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Poortman SR, Barendse ME, Setiaman N, van den Heuvel MP, de Lange SC, Hillegers MH, van Haren NE. Age Trajectories of the Structural Connectome in Child and Adolescent Offspring of Individuals With Bipolar Disorder or Schizophrenia. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100336. [PMID: 39040431 PMCID: PMC11260845 DOI: 10.1016/j.bpsgos.2024.100336] [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: 12/22/2023] [Revised: 04/08/2024] [Accepted: 05/09/2024] [Indexed: 07/24/2024] Open
Abstract
Background Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at elevated risk of developing psychiatric illness owing to both genetic predisposition and increased burden of environmental stress. Emerging evidence indicates a disruption of brain network connectivity in young offspring of patients with bipolar disorder and schizophrenia, but the age trajectories of these brain networks in this high-familial-risk population remain to be elucidated. Methods A total of 271 T1-weighted and diffusion-weighted scans were obtained from 174 offspring of at least 1 parent diagnosed with bipolar disorder (n = 74) or schizophrenia (n = 51) and offspring of parents without severe mental illness (n = 49). The age range was 8 to 23 years; 97 offspring underwent 2 scans. Anatomical brain networks were reconstructed into structural connectivity matrices. Network analysis was performed to investigate anatomical brain connectivity. Results Offspring of parents with schizophrenia had differential trajectories of connectivity strength and clustering compared with offspring of parents with bipolar disorder and parents without severe mental illness, of global efficiency compared with offspring of parents without severe mental illness, and of local connectivity compared with offspring of parents with bipolar disorder. Conclusions The findings of this study suggest that familial high risk of schizophrenia is related to deviations in age trajectories of global structural connectome properties and local connectivity strength.
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Affiliation(s)
- Simon R. Poortman
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
| | - Marjolein E.A. Barendse
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
| | - Nikita Setiaman
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, the Netherlands
| | - Martijn P. van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Department of Child Psychiatry, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Siemon C. de Lange
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Manon H.J. Hillegers
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, the Netherlands
| | - Neeltje E.M. van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, the Netherlands
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Del Mauro G, Li Y, Wang Z. Global brain connectivity: Test-retest stability and association with biological and neurocognitive variables. J Neurosci Methods 2024; 409:110205. [PMID: 38914376 DOI: 10.1016/j.jneumeth.2024.110205] [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: 01/08/2024] [Revised: 06/03/2024] [Accepted: 06/21/2024] [Indexed: 06/26/2024]
Abstract
BACKGROUND Global brain connectivity (GBC) enables measuring brain regions' functional connectivity strength at rest by computing the average correlation between each brain voxel's time-series and that of all other voxels. NEW METHOD We used resting-state fMRI (rs-fMRI) data of young adult participants from the Human Connectome Project (HCP) dataset to explore the test-retest stability of GBC, the brain regions with higher or lower GBC, as well as the associations of this measure with age, sex, and fluid intelligence. GBC was computed by considering separately the positive and negative correlation coefficients (positive GBC and negative GBC). RESULTS Test-retest stability was higher for positive compared to negative GBC. Areas with higher GBC were located in the default mode network, insula, and visual areas, while regions with lower GBC were in subcortical regions, temporal cortex, and cerebellum. Higher age was related to global reduction of positive GBC. Males displayed higher positive GBC in the whole brain. Fluid intelligence was associated to increased positive GBC in fronto-parietal, occipital and temporal regions. COMPARISON WITH EXISTING METHOD Compared to previous works, this study adopted a larger sample size and tested GBC stability using data from different rs-fMRI sessions. Moreover, these associations were examined by testing positive and negative GBC separately. CONCLUSIONS Lower stability for negative compared to positive GBC suggests that negative correlations may reflect less stable couplings between brain regions. Our findings indicate a greater importance of positive compared to negative GBC for the associations of functional connectivity strength with biological and neurocognitive variables.
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Affiliation(s)
- Gianpaolo Del Mauro
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 670 W Baltimore St, HSF III, Baltimore, MD 21202, United States
| | - Yiran Li
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 670 W Baltimore St, HSF III, Baltimore, MD 21202, United States
| | - Ze Wang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 670 W Baltimore St, HSF III, Baltimore, MD 21202, United States.
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3
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Kavčič A, Borko DK, Kodrič J, Georgiev D, Demšar J, Soltirovska-Šalamon A. EEG alpha band functional brain network correlates of cognitive performance in children after perinatal stroke. Neuroimage 2024; 297:120743. [PMID: 39067554 DOI: 10.1016/j.neuroimage.2024.120743] [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: 04/06/2024] [Revised: 07/08/2024] [Accepted: 07/17/2024] [Indexed: 07/30/2024] Open
Abstract
Mechanisms underlying cognitive impairment after perinatal stroke could be explained through brain network alterations. With aim to explore this connection, we conducted a matched test-control study to find a correlation between functional brain network properties and cognitive functions in children after perinatal stroke. First, we analyzed resting-state functional connectomes in the alpha frequency band from a 64-channel resting state EEG in 24 children with a history of perinatal stroke (12 with neonatal arterial ischemic stroke and 12 with neonatal hemorrhagic stroke) and compared them to the functional connectomes of 24 healthy controls. Next, all participants underwent cognitive evaluation. We analyzed the differences in functional brain network properties and cognitive abilities between groups and studied the correlation between network characteristics and specific cognitive functions. Functional brain networks after perinatal stroke had lower modularity, higher clustering coefficient, higher interhemispheric strength, higher characteristic path length and higher small world index. Modularity correlated positively with the IQ and processing speed, while clustering coefficient correlated negatively with IQ. Graph metrics, reflecting network segregation (clustering coefficient and small world index) correlated positively with a tendency to impulsive decision making, which also correlated positively with graph metrics, reflecting stronger functional connectivity (characteristic path length and interhemispheric strength). Our study suggests that specific cognitive functions correlate with different brain network properties and that functional network characteristics after perinatal stroke reflect poorer cognitive functioning.
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Affiliation(s)
- Alja Kavčič
- Department for Neonatology, University Children's Hospital, University Medical Center Ljubljana, Bohoričeva 20, 1000 Ljubljana, Slovenia; Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia
| | - Daša Kocjančič Borko
- University Children's Hospital, University Medical Center Ljubljana, Bohoričeva 20, 1000 Ljubljana, Slovenia
| | - Jana Kodrič
- University Children's Hospital, University Medical Center Ljubljana, Bohoričeva 20, 1000 Ljubljana, Slovenia
| | - Dejan Georgiev
- Department for Neurology, University Medical Center Ljubljana, Zaloška cesta 2, 1000 Ljubljana, Slovenia; Faculty of Computer and Information Sciences, University of Ljubljana, Večna pot 113, 1000 Ljubljana, Slovenia
| | - Jure Demšar
- Faculty of Computer and Information Sciences, University of Ljubljana, Večna pot 113, 1000 Ljubljana, Slovenia; Department of Psychology, Faculty of Arts, University of Ljubljana, Aškerčeva cesta 2, 1000 Ljubljana, Slovenia
| | - Aneta Soltirovska-Šalamon
- Department for Neonatology, University Children's Hospital, University Medical Center Ljubljana, Bohoričeva 20, 1000 Ljubljana, Slovenia; Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia.
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4
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Dong K, Zhang L, Zhong Y, Xu T, Zhao Y, Chen S, Mahmoud SS, Fang Q. Meso-scale reorganization of local-global brain networks under mild sedation of propofol anesthesia. Neuroimage 2024; 297:120744. [PMID: 39033791 DOI: 10.1016/j.neuroimage.2024.120744] [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: 05/16/2024] [Revised: 06/30/2024] [Accepted: 07/18/2024] [Indexed: 07/23/2024] Open
Abstract
The fragmentation of the functional brain network has been identified through the functional connectivity (FC) analysis in studies investigating anesthesia-induced loss of consciousness (LOC). However, it remains unclear whether mild sedation of anesthesia can cause similar effects. This paper aims to explore the changes in local-global brain network topology during mild anesthesia, to better understand the macroscopic neural mechanism underlying anesthesia sedation. We analyzed high-density EEG from 20 participants undergoing mild and moderate sedation of propofol anesthesia. By employing a local-global brain parcellation in EEG source analysis, we established binary functional brain networks for each participant. Furthermore, we investigated the global-scale properties of brain networks by estimating global efficiency and modularity, and examined the changes in meso-scale properties of brain networks by quantifying the distribution of high-degree and high-betweenness hubs and their corresponding rich-club coefficients. It is evident from the results that the mild sedation of anesthesia does not cause a significant change in the global-scale properties of brain networks. However, network components centered on SomMot L show a significant decrease, while those centered on Default L, Vis L and Limbic L exhibit a significant increase during the transition from wakefulness to mild sedation (p<0.05). Compared to the baseline state, mild sedation almost doubled the number of high-degree hubs in Vis L, DorsAttn L, Limbic L, Cont L, and reduced by half the number of high-degree hubs in SomMot R, DorsAttn R, SalVentAttn R. Further, mild sedation almost doubled the number of high-betweenness hubs in Vis L, Vis R, Limbic R, Cont R, and reduced by half the number of high-betweenness hubs in SomMot L, SalVentAttn L, Default L, and SomMot R. Our results indicate that mild anesthesia cannot affect the global integration and segregation of brain networks, but influence meso-scale function for integrating different resting-state systems involved in various segregation processes. Our findings suggest that the meso-scale brain network reorganization, situated between global integration and local segregation, could reflect the autonomic compensation of the brain for drug effects. As a direct response and adjustment of the brain network system to drug administration, this spontaneous reorganization of the brain network aims at maintaining consciousness in the case of sedation.
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Affiliation(s)
- Kangli Dong
- Department of Biomedical Engineering, College of Engineering, Shantou University, Shantou 515063, Guangdong, China.
| | - Lu Zhang
- Department of Rehabilitation, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310027, Zhejiang, China.
| | - Yuming Zhong
- Department of Biomedical Engineering, College of Engineering, Shantou University, Shantou 515063, Guangdong, China.
| | - Tao Xu
- Department of Biomedical Engineering, College of Engineering, Shantou University, Shantou 515063, Guangdong, China.
| | - Yue Zhao
- Department of Urology, Xiang'an Hospital of Xiamen University, Xiamen University, Xiamen 361102, Fujian, China.
| | - Siya Chen
- Department of Computer Science, City University of Hong Kong, Hong Kong 999077, Hong Kong, China.
| | - Seedahmed S Mahmoud
- Department of Biomedical Engineering, College of Engineering, Shantou University, Shantou 515063, Guangdong, China.
| | - Qiang Fang
- Department of Biomedical Engineering, College of Engineering, Shantou University, Shantou 515063, Guangdong, China.
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Nakajima R, Osada T, Kinoshita M, Ogawa A, Okita H, Konishi S, Nakada M. More widespread functionality of posterior language area in patients with brain tumors. Hum Brain Mapp 2024; 45:e26801. [PMID: 39087903 PMCID: PMC11293139 DOI: 10.1002/hbm.26801] [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: 02/29/2024] [Revised: 07/11/2024] [Accepted: 07/15/2024] [Indexed: 08/02/2024] Open
Abstract
Damage to the posterior language area (PLA), or Wernicke's area causes cortical reorganization in the corresponding regions of the contralateral hemisphere. However, the details of reorganization within the ipsilateral hemisphere are not fully understood. In this context, direct electrical stimulation during awake surgery can provide valuable opportunities to investigate neuromodulation of the human brain in vivo, which is difficult through the non-invasive approaches. Thus, in this study, we aimed to investigate the characteristics of the cortical reorganization of the PLA within the ipsilateral hemisphere. Sixty-two patients with left hemispheric gliomas were divided into groups depending on whether the lesion extended to the PLA. All patients underwent direct cortical stimulation with a picture-naming task. We further performed functional connectivity analyses using resting-state functional magnetic resonance imaging (MRI) in a subset of patients and calculated betweenness centrality, an index of the network importance of brain areas. During direct cortical stimulation, the regions showing positive (impaired) responses in the non-PLA group were localized mainly in the posterior superior temporal gyrus (pSTG), whereas those in the PLA group were widely distributed from the pSTG to the posterior supramarginal gyrus (pSMG). Notably, the percentage of positive responses in the pSMG was significantly higher in the PLA group (47%) than in the non-PLA group (8%). In network analyses of functional connectivity, the pSMG was identified as a hub region with high betweenness centrality in both the groups. These findings suggest that the language area can spread beyond the PLA to the pSMG, a hub region, in patients with lesion progression to the pSTG. The change in the pattern of the language area may be a compensatory mechanism to maintain efficient brain networks.
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Affiliation(s)
- Riho Nakajima
- Department of Occupational Therapy, Faculty of Health Science, Institute of Medical, Pharmaceutical and Health SciencesKanazawa UniversityKanazawaJapan
| | - Takahiro Osada
- Department of NeurophysiologyJuntendo University School of MedicineTokyoJapan
| | - Masashi Kinoshita
- Department of Neurosurgery, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health SciencesKanazawa UniversityKanazawaJapan
| | - Akitoshi Ogawa
- Department of NeurophysiologyJuntendo University School of MedicineTokyoJapan
| | - Hirokazu Okita
- Department of Physical Medicine and RehabilitationKanazawa University HospitalKanazawaJapan
| | - Seiki Konishi
- Department of NeurophysiologyJuntendo University School of MedicineTokyoJapan
| | - Mitsutoshi Nakada
- Department of Neurosurgery, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health SciencesKanazawa UniversityKanazawaJapan
- Sapiens Life SciencesEvolution and Medicine Research CenterKanazawa UniversityKanazawaJapan
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Fukushima M, Leibnitz K. Effects of packetization on communication dynamics in brain networks. Netw Neurosci 2024; 8:418-436. [PMID: 38952819 PMCID: PMC11142457 DOI: 10.1162/netn_a_00360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/18/2024] [Indexed: 07/03/2024] Open
Abstract
Computational studies in network neuroscience build models of communication dynamics in the connectome that help us understand the structure-function relationships of the brain. In these models, the dynamics of cortical signal transmission in brain networks are approximated with simple propagation strategies such as random walks and shortest path routing. Furthermore, the signal transmission dynamics in brain networks can be associated with the switching architectures of engineered communication systems (e.g., message switching and packet switching). However, it has been unclear how propagation strategies and switching architectures are related in models of brain network communication. Here, we investigate the effects of the difference between packet switching and message switching (i.e., whether signals are packetized or not) on the transmission completion time of propagation strategies when simulating signal propagation in mammalian brain networks. The results show that packetization in the connectome with hubs increases the time of the random walk strategy and does not change that of the shortest path strategy, but decreases that of more plausible strategies for brain networks that balance between communication speed and information requirements. This finding suggests an advantage of packet-switched communication in the connectome and provides new insights into modeling the communication dynamics in brain networks.
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Affiliation(s)
- Makoto Fukushima
- Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, Japan
| | - Kenji Leibnitz
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
- Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
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7
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Bardella G, Giuffrida V, Giarrocco F, Brunamonti E, Pani P, Ferraina S. Response inhibition in premotor cortex corresponds to a complex reshuffle of the mesoscopic information network. Netw Neurosci 2024; 8:597-622. [PMID: 38952814 PMCID: PMC11168728 DOI: 10.1162/netn_a_00365] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 01/18/2024] [Indexed: 07/03/2024] Open
Abstract
Recent studies have explored functional and effective neural networks in animal models; however, the dynamics of information propagation among functional modules under cognitive control remain largely unknown. Here, we addressed the issue using transfer entropy and graph theory methods on mesoscopic neural activities recorded in the dorsal premotor cortex of rhesus monkeys. We focused our study on the decision time of a Stop-signal task, looking for patterns in the network configuration that could influence motor plan maturation when the Stop signal is provided. When comparing trials with successful inhibition to those with generated movement, the nodes of the network resulted organized into four clusters, hierarchically arranged, and distinctly involved in information transfer. Interestingly, the hierarchies and the strength of information transmission between clusters varied throughout the task, distinguishing between generated movements and canceled ones and corresponding to measurable levels of network complexity. Our results suggest a putative mechanism for motor inhibition in premotor cortex: a topological reshuffle of the information exchanged among ensembles of neurons.
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Affiliation(s)
- Giampiero Bardella
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Valentina Giuffrida
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Franco Giarrocco
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Emiliano Brunamonti
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Pierpaolo Pani
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Stefano Ferraina
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
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8
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Yu P, Dong R, Wang X, Tang Y, Liu Y, Wang C, Zhao L. Neuroimaging of motor recovery after ischemic stroke - functional reorganization of motor network. Neuroimage Clin 2024; 43:103636. [PMID: 38950504 PMCID: PMC11267109 DOI: 10.1016/j.nicl.2024.103636] [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: 03/10/2024] [Revised: 06/01/2024] [Accepted: 06/27/2024] [Indexed: 07/03/2024]
Abstract
The long-term motor outcome of acute stroke patients may be correlated to the reorganization of brain motor network. Abundant neuroimaging studies contribute to understand the pathological changes and recovery of motor networks after stroke. In this review, we summarized how current neuroimaging studies have increased understanding of reorganization and plasticity in post stroke motor recovery. Firstly, we discussed the changes in the motor network over time during the motor-activation and resting states, as well as the overall functional integration trend of the motor network. These studies indicate that the motor network undergoes dynamic bilateral hemispheric functional reorganization, as well as a trend towards network randomization. In the second part, we summarized the current study progress in the application of neuroimaging technology to early predict the post-stroke motor outcome. In the third part, we discuss the neuroimaging techniques commonly used in the post-stroke recovery. These methods provide direct or indirect visualization patterns to understand the neural mechanisms of post-stroke motor recovery, opening up new avenues for studying spontaneous and treatment-induced recovery and plasticity after stroke.
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Affiliation(s)
- Pei Yu
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Ruoyu Dong
- Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, China
| | - Xiao Wang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yuqi Tang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yaning Liu
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Can Wang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Ling Zhao
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
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9
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Pailthorpe BA. Network analysis of marmoset cortical connections reveals pFC and sensory clusters. Front Neuroanat 2024; 18:1403170. [PMID: 38933918 PMCID: PMC11199858 DOI: 10.3389/fnana.2024.1403170] [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: 03/19/2024] [Accepted: 05/10/2024] [Indexed: 06/28/2024] Open
Abstract
A new analysis is presented of the retrograde tracer measurements of connections between anatomical areas of the marmoset cortex. The original normalisation of raw data yields the fractional link weight measure, FLNe. That is re-examined to consider other possible measures that reveal the underlying in link weights. Predictions arising from both are used to examine network modules and hubs. With inclusion of the in weights the InfoMap algorithm identifies eight structural modules in marmoset cortex. In and out hubs and major connector nodes are identified using module assignment and participation coefficients. Time evolving network tracing around the major hubs reveals medium sized clusters in pFC, temporal, auditory and visual areas; the most tightly coupled and significant of which is in the pFC. A complementary viewpoint is provided by examining the highest traffic links in the cortical network, and reveals parallel sensory flows to pFC and via association areas to frontal areas.
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Affiliation(s)
- Bernard A. Pailthorpe
- Brain Dynamics Group, School of Physics, The University of Sydney, Sydney, NSW, Australia
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Sheppard PAS, Oomen CA, Bussey TJ, Saksida LM. The Granular Retrosplenial Cortex Is Necessary in Male Rats for Object-Location Associative Learning and Memory, But Not Spatial Working Memory or Visual Discrimination and Reversal, in the Touchscreen Operant Chamber. eNeuro 2024; 11:ENEURO.0120-24.2024. [PMID: 38844347 PMCID: PMC11208985 DOI: 10.1523/eneuro.0120-24.2024] [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: 03/18/2024] [Revised: 05/28/2024] [Accepted: 05/30/2024] [Indexed: 06/20/2024] Open
Abstract
The retrosplenial cortex (RSC) is a hub of diverse afferent and efferent projections thought to be involved in associative learning. RSC shows early pathology in mild cognitive impairment and Alzheimer's disease (AD), which impairs associative learning. To understand and develop therapies for diseases such as AD, animal models are essential. Given the importance of human RSC in object-location associative learning and the success of object-location associative paradigms in human studies and in the clinic, it would be of considerable value to establish a translational model of object-location learning for the rodent. For this reason, we sought to test the role of RSC in object-location learning in male rats using the object-location paired-associates learning (PAL) touchscreen task. First, increased cFos immunoreactivity was observed in granular RSC following PAL training when compared with extended pretraining controls. Following this, RSC lesions following PAL acquisition were used to explore the necessity of the RSC in object-location associative learning and memory and two tasks involving only one modality: trial-unique nonmatching-to-location for spatial working memory and pairwise visual discrimination/reversal. RSC lesions impaired both memory for learned paired-associates and learning of new object-location associations but did not affect performance in either the spatial or visual single-modality tasks. These findings provide evidence that RSC is necessary for object-location learning and less so for learning and memory involving the individual modalities therein.
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Affiliation(s)
- Paul A S Sheppard
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - Charlotte A Oomen
- Department of Experimental Psychology, University of Cambridge, Cambridge CB2 1TN, United Kingdom
- MRC and Wellcome Trust Behavioural and Clinical Neurosciences Institute, University of Cambridge, Cambridge CB2 1TN, United Kingdom
| | - Timothy J Bussey
- Department of Experimental Psychology, University of Cambridge, Cambridge CB2 1TN, United Kingdom
- MRC and Wellcome Trust Behavioural and Clinical Neurosciences Institute, University of Cambridge, Cambridge CB2 1TN, United Kingdom
| | - Lisa M Saksida
- Department of Experimental Psychology, University of Cambridge, Cambridge CB2 1TN, United Kingdom
- MRC and Wellcome Trust Behavioural and Clinical Neurosciences Institute, University of Cambridge, Cambridge CB2 1TN, United Kingdom
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Li J, Qin Y, Zhong Z, Meng L, Huang L, Li B. Pain experience reduces social avoidance to others in pain: a c-Fos-based functional connectivity network study in mice. Cereb Cortex 2024; 34:bhae207. [PMID: 38798004 DOI: 10.1093/cercor/bhae207] [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: 10/27/2023] [Revised: 04/24/2024] [Accepted: 04/25/2024] [Indexed: 05/29/2024] Open
Abstract
Pain experience increases individuals' perception and contagion of others' pain, but whether pain experience affects individuals' affiliative or antagonistic responses to others' pain is largely unknown. Additionally, the neural mechanisms underlying how pain experience modulates individuals' responses to others' pain remain unclear. In this study, we explored the effects of pain experience on individuals' responses to others' pain and the underlying neural mechanisms. By comparing locomotion, social, exploration, stereotyped, and anxiety-like behaviors of mice without any pain experience (naïve observers) and mice with a similar pain experience (experienced observers) when they observed the pain-free demonstrator with intraperitoneal injection of normal saline and the painful demonstrator with intraperitoneal injection of acetic acid, we found that pain experience of the observers led to decreased social avoidance to the painful demonstrator. Through whole-brain c-Fos quantification, we discovered that pain experience altered neuronal activity and enhanced functional connectivity in the mouse brain. The analysis of complex network and graph theory exhibited that functional connectivity networks and activated hub regions were altered by pain experience. Together, these findings reveal that neuronal activity and functional connectivity networks are involved in the modulation of individuals' responses to others' pain by pain experience.
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Affiliation(s)
- Jiali Li
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Neuroscience Program, Zhongshan School of Medicine and the Fifth Affiliated Hospital, Sun Yat-sen University, 74 Zhongshan Second Road, Yuexiu District, 510080 Guangzhou, China
| | - Yuxin Qin
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Neuroscience Program, Zhongshan School of Medicine and the Fifth Affiliated Hospital, Sun Yat-sen University, 74 Zhongshan Second Road, Yuexiu District, 510080 Guangzhou, China
| | - Zifeng Zhong
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Neuroscience Program, Zhongshan School of Medicine and the Fifth Affiliated Hospital, Sun Yat-sen University, 74 Zhongshan Second Road, Yuexiu District, 510080 Guangzhou, China
| | - Linjie Meng
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Neuroscience Program, Zhongshan School of Medicine and the Fifth Affiliated Hospital, Sun Yat-sen University, 74 Zhongshan Second Road, Yuexiu District, 510080 Guangzhou, China
| | - Lianyan Huang
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Neuroscience Program, Zhongshan School of Medicine and the Fifth Affiliated Hospital, Sun Yat-sen University, 74 Zhongshan Second Road, Yuexiu District, 510080 Guangzhou, China
| | - Boxing Li
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Neuroscience Program, Zhongshan School of Medicine and the Fifth Affiliated Hospital, Sun Yat-sen University, 74 Zhongshan Second Road, Yuexiu District, 510080 Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, 74 Zhongshan Second Road, Yuexiu District, 510080 Guangzhou, China
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12
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Stock M, Popp N, Fiorentino J, Scialdone A. Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data. Bioinformatics 2024; 40:btae267. [PMID: 38627250 PMCID: PMC11096270 DOI: 10.1093/bioinformatics/btae267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 02/28/2024] [Accepted: 04/16/2024] [Indexed: 05/18/2024] Open
Abstract
MOTIVATION In recent years, many algorithms for inferring gene regulatory networks from single-cell transcriptomic data have been published. Several studies have evaluated their accuracy in estimating the presence of an interaction between pairs of genes. However, these benchmarking analyses do not quantify the algorithms' ability to capture structural properties of networks, which are fundamental, e.g., for studying the robustness of a gene network to external perturbations. Here, we devise a three-step benchmarking pipeline called STREAMLINE that quantifies the ability of algorithms to capture topological properties of networks and identify hubs. RESULTS To this aim, we use data simulated from different types of networks as well as experimental data from three different organisms. We apply our benchmarking pipeline to four inference algorithms and provide guidance on which algorithm should be used depending on the global network property of interest. AVAILABILITY AND IMPLEMENTATION STREAMLINE is available at https://github.com/ScialdoneLab/STREAMLINE. The data generated in this study are available at https://doi.org/10.5281/zenodo.10710444.
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Affiliation(s)
- Marco Stock
- Institute of Epigenetics and Stem Cells, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 81377, Germany
- Institute of Functional Epigenetics, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 85764, Germany
- Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 85764, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich 85354, Germany
| | - Niclas Popp
- Institute of Epigenetics and Stem Cells, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 81377, Germany
- Institute of Functional Epigenetics, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 85764, Germany
- Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 85764, Germany
| | - Jonathan Fiorentino
- Institute of Epigenetics and Stem Cells, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 81377, Germany
- Institute of Functional Epigenetics, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 85764, Germany
- Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 85764, Germany
| | - Antonio Scialdone
- Institute of Epigenetics and Stem Cells, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 81377, Germany
- Institute of Functional Epigenetics, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 85764, Germany
- Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Munich 85764, Germany
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13
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Hermosillo RJM, Moore LA, Feczko E, Miranda-Domínguez Ó, Pines A, Dworetsky A, Conan G, Mooney MA, Randolph A, Graham A, Adeyemo B, Earl E, Perrone A, Carrasco CM, Uriarte-Lopez J, Snider K, Doyle O, Cordova M, Koirala S, Grimsrud GJ, Byington N, Nelson SM, Gratton C, Petersen S, Feldstein Ewing SW, Nagel BJ, Dosenbach NUF, Satterthwaite TD, Fair DA. A precision functional atlas of personalized network topography and probabilities. Nat Neurosci 2024; 27:1000-1013. [PMID: 38532024 PMCID: PMC11089006 DOI: 10.1038/s41593-024-01596-5] [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: 02/14/2022] [Accepted: 02/08/2024] [Indexed: 03/28/2024]
Abstract
Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.
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Affiliation(s)
- Robert J M Hermosillo
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Lucille A Moore
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Óscar Miranda-Domínguez
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Adam Pines
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Ally Dworetsky
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Gregory Conan
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Michael A Mooney
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Center for Mental Health Innovation, Oregon Health and Science University, Portland, OR, USA
| | - Anita Randolph
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Alice Graham
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric Earl
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Cristian Morales Carrasco
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | | | - Kathy Snider
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Olivia Doyle
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Michaela Cordova
- Joint Doctoral Program in Clinical Psychology, San Diego State University, San Diego, CA, USA
- Joint Doctoral Program in Clinical Psychology, University of California San Diego, San Diego, CA, USA
| | - Sanju Koirala
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Gracie J Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Steven M Nelson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Steven Petersen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Bonnie J Nagel
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
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14
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Bandet MV, Winship IR. Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice. eLife 2024; 12:RP90080. [PMID: 38687189 PMCID: PMC11060715 DOI: 10.7554/elife.90080] [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] [Indexed: 05/02/2024] Open
Abstract
Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within 'remapped' forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.
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Affiliation(s)
- Mischa Vance Bandet
- Neuroscience and Mental Health Institute, University of AlbertaEdmontonCanada
- Neurochemical Research Unit, University of AlbertaEdmontonCanada
- Department of Psychiatry, University of AlbertaEdmontonCanada
| | - Ian Robert Winship
- Neuroscience and Mental Health Institute, University of AlbertaEdmontonCanada
- Neurochemical Research Unit, University of AlbertaEdmontonCanada
- Department of Psychiatry, University of AlbertaEdmontonCanada
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15
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Papadopouli M, Smyrnakis I, Koniotakis E, Savaglio MA, Brozi C, Psilou E, Palagina G, Smirnakis SM. Brain orchestra under spontaneous conditions: Identifying communication modules from the functional architecture of area V1. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.29.582364. [PMID: 38496414 PMCID: PMC10942267 DOI: 10.1101/2024.02.29.582364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
We used two-photon imaging to record from granular and supragranular layers in mouse primary visual cortex (V1) under spontaneous conditions and applied an extension of the spike time tiling coefficient (STTC; introduced by Cutts and Eglen) to map functional connectivity architecture within and across layers. We made several observations: Approximately, 19-34% of neuronal pairs within 300 μm of each other exhibit statistically significant functional connections, compared to ~10% at distances of 1mm or more. As expected, neuronal pairs with similar tuning functions exhibit a significant, though relatively small, increase in the fraction of functional inter-neuronal correlations. In contrast, internal state as reflected by pupillary diameter or aggregate neuronal activity appears to play a much stronger role in determining inter-neuronal correlation distributions and topography. Overall, inter-neuronal correlations appear to be slightly more prominent in L4. The first-order functionally connected (i.e., direct) neighbors of neurons determine the hub structure of the V1 microcircuit. L4 exhibits a nearly flat degree of connectivity distribution, extending to higher values than seen in supragranular layers, whose distribution drops exponentially. In all layers, functional connectivity exhibits small-world characteristics and network robustness. The probability of firing of L2/3 pyramidal neurons can be predicted as a function of the aggregate activity in their first-order functionally connected partners within L4, which represent their putative input group. The functional form of this prediction conforms well to a ReLU function, reaching up to firing probability one in some neurons. Interestingly, the properties of L2/3 pyramidal neurons differ based on the size of their L4 functional connectivity group. Specifically, L2/3 neurons with small layer-4 degrees of connectivity appear to be more sensitive to the firing of their L4 functional connectivity partners, suggesting they may be more effective at transmitting synchronous activity downstream from L4. They also appear to fire largely independently from each other, compared to neurons with high layer-4 degrees of connectivity, and are less modulated by changes in pupil size and aggregate population dynamics. Information transmission is best viewed as occurring from neuronal ensembles in L4 to neuronal ensembles in L2/3. Under spontaneous conditions, we were able to identify such candidate neuronal ensembles, which exhibit high sensitivity, precision, and specificity for L4 to L2/3 information transmission. In sum, functional connectivity analysis under spontaneous activity conditions reveals a modular neuronal ensemble architecture within and across granular and supragranular layers of mouse primary visual cortex. Furthermore, modules with different degrees of connectivity appear to obey different rules of engagement and communication across the V1 columnar circuit.
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Affiliation(s)
- Maria Papadopouli
- Department of Computer Science, University of Crete, Heraklion, Greece
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | | | - Emmanouil Koniotakis
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | - Mario-Alexios Savaglio
- Department of Computer Science, University of Crete, Heraklion, Greece
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | - Christina Brozi
- Department of Computer Science, University of Crete, Heraklion, Greece
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | - Eleftheria Psilou
- Department of Computer Science, University of Crete, Heraklion, Greece
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | - Ganna Palagina
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
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Bagarinao E, Maesawa S, Kato S, Mutoh M, Ito Y, Ishizaki T, Tanei T, Tsuboi T, Suzuki M, Watanabe H, Hoshiyama M, Isoda H, Katsuno M, Sobue G, Saito R. Cerebellar and thalamic connector hubs facilitate the involvement of visual and cognitive networks in essential tremor. Parkinsonism Relat Disord 2024; 121:106034. [PMID: 38382401 DOI: 10.1016/j.parkreldis.2024.106034] [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: 11/30/2023] [Revised: 02/05/2024] [Accepted: 02/09/2024] [Indexed: 02/23/2024]
Abstract
INTRODUCTION Connector hubs are specialized brain regions that connect multiple brain networks and therefore have the potential to affect the functions of multiple systems. This study aims to examine the involvement of connector hub regions in essential tremor. METHODS We examined whole-brain functional connectivity alterations across multiple brain networks in 27 patients with essential tremor and 27 age- and sex-matched healthy controls to identify affected hub regions using a network metric called functional connectivity overlap ratio estimated from resting-state functional MRI. We also evaluated the relationships of affected hubs with cognitive and tremor scores in all patients and with motor function improvement scores in 15 patients who underwent postoperative follow-up evaluations after focused ultrasound thalamotomy. RESULTS We have identified affected connector hubs in the cerebellum and thalamus. Specifically, the dentate nucleus in the cerebellum and the dorsomedial thalamus exhibited more extensive connections with the sensorimotor network in patients. Moreover, the connections of the thalamic pulvinar with the visual network were also significantly widespread in the patient group. The connections of these connector hub regions with cognitive networks were negatively associated (FDR q < 0.05) with cognitive, tremor, and motor function improvement scores. CONCLUSION In patients with essential tremor, connector hub regions within the cerebellum and thalamus exhibited widespread functional connections with sensorimotor and visual networks, leading to alternative pathways outside the classical tremor axis. Their connections with cognitive networks also affect patients' cognitive function.
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Affiliation(s)
- Epifanio Bagarinao
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan; Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan.
| | - Satoshi Maesawa
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan; Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Sachiko Kato
- Focused Ultrasound Therapy Center, Nagoya Kyoritsu Hospital, Nagoya, Aichi, Japan
| | - Manabu Mutoh
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Yoshiki Ito
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Tomotaka Ishizaki
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Takafumi Tanei
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Takashi Tsuboi
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Masashi Suzuki
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Hirohisa Watanabe
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan; Department of Neurology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Minoru Hoshiyama
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan; Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Haruo Isoda
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan; Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Masahisa Katsuno
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan; Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan; Department of Clinical Research Education, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Gen Sobue
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan; Aichi Medical University, Nagakute, Aichi, Japan
| | - Ryuta Saito
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan; Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
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17
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Mareva S, Holmes J. Mapping neurodevelopmental diversity in executive function. Cortex 2024; 172:204-221. [PMID: 38354470 DOI: 10.1016/j.cortex.2023.11.021] [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: 04/28/2023] [Revised: 09/30/2023] [Accepted: 11/14/2023] [Indexed: 02/16/2024]
Abstract
Executive function, an umbrella term used to describe the goal-directed regulation of thoughts, actions, and emotions, is an important dimension implicated in neurodiversity and established malleable predictor of multiple adult outcomes. Neurodevelopmental differences have been linked to both executive function strengths and weaknesses, but evidence for associations between specific profiles of executive function and specific neurodevelopmental conditions is mixed. In this exploratory study, we adopt an unsupervised machine learning approach (self-organising maps), combined with k-means clustering to identify data-driven profiles of executive function in a transdiagnostic sample of 566 neurodivergent children aged 8-18 years old. We include measures designed to capture two distinct aspects of executive function: performance-based tasks designed to tap the state-like efficiency of cognitive skills under optimal conditions, and behaviour ratings suited to capturing the trait-like application of cognitive control in everyday contexts. Three profiles of executive function were identified: one had consistent difficulties across both types of assessments, while the other two had inconsistent profiles of predominantly rating- or predominantly task-based difficulties. Girls and children without a formal diagnosis were more likely to have an inconsistent profile of primarily task-based difficulties. Children with these different profiles had differences in academic achievement and mental health outcomes and could further be differentiated from a comparison group of children on both shared and profile-unique patterns of neural white matter organisation. Importantly, children's executive function profiles were not directly related to diagnostic categories or to dimensions of neurodiversity associated with specific diagnoses (e.g., hyperactivity, inattention, social communication). These findings support the idea that the two types of executive function assessments provide non-redundant information related to children's neurodevelopmental differences and that they should not be used interchangeably. The findings advance our understanding of executive function profiles and their relationship to behavioural outcomes and neural variation in neurodivergent populations.
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Affiliation(s)
- Silvana Mareva
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK; Psychology Department, Faculty of Health and Life Sciences, University of Exeter, UK.
| | - Joni Holmes
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK; School of Psychology, University of East Anglia, UK
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Liloia D, Manuello J, Costa T, Keller R, Nani A, Cauda F. Atypical local brain connectivity in pediatric autism spectrum disorder? A coordinate-based meta-analysis of regional homogeneity studies. Eur Arch Psychiatry Clin Neurosci 2024; 274:3-18. [PMID: 36599959 PMCID: PMC10787009 DOI: 10.1007/s00406-022-01541-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 12/16/2022] [Indexed: 01/05/2023]
Abstract
Despite decades of massive neuroimaging research, the comprehensive characterization of short-range functional connectivity in autism spectrum disorder (ASD) remains a major challenge for scientific advances and clinical translation. From the theoretical point of view, it has been suggested a generalized local over-connectivity that would characterize ASD. This stance is known as the general local over-connectivity theory. However, there is little empirical evidence supporting such hypothesis, especially with regard to pediatric individuals with ASD (age [Formula: see text] 18 years old). To explore this issue, we performed a coordinate-based meta-analysis of regional homogeneity studies to identify significant changes of local connectivity. Our analyses revealed local functional under-connectivity patterns in the bilateral posterior cingulate cortex and superior frontal gyrus (key components of the default mode network) and in the bilateral paracentral lobule (a part of the sensorimotor network). We also performed a functional association analysis of the identified areas, whose dysfunction is clinically consistent with the well-known deficits affecting individuals with ASD. Importantly, we did not find relevant clusters of local hyper-connectivity, which is contrary to the hypothesis that ASD may be characterized by generalized local over-connectivity. If confirmed, our result will provide a valuable insight into the understanding of the complex ASD pathophysiology.
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Affiliation(s)
- Donato Liloia
- GCS-fMRI Research Group, Koelliker Hospital and Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Jordi Manuello
- GCS-fMRI Research Group, Koelliker Hospital and Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Tommaso Costa
- GCS-fMRI Research Group, Koelliker Hospital and Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy.
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
- Neuroscience Institute of Turin (NIT), Turin, Italy.
| | - Roberto Keller
- Adult Autism Center, DSM Local Health Unit, ASL TO, Turin, Italy
| | - Andrea Nani
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI Research Group, Koelliker Hospital and Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
- Neuroscience Institute of Turin (NIT), Turin, Italy
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19
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Chang Y, Wang X, Liao J, Chen S, Liu X, Liu S, Ming D. Temporal hyper-connectivity and frontal hypo-connectivity within gamma band in schizophrenia: A resting state EEG study. Schizophr Res 2024; 264:220-230. [PMID: 38183959 DOI: 10.1016/j.schres.2023.12.017] [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: 12/27/2022] [Revised: 11/12/2023] [Accepted: 12/16/2023] [Indexed: 01/08/2024]
Abstract
OBJECTIVE The brain network serves as the physiological foundation for information processing of the brain. Many studies have reported abnormalities of gamma oscillations in Schizophrenia. The aim of this study was to investigate the gamma-band connectivity in Schizophrenia patients. METHODS We recorded the resting state electroencephalogram (EEG) for 15 schizophrenia patients with refractory auditory hallucinations and 14 healthy controls, with eyes open and closed. The brain network was constructed based on weighted phase lag index for gamma band. Whole scalp metrics (clustering coefficient, global efficiency and local efficiency) and local region metrics (degree and betweenness centrality) in the frontal and temporal lobes were computed. Correlation analyses between network metrics and symptom scales were examined to find associations with symptom severity. RESULTS Schizophrenia patients had larger global efficiency and local efficiency (p < 0.05) with eyes closed, probably representing greater brain activity and information exchange. For degree and betweenness centrality, schizophrenia patients showed an increase (p < 0.05) in the temporal lobe but a decrease (p < 0.05) in the frontal lobe with eyes closed and open, potentially account for the patients' symptoms such as hallucinations and thought disorders. Local efficiency and frontal lobe degree were positively and negatively correlated with the scales, respectively (both p < 0.05). CONCLUSIONS Altered connectivity of the resting state brain network has been revealed and may be associated with the core symptoms of schizophrenia. Our study provides promising evidence for the investigation of the pathological basis of Schizophrenia and could aid in objective diagnosis.
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Affiliation(s)
- Yuan Chang
- Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, China
| | - Xiaojuan Wang
- Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, China
| | - Jingmeng Liao
- Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, China
| | - Sitong Chen
- Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, China
| | - Xiaoya Liu
- Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, China
| | - Shuang Liu
- Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, China.
| | - Dong Ming
- Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, China
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Samfira IMA, Galanopoulou AS, Nariai H, Gursky JM, Moshé SL, Bardakjian BL. EEG-based spatiotemporal dynamics of fast ripple networks and hubs in infantile epileptic spasms. Epilepsia Open 2024; 9:122-137. [PMID: 37743321 PMCID: PMC10839371 DOI: 10.1002/epi4.12831] [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: 03/21/2023] [Accepted: 09/17/2023] [Indexed: 09/26/2023] Open
Abstract
OBJECTIVE Infantile epileptic spasms (IS) are epileptic seizures that are associated with increased risk for developmental impairments, adult epilepsies, and mortality. Here, we investigated coherence-based network dynamics in scalp EEG of infants with IS to identify frequency-dependent networks associated with spasms. We hypothesized that there is a network of increased fast ripple connectivity during the electrographic onset of clinical spasms, which is distinct from controls. METHODS We retrospectively analyzed peri-ictal and interictal EEG recordings of 14 IS patients. The data was compared with 9 age-matched controls. Wavelet phase coherence (WPC) was computed between 0.2 and 400 Hz. Frequency- and time-dependent brain networks were constructed using this coherence as the strength of connection between two EEG channels, based on graph theory principles. Connectivity was evaluated through global efficiency (GE) and channel-based closeness centrality (CC), over frequency and time. RESULTS GE in the fast ripple band (251-400 Hz) was significantly greater following the onset of spasms in all patients (P < 0.05). Fast ripple networks during the first 10s from spasm onset show enhanced anteroposterior gradient in connectivity (posterior > central > anterior, Kruskal-Wallis P < 0.001), with maximum CC over the centroparietal channels in 10/14 patients. Additionally, this anteroposterior gradient in CC connectivity is observed during spasms but not during the interictal awake or asleep states of infants with IS. In controls, anteroposterior gradient in fast ripple CC was noted during arousals and wakefulness but not during sleep. There was also a simultaneous decrease in GE in the 5-8 Hz range after the onset of spasms (P < 0.05), of unclear biological significance. SIGNIFICANCE We identified an anteroposterior gradient in the CC connectivity of fast ripple hubs during spasms. This anteroposterior gradient observed during spasms is similar to the anteroposterior gradient in the CC connectivity observed in wakefulness or arousals in controls, suggesting that this state change is related to arousal networks.
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Affiliation(s)
- Ioana M. A. Samfira
- Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoTorontoOntarioCanada
| | - Aristea S. Galanopoulou
- Saul R. Korey Department of Neurology and Comprehensive Einstein/Montefiore Epilepsy CenterAlbert Einstein College of MedicineBronxNew YorkUSA
- Isabelle Rapin Division of Child NeurologyAlbert Einstein College of MedicineBronxNew YorkUSA
- Dominick P. Purpura Department of NeuroscienceAlbert Einstein College of MedicineBronxNew YorkUSA
| | - Hiroki Nariai
- Department of PediatricsUCLA Mattel Children's HospitalLos AngelesCaliforniaUSA
| | - Jonathan M. Gursky
- Saul R. Korey Department of Neurology and Comprehensive Einstein/Montefiore Epilepsy CenterAlbert Einstein College of MedicineBronxNew YorkUSA
| | - Solomon L. Moshé
- Saul R. Korey Department of Neurology and Comprehensive Einstein/Montefiore Epilepsy CenterAlbert Einstein College of MedicineBronxNew YorkUSA
- Isabelle Rapin Division of Child NeurologyAlbert Einstein College of MedicineBronxNew YorkUSA
- Dominick P. Purpura Department of NeuroscienceAlbert Einstein College of MedicineBronxNew YorkUSA
- Department of PediatricsEinstein College of MedicineBronxNew YorkUSA
| | - Berj L. Bardakjian
- Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoTorontoOntarioCanada
- Institute of Biomedical EngineeringUniversity of TorontoTorontoOntarioCanada
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21
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Magnani M, Rustici A, Zoli M, Tuleasca C, Chaurasia B, Franceschi E, Tonon C, Lodi R, Conti A. Connectome-Based Neurosurgery in Primary Intra-Axial Neoplasms: Beyond the Traditional Modular Conception of Brain Architecture for the Preservation of Major Neurological Domains and Higher-Order Cognitive Functions. Life (Basel) 2024; 14:136. [PMID: 38255752 PMCID: PMC10817682 DOI: 10.3390/life14010136] [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: 12/13/2023] [Revised: 01/06/2024] [Accepted: 01/12/2024] [Indexed: 01/24/2024] Open
Abstract
Despite the therapeutical advancements in the surgical treatment of primary intra-axial neoplasms, which determined both a significative improvement in OS and QoL and a reduction in the incidence of surgery-induced major neurological deficits, nowadays patients continue to manifest subtle post-operative neurocognitive impairments, preventing them from a full reintegration back into social life and into the workforce. The birth of connectomics paved the way for a profound reappraisal of the traditional conception of brain architecture, in favour of a model based on large-scale structural and functional interactions of a complex mosaic of cortical areas organized in a fluid network interconnected by subcortical bundles. Thanks to these advancements, neurosurgery is facing a new era of connectome-based resections, in which the core principle is still represented by the achievement of an ideal onco-functional balance, but with a closer eye on whole-brain circuitry, which constitutes the foundations of both major neurological functions, to be intended as motricity; language and visuospatial function; and higher-order cognitive functions such as cognition, conation, emotion and adaptive behaviour. Indeed, the achievement of an ideal balance between the radicality of tumoral resection and the preservation, as far as possible, of the integrity of local and global brain networks stands as a mandatory goal to be fulfilled to allow patients to resume their previous life and to make neurosurgery tailored and gentler to their individual needs.
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Affiliation(s)
- Marcello Magnani
- IRCCS Istituto Delle Scienze Neurologiche di Bologna, UOC Neurochirurgia, 40123 Bologna, Italy;
- Dipartimento di Scienze Biomediche e Neuromotorie (DIBINEM), Università di Bologna, 40123 Bologna, Italy; (A.R.); (M.Z.); (C.T.); (R.L.)
| | - Arianna Rustici
- Dipartimento di Scienze Biomediche e Neuromotorie (DIBINEM), Università di Bologna, 40123 Bologna, Italy; (A.R.); (M.Z.); (C.T.); (R.L.)
- IRCCS Istituto Delle Scienze Neurologiche di Bologna, UOSI Neuroradiologia, Ospedale Maggiore, 40138 Bologna, Italy
| | - Matteo Zoli
- Dipartimento di Scienze Biomediche e Neuromotorie (DIBINEM), Università di Bologna, 40123 Bologna, Italy; (A.R.); (M.Z.); (C.T.); (R.L.)
- Programma Neurochirurgia Ipofisi—Pituitary Unit, IRCCS Istituto Delle Scienze Neurologiche di Bologna, 40121 Bologna, Italy
| | - Constantin Tuleasca
- Department of Neurosurgery, University Hospital of Lausanne and Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland;
- Signal Processing Laboratory (LTS 5), Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne, 1015 Lausanne, Switzerland
| | - Bipin Chaurasia
- Department of Neurosurgery, Neurosurgery Clinic, Birgunj 44300, Nepal;
| | - Enrico Franceschi
- IRCCS Istituto Delle Scienze Neurologiche di Bologna, UOC Oncologia Sistema Nervoso, 40139 Bologna, Italy;
| | - Caterina Tonon
- Dipartimento di Scienze Biomediche e Neuromotorie (DIBINEM), Università di Bologna, 40123 Bologna, Italy; (A.R.); (M.Z.); (C.T.); (R.L.)
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto Delle Scienze Neurologiche di Bologna, 40123 Bologna, Italy
| | - Raffaele Lodi
- Dipartimento di Scienze Biomediche e Neuromotorie (DIBINEM), Università di Bologna, 40123 Bologna, Italy; (A.R.); (M.Z.); (C.T.); (R.L.)
- IRCCS Istituto Delle Scienze Neurologiche di Bologna, 40123 Bologna, Italy
| | - Alfredo Conti
- IRCCS Istituto Delle Scienze Neurologiche di Bologna, UOC Neurochirurgia, 40123 Bologna, Italy;
- Dipartimento di Scienze Biomediche e Neuromotorie (DIBINEM), Università di Bologna, 40123 Bologna, Italy; (A.R.); (M.Z.); (C.T.); (R.L.)
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22
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Khalilian M, Toba MN, Roussel M, Tasseel-Ponche S, Godefroy O, Aarabi A. Age-related differences in structural and resting-state functional brain network organization across the adult lifespan: A cross-sectional study. AGING BRAIN 2024; 5:100105. [PMID: 38273866 PMCID: PMC10809105 DOI: 10.1016/j.nbas.2023.100105] [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: 04/11/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/27/2024] Open
Abstract
We investigated age-related trends in the topology and hierarchical organization of brain structural and functional networks using diffusion-weighted imaging and resting-state fMRI data from a large cohort of healthy aging adults. At the cross-modal level, we explored age-related patterns in the RC involvement of different functional subsystems using a high-resolution functional parcellation. We further assessed age-related differences in the structure-function coupling as well as the network vulnerability to damage to rich club connectivity. Regardless of age, the structural and functional brain networks exhibited a rich club organization and small-world topology. In older individuals, we observed reduced integration and segregation within the frontal-occipital regions and the cerebellum along the brain's medial axis. Additionally, functional brain networks displayed decreased integration and increased segregation in the prefrontal, centrotemporal, and occipital regions, and the cerebellum. In older subjects, structural networks also exhibited decreased within-network and increased between-network RC connectivity. Furthermore, both within-network and between-network RC connectivity decreased in functional networks with age. An age-related decline in structure-function coupling was observed within sensory-motor, cognitive, and subcortical networks. The structural network exhibited greater vulnerability to damage to RC connectivity within the language-auditory, visual, and subcortical networks. Similarly, for functional networks, increased vulnerability was observed with damage to RC connectivity in the cerebellum, language-auditory, and sensory-motor networks. Overall, the network vulnerability decreased significantly in subjects older than 70 in both networks. Our findings underscore significant age-related differences in both brain functional and structural RC connectivity, with distinct patterns observed across the adult lifespan.
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Affiliation(s)
- Maedeh Khalilian
- Laboratory of Functional Neuroscience and Pathologies (UR UPJV 4559), University Research Center (CURS), University of Picardy Jules Verne, Amiens, France
| | - Monica N. Toba
- Laboratory of Functional Neuroscience and Pathologies (UR UPJV 4559), University Research Center (CURS), University of Picardy Jules Verne, Amiens, France
- Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
| | - Martine Roussel
- Laboratory of Functional Neuroscience and Pathologies (UR UPJV 4559), University Research Center (CURS), University of Picardy Jules Verne, Amiens, France
| | - Sophie Tasseel-Ponche
- Laboratory of Functional Neuroscience and Pathologies (UR UPJV 4559), University Research Center (CURS), University of Picardy Jules Verne, Amiens, France
- Neurological Physical Medicine and Rehabilitation Department, Amiens University Hospital, University of Picardy Jules Verne, Amiens, France
| | - Olivier Godefroy
- Laboratory of Functional Neuroscience and Pathologies (UR UPJV 4559), University Research Center (CURS), University of Picardy Jules Verne, Amiens, France
- Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
- Neurology Department, Amiens University Hospital, Amiens, France
| | - Ardalan Aarabi
- Laboratory of Functional Neuroscience and Pathologies (UR UPJV 4559), University Research Center (CURS), University of Picardy Jules Verne, Amiens, France
- Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
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23
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Ghosh A, Som A. Network analysis of transcriptomic data uncovers molecular signatures and the interplay of mRNAs, lncRNAs, and miRNAs in human embryonic stem cells. Differentiation 2024; 135:100738. [PMID: 38008592 DOI: 10.1016/j.diff.2023.11.001] [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: 08/21/2023] [Revised: 10/30/2023] [Accepted: 11/09/2023] [Indexed: 11/28/2023]
Abstract
Growing evidence has shown that besides the protein coding genes, the non-coding elements of the genome are indispensable for maintaining the property of self-renewal in human embryonic stem cells and in cell fate determination. However, the regulatory mechanisms and the landscape of interactions between the coding and non-coding elements is poorly understood. In this work, we used weighted gene co-expression network analysis (WGCNA) on transcriptomic data retrieved from RNA-seq and small RNA-seq experiments and reconstructed the core human pluripotency network (called PluriMLMiNet) consisting of 375 mRNA, 57 lncRNA and 207 miRNAs. Furthermore, we derived networks specific to the naïve and primed states of human pluripotency (called NaiveMLMiNet and PrimedMLMiNet respectively) that revealed a set of molecular markers (RPS6KA1, ZYG11A, ZNF695, ZNF273, and NLRP2 for naive state, and RAB34, TMEM178B, PTPRZ1, USP44, KIF1A and LRRN1 for primed state) which can be used to distinguish the pluripotent state from the non-pluripotent state and also to identify the intra-pluripotency states (i.e., naïve and primed state). The lncRNA DANT1 was found to be a crucial as it formed a bridge between the naive and primed state-specific networks. Analysis of the genes neighbouring DANT1 suggested its possible role as a competing endogenous RNA (ceRNA) for the induction and maintenance of human pluripotency. This was computationally validated by predicting the missing DANT1-miRNA interactions to complete the ceRNA circuit. Here we first report that DANT1 might harbour binding sites for miRNAs hsa-miR-30c-2-3p, hsa-miR-210-3p and hsa-let-7b-5p which may influence pluripotency.
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Affiliation(s)
- Arindam Ghosh
- Centre of Bioinformatics, Institute of Interdisciplinary Studies, University of Allahabad, Prayagraj, 211002, India; Institute of Biomedicine, University of Eastern Finland, FI-70210, Kuopio, Finland.
| | - Anup Som
- Centre of Bioinformatics, Institute of Interdisciplinary Studies, University of Allahabad, Prayagraj, 211002, India.
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Ai H, Yang C, Lu M, Ren J, Li Z, Zhang Y. Abnormal white matter structural network topological property in patients with temporal lobe epilepsy. CNS Neurosci Ther 2024; 30:e14414. [PMID: 37622409 PMCID: PMC10805448 DOI: 10.1111/cns.14414] [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: 02/13/2023] [Revised: 08/02/2023] [Accepted: 08/04/2023] [Indexed: 08/26/2023] Open
Abstract
BACKGROUND Diffusion tensor imaging (DTI) studies have demonstrated white matter (WM) abnormalities in patients with temporal lobe epilepsy (TLE). However, alterations in the topological properties of the WM structural network in patients with TLE remain unclear. Graph theoretical analysis provides a new perspective for evaluating the connectivity of WM structural networks. METHODS DTI was used to map the structural networks of 18 patients with TLE (10 males and 8 females) and 29 (17 males and 12 females) age- and gender-matched normal controls (NC). Graph theory was used to analyze the whole-brain networks and their topological properties between the two groups. Finally, partial correlation analyses were performed on the weighted network properties and clinical characteristics, namely, duration of epilepsy, verbal intelligence quotient (IQ), and performance IQ. RESULTS Patients with TLE exhibited reduced global efficiency and increased characteristic path length. A total of 31 regions with nodal efficiency alterations were detected in the fractional anisotropy_ weighted network of the patients. Communication hubs, such as the middle temporal gyrus, right inferior temporal gyrus, left calcarine, and right superior parietal gyrus, were also differently distributed in the patients compared with the NC. Several node regions showed close relationships with duration of epilepsy, verbal IQ, and performance IQ. CONCLUSIONS Our results demonstrate the disruption of the WM structural network in TLE patients. This study may contribute to the further understanding of the pathological mechanism of TLE.
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Affiliation(s)
- Haiming Ai
- Faculty of Science and TechnologyBeijing Open UniversityBeijingChina
| | - Chunlan Yang
- College of Life Science and BioengineeringBeijing University of TechnologyBeijingChina
| | - Min Lu
- College of Life Science and BioengineeringBeijing University of TechnologyBeijingChina
| | - Jiechuan Ren
- Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zhimei Li
- Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Yining Zhang
- Department of EquipmentBaoding first Central HospitalBaodingChina
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25
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Bazinet V, Hansen JY, Misic B. Towards a biologically annotated brain connectome. Nat Rev Neurosci 2023; 24:747-760. [PMID: 37848663 DOI: 10.1038/s41583-023-00752-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/20/2023] [Indexed: 10/19/2023]
Abstract
The brain is a network of interleaved neural circuits. In modern connectomics, brain connectivity is typically encoded as a network of nodes and edges, abstracting away the rich biological detail of local neuronal populations. Yet biological annotations for network nodes - such as gene expression, cytoarchitecture, neurotransmitter receptors or intrinsic dynamics - can be readily measured and overlaid on network models. Here we review how connectomes can be represented and analysed as annotated networks. Annotated connectomes allow us to reconceptualize architectural features of networks and to relate the connection patterns of brain regions to their underlying biology. Emerging work demonstrates that annotated connectomes help to make more veridical models of brain network formation, neural dynamics and disease propagation. Finally, annotations can be used to infer entirely new inter-regional relationships and to construct new types of network that complement existing connectome representations. In summary, biologically annotated connectomes offer a compelling way to study neural wiring in concert with local biological features.
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Affiliation(s)
- Vincent Bazinet
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada.
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26
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Guo W, Zhang W, Zhang J, Li Z, Zhu W. Effective connectivity analysis of verbal working memory advantage across materials for pathological smartphone users by fNIRS. Psychiatry Res Neuroimaging 2023; 336:111731. [PMID: 37875058 DOI: 10.1016/j.pscychresns.2023.111731] [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: 04/13/2023] [Revised: 07/31/2023] [Accepted: 10/10/2023] [Indexed: 10/26/2023]
Abstract
Previous studies have found working memory (WM) advantages of the pathological smartphone use (PSU) group, but most of which were emphasized in the network-related domain. Whether the advantages can transfer to other domains has yet to be confirmed. In particular, exploring from a brain mechanism perspective is necessary. Using the classical N-back paradigm, this study selected network-related words and neutral words as materials combined with fNIRS to probe the verbal WM characteristics of the PSU group. The results showed that β in channel 3, channel 4, and channel 5 were significantly lower in the PSU group than those in the control group The analysis of the region of interest revealed that the PSU group showed significantly lower β in the l-DLPFC and frontopolar. Granger Causality results showed that functional connectivity between frontopolar and R-DLPFC for the PSU group was significantly higher than for the control group in the network word condition. These results demonstrate that the PSU group has an advantage in WM, transferring from the network-related stimulus to the neutral stimulus. The advantages of network stimulus were related to bidirectional connectivity between frontopolar and R-DLPFC. Also, the l-DLPFC and frontopolar are associated with the cross-material consistency of WM.
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Affiliation(s)
- Wenxin Guo
- School of Psychology, Central China Normal University, No. 152 Luoyu Street, HongShan District, Hubei 430079, Wuhan, PR China
| | - Wei Zhang
- School of Psychology, Central China Normal University, No. 152 Luoyu Street, HongShan District, Hubei 430079, Wuhan, PR China.
| | - Jianli Zhang
- Chengdu Longquan No.1 High School, Chengdu, Sichuan, PR China
| | - Ziyi Li
- School of Psychology, Central China Normal University, No. 152 Luoyu Street, HongShan District, Hubei 430079, Wuhan, PR China
| | - Wanling Zhu
- School of Psychology, Central China Normal University, No. 152 Luoyu Street, HongShan District, Hubei 430079, Wuhan, PR China
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Zhou YM, Xie W, Zhi JR, Zou X. Frankliniella occidentalis pathogenic fungus Lecanicillium interacts with internal microbes and produces sublethal effects. PESTICIDE BIOCHEMISTRY AND PHYSIOLOGY 2023; 197:105679. [PMID: 38072536 DOI: 10.1016/j.pestbp.2023.105679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/21/2023] [Accepted: 10/25/2023] [Indexed: 12/18/2023]
Abstract
Frankliniella occidentalis (Thysanoptera: Thripidae) is a pest that feeds on various crops worldwide. A prior study identified Lecanicillium attenuatum and L. cauligalbarum as pathogens of F. occidentalis. Unfortunately, the potential of these two entomopathogenic fungi for the biocontrol of F. occidentalis has not been effectively evaluated. The internal microbes (endosymbionts and the gut microbiota) of insects, especially gut bacteria, are crucial in regulating the interactions between the host and intestinal pathogens. The role of thrips internal microbes in the infection of these two entomopathogenic fungi is also unknown. Therefore, biological control of thrips is immediately needed, and to accomplish that, an improved understanding of the internal microbes of thrips against Lecanicillium infection is essential. The virulence of the two pathogenic fungi against F. occidentalis increased with the conidia concentration. Overall, the LC50 of L. cauligalbarum was lower than that of L. attenuatum, and the pathogenicity degree was adult > pupa > nymphs. The activities of protective enzymes include superoxide dismutase (SOD), catalase (CAT), peroxidase (POD); detoxification enzymes include polyphenol oxidase (PPO), glutathione s-transferase (GSTs), and carboxylesterase (CarE); hormones include ecdysone and juvenile hormone; and the composition and proportion of microorganisms (fungi and bacteria) in F. occidentalis infected by L. cauligalbarum and L. attenuatum have changed significantly. According to the network correlation results, there was a considerable correlation among the internal microbes (including bacteria and fungi), enzyme activities, and hormones, which indicates that in addition to bacteria, internal fungi of F. occidentalis are also involved in the L. cauligalbarum and L. attenuatum infection process. In addition, the development time of the surviving F. occidentalis exposed to L. cauligalbarum or L. attenuatum was significantly shorter than that of the control group. Furthermore, the intrinsic rate of increase (rm), finite rate of increase (λ), net reproductive rate (R0), mean generation time (T), and gross reproductive rate (GRR) were significantly lower in the treatment groups than in the control group. L. attenuatum and L. cauligalbarum have biocontrol potential against F. occidentalis. In addition to bacteria, internal fungi of F. occidentalis are also involved in the infection process of insect pathogenic fungi. Disruption of the internal microbial balance results in discernible sublethal effects. Such prevention and control potential should not be ignored. These findings provide an improved understanding of physiological responses in thrips with altered immunity against entomopathogenic fungal infections, which can guide us toward the development of novel biocontrol strategies against thrips.
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Affiliation(s)
- Ye-Ming Zhou
- Institute of Entomology, Guizhou University, The Provincial Key Laboratory for Agricultural Pest Management of the Mountainous Region, Guiyang 550025, Guizhou, China; Institute of Fungus Resources, Key laboratory of Plant Resource Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), College of life Sciences, Guizhou University, Guiyang 550025, Guizhou, China
| | - Wen Xie
- Institute of Entomology, Guizhou University, The Provincial Key Laboratory for Agricultural Pest Management of the Mountainous Region, Guiyang 550025, Guizhou, China
| | - Jun-Rui Zhi
- Institute of Entomology, Guizhou University, The Provincial Key Laboratory for Agricultural Pest Management of the Mountainous Region, Guiyang 550025, Guizhou, China.
| | - Xiao Zou
- Institute of Fungus Resources, Key laboratory of Plant Resource Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), College of life Sciences, Guizhou University, Guiyang 550025, Guizhou, China
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28
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Oujamaa L, Delon-Martin C, Jaroszynski C, Termenon M, Silva S, Payen JF, Achard S. Functional hub disruption emphasizes consciousness recovery in severe traumatic brain injury. Brain Commun 2023; 5:fcad319. [PMID: 38757093 PMCID: PMC11098044 DOI: 10.1093/braincomms/fcad319] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 08/20/2023] [Accepted: 11/21/2023] [Indexed: 05/18/2024] Open
Abstract
Severe traumatic brain injury can lead to transient or even chronic disorder of consciousness. To increase diagnosis and prognosis accuracy of disorder of consciousness, functional neuroimaging is recommended 1 month post-injury. Here, we investigated brain networks remodelling on longitudinal data between 1 and 3 months post severe traumatic brain injury related to change of consciousness. Thirty-four severe traumatic brain-injured patients were included in a cross-sectional and longitudinal clinical study, and their MRI data were compared to those of 20 healthy subjects. Long duration resting-state functional MRI were acquired in minimally conscious and conscious patients at two time points after their brain injury. The first time corresponds to the exit from intensive care unit and the second one to the discharge from post-intensive care rehabilitation ward. Brain networks data were extracted using graph analysis and metrics at each node quantifying local (clustering) and global (degree) connectivity characteristics. Comparison with brain networks of healthy subjects revealed patterns of hyper- and hypo-connectivity that characterize brain networks reorganization through the hub disruption index, a value quantifying the functional disruption in each individual severe traumatic brain injury graph. At discharge from intensive care unit, 24 patients' graphs (9 minimally conscious and 15 conscious) were fully analysed and demonstrated significant network disruption. Clustering and degree nodal metrics, respectively, related to segregation and integration properties of the network, were relevant to distinguish minimally conscious and conscious groups. At discharge from post-intensive care rehabilitation unit, 15 patients' graphs (2 minimally conscious, 13 conscious) were fully analysed. The conscious group still presented a significant difference with healthy subjects. Using mixed effects models, we showed that consciousness state, rather than time, explained the hub disruption index differences between minimally conscious and conscious groups. While severe traumatic brain-injured patients recovered full consciousness, regional functional connectivity evolved towards a healthy pattern. More specifically, the restoration of a healthy brain functional segregation could be necessary for consciousness recovery after severe traumatic brain injury. For the first time, extracting the hub disruption index directly from each patient's graph, we were able to track the clinical alteration and subsequent recovery of consciousness during the first 3 months following a severe traumatic brain injury.
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Affiliation(s)
- Lydia Oujamaa
- University Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Chantal Delon-Martin
- University Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Chloé Jaroszynski
- University Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Maite Termenon
- Faculty of Engineering, Biomedical Engineering Department, Mondragon Unibertsitatea (MU-ENG), 20500 Mondragon, Spain
| | - Stein Silva
- Toulouse NeuroImaging Center, Toulouse III Paul Sabatier University, Inserm, 31062 Toulouse, France
- Critical Care Unit, University Teaching Hospital of Purpan, 31059 Toulouse, France
| | - Jean-François Payen
- University Grenoble Alpes, Inserm U1216, Grenoble Institut Neurosciences, CHU Grenoble Alpes, 38000 Grenoble, France
| | - Sophie Achard
- University Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, 38000 Grenoble, France
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29
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Feng C, Tian X, Luo YJ. Neurocomputational Substrates Underlying the Effect of Identifiability on Third-Party Punishment. J Neurosci 2023; 43:8018-8031. [PMID: 37752000 PMCID: PMC10669760 DOI: 10.1523/jneurosci.0460-23.2023] [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: 03/22/2023] [Revised: 09/08/2023] [Accepted: 09/19/2023] [Indexed: 09/28/2023] Open
Abstract
The identifiable target effect refers to the preference for helping identified victims and punishing identifiable perpetrators compared with equivalent but unidentifiable counterparts. The identifiable target effect is often attributed to the heightened moral emotions evoked by identified targets. However, the specific neurocognitive processes that mediate and/or modulate this effect remain largely unknown. Here, we combined a third-party punishment game with brain imaging and computational modeling to unravel the neurocomputational underpinnings of the identifiable transgressor effect. Human participants (males and females) acted as bystanders and punished identified or anonymous wrongdoers. Participants were more punitive toward identified wrongdoers than anonymous wrongdoers because they took a vicarious perspective of victims and adopted lower reference points of inequity (i.e., more stringent norms) in the identified context than in the unidentified context. Accordingly, there were larger activity of the ventral anterior insula, more distinct multivariate neural patterns in the dorsal anterior insula and dorsal anterior cingulate cortex, and lower strength between ventral anterior insula and dorsolateral PFC and between dorsal anterior insula and ventral striatum connectivity in response to identified transgressors than anonymous transgressors. These findings implicate the interplay of expectancy violations, emotions, and self-interest in the identifiability effect. Last, individual differences in the identifiability effect were associated with empathic concern/social dominance orientation, activity in the precuneus/cuneus and temporo-parietal junction, and intrinsic functional connectivity of the dorsolateral PFC. Together, our work is the first to uncover the neurocomputational processes mediating identifiable transgressor effect and to characterize psychophysiological profiles modulating the effect.SIGNIFICANCE STATEMENT The identifiable target effect, more help to identified victims or stronger punishment to identifiable perpetrators, is common in daily life. We examined the neurocomputational mechanisms mediating/modulating the identifiability effect on third-party punishment by bridging literature from economics and cognitive neuroscience. Our findings reveal that identifiable transgressor effect is mediated by lower reference points of inequity (i.e., more stringent norms), which might be associated with a stronger involvement of the emotion processes and a weaker engagement of the analytic/deliberate processes. Furthermore, personality traits, altered brain activity, and intrinsic functional connectivity contribute to the individual variance in the identifiability effect. Overall, our study advances the understanding of the identifiability effect by shedding light on its component processes and modulating factors.
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Affiliation(s)
- Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences, South China Normal University, Ministry of Education, Guangzhou, 510631, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Xia Tian
- Key Laboratory of Brain, Cognition and Education Sciences, South China Normal University, Ministry of Education, Guangzhou, 510631, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Yue-Jia Luo
- The State Key Lab of Cognitive and Learning, Faculty of Psychology, Beijing Normal University, Beijing, 100875, China
- Institute for Neuropsychological Rehabilitation, University of Health and Rehabilitation Sciences, Qingdao, 266113, China
- School of Psychology, Chengdu Medical College, Chengdu, 610500, China
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Wang Y, Guo L, Wang R, Wang Y, Duan F, Zhan Y, Cheng J, Sun X, Tang Z. Abnormal Topological Organization of White Matter Structural Networks in Normal Tension Glaucoma Revealed via Diffusion Tensor Tractography. Brain Sci 2023; 13:1597. [PMID: 38002558 PMCID: PMC10669977 DOI: 10.3390/brainsci13111597] [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: 10/17/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND Normal tension glaucoma (NTG) is considered a neurodegenerative disease with glaucomatous damage extending to diffuse brain areas. Therefore, this study aims to explore the abnormalities in the NTG structural network to help in the early diagnosis and course evaluation of NTG. METHODS The structural networks of 46 NTG patients and 19 age- and sex-matched healthy controls were constructed using diffusion tensor imaging, followed by graph theory analysis and correlation analysis of small-world properties with glaucoma clinical indicators. In addition, the network-based statistical analysis (NBS) method was used to compare structural network connectivity differences between NTG patients and healthy controls. RESULTS Structural brain networks in both NTG and NC groups exhibited small-world properties. However, the small-world index in the severe NTG group was reduced and correlated with a mean deviation of the visual field (MDVF) and retinal nerve fiber layer (RNFL) thickness. When compared to healthy controls, degree centrality and nodal efficiency in visual brain areas were significantly decreased, and betweenness centrality and nodal local efficiency in both visual and nonvisual brain areas were also significantly altered in NTG patients (all p < 0.05, FDR corrected). Furthermore, NTG patients exhibited increased structural connectivity in the occipitotemporal area, with the left fusiform gyrus (FFG.L) as the hub (p < 0.05). CONCLUSIONS NTG exhibited altered global properties and local properties of visual and cognitive-emotional brain areas, with enhanced structural connections within the occipitotemporal area. Moreover, the disrupted small-world properties of white matter might be imaging biomarkers for assessing NTG progression.
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Affiliation(s)
- Yin Wang
- Department of Radiology, Eye & ENT Hospital of Fudan University, Fudan University, Shanghai 200031, China (F.D.)
| | - Linying Guo
- Department of Radiology, Eye & ENT Hospital of Fudan University, Fudan University, Shanghai 200031, China (F.D.)
| | - Rong Wang
- Department of Radiology, Huashan Hospital of Fudan University, Fudan University, Shanghai 200040, China
| | - Yuzhe Wang
- Department of Radiology, Zhongshan Hospital of Fudan University, Fudan University, Shanghai 200032, China; (Y.W.)
| | - Fei Duan
- Department of Radiology, Eye & ENT Hospital of Fudan University, Fudan University, Shanghai 200031, China (F.D.)
| | - Yang Zhan
- Department of Radiology, Zhongshan Hospital of Fudan University, Fudan University, Shanghai 200032, China; (Y.W.)
| | - Jingfeng Cheng
- Department of Radiology, Eye & ENT Hospital of Fudan University, Fudan University, Shanghai 200031, China (F.D.)
| | - Xinghuai Sun
- Department of Ophthalmology & Visual Science, Eye & ENT Hospital of Fudan University, Fudan University, Shanghai 200031, China;
| | - Zuohua Tang
- Department of Radiology, Eye & ENT Hospital of Fudan University, Fudan University, Shanghai 200031, China (F.D.)
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Williamson BJ, Greiner HM, Kadis DS. Virtual lesions in MEG reveal increasing vulnerability of the language network from early childhood through adolescence. Nat Commun 2023; 14:7313. [PMID: 37951971 PMCID: PMC10640569 DOI: 10.1038/s41467-023-43165-7] [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: 12/21/2022] [Accepted: 11/02/2023] [Indexed: 11/14/2023] Open
Abstract
In childhood, language outcomes following brain injury are inversely related to age. Neuroimaging findings suggest that extensive representation and/or topological redundancy may confer the pediatric advantage. Here, we assess whole brain and language network resilience using in silico attacks, for 85 children participating in a magnetoencephalography (MEG) study. Nodes are targeted based on eigenvector centrality, betweenness centrality, or at random. The size of each connected component is assessed after iterated node removal; the percolation point, or moment of dis-integration, is defined as the first instance where the second largest component peaks in size. To overcome known effects of fixed thresholding on subsequent graph and resilience analyses, we study percolation across all possible network densities, within a Functional Data Analysis (FDA) framework. We observe age-related increases in vulnerability for random and betweenness centrality-based attacks for whole-brain and stories networks (adjusted-p < 0.05). Here we show that changes in topology underlie increasing language network vulnerability in development.
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Affiliation(s)
| | - Hansel M Greiner
- Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Darren S Kadis
- Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada.
- Department of Physiology, University of Toronto, Toronto, ON, Canada.
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Tu JC, Millar PR, Strain JF, Eck A, Adeyemo B, Daniels A, Karch C, Huey ED, McDade E, Day GS, Yakushev I, Hassenstab J, Morris J, Llibre-Guerra JJ, Ibanez L, Jucker M, Mendez PC, Bateman RJ, Perrin RJ, Benzinger T, Jack CR, Betzel R, Ances BM, Eggebrecht AT, Gordon BA, Wheelock MD. Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.29.564633. [PMID: 37961586 PMCID: PMC10634945 DOI: 10.1101/2023.10.29.564633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Given their essential role in neural communication, disruptions to these hubs have profound implications for overall brain network integrity and functionality. Hub disruption, or targeted impairment of functional connectivity at the hubs, is recognized in AD patients. Computational models paired with evidence from animal experiments hint at a mechanistic explanation, suggesting that these hubs may be preferentially targeted in neurodegeneration, due to their high neuronal activity levels-a phenomenon termed "activity-dependent degeneration". Yet, two critical issues were unresolved. First, past research hasn't definitively shown whether hub regions face a higher likelihood of impairment (targeted attack) compared to other regions or if impairment likelihood is uniformly distributed (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We applied a refined hub disruption index to determine the presence of targeted attacks in AD. Furthermore, we explored potential evidence for activity-dependent degeneration by evaluating if hub vulnerability is better explained by global connectivity or connectivity variations across functional systems, as well as comparing its timing relative to amyloid beta deposition in the brain. Our unique cohort of participants with autosomal dominant Alzheimer Disease (ADAD) allowed us to probe into the preclinical stages of AD to determine the hub disruption timeline in relation to expected symptom emergence. Our findings reveal a hub disruption pattern in ADAD aligned with targeted attacks, detectable even in pre-clinical stages. Notably, the disruption's severity amplified alongside symptomatic progression. Moreover, since excessive local neuronal activity has been shown to increase amyloid deposition and high connectivity regions show high level of neuronal activity, our observation that hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in Aβ PET cortical markers is consistent with the activity-dependent degeneration model. Intriguingly, these disruptions were discernible 8 years before the expected age of symptom onset. Taken together, our findings not only align with the targeted attack on hubs model but also suggest that activity-dependent degeneration might be the cause of hub vulnerability. This deepened understanding could be instrumental in refining diagnostic techniques and developing targeted therapeutic strategies for AD in the future.
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Affiliation(s)
- Jiaxin Cindy Tu
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Peter R Millar
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Jeremy F Strain
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Andrew Eck
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Babatunde Adeyemo
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Alisha Daniels
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Celeste Karch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Edward D Huey
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, 02912
| | - Eric McDade
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Gregory S Day
- Department of Neurology, Mayo Clinic College of Medicine, Jacksonville, FL, USA, 32224
| | - Igor Yakushev
- Department of Nuclear Medicine, Technical University of Munich, Munich, Germany, 81675
| | - Jason Hassenstab
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - John Morris
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Jorge J Llibre-Guerra
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Laura Ibanez
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA, 63108
- NeuroGenomics and Informatics Center, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Mathias Jucker
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany, 72076
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany, 72076
| | | | - Randell J Bateman
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Richard J Perrin
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
- Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Tammie Benzinger
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA 55905
| | - Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN USA, 47405
| | - Beau M Ances
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Adam T Eggebrecht
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Brian A Gordon
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA, 63108
| | - Muriah D Wheelock
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA, 63108
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Chappel-Farley MG, Adams JN, Betzel RF, Janecek JC, Sattari NS, Berisha DE, Meza NJ, Niknazar H, Kim S, Dave A, Chen IY, Lui KK, Neikrug AB, Benca RM, Yassa MA, Mander BA. Medial temporal lobe functional network architecture supports sleep-related emotional memory processing in older adults. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.27.564260. [PMID: 37961192 PMCID: PMC10634911 DOI: 10.1101/2023.10.27.564260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Memory consolidation occurs via reactivation of a hippocampal index during non-rapid eye movement slow-wave sleep (NREM SWS) which binds attributes of an experience existing within cortical modules. For memories containing emotional content, hippocampal-amygdala dynamics facilitate consolidation over a sleep bout. This study tested if modularity and centrality-graph theoretical measures that index the level of segregation/integration in a system and the relative import of its nodes-map onto central tenets of memory consolidation theory and sleep-related processing. Findings indicate that greater network integration is tied to overnight emotional memory retention via NREM SWS expression. Greater hippocampal and amygdala influence over network organization supports emotional memory retention, and hippocampal or amygdala control over information flow are differentially associated with distinct stages of memory processing. These centrality measures are also tied to the local expression and coupling of key sleep oscillations tied to sleep-dependent memory consolidation. These findings suggest that measures of intrinsic network connectivity may predict the capacity of brain functional networks to acquire, consolidate, and retrieve emotional memories.
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Affiliation(s)
- Miranda G. Chappel-Farley
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Jenna N. Adams
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Richard F. Betzel
- Department of Psychological and Brain Sciences, University of Indiana Bloomington, Bloomington IN, 47405
| | - John C. Janecek
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Negin S. Sattari
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
| | - Destiny E. Berisha
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Novelle J. Meza
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Hamid Niknazar
- Department of Cognitive Sciences, University of California Irvine, Irvine CA, 92697, USA
| | - Soyun Kim
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Abhishek Dave
- Department of Cognitive Sciences, University of California Irvine, Irvine CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
| | - Ivy Y. Chen
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
| | - Kitty K. Lui
- San Diego State University/University of California San Diego, Joint Doctoral Program in Clinical Psychology, San Diego, CA, 92093, USA
| | - Ariel B. Neikrug
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
| | - Ruth M. Benca
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, 53706, WI, USA
- Department of Psychiatry and Behavioral Medicine, Wake Forest University, Winston-Salem, NC, 27109, USA
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine CA, 92697, USA
| | - Michael A. Yassa
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine CA, 92697, USA
- Department of Neurology, University of California Irvine, Irvine CA, 92697, USA
| | - Bryce A. Mander
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
- Department of Cognitive Sciences, University of California Irvine, Irvine CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine CA, 92697, USA
- Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine CA, 92697, USA
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Liu H, Zheng H, Zhang G, Zhuang J, Li W, Wu B, Zheng W. A Graph Theory Study of Resting-State Functional MRI Connectivity in Children With Carbon Monoxide Poisoning. J Magn Reson Imaging 2023; 58:1452-1459. [PMID: 36994898 DOI: 10.1002/jmri.28706] [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: 07/16/2022] [Revised: 03/21/2023] [Accepted: 03/21/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND The effect of carbon monoxide (CO) poisoning on the topology of brain functional networks is unclear, especially in children whose brains are still developing. PURPOSE To investigate the topological alterations of the whole-brain functional connectome in children with CO poisoning and characterize its relationship with disease severity. STUDY TYPE Cross-sectional and prospective study. SUBJECTS A total of 26 patients with CO poisoning and 26 healthy controls. FIELD STRENGTH/SEQUENCE A 3.0 T MRI system/echo planar imaging (EPI) and 3D brain volume imaging (BRAVO) sequences. ASSESSMENT We used the network-based statistics (NBS) method to explore between-group differences in functional connectivity strength and a graph-theoretical-based analytic method to explore the topology of brain networks. STATISTICAL TESTS Student's t-test, chi-square test, NBS, Pearson correlation coefficient, and false discovery rate correction. The statistical significance threshold was set at P < 0.05. RESULTS The case group's brain functional network topology was impaired in comparison to the control group (reduced global efficiency and small-worldness, increased characteristic path length). According to node and edge analyses, the case group showed topologically damaged regions in the frontal lobe and basal ganglia, as well as neuronal circuits with weaker connections. Also, there was a significant correlation between the patients' coma time and the degree (r = -0.4564), efficiency (r = -0.4625), and characteristic path length (r = 0.4383) of the nodes in the left orbital inferior frontal gyrus. Carbon monoxide hemoglobin content (COHb) concentration and right rolandic operculum node characteristic path length (r = -0.3894) were significantly correlated. The node efficiency and node degree of the right middle frontal gyrus (r = 0.4447 and 0.4539) and right pallidum (r = 0.4136 and 0.4501) significantly correlated with the MMSE score. DATA CONCLUSION The brain network topology of CO poisoned children is damaged, which is manifested by reduced network integration and may lead to a series of clinical symptoms in patients. EVIDENCE LEVEL 2. TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- HongKun Liu
- Department of Radiology, Huizhou Central People's Hospital, Huizhou, Guangdong, China
| | - HongYi Zheng
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - GengBiao Zhang
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - JiaYan Zhuang
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - WeiJia Li
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - BiXia Wu
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - WenBin Zheng
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
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Bitra VR, Challa SR, Adiukwu PC, Rapaka D. Tau trajectory in Alzheimer's disease: Evidence from the connectome-based computational models. Brain Res Bull 2023; 203:110777. [PMID: 37813312 DOI: 10.1016/j.brainresbull.2023.110777] [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: 05/23/2023] [Revised: 07/08/2023] [Accepted: 10/06/2023] [Indexed: 10/11/2023]
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder with an impairment of cognition and memory. Current research on connectomics have now related changes in the network organization in AD to the patterns of accumulation and spread of amyloid and tau, providing insights into the neurobiological mechanisms of the disease. In addition, network analysis and modeling focus on particular use of graphs to provide intuition into key organizational principles of brain structure, that stipulate how neural activity propagates along structural connections. The utility of connectome-based computational models aids in early predicting, tracking the progression of biomarker-directed AD neuropathology. In this article, we present a short review of tau trajectory, the connectome changes in tau pathology, and the dependent recent connectome-based computational modelling approaches for tau spreading, reproducing pragmatic findings, and developing significant novel tau targeted therapies.
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Affiliation(s)
- Veera Raghavulu Bitra
- School of Pharmacy, Faculty of Health Sciences, University of Botswana, P/Bag-0022, Gaborone, Botswana.
| | - Siva Reddy Challa
- Department of Cancer Biology and Pharmacology, University of Illinois College of Medicine, Peoria, IL 61614, USA; KVSR Siddartha College of Pharmaceutical Sciences, Vijayawada, Andhra Pradesh, India
| | - Paul C Adiukwu
- School of Pharmacy, Faculty of Health Sciences, University of Botswana, P/Bag-0022, Gaborone, Botswana
| | - Deepthi Rapaka
- Pharmacology Division, D.D.T. College of Medicine, Gaborone, Botswana.
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Winters DE, Leopold DR, Sakai JT, Carter RM. Efficiency of Heterogenous Functional Connectomes Explains Variance in Callous-Unemotional Traits After Computational Lesioning of Cortical Midline and Salience Regions. Brain Connect 2023; 13:410-426. [PMID: 37221853 PMCID: PMC10517336 DOI: 10.1089/brain.2022.0074] [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] [Indexed: 05/25/2023] Open
Abstract
Introduction: Callous-unemotional (CU) traits are a youth antisocial phenotype hypothesized to be a result of differences in the integration of multiple brain systems. However, mechanistic insights into these brain systems are a continued challenge. Where prior work describes activation and connectivity, new mechanistic insights into the brain's functional connectome can be derived by removing nodes and quantifying changes in network properties (hereafter referred to as computational lesioning) to characterize connectome resilience and vulnerability. Methods: Here, we study the resilience of connectome integration in CU traits by estimating changes in efficiency after computationally lesioning individual-level connectomes. From resting-state data of 86 participants (48% female, age 14.52 ± 1.31) drawn from the Nathan Kline institute's Rockland study, individual-level connectomes were estimated using graphical lasso. Computational lesioning was conducted both sequentially and by targeting global and local hubs. Elastic net regression was applied to determine how these changes explained variance in CU traits. Follow-up analyses characterized modeled node hubs, examined moderation, determined impact of targeting, and decoded the brain mask by comparing regions to meta-analytic maps. Results: Elastic net regression revealed that computational lesioning of 23 nodes, network modularity, and Tanner stage explained variance in CU traits. Hub assignment of selected hubs differed at higher CU traits. No evidence for moderation between simulated lesioning and CU traits was found. Targeting global hubs increased efficiency and targeting local hubs had no effect at higher CU traits. Identified brain mask meta-analytically associated with more emotion and cognitive terms. Although reliable patterns were found across participants, adolescent brains were heterogeneous even for those with a similar CU traits score. Conclusion: Adolescent brain response to simulated lesioning revealed a pattern of connectome resiliency and vulnerability that explains variance in CU traits, which can aid prediction of youth at greater risk for higher CU traits.
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Affiliation(s)
- Drew E. Winters
- Department of Psychiatry, University of Colorado School of Medicine Anschutz Medical Campus, Aurora, Colorado, USA
| | - Daniel R. Leopold
- Department of Psychiatry, University of Colorado School of Medicine Anschutz Medical Campus, Aurora, Colorado, USA
| | - Joseph T. Sakai
- Department of Psychiatry, University of Colorado School of Medicine Anschutz Medical Campus, Aurora, Colorado, USA
| | - R. McKell Carter
- Department of Psychology & Neuroscience; Computer and Energy Engineering; University of Colorado Boulder, Boulder, Colorado, USA
- Institute of Cognitive Science; Computer and Energy Engineering; University of Colorado Boulder, Boulder, Colorado, USA
- Department of Electrical, Computer and Energy Engineering; University of Colorado Boulder, Boulder, Colorado, USA
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Hansen JY, Shafiei G, Voigt K, Liang EX, Cox SML, Leyton M, Jamadar SD, Misic B. Integrating multimodal and multiscale connectivity blueprints of the human cerebral cortex in health and disease. PLoS Biol 2023; 21:e3002314. [PMID: 37747886 PMCID: PMC10553842 DOI: 10.1371/journal.pbio.3002314] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 10/05/2023] [Accepted: 08/28/2023] [Indexed: 09/27/2023] Open
Abstract
The brain is composed of disparate neural populations that communicate and interact with one another. Although fiber bundles, similarities in molecular architecture, and synchronized neural activity all reflect how brain regions potentially interact with one another, a comprehensive study of how all these interregional relationships jointly reflect brain structure and function remains missing. Here, we systematically integrate 7 multimodal, multiscale types of interregional similarity ("connectivity modes") derived from gene expression, neurotransmitter receptor density, cellular morphology, glucose metabolism, haemodynamic activity, and electrophysiology in humans. We first show that for all connectivity modes, feature similarity decreases with distance and increases when regions are structurally connected. Next, we show that connectivity modes exhibit unique and diverse connection patterns, hub profiles, spatial gradients, and modular organization. Throughout, we observe a consistent primacy of molecular connectivity modes-namely correlated gene expression and receptor similarity-that map onto multiple phenomena, including the rich club and patterns of abnormal cortical thickness across 13 neurological, psychiatric, and neurodevelopmental disorders. Finally, to construct a single multimodal wiring map of the human cortex, we fuse all 7 connectivity modes and show that the fused network maps onto major organizational features of the cortex including structural connectivity, intrinsic functional networks, and cytoarchitectonic classes. Altogether, this work contributes to the integrative study of interregional relationships in the human cerebral cortex.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Katharina Voigt
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Emma X. Liang
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | | | - Marco Leyton
- Montréal Neurological Institute, McGill University, Montréal, Canada
- Department of Psychiatry, McGill University, Montréal, Canada
| | - Sharna D. Jamadar
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Canada
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Kohsaka H. Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion. Front Neural Circuits 2023; 17:1175899. [PMID: 37711343 PMCID: PMC10499525 DOI: 10.3389/fncir.2023.1175899] [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: 02/28/2023] [Accepted: 06/13/2023] [Indexed: 09/16/2023] Open
Abstract
The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.
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Affiliation(s)
- Hiroshi Kohsaka
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Chofu, Tokyo, Japan
- Department of Complexity Science and Engineering, Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan
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Fan L, Li Y, Huang ZG, Zhang W, Wu X, Liu T, Wang J. Low-frequency repetitive transcranial magnetic stimulation alters the individual functional dynamical landscape. Cereb Cortex 2023; 33:9583-9598. [PMID: 37376783 DOI: 10.1093/cercor/bhad228] [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: 04/26/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/29/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive approach to modulate brain activity and behavior in humans. Still, how individual resting-state brain dynamics after rTMS evolves across different functional configurations is rarely studied. Here, using resting state fMRI data from healthy subjects, we aimed to examine the effects of rTMS to individual large-scale brain dynamics. Using Topological Data Analysis based Mapper approach, we construct the precise dynamic mapping (PDM) for each participant. To reveal the relationship between PDM and canonical functional representation of the resting brain, we annotated the graph using relative activation proportion of a set of large-scale resting-state networks (RSNs) and assigned the single brain volume to corresponding RSN-dominant or a hub state (not any RSN was dominant). Our results show that (i) low-frequency rTMS could induce changed temporal evolution of brain states; (ii) rTMS didn't alter the hub-periphery configurations underlined resting-state brain dynamics; and (iii) the rTMS effects on brain dynamics differ across the left frontal and occipital lobe. In conclusion, low-frequency rTMS significantly alters the individual temporo-spatial dynamics, and our finding further suggested a potential target-dependent alteration of brain dynamics. This work provides a new perspective to comprehend the heterogeneous effect of rTMS.
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Affiliation(s)
- Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Zi-Gang Huang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Wenlong Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Xiaofeng Wu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
- The Key Laboratory of Neuro-Informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China
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Hadjiabadi D, Soltesz I. From single-neuron dynamics to higher-order circuit motifs in control and pathological brain networks. J Physiol 2023; 601:3011-3024. [PMID: 35815823 PMCID: PMC10655857 DOI: 10.1113/jp282749] [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: 04/15/2022] [Accepted: 06/27/2022] [Indexed: 11/08/2022] Open
Abstract
The convergence of advanced single-cell in vivo functional imaging techniques, computational modelling tools and graph-based network analytics has heralded new opportunities to study single-cell dynamics across large-scale networks, providing novel insights into principles of brain communication and pointing towards potential new strategies for treating neurological disorders. A major recent finding has been the identification of unusually richly connected hub cells that have capacity to synchronize networks and may also be critical in network dysfunction. While hub neurons are traditionally defined by measures that consider solely the number and strength of connections, novel higher-order graph analytics now enables the mining of massive networks for repeating subgraph patterns called motifs. As an illustration of the power offered by higher-order analysis of neuronal networks, we highlight how recent methodological advances uncovered a new functional cell type, the superhub, that is predicted to play a major role in regulating network dynamics. Finally, we discuss open questions that will be critical for assessing the importance of higher-order cellular-scale network analytics in understanding brain function in health and disease.
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Affiliation(s)
- Darian Hadjiabadi
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Ivan Soltesz
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
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Voon NS, Manan HA, Yahya N. Role of resting-state functional MRI in detecting brain functional changes following radiotherapy for head and neck cancer: a systematic review and meta-analysis. Strahlenther Onkol 2023; 199:706-717. [PMID: 37280382 DOI: 10.1007/s00066-023-02089-3] [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: 12/25/2022] [Accepted: 04/23/2023] [Indexed: 06/08/2023]
Abstract
PURPOSE Increasing evidence implicates changes in brain function following radiotherapy for head and neck cancer as precursors for brain dysfunction. These changes may thus be used as biomarkers for early detection. This review aimed to determine the role of resting-state functional magnetic resonance imaging (rs-fMRI) in detecting brain functional changes. METHODS A systematic search was performed in the PubMed, Scopus, and Web of Science (WoS) databases in June 2022. Patients with head and neck cancer treated with radiotherapy and periodic rs-fMRI assessments were included. A meta-analysis was performed to determine the potential of rs-fMRI for detecting brain changes. RESULTS Ten studies with a total of 513 subjects (head and neck cancer patients, n = 437; healthy controls, n = 76) were included. A significance of rs-fMRI for detecting brain changes in the temporal and frontal lobes, cingulate cortex, and cuneus was demonstrated in most studies. These changes were reported to be associated with dose (6/10 studies) and latency (4/10 studies). A strong effect size (r = 0.71, p < 0.001) between rs-fMRI and brain changes was also reported, suggesting rs-fMRI's capability for monitoring brain alterations. CONCLUSION Resting-state functional MRI is a promising tool for detecting brain functional changes following head and neck radiotherapy. These changes are correlated with latency and prescription dose.
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Affiliation(s)
- Noor Shatirah Voon
- Diagnostic Imaging and Radiotherapy, Centre of Diagnostic, Therapeutic and Investigative Sciences, Faculty of Health Sciences, National University of Malaysia, Jalan Raja Muda Aziz, 50300, Kuala Lumpur, Malaysia
- Department of Radiotherapy & Oncology, National Cancer Institute, Putrajaya, Malaysia
| | - Hanani Abdul Manan
- Functional Image Processing Laboratory, Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Cheras, 56000, Kuala Lumpur, Malaysia
| | - Noorazrul Yahya
- Diagnostic Imaging and Radiotherapy, Centre of Diagnostic, Therapeutic and Investigative Sciences, Faculty of Health Sciences, National University of Malaysia, Jalan Raja Muda Aziz, 50300, Kuala Lumpur, Malaysia.
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Wesley MJ, Lile JA. Combining noninvasive brain stimulation with behavioral pharmacology methods to study mechanisms of substance use disorder. Front Neurosci 2023; 17:1150109. [PMID: 37554294 PMCID: PMC10405288 DOI: 10.3389/fnins.2023.1150109] [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: 01/23/2023] [Accepted: 07/06/2023] [Indexed: 08/10/2023] Open
Abstract
Psychotropic drugs and transcranial magnetic stimulation (TMS) are effective for treating certain psychiatric conditions. Drugs and TMS have also been used as tools to explore the relationship between brain function and behavior in humans. Combining centrally acting drugs and TMS has proven useful for characterizing the neural basis of movement. This combined intervention approach also holds promise for improving our understanding of the mechanisms underlying disordered behavior associated with psychiatric conditions, including addiction, though challenges exist. For example, altered neocortical function has been implicated in substance use disorder, but the relationship between acute neuromodulation of neocortex with TMS and direct effects on addiction-related behaviors is not well established. We propose that the combination of human behavioral pharmacology methods with TMS can be leveraged to help establish these links. This perspective article describes an ongoing study that combines the administration of delta-9-tetrahydrocannabinol (THC), the main psychoactive compound in cannabis, with neuroimaging-guided TMS in individuals with problematic cannabis use. The study examines the impact of the left dorsolateral prefrontal cortex (DLPFC) stimulation on cognitive outcomes impacted by THC intoxication, including the subjective response to THC and the impairing effects of THC on behavioral performance. A framework for integrating TMS with human behavioral pharmacology methods, along with key details of the study design, are presented. We also discuss challenges, alternatives, and future directions.
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Affiliation(s)
- Michael J. Wesley
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, United States
- Department of Psychiatry, College of Medicine, University of Kentucky, Lexington, KY, United States
- Department of Psychology, College of Arts and Sciences, University of Kentucky, Lexington, KY, United States
| | - Joshua A. Lile
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, United States
- Department of Psychiatry, College of Medicine, University of Kentucky, Lexington, KY, United States
- Department of Psychology, College of Arts and Sciences, University of Kentucky, Lexington, KY, United States
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43
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Shamir I, Assaf Y. Expanding connectomics to the laminar level: A perspective. Netw Neurosci 2023; 7:377-388. [PMID: 37397881 PMCID: PMC10312257 DOI: 10.1162/netn_a_00304] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 12/15/2022] [Indexed: 11/10/2023] Open
Abstract
Despite great progress in uncovering the complex connectivity patterns of the human brain over the last two decades, the field of connectomics still experiences a bias in its viewpoint of the cerebral cortex. Due to a lack of information regarding exact end points of fiber tracts inside cortical gray matter, the cortex is commonly reduced to a single homogenous unit. Concurrently, substantial developments have been made over the past decade in the use of relaxometry and particularly inversion recovery imaging for exploring the laminar microstructure of cortical gray matter. In recent years, these developments have culminated in an automated framework for cortical laminar composition analysis and visualization, followed by studies of cortical dyslamination in epilepsy patients and age-related differences in laminar composition in healthy subjects. This perspective summarizes the developments and remaining challenges of multi-T1 weighted imaging of cortical laminar substructure, the current limitations in structural connectomics, and the recent progress in integrating these fields into a new model-based subfield termed 'laminar connectomics'. In the coming years, we predict an increased use of similar generalizable, data-driven models in connectomics with the purpose of integrating multimodal MRI datasets and providing a more nuanced and detailed characterization of brain connectivity.
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Affiliation(s)
- Ittai Shamir
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yaniv Assaf
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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44
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Garcia-Ramos C, Adluru N, Chu DY, Nair V, Adluru A, Nencka A, Maganti R, Mathis J, Conant LL, Alexander AL, Prabhakaran V, Binder JR, Meyerand ME, Hermann B, Struck AF. Multi-shell connectome DWI-based graph theory measures for the prediction of temporal lobe epilepsy and cognition. Cereb Cortex 2023; 33:8056-8065. [PMID: 37067514 PMCID: PMC10267614 DOI: 10.1093/cercor/bhad098] [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: 11/11/2022] [Revised: 02/28/2023] [Accepted: 03/02/2023] [Indexed: 04/18/2023] Open
Abstract
Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a network disorder, which makes graph theory (GT) a practical approach to understand it. Multi-shell diffusion-weighted imaging (DWI) was obtained from 89 TLE and 50 controls. GT measures extracted from harmonized DWI matrices were used as factors in a support vector machine (SVM) analysis to discriminate between groups, and in a k-means algorithm to find intrinsic structural phenotypes within TLE. SVM was able to predict group membership (mean accuracy = 0.70, area under the curve (AUC) = 0.747, Brier score (BS) = 0.264) using 10-fold cross-validation. In addition, k-means clustering identified 2 TLE clusters: 1 similar to controls, and 1 dissimilar. Clusters were significantly different in their distribution of cognitive phenotypes, with the Dissimilar cluster containing the majority of TLE with cognitive impairment (χ2 = 6.641, P = 0.036). In addition, cluster membership showed significant correlations between GT measures and clinical variables. Given that SVM classification seemed driven by the Dissimilar cluster, SVM analysis was repeated to classify Dissimilar versus Similar + Controls with a mean accuracy of 0.91 (AUC = 0.957, BS = 0.189). Altogether, the pattern of results shows that GT measures based on connectome DWI could be significant factors in the search for clinical and neurobehavioral biomarkers in TLE.
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Affiliation(s)
- Camille Garcia-Ramos
- Department of Neurology, University of Wisconsin-Madison, Medical Foundation Centennial Building, 1685 Highland Ave, Madison, WI 53705-2281, United States
| | - Nagesh Adluru
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, United States
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Ave, Madison, WI 53705, United States
| | - Daniel Y Chu
- Department of Neurology, University of Wisconsin-Madison, Medical Foundation Centennial Building, 1685 Highland Ave, Madison, WI 53705-2281, United States
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, United States
| | - Veena Nair
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, United States
| | - Anusha Adluru
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, United States
| | - Andrew Nencka
- Department of Radiology, Medical College of Wisconsin, 9200 W. Wisconsin Ave. Milwaukee, WI 53226, United States
| | - Rama Maganti
- Department of Neurology, University of Wisconsin-Madison, Medical Foundation Centennial Building, 1685 Highland Ave, Madison, WI 53705-2281, United States
| | - Jedidiah Mathis
- Department of Neurology, Medical College of Wisconsin, 9200 W. Wisconsin Ave. Milwaukee, WI 53226, United States
| | - Lisa L Conant
- Department of Neurology, Medical College of Wisconsin, 9200 W. Wisconsin Ave. Milwaukee, WI 53226, United States
| | - Andrew L Alexander
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Ave, Madison, WI 53705, United States
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Ave, Rm 1005, Madison, WI 53705-2275, United States
| | - Vivek Prabhakaran
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, United States
| | - Jeffrey R Binder
- Department of Neurology, Medical College of Wisconsin, 9200 W. Wisconsin Ave. Milwaukee, WI 53226, United States
| | - Mary E Meyerand
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Ave, Rm 1005, Madison, WI 53705-2275, United States
| | - Bruce Hermann
- Department of Neurology, University of Wisconsin-Madison, Medical Foundation Centennial Building, 1685 Highland Ave, Madison, WI 53705-2281, United States
| | - Aaron F Struck
- Department of Neurology, University of Wisconsin-Madison, Medical Foundation Centennial Building, 1685 Highland Ave, Madison, WI 53705-2281, United States
- William S. Middleton VA Hospital, 2500 Overlook Terrace, Madison, WI 53705, United States
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45
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Baker CM, Gong Y. Identifying properties of pattern completion neurons in a computational model of the visual cortex. PLoS Comput Biol 2023; 19:e1011167. [PMID: 37279242 DOI: 10.1371/journal.pcbi.1011167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 05/09/2023] [Indexed: 06/08/2023] Open
Abstract
Neural ensembles are found throughout the brain and are believed to underlie diverse cognitive functions including memory and perception. Methods to activate ensembles precisely, reliably, and quickly are needed to further study the ensembles' role in cognitive processes. Previous work has found that ensembles in layer 2/3 of the visual cortex (V1) exhibited pattern completion properties: ensembles containing tens of neurons were activated by stimulation of just two neurons. However, methods that identify pattern completion neurons are underdeveloped. In this study, we optimized the selection of pattern completion neurons in simulated ensembles. We developed a computational model that replicated the connectivity patterns and electrophysiological properties of layer 2/3 of mouse V1. We identified ensembles of excitatory model neurons using K-means clustering. We then stimulated pairs of neurons in identified ensembles while tracking the activity of the entire ensemble. Our analysis of ensemble activity quantified a neuron pair's power to activate an ensemble using a novel metric called pattern completion capability (PCC) based on the mean pre-stimulation voltage across the ensemble. We found that PCC was directly correlated with multiple graph theory parameters, such as degree and closeness centrality. To improve selection of pattern completion neurons in vivo, we computed a novel latency metric that was correlated with PCC and could potentially be estimated from modern physiological recordings. Lastly, we found that stimulation of five neurons could reliably activate ensembles. These findings can help researchers identify pattern completion neurons to stimulate in vivo during behavioral studies to control ensemble activation.
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Affiliation(s)
- Casey M Baker
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America
| | - Yiyang Gong
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America
- Department of Neurobiology, Duke University, Durham, North Carolina, United States of America
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Yu Y, Qiu M, Zou W, Zhao Y, Tang Y, Tian J, Chen X, Qiu W. Impaired rich-club connectivity in childhood absence epilepsy. Front Neurol 2023; 14:1135305. [PMID: 37251238 PMCID: PMC10213928 DOI: 10.3389/fneur.2023.1135305] [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: 12/31/2022] [Accepted: 04/12/2023] [Indexed: 05/31/2023] Open
Abstract
Introduction Childhood absence epilepsy (CAE) is a well-known pediatric epilepsy syndrome. Recent evidence has shown the presence of a disrupted structural brain network in CAE. However, little is known about the rich-club topology. This study aimed to explore the rich-club alterations in CAE and their association with clinical characteristics. Methods Diffusion tensor imaging (DTI) datasets were acquired in a sample of 30 CAE patients and 31 healthy controls. A structural network was derived from DTI data for each participant using probabilistic tractography. Then, the rich-club organization was examined, and the network connections were divided into rich-club connections, feeder connections, and local connections. Results Our results confirmed a less dense whole-brain structural network in CAE with lower network strength and global efficiency. In addition, the optimal organization of small-worldness was also damaged. A small number of highly connected and central brain regions were identified to form the rich-club organization in both patients and controls. However, patients exhibited a significantly reduced rich-club connectivity, while the other class of feeder and local connections was relatively spared. Moreover, the lower levels of rich-club connectivity strength were statistically correlated with disease duration. Discussion Our reports suggest that CAE is characterized by abnormal connectivity concentrated to rich-club organizations and might contribute to understanding the pathophysiological mechanism of CAE.
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Affiliation(s)
- Yadong Yu
- Department of Neurology, Lianshui County People's Hospital, Huai'an, China
| | - Mengdi Qiu
- Department of Neurology, The Fifth People's Hospital of Huai'an, Huai'an, China
| | - Wenwei Zou
- Department of Neurology, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, China
| | - Ying Zhao
- Department of Neurology, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, China
| | - Yan Tang
- Department of Neurology, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, China
| | - Jisha Tian
- Department of Neurology, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, China
| | - Xiaoyu Chen
- Department of Radiology, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, China
| | - Wenchao Qiu
- Department of Neurology, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, China
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Prasad K, Rubin J, Iyengar S, Cape J. Global network disorganization underlying psychosis high risk states. Schizophr Res 2023; 255:67-68. [PMID: 36965361 DOI: 10.1016/j.schres.2023.03.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 03/18/2023] [Indexed: 03/27/2023]
Affiliation(s)
- Konasale Prasad
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America; VA Pittsburgh Healthcare System, Pittsburgh, PA, United States of America; Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, PA, United States of America.
| | - Jonathan Rubin
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Joshua Cape
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, United States of America; Department of Statistics, University of Wisconsin-Madison, Madison, WI, United States of America
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48
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Neuronal Cultures: Exploring Biophysics, Complex Systems, and Medicine in a Dish. BIOPHYSICA 2023. [DOI: 10.3390/biophysica3010012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Neuronal cultures are one of the most important experimental models in modern interdisciplinary neuroscience, allowing to investigate in a control environment the emergence of complex behavior from an ensemble of interconnected neurons. Here, I review the research that we have conducted at the neurophysics laboratory at the University of Barcelona over the last 15 years, describing first the neuronal cultures that we prepare and the associated tools to acquire and analyze data, to next delve into the different research projects in which we actively participated to progress in the understanding of open questions, extend neuroscience research on new paradigms, and advance the treatment of neurological disorders. I finish the review by discussing the drawbacks and limitations of neuronal cultures, particularly in the context of brain-like models and biomedicine.
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Wang Y, Yan G, Wang X, Li S, Peng L, Tudorascu DL, Zhang T. A variational Bayesian approach to identifying whole-brain directed networks with fMRI data. Ann Appl Stat 2023. [DOI: 10.1214/22-aoas1640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Yaotian Wang
- Department of Statistics, University of Pittsburgh
| | - Guofen Yan
- Department of Public Health Sciences, University of Virginia
| | - Xiaofeng Wang
- Department of Quantitative Health Sciences, Cleveland Clinic
| | - Shuoran Li
- Department of Statistics, University of Pittsburgh
| | - Lingyi Peng
- Department of Biostatistics, University of Pittsburgh
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A critical role of brain network architecture in a continuum model of autism spectrum disorders spanning from healthy individuals with genetic liability to individuals with ASD. Mol Psychiatry 2023; 28:1210-1218. [PMID: 36575304 PMCID: PMC10005951 DOI: 10.1038/s41380-022-01916-w] [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: 09/02/2021] [Revised: 11/21/2022] [Accepted: 12/09/2022] [Indexed: 12/28/2022]
Abstract
Studies have shown cortical alterations in individuals with autism spectrum disorders (ASD) as well as in individuals with high polygenic risk for ASD. An important addition to the study of altered cortical anatomy is the investigation of the underlying brain network architecture that may reveal brain-wide mechanisms in ASD and in polygenic risk for ASD. Such an approach has been proven useful in other psychiatric disorders by revealing that brain network architecture shapes (to an extent) the disorder-related cortical alterations. This study uses data from a clinical dataset-560 male subjects (266 individuals with ASD and 294 healthy individuals, CTL, mean age at 17.2 years) from the Autism Brain Imaging Data Exchange database, and data of 391 healthy individuals (207 males, mean age at 12.1 years) from the Pediatric Imaging, Neurocognition and Genetics database. ASD-related cortical alterations (group difference, ASD-CTL, in cortical thickness) and cortical correlates of polygenic risk for ASD were assessed, and then statistically compared with structural connectome-based network measures (such as hubs) using spin permutation tests. Next, we investigated whether polygenic risk for ASD could be predicted by network architecture by building machine-learning based prediction models, and whether the top predictors of the model were identified as disease epicenters of ASD. We observed that ASD-related cortical alterations as well as cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. We also observed that age progression of ASD-related cortical alterations and cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. Further investigation revealed that structural connectomes predicted polygenic risk for ASD (r = 0.30, p < 0.0001), and two brain regions (the left inferior parietal and left suparmarginal) with top predictive connections were identified as disease epicenters of ASD. Our study highlights a critical role of network architecture in a continuum model of ASD spanning from healthy individuals with genetic risk to individuals with ASD. Our study also highlights the strength of investigating polygenic risk scores in addition to multi-modal neuroimaging measures to better understand the interplay between genetic risk and brain alterations associated with ASD.
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