1
|
Li M, Lebois LAM, Ridgewell C, Palermo CA, Winternitz S, Liu H, Kaufman M, Shinn AK. Functional connectivity of the auditory cortex in women with trauma-related disorders who hear voices. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00167-8. [PMID: 38944384 DOI: 10.1016/j.bpsc.2024.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/06/2024] [Accepted: 06/21/2024] [Indexed: 07/01/2024]
Abstract
BACKGROUND 'Voice-hearing' (VH) is a transdiagnostic experience that is common in trauma-related disorders (trauma-D). However, the neural substrates underlying trauma-related VH remain largely unexplored. While auditory perceptual dysfunction is among the abnormalities implicated in schizophrenia VH, whether VH in trauma-D also involves auditory perceptual alterations is unknown. METHODS We investigated auditory cortex (AC)-related functional connectivity (FC) in n=65 women with trauma-D related to childhood abuse with varying severities of VH. Using a novel, computationally-driven and individual-specific method of functionally parcellating the brain, we calculated the FC of two distinct AC subregions-Heschl's gyrus (HG, corresponding to primary AC) and lateral superior temporal gyrus (lSTG, in non-primary AC)- with both the cerebrum and cerebellum. We then measured the association between VH severity and FC using leave-one-out cross validation within the cerebrum, and voxel-wise multiple regression analyses in the cerebellum. RESULTS We found that VH severity positively correlated with left lSTG-frontoparietal network FC, while it negatively correlated with FC between left lSTG and both cerebral and cerebellar representations of the default mode network. VH severity was not predicted by FC of left HG or right AC subregions. CONCLUSIONS Our findings point to altered interactions between auditory perceptual processing and higher-level processes related to self-reference and executive functioning. This is the first study to show alterations in auditory cortical connectivity in trauma-related VH. While VH in trauma-D appears to be mediated by brain networks that are also implicated in schizophrenia VH, the results suggest a unique mechanism that could distinguish VH in trauma-D.
Collapse
Affiliation(s)
- Meiling Li
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China
| | - Lauren A M Lebois
- Depression and Anxiety Disorders Division, McLean Hospital, Belmont, MA; Department of Psychiatry, Harvard Medical School, Boston, MA
| | | | - Cori A Palermo
- Depression and Anxiety Disorders Division, McLean Hospital, Belmont, MA
| | - Sherry Winternitz
- Depression and Anxiety Disorders Division, McLean Hospital, Belmont, MA; Department of Psychiatry, Harvard Medical School, Boston, MA
| | - Hesheng Liu
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China; Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China
| | - Milissa Kaufman
- Depression and Anxiety Disorders Division, McLean Hospital, Belmont, MA; Department of Psychiatry, Harvard Medical School, Boston, MA
| | - Ann K Shinn
- Psychotic Disorders Division, McLean Hospital, Belmont, MA; Department of Psychiatry, Harvard Medical School, Boston, MA.
| |
Collapse
|
2
|
Huang J, Ren J, Xie W, Pan R, Xu N, Liu H. Personalised functional imaging-guided multitarget continuous theta burst stimulation for post-stroke aphasia: study protocol for a randomised controlled trial. BMJ Open 2024; 14:e081847. [PMID: 38754874 PMCID: PMC11097845 DOI: 10.1136/bmjopen-2023-081847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 04/29/2024] [Indexed: 05/18/2024] Open
Abstract
INTRODUCTION Continuous theta burst stimulation (cTBS), a form of repetitive transcranial magnetic stimulation (rTMS), targeting the language network in the right hemisphere of post-stroke aphasia (PSA) patients shows promising results in clinical trials. However, existing PSA studies have focused on single-target rTMS, leaving unexplored the potential benefits of multitarget brain stimulation. Consequently, there is a need for a randomised clinical trial aimed to evaluate the efficacy and safety of cTBS targeting on multiple critical nodes in the language network for PSA. METHODS AND ANALYSIS This is a prospective, multicentre, double-blind, two-arm parallel-group, sham-controlled randomised trial. The study will include a total of 60 participants who will be randomly assigned in a 1:1 ratio to either the active cTBS group or the sham cTBS group. Using precision resting-state functional MRI for each participant, we will map personalised language networks and design personalised targets in the inferior frontal gyrus, superior temporal gyrus and superior frontal gyrus. Participants will undergo a 3-week cTBS intervention targeting the three personalised targets, coupled with speech and language therapy. The primary outcome is the change in the Western Aphasia Battery-Revised aphasia quotient score among participants after a 3-week treatment. Secondary outcomes include Boston Diagnostic Aphasia Examination severity ratings, Token Test and the Chinese-version of the Stroke and Aphasia Quality of Life Scale 39-generic version. ETHICS AND DISSEMINATION The study has been approved by the ethics committees of Affiliated Hospital of Hebei University, Hebei General Hospital and Affiliated Hospital of Chengde Medical University. The findings of this study will be reported in peer-reviewed scientific journals. TRIAL REGISTRATION NUMBER The study has been registered on ClinicalTrials.gov (NCT05957445).
Collapse
Affiliation(s)
- Jianting Huang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Division of Brain Sciences, Changping Laboratory, Beijing, China
| | - Jianxun Ren
- Division of Brain Sciences, Changping Laboratory, Beijing, China
| | - Wuxiang Xie
- Peking University Clinical Research Institute, Peking University Health Science Center, Beijing, China
| | | | - Na Xu
- Division of Brain Sciences, Changping Laboratory, Beijing, China
| | - Hesheng Liu
- Division of Brain Sciences, Changping Laboratory, Beijing, China
- Biomedical Pioneering Innovation Center, Peking University, Beijing, China
| |
Collapse
|
3
|
Hakonen M, Dahmani L, Lankinen K, Ren J, Barbaro J, Blazejewska A, Cui W, Kotlarz P, Li M, Polimeni JR, Turpin T, Uluç I, Wang D, Liu H, Ahveninen J. Individual connectivity-based parcellations reflect functional properties of human auditory cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576475. [PMID: 38293021 PMCID: PMC10827228 DOI: 10.1101/2024.01.20.576475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Neuroimaging studies of the functional organization of human auditory cortex have focused on group-level analyses to identify tendencies that represent the typical brain. Here, we mapped auditory areas of the human superior temporal cortex (STC) in 30 participants by combining functional network analysis and 1-mm isotropic resolution 7T functional magnetic resonance imaging (fMRI). Two resting-state fMRI sessions, and one or two auditory and audiovisual speech localizer sessions, were collected on 3-4 separate days. We generated a set of functional network-based parcellations from these data. Solutions with 4, 6, and 11 networks were selected for closer examination based on local maxima of Dice and Silhouette values. The resulting parcellation of auditory cortices showed high intraindividual reproducibility both between resting state sessions (Dice coefficient: 69-78%) and between resting state and task sessions (Dice coefficient: 62-73%). This demonstrates that auditory areas in STC can be reliably segmented into functional subareas. The interindividual variability was significantly larger than intraindividual variability (Dice coefficient: 57%-68%, p<0.001), indicating that the parcellations also captured meaningful interindividual variability. The individual-specific parcellations yielded the highest alignment with task response topographies, suggesting that individual variability in parcellations reflects individual variability in auditory function. Connectional homogeneity within networks was also highest for the individual-specific parcellations. Furthermore, the similarity in the functional parcellations was not explainable by the similarity of macroanatomical properties of auditory cortex. Our findings suggest that individual-level parcellations capture meaningful idiosyncrasies in auditory cortex organization.
Collapse
Affiliation(s)
- M Hakonen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - L Dahmani
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - K Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - J Ren
- Division of Brain Sciences, Changping Laboratory, Beijing, China
| | - J Barbaro
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
| | - A Blazejewska
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - W Cui
- Division of Brain Sciences, Changping Laboratory, Beijing, China
| | - P Kotlarz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
| | - M Li
- Division of Brain Sciences, Changping Laboratory, Beijing, China
| | - J R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - T Turpin
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
| | - I Uluç
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - D Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - H Liu
- Division of Brain Sciences, Changping Laboratory, Beijing, China
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
| | - J Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
4
|
Wang F, Ren J, Cui W, Zhou Y, Yao P, Lai X, Pang Y, Chen Z, Lin Y, Liu H. Verbal memory network mapping in individual patients predicts postoperative functional impairments. Hum Brain Mapp 2024; 45:e26691. [PMID: 38703114 PMCID: PMC11069337 DOI: 10.1002/hbm.26691] [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: 12/13/2023] [Revised: 03/15/2024] [Accepted: 04/08/2024] [Indexed: 05/06/2024] Open
Abstract
Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter-individual variability in functional networks and brain function-structural dissociations pose challenges when relying solely on group-level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting-state functional MRI (rs-fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30-min rs-fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs-fMRI data for each patient. The accuracy of PVMN was assessed by comparing post-operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group-level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra-temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group-level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = -0.39, p = .038; group-level atlas: r = -0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs-fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals.
Collapse
Affiliation(s)
- Feng Wang
- Department of Neurosurgery, Neurosurgery Research InstituteThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
| | | | | | | | - Peisen Yao
- Department of Neurosurgery, Neurosurgery Research InstituteThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Department of Neurosurgery, Binhai Branch of National Regional Medical CenterThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Fujian Provincial Institutes of Brain Disorders and Brain SciencesThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
| | - Xuemiao Lai
- Department of Neurosurgery, Neurosurgery Research InstituteThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Department of Neurosurgery, Binhai Branch of National Regional Medical CenterThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Fujian Provincial Institutes of Brain Disorders and Brain SciencesThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
| | - Yue Pang
- Department of Neurosurgery, Neurosurgery Research InstituteThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Department of Neurosurgery, Binhai Branch of National Regional Medical CenterThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Fujian Provincial Institutes of Brain Disorders and Brain SciencesThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
| | - Zhili Chen
- Department of Neurosurgery, Neurosurgery Research InstituteThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Department of Neurosurgery, Binhai Branch of National Regional Medical CenterThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Fujian Provincial Institutes of Brain Disorders and Brain SciencesThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
| | - Yuanxiang Lin
- Department of Neurosurgery, Neurosurgery Research InstituteThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Department of Neurosurgery, Binhai Branch of National Regional Medical CenterThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
- Fujian Provincial Institutes of Brain Disorders and Brain SciencesThe First Affiliated Hospital of Fujian Medical UniversityFuzhouChina
| | - Hesheng Liu
- Changping LaboratoryBeijingChina
- Biomedical Pioneering Innovation Center (BIOPIC)Peking UniversityBeijingChina
| |
Collapse
|
5
|
Guo Y, Ren J, Cui W, Dahmani L, Wang D, Fu X, Li M, Li S, Zhang Y, Lin X, Zhen Z, Xu Y, Xie D, Guan H, Yi F, Wang J, Shi Q, Liu H. Personalized brain MRI revealed distinct functional and anatomical disruptions in Creutzfeldt-Jakob disease and Alzheimer's disease. CNS Neurosci Ther 2024; 30:e14404. [PMID: 37577861 PMCID: PMC10848072 DOI: 10.1111/cns.14404] [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: 04/18/2023] [Revised: 07/01/2023] [Accepted: 07/31/2023] [Indexed: 08/15/2023] Open
Abstract
AIMS Creutzfeldt-Jakob disease (CJD) is a lethal neurodegenerative disorder, which leads to a rapidly progressive dementia. This study aimed to examine the cortical alterations in CJD, changes in these brain characteristics over time, and the differences between CJD and Alzheimer's disease (AD) that show similar clinical manifestations. METHODS To obtain reliable, subject-specific functional measures, we acquired 24 min of resting-state fMRI data from each subject. We applied an individual-based approach to characterize the functional brain organization of 10 patients with CJD, 8 matched patients with AD, and 8 normal controls. We measured cortical atrophy as well as disruption in resting-state functional connectivity (rsFC) and then investigated longitudinal brain changes in a subset of CJD patients. RESULTS CJD was associated with widespread cortical thinning and weakened rsFC. Compared with AD, CJD showed distinct atrophy patterns and greater disruptions in rsFC. Moreover, the longitudinal data demonstrated that the progressive cortical thinning and disruption in rsFC mainly affected the association rather than the primary cortex in CJD. CONCLUSIONS CJD shows unique anatomical and functional disruptions in the cerebral cortex, distinct from AD. Rapid progression of CJD affects both the cortical thickness and rsFC in the association cortex.
Collapse
Affiliation(s)
- Yanjun Guo
- Department of NeurologyBeijing Tongren Hospital, Capital Medical UniversityBeijingChina
| | | | - Weigang Cui
- School of Engineering MedicineBeihang UniversityBeijingChina
| | - Louisa Dahmani
- Department of RadiologyAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusettsUSA
| | - Danhong Wang
- Department of RadiologyAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusettsUSA
| | | | | | - Shiyi Li
- Changping LaboratoryBeijingChina
| | - Yi Zhang
- Department of RadiologyBeijing Friendship Hospital, Capital Medical UniversityBeijingChina
| | - Xue Lin
- Department of NeurologyBeijing Tongren Hospital, Capital Medical UniversityBeijingChina
| | - Zhen Zhen
- Department of NeurologyBeijing Tongren Hospital, Capital Medical UniversityBeijingChina
| | - Yichen Xu
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Dan Xie
- Department of NeurologyBeijing Friendship Hospital, Capital Medical UniversityBeijingChina
| | - Hongzhi Guan
- Department of NeurologyPeking Union Medical College Hospital, Chinese Academy of Medical SciencesBeijingChina
| | - Fang Yi
- Department of NeurologyLishilu Outpatient, Jingzhong Medical District, Chinese PLA General HospitalBeijingChina
| | - Jiawei Wang
- Department of NeurologyBeijing Tongren Hospital, Capital Medical UniversityBeijingChina
| | - Qi Shi
- State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and PreventionBeijingChina
| | - Hesheng Liu
- Changping LaboratoryBeijingChina
- Biomedical Pioneering Innovation CenterPeking UniversityBeijingChina
| |
Collapse
|
6
|
Luo J, Qin P, Bi Q, Wu K, Gong G. Individual variability in functional connectivity of human auditory cortex. Cereb Cortex 2024; 34:bhae007. [PMID: 38282455 DOI: 10.1093/cercor/bhae007] [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: 10/19/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/30/2024] Open
Abstract
Individual variability in functional connectivity underlies individual differences in cognition and behaviors, yet its association with functional specialization in the auditory cortex remains elusive. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, this study was designed to investigate the spatial distribution of auditory cortex individual variability in its whole-brain functional network architecture. An inherent hierarchical axis of the variability was discerned, which radiates from the medial to lateral orientation, with the left auditory cortex demonstrating more pronounced variations than the right. This variability exhibited a significant correlation with the variations in structural and functional metrics in the auditory cortex. Four auditory cortex subregions, which were identified from a clustering analysis based on this variability, exhibited unique connectional fingerprints and cognitive maps, with certain subregions showing specificity to speech perception functional activation. Moreover, the lateralization of the connectional fingerprint exhibited a U-shaped trajectory across the subregions. These findings emphasize the role of individual variability in functional connectivity in understanding cortical functional organization, as well as in revealing its association with functional specialization from the activation, connectome, and cognition perspectives.
Collapse
Affiliation(s)
- Junhao Luo
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Peipei Qin
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Qiuhui Bi
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China
| | - Ke Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- Chinese Institute for Brain Research, Beijing 102206, China
| |
Collapse
|
7
|
Liu X, Hu Y, Hao Y, Yang L. Individual differences in the neural architecture in semantic processing. Sci Rep 2024; 14:170. [PMID: 38168133 PMCID: PMC10761854 DOI: 10.1038/s41598-023-49538-8] [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: 05/24/2023] [Accepted: 12/09/2023] [Indexed: 01/05/2024] Open
Abstract
Neural mechanisms underlying semantic processing have been extensively studied by using functional magnetic resonance imaging, nevertheless, the individual differences of it are yet to be unveiled. To further our understanding of functional and anatomical brain organization underlying semantic processing to the level of individual humans, we used out-of-scanner language behavioral data, T1, resting-state, and story comprehension task-evoked functional image data in the Human Connectome Project, to investigate individual variability in the task-evoked semantic processing network, and attempted to predict individuals' language skills based on task and intrinsic functional connectivity of highly variable regions, by employing a machine-learning framework. Our findings first confirmed that individual variability in both functional and anatomical markers were heterogeneously distributed throughout the semantic processing network, and that the variability increased towards higher levels in the processing hierarchy. Furthermore, intrinsic functional connectivities among these highly variable regions were found to contribute to predict individual reading decoding abilities. The contributing nodes in the overall network were distributed in the left superior, inferior frontal, and temporo-parietal cortices. Our results suggested that the individual differences of neurobiological markers were heterogeneously distributed in the semantic processing network, and that neurobiological markers of highly variable areas are not only linked to individual variability in language skills, but can predict language skills at the individual level.
Collapse
Affiliation(s)
- Xin Liu
- Air Force Medical Center, Air Force Medical University, No. 28, Fucheng Street, Haidian District, Beijing, 100142, China.
| | - Yiwen Hu
- Air Force Medical Center, Air Force Medical University, No. 28, Fucheng Street, Haidian District, Beijing, 100142, China
| | - Yaokun Hao
- Air Force Medical Center, Air Force Medical University, No. 28, Fucheng Street, Haidian District, Beijing, 100142, China
| | - Liu Yang
- Air Force Medical Center, Air Force Medical University, No. 28, Fucheng Street, Haidian District, Beijing, 100142, China
| |
Collapse
|
8
|
Liu X, Yang L. Individual differences in the language task-evoked and resting-state functional networks. Front Hum Neurosci 2023; 17:1283069. [PMID: 38021226 PMCID: PMC10656779 DOI: 10.3389/fnhum.2023.1283069] [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: 08/25/2023] [Accepted: 09/29/2023] [Indexed: 12/01/2023] Open
Abstract
The resting state functional network is highly variable across individuals. However, inter-individual differences in functional networks evoked by language tasks and their comparison with resting state are still unclear. To address these two questions, we used T1 anatomical data and functional brain imaging data of resting state and a story comprehension task from the Human Connectome Project (HCP) to characterize functional network variability and investigate the uniqueness of the functional network in both task and resting states. We first demonstrated that intrinsic and task-induced functional networks exhibited remarkable differences across individuals, and language tasks can constrain inter-individual variability in the functional brain network. Furthermore, we found that the inter-individual variability of functional networks in two states was broadly consistent and spatially heterogeneous, with high-level association areas manifesting more significant variability than primary visual processing areas. Our results suggested that the functional network underlying language comprehension is unique at the individual level, and the inter-individual variability architecture of the functional network is broadly consistent in language task and resting state.
Collapse
Affiliation(s)
- Xin Liu
- Air Force Medical Center, Air Force Medical University, Beijing, China
| | - Liu Yang
- Air Force Medical Center, Air Force Medical University, Beijing, China
| |
Collapse
|
9
|
Ren J, Ren W, Zhou Y, Dahmani L, Duan X, Fu X, Wang Y, Pan R, Zhao J, Zhang P, Wang B, Yu W, Chen Z, Zhang X, Sun J, Ding M, Huang J, Xu L, Li S, Wang W, Xie W, Zhang H, Liu H. Personalized functional imaging-guided rTMS on the superior frontal gyrus for post-stroke aphasia: A randomized sham-controlled trial. Brain Stimul 2023; 16:1313-1321. [PMID: 37652135 DOI: 10.1016/j.brs.2023.08.023] [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: 04/23/2023] [Revised: 08/23/2023] [Accepted: 08/27/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Aphasia affects approximately one-third of stroke patients and yet its rehabilitation outcomes are often unsatisfactory. More effective strategies are needed to promote recovery. OBJECTIVE We aimed to examine the efficacy and safety of the theta-burst stimulation (TBS) on the language area in the superior frontal gyrus (SFG) localized by personalized functional imaging, in facilitating post-stroke aphasia recovery. METHODS This randomized sham-controlled trial uses a parallel design (intermittent TBS [iTBS] in ipsilesional hemisphere vs. continuous TBS [cTBS] in contralesional hemisphere vs. sham group). Participants had aphasia symptoms resulting from their first stroke in the left hemisphere at least one month prior. Participants received three-week speech-language therapy coupled with either active or sham stimulation applied to the left or right SFG. The primary outcome was the change in Western Aphasia Battery-Revised (WAB-R) aphasia quotient after the three-week treatment. The secondary outcome was WAB-R aphasia quotient improvement after one week of treatment. RESULTS Ninety-seven patients were screened between January 2021 and January 2022, 45 of whom were randomized and 44 received intervention (15 in each active group, 14 in sham). Both iTBS (estimated difference = 14.75, p < 0.001) and cTBS (estimated difference = 13.43, p < 0.001) groups showed significantly greater improvement than sham stimulation after the 3-week intervention and immediately after one week of treatment (p's < 0.001). The adverse events observed were similar across groups. A seizure was recorded three days after the termination of the treatment in the iTBS group. CONCLUSION The stimulation showed high efficacy and SFG is a promising stimulation target for post-stroke language recovery.
Collapse
Affiliation(s)
- Jianxun Ren
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China
| | - Weijing Ren
- Department of Neurorehabilitation, Beijing Bo'ai Hospital, China Rehabilitation Research Center, School of Rehabilitation, Capital Medical University, Beijing, 100069, China; University of Health and Rehabilitation Sciences, Qingdao, Shandong, 266000, China
| | - Ying Zhou
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China
| | - Louisa Dahmani
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Xinyu Duan
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China
| | - Xiaoxuan Fu
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Yezhe Wang
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China
| | - Ruiqi Pan
- Neural Galaxy Inc., Beijing, 102206, China
| | - Jingdu Zhao
- Department of Neurorehabilitation, Beijing Bo'ai Hospital, China Rehabilitation Research Center, School of Rehabilitation, Capital Medical University, Beijing, 100069, China
| | - Ping Zhang
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China
| | - Bo Wang
- Department of Hearing and Language Rehabilitation, Beijing Bo'ai Hospital, China Rehabilitation Research Center, Beijing, 100068, China
| | - Weiyong Yu
- Department of Radiology, Beijing Bo'ai Hospital, China Rehabilitation Research Center, Beijing, 100068, China
| | - Zhenbo Chen
- Department of Radiology, Beijing Bo'ai Hospital, China Rehabilitation Research Center, Beijing, 100068, China
| | - Xin Zhang
- Department of Neurorehabilitation, Beijing Bo'ai Hospital, China Rehabilitation Research Center, School of Rehabilitation, Capital Medical University, Beijing, 100069, China
| | - Jian Sun
- Neural Galaxy Inc., Beijing, 102206, China
| | | | - Jianting Huang
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China; Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China
| | - Liu Xu
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China; West China Medical School, Sichuan University, Chengdu, 610041, China
| | - Shiyi Li
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China
| | | | - Wuxiang Xie
- Peking University Clinical Research Institute, Peking University Health Science Center, Beijing, 100191, China
| | - Hao Zhang
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China; Department of Neurorehabilitation, Beijing Bo'ai Hospital, China Rehabilitation Research Center, School of Rehabilitation, Capital Medical University, Beijing, 100069, China; University of Health and Rehabilitation Sciences, Qingdao, Shandong, 266000, China; Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250100, China.
| | - Hesheng Liu
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China; Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China.
| |
Collapse
|
10
|
Lankinen K, Ahlfors SP, Mamashli F, Blazejewska AI, Raij T, Turpin T, Polimeni JR, Ahveninen J. Cortical depth profiles of auditory and visual 7 T functional MRI responses in human superior temporal areas. Hum Brain Mapp 2023; 44:362-372. [PMID: 35980015 PMCID: PMC9842898 DOI: 10.1002/hbm.26046] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 07/06/2022] [Accepted: 07/16/2022] [Indexed: 02/02/2023] Open
Abstract
Invasive neurophysiological studies in nonhuman primates have shown different laminar activation profiles to auditory vs. visual stimuli in auditory cortices and adjacent polymodal areas. Means to examine the underlying feedforward vs. feedback type influences noninvasively have been limited in humans. Here, using 1-mm isotropic resolution 3D echo-planar imaging at 7 T, we studied the intracortical depth profiles of functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) signals to brief auditory (noise bursts) and visual (checkerboard) stimuli. BOLD percent-signal-changes were estimated at 11 equally spaced intracortical depths, within regions-of-interest encompassing auditory (Heschl's gyrus, Heschl's sulcus, planum temporale, and posterior superior temporal gyrus) and polymodal (middle and posterior superior temporal sulcus) areas. Effects of differing BOLD signal strengths for auditory and visual stimuli were controlled via normalization and statistical modeling. The BOLD depth profile shapes, modeled with quadratic regression, were significantly different for auditory vs. visual stimuli in auditory cortices, but not in polymodal areas. The different depth profiles could reflect sensory-specific feedforward versus cross-sensory feedback influences, previously shown in laminar recordings in nonhuman primates. The results suggest that intracortical BOLD profiles can help distinguish between feedforward and feedback type influences in the human brain. Further experimental studies are still needed to clarify how underlying signal strength influences BOLD depth profiles under different stimulus conditions.
Collapse
Affiliation(s)
- Kaisu Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Seppo P. Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Fahimeh Mamashli
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Anna I. Blazejewska
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Tommi Raij
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Tori Turpin
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Division of Health Sciences and TechnologyMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| |
Collapse
|
11
|
Regev TI, Lipkin B, Boebinger D, Paunov A, Kean H, Norman-Haignere S, Fedorenko E. Preserved functional organization of human auditory cortex in individuals missing one temporal lobe from infancy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.18.523979. [PMID: 36711687 PMCID: PMC9882328 DOI: 10.1101/2023.01.18.523979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Human cortical responses to natural sounds, measured with fMRI, can be approximated as the weighted sum of a small number of canonical response patterns (components), each having interpretable functional and anatomical properties. Here, we asked whether this organization is preserved in cases where only one temporal lobe is available due to early brain damage by investigating a unique family: one sibling born without a left temporal lobe, another without a right temporal lobe, and a third anatomically neurotypical. We analyzed fMRI responses to diverse natural sounds within the intact hemispheres of these individuals and compared them to 12 neurotypical participants. All siblings manifested the neurotypical auditory responses in their intact hemispheres. These results suggest that the development of the auditory cortex in each hemisphere does not depend on the existence of the other hemisphere, highlighting the redundancy and equipotentiality of the bilateral auditory system.
Collapse
Affiliation(s)
- Tamar I Regev
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge MA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge MA
| | - Benjamin Lipkin
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge MA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge MA
| | - Dana Boebinger
- Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, NY
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY
| | - Alexander Paunov
- INSERM-CEA Cognitive Neuroimaging Unit (UNICOG), NeuroSpin Center, Gif sur Yvette, France
| | - Hope Kean
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge MA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge MA
| | - Sam Norman-Haignere
- Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, NY
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY
- Department of Biomedical Engineering, University of Rochester, Rochester, NY
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY
| | - Evelina Fedorenko
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge MA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge MA
- Speech and Hearing Bioscience and Technology (SHBT) Program, Harvard University, Boston MA
| |
Collapse
|
12
|
Environmental neuroscience linking exposome to brain structure and function underlying cognition and behavior. Mol Psychiatry 2023; 28:17-27. [PMID: 35790874 DOI: 10.1038/s41380-022-01669-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 06/02/2022] [Accepted: 06/09/2022] [Indexed: 01/07/2023]
Abstract
Individual differences in human brain structure, function, and behavior can be attributed to genetic variations, environmental exposures, and their interactions. Although genome-wide association studies have identified many genetic variants associated with brain imaging phenotypes, environmental exposures associated with these phenotypes remain largely unknown. Here, we propose that environmental neuroscience should pay more attention on exploring the associations between lifetime environmental exposures (exposome) and brain imaging phenotypes and identifying both cumulative environmental effects and their vulnerable age windows during the life course. Exposome-neuroimaging association studies face several challenges including the accurate measurement of the totality of environmental exposures varied in space and time, the highly correlated structure of the exposome, and the lack of standardized approaches for exposome-wide association studies. By agnostically scanning the effects of environmental exposures on brain imaging phenotypes and their interactions with genomic variations, exposome-neuroimaging association analyses will improve our understanding of causal factors associated with individual differences in brain structure and function as well as their relations with cognitive abilities and neuropsychiatric disorders.
Collapse
|
13
|
Xu X, Feng Y, Wang J, Salvi R, Yin X, Gao J, Chen Y. Auditory-limbic-cerebellum interactions and cognitive impairments in noise-induced hearing loss. CNS Neurosci Ther 2022; 29:932-940. [PMID: 36377461 PMCID: PMC9928548 DOI: 10.1111/cns.14028] [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: 09/18/2022] [Revised: 10/23/2022] [Accepted: 10/24/2022] [Indexed: 11/16/2022] Open
Abstract
AIMS This study aimed to explore the neural substrate of hearing loss-related central nervous system in rats and its correlation with cognition. METHODS We identified the neural mechanism for these debilitating abnormalities by inducing a bilateral hearing loss animal model using intense broadband noise (122 dB of broadband noise for 2 h) and used the Morris water maze test to characterize the behavioral changes at 6 months post-noise exposure. Functional magnetic resonance imaging (fMRI) was conducted to clarify disrupted functional network using bilateral auditory cortex (ACx) as a seed. Structural diffusion tensor imaging (DTI) was applied to illustrate characteristics of fibers in ACx and hippocampus. Pearson correlation was computed behavioral tests and other features. RESULTS A deficit in spatial learning/memory, body weight, and negative correlation between them was observed. Functional connectivity revealed weakened coupling within the ACx and inferior colliculus, lateral lemniscus, the primary motor cortex, the olfactory tubercle, hippocampus, and the paraflocculus lobe of the cerebellum. The fiber number and mean length of ACx and different hippocampal subregions were also damaged in hearing loss rats. CONCLUSION A new model of auditory-limbic-cerebellum interactions accounting for noise-induced hearing loss and cognitive impairments is proposed.
Collapse
Affiliation(s)
- Xiao‐Min Xu
- Department of Radiology, Nanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Yuan Feng
- Department of Radiology, Nanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Jian Wang
- School of Human Communication DisordersDalhousie UniversityHalifaxNova ScotiaCanada
| | - Richard Salvi
- Center for Hearing and DeafnessUniversity at BuffaloBuffaloNew YorkUSA
| | - Xindao Yin
- Department of Radiology, Nanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Jun Gao
- The Department of Neurobiology, Key Laboratory of Human Functional Genomics of JiangsuNanjing Medical UniversityNanjingChina
| | - Yu‐Chen Chen
- Department of Radiology, Nanjing First HospitalNanjing Medical UniversityNanjingChina
| |
Collapse
|
14
|
Ignatiadis K, Barumerli R, Tóth B, Baumgartner R. Effects of individualized brain anatomies and EEG electrode positions on inferred activity of the primary auditory cortex. Front Neuroinform 2022; 16:970372. [DOI: 10.3389/fninf.2022.970372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 09/05/2022] [Indexed: 11/13/2022] Open
Abstract
Due to its high temporal resolution and non-invasive nature, electroencephalography (EEG) is considered a method of great value for the field of auditory cognitive neuroscience. In performing source space analyses, localization accuracy poses a bottleneck, which precise forward models based on individualized attributes such as subject anatomy or electrode locations aim to overcome. Yet acquiring anatomical images or localizing EEG electrodes requires significant additional funds and processing time, making it an oftentimes inaccessible asset. Neuroscientific software offers template solutions, on which analyses can be based. For localizing the source of auditory evoked responses, we here compared the results of employing such template anatomies and electrode positions versus the subject-specific ones, as well as combinations of the two. All considered cases represented approaches commonly used in electrophysiological studies. We considered differences between two commonly used inverse solutions (dSPM, sLORETA) and targeted the primary auditory cortex; a notoriously small cortical region that is located within the lateral sulcus, thus particularly prone to errors in localization. Through systematical comparison of early evoked component metrics and spatial leakage, we assessed how the individualization steps impacted the analyses outcomes. Both electrode locations as well as subject anatomies were found to have an effect, which though varied based on the configuration considered. When comparing the inverse solutions, we moreover found that dSPM more consistently benefited from individualization of subject morphologies compared to sLORETA, suggesting it to be the better choice for auditory cortex localization.
Collapse
|
15
|
Ren W, Jia C, Zhou Y, Zhao J, Wang B, Yu W, Li S, Hu Y, Zhang H. A precise language network revealed by the independent component-based lesion mapping in post-stroke aphasia. Front Neurol 2022; 13:981653. [PMID: 36247758 PMCID: PMC9561861 DOI: 10.3389/fneur.2022.981653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/09/2022] [Indexed: 11/17/2022] Open
Abstract
Brain lesion mapping studies have provided the strongest evidence regarding the neural basis of cognition. However, it remained a problem to identify symptom-specific brain networks accounting for observed clinical and neuroanatomical heterogeneity. Independent component analysis (ICA) is a statistical method that decomposes mixed signals into multiple independent components. We aimed to solve this issue by proposing an independent component-based lesion mapping (ICLM) method to identify the language network in patients with moderate to severe post-stroke aphasia. Lesions were first extracted from 49 patients with post-stroke aphasia as masks applied to fMRI data in a cohort of healthy participants to calculate the functional connectivity (FC) within the masks and non-mask brain voxels. ICA was further performed on a reformatted FC matrix to extract multiple independent networks. Specifically, we found that one of the lesion-related independent components (ICs) highly resembled classical language networks. Moreover, the damaged level within the language-related lesioned network is strongly associated with language deficits, including aphasia quotient, naming, and auditory comprehension scores. In comparison, none of the other two traditional lesion mapping methods found any regions responsible for language dysfunction. The language-related lesioned network extracted with the ICLM method showed high specificity in detecting aphasia symptoms compared with the performance of resting ICs and classical language networks. In total, we detected a precise language network in patients with aphasia and proved its efficiency in the relationship with language symptoms. In general, our ICLM could successfully identify multiple lesion-related networks from complicated brain diseases, and be used as an effective tool to study brain-behavior relationships and provide potential biomarkers of particular clinical behavioral deficits.
Collapse
Affiliation(s)
- Weijing Ren
- School of Rehabilitation, Capital Medical University, Beijing, China
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
- University of Health and Rehabilitation Sciences, Qingdao, China
| | - Chunying Jia
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Ying Zhou
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Jingdu Zhao
- School of Rehabilitation, Capital Medical University, Beijing, China
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
| | - Bo Wang
- Department of Hearing and Language Rehabilitation, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
| | - Weiyong Yu
- Department of Radiology, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
| | - Shiyi Li
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Yiru Hu
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Hao Zhang
- School of Rehabilitation, Capital Medical University, Beijing, China
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
- University of Health and Rehabilitation Sciences, Qingdao, China
- *Correspondence: Hao Zhang
| |
Collapse
|
16
|
Trambaiolli LR, Peng X, Lehman JF, Linn G, Russ BE, Schroeder CE, Liu H, Haber SN. Anatomical and functional connectivity support the existence of a salience network node within the caudal ventrolateral prefrontal cortex. eLife 2022; 11:e76334. [PMID: 35510840 PMCID: PMC9106333 DOI: 10.7554/elife.76334] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 05/04/2022] [Indexed: 11/13/2022] Open
Abstract
Three large-scale networks are considered essential to cognitive flexibility: the ventral and dorsal attention (VANet and DANet) and salience (SNet) networks. The ventrolateral prefrontal cortex (vlPFC) is a known component of the VANet and DANet, but there is a gap in the current knowledge regarding its involvement in the SNet. Herein, we used a translational and multimodal approach to demonstrate the existence of a SNet node within the vlPFC. First, we used tract-tracing methods in non-human primates (NHP) to quantify the anatomical connectivity strength between different vlPFC areas and the frontal and insular cortices. The strongest connections were with the dorsal anterior cingulate cortex (dACC) and anterior insula (AI) - the main cortical SNet nodes. These inputs converged in the caudal area 47/12, an area that has strong projections to subcortical structures associated with the SNet. Second, we used resting-state functional MRI (rsfMRI) in NHP data to validate this SNet node. Third, we used rsfMRI in the human to identify a homologous caudal 47/12 region that also showed strong connections with the SNet cortical nodes. Taken together, these data confirm a SNet node in the vlPFC, demonstrating that the vlPFC contains nodes for all three cognitive networks: VANet, DANet, and SNet. Thus, the vlPFC is in a position to switch between these three networks, pointing to its key role as an attentional hub. Its additional connections to the orbitofrontal, dorsolateral, and premotor cortices, place the vlPFC at the center for switching behaviors based on environmental stimuli, computing value, and cognitive control.
Collapse
Affiliation(s)
- Lucas R Trambaiolli
- McLean Hospital, Harvard Medical SchoolBelmontUnited States
- University of Rochester School of Medicine & DentistryRochesterUnited States
| | - Xiaolong Peng
- Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
- Medical University of South CarolinaCharlestonUnited States
| | - Julia F Lehman
- University of Rochester School of Medicine & DentistryRochesterUnited States
| | - Gary Linn
- Translational Neuropscienc lab Division, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric ResearchOrangeburgUnited States
| | - Brian E Russ
- Translational Neuropscienc lab Division, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric ResearchOrangeburgUnited States
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount SinaiNew YorkUnited States
- Department of Psychiatry, New York University at LangoneNew YorkUnited States
| | - Charles E Schroeder
- Translational Neuropscienc lab Division, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric ResearchOrangeburgUnited States
- Department of Psychiatry, Columbia University Medical CenterNew YorkUnited States
| | - Hesheng Liu
- Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
- Medical University of South CarolinaCharlestonUnited States
| | - Suzanne N Haber
- McLean Hospital, Harvard Medical SchoolBelmontUnited States
- University of Rochester School of Medicine & DentistryRochesterUnited States
| |
Collapse
|
17
|
Ren J, Hu Q, Wang W, Zhang W, Hubbard CS, Zhang P, An N, Zhou Y, Dahmani L, Wang D, Fu X, Sun Z, Wang Y, Wang R, Li L, Liu H. Fast cortical surface reconstruction from MRI using deep learning. Brain Inform 2022; 9:6. [PMID: 35262808 PMCID: PMC8907118 DOI: 10.1186/s40708-022-00155-7] [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: 01/02/2022] [Accepted: 02/25/2022] [Indexed: 11/23/2022] Open
Abstract
Reconstructing cortical surfaces from structural magnetic resonance imaging (MRI) is a prerequisite for surface-based functional and anatomical image analyses. Conventional algorithms for cortical surface reconstruction are computationally inefficient and typically take several hours for each subject, causing a bottleneck in applications when a fast turnaround time is needed. To address this challenge, we propose a fast cortical surface reconstruction (FastCSR) pipeline by leveraging deep machine learning. We trained our model to learn an implicit representation of the cortical surface in volumetric space, termed the “level set representation”. A fast volumetric topology correction method and a topology-preserving surface mesh extraction procedure were employed to reconstruct the cortical surface based on the level set representation. Using 1-mm isotropic T1-weighted images, the FastCSR pipeline was able to reconstruct a subject’s cortical surfaces within 5 min with comparable surface quality, which is approximately 47 times faster than the traditional FreeSurfer pipeline. The advantage of FastCSR becomes even more apparent when processing high-resolution images. Importantly, the model demonstrated good generalizability in previously unseen data and showed high test–retest reliability in cortical morphometrics and anatomical parcellations. Finally, FastCSR was robust to images with compromised quality or with distortions caused by lesions. This fast and robust pipeline for cortical surface reconstruction may facilitate large-scale neuroimaging studies and has potential in clinical applications wherein brain images may be compromised.
Collapse
Affiliation(s)
- Jianxun Ren
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Qingyu Hu
- School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230027, China
| | | | - Wei Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100080, China
| | - Catherine S Hubbard
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA
| | | | - Ning An
- Neural Galaxy, Beijing, 102206, China
| | - Ying Zhou
- Neural Galaxy, Beijing, 102206, China
| | - Louisa Dahmani
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Xiaoxuan Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA.,Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA.,State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, 300401, China
| | | | | | - Ruiqi Wang
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China. .,Precision Medicine and Healthcare Research Center, Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, 518055, China. .,IDG/McGovern Institute for Brain Research at Tsinghua University, Beijing, 100084, China. .,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA. .,Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA.
| |
Collapse
|
18
|
Cui W, Wang Y, Ren J, Hubbard CS, Fu X, Fang S, Wang D, Zhang H, Li Y, Li L, Jiang T, Liu H. Personalized
fMRI
delineates functional regions preserved within brain tumors. Ann Neurol 2022; 91:353-366. [PMID: 35023218 PMCID: PMC9107064 DOI: 10.1002/ana.26303] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 01/09/2022] [Accepted: 01/10/2022] [Indexed: 11/09/2022]
Abstract
Objective Methods Results Interpretation
Collapse
Affiliation(s)
- Weigang Cui
- Department of Automation Science and Electrical Engineering Beihang University Beijing China
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
- Department of Neuroscience Medical University of South Carolina Charleston SC USA
- School of Engineering Medicine, Beihang University Beijing China
| | - Yinyan Wang
- Department of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing China
- Beijing Neurosurgical Institute, Capital Medical University Beijing China
| | - Jianxun Ren
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
- National Engineering Laboratory for Neuromodulation School of Aerospace Engineering, Tsinghua University Beijing China
| | - Catherine S. Hubbard
- Department of Neuroscience Medical University of South Carolina Charleston SC USA
| | - Xiaoxuan Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
- Department of Neuroscience Medical University of South Carolina Charleston SC USA
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin China
| | - Shengyu Fang
- Beijing Neurosurgical Institute, Capital Medical University Beijing China
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
| | - Hao Zhang
- Department of Neurological Rehabilitation Beijing Bo'ai Hospital, China Rehabilitation Research Center Beijing China
| | - Yang Li
- Department of Automation Science and Electrical Engineering Beihang University Beijing China
| | - Luming Li
- National Engineering Laboratory for Neuromodulation School of Aerospace Engineering, Tsinghua University Beijing China
- Precision Medicine & Healthcare Research Center, Tsinghua‐Berkeley Shenzhen Institute, Tsinghua University Shenzhen Guangdong China
- IDG/McGovern Institute for Brain Research at Tsinghua University Beijing China
| | - Tao Jiang
- Department of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing China
- Beijing Neurosurgical Institute, Capital Medical University Beijing China
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital, Harvard Medical School Charlestown MA USA
- Department of Neuroscience Medical University of South Carolina Charleston SC USA
| |
Collapse
|
19
|
Lancione M, Costagli M, Handjaras G, Tosetti M, Ricciardi E, Pietrini P, Cecchetti L. Complementing canonical fMRI with functional Quantitative Susceptibility Mapping (fQSM) in modern neuroimaging research. Neuroimage 2021; 244:118574. [PMID: 34508897 DOI: 10.1016/j.neuroimage.2021.118574] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 09/03/2021] [Accepted: 09/07/2021] [Indexed: 10/20/2022] Open
Abstract
Functional Quantitative Susceptibility Mapping (fQSM) allows for the quantitative measurement of time-varying magnetic susceptibility across cortical and subcortical brain structures with a potentially higher spatial specificity than conventional fMRI. While the usefulness of fQSM with General Linear Model and "On/Off" paradigms has been assessed, little is known about the potential applications and limitations of this technique in more sophisticated experimental paradigms and analyses, such as those currently used in modern neuroimaging. To thoroughly characterize fQSM activations, here we used 7T MRI, tonotopic mapping, as well as univariate (i.e., GLM and population Receptive Field) and multivariate (Representational Similarity Analysis; RSA) analyses. Although fQSM detected less tone-responsive voxels than fMRI, they were more consistently localized in gray matter. Also, the majority of active gray matter voxels exhibited negative fQSM response, signaling the expected oxyhemoglobin increase, whereas positive fQSM activations were mainly in white matter. Though fMRI- and fQSM-based tonotopic maps were overall comparable, the representation of frequency tunings in tone-sensitive regions was significantly more balanced for fQSM. Lastly, RSA revealed that frequency information from the auditory cortex could be successfully retrieved by using either methods. Overall, fQSM produces complementary results to conventional fMRI, as it captures small-scale variations in the activation pattern which inform multivariate measures. Although positive fQSM responses deserve further investigation, they do not impair the interpretation of contrasts of interest. The quantitative nature of fQSM, its spatial specificity and the possibility to simultaneously acquire canonical fMRI support the use of this technique for longitudinal and multicentric studies and pre-surgical mapping.
Collapse
Affiliation(s)
- Marta Lancione
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy; IMAGO7 Foundation, Pisa, Italy.
| | - Mauro Costagli
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Pisa, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy
| | - Giacomo Handjaras
- Social and Affective Neuroscience (SANe) Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Michela Tosetti
- IMAGO7 Foundation, Pisa, Italy; Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Pisa, Italy
| | - Emiliano Ricciardi
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Pietro Pietrini
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Luca Cecchetti
- Social and Affective Neuroscience (SANe) Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| |
Collapse
|
20
|
Raut RV, Snyder AZ, Mitra A, Yellin D, Fujii N, Malach R, Raichle ME. Global waves synchronize the brain's functional systems with fluctuating arousal. SCIENCE ADVANCES 2021; 7:7/30/eabf2709. [PMID: 34290088 PMCID: PMC8294763 DOI: 10.1126/sciadv.abf2709] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 06/04/2021] [Indexed: 05/04/2023]
Abstract
We propose and empirically support a parsimonious account of intrinsic, brain-wide spatiotemporal organization arising from traveling waves linked to arousal. We hypothesize that these waves are the predominant physiological process reflected in spontaneous functional magnetic resonance imaging (fMRI) signal fluctuations. The correlation structure ("functional connectivity") of these fluctuations recapitulates the large-scale functional organization of the brain. However, a unifying physiological account of this structure has so far been lacking. Here, using fMRI in humans, we show that ongoing arousal fluctuations are associated with global waves of activity that slowly propagate in parallel throughout the neocortex, thalamus, striatum, and cerebellum. We show that these waves can parsimoniously account for many features of spontaneous fMRI signal fluctuations, including topographically organized functional connectivity. Last, we demonstrate similar, cortex-wide propagation of neural activity measured with electrocorticography in macaques. These findings suggest that traveling waves spatiotemporally pattern brain-wide excitability in relation to arousal.
Collapse
Affiliation(s)
- Ryan V Raut
- Department of Radiology, Washington University, St. Louis, MO 63110, USA.
| | - Abraham Z Snyder
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Anish Mitra
- Department of Psychiatry, Stanford University, Stanford, CA 94305, USA
| | - Dov Yellin
- Department of Neurobiology, Weizmann Institute of Science, 76100 Rehovot, Israel
| | - Naotaka Fujii
- Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan
| | - Rafael Malach
- Department of Neurobiology, Weizmann Institute of Science, 76100 Rehovot, Israel
| | - Marcus E Raichle
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| |
Collapse
|
21
|
Ren J, Hubbard CS, Ahveninen J, Cui W, Li M, Peng X, Luan G, Han Y, Li Y, Shinn AK, Wang D, Li L, Liu H. Dissociable Auditory Cortico-Cerebellar Pathways in the Human Brain Estimated by Intrinsic Functional Connectivity. Cereb Cortex 2021; 31:2898-2912. [PMID: 33497437 PMCID: PMC8107796 DOI: 10.1093/cercor/bhaa398] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 11/10/2020] [Accepted: 12/11/2020] [Indexed: 12/16/2022] Open
Abstract
The cerebellum, a structure historically associated with motor control, has more recently been implicated in several higher-order auditory-cognitive functions. However, the exact functional pathways that mediate cerebellar influences on auditory cortex (AC) remain unclear. Here, we sought to identify auditory cortico-cerebellar pathways based on intrinsic functional connectivity magnetic resonance imaging. In contrast to previous connectivity studies that principally consider the AC as a single functionally homogenous unit, we mapped the cerebellar connectivity across different parts of the AC. Our results reveal that auditory subareas demonstrating different levels of interindividual functional variability are functionally coupled with distinct cerebellar regions. Moreover, auditory and sensorimotor areas show divergent cortico-cerebellar connectivity patterns, although sensorimotor areas proximal to the AC are often functionally grouped with the AC in previous connectivity-based network analyses. Lastly, we found that the AC can be functionally segmented into highly similar subareas based on either cortico-cerebellar or cortico-cortical functional connectivity, suggesting the existence of multiple parallel auditory cortico-cerebellar circuits that involve different subareas of the AC. Overall, the present study revealed multiple auditory cortico-cerebellar pathways and provided a fine-grained map of AC subareas, indicative of the critical role of the cerebellum in auditory processing and multisensory integration.
Collapse
Affiliation(s)
- Jianxun Ren
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, 100084 Beijing, China
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Catherine S Hubbard
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Weigang Cui
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425, USA
- Department of Automation Sciences and Electrical Engineering, Beihang University, 100083 Beijing, China
| | - Meiling Li
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Xiaolong Peng
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Guoming Luan
- Department of Neurosurgery, Comprehensive Epilepsy Center, Sanbo Brain Hospital, Capital Medical University, 100093 Beijing, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, 100053 Beijing, China
| | - Yang Li
- Department of Automation Sciences and Electrical Engineering, Beihang University, 100083 Beijing, China
| | - Ann K Shinn
- Psychotic Disorders Division, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, 100084 Beijing, China
- Precision Medicine & Healthcare Research Center, Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, 518055 Shenzhen, China
- IDG/McGovern Institute for Brain Research at Tsinghua University, 100084 Beijing, China
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425, USA
| |
Collapse
|