link alterations. The FC between the right superior occipital gyrus and the right postcentral gyrus correlated positively with executive function, while the FC between the right middle occipital gyrus and the left angular gyrus correlated positively with episodic memory in SCD individuals. Conclusion SCD involves multifocal impairments, of which regions of default mode network (DMN) and occipital lobe should be specially focused. Cross-hemispheric alterations indicate an internal interactive impairment pattern in SCD. The reduced FC between the right superior occipital gyrus and the right postcentral gyrus, and between the right middle occipital gyrus and the left angular gyrus, which correlate with specific cognitive functions, could serve as potential biomarkers for SCD diagnosis.
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Affiliation(s)
- Shaochun Huang
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Siyu Wang
- Fourth Clinical College, Nanjing Medical University, Nanjing, China
| | - Zigang Che
- Department of Radiology, Nanjing Tongren Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Honglin Ge
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zheng Yan
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jia Fan
- Department of Human Biology, University of Cape Town Faculty of Health Sciences, Cape Town, South Africa
| | - Xiang Lu
- Department of Neurology, Northern Jiangsu People's Hospital, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Li Liu
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Wan Liu
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yeming Zhong
- Department of Radiology, Nanjing Tongren Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Caiyun Zou
- Department of Radiology, Nanjing Tongren Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Jiang Rao
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jiu Chen
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
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Siva K, Ponnusamy P, Ramanathan M. Disrupted Brain Network Measures in Parkinson's Disease Patients with Severe Hyposmia and Cognitively Normal Ability. Brain Sci 2024; 14:685. [PMID: 39061425 PMCID: PMC11274763 DOI: 10.3390/brainsci14070685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 06/30/2024] [Accepted: 07/04/2024] [Indexed: 07/28/2024] Open
Abstract
Neuroscience has revolved around brain structural changes, functional activity, and connectivity alteration in Parkinson's Disease (PD); however, how the network topology organization becomes altered is still unclear, specifically in Parkinson's patients with severe hyposmia. In this study, we have examined the functional network topological alteration in patients affected by Parkinson's Disease with normal cognitive ability (ODN), Parkinson's Disease with severe hyposmia (ODP), and healthy controls (HCs) using resting-state functional magnetic resonance imaging (rsfMRI) data. We have analyzed brain topological organization using popular graph measures such as network segregation (clustering coefficient, modularity), network integration (participation coefficient, path length), small-worldness, efficiency, centrality, and assortativity. Then, we used a feature ranking approach based on the diagonal adaptation of neighborhood component analysis, aiming to determine a graph measure that is sensitive enough to distinguish between these three different groups. We noted significantly lower segregation and local efficiency and small-worldness in ODP compared to ODN and HCs. On the contrary, we did not find differences in network integration in ODP compared to ODN and HCs, which indicates that the brain network becomes fragmented in ODP. At the brain network level, a progressive increase in the DMN (Default Mode Network) was observed from healthy controls to ODN to ODP, and a continuous decrease in the cingulo-opercular network was observed from healthy controls to ODN to ODP. Further, the feature ranking approach has shown that the whole-brain clustering coefficient and small-worldness are sensitive measures to classify ODP vs. ODN, as well as HCs. Looking at the brain regional network segregation, we have found that the cerebellum and limbic, fronto-parietal, and occipital lobes have higher ODP reductions than ODN and HCs. Our results suggest network topological measures, specifically whole-brain segregation and small-worldness decreases. At the network level, an increase in DMN and a decrease in the cingulo-opercular network could be used as biomarkers to characterize ODN and ODP.
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Affiliation(s)
| | | | - Malmathanraj Ramanathan
- Department of Electronics and Communication Engineering, National Institute of Technology, Tiruchirappalli 620015, India; (K.S.); (P.P.)
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Rolls ET, Feng J, Zhang R. Selective activations and functional connectivities to the sight of faces, scenes, body parts and tools in visual and non-visual cortical regions leading to the human hippocampus. Brain Struct Funct 2024; 229:1471-1493. [PMID: 38839620 PMCID: PMC11176242 DOI: 10.1007/s00429-024-02811-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 05/22/2024] [Indexed: 06/07/2024]
Abstract
Connectivity maps are now available for the 360 cortical regions in the Human Connectome Project Multimodal Parcellation atlas. Here we add function to these maps by measuring selective fMRI activations and functional connectivity increases to stationary visual stimuli of faces, scenes, body parts and tools from 956 HCP participants. Faces activate regions in the ventrolateral visual cortical stream (FFC), in the superior temporal sulcus (STS) visual stream for face and head motion; and inferior parietal visual (PGi) and somatosensory (PF) regions. Scenes activate ventromedial visual stream VMV and PHA regions in the parahippocampal scene area; medial (7m) and lateral parietal (PGp) regions; and the reward-related medial orbitofrontal cortex. Body parts activate the inferior temporal cortex object regions (TE1p, TE2p); but also visual motion regions (MT, MST, FST); and the inferior parietal visual (PGi, PGs) and somatosensory (PF) regions; and the unpleasant-related lateral orbitofrontal cortex. Tools activate an intermediate ventral stream area (VMV3, VVC, PHA3); visual motion regions (FST); somatosensory (1, 2); and auditory (A4, A5) cortical regions. The findings add function to cortical connectivity maps; and show how stationary visual stimuli activate other cortical regions related to their associations, including visual motion, somatosensory, auditory, semantic, and orbitofrontal cortex value-related, regions.
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Affiliation(s)
- Edmund T Rolls
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK.
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, 200403, China.
- Oxford Centre for Computational Neuroscience, Oxford, UK.
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, 200403, China
| | - Ruohan Zhang
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK.
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Jeon H, Hur A, Lee H, Shin YW, Lee SI, Shin CJ, Kim S, Ju G, Lee J, Jung JH, Chung S, Son JW. The Relationship Between Brain Activation for Taking Others' Perspective and Interoceptive Abilities in Autism Spectrum Disorder: An fMRI Study. Soa Chongsonyon Chongsin Uihak 2024; 35:197-209. [PMID: 38966201 PMCID: PMC11220477 DOI: 10.5765/jkacap.240008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/21/2024] [Accepted: 05/07/2024] [Indexed: 07/06/2024] Open
Abstract
Objectives In this functional magnetic resonance imaging study, we aimed to investigate the differences in brain activation between individuals with autism spectrum disorder (ASD) and typically developing (TD) individuals during perspective taking. We also examined the association between brain activation and empathic and interoceptive abilities. Methods During scanning, participants from the ASD (n=17) and TD (n=22) groups were shown pain stimuli and asked to rate the level of the observed pain from both self- and other-perspectives. Empathic abilities, including perspective taking, were measured using an empathic questionnaire, and three dimensions of interoception were assessed: interoceptive accuracy, interoceptive sensibility, and interoceptive trait prediction errors. Results During self-perspective taking, the ASD group exhibited greater activation in the left precuneus than the TD group. During other-perspective taking, relative hyperactivation extended to areas including the right precuneus, right superior frontal gyrus, left caudate nucleus, and left amygdala. Brain activation levels in the right superior frontal gyrus while taking other-perspective were negatively correlated with interoceptive accuracy, and those in the left caudate were negatively correlated with perspective taking ability in the ASD group. Conclusion Individuals with ASD show atypical brain activation during perspective taking. Notably, their brain regions associated with stress reactions and escape responses are overactivated when taking other-perspective. This overactivity is related to poor interoceptive accuracy, suggesting that individuals with ASD may experience difficulties with the self-other distinction or atypical embodiment when considering another person's perspective.
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Affiliation(s)
- Huiyeong Jeon
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
| | - Ahjeong Hur
- Department of Psychology, Chungbuk National University, Cheongju, Korea
| | - Hoyeon Lee
- Autism and Developmental Disorders Treatment Center, Chungbuk National University Hospital, Cheongju, Korea
| | - Yong-Wook Shin
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sang-Ick Lee
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
- Department of Neuropsychiatry, College of Medicine, Chungbuk National University, Cheongju, Korea
| | - Chul-Jin Shin
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
- Department of Neuropsychiatry, College of Medicine, Chungbuk National University, Cheongju, Korea
| | - Siekyeong Kim
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
- Department of Neuropsychiatry, College of Medicine, Chungbuk National University, Cheongju, Korea
| | - Gawon Ju
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
- Department of Neuropsychiatry, College of Medicine, Chungbuk National University, Cheongju, Korea
| | - Jeonghwan Lee
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
| | - Joon Hyung Jung
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
| | - Seungwon Chung
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
- Autism and Developmental Disorders Treatment Center, Chungbuk National University Hospital, Cheongju, Korea
| | - Jung-Woo Son
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Korea
- Autism and Developmental Disorders Treatment Center, Chungbuk National University Hospital, Cheongju, Korea
- Department of Neuropsychiatry, College of Medicine, Chungbuk National University, Cheongju, Korea
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Zhang H, Chen J, Liao B, Wu FX, Bi XA. Deep Canonical Correlation Fusion Algorithm Based on Denoising Autoencoder for ASD Diagnosis and Pathogenic Brain Region Identification. Interdiscip Sci 2024; 16:455-468. [PMID: 38573456 DOI: 10.1007/s12539-024-00625-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/22/2024] [Accepted: 02/25/2024] [Indexed: 04/05/2024]
Abstract
Autism Spectrum Disorder (ASD) is defined as a neurodevelopmental condition distinguished by unconventional neural activities. Early intervention is key to managing the progress of ASD, and current research primarily focuses on the use of structural magnetic resonance imaging (sMRI) or resting-state functional magnetic resonance imaging (rs-fMRI) for diagnosis. Moreover, the use of autoencoders for disease classification has not been sufficiently explored. In this study, we introduce a new framework based on autoencoder, the Deep Canonical Correlation Fusion algorithm based on Denoising Autoencoder (DCCF-DAE), which proves to be effective in handling high-dimensional data. This framework involves efficient feature extraction from different types of data with an advanced autoencoder, followed by the fusion of these features through the DCCF model. Then we utilize the fused features for disease classification. DCCF integrates functional and structural data to help accurately diagnose ASD and identify critical Regions of Interest (ROIs) in disease mechanisms. We compare the proposed framework with other methods by the Autism Brain Imaging Data Exchange (ABIDE) database and the results demonstrate its outstanding performance in ASD diagnosis. The superiority of DCCF-DAE highlights its potential as a crucial tool for early ASD diagnosis and monitoring.
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Affiliation(s)
- Huilian Zhang
- Key Laboratory of Data Science and Intelligence Education, Ministry of Education, Hainan Normal University, Haikou, 571126, China
- College of Mathematics and Statistics, Hainan Normal University, Haikou, 571126, China
| | - Jie Chen
- Key Laboratory of Data Science and Intelligence Education, Ministry of Education, Hainan Normal University, Haikou, 571126, China
- College of Mathematics and Statistics, Hainan Normal University, Haikou, 571126, China
| | - Bo Liao
- Key Laboratory of Data Science and Intelligence Education, Ministry of Education, Hainan Normal University, Haikou, 571126, China
- College of Mathematics and Statistics, Hainan Normal University, Haikou, 571126, China
| | - Fang-Xiang Wu
- Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, S7N5A9, Canada
| | - Xia-An Bi
- Key Laboratory of Data Science and Intelligence Education, Ministry of Education, Hainan Normal University, Haikou, 571126, China.
- College of Mathematics and Statistics, Hainan Normal University, Haikou, 571126, China.
- College of Information Science and Engineering, Hunan Normal University, Changsha, Hunan, 410081, China.
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Chen Y, Yan J, Jiang M, Zhang T, Zhao Z, Zhao W, Zheng J, Yao D, Zhang R, Kendrick KM, Jiang X. Adversarial Learning Based Node-Edge Graph Attention Networks for Autism Spectrum Disorder Identification. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024; 35:7275-7286. [PMID: 35286265 DOI: 10.1109/tnnls.2022.3154755] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Graph neural networks (GNNs) have received increasing interest in the medical imaging field given their powerful graph embedding ability to characterize the non-Euclidean structure of brain networks based on magnetic resonance imaging (MRI) data. However, previous studies are largely node-centralized and ignore edge features for graph classification tasks, resulting in moderate performance of graph classification accuracy. Moreover, the generalizability of GNN model is still far from satisfactory in brain disorder [e.g., autism spectrum disorder (ASD)] identification due to considerable individual differences in symptoms among patients as well as data heterogeneity among different sites. In order to address the above limitations, this study proposes a novel adversarial learning-based node-edge graph attention network (AL-NEGAT) for ASD identification based on multimodal MRI data. First, both node and edge features are modeled based on structural and functional MRI data to leverage complementary brain information and preserved in the constructed weighted adjacent matrix for individuals through the attention mechanism in the proposed NEGAT. Second, two AL methods are employed to improve the generalizability of NEGAT. Finally, a gradient-based saliency map strategy is utilized for model interpretation to identify important brain regions and connections contributing to the classification. Experimental results based on the public Autism Brain Imaging Data Exchange I (ABIDE I) data demonstrate that the proposed framework achieves a classification accuracy of 74.7% between ASD and typical developing (TD) groups based on 1007 subjects across 17 different sites and outperforms the state-of-the-art methods, indicating satisfying classification ability and generalizability of the proposed AL-NEGAT model. Our work provides a powerful tool for brain disorder identification.
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8
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Ke M, Hou Y, Zhang L, Liu G. Brain functional network changes in patients with juvenile myoclonic epilepsy: a study based on graph theory and Granger causality analysis. Front Neurosci 2024; 18:1363255. [PMID: 38774788 PMCID: PMC11106382 DOI: 10.3389/fnins.2024.1363255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 04/04/2024] [Indexed: 05/24/2024] Open
Abstract
Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have shown that the brain networks are disrupted in adolescent patients with juvenile myoclonic epilepsy (JME). However, previous studies have mainly focused on investigating brain connectivity disruptions from the perspective of static functional connections, overlooking the dynamic causal characteristics between brain network connections. In our study involving 37 JME patients and 35 Healthy Controls (HC), we utilized rs-fMRI to construct whole-brain functional connectivity network. By applying graph theory, we delved into the altered topological structures of the brain functional connectivity network in JME patients and identified abnormal regions as key regions of interest (ROIs). A novel aspect of our research was the application of a combined approach using the sliding window technique and Granger causality analysis (GCA). This method allowed us to delve into the dynamic causal relationships between these ROIs and uncover the intricate patterns of dynamic effective connectivity (DEC) that pervade various brain functional networks. Graph theory analysis revealed significant deviations in JME patients, characterized by abnormal increases or decreases in metrics such as nodal betweenness centrality, degree centrality, and efficiency. These findings underscore the presence of widespread disruptions in the topological features of the brain. Further, clustering analysis of the time series data from abnormal brain regions distinguished two distinct states indicative of DEC patterns: a state of strong connectivity at a lower frequency (State 1) and a state of weak connectivity at a higher frequency (State 2). Notably, both states were associated with connectivity abnormalities across different ROIs, suggesting the disruption of local properties within the brain functional connectivity network and the existence of widespread multi-functional brain functional networks damage in JME patients. Our findings elucidate significant disruptions in the local properties of whole-brain functional connectivity network in patients with JME, revealing causal impairments across multiple functional networks. These findings collectively suggest that JME is a generalized epilepsy with localized abnormalities. Such insights highlight the intricate network dysfunctions characteristic of JME, thereby enriching our understanding of its pathophysiological features.
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Affiliation(s)
- Ming Ke
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Yaru Hou
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Li Zhang
- Hospital of Lanzhou University of Technology, Lanzhou University of Technology, Lanzhou, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
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Kausel L, Michon M, Soto-Icaza P, Aboitiz F. A multimodal interface for speech perception: the role of the left superior temporal sulcus in social cognition and autism. Cereb Cortex 2024; 34:84-93. [PMID: 38696598 DOI: 10.1093/cercor/bhae066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/17/2024] [Accepted: 02/03/2024] [Indexed: 05/04/2024] Open
Abstract
Multimodal integration is crucial for human interaction, in particular for social communication, which relies on integrating information from various sensory modalities. Recently a third visual pathway specialized in social perception was proposed, which includes the right superior temporal sulcus (STS) playing a key role in processing socially relevant cues and high-level social perception. Importantly, it has also recently been proposed that the left STS contributes to audiovisual integration of speech processing. In this article, we propose that brain areas along the right STS that support multimodal integration for social perception and cognition can be considered homologs to those in the left, language-dominant hemisphere, sustaining multimodal integration of speech and semantic concepts fundamental for social communication. Emphasizing the significance of the left STS in multimodal integration and associated processes such as multimodal attention to socially relevant stimuli, we underscore its potential relevance in comprehending neurodevelopmental conditions characterized by challenges in social communication such as autism spectrum disorder (ASD). Further research into this left lateral processing stream holds the promise of enhancing our understanding of social communication in both typical development and ASD, which may lead to more effective interventions that could improve the quality of life for individuals with atypical neurodevelopment.
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Affiliation(s)
- Leonie Kausel
- Centro de Estudios en Neurociencia Humana y Neuropsicología (CENHN), Facultad de Psicología, Universidad Diego Portales, Chile, Vergara 275, 8370076 Santiago, Chile
| | - Maëva Michon
- Praxiling Laboratory, Joint Research Unit (UMR 5267), Centre National de la Recherche Scientifique (CNRS), Université Paul Valéry, Montpellier, France, Route de Mende, 34199 Montpellier cedex 5, France
- Centro Interdisciplinario de Neurociencia, Pontificia Universidad Católica de Chile, Chile, Marcoleta 391, 2do piso, 8330024 Santiago, Chile
- Laboratorio de Neurociencia Cognitiva y Evolutiva, Facultad de Medicina, Pontificia Universidad Católica de Chile, Chile, Marcoleta 391, 2do piso, 8330024 Santiago, Chile
| | - Patricia Soto-Icaza
- Centro de Investigación en Complejidad Social (CICS), Facultad de Gobierno, Universidad del Desarrollo, Chile, Av. Las Condes 12461, edificio 3, piso 3, 7590943, Las Condes Santiago, Chile
| | - Francisco Aboitiz
- Centro Interdisciplinario de Neurociencia, Pontificia Universidad Católica de Chile, Chile, Marcoleta 391, 2do piso, 8330024 Santiago, Chile
- Laboratorio de Neurociencia Cognitiva y Evolutiva, Facultad de Medicina, Pontificia Universidad Católica de Chile, Chile, Marcoleta 391, 2do piso, 8330024 Santiago, Chile
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Rolls ET. Two what, two where, visual cortical streams in humans. Neurosci Biobehav Rev 2024; 160:105650. [PMID: 38574782 DOI: 10.1016/j.neubiorev.2024.105650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/25/2024] [Accepted: 03/31/2024] [Indexed: 04/06/2024]
Abstract
ROLLS, E. T. Two What, Two Where, Visual Cortical Streams in Humans. NEUROSCI BIOBEHAV REV 2024. Recent cortical connectivity investigations lead to new concepts about 'What' and 'Where' visual cortical streams in humans, and how they connect to other cortical systems. A ventrolateral 'What' visual stream leads to the inferior temporal visual cortex for object and face identity, and provides 'What' information to the hippocampal episodic memory system, the anterior temporal lobe semantic system, and the orbitofrontal cortex emotion system. A superior temporal sulcus (STS) 'What' visual stream utilising connectivity from the temporal and parietal visual cortex responds to moving objects and faces, and face expression, and connects to the orbitofrontal cortex for emotion and social behaviour. A ventromedial 'Where' visual stream builds feature combinations for scenes, and provides 'Where' inputs via the parahippocampal scene area to the hippocampal episodic memory system that are also useful for landmark-based navigation. The dorsal 'Where' visual pathway to the parietal cortex provides for actions in space, but also provides coordinate transforms to provide inputs to the parahippocampal scene area for self-motion update of locations in scenes in the dark or when the view is obscured.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, UK; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China.
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Das S, Zomorrodi R, Kirkovski M, Hill AT, Enticott PG, Blumberger DM, Rajji TK, Desarkar P. Atypical alpha band microstates produced during eyes-closed resting state EEG in autism. Prog Neuropsychopharmacol Biol Psychiatry 2024; 131:110958. [PMID: 38309329 DOI: 10.1016/j.pnpbp.2024.110958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 02/05/2024]
Abstract
Electroencephalogram (EEG) microstates, which represent quasi-stable patterns of scalp topography, are a promising tool that has the temporal resolution to study atypical spatial and temporal networks in autism spectrum disorder (ASD). While current literature suggests microstates are atypical in ASD, their clinical utility, i.e., relationship with the core behavioural characteristics of ASD, is not fully understood. The aim of this study was to examine microstate parameters in ASD, and examine the relationship between these parameters and core behavioural characteristics in ASD. We compared duration, occurrence, coverage, global explained variance percentage, global field power and spatial correlation of EEG microstates between autistic and neurotypical (NT) adults. Modified k-means cluster analysis was used on eyes-closed, resting state EEG from 30 ASD (10 females, 28.97 ± 9.34 years) and 30 age-equated NT (13 females, 29.33 ± 8.88 years) adults. Five optimal microstates, A to E, were selected to best represent the data. Five microstate maps explaining 80.44% of the NT and 78.44% of the ASD data were found. The ASD group was found to have atypical parameters of microstate A, C, D, and E. Of note, all parameters of microstate C in the ASD group were found to be significantly less than NT. While parameters of microstate D, and E were also found to significantly correlate with subscales of the Ritvo Autism Asperger Diagnostic Scale - Revised (RAADS-R), these findings did not survive a Bonferroni Correction. These findings, in combination with previous findings, highlight the potential clinical utility of EEG microstates and indicate their potential value as a neurophysiologic marker that can be further studied.
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Affiliation(s)
- Sushmit Das
- Centre for Addiction and Mental Health, Toronto, Canada; Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Reza Zomorrodi
- Centre for Addiction and Mental Health, Toronto, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Melissa Kirkovski
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Institute for Health and Sport, Victoria University, Melbourne, Australia
| | - Aron T Hill
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Department of Psychiatry, Central Clinical School, Monash University, Melbourne, Australia
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Daniel M Blumberger
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Toronto Dementia Research Alliance, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Pushpal Desarkar
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.
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12
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Chen D, Jia T, Cheng W, Desrivières S, Heinz A, Schumann G, Feng J. Evaluation of behavioral variance/covariance explained by the neuroimaging data through a pattern-based regression. Hum Brain Mapp 2024; 45:e26601. [PMID: 38488475 PMCID: PMC10941514 DOI: 10.1002/hbm.26601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 01/01/2024] [Accepted: 01/08/2024] [Indexed: 03/18/2024] Open
Abstract
Neuroimaging data have been widely used to understand the neural bases of human behaviors. However, most studies were either based on a few predefined regions of interest or only able to reveal limited vital regions, hence not providing an overarching description of the relationship between neuroimaging and behaviors. Here, we proposed a voxel-based pattern regression that not only could investigate the overall brain-associated variance (BAV) for a given behavioral measure but could also evaluate the shared neural bases between different behaviors across multiple neuroimaging data. The proposed method demonstrated consistently high reliability and accuracy through comprehensive simulations. We further implemented this approach on real data of adolescents (IMAGEN project, n = 2089) and adults (HCP project, n = 808) to investigate brain-based variances of multiple behavioral measures, for instance, cognitive behaviors, substance use, and psychiatric disorders. Notably, intelligence-related scores showed similar high BAVs with the gray matter volume across both datasets. Further, our approach allows us to reveal the latent brain-based correlation across multiple behavioral measures, which are challenging to obtain otherwise. For instance, we observed a shared brain architecture underlying depression and externalizing problems in adolescents, while the symptom comorbidity may only emerge later in adults. Overall, our approach will provide an important statistical tool for understanding human behaviors using neuroimaging data.
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Affiliation(s)
- Di Chen
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghaiChina
| | - Tianye Jia
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghaiChina
- Institute of Psychiatry, Psychology & NeuroscienceSGDP Centre, King's College LondonLondonUK
| | - Wei Cheng
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghaiChina
| | - Sylvane Desrivières
- Institute of Psychiatry, Psychology & NeuroscienceSGDP Centre, King's College LondonLondonUK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCMCharité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of HealthBerlinGermany
| | - Gunter Schumann
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Department of Psychiatry and Psychotherapy CCMCharité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of HealthBerlinGermany
| | - Jianfeng Feng
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghaiChina
- Department of Computer ScienceUniversity of WarwickCoventryUK
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13
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Zhou C, Tang X, Yu M, Zhang H, Zhang X, Gao J, Zhang X, Chen J. Convergent and divergent genes expression profiles associated with brain-wide functional connectome dysfunction in deficit and non-deficit schizophrenia. Transl Psychiatry 2024; 14:124. [PMID: 38413564 PMCID: PMC10899251 DOI: 10.1038/s41398-024-02827-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 02/07/2024] [Accepted: 02/13/2024] [Indexed: 02/29/2024] Open
Abstract
Deficit schizophrenia (DS) is a subtype of schizophrenia characterized by the primary and persistent negative symptoms. Previous studies have identified differences in brain functions between DS and non-deficit schizophrenia (NDS) patients. However, the genetic regulation features underlying these abnormal changes are still unknown. This study aimed to detect the altered patterns of functional connectivity (FC) in DS and NDS and investigate the gene expression profiles underlying these abnormal FC. The study recruited 82 DS patients, 96 NDS patients, and 124 healthy controls (CN). Voxel-based unbiased brain-wide association study was performed to reveal altered patterns of FC in DS and NDS patients. Machine learning techniques were used to access the utility of altered FC for diseases diagnosis. Weighted gene co-expression network analysis (WGCNA) was employed to explore the associations between altered FC and gene expression of 6 donated brains. Enrichment analysis was conducted to identify the genetic profiles, and the spatio-temporal expression patterns of the key genes were further explored. Comparing to CN, 23 and 20 brain regions with altered FC were identified in DS and NDS patients. The altered FC among these regions showed significant correlations with the SDS scores and exhibited high efficiency in disease classification. WGCNA revealed associations between DS/NDS-related gene expression and altered FC. Additionally, 22 overlapped genes, including 12 positive regulation genes and 10 negative regulation genes, were found between NDS and DS. Enrichment analyses demonstrated relationships between identified genes and significant pathways related to cellular response, neuro regulation, receptor binding, and channel activity. Spatial and temporal gene expression profiles of SCN1B showed the lowest expression at the initiation of embryonic development, while DPYSL3 exhibited rapid increased in the fetal. The present study revealed different altered patterns of FC in DS and NDS patients and highlighted the potential value of FC in disease classification. The associations between gene expression and neuroimaging provided insights into specific and common genetic regulation underlying these brain functional changes in DS and NDS, suggesting a potential genetic-imaging pathogenesis of schizophrenia.
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Affiliation(s)
- Chao Zhou
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiaowei Tang
- Department of Psychiatry, Affiliated WuTaiShan Hospital of Medical College of Yangzhou University, Yangzhou, Jiangsu, China
| | - Miao Yu
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongying Zhang
- Department of Radiology, Subei People's Hospital of Jiangsu Province, Yangzhou University, Yangzhou, Jiangsu, China
| | - Xiaobin Zhang
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Ju Gao
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Jiu Chen
- Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, China.
- Medical Imaging Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
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14
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Sun K, Li Y, Zhai Z, Yin H, Liang S, Zhai F, Cui Y, Zhang G. Effects of transcutaneous auricular vagus nerve stimulation and exploration of brain network mechanisms in children with high-functioning autism spectrum disorder: study protocol for a randomized controlled trial. Front Psychiatry 2024; 15:1337101. [PMID: 38374975 PMCID: PMC10875019 DOI: 10.3389/fpsyt.2024.1337101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 01/19/2024] [Indexed: 02/21/2024] Open
Abstract
Background Autism Spectrum Disorders (ASD) are a collection of neurodevelopmental diseases characterized by poor social interaction and communication, a limited range of interests, and stereotyped behavior. High-functioning autism (HFA) indicates a subgroup of individuals with autism who possess cognitive and/or language skills that are within the average to above-normal range for their age. Transcutaneous auricular vagus nerve stimulation (taVNS) holds promise in children with HFA. However, few studies have used randomized controlled trials to validate the effectiveness of taVNS. Therefore, in this study, we intend to provide a study protocol to examine the therapeutic effects of taVNS in individuals diagnosed with HFA and to investigate the process of brain network remodeling in individuals with ASD using functional imaging techniques to observe alterations in large-scale neural networks. Methods and design We planned to employ a randomized, double-blind experimental design, including 40 children receiving sham stimulation and 40 children receiving real stimulation. We will assess clinical scales and perform functional imaging examinations before and after the stimulation. Additionally, we will include age- and gender-matched healthy children as controls and conduct functional imaging examinations. We plan first to observe the therapeutic effects of taVNS. Furthermore, we will observe the impact of taVNS stimulation on the brain network. Discussion taVNS was a low-risk, easy-to-administer, low-cost, and portable option to modulate the vagus system. taVNS may improve the social performance of HFA. Changes in the network properties of the large-scale brain network may be related to the efficacy of taVNS. Clinical trial registration http://www.chictr.org.cn, identifier ChiCTR2300074035.
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Affiliation(s)
- Ke Sun
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Ying Li
- Department of Psychiatry, Beijing Children’s Hospital, Beijing, China
| | - Zhenhang Zhai
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Heqing Yin
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Shuli Liang
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Feng Zhai
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Yonghua Cui
- Department of Psychiatry, Beijing Children’s Hospital, Beijing, China
| | - Guojun Zhang
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
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Persichetti AS, Shao J, Gotts SJ, Martin A. A functional parcellation of the whole brain in individuals with autism spectrum disorder reveals atypical patterns of network organization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.15.571854. [PMID: 38168156 PMCID: PMC10760210 DOI: 10.1101/2023.12.15.571854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
BACKGROUND Researchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy individuals with ASD and a group of seventy typically developing (TD) individuals. METHODS The rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates stability and replicability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ. RESULTS We compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: 1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, 2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and 3) subcortical structures and the hippocampus are atypically integrated with the neocortex. CONCLUSIONS These results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.
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Affiliation(s)
- Andrew S Persichetti
- Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Jiayu Shao
- Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Stephen J Gotts
- Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Alex Martin
- Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
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16
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Schwingel GB, Fontes-Dutra M, Ramos B, Riesgo R, Bambini-Junior V, Gottfried C. Preventive effects of resveratrol against early-life impairments in the animal model of autism induced by valproic acid. IBRO Neurosci Rep 2023; 15:242-251. [PMID: 37841088 PMCID: PMC10570715 DOI: 10.1016/j.ibneur.2023.09.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 09/02/2023] [Accepted: 09/21/2023] [Indexed: 10/17/2023] Open
Abstract
Background Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by social interaction deficits and repetitive/stereotyped behaviors. Its prevalence is increasing, affecting one in 36 children in the United States. The valproic acid (VPA) induced animal model of ASD is a reliable method for investigating cellular, molecular, and behavioral aspects related to the disorder. Trans-Resveratrol (RSV), a polyphenol with anti-inflammatory and antioxidant effects studied in various diseases, has recently demonstrated the ability to prevent cellular, molecular, sensory, and social deficits in the VPA model. In this study, we examined the effects of prenatal exposure to VPA and the potential preventive effects of RSV on the offspring. Method We monitored gestational weight from embryonic day 6.5 until 18.5 and assessed the onset of developmental milestones and morphometric parameters in litters. The generalized estimating equations (GEE) were used to analyze longitudinal data. Results Exposure to VPA during rat pregnancy resulted in abnormal weight gain fold-changes on embryonic days 13.5 and 18.5, followed by fewer animals per litter. Additionally, we discovered a positive correlation between weight variation during E15.5-E18.5 and the number of rat pups in the VPA group. Conclusion VPA exposure led to slight length deficiencies and delays in the onset of developmental milestones. Interestingly, the prenatal RSV treatment not only prevented most of these delays but also led to the early onset of certain milestones and improved morphometric characteristics in the offspring. In summary, our findings suggest that RSV may have potential as a therapeutic intervention to protect against the negative effects of prenatal VPA exposure, highlighting its importance in future studies of prenatal neurodevelopmental disorders.
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Affiliation(s)
- Gustavo Brum Schwingel
- Translational Research Group in Autism Spectrum Disorders-GETTEA, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Brazil
- Autism Wellbeing and Research Development (AWARD) Initiative, BR-UK-CA, Brazil
| | - Mellanie Fontes-Dutra
- Translational Research Group in Autism Spectrum Disorders-GETTEA, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Brazil
- Autism Wellbeing and Research Development (AWARD) Initiative, BR-UK-CA, Brazil
| | - Bárbara Ramos
- Translational Research Group in Autism Spectrum Disorders-GETTEA, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Rudimar Riesgo
- Translational Research Group in Autism Spectrum Disorders-GETTEA, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Brazil
- Autism Wellbeing and Research Development (AWARD) Initiative, BR-UK-CA, Brazil
- Child Neurology Unit, Hospital de Clínicas de Porto Alegre (HCPA), Brazil
| | - Victorio Bambini-Junior
- National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Brazil
- Autism Wellbeing and Research Development (AWARD) Initiative, BR-UK-CA, Brazil
- Division of Biomedical and Life Sciences, Faculty of Health and Medicine, Lancaster University, Lancaster, United Kingdom
| | - Carmem Gottfried
- Translational Research Group in Autism Spectrum Disorders-GETTEA, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Department of Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- National Institute of Science and Technology on Neuroimmunomodulation (INCT-NIM), Brazil
- Autism Wellbeing and Research Development (AWARD) Initiative, BR-UK-CA, Brazil
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Zhu J, Jiao Y, Chen R, Wang XH, Han Y. Aberrant dynamic and static functional connectivity of the striatum across specific low-frequency bands in patients with autism spectrum disorder. Psychiatry Res Neuroimaging 2023; 336:111749. [PMID: 37977097 DOI: 10.1016/j.pscychresns.2023.111749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 10/06/2023] [Accepted: 11/03/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND Dysfunctions of the striatum have been repeatedly observed in autism spectrum disorder (ASD). However, previous studies have explored the static functional connectivity (sFC) of the striatum in a single frequency band, ignoring the dynamics and frequency specificity of brain FC. Therefore, we investigated the dynamic FC (dFC) and sFC of the striatum in the slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) frequency bands. METHODS Data of 47 ASD patients and 47 typically developing (TD) controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. A seed-based approach was used to compute the dFC and sFC. Then, a two-sample t-test was performed. For regions showing abnormal sFC and dFC, we performed clinical correlation analysis and constructed support vector machine (SVM) models. RESULTS The middle frontal gyrus (MFG), precuneus, and medial superior frontal gyrus (mPFC) showed both dynamic and static alterations. The reduced striatal dFC in the right MFG was associated with autism symptoms. The dynamic‒static FC model had a great performance in ASD classification, with 95.83 % accuracy. CONCLUSIONS The striatal dFC and sFC were altered in ASD, which were frequency specific. Examining brain activity using dynamic and static FC provides a comprehensive view of brain activity.
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Affiliation(s)
- Junsa Zhu
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China
| | - Yun Jiao
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China; Network Information Center, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China.
| | - Ran Chen
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, China
| | - Xun-Heng Wang
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Yunyan Han
- Public Health School of Dalian Medical University, Dalian 116000, China
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Costa-Cordella S, Soto-Icaza P, Borgeaud K, Grasso-Cladera A, Malberg NT. Towards a comprehensive approach to mentalization-based treatment for children with autism: integrating attachment, neurosciences, and mentalizing. Front Psychiatry 2023; 14:1259432. [PMID: 38098626 PMCID: PMC10719951 DOI: 10.3389/fpsyt.2023.1259432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 11/15/2023] [Indexed: 12/17/2023] Open
Abstract
Autism spectrum disorder (ASD) is diagnosed based on socio-communicative difficulties, which are believed to result from deficits in mentalizing, mainly evidenced by alterations in recognizing and responding to the mental states of others. In recent years, efforts have been made to develop mentalization-based treatment (MBT) models for this population. These models focus on enhancing individuals' ability to understand and reflect on their own mental states, as well as those of others. However, MBT approaches for people with ASD are limited by their existing theoretical background, which lacks a strong foundation grounded in neuroscience-based evidence properly integrated with attachment, and mentalizing. These are crucial aspects for understanding psychological processes in autism, and as such, they play a pivotal role in shaping the development of tailored and effective therapeutic strategies for this specific population. In this paper we review evidence related to the neurobiological, interpersonal, and psychological dimensions of autism and their implications for mentalizing processes. We also review previous mentalization-based frameworks on the psychosis continuum to provide a comprehensive understanding of attachment, neurobiology, and mentalization domains in therapeutic approaches for autism. After presenting a synthesis of the literature, we offer a set of clinical strategies for the work with children with autism. Finally, we provide recommendations to advance the field towards more robust models that can serve as a basis for evidence-based therapeutic strategies.
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Affiliation(s)
- Stefanella Costa-Cordella
- Centro de Estudios en Psicología Clínica y Psicoterapia, Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
- Centro de Estudios en Neurociencia y Neuropsicología Humana, Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
- Millennium Institute for Depression and Personality Research (MIDAP), Santiago, Chile
| | - Patricia Soto-Icaza
- Laboratorio de Neurociencia Social y Neuromodulación (neuroCICS), Centro de Investigación en Complejidad Social (CICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago, Chile
| | | | - Aitana Grasso-Cladera
- Centro de Estudios en Neurociencia y Neuropsicología Humana, Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
- Institute of Cognitive Science, Universität Osnabrück, Osnabrück, Germany
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Ong LT, Fan SWD. Morphological and Functional Changes of Cerebral Cortex in Autism Spectrum Disorder. INNOVATIONS IN CLINICAL NEUROSCIENCE 2023; 20:40-47. [PMID: 38193097 PMCID: PMC10773605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Abstract
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by early-onset impairments in socialization, communication, repetitive behaviors, and restricted interests. ASD exhibits considerable heterogeneity, with clinical presentations varying across individuals and age groups. The pathophysiology of ASD is hypothesized to be due to abnormal brain development influenced by a combination of genetic and environmental factors. One of the most consistent morphological parameters for assessing the abnormal brain structures in patients with ASD is cortical thickness. Studies have shown changes in the cortical thickness within the frontal, temporal, parietal, and occipital lobes of individuals with ASD. These changes in cortical thickness often correspond to specific clinical features observed in individuals with ASD. Furthermore, the aberrant brain anatomical features and cortical thickness alterations may lead to abnormal brain connectivity and synaptic structure. Additionally, ASD is associated with cortical hyperplasia in early childhood, followed by a cortical plateau and subsequent decline in later stages of development. However, research in this area has yielded contradictory findings regarding the cortical thickness across various brain regions in ASD.
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Affiliation(s)
- Leong Tung Ong
- Both authors are with Faculty of Medicine, University of Malaya in Kuala Lumpur, Malaysia
| | - Si Wei David Fan
- Both authors are with Faculty of Medicine, University of Malaya in Kuala Lumpur, Malaysia
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20
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Jia Y, Gu H, Li Y. Influence of inhibitory autapses on synchronization of inhibitory network gamma oscillations. Cogn Neurodyn 2023; 17:1131-1152. [PMID: 37786650 PMCID: PMC10542088 DOI: 10.1007/s11571-022-09856-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 06/22/2022] [Accepted: 07/12/2022] [Indexed: 11/30/2022] Open
Abstract
A recent experimental study showed that inhibitory autapses favor firing synchronization of parvalbumin interneurons in the neocortex during gamma oscillations. In the present paper, to provide a comprehensive and deep understanding to the experimental observation, the influence of inhibitory autapses on synchronization of interneuronal network gamma oscillations is theoretically investigated. Weak, middle, and strong synchronizations of a globally inhibitory coupled network composed of Wang-Buzsáki model without autapses appear at the bottom-left, middle, and top-right of the parameter plane with the conductance (gsyn) and the decay constant (τsyn) of inhibitory synapses taken as the x-axis and y-axis, respectively. After introducing inhibitory autapses, the border between the strong and middle synchronizations in the (gsyn, τsyn) plane moves to the top-right with increasing the conductance (gaut) and the decay constant (τaut) of autapses, due to that interspike interval of the single neuron becomes longer, leading to that larger τsyn is needed to ensure the strong synchronization. Then, the synchronization degree of middle and strong synchronizations around the border in the (gsyn, τsyn) plane decreases, while of strong synchronization in the remaining region remains unchanged. The synchronization degree of weak synchronization increases with increasing τaut and gaut, due to that the inhibitory autaptic current becomes strong and long to facilitate synchronization. The enhancement of weak synchronization modulated by inhibitory autapses is also simulated in the random, small-world, and scale-free networks, which may provide explanations to the experimental observation. These results present complex dynamics of synchronization modulated by inhibitory autapses, which needs future experimental demonstrations.
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Affiliation(s)
- Yanbing Jia
- School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, 471000 China
| | - Huaguang Gu
- School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, 200092 China
| | - Yuye Li
- College of Mathematics and Computer Science, Chifeng University, Chifeng, 024000 China
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21
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Shan J, Gu Y, Zhang J, Hu X, Wu H, Yuan T, Zhao D. A scoping review of physiological biomarkers in autism. Front Neurosci 2023; 17:1269880. [PMID: 37746140 PMCID: PMC10512710 DOI: 10.3389/fnins.2023.1269880] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/23/2023] [Indexed: 09/26/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by pervasive deficits in social interaction, communication impairments, and the presence of restricted and repetitive behaviors. This complex disorder is a significant public health concern due to its escalating incidence and detrimental impact on quality of life. Currently, extensive investigations are underway to identify prospective susceptibility or predictive biomarkers, employing a physiological biomarker-based framework. However, knowledge regarding physiological biomarkers in relation to Autism is sparse. We performed a scoping review to explore putative changes in physiological activities associated with behaviors in individuals with Autism. We identified studies published between January 2000 and June 2023 from online databases, and searched keywords included electroencephalography (EEG), magnetoencephalography (MEG), electrodermal activity markers (EDA), eye-tracking markers. We specifically detected social-related symptoms such as impaired social communication in ASD patients. Our results indicated that the EEG/ERP N170 signal has undergone the most rigorous testing as a potential biomarker, showing promise in identifying subgroups within ASD and displaying potential as an indicator of treatment response. By gathering current data from various physiological biomarkers, we can obtain a comprehensive understanding of the physiological profiles of individuals with ASD, offering potential for subgrouping and targeted intervention strategies.
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Affiliation(s)
- Jiatong Shan
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Arts and Sciences, New York University Shanghai, Shanghai, China
| | - Yunhao Gu
- Graduate School of Education, University of Pennsylvania, Philadelphia, PA, United States
| | - Jie Zhang
- Department of Neurology, Institute of Neurology, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoqing Hu
- Department of Psychology, The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
- HKU, Shenzhen Institute of Research and Innovation, Shenzhen, China
| | - Haiyan Wu
- Center for Cognitive and Brain Sciences and Department of Psychology, Macau, China
| | - Tifei Yuan
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Di Zhao
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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22
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Wang Y, Long H, Zhou Q, Bo T, Zheng J. PLSNet: Position-aware GCN-based autism spectrum disorder diagnosis via FC learning and ROIs sifting. Comput Biol Med 2023; 163:107184. [PMID: 37356292 DOI: 10.1016/j.compbiomed.2023.107184] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 05/25/2023] [Accepted: 06/13/2023] [Indexed: 06/27/2023]
Abstract
Brain function connectivity, derived from functional magnetic resonance imaging (fMRI), has enjoyed high popularity in the studies of Autism Spectrum Disorder (ASD) diagnosis. Albeit rapid progress has been made, most studies still suffer from several knotty issues: (1) the hardship of modeling the sophisticated brain neuronal connectivity; (2) the mismatch of identically graph node setup to the variations of different brain regions; (3) the dimensionality explosion resulted from excessive voxels in each fMRI sample; (4) the poor interpretability giving rise to unpersuasive diagnosis. To ameliorate these issues, we propose a position-aware graph-convolution-network-based model, namely PLSNet, with superior accuracy and compelling built-in interpretability for ASD diagnosis. Specifically, a time-series encoder is designed for context-rich feature extraction, followed by a function connectivity generator to model the correlation with long range dependencies. In addition, to discriminate the brain nodes with different locations, the position embedding technique is adopted, giving a unique identity to each graph region. We then embed a rarefying method to sift the salient nodes during message diffusion, which would also benefit the reduction of the dimensionality complexity. Extensive experiments conducted on Autism Brain Imaging Data Exchange demonstrate that our PLSNet achieves state-of-the-art performance. Notably, on CC200 atlas, PLSNet reaches an accuracy of 76.4% and a specificity of 78.6%, overwhelming the previous state-of-the-art with 2.5% and 6.5% under five-fold cross-validation policy. Moreover, the most salient brain regions predicted by PLSNet are closely consistent with the theoretical knowledge in the medical domain, providing potential biomarkers for ASD clinical diagnosis. Our code is available at https://github.com/CodeGoat24/PLSNet.
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Affiliation(s)
- Yibin Wang
- College of Computer Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China
| | - Haixia Long
- College of Computer Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China
| | - Qianwei Zhou
- College of Computer Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China
| | - Tao Bo
- Scientific Center, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
| | - Jianwei Zheng
- College of Computer Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China.
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23
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Dadario NB, Sughrue ME. The functional role of the precuneus. Brain 2023; 146:3598-3607. [PMID: 37254740 DOI: 10.1093/brain/awad181] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 06/01/2023] Open
Abstract
Recent advancements in computational approaches and neuroimaging techniques have refined our understanding of the precuneus. While previously believed to be largely a visual processing region, the importance of the precuneus in complex cognitive functions has been previously less familiar due to a lack of focal lesions in this deeply seated region, but also a poor understanding of its true underlying anatomy. Fortunately, recent studies have revealed significant information on the structural and functional connectivity of this region, and this data has provided a more detailed mechanistic understanding of the importance of the precuneus in healthy and pathologic states. Through improved resting-state functional MRI analyses, it has become clear that the function of the precuneus can be better understood based on its functional association with large scale brain networks. Dual default mode network systems have been well explained in recent years in supporting episodic memory and theory of mind; however, a novel 'para-cingulate' network, which is a subnetwork of the larger central executive network, with likely significant roles in self-referential processes and related psychiatric symptoms is introduced here and requires further clarification. Importantly, detailed anatomic studies on the precuneus structural connectivity inside and beyond the cingulate cortex has demonstrated the presence of large structural white matter connections, which provide an additional layer of meaning to the structural-functional significance of this region and its association with large scale brain networks. Together, the structural-functional connectivity of the precuneus has provided central elements which can model various neurodegenerative diseases and psychiatric disorders, such as Alzheimer's disease and depression.
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Affiliation(s)
- Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 07102, USA
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24
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Li C, Li T, Chen Y, Zhang C, Ning M, Qin R, Li L, Wang X, Chen L. Sex differences of the triple network model in children with autism: A resting-state fMRI investigation of effective connectivity. Autism Res 2023; 16:1693-1706. [PMID: 37565548 DOI: 10.1002/aur.2991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 07/06/2023] [Indexed: 08/12/2023]
Abstract
Autism spectrum disorder (ASD) has a pronounced male predominance, but the underlying neurobiological basis of this sex bias remains unclear. Gender incoherence (GI) theory suggests that ASD is more neurally androgynous than same-sex controls. Given its central role, altered structures and functions, and sex-dependent network differences in ASD, the triple network model, including the central executive network (CEN), default mode network (DMN), and salience network (SN), has emerged as a candidate for characterizing this sex difference. Here, we measured the sex-related effective connectivity (EC) differences within and between these three networks in 72 children with ASD (36 females, 8-14 years) and 72 typically developing controls (TCs) (36 females, 8-14 years) from 5 sites of the Autism Brain Imaging Data Exchange repositories using a 2 × 2 analysis of covariance factorial design. We also assessed brain-behavior relationships and the effects of age on EC. We found significant diagnosis-by-sex interactions on EC: females with ASD had significantly higher EC than their male counterparts within the DMN and between the SN and CEN. The interaction pattern supported the GI theory by showing that the higher EC observed in females with ASD reflected a shift towards the higher level of EC displayed in male TCs (neural masculinization), and the lower EC seen in males with ASD reflected a shift towards the lower level of EC displayed in female TCs (neural feminization). We also found significant brain-behavior correlations and significant effects of age on EC.
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Affiliation(s)
- Cuicui Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Tong Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Ying Chen
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Chunling Zhang
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Mingmin Ning
- Department of Neurology, Guangzhou Women and Children's Medical Center, China
| | - Rui Qin
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Lin Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Ximing Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Linglong Chen
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, China
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25
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Chen J, Engelhard M, Henao R, Berchuck S, Eichner B, Perrin EM, Sapiro G, Dawson G. Enhancing early autism prediction based on electronic records using clinical narratives. J Biomed Inform 2023; 144:104390. [PMID: 37182592 PMCID: PMC10526711 DOI: 10.1016/j.jbi.2023.104390] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 04/14/2023] [Accepted: 05/09/2023] [Indexed: 05/16/2023]
Abstract
Recent work has shown that predictive models can be applied to structured electronic health record (EHR) data to stratify autism likelihood from an early age (<1 year). Integrating clinical narratives (or notes) with structured data has been shown to improve prediction performance in other clinical applications, but the added predictive value of this information in early autism prediction has not yet been explored. In this study, we aimed to enhance the performance of early autism prediction by using both structured EHR data and clinical narratives. We built models based on structured data and clinical narratives separately, and then an ensemble model that integrated both sources of data. We assessed the predictive value of these models from Duke University Health System over a 14-year span to evaluate ensemble models predicting later autism diagnosis (by age 4 years) from data collected from ages 30 to 360 days. Our sample included 11,750 children above by age 3 years (385 meeting autism diagnostic criteria). The ensemble model for autism prediction showed superior performance and at age 30 days achieved 46.8% sensitivity (95% confidence interval, CI: 22.0%, 52.9%), 28.0% positive predictive value (PPV) at high (90%) specificity (CI: 2.0%, 33.1%), and AUC4 (with at least 4-year follow-up for controls) reaching 0.769 (CI: 0.715, 0.811). Prediction by 360 days achieved 44.5% sensitivity (CI: 23.6%, 62.9%), and 13.7% PPV at high (90%) specificity (CI: 9.6%, 18.9%), and AUC4 reaching 0.797 (CI: 0.746, 0.840). Results show that incorporating clinical narratives in early autism prediction achieved promising accuracy by age 30 days, outperforming models based on structured data only. Furthermore, findings suggest that additional features learned from clinician narratives might be hypothesis generating for understanding early development in autism.
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Affiliation(s)
- Junya Chen
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27705, United States.
| | - Matthew Engelhard
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27705, United States
| | - Ricardo Henao
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27705, United States
| | - Samuel Berchuck
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27705, United States
| | - Brian Eichner
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27705, United States
| | - Eliana M Perrin
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27705, United States
| | - Guillermo Sapiro
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27705, United States
| | - Geraldine Dawson
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27705, United States
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26
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Zhang L, Pini L, Corbetta M. Different MRI structural processing methods do not impact functional connectivity computation. Sci Rep 2023; 13:8589. [PMID: 37237072 DOI: 10.1038/s41598-023-34645-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 05/04/2023] [Indexed: 05/28/2023] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly popular technique. This technique can assess several features of brain connectivity, such as inter-regional temporal correlation (functional connectivity), from which graph measures of network organization can be derived. However, these measures are prone to a certain degree of variability depending on the analytical steps during preprocessing. Many studies have investigated the effect of different preprocessing steps on functional connectivity measures; however, no study investigated whether different structural reconstructions lead to different functional connectivity metrics. Here, we evaluated the impact of different structural segmentation strategies on functional connectivity outcomes. To this aim, we compared different metrics computed after two different registration strategies. The first strategy used structural information from the 3D T1-weighted image (unimodal), while the second strategy implemented a multimodal approach, where an additional registration step used the information from the T2-weighted image. The impact of these different approaches was evaluated on a sample of 58 healthy adults. As expected, different approaches led to significant differences in structural measures (i.e., cortical thickness, volume, and gyrification index), with the maximum impact on the insula cortex. However, these differences were only slightly translated to functional metrics. We reported no differences in graph measures and seed-based functional connectivity maps, but slight differences in the insula when we compared the mean functional strength for each parcel. Overall, these results suggested that functional metrics are only slightly different when using a unimodal compared to a multimodal approach, while the structural output can be significantly affected.
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Affiliation(s)
- Lu Zhang
- Padova Neuroscience Center, University of Padova, 35131, Padua, Italy
| | - Lorenzo Pini
- Padova Neuroscience Center, University of Padova, 35131, Padua, Italy
| | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padova, 35131, Padua, Italy.
- Venetian Institute of Molecular Medicine (VIMM), 35129, Padua, Italy.
- Clinica Neurologica, Department of Neuroscience, University of Padova, 35131, Padua, Italy.
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27
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Zhang J, Fang S, Yao Y, Li F, Luo Q. Parsing the heterogeneity of brain-symptom associations in autism spectrum disorder via random forest with homogeneous canonical correlation. J Affect Disord 2023; 335:36-43. [PMID: 37156272 DOI: 10.1016/j.jad.2023.04.102] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 04/16/2023] [Accepted: 04/28/2023] [Indexed: 05/10/2023]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a highly heterogeneous developmental disorder, but the neuroimaging substrates of its heterogeneity remain unknown. The difficulty lies mainly on the significant individual variability in the brain-symptom association. METHODS T1-weighted magnetic resonance imaging data from the Autism Brain Imaging Database Exchange (ABIDE) (NTDC = 1146) were used to generate a normative model to map brain structure deviations of cases (NASD = 571). Voxel-based morphometry (VBM) was used to compute gray matter volume (GMV). Singular Value Decomposition (SVD) was employed to perform dimensionality reduction. A tree-based algorithm was proposed to identify the ASD subtypes according to the pattern of brain-symptom association as assessed by a homogeneous canonical correlation. RESULTS We identified 4 ASD subtypes with distinct association patterns between residual volumes and a social symptom score. More severe the social symptom was associated with greater GMVs in both the frontoparietal regions for the subtype1 (r = 0.29-0.44) and the ventral visual pathway for the subtype3 (r = 0.19-0.23), but lower GMVs in both the right anterior cingulate cortex for the subtype4 (r = -0.25) and a few subcortical regions for the subtype2 (r = -0.31-0.20). The subtyping significantly improved the classification accuracy between cases and controls from 0.64 to 0.75 (p < 0.05, permutation test), which was also better than the accuracy of 0.68 achieved by the k-means-based subtyping (p < 0.01). LIMITATIONS Sample size limited the study due to the missing data. CONCLUSIONS These findings suggest that the heterogeneity of ASD might reflect changes in different subsystems of the social brain, especially including social attention, motivation, perceiving and evaluation.
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Affiliation(s)
- Jiajun Zhang
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, Institute of Science and Technology for Brain-Inspired Intelligence, School of Life Sciences, Fudan University, Shanghai 200433, PR China
| | - Shuanfeng Fang
- Department of Children Health Care, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou 450007, PR China
| | - Yin Yao
- Department of Computational Biology, School of Life Sciences, Fudan University, PR China
| | - Fei Li
- Developmental and Behavioral Pediatric Department & Child Primary Care Department, Ministry of Education Key Laboratory for Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, PR China
| | - Qiang Luo
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, Institute of Science and Technology for Brain-Inspired Intelligence, School of Life Sciences, Fudan University, Shanghai 200433, PR China; Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Human Phenome Institute, Fudan University, Shanghai 200032, China.
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28
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Fetcho RN, Hall BS, Estrin DJ, Walsh AP, Schuette PJ, Kaminsky J, Singh A, Roshgodal J, Bavley CC, Nadkarni V, Antigua S, Huynh TN, Grosenick L, Carthy C, Komer L, Adhikari A, Lee FS, Rajadhyaksha AM, Liston C. Regulation of social interaction in mice by a frontostriatal circuit modulated by established hierarchical relationships. Nat Commun 2023; 14:2487. [PMID: 37120443 PMCID: PMC10148889 DOI: 10.1038/s41467-023-37460-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 03/17/2023] [Indexed: 05/01/2023] Open
Abstract
Social hierarchies exert a powerful influence on behavior, but the neurobiological mechanisms that detect and regulate hierarchical interactions are not well understood, especially at the level of neural circuits. Here, we use fiber photometry and chemogenetic tools to record and manipulate the activity of nucleus accumbens-projecting cells in the ventromedial prefrontal cortex (vmPFC-NAcSh) during tube test social competitions. We show that vmPFC-NAcSh projections signal learned hierarchical relationships, and are selectively recruited by subordinate mice when they initiate effortful social dominance behavior during encounters with a dominant competitor from an established hierarchy. After repeated bouts of social defeat stress, this circuit is preferentially activated during social interactions initiated by stress resilient individuals, and plays a necessary role in supporting social approach behavior in subordinated mice. These results define a necessary role for vmPFC-NAcSh cells in the adaptive regulation of social interaction behavior based on prior hierarchical interactions.
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Affiliation(s)
- Robert N Fetcho
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program, New York, NY, USA
| | - Baila S Hall
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - David J Estrin
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Alexander P Walsh
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Peter J Schuette
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jesse Kaminsky
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Ashna Singh
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Jacob Roshgodal
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Charlotte C Bavley
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Viraj Nadkarni
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Susan Antigua
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Thu N Huynh
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Logan Grosenick
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Camille Carthy
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Lauren Komer
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Avishek Adhikari
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Francis S Lee
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Anjali M Rajadhyaksha
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
- Department of Pediatrics, Division of Pediatric Neurology, Weill Cornell Medicine, New York, NY, USA.
- Weill Cornell Autism Research Program, New York, NY, USA.
| | - Conor Liston
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
- Weill Cornell Autism Research Program, New York, NY, USA.
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29
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Savino R, Polito AN, Marsala G, Ventriglio A, Di Salvatore M, De Stefano MI, Valenzano A, Marinaccio L, Bellomo A, Cibelli G, Monda M, Monda V, Messina A, Polito R, Carotenuto M, Messina G. Agomelatine: A Potential Multitarget Compound for Neurodevelopmental Disorders. Brain Sci 2023; 13:734. [PMID: 37239206 PMCID: PMC10216109 DOI: 10.3390/brainsci13050734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/21/2023] [Accepted: 04/25/2023] [Indexed: 05/28/2023] Open
Abstract
Agomelatine (AGM) is one of the latest atypical antidepressants, prescribed exclusively for the treatment of depression in adults. AGM belongs to the pharmaceutical class of melatonin agonist and selective serotonin antagonist ("MASS"), as it acts both as a selective agonist of melatonin receptors MT1 and MT2, and as a selective antagonist of 5-HT2C/5-HT2B receptors. AGM is involved in the resynchronization of interrupted circadian rhythms, with beneficial effects on sleep patterns, while antagonism on serotonin receptors increases the availability of norepinephrine and dopamine in the prefrontal cortex, with an antidepressant and nootropic effect. The use of AGM in the pediatric population is limited by the scarcity of data. In addition, few studies and case reports have been published on the use of AGM in patients with attention deficit and hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Considering this evidence, the purpose of this review is to report the potential role of AGM in neurological developmental disorders. AGM would increase the expression of the cytoskeleton-associated protein (ARC) in the prefrontal cortex, with optimization of learning, long-term memory consolidation, and improved survival of neurons. Another important feature of AGM is the ability to modulate glutamatergic neurotransmission in regions associated with mood and cognition. With its synergistic activity a melatoninergic agonist and an antagonist of 5-HT2C, AGM acts as an antidepressant, psychostimulant, and promoter of neuronal plasticity, regulating cognitive symptoms, resynchronizing circadian rhythms in patients with autism, ADHD, anxiety, and depression. Given its good tolerability and good compliance, it could potentially be administered to adolescents and children.
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Affiliation(s)
- Rosa Savino
- Department of Woman and Child, Neuropsychiatry for Child and Adolescent Unit, General Hospital "Riuniti" of Foggia, 71122 Foggia, Italy
| | - Anna Nunzia Polito
- Department of Woman and Child, Neuropsychiatry for Child and Adolescent Unit, General Hospital "Riuniti" of Foggia, 71122 Foggia, Italy
| | | | - Antonio Ventriglio
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy
| | - Melanie Di Salvatore
- Department of Woman and Child, Neuropsychiatry for Child and Adolescent Unit, General Hospital "Riuniti" of Foggia, 71122 Foggia, Italy
| | - Maria Ida De Stefano
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy
| | - Anna Valenzano
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy
| | - Luigi Marinaccio
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy
| | - Antonello Bellomo
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy
| | - Giuseppe Cibelli
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy
| | - Marcellino Monda
- Department of Experimental Medicine, Section of Human Physiology and Unit of Dietetics and Sports Medicine, Università degli Studi della Campania "Luigi Vanvitelli", 80131 Naples, Italy
| | - Vincenzo Monda
- Department of Movement Sciences and Wellbeing, University of Naples "Parthenope", 80133 Naples, Italy
| | - Antonietta Messina
- Department of Experimental Medicine, Section of Human Physiology and Unit of Dietetics and Sports Medicine, Università degli Studi della Campania "Luigi Vanvitelli", 80131 Naples, Italy
| | - Rita Polito
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy
| | - Marco Carotenuto
- Department of Mental and Physical Health and Preventive Medicine, Università degli Studi della Campania "Luigi Vanvitelli", 80131 Naples, Italy
| | - Giovanni Messina
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy
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30
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Khandan Khadem-Reza Z, Shahram MA, Zare H. Altered resting-state functional connectivity of the brain in children with autism spectrum disorder. Radiol Phys Technol 2023; 16:284-291. [PMID: 37040021 DOI: 10.1007/s12194-023-00717-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 03/27/2023] [Accepted: 03/27/2023] [Indexed: 04/12/2023]
Abstract
Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders. Brain mapping has shown that functional brain connections are altered in autism. This study investigated the pattern of brain connection changes in autistic people compared to healthy people. This study aimed to analyze functional abnormalities within the brain due to ASD, using resting-state functional magnetic resonance imaging (fMRI). Resting-state functional magnetic resonance images of 26 individuals with ASD and 26 healthy controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. The DPARSF (data processing assistant for resting-state fMRI) toolbox was used for resting-state functional image processing, and features related to functional connections were extracted from these images. Then, the extracted features from both groups were compared using an Independent Two-Sample T Test, and the features with significant differences between the two groups were identified. Compared with healthy controls, individuals with ASD showed hyper-connectivity in the frontal lobe, anterior cingulum, parahippocampal, left precuneus, angular, caudate, superior temporal, and left pallidum, as well as hypo-connectivity in the precentral, left superior frontal, left middle orbitofrontal, right amygdala, and left posterior cingulum. Our findings show that abnormal functional connectivity exists in patients with ASD. This study makes an important advancement in our understanding of the abnormal neurocircuits causing autism.
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Affiliation(s)
- Zahra Khandan Khadem-Reza
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Razavi Khorasan, Iran
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Vakil Abad Street, Mashhad, Razavi Khorasan, Iran
| | - Mohammad Amin Shahram
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Razavi Khorasan, Iran
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Vakil Abad Street, Mashhad, Razavi Khorasan, Iran
| | - Hoda Zare
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Razavi Khorasan, Iran.
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Vakil Abad Street, Mashhad, Razavi Khorasan, Iran.
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31
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Early Identification and Intervention in Pediatric Obsessive-Compulsive Disorder. Brain Sci 2023; 13:brainsci13030399. [PMID: 36979207 PMCID: PMC10046131 DOI: 10.3390/brainsci13030399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/19/2023] [Accepted: 02/24/2023] [Indexed: 03/03/2023] Open
Abstract
Obsessive-compulsive disorder (OCD) is a psychiatric disorder characterized by persistent thoughts with subsequent repetitive behaviors. Interventions that are effective for adult OCD cannot simply be generalized to pediatric OCD, since OCD in children and adolescents usually has a different clinical presentation, etiology and course from adult OCD. Delayed and inadequate treatment is associated with a worse prognosis, making the need for early identification and intervention in pediatric OCD very urgent. In this paper, we reflected on the current constraints that make early interventions for pediatric OCD unpromoted and reviewed the approaches with potential application for early identification and early intervention in pediatric OCD, categorized by three-level prevention stages corresponding to a clinical staging model. Since the etiology of pediatric OCD is still unclear, primary prevention is most lacking, and early interventions for pediatric OCD are currently focused on the secondary prevention stage, which aims to prevent the conversion of obsessive-compulsive symptoms into full-blown OCD; tertiary prevention mostly focuses on the alleviation of mild to moderate OCD, while interventions for co-morbidities are still in their infancy. We closed by considering the important research questions on this topic.
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32
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Shayestehfar M, Nakhostin-Ansari A, Memari A, Hosseini Asl SH, Faghihi F. Risk of autism spectrum disorder in offspring with parental schizophrenia: a systematic review and meta-analysis. Nord J Psychiatry 2023; 77:127-136. [PMID: 35507890 DOI: 10.1080/08039488.2022.2070664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND The effect of parental schizophrenia on the risk of Autism Spectrum Disorders (ASD) in offspring has been evaluated in previous studies. However, to our knowledge, no systematic review and meta-analysis have assessed this association. In this study, we aimed to evaluate the risk of ASD in offspring with parental schizophrenia. METHODS The electronic databases EMBASE, PubMed, and Scopus were systematically searched. We administered the Newcastle Ottawa quality assessment scale (NOS) to assess the quality of all selected studies. Combined effect values, as well as their 95% confidence intervals (CI), were calculated. We evaluated heterogeneity using Q and I2 statistics. The publication bias was evaluated by funnel plot and Egger's regression test. In addition, a leave-one-out sensitivity analysis was performed to assess the robustness of the finding. RESULTS A total of 12 observational studies (10 cohorts and two case-control) were included. Our study found a high risk of ASD in offspring exposed to parental schizophrenia [RR = 2.38 (CI%95 2.0-2.83)]. Subgroup and sensitivity analysis confirmed the robustness of our main analysis. CONCLUSION The risk of ASD is considerably higher in offspring with parental schizophrenia. Our findings may suggest a shared pathologic pathway between schizophrenia and ASD.
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Affiliation(s)
- Monir Shayestehfar
- Neuroscience Department, School of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran Iran
| | - Amin Nakhostin-Ansari
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Amirhossein Memari
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Hossein Hosseini Asl
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.,Students' Scientific Research center, Exceptional Talents Development Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Faezeh Faghihi
- Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran
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33
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Randeniya R, Vilares I, Mattingley JB, Garrido MI. Increased functional activity, bottom-up and intrinsic effective connectivity in autism. Neuroimage Clin 2023; 37:103293. [PMID: 36527995 PMCID: PMC9791168 DOI: 10.1016/j.nicl.2022.103293] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 08/17/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
Sensory perceptual alterations such as sensory sensitivities in autism have been proposed to be caused by differences in sensory observation (Likelihood) or in forming models of the environment (Prior), which result in an increase in bottom-up information flow relative to top-down control. To investigate this conjecture, we had autistic individuals (AS) and neurotypicals (NT) perform a decision-under-uncertainty paradigm while undergoing functional magnetic resonance imaging (fMRI). There were no group differences in task performance and in Prior and Likelihood representations in brain activity. However, there were significant group differences in overall task activity, with the AS group showing significantly greater activation in the bilateral precuneus, mid-occipital gyrus, cuneus, superior frontal gyrus (SFG) and left putamen relative to the NT group. Further, when pooling the data across both groups, we found that those with higher AQ scores showed greater activity in the left cuneus and precuneus. Effective connectivity analysis using dynamic causal modelling (DCM) revealed that group differences in BOLD signals were underpinned by increased activity within sensory regions and a net increase in bottom-up connectivity from the occipital region to the precuneus and the left SFG. These findings support the hypothesis of increased bottom-up information flow in autism during sensory learning tasks.
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Affiliation(s)
- R Randeniya
- Queensland Brain Institute, The University of Queensland, Australia.
| | - I Vilares
- Department of Psychology, University of Minnesota, USA
| | - J B Mattingley
- Queensland Brain Institute, The University of Queensland, Australia; School of Psychology, The University of Queensland, Australia; Canadian Institute for Advanced Research (CIFAR), Canada; Australian Research Council Centre of Excellence for Integrative Brain Function, Australia
| | - M I Garrido
- Melbourne School of Psychological Sciences, University of Melbourne, Australia; Australian Research Council Centre of Excellence for Integrative Brain Function, Australia
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34
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Talesh Jafadideh A, Mohammadzadeh Asl B. Topological analysis of brain dynamics in autism based on graph and persistent homology. Comput Biol Med 2022; 150:106202. [PMID: 37859293 DOI: 10.1016/j.compbiomed.2022.106202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/02/2022] [Accepted: 10/09/2022] [Indexed: 11/22/2022]
Abstract
Autism spectrum disorder (ASD) is a heterogeneous disorder with a rapidly growing prevalence. In recent years, the dynamic functional connectivity (DFC) technique has been used to reveal the transient connectivity behavior of ASDs' brains by clustering connectivity matrices in different states. However, the states of DFC have not been yet studied from a topological point of view. In this paper, this study was performed using global metrics of the graph and persistent homology (PH) and resting-state functional magnetic resonance imaging (fMRI) data. The PH has been recently developed in topological data analysis and deals with persistent structures of data. The structural connectivity (SC) and static FC (SFC) were also studied to know which one of the SC, SFC, and DFC could provide more discriminative topological features when comparing ASDs with typical controls (TCs). Significant discriminative features were only found in states of DFC. Moreover, the best classification performance was offered by persistent homology-based metrics and in two out of four states. In these two states, some networks of ASDs compared to TCs were more segregated and isolated (showing the disruption of network integration in ASDs). The results of this study demonstrated that topological analysis of DFC states could offer discriminative features which were not discriminative in SFC and SC. Also, PH metrics can provide a promising perspective for studying ASD and finding candidate biomarkers.
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35
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Prany W, Patrice C, Franck D, Fabrice W, Mahdi M, Pierre D, Christian M, Jean-Marc G, Fabian G, Francis E, Jean-Marc B, Bérengère GG. EEG resting-state functional connectivity: evidence for an imbalance of external/internal information integration in autism. J Neurodev Disord 2022; 14:47. [PMID: 36030210 PMCID: PMC9419397 DOI: 10.1186/s11689-022-09456-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 08/04/2022] [Indexed: 01/12/2023] Open
Abstract
Background Autism spectrum disorder (ASD) is associated with atypical neural activity in resting state. Most of the studies have focused on abnormalities in alpha frequency as a marker of ASD dysfunctions. However, few have explored alpha synchronization within a specific interest in resting-state networks, namely the default mode network (DMN), the sensorimotor network (SMN), and the dorsal attention network (DAN). These functional connectivity analyses provide relevant insight into the neurophysiological correlates of multimodal integration in ASD. Methods Using high temporal resolution EEG, the present study investigates the functional connectivity in the alpha band within and between the DMN, SMN, and the DAN. We examined eyes-closed EEG alpha lagged phase synchronization, using standardized low-resolution brain electromagnetic tomography (sLORETA) in 29 participants with ASD and 38 developing (TD) controls (age, sex, and IQ matched). Results We observed reduced functional connectivity in the ASD group relative to TD controls, within and between the DMN, the SMN, and the DAN. We identified three hubs of dysconnectivity in ASD: the posterior cingulate cortex, the precuneus, and the medial frontal gyrus. These three regions also presented decreased current source density in the alpha band. Conclusion These results shed light on possible multimodal integration impairments affecting the communication between bottom-up and top-down information. The observed hypoconnectivity between the DMN, SMN, and DAN could also be related to difficulties in switching between externally oriented attention and internally oriented thoughts. Supplementary Information The online version contains supplementary material available at 10.1186/s11689-022-09456-8.
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Affiliation(s)
- Wantzen Prany
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.,Université de Paris, LaPsyDÉ, CNRS, F-75005, Paris, France
| | - Clochon Patrice
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Doidy Franck
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Wallois Fabrice
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France
| | - Mahmoudzadeh Mahdi
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France
| | - Desaunay Pierre
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Mille Christian
- Centre Ressources Autisme Picardie, Service de Psychopathologie Enfants et Adolescents, CHU, 4 rue Grenier et Bernard, 80000, Amiens, France
| | - Guilé Jean-Marc
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, 80025, Amiens, France.,Centre Ressources Autisme Picardie, Service de Psychopathologie Enfants et Adolescents, CHU, 4 rue Grenier et Bernard, 80000, Amiens, France
| | - Guénolé Fabian
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Eustache Francis
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Baleyte Jean-Marc
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.,Service de Psychiatrie de l'enfant et de l'adolescent, Centre Hospitalier Interuniversitaire de Créteil, 94000, Créteil, France
| | - Guillery-Girard Bérengère
- Normandie univ, UNICAEN, PSL Université Paris, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.
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36
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Luo L, Li L. Online two-way estimation and inference via linear mixed-effects models. Stat Med 2022; 41:5113-5133. [PMID: 35983945 DOI: 10.1002/sim.9557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 11/10/2022]
Abstract
In this article, we tackle the estimation and inference problem of analyzing distributed streaming data that is collected continuously over multiple data sites. We propose an online two-way approach via linear mixed-effects models. We explicitly model the site-specific effects as random-effect terms, and tackle both between-site heterogeneity and within-site correlation. We develop an online updating procedure that does not need to re-access the previous data and can efficiently update the parameter estimate, when either new data sites, or new streams of sample observations of the existing data sites, become available. We derive the non-asymptotic error bound for our proposed online estimator, and show that it is asymptotically equivalent to the offline counterpart based on all the raw data. We compare with some key alternative solutions both analytically and numerically, and demonstrate the advantages of our proposal. We further illustrate our method with two data applications.
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Affiliation(s)
- Lan Luo
- Department of Statistics and Actuarial Science, University of Iowa, Iowa City, Iowa, USA
| | - Lexin Li
- Department of Biostatistics and Epidemiology, University of California, Berkeley, Berkeley, California, USA
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37
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Jiao Z, Lai Y, Kang J, Gong W, Ma L, Jia T, Xie C, Xiang S, Cheng W, Heinz A, Desrivières S, Schumann G, Sun F, Feng J. A model-based approach to assess reproducibility for large-scale high-throughput MRI-based studies. Neuroimage 2022; 255:119166. [PMID: 35398282 DOI: 10.1016/j.neuroimage.2022.119166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 03/26/2022] [Accepted: 03/30/2022] [Indexed: 12/21/2022] Open
Abstract
Magnetic Resonance Imaging (MRI) technology has been increasingly used in neuroscience studies. Reproducibility of statistically significant findings generated by MRI-based studies, especially association studies (phenotype vs. MRI metric) and task-induced brain activation, has been recently heavily debated. However, most currently available reproducibility measures depend on thresholds for the test statistics and cannot be use to evaluate overall study reproducibility. It is also crucial to elucidate the relationship between overall study reproducibility and sample size in an experimental design. In this study, we proposed a model-based reproducibility index to quantify reproducibility which could be used in large-scale high-throughput MRI-based studies including both association studies and task-induced brain activation. We performed the model-based reproducibility assessments for a few association studies and task-induced brain activation by using several recent large sMRI/fMRI databases. For large sample size association studies between brain structure/function features and some basic physiological phenotypes (i.e. Sex, BMI), we demonstrated that the model-based reproducibility of these studies is more than 0.99. For MID task activation, similar results could be observed. Furthermore, we proposed a model-based analytical tool to evaluate minimal sample size for the purpose of achieving a desirable model-based reproducibility. Additionally, we evaluated the model-based reproducibility of gray matter volume (GMV) changes for UK Biobank (UKB) vs. Parkinson Progression Marker Initiative (PPMI) and UK Biobank (UKB) vs. Human Connectome Project (HCP). We demonstrated that both sample size and study-specific experimental factors play important roles in the model-based reproducibility assessments for different experiments. In summary, a systematic assessment of reproducibility is fundamental and important in the current large-scale high-throughput MRI-based studies.
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Affiliation(s)
- Zeyu Jiao
- Shanghai Center for Mathematical Sciences, Fudan University, 220 Handan Road, Shanghai, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, China
| | - Yinglei Lai
- School of Mathematical Sciences, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, China
| | - Jujiao Kang
- Shanghai Center for Mathematical Sciences, Fudan University, 220 Handan Road, Shanghai, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, China
| | - Weikang Gong
- Center for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Welcome Center for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Liang Ma
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, China; Center for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Center, King's College London, United Kingdom
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, China
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Sylvane Desrivières
- Center for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Center, King's College London, United Kingdom
| | - Gunter Schumann
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Center for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Center, King's College London, United Kingdom; PONS Research Group, Department of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, Berlin, Germany
| | | | - Fengzhu Sun
- Quantitative and Computational Biology Department, University of Southern California, 1050 Childs Way, Los Angeles, CA 90089, United States
| | - Jianfeng Feng
- Shanghai Center for Mathematical Sciences, Fudan University, 220 Handan Road, Shanghai, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom; School of Life Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China.
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38
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Zhao W, Voon V, Xue K, Xie C, Kang J, Lin CP, Wang J, Cheng J, Feng J. Common abnormal connectivity in first-episode and chronic schizophrenia in pre- and post-central regions: Implications for neuromodulation targeting. Prog Neuropsychopharmacol Biol Psychiatry 2022; 117:110556. [PMID: 35367293 DOI: 10.1016/j.pnpbp.2022.110556] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 03/23/2022] [Accepted: 03/27/2022] [Indexed: 11/30/2022]
Abstract
Schizophrenia is a neurodevelopmental disorder manifesting differing impairments at early onset and chronic disease stages. Brain imaging research suggests a core pathological region in patients with first-episode schizophrenia is Broca's area. With disease progression, alterations in thalamic connectivity becomes more prevalent. Understanding the common circuitry underlying pathology in these two groups might highlight a critical common network and novel targets for treatment. In this study, 937 subject samples were collected including patients with first-episode schizophrenia and those with chronic schizophrenia. We used hypothesis-based voxel-level functional connectivity analyses to calculate functional connectivity using the left Broca's area and thalamus as regions of interest in those with first-episode and chronic schizophrenia, respectively. We show for the first time that in both patients with first-episode and chronic schizophrenia the greatest functional connectivity disruption ended in the pre- and postcentral regions. At the early-onset stage, the core brain region is abnormally connected to pre- and postcentral areas responsible for mouth movement, while in the chronic stage, it expanded to a wider range of sensorimotor areas. Our findings suggest that expanding the focus on the low-order sensory-motor systems beyond high-order cognitive impairments in schizophrenia may show potential for neuromodulation treatment, given the relative accessibility of these cortical regions and their functional and structural connections to the core region at different stages of illness.
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Affiliation(s)
- Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Kangkang Xue
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders (No. 13dz2260500), Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China; Shanghai Center for Mathematical Sciences, Shanghai, China.
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39
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Talesh Jafadideh A, Mohammadzadeh Asl B. Rest-fMRI based comparison study between autism spectrum disorder and typically control using graph frequency bands. Comput Biol Med 2022; 146:105643. [DOI: 10.1016/j.compbiomed.2022.105643] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/17/2022] [Accepted: 05/14/2022] [Indexed: 01/01/2023]
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40
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Brain functional connectivities that mediate the association between childhood traumatic events, and adult mental health and cognition. EBioMedicine 2022; 79:104002. [PMID: 35472671 PMCID: PMC9058958 DOI: 10.1016/j.ebiom.2022.104002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 03/16/2022] [Accepted: 03/29/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Childhood traumatic events are risk factors for psychopathology, but large-scale studies of how childhood traumatic events relate to mental health and cognition in adulthood, and how the brain is involved, are needed. METHODS The associations between childhood traumatic events (such as abuse and neglect, and defined by the 'Childhood Trauma' questions in the UK Biobank database) and brain functional connectivity, mental health problems, and cognitive performance were investigated by a univariate correlation analysis with 19,535 participants aged 45-79 from the UK Biobank dataset. The results were replicated with 17,747 independent participants in the second release from the same dataset. FINDINGS Childhood traumatic events were significantly associated with mental health problems in adulthood including anxiety (r=0.19, p<1.0 × 10-323), depression (r=0.21, p<1.0 × 10-323), and self-harm (r=0.24, p<1.0 × 10-323), and with adult cognitive performance including fluid intelligence (r=-0.05, p=2.8 × 10-10) and prospective memory (r=-0.04, p=6.8 × 10-8). Functional connectivities of the medial and lateral temporal cortex, the precuneus, the medial orbitofrontal cortex; and the superior, middle and inferior prefrontal cortex extending back to precentral regions were negatively correlated with the childhood traumatic events (FDR corrected, p<0.01). These lower functional connectivities significantly mediated the associations between childhood traumatic events and addiction, anxiety, depression and well-being (all p<1.0 × 10-3), and cognitive performance. The association between childhood traumatic events and behavioural measures and functional connectivity were confirmed in a replication with different participants in the second release of the UK Biobank dataset. INTERPRETATION Childhood traumatic events are strongly associated with adult mental health problems mediated by brain functional connectivities in brain areas involved in executive function, emotion, face processing, and memory. This understanding may help with prevention and treatment. FUNDING Funding was provided by the National Key R&D Program of China (No. 2018YFC1312900 and No. 2019YFA0709502).
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Zhao L, Sun YK, Xue SW, Luo H, Lu XD, Zhang LH. Identifying Boys With Autism Spectrum Disorder Based on Whole-Brain Resting-State Interregional Functional Connections Using a Boruta-Based Support Vector Machine Approach. Front Neuroinform 2022; 16:761942. [PMID: 35273487 PMCID: PMC8901599 DOI: 10.3389/fninf.2022.761942] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 01/12/2022] [Indexed: 11/13/2022] Open
Abstract
An increasing number of resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used functional connections as discriminative features for machine learning to identify patients with brain diseases. However, it remains unclear which functional connections could serve as highly discriminative features to realize the classification of autism spectrum disorder (ASD). The aim of this study was to find ASD-related functional connectivity patterns and examine whether these patterns had the potential to provide neuroimaging-based information to clinically assist with the diagnosis of ASD by means of machine learning. We investigated the whole-brain interregional functional connections derived from R-fMRI. Data were acquired from 48 boys with ASD and 50 typically developing age-matched controls at NYU Langone Medical Center from the publicly available Autism Brain Imaging Data Exchange I (ABIDE I) dataset; the ASD-related functional connections identified by the Boruta algorithm were used as the features of support vector machine (SVM) to distinguish patients with ASD from typically developing controls (TDC); a permutation test was performed to assess the classification performance. Approximately, 92.9% of participants were correctly classified by a combined SVM and leave-one-out cross-validation (LOOCV) approach, wherein 95.8% of patients with ASD were correctly identified. The default mode network (DMN) exhibited a relatively high network degree and discriminative power. Eight important brain regions showed a high discriminative power, including the posterior cingulate cortex (PCC) and the ventrolateral prefrontal cortex (vlPFC). Significant correlations were found between the classification scores of several functional connections and ASD symptoms (p < 0.05). This study highlights the important role of DMN in ASD identification. Interregional functional connections might provide useful information for the clinical diagnosis of ASD.
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Affiliation(s)
- Lei Zhao
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
- Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Yun-Kai Sun
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shao-Wei Xue
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
- Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
- *Correspondence: Shao-Wei Xue
| | - Hong Luo
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
- Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Xiao-Dong Lu
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
- Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Lan-Hua Zhang
- College of Medical Information and Engineering, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai'an, China
- Lan-Hua Zhang
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42
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Li J, Zhang G, Wang J, Liu D, Wan C, Fang J, Wu D, Zhou Y, Tian T, Zhu W. Experience-dependent associations between distinct subtypes of childhood trauma and brain function and architecture. Quant Imaging Med Surg 2022; 12:1172-1185. [PMID: 35111614 DOI: 10.21037/qims-21-435] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 08/31/2021] [Indexed: 11/06/2022]
Abstract
Background Childhood trauma can alter brain-development trajectories and lead to a greater risk of psychopathology developing in adulthood. For this reason, understanding experience-dependent brain abnormalities associated with different trauma subtypes is crucial for identifying developmental processes disrupted by unfavorable early environments and for proposing early intervention measures to reduce trauma's negative effects. Methods This study used multimodal magnetic resonance imaging (MRI) to explore the neural correlates of distinct subtypes of childhood trauma. We recruited a large community sample of young adults (mean age, 24.1, SD 1.9 years) who completed a Childhood Trauma Questionnaire, were given behavioral scores, and underwent multimodal MRI. To quantify brain changes, we used functional connectivity density (FCD) mapping based on whole brain analysis, regions of interest (ROI) analysis, and morphological measurements. Experience-dependent brain abnormalities were identified by multivariable linear regression. Results We found that diverse brain regions in the FCD mapping were significantly related to 4 trauma subtypes and belonged to different cognitive components used for various behaviors. Experience-related influences on functional circuits and brain morphology were observed in extensive regions, including the sensorimotor, cingulum, accumbens, insula, and frontal-parietal areas, as well as in regions within the default mode network. Conclusions Identifying specific regions or systems may be a valid strategy for understanding the pathogenesis and development process of psychiatric disorders in people with different traumatic experiences and may facilitate better-targeted intervention strategies for maltreated children.
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Affiliation(s)
- Jia Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guiling Zhang
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dong Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Changhua Wan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jicheng Fang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Di Wu
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yiran Zhou
- Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tian Tian
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Association between parental age, brain structure, and behavioral and cognitive problems in children. Mol Psychiatry 2022; 27:967-975. [PMID: 34650205 DOI: 10.1038/s41380-021-01325-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 09/10/2021] [Accepted: 09/27/2021] [Indexed: 11/08/2022]
Abstract
OBJECTIVE To investigate the relation between parental age, and behavioral, cognitive and brain differences in the children. METHOD Data with children aged 9-11 of 8709 mothers with parental age 15-45 years were analyzed from the Adolescent Brain Cognitive Development (ABCD) study. A general linear model was used to test the associations of the parental age with brain structure, and behavioral and cognitive problems scores. RESULTS Behavioral and cognitive problems were greater in the children of the younger mothers, and were associated with lower volumes of cortical regions in the children. There was a linear correlation between the behavioral and cognitive problems scores, and the lower brain volumes (r > 0.6), which was evident when parental age was included as a stratification factor. The regions with lower volume included the anterior cingulate cortex, medial and lateral orbitofrontal cortex and amygdala, parahippocampal gyrus and hippocampus, and temporal lobe (FDR corrected p < 0.01). The lower cortical volumes and areas in the children significantly mediated the association between the parental age and the behavioral and cognitive problems in the children (all p < 10-4). The effects were large, such as the 71.4% higher depressive problems score, and 27.5% higher rule-breaking score, in the children of mothers aged 15-19 than the mothers aged 34-35. CONCLUSIONS Lower parental age is associated with behavioral problems and reduced cognitive performance in the children, and these differences are related to lower volumes and areas of some cortical regions which mediate the effects in the children. The findings are relevant to psychiatric understanding and assessment.
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Rolls ET, Deco G, Huang CC, Feng J. The Effective Connectivity of the Human Hippocampal Memory System. Cereb Cortex 2022; 32:3706-3725. [PMID: 35034120 DOI: 10.1093/cercor/bhab442] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 11/05/2021] [Accepted: 11/08/2021] [Indexed: 02/04/2023] Open
Abstract
Effective connectivity measurements in the human hippocampal memory system based on the resting-state blood oxygenation-level dependent signal were made in 172 participants in the Human Connectome Project to reveal the directionality and strength of the connectivity. A ventral "what" hippocampal stream involves the temporal lobe cortex, perirhinal and parahippocampal TF cortex, and entorhinal cortex. A dorsal "where" hippocampal stream connects parietal cortex with posterior and retrosplenial cingulate cortex, and with parahippocampal TH cortex, which, in turn, project to the presubiculum, which connects to the hippocampus. A third stream involves the orbitofrontal and ventromedial-prefrontal cortex with effective connectivity with the hippocampal, entorhinal, and perirhinal cortex. There is generally stronger forward connectivity to the hippocampus than backward. Thus separate "what," "where," and "reward" streams can converge in the hippocampus, from which back projections return to the sources. However, unlike the simple dual stream hippocampal model, there is a third stream related to reward value; there is some cross-connectivity between these systems before the hippocampus is reached; and the hippocampus has some effective connectivity with earlier stages of processing than the entorhinal cortex and presubiculum. These findings complement diffusion tractography and provide a foundation for new concepts on the operation of the human hippocampal memory system.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, UK
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Gustavo Deco
- Department of Information and Communication Technologies, Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona 08018, Spain
- Brain and Cognition, Pompeu Fabra University, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Barcelona 08010, Spain
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200433, China
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Ventromedial Thalamus-Projecting DCN Neurons Modulate Associative Sensorimotor Responses in Mice. Neurosci Bull 2022; 38:459-473. [PMID: 34989972 PMCID: PMC9106783 DOI: 10.1007/s12264-021-00810-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 09/09/2021] [Indexed: 10/19/2022] Open
Abstract
The deep cerebellar nuclei (DCN) integrate various inputs to the cerebellum and form the final cerebellar outputs critical for associative sensorimotor learning. However, the functional relevance of distinct neuronal subpopulations within the DCN remains poorly understood. Here, we examined a subpopulation of mouse DCN neurons whose axons specifically project to the ventromedial (Vm) thalamus (DCNVm neurons), and found that these neurons represent a specific subset of DCN units whose activity varies with trace eyeblink conditioning (tEBC), a classical associative sensorimotor learning task. Upon conditioning, the activity of DCNVm neurons signaled the performance of conditioned eyeblink responses (CRs). Optogenetic activation and inhibition of the DCNVm neurons in well-trained mice amplified and diminished the CRs, respectively. Chemogenetic manipulation of the DCNVm neurons had no effects on non-associative motor coordination. Furthermore, optogenetic activation of the DCNVm neurons caused rapid elevated firing activity in the cingulate cortex, a brain area critical for bridging the time gap between sensory stimuli and motor execution during tEBC. Together, our data highlights DCNVm neurons' function and delineates their kinematic parameters that modulate the strength of associative sensorimotor responses.
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Das S, Zomorrodi R, Enticott PG, Kirkovski M, Blumberger DM, Rajji TK, Desarkar P. Resting state electroencephalography microstates in autism spectrum disorder: A mini-review. Front Psychiatry 2022; 13:988939. [PMID: 36532178 PMCID: PMC9752812 DOI: 10.3389/fpsyt.2022.988939] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 11/09/2022] [Indexed: 12/04/2022] Open
Abstract
Atypical spatial organization and temporal characteristics, found via resting state electroencephalography (EEG) microstate analysis, have been associated with psychiatric disorders but these temporal and spatial parameters are less known in autism spectrum disorder (ASD). EEG microstates reflect a short time period of stable scalp potential topography. These canonical microstates (i.e., A, B, C, and D) and more are identified by their unique topographic map, mean duration, fraction of time covered, frequency of occurrence and global explained variance percentage; a measure of how well topographical maps represent EEG data. We reviewed the current literature for resting state microstate analysis in ASD and identified eight publications. This current review indicates there is significant alterations in microstate parameters in ASD populations as compared to typically developing (TD) populations. Microstate parameters were also found to change in relation to specific cognitive processes. However, as microstate parameters are found to be changed by cognitive states, the differently acquired data (e.g., eyes closed or open) resting state EEG are likely to produce disparate results. We also review the current understanding of EEG sources of microstates and the underlying brain networks.
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Affiliation(s)
- Sushmit Das
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Reza Zomorrodi
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Melissa Kirkovski
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia.,Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia
| | - Daniel M Blumberger
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Pushpal Desarkar
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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Jia H, Wu X, Wu Z, Wang E. Aberrant dynamic minimal spanning tree parameters within default mode network in patients with autism spectrum disorder. Front Psychiatry 2022; 13:860348. [PMID: 36186871 PMCID: PMC9524021 DOI: 10.3389/fpsyt.2022.860348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
The altered functional connectivity (FC) level and its temporal characteristics within certain cortical networks, such as the default mode network (DMN), could provide a possible explanatory framework for Autism spectrum disorder (ASD). In the current study, we hypothesized that the topographical organization along with its temporal dynamics of the autistic brain measured by temporal mean and variance of complex network measures, respectively, were significantly altered, which may further explain the autistic symptom severity in patients with ASD. To validate these hypotheses, the precise FCs between DMN regions at each time point were calculated using the resting-state functional magnetic resonance imaging (fMRI) datasets from the Autism Brain Imaging Data Exchange (ABIDE) project. Then, the minimal spanning tree (MST) technique was applied to construct a time-varying complex network of DMN. By analyzing the temporal mean and variance of MST parameters and their relationship with autistic symptom severity, we found that in persons with ASD, the information exchange efficiencies between cortical regions within DMN were significantly lower and more volatile compared with those in typical developing participants. Moreover, these alterations within DMN were closely associated with the autistic symptom severity of the ASD group.
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Affiliation(s)
- Huibin Jia
- Institute of Psychology and Behavior, Henan University, Kaifeng, China.,School of Psychology, Henan University, Kaifeng, China
| | - Xiangci Wu
- Institute of Psychology and Behavior, Henan University, Kaifeng, China.,School of Psychology, Henan University, Kaifeng, China
| | - Zhiyu Wu
- Huaxian People's Hospital of Henan Province, Anyang, China
| | - Enguo Wang
- Institute of Psychology and Behavior, Henan University, Kaifeng, China.,School of Psychology, Henan University, Kaifeng, China
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Li D, Liu R, Meng L, Xiong P, Ren H, Zhang L, Gao Y. Abnormal Ventral Somatomotor Network Homogeneity in Patients With Temporal Lobe Epilepsy. Front Psychiatry 2022; 13:877956. [PMID: 35782421 PMCID: PMC9247252 DOI: 10.3389/fpsyt.2022.877956] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 05/16/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Abnormalities of functional connectivity in the somatomotor network have been thought to play an essential role in the pathophysiology of epilepsy. However, there has been no network homogeneity (NH) study about the ventral somatomotor network (VSN) in patients with temporal lobe epilepsy (TLE). Therefore, we explored the NH of the VSN in TLE patients in this study. METHODS The sample included 52 patients with left temporal lobe epilepsy, 83 patients with right temporal lobe epilepsy, and 68 healthy controls. The NH method was utilized to analyze the resting-state functional magnetic resonance imaging data. RESULTS Compared to the controls, rTLE patients had significantly higher NH in the bilateral postcentral gyrus, and significantly lower NH in the bilateral Rolandic operculum and the right superior temporal gyrus (STG). The NH values of the left postcentral gyrus were significantly higher in lTLE patients than in the healthy controls, and lTLE patients had lower NH in the right Rolandic operculum. The altered NH in the postcentral gyrus was negatively correlated with the illness duration, and the decreased NH in the left Rolandic operculum was negatively correlated with the executive control reaction time (ECRT). CONCLUSION Our findings suggest that altered NH of the postcentral gyrus, Rolandic operculum and STG might be associated with the pathophysiology of TLE, and thus, highlight the contribution of the VSN to the pathophysiology of TLE.
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Affiliation(s)
- Dongbin Li
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,First Department of Neurology and Neuroscience Center, Heilongjiang Provincial Hospital, Harbin, China
| | - Ruoshi Liu
- Department of Neurology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Lili Meng
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, China.,Department of Sleep, Wuhan Hospital for Psychotherapy, Wuhan, China
| | - Pingan Xiong
- Department of Taihe Hospital Reproductive Medicine Center Affiliated To Hubei University of Medicine, Shiyan, China
| | - Hongwei Ren
- Department of Medical Imaging, Tianyou Hospital Affiliated To Wuhan University of Science and Technology, Wuhan, China
| | - Liming Zhang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yujun Gao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
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Zhu S, Zhang X, Zhou M, Kendrick KM, Zhao W. Therapeutic applications of transcutaneous auricular vagus nerve stimulation with potential for application in neurodevelopmental or other pediatric disorders. Front Endocrinol (Lausanne) 2022; 13:1000758. [PMID: 36313768 PMCID: PMC9596914 DOI: 10.3389/fendo.2022.1000758] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 09/27/2022] [Indexed: 11/13/2022] Open
Abstract
Non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) as a newly developed technique involves stimulating the cutaneous receptive field formed by the auricular branch of the vagus nerve in the outer ear, with resulting activation of vagal connections to central and peripheral nervous systems. Increasing evidence indicates that maladaptive neural plasticity may underlie the pathology of several pediatric neurodevelopmental and psychiatric disorders, such as autism spectrum disorder, attention deficit hyperactivity disorder, disruptive behavioral disorder and stress-related disorder. Vagal stimulation may therefore provide a useful intervention for treating maladaptive neural plasticity. In the current review we summarize the current literature primarily on therapeutic use in adults and discuss the prospects of applying taVNS as a therapeutic intervention in specific pediatric neurodevelopmental and other psychiatric disorders. Furthermore, we also briefly discuss factors that would help optimize taVNS protocols in future clinical applications. We conclude from these initial findings that taVNS may be a promising alternative treatment for pediatric disorders which do not respond to other interventions.
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Affiliation(s)
- Siyu Zhu
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaolu Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Menghan Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Keith M. Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Weihua Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Institute of Electronic and Information Engineering of University of Electronic Science and Technology of China (UESTC) in Guangdong, Dongguan, China
- *Correspondence: Weihua Zhao,
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Reardon AM, Li K, Hu XP. Improving Between-Group Effect Size for Multi-Site Functional Connectivity Data via Site-Wise De-Meaning. Front Comput Neurosci 2021; 15:762781. [PMID: 34924984 PMCID: PMC8674307 DOI: 10.3389/fncom.2021.762781] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 11/04/2021] [Indexed: 11/18/2022] Open
Abstract
Background: Multi-site functional MRI (fMRI) databases are becoming increasingly prevalent in the study of neurodevelopmental and psychiatric disorders. However, multi-site databases are known to introduce site effects that may confound neurobiological and measures such as functional connectivity (FC). Although studies have been conducted to mitigate site effects, these methods often result in reduced effect size in FC comparisons between controls and patients. Methods: We present a site-wise de-meaning (SWD) strategy in multi-site FC analysis and compare its performance with two common site-effect mitigation methods, i.e., generalized linear model (GLM) and Combining Batches (ComBat) Harmonization. For SWD, after FC was calculated and Fisher z-transformed, the site-wise FC mean was removed from each subject before group-level statistical analysis. The above methods were tested on two multi-site psychiatric consortiums [Autism Brain Imaging Data Exchange (ABIDE) and Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP)]. Preservation of consistent FC alterations in patients were evaluated for each method through the effect sizes (Hedge’s g) of patients vs. controls. Results: For the B-SNIP dataset, SWD improved the effect size between schizophrenic and control subjects by 4.5–7.9%, while GLM and ComBat decreased the effect size by 22.5–42.6%. For the ABIDE dataset, SWD improved the effect size between autistic and control subjects by 2.9–5.3%, while GLM and ComBat decreased the effect size by up to 11.4%. Conclusion: Compared to the original data and commonly used methods, the SWD method demonstrated superior performance in preserving the effect size in FC features associated with disorders.
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Affiliation(s)
- Alexandra M Reardon
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States
| | - Kaiming Li
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States
| | - Xiaoping P Hu
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States.,Center for Advanced Neuroimaging, University of California, Riverside, Riverside, CA, United States
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