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Jia Y, Kudo K, Jariwala N, Tarapore P, Nagarajan S, Subramaniam K. Causal role of medial superior frontal cortex on enhancing neural information flow and self-agency judgments in the self-agency network. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.13.24302764. [PMID: 38405834 PMCID: PMC10888992 DOI: 10.1101/2024.02.13.24302764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Self-agency is being aware of oneself as the agent of one's thoughts and actions. Self-agency is necessary for successful interactions with the outside world (reality-monitoring). Prior research has shown that the medial superior prefrontal gyri (mPFC/SFG) may represent one neural correlate underlying self-agency judgments. However, the causal relationship remains unknown. Here, we applied high-frequency 10Hz repetitive transcranial magnetic stimulation (rTMS) to modulate the excitability of the mPFC/SFG site that we have previously shown to mediate self-agency. For the first time, we delineate causal neural mechanisms, revealing precisely how rTMS modulates SFG excitability and impacts directional neural information flow in the self-agency network by implementing innovative magnetoencephalography (MEG) phase-transfer entropy (PTE) metrics, measured from pre-to-post rTMS. We found that, compared to control rTMS, enhancing SFG excitability by rTMS induced significant increases in information flow between SFG and specific cingulate and paracentral regions in the self-agency network in delta-theta, alpha, and gamma bands, which predicted improved self-agency judgments. This is the first multimodal imaging study in which we implement MEG PTE metrics of 5D imaging of space, frequency and time, to provide cutting-edge analyses of the causal neural mechanisms of how rTMS enhances SFG excitability and improves neural information flow between distinct regions in the self-agency network to potentiate improved self-agency judgments. Our findings provide a novel perspective for investigating causal neural mechanisms underlying self-agency and create a path towards developing novel neuromodulation interventions to improve self-agency that will be particularly useful for patients with psychosis who exhibit severe impairments in self-agency.
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Demopoulos C, Jesson X, Gerdes MR, Jurigova BG, Hinkley LB, Ranasinghe KG, Desai S, Honma S, Mizuiri D, Findlay A, Nagarajan SS, Marco EJ. Global MEG Resting State Functional Connectivity in Children with Autism and Sensory Processing Dysfunction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.26.577499. [PMID: 38352614 PMCID: PMC10862722 DOI: 10.1101/2024.01.26.577499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Sensory processing dysfunction not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience dysfunctional sensory processing. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. This study compared long-range resting state functional connectivity of neural oscillatory behavior in children aged 8-12 years with autism spectrum disorder (ASD; N=18), those with sensory processing dysfunction (SPD; N=18) who do not meet ASD criteria, and typically developing control participants (TDC; N=24) using magnetoencephalography (MEG). Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Somatosensory cortical beta-band functional connectivity was associated with tactile processing abilities, while higher-order auditory cortical alpha-band functional connectivity was associated with auditory processing abilities. These findings demonstrate distinct long-range neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities. Neural synchrony measures could serve as potential sensitive biomarkers for ASD and SPD.
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Affiliation(s)
- Carly Demopoulos
- Department of Psychiatry, University of California San Francisco, 675 18 Street, San Francisco, CA 94107
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Xuan Jesson
- Department of Psychology, Palo Alto University, 1791 Arastradero Road, Palo Alto, CA 94304
| | - Molly Rae Gerdes
- Cortica Healthcare, Department of Neurodevelopmental Medicine, 4000 Civic Center Drive, San Rafael, CA 94903
| | - Barbora G. Jurigova
- Cortica Healthcare, Department of Neurodevelopmental Medicine, 4000 Civic Center Drive, San Rafael, CA 94903
| | - Leighton B. Hinkley
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Kamalini G. Ranasinghe
- University of California-San Francisco, Department of Neurology, 675 Nelson Rising Lane, San Francisco, CA 94143
| | - Shivani Desai
- University of California-San Francisco, Department of Neurology, 675 Nelson Rising Lane, San Francisco, CA 94143
| | - Susanne Honma
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Danielle Mizuiri
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Anne Findlay
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Srikantan S. Nagarajan
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Elysa J. Marco
- Cortica Healthcare, Department of Neurodevelopmental Medicine, 4000 Civic Center Drive, San Rafael, CA 94903
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3
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Krishna S, Choudhury A, Keough MB, Seo K, Ni L, Kakaizada S, Lee A, Aabedi A, Popova G, Lipkin B, Cao C, Nava Gonzales C, Sudharshan R, Egladyous A, Almeida N, Zhang Y, Molinaro AM, Venkatesh HS, Daniel AGS, Shamardani K, Hyer J, Chang EF, Findlay A, Phillips JJ, Nagarajan S, Raleigh DR, Brang D, Monje M, Hervey-Jumper SL. Glioblastoma remodelling of human neural circuits decreases survival. Nature 2023; 617:599-607. [PMID: 37138086 PMCID: PMC10191851 DOI: 10.1038/s41586-023-06036-1] [Citation(s) in RCA: 75] [Impact Index Per Article: 75.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 03/31/2023] [Indexed: 05/05/2023]
Abstract
Gliomas synaptically integrate into neural circuits1,2. Previous research has demonstrated bidirectional interactions between neurons and glioma cells, with neuronal activity driving glioma growth1-4 and gliomas increasing neuronal excitability2,5-8. Here we sought to determine how glioma-induced neuronal changes influence neural circuits underlying cognition and whether these interactions influence patient survival. Using intracranial brain recordings during lexical retrieval language tasks in awake humans together with site-specific tumour tissue biopsies and cell biology experiments, we find that gliomas remodel functional neural circuitry such that task-relevant neural responses activate tumour-infiltrated cortex well beyond the cortical regions that are normally recruited in the healthy brain. Site-directed biopsies from regions within the tumour that exhibit high functional connectivity between the tumour and the rest of the brain are enriched for a glioblastoma subpopulation that exhibits a distinct synaptogenic and neuronotrophic phenotype. Tumour cells from functionally connected regions secrete the synaptogenic factor thrombospondin-1, which contributes to the differential neuron-glioma interactions observed in functionally connected tumour regions compared with tumour regions with less functional connectivity. Pharmacological inhibition of thrombospondin-1 using the FDA-approved drug gabapentin decreases glioblastoma proliferation. The degree of functional connectivity between glioblastoma and the normal brain negatively affects both patient survival and performance in language tasks. These data demonstrate that high-grade gliomas functionally remodel neural circuits in the human brain, which both promotes tumour progression and impairs cognition.
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Affiliation(s)
- Saritha Krishna
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Abrar Choudhury
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | | | - Kyounghee Seo
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Lijun Ni
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Sofia Kakaizada
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Anthony Lee
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Alexander Aabedi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Galina Popova
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Benjamin Lipkin
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Caroline Cao
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Cesar Nava Gonzales
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Rasika Sudharshan
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew Egladyous
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Nyle Almeida
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Yalan Zhang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | | | - Andy G S Daniel
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | | | - Jeanette Hyer
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Anne Findlay
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Joanna J Phillips
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Srikantan Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - David R Raleigh
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiation Oncology, University of California, San Francisco, San Francisco, USA
| | - David Brang
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Michelle Monje
- Department of Neurology, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
| | - Shawn L Hervey-Jumper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
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4
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Jia Y, Kudo K, Hinkley LBN, Fisher M, Vinogradov S, Nagarajan S, Subramaniam K. Abnormal Information Flow in Schizophrenia Is Linked to Psychosis. Schizophr Bull 2022; 48:1384-1393. [PMID: 36073155 PMCID: PMC9673273 DOI: 10.1093/schbul/sbac075] [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] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND HYPOTHESIS Prior research has shown that patients with schizophrenia (SZ) show disruption in brain network connectivity that is thought to underlie their cognitive and psychotic symptoms. However, most studies examining functional network disruption in schizophrenia have focused on the temporally correlated coupling of the strength of network connections. Here, we move beyond correlative metrics to assay causal computations of connectivity changes in directed neural information flow, assayed from a neural source to a target in SZ. STUDY DESIGN This study describes a whole-brain magnetoencephalography-imaging approach to examine causal computations of connectivity changes in directed neural information flow between brain regions during resting states, quantified by phase-transfer entropy (PTE) metrics, assayed from a neural source to an endpoint, in 21 SZ compared with 21 healthy controls (HC), and associations with cognitive and clinical psychotic symptoms in SZ. STUDY RESULTS We found that SZ showed significant disruption in information flow in alpha (8-12 Hz) and beta (12-30 Hz) frequencies, compared to HC. Reduced information flow in alpha frequencies from the precuneus to the medio-ventral occipital cortex was associated with more severe clinical psychopathology (ie, positive psychotic symptoms), while reduced information flow between insula and middle temporal gyrus was associated with worsening cognitive symptoms. CONCLUSIONS The present findings highlight the importance of delineating dysfunction in neural information flow in specific oscillatory frequencies between distinct regions that underlie the cognitive and psychotic symptoms in SZ, and provide potential neural biomarkers that could lead to innovations in future neuromodulation treatment development.
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Affiliation(s)
- Yingxin Jia
- Department of Radiology and Biomedical Imaging, University of California, San, Francisco, CA 94143, USA
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California, San, Francisco, CA 94143, USA
- Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, Japan
| | - Leighton B N Hinkley
- Department of Radiology and Biomedical Imaging, University of California, San, Francisco, CA 94143, USA
| | - Melissa Fisher
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55454, USA
| | - Sophia Vinogradov
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55454, USA
| | - Srikantan Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San, Francisco, CA 94143, USA
| | - Karuna Subramaniam
- Department of Psychiatry, University of California, San Francisco, CA 94143, USA
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5
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Fred AL, Kumar SN, Kumar Haridhas A, Ghosh S, Purushothaman Bhuvana H, Sim WKJ, Vimalan V, Givo FAS, Jousmäki V, Padmanabhan P, Gulyás B. A Brief Introduction to Magnetoencephalography (MEG) and Its Clinical Applications. Brain Sci 2022; 12:brainsci12060788. [PMID: 35741673 PMCID: PMC9221302 DOI: 10.3390/brainsci12060788] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/01/2022] [Accepted: 06/08/2022] [Indexed: 11/30/2022] Open
Abstract
Magnetoencephalography (MEG) plays a pivotal role in the diagnosis of brain disorders. In this review, we have investigated potential MEG applications for analysing brain disorders. The signal-to-noise ratio (SNRMEG = 2.2 db, SNREEG < 1 db) and spatial resolution (SRMEG = 2−3 mm, SREEG = 7−10 mm) is higher for MEG than EEG, thus MEG potentially facilitates accurate monitoring of cortical activity. We found that the direct electrophysiological MEG signals reflected the physiological status of neurological disorders and play a vital role in disease diagnosis. Single-channel connectivity, as well as brain network analysis, using MEG data acquired during resting state and a given task has been used for the diagnosis of neurological disorders such as epilepsy, Alzheimer’s, Parkinsonism, autism, and schizophrenia. The workflow of MEG and its potential applications in the diagnosis of disease and therapeutic planning are also discussed. We forecast that computer-aided algorithms will play a prominent role in the diagnosis and prediction of neurological diseases in the future. The outcome of this narrative review will aid researchers to utilise MEG in diagnostics.
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Affiliation(s)
- Alfred Lenin Fred
- Department of CSE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India; (A.L.F.); (F.A.S.G.)
| | | | - Ajay Kumar Haridhas
- Department of ECE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India;
| | - Sayantan Ghosh
- Department of Integrative Biology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India;
| | - Harishita Purushothaman Bhuvana
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
| | - Wei Khang Jeremy Sim
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Vijayaragavan Vimalan
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Fredin Arun Sedly Givo
- Department of CSE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India; (A.L.F.); (F.A.S.G.)
| | - Veikko Jousmäki
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Aalto NeuroImaging, Department of Neuroscience and Biomedical Engineering, Aalto University, 12200 Espoo, Finland
| | - Parasuraman Padmanabhan
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Correspondence: (P.P.); (B.G.)
| | - Balázs Gulyás
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Department of Clinical Neuroscience, Karolinska Institute, 17176 Stockholm, Sweden
- Correspondence: (P.P.); (B.G.)
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6
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Speers LJ, Bilkey DK. Disorganization of Oscillatory Activity in Animal Models of Schizophrenia. Front Neural Circuits 2021; 15:741767. [PMID: 34675780 PMCID: PMC8523827 DOI: 10.3389/fncir.2021.741767] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 09/16/2021] [Indexed: 01/02/2023] Open
Abstract
Schizophrenia is a chronic, debilitating disorder with diverse symptomatology, including disorganized cognition and behavior. Despite considerable research effort, we have only a limited understanding of the underlying brain dysfunction. In this article, we review the potential role of oscillatory circuits in the disorder with a particular focus on the hippocampus, a region that encodes sequential information across time and space, as well as the frontal cortex. Several mechanistic explanations of schizophrenia propose that a loss of oscillatory synchrony between and within these brain regions may underlie some of the symptoms of the disorder. We describe how these oscillations are affected in several animal models of schizophrenia, including models of genetic risk, maternal immune activation (MIA) models, and models of NMDA receptor hypofunction. We then critically discuss the evidence for disorganized oscillatory activity in these models, with a focus on gamma, sharp wave ripple, and theta activity, including the role of cross-frequency coupling as a synchronizing mechanism. Finally, we focus on phase precession, which is an oscillatory phenomenon whereby individual hippocampal place cells systematically advance their firing phase against the background theta oscillation. Phase precession is important because it allows sequential experience to be compressed into a single 120 ms theta cycle (known as a 'theta sequence'). This time window is appropriate for the induction of synaptic plasticity. We describe how disruption of phase precession could disorganize sequential processing, and thereby disrupt the ordered storage of information. A similar dysfunction in schizophrenia may contribute to cognitive symptoms, including deficits in episodic memory, working memory, and future planning.
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Affiliation(s)
| | - David K. Bilkey
- Department of Psychology, Otago University, Dunedin, New Zealand
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7
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Demopoulos C, Duong X, Hinkley LB, Ranasinghe KG, Mizuiri D, Garrett C, Honma S, Henderson-Sabes J, Findlay A, Racine-Belkoura C, Cheung SW, Nagarajan SS. Global resting-state functional connectivity of neural oscillations in tinnitus with and without hearing loss. Hum Brain Mapp 2020; 41:2846-2861. [PMID: 32243040 PMCID: PMC7294064 DOI: 10.1002/hbm.24981] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 02/04/2020] [Accepted: 02/26/2020] [Indexed: 12/11/2022] Open
Abstract
This study examined global resting-state functional connectivity of neural oscillations in individuals with chronic tinnitus and normal and impaired hearing. We tested the hypothesis that distinct neural oscillatory networks are engaged in tinnitus with and without hearing loss. In both tinnitus groups, with and without hearing loss, we identified multiple frequency band-dependent regions of increased and decreased global functional connectivity. We also found that the auditory domain of tinnitus severity, assayed by the Tinnitus Functional Index, was associated with global functional connectivity in both auditory and nonauditory regions. These findings provide candidate biomarkers to target and monitor treatments for tinnitus with and without hearing loss.
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Affiliation(s)
- Carly Demopoulos
- Department of Psychiatry, University of California San Francisco, San Francisco, California.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Xuan Duong
- Department of Psychology, Palo Alto University, Palo Alto, California
| | - Leighton B Hinkley
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Kamalini G Ranasinghe
- Department of Neurology, University of California San Francisco, San Francisco, California
| | - Danielle Mizuiri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Coleman Garrett
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Susanne Honma
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Jennifer Henderson-Sabes
- Department of Otolaryngology-Head and Neck Surgery, University of California San Francisco, San Francisco, California
| | - Anne Findlay
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Caroline Racine-Belkoura
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California
| | - Steven W Cheung
- Department of Otolaryngology-Head and Neck Surgery, University of California San Francisco, San Francisco, California
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
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8
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Lee AT, Faltermeier C, Morshed RA, Young JS, Kakaizada S, Valdivia C, Findlay AM, Tarapore PE, Nagarajan SS, Hervey-Jumper SL, Berger MS. The impact of high functional connectivity network hub resection on language task performance in adult low- and high-grade glioma. J Neurosurg 2020; 134:1102-1112. [PMID: 32244221 DOI: 10.3171/2020.1.jns192267] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 01/13/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Gliomas are intrinsic brain tumors with the hallmark of diffuse white matter infiltration, resulting in short- and long-range network dysfunction. Preoperative magnetoencephalography (MEG) can assist in maximizing the extent of resection while minimizing morbidity. While MEG has been validated in motor mapping, its role in speech mapping remains less well studied. The authors assessed how the resection of intraoperative electrical stimulation (IES)-negative, high functional connectivity (HFC) network sites, as identified by MEG, impacts language performance. METHODS Resting-state, whole-brain MEG recordings were obtained from 26 patients who underwent perioperative language evaluation and glioma resection that was guided by awake language and IES mapping. The functional connectivity of an individual voxel was determined by the imaginary coherence between the index voxel and the rest of the brain, referenced to its contralesional pair. The percentage of resected HFC voxels was correlated with postoperative language outcomes in tasks of increasing complexity: text reading, 4-syllable repetition, picture naming, syntax (SYN), and auditory stimulus naming (AN). RESULTS Overall, 70% of patients (14/20) in whom any HFC tissue was resected developed an early postoperative language deficit (mean 2.3 days, range 1-8 days), compared to 33% of patients (2/6) in whom no HFC tissue was resected (p = 0.16). When bifurcated by the amount of HFC tissue that was resected, 100% of patients (3/3) with an HFC resection > 25% displayed deficits in AN, compared to 30% of patients (6/20) with an HFC resection < 25% (p = 0.04). Furthermore, there was a linear correlation between the severity of AN and SYN decline with percentage of HFC sites resected (p = 0.02 and p = 0.04, respectively). By 2.2 months postoperatively (range 1-6 months), the correlation between HFC resection and both AN and SYN decline had resolved (p = 0.94 and p = 1.00, respectively) in all patients (9/9) except two who experienced early postoperative tumor progression or stroke involving inferior frontooccipital fasciculus. CONCLUSIONS Imaginary coherence measures of functional connectivity using MEG are able to identify HFC network sites within and around low- and high-grade gliomas. Removal of IES-negative HFC sites results in early transient postoperative decline in AN and SYN, which resolved by 3 months in all patients without stroke or early tumor progression. Measures of functional connectivity may therefore be a useful means of counseling patients about postoperative risk and assist with preoperative surgical planning.
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Affiliation(s)
| | | | | | | | | | | | - Anne M Findlay
- 2Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | | | - Srikantan S Nagarajan
- 2Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
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9
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Candelaria-Cook FT, Stephen JM. Test-Retest Reliability of Magnetoencephalography Resting-State Functional Connectivity in Schizophrenia. Front Psychiatry 2020; 11:551952. [PMID: 33391043 PMCID: PMC7772354 DOI: 10.3389/fpsyt.2020.551952] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 11/23/2020] [Indexed: 12/17/2022] Open
Abstract
The reliability of magnetoencephalography (MEG) resting-state functional connectivity in schizophrenia (SZ) is unknown as previous research has focused on healthy controls (HC). Here, we examined reliability in 26 participants (13-SZ, 13-HC). Eyes opened and eyes closed resting-state data were collected on 4 separate occasions during 2 visits, 1 week apart. For source modeling, we used minimum norm software to apply dynamic statistical parametric mapping. Source analyses compared the following functional connectivity metrics from each data run: coherence (coh), imaginary coherence (imcoh), pairwise phase consistency (ppc), phase-locking value (plv), phase lag index (pli), weighted phase lag index (wpli), and weighted phase lag index debiased (wpli2). Intraclass correlation coefficients (ICCs) were calculated for whole brain, network, and network pair averages. For reliability, ICCs above 0.75 = excellent, above 0.60 = good, above 0.40 = fair, and below 0.40 = poor reliability. We found the reliability of these metrics varied greatly depending on frequency band, network, network pair, and participant group examined. Broadband (1-58 Hz) whole brain averages in both HC and SZ showed excellent reliability for wpli2, and good to fair reliability for ppc, plv, and coh. Broadband network averages showed excellent to good reliability across 1 hour and 1 week for coh, imcoh, ppc, plv, wpli within default mode, cognitive control, and visual networks in HC, while the same metrics had excellent to fair reliability in SZ. Regional network pair averages showed good to fair reliability for coh, ppc, plv within default mode, cognitive control and visual network pairs in HC and SZ. In general, HC had higher reliability compared to SZ, and the default mode, cognitive control, and visual networks had higher reliability compared to somatosensory and auditory networks. Similar reliability levels occurred for both eyes opened and eyes closed resting-states for most metrics. The functional connectivity metrics of coh, ppc, and plv performed best across 1 hour and 1 week in HC and SZ. We also found that SZ had reduced coh, plv, and ppc in the dmn average and pair values indicating dysconnectivity in SZ. These findings encourage collecting both eyes opened and eyes closed resting-state MEG, while demonstrating that clinical populations may differ in reliability.
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10
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Candelaria-Cook FT, Schendel ME, Ojeda CJ, Bustillo JR, Stephen JM. Reduced parietal alpha power and psychotic symptoms: Test-retest reliability of resting-state magnetoencephalography in schizophrenia and healthy controls. Schizophr Res 2020; 215:229-240. [PMID: 31706785 PMCID: PMC7036030 DOI: 10.1016/j.schres.2019.10.023] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 10/07/2019] [Accepted: 10/09/2019] [Indexed: 11/29/2022]
Abstract
BACKGROUND Despite increased reporting of resting-state magnetoencephalography (MEG), reliability of those measures remains scarce and predominately reported in healthy controls (HC). As such, there is limited knowledge on MEG resting-state reliability in schizophrenia (SZ). METHODS To address test-retest reliability in psychosis, a reproducibility study of 26 participants (13-SZ, 13-HC) was performed. We collected eyes open and eyes closed resting-state data during 4 separate instances (2 Visits, 2 runs per visit) to estimate spectral power reliability (power, normalized power, alpha reactivity) across one hour and one week. Intraclass correlation coefficients (ICCs) were calculated. For source modeling, we applied an anatomically constrained linear estimation inverse model known as dynamic statistical parametric mapping (MNE dSPM) and source-based connectivity using the weighted phase lag index. RESULTS Across one week there was excellent test-retest reliability in global spectral measures in theta-gamma bands (HC ICCAvg = 0.87, SZ ICCAvg = 0.87), regional spectral measures in all bands (HC ICCAvg = 0.86, SZ ICCAvg = 0.80), and parietal alpha measures (HC ICCAvg = 0.90, SZ ICCAvg = 0.84). Conversely, functional connectivity had poor reliability, as did source spectral power across one hour for SZ. Relative to HC, SZ also had reduced parietal alpha normalized power during eyes closed only, reduced alpha reactivity, and an association between higher PANSS positive scores and lower parietal alpha power. CONCLUSIONS There was excellent to good test-retest reliability in most MEG spectral measures with a few exceptions in the schizophrenia patient group. Overall, these findings encourage the use of resting-state MEG while emphasizing the importance of determining reliability in clinical populations.
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Affiliation(s)
| | | | - Cesar J. Ojeda
- Department of Psychiatry and Behavioral Sciences, Center for Psychiatric Research, University of New Mexico School of Medicine, Albuquerque, New Mexico
| | - Juan R. Bustillo
- Department of Psychiatry and Behavioral Sciences, Center for Psychiatric Research, University of New Mexico School of Medicine, Albuquerque, New Mexico
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11
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Dale CL, Brown EG, Herman AB, Hinkley LBN, Subramaniam K, Fisher M, Vinogradov S, Nagarajan SS. Intervention-specific patterns of cortical function plasticity during auditory encoding in people with schizophrenia. Schizophr Res 2020; 215:241-249. [PMID: 31648842 PMCID: PMC7035971 DOI: 10.1016/j.schres.2019.10.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Revised: 08/06/2019] [Accepted: 10/03/2019] [Indexed: 01/07/2023]
Abstract
Schizophrenia is a neurocognitive illness characterized by behavioral and neural impairments in both early auditory processing and higher order verbal working memory. Previously we have shown intervention-specific cognitive performance improvements with computerized, targeted training of auditory processing (AT) when compared to a computer games (CG) control intervention that emphasized visual processing. To investigate spatiotemporal changes in patterns of neural activity specific to the AT intervention, the current study used magnetoencephalography (MEG) imaging to derive induced high gamma band oscillations (HGO) during auditory encoding, before and after 50 h (∼10 weeks) of exposure to either the AT or CG intervention. During stimulus encoding, AT intervention-specific changes in high gamma activity occurred in left middle frontal and left middle-superior temporal cortices. In contrast, CG intervention-specific changes were observed in right medial frontal and supramarginal gyri during stimulus encoding, and in bilateral temporal cortices during response preparation. These data reveal that, in schizophrenia, intensive exposure to either training of auditory processing or exposure to visuospatial activities produces significant but complementary patterns of cortical function plasticity within a distributed fronto-temporal network. These results underscore the importance of delineating the specific neuroplastic effects of targeted behavioral interventions to ensure desired neurophysiological changes and avoid unintended consequences on neural system functioning.
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Affiliation(s)
- Corby L Dale
- Department of Radiology and Biomedical Imaging, University of California San Francisco, United States; San Francisco Veterans' Affairs Medical Center, United States.
| | - Ethan G Brown
- Weill Cornell Medical College, New York, United States
| | - Alexander B Herman
- Department of Radiology and Biomedical Imaging, University of California San Francisco, United States; UCB-UCSF Graduate Program in Bioengineering, University of California, Berkeley, United States; Medical Science Training Program, University of California, San Francisco, United States
| | - Leighton B N Hinkley
- Department of Radiology and Biomedical Imaging, University of California San Francisco, United States
| | - Karuna Subramaniam
- Department of Radiology and Biomedical Imaging, University of California San Francisco, United States
| | - Melissa Fisher
- San Francisco Veterans' Affairs Medical Center, United States; Department of Psychiatry, University of California, San Francisco, United States
| | - Sophia Vinogradov
- San Francisco Veterans' Affairs Medical Center, United States; Department of Psychiatry, University of California, San Francisco, United States
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, United States; UCB-UCSF Graduate Program in Bioengineering, University of California, Berkeley, United States
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12
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Michelini G, Jurgiel J, Bakolis I, Cheung CHM, Asherson P, Loo SK, Kuntsi J, Mohammad-Rezazadeh I. Atypical functional connectivity in adolescents and adults with persistent and remitted ADHD during a cognitive control task. Transl Psychiatry 2019; 9:137. [PMID: 30979865 PMCID: PMC6461684 DOI: 10.1038/s41398-019-0469-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 01/10/2019] [Accepted: 03/23/2019] [Indexed: 12/12/2022] Open
Abstract
We previously provided initial evidence for cognitive and event-related potential markers of persistence/remission of attention-deficit/hyperactivity disorder (ADHD) from childhood to adolescence and adulthood. Here, using a novel brain-network connectivity approach, we aimed to examine whether task-based functional connectivity reflects a marker of ADHD remission or an enduring deficit unrelated to ADHD outcome. High-density EEG was recorded in a follow-up of 110 adolescents and young adults with childhood ADHD (87 persisters, 23 remitters) and 169 typically developing individuals during an arrow-flanker task, eliciting cognitive control. Functional connectivity was quantified with network-based graph-theory metrics before incongruent (high-conflict) target onset (pre-stimulus), during target processing (post-stimulus) and in the degree of change between pre-stimulus/post-stimulus. ADHD outcome was examined with parent-reported symptoms and impairment using both a categorical (DSM-IV) and a dimensional approach. Graph-theory measures converged in indicating that, compared to controls, ADHD persisters showed increased connectivity in pre-stimulus theta, alpha, and beta and in post-stimulus beta (all p < .01) and reduced pre-stimulus/post-stimulus change in theta connectivity (p < .01). In the majority of indices showing ADHD persister-control differences, ADHD remitters differed from controls (all p < .05) but not from persisters. Similarly, connectivity measures were unrelated to continuous outcome measures of ADHD symptoms and impairment in participants with childhood ADHD. These findings indicate that adolescents and young adults with persistent and remitted ADHD share atypical over-connectivity profiles and reduced ability to modulate connectivity patterns with task demands, compared to controls. Task-based functional connectivity impairments may represent enduring deficits in individuals with childhood ADHD irrespective of diagnostic status in adolescence/young adulthood.
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Affiliation(s)
- Giorgia Michelini
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
- Department of Psychiatry and Behavioral Health, State University New York (SUNY) Stony Brook University, Stony Brook, NY, USA.
| | - Joseph Jurgiel
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Ioannis Bakolis
- Department of Biostatistics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Celeste H M Cheung
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Philip Asherson
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Sandra K Loo
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Jonna Kuntsi
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Iman Mohammad-Rezazadeh
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
- HRL Laboratories, Malibu, CA, USA
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13
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Mäki-Marttunen T, Krull F, Bettella F, Hagen E, Næss S, Ness TV, Moberget T, Elvsåshagen T, Metzner C, Devor A, Edwards AG, Fyhn M, Djurovic S, Dale AM, Andreassen OA, Einevoll GT. Alterations in Schizophrenia-Associated Genes Can Lead to Increased Power in Delta Oscillations. Cereb Cortex 2019; 29:875-891. [PMID: 30475994 PMCID: PMC6319172 DOI: 10.1093/cercor/bhy291] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 10/03/2018] [Indexed: 12/13/2022] Open
Abstract
Genome-wide association studies have implicated many ion channels in schizophrenia pathophysiology. Although the functions of these channels are relatively well characterized by single-cell studies, the contributions of common variation in these channels to neurophysiological biomarkers and symptoms of schizophrenia remain elusive. Here, using computational modeling, we show that a common biomarker of schizophrenia, namely, an increase in delta-oscillation power, may be a direct consequence of altered expression or kinetics of voltage-gated ion channels or calcium transporters. Our model of a circuit of layer V pyramidal cells highlights multiple types of schizophrenia-related variants that contribute to altered dynamics in the delta-frequency band. Moreover, our model predicts that the same membrane mechanisms that increase the layer V pyramidal cell network gain and response to delta-frequency oscillations may also cause a deficit in a single-cell correlate of the prepulse inhibition, which is a behavioral biomarker highly associated with schizophrenia.
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Affiliation(s)
- Tuomo Mäki-Marttunen
- Simula Research Laboratory, Oslo, Norway
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Florian Krull
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Francesco Bettella
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Espen Hagen
- Department of Physics, University of Oslo, Oslo, Norway
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Solveig Næss
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Torbjørn V Ness
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Torgeir Moberget
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torbjørn Elvsåshagen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Christoph Metzner
- Centre for Computer Science and Informatics Research, University of Hertfordshire, Hatfield, UK
| | - Anna Devor
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | | | - Marianne Fyhn
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anders M Dale
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Gaute T Einevoll
- Department of Physics, University of Oslo, Oslo, Norway
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
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14
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Ranasinghe KG, Hinkley LB, Beagle AJ, Mizuiri D, Honma SM, Welch AE, Hubbard I, Mandelli ML, Miller ZA, Garrett C, La A, Boxer AL, Houde JF, Miller BL, Vossel KA, Gorno-Tempini ML, Nagarajan SS. Distinct spatiotemporal patterns of neuronal functional connectivity in primary progressive aphasia variants. Brain 2017; 140:2737-2751. [PMID: 28969381 DOI: 10.1093/brain/awx217] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2017] [Accepted: 07/04/2017] [Indexed: 12/15/2022] Open
Abstract
Primary progressive aphasia is a syndrome characterized by progressive loss of language abilities with three main phenotypic clinical presentations, including logopenic, non-fluent/agrammatic, and semantic variants. Previous imaging studies have shown unique anatomic impacts within language networks in each variant. However, direct measures of spontaneous neuronal activity and functional integrity of these impacted neural networks in primary progressive aphasia are lacking. The aim of this study was to characterize the spatial and temporal patterns of resting state neuronal synchronizations in primary progressive aphasia syndromes. We hypothesized that resting state brain oscillations will show unique deficits within language network in each variant of primary progressive aphasia. We examined 39 patients with primary progressive aphasia including logopenic variant (n = 14, age = 61 ± 9 years), non-fluent/agrammatic variant (n = 12, age = 71 ± 8 years) and semantic variant (n = 13, age = 65 ± 7 years) using magnetoencephalographic imaging, compared to a control group that was matched in age and gender to each primary progressive aphasia subgroup (n = 20, age = 65 ± 5 years). Each patient underwent a complete clinical evaluation including a comprehensive battery of language tests. We examined the whole-brain resting state functional connectivity as measured by imaginary coherence in each patient group compared to the control cohort, in three frequency oscillation bands-delta-theta (2-8 Hz); alpha (8-12 Hz); beta (12-30 Hz). Each variant showed a distinct spatiotemporal pattern of altered functional connectivity compared to age-matched controls. Specifically, we found significant hyposynchrony of alpha and beta frequency within the left posterior temporal and occipital cortices in patients with the logopenic variant, within the left inferior frontal cortex in patients with the non-fluent/agrammatic variant, and within the left temporo-parietal junction in patients with the semantic variant. Patients with logopenic variant primary progressive aphasia also showed significant hypersynchrony of delta-theta frequency within bilateral medial frontal and posterior parietal cortices. Furthermore, region of interest-based analyses comparing the spatiotemporal patterns of variant-specific regions of interest identified in comparison to age-matched controls showed significant differences between primary progressive aphasia variants themselves. We also found distinct patterns of regional spectral power changes in each primary progressive aphasia variant, compared to age-matched controls. Our results demonstrate neurophysiological signatures of network-specific neuronal dysfunction in primary progressive aphasia variants. The unique spatiotemporal patterns of neuronal synchrony signify diverse neurophysiological disruptions and pathological underpinnings of the language network in each variant.
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Affiliation(s)
- Kamalini G Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Leighton B Hinkley
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco CA 94143, USA
| | - Alexander J Beagle
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Danielle Mizuiri
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco CA 94143, USA
| | - Susanne M Honma
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco CA 94143, USA
| | - Ariane E Welch
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Isabel Hubbard
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Maria Luisa Mandelli
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Zachary A Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Coleman Garrett
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco CA 94143, USA
| | - Alice La
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - John F Houde
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco CA 94143, USA.,Speech Neuroscience Laboratory, Department of Otolaryngology, Head and Neck Surgery, University of California San Francisco, San Francisco CA 94143, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Keith A Vossel
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Srikantan S Nagarajan
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco CA 94143, USA.,Speech Neuroscience Laboratory, Department of Otolaryngology, Head and Neck Surgery, University of California San Francisco, San Francisco CA 94143, USA
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15
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MEG Analysis of Neural Interactions in Attention-Deficit/Hyperactivity Disorder. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2016; 2016:8450241. [PMID: 27118965 PMCID: PMC4828555 DOI: 10.1155/2016/8450241] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/24/2015] [Accepted: 03/07/2016] [Indexed: 11/30/2022]
Abstract
The aim of the present study was to explore the interchannel relationships of resting-state brain activity in patients with attention-deficit/hyperactivity disorder (ADHD), one of the most common mental disorders that develop in children. Magnetoencephalographic (MEG) signals were recorded using a 148-channel whole-head magnetometer in 13 patients with ADHD (range: 8–12 years) and 14 control subjects (range: 8–13 years). Three complementary measures (coherence, phase-locking value, and Euclidean distance) were calculated in the conventional MEG frequency bands: delta, theta, alpha, beta, and gamma. Our results showed that the interactions among MEG channels are higher for ADHD patients than for control subjects in all frequency bands. Statistically significant differences were observed for short-distance values within right-anterior and central regions, especially at delta, beta, and gamma-frequency bands (p < 0.05; Mann-Whitney U test with false discovery rate correction). These frequency bands also showed statistically significant differences in long-distance interactions, mainly among anterior and central regions, as well as among anterior, central, and other areas. These differences might reflect alterations during brain development in children with ADHD. Our results support the role of frontal abnormalities in ADHD pathophysiology, which may reflect a delay in cortical maturation in the frontal cortex.
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16
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Brown M, Kuperberg GR. A Hierarchical Generative Framework of Language Processing: Linking Language Perception, Interpretation, and Production Abnormalities in Schizophrenia. Front Hum Neurosci 2015; 9:643. [PMID: 26640435 PMCID: PMC4661240 DOI: 10.3389/fnhum.2015.00643] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2015] [Accepted: 11/12/2015] [Indexed: 12/27/2022] Open
Abstract
Language and thought dysfunction are central to the schizophrenia syndrome. They are evident in the major symptoms of psychosis itself, particularly as disorganized language output (positive thought disorder) and auditory verbal hallucinations (AVHs), and they also manifest as abnormalities in both high-level semantic and contextual processing and low-level perception. However, the literatures characterizing these abnormalities have largely been separate and have sometimes provided mutually exclusive accounts of aberrant language in schizophrenia. In this review, we propose that recent generative probabilistic frameworks of language processing can provide crucial insights that link these four lines of research. We first outline neural and cognitive evidence that real-time language comprehension and production normally involve internal generative circuits that propagate probabilistic predictions to perceptual cortices - predictions that are incrementally updated based on prediction error signals as new inputs are encountered. We then explain how disruptions to these circuits may compromise communicative abilities in schizophrenia by reducing the efficiency and robustness of both high-level language processing and low-level speech perception. We also argue that such disruptions may contribute to the phenomenology of thought-disordered speech and false perceptual inferences in the language system (i.e., AVHs). This perspective suggests a number of productive avenues for future research that may elucidate not only the mechanisms of language abnormalities in schizophrenia, but also promising directions for cognitive rehabilitation.
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Affiliation(s)
- Meredith Brown
- Department of Psychiatry–Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, CharlestownMA, USA
- Department of Psychology, Tufts University, MedfordMA, USA
| | - Gina R. Kuperberg
- Department of Psychiatry–Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, CharlestownMA, USA
- Department of Psychology, Tufts University, MedfordMA, USA
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17
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Ranasinghe KG, Hinkley LB, Beagle AJ, Mizuiri D, Dowling AF, Honma SM, Finucane MM, Scherling C, Miller BL, Nagarajan SS, Vossel KA. Regional functional connectivity predicts distinct cognitive impairments in Alzheimer's disease spectrum. NEUROIMAGE-CLINICAL 2014; 5:385-95. [PMID: 25180158 PMCID: PMC4145532 DOI: 10.1016/j.nicl.2014.07.006] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2014] [Revised: 06/27/2014] [Accepted: 07/17/2014] [Indexed: 11/12/2022]
Abstract
Understanding neural network dysfunction in neurodegenerative disease is imperative to effectively develop network-modulating therapies. In Alzheimer’s disease (AD), cognitive decline associates with deficits in resting-state functional connectivity of diffuse brain networks. The goal of the current study was to test whether specific cognitive impairments in AD spectrum correlate with reduced functional connectivity of distinct brain regions. We recorded resting-state functional connectivity of alpha-band activity in 27 patients with AD spectrum − 22 patients with probable AD (5 logopenic variant primary progressive aphasia, 7 posterior cortical atrophy, and 10 early-onset amnestic/dysexecutive AD) and 5 patients with mild cognitive impairment due to AD. We used magnetoencephalographic imaging (MEGI) to perform an unbiased search for regions where patterns of functional connectivity correlated with disease severity and cognitive performance. Functional connectivity measured the strength of coherence between a given region and the rest of the brain. Decreased neural connectivity of multiple brain regions including the right posterior perisylvian region and left middle frontal cortex correlated with a higher degree of disease severity. Deficits in executive control and episodic memory correlated with reduced functional connectivity of the left frontal cortex, whereas visuospatial impairments correlated with reduced functional connectivity of the left inferior parietal cortex. Our findings indicate that reductions in region-specific alpha-band resting-state functional connectivity are strongly correlated with, and might contribute to, specific cognitive deficits in AD spectrum. In the future, MEGI functional connectivity could be an important biomarker to map and follow defective networks in the early stages of AD. Magnetoencephalographic imaging (MEGI) measures brain functional connectivity. We investigated MEGIalpha-band connectivity in a cohort with Alzheimer’s disease spectrum. Decreased connectivity of multiple brain regions correlates with disease severity. Decreased connectivity of focal brain regions correlates with cognitive deficits. MEGI is a novel, unbiased approach to map neural network defects in dementia.
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Affiliation(s)
- Kamalini G Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Leighton B Hinkley
- Department of Radiology and Biomedical Imaging, Biomagnetic Imaging Laboratory, University of California San Francisco, San Francisco, CA 94143, USA
| | - Alexander J Beagle
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Danielle Mizuiri
- Department of Radiology and Biomedical Imaging, Biomagnetic Imaging Laboratory, University of California San Francisco, San Francisco, CA 94143, USA
| | - Anne F Dowling
- Department of Radiology and Biomedical Imaging, Biomagnetic Imaging Laboratory, University of California San Francisco, San Francisco, CA 94143, USA
| | - Susanne M Honma
- Department of Radiology and Biomedical Imaging, Biomagnetic Imaging Laboratory, University of California San Francisco, San Francisco, CA 94143, USA
| | - Mariel M Finucane
- Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
| | - Carole Scherling
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, Biomagnetic Imaging Laboratory, University of California San Francisco, San Francisco, CA 94143, USA
| | - Keith A Vossel
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA ; Gladstone Institute of Neurological Disease, San Francisco, CA 94158, USA
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18
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Rutter L, Nadar SR, Holroyd T, Carver FW, Apud J, Weinberger DR, Coppola R. Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks. Front Comput Neurosci 2013; 7:93. [PMID: 23874288 PMCID: PMC3709101 DOI: 10.3389/fncom.2013.00093] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2013] [Accepted: 06/21/2013] [Indexed: 11/13/2022] Open
Abstract
Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear.
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Affiliation(s)
- Lindsay Rutter
- MEG Core Facility, National Institute of Mental HealthBethesda, MD, USA
| | | | - Tom Holroyd
- MEG Core Facility, National Institute of Mental HealthBethesda, MD, USA
| | | | - Jose Apud
- Clinical Brain Disorders Branch, National Institute of Mental HealthBethesda, MD, USA
| | | | - Richard Coppola
- MEG Core Facility, National Institute of Mental HealthBethesda, MD, USA
- Clinical Brain Disorders Branch, National Institute of Mental HealthBethesda, MD, USA
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19
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Tarapore PE, Martino J, Guggisberg AG, Owen J, Honma SM, Findlay A, Berger MS, Kirsch HE, Nagarajan SS. Magnetoencephalographic imaging of resting-state functional connectivity predicts postsurgical neurological outcome in brain gliomas. Neurosurgery 2013; 71:1012-22. [PMID: 22895403 DOI: 10.1227/neu.0b013e31826d2b78] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The removal of brain tumors in perieloquent or eloquent cortex risks causing new neurological deficits in patients. The assessment of the functionality of perilesional tissue is essential to avoid postoperative neurological morbidity. OBJECTIVE To evaluate preoperative magnetoencephalography-based functional connectivity as a predictor of short- and medium-term neurological outcome after removal of gliomas in perieloquent and eloquent areas. METHODS Resting-state whole-brain magnetoencephalography recordings were obtained from 79 consecutive subjects with focal brain gliomas near or within motor, sensory, or language areas. Neural activity was estimated using adaptive spatial filtering. The mean imaginary coherence between voxels in and around brain tumors was compared with contralesional voxels and used as an index of their functional connectivity with the rest of the brain. The connectivity values of the tissue resected during surgery were correlated with the early (1 week postoperatively) and medium-term (6 months postoperatively) neurological morbidity. RESULTS Patients undergoing resection of tumors with decreased functional connectivity had a 29% rate of a new neurological deficit 1 week after surgery and a 0% rate at 6-month follow-up. Patients undergoing resection of tumors with increased functional connectivity had a 60% rate of a new deficit at 1 week and a 25% rate at 6 months. CONCLUSION Magnetoencephalography connectivity analysis gives a valuable preoperative evaluation of the functionality of the tissue surrounding tumors in perieloquent and eloquent areas. These data may be used to optimize preoperative patient counseling and surgical strategy.
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Affiliation(s)
- Phiroz E Tarapore
- Department of Neurological Surgery, University of California-San Francisco, San Francisco, California 94143-0628, USA
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Tarapore PE, Findlay AM, Lahue SC, Lee H, Honma SM, Mizuiri D, Luks TL, Manley GT, Nagarajan SS, Mukherjee P. Resting state magnetoencephalography functional connectivity in traumatic brain injury. J Neurosurg 2013; 118:1306-16. [PMID: 23600939 DOI: 10.3171/2013.3.jns12398] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECT Traumatic brain injury (TBI) is one of the leading causes of morbidity worldwide. One mechanism by which blunt head trauma may disrupt normal cognition and behavior is through alteration of functional connectivity between brain regions. In this pilot study, the authors applied a rapid automated resting state magnetoencephalography (MEG) imaging technique suitable for routine clinical use to test the hypothesis that there is decreased functional connectivity in patients with TBI compared with matched controls, even in cases of mild TBI. Furthermore, they posit that these abnormal reductions in MEG functional connectivity can be detected even in TBI patients without specific evidence of traumatic lesions on 3-T MR images. Finally, they hypothesize that the reductions of functional connectivity can improve over time across serial MEG scans during recovery from TBI. METHODS Magnetoencephalography maps of functional connectivity in the alpha (8- to 12-Hz) band from 21 patients who sustained a TBI were compared with those from 18 age- and sex-matched controls. Regions of altered functional connectivity in each patient were detected in automated fashion through atlas-based registration to the control database. The extent of reduced functional connectivity in the patient group was tested for correlations with clinical characteristics of the injury as well as with findings on 3-T MRI. Finally, the authors compared initial connectivity maps with 2-year follow-up functional connectivity in a subgroup of 5 patients with TBI. RESULTS Fourteen male and 7 female patients (17-53 years old, median 29 years) were enrolled. By Glasgow Coma Scale (GCS) criteria, 11 patients had mild, 1 had moderate, and 3 had severe TBI, and 6 had no GCS score recorded. On 3-T MRI, 16 patients had abnormal findings attributable to the trauma and 5 had findings in the normal range. As a group, the patients with TBI had significantly lower functional connectivity than controls (p < 0.01). Three of the 5 patients with normal findings on 3-T MRI showed regions of abnormally reduced MEG functional connectivity. No significant correlations were seen between extent of functional disconnection and injury severity or posttraumatic symptoms (p > 0.05). In the subgroup undergoing 2-year follow-up, the second MEG scan demonstrated a significantly lower percentage of voxels with decreased connectivity (p < 0.05) than the initial MEG scan. CONCLUSIONS A rapid automated resting-state MEG imaging technique demonstrates abnormally decreased functional connectivity that may persist for years after TBI, including cases classified as "mild" by GCS criteria. Disrupted MEG connectivity can be detected even in some patients with normal findings on 3-T MRI. Analysis of follow-up MEG scans in a subgroup of patients shows that, over time, the abnormally reduced connectivity can improve, suggesting neuroplasticity during the recovery from TBI. Resting state MEG deserves further investigation as a prognostic and predictive biomarker for TBI.
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Affiliation(s)
- Phiroz E Tarapore
- Department of Neurological Surgery, University of California, San Francisco, California 94107-0946, USA
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Hinkley LBN, Marco EJ, Findlay AM, Honma S, Jeremy RJ, Strominger Z, Bukshpun P, Wakahiro M, Brown WS, Paul LK, Barkovich AJ, Mukherjee P, Nagarajan SS, Sherr EH. The role of corpus callosum development in functional connectivity and cognitive processing. PLoS One 2012; 7:e39804. [PMID: 22870191 PMCID: PMC3411722 DOI: 10.1371/journal.pone.0039804] [Citation(s) in RCA: 115] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2011] [Accepted: 05/29/2012] [Indexed: 12/17/2022] Open
Abstract
The corpus callosum is hypothesized to play a fundamental role in integrating information and mediating complex behaviors. Here, we demonstrate that lack of normal callosal development can lead to deficits in functional connectivity that are related to impairments in specific cognitive domains. We examined resting-state functional connectivity in individuals with agenesis of the corpus callosum (AgCC) and matched controls using magnetoencephalographic imaging (MEG-I) of coherence in the alpha (8-12 Hz), beta (12-30 Hz) and gamma (30-55 Hz) bands. Global connectivity (GC) was defined as synchronization between a region and the rest of the brain. In AgCC individuals, alpha band GC was significantly reduced in the dorsolateral pre-frontal (DLPFC), posterior parietal (PPC) and parieto-occipital cortices (PO). No significant differences in GC were seen in either the beta or gamma bands. We also explored the hypothesis that, in AgCC, this regional reduction in functional connectivity is explained primarily by a specific reduction in interhemispheric connectivity. However, our data suggest that reduced connectivity in these regions is driven by faulty coupling in both inter- and intrahemispheric connectivity. We also assessed whether the degree of connectivity correlated with behavioral performance, focusing on cognitive measures known to be impaired in AgCC individuals. Neuropsychological measures of verbal processing speed were significantly correlated with resting-state functional connectivity of the left medial and superior temporal lobe in AgCC participants. Connectivity of DLPFC correlated strongly with performance on the Tower of London in the AgCC cohort. These findings indicate that the abnormal callosal development produces salient but selective (alpha band only) resting-state functional connectivity disruptions that correlate with cognitive impairment. Understanding the relationship between impoverished functional connectivity and cognition is a key step in identifying the neural mechanisms of language and executive dysfunction in common neurodevelopmental and psychiatric disorders where disruptions of callosal development are consistently identified.
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Affiliation(s)
- Leighton B. N. Hinkley
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - Elysa J. Marco
- Department of Neurology, University of California San Francisco, San Francisco, California, United States of America
- Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
| | - Anne M. Findlay
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - Susanne Honma
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - Rita J. Jeremy
- Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
| | - Zoe Strominger
- Department of Neurology, University of California San Francisco, San Francisco, California, United States of America
| | - Polina Bukshpun
- Department of Neurology, University of California San Francisco, San Francisco, California, United States of America
| | - Mari Wakahiro
- Department of Neurology, University of California San Francisco, San Francisco, California, United States of America
| | - Warren S. Brown
- Travis Research Institute, Fuller Theological Seminary, Pasadena, California, United States of America
| | - Lynn K. Paul
- Travis Research Institute, Fuller Theological Seminary, Pasadena, California, United States of America
- Department of Neuroscience, Caltech, Pasadena, California, United States of America
| | - A. James Barkovich
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
- Department of Neurology, University of California San Francisco, San Francisco, California, United States of America
- Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
| | - Pratik Mukherjee
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - Srikantan S. Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - Elliott H. Sherr
- Department of Neurology, University of California San Francisco, San Francisco, California, United States of America
- Department of Pediatrics, University of California San Francisco, San Francisco, California, United States of America
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Freyer F, Reinacher M, Nolte G, Dinse HR, Ritter P. Repetitive tactile stimulation changes resting-state functional connectivity-implications for treatment of sensorimotor decline. Front Hum Neurosci 2012; 6:144. [PMID: 22654748 PMCID: PMC3358755 DOI: 10.3389/fnhum.2012.00144] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2012] [Accepted: 05/08/2012] [Indexed: 11/13/2022] Open
Abstract
Neurological disorders and physiological aging can lead to a decline of perceptual abilities. In contrast to the conventional therapeutic approach that comprises intensive training and practicing, passive repetitive sensory stimulation (RSS) has recently gained increasing attention as an alternative to countervail the sensory decline by improving perceptual abilities without the need of active participation. A particularly effective type of high-frequency RSS, utilizing Hebbian learning principles, improves perceptual acuity as well as sensorimotor functions and has been successfully applied to treat chronic stroke patients and elderly subjects. High-frequency RSS has been shown to induce plastic changes of somatosensory cortex such as representational map reorganization, but its impact on the brain's ongoing network activity and resting-state functional connectivity has not been investigated so far. Here, we applied high-frequency RSS in healthy human subjects and analyzed resting state Electroencephalography (EEG) functional connectivity patterns before and after RSS by means of imaginary coherency (ImCoh), a frequency-specific connectivity measure which is known to reduce over-estimation biases due to volume conduction and common reference. Thirty minutes of passive high-frequency RSS lead to significant ImCoh-changes of the resting state mu-rhythm in the individual upper alpha frequency band within distributed sensory and motor cortical areas. These stimulation induced distributed functional connectivity changes likely underlie the previously observed improvement in sensorimotor integration.
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Affiliation(s)
- Frank Freyer
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational NeuroscienceBerlin, Germany
- Department of Neurology, Charité University MedicineBerlin, Germany
- Institute for Neuroinformatics, Neural Plasticity Lab, Ruhr-University BochumGermany
| | - Matthias Reinacher
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational NeuroscienceBerlin, Germany
- Department of Neurology, Charité University MedicineBerlin, Germany
| | - Guido Nolte
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-EppendorfHamburg, Germany
| | - Hubert R. Dinse
- Institute for Neuroinformatics, Neural Plasticity Lab, Ruhr-University BochumGermany
| | - Petra Ritter
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational NeuroscienceBerlin, Germany
- Department of Neurology, Charité University MedicineBerlin, Germany
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzig, Germany
- Berlin School of Mind and Brain and Mind and Brain Institute, Humboldt UniversityBerlin, Germany
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Hinkley LBN, Vinogradov S, Guggisberg AG, Fisher M, Findlay AM, Nagarajan SS. Clinical symptoms and alpha band resting-state functional connectivity imaging in patients with schizophrenia: implications for novel approaches to treatment. Biol Psychiatry 2011; 70:1134-42. [PMID: 21861988 PMCID: PMC3327723 DOI: 10.1016/j.biopsych.2011.06.029] [Citation(s) in RCA: 101] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2010] [Revised: 05/18/2011] [Accepted: 06/01/2011] [Indexed: 12/20/2022]
Abstract
BACKGROUND Schizophrenia (SZ) is associated with functional decoupling between cortical regions, but we do not know whether and where this occurs in low-frequency electromagnetic oscillations. The goal of this study was to use magnetoencephalography (MEG) to identify brain regions that exhibit abnormal resting-state connectivity in the alpha frequency range in patients with schizophrenia and investigate associations between functional connectivity and clinical symptoms in stable outpatient participants. METHODS Thirty patients with SZ and 15 healthy comparison participants were scanned in resting-state MEG (eyes closed). Functional connectivity MEG source data were reconstructed globally in the alpha range, quantified by the mean imaginary coherence between a voxel and the rest of the brain. RESULTS In patients, decreased connectivity was observed in left prefrontal cortex (PFC) and right superior temporal cortex, whereas increased connectivity was observed in left extrastriate cortex and the right inferior PFC. Functional connectivity of left inferior parietal cortex was negatively related to positive symptoms. Low left PFC connectivity was associated with negative symptoms. Functional connectivity of midline PFC was negatively correlated with depressed symptoms. Functional connectivity of right PFC was associated with other (cognitive) symptoms. CONCLUSIONS This study demonstrates direct functional disconnection in SZ between specific cortical fields within low-frequency resting-state oscillations. Impaired alpha coupling in frontal, parietal, and temporal regions is associated with clinical symptoms in these stable outpatients. Our findings indicate that this level of functional disconnection between cortical regions is an important treatment target in SZ.
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Affiliation(s)
- Leighton B N Hinkley
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California 94143, USA
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Hillebrand A, Barnes GR, Bosboom JL, Berendse HW, Stam CJ. Frequency-dependent functional connectivity within resting-state networks: an atlas-based MEG beamformer solution. Neuroimage 2011; 59:3909-21. [PMID: 22122866 PMCID: PMC3382730 DOI: 10.1016/j.neuroimage.2011.11.005] [Citation(s) in RCA: 294] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2011] [Revised: 10/27/2011] [Accepted: 11/02/2011] [Indexed: 11/08/2022] Open
Abstract
The brain consists of functional units with more-or-less specific information processing capabilities, yet cognitive functions require the co-ordinated activity of these spatially separated units. Magnetoencephalography (MEG) has the temporal resolution to capture these frequency-dependent interactions, although, due to volume conduction and field spread, spurious estimates may be obtained when functional connectivity is estimated on the basis of the extra-cranial recordings directly. Connectivity estimates on the basis of reconstructed sources may similarly be affected by biases introduced by the source reconstruction approach. Here we propose an analysis framework to reliably determine functional connectivity that is based around two main ideas: (i) functional connectivity is computed for a set of atlas-based ROIs in anatomical space that covers almost the entire brain, aiding the interpretation of MEG functional connectivity/network studies, as well as the comparison with other modalities; (ii) volume conduction and similar bias effects are removed by using a functional connectivity estimator that is insensitive to these effects, namely the Phase Lag Index (PLI). Our analysis approach was applied to eyes-closed resting-state MEG data for thirteen healthy participants. We first demonstrate that functional connectivity estimates based on phase coherence, even at the source-level, are biased due to the effects of volume conduction and field spread. In contrast, functional connectivity estimates based on PLI are not affected by these biases. We then looked at mean PLI, or weighted degree, over areas and subjects and found significant mean connectivity in three (alpha, beta, gamma) of the five (including theta and delta) classical frequency bands tested. These frequency-band dependent patterns of resting-state functional connectivity were distinctive; with the alpha and beta band connectivity confined to posterior and sensorimotor areas respectively, and with a generally more dispersed pattern for the gamma band. Generally, these patterns corresponded closely to patterns of relative source power, suggesting that the most active brain regions are also the ones that are most-densely connected. Our results reveal for the first time, using an analysis framework that enables the reliable characterisation of resting-state dynamics in the human brain, how resting-state networks of functionally connected regions vary in a frequency-dependent manner across the cortex.
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Affiliation(s)
- Arjan Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands.
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Weiss SA, Bassett DS, Rubinstein D, Holroyd T, Apud J, Dickinson D, Coppola R. Functional Brain Network Characterization and Adaptivity during Task Practice in Healthy Volunteers and People with Schizophrenia. Front Hum Neurosci 2011; 5:81. [PMID: 21887140 PMCID: PMC3157023 DOI: 10.3389/fnhum.2011.00081] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2011] [Accepted: 07/26/2011] [Indexed: 12/24/2022] Open
Abstract
Cognitive remediation involves task practice and may improve deficits in people suffering from schizophrenia, but little is known about underlying neurophysiological mechanisms. In people with schizophrenia and controls, we used magnetoencephalography (MEG) to examine accuracy and practice-related changes in parameters indexing neural network structure and activity, to determine whether these might be useful assays of the efficacy of cognitive remediation. Two MEG recordings were acquired during performance of a tone discrimination task used to improve the acuity of auditory processing, before and after ∼2.5 h of task practice. Accuracy before practice was negatively correlated with beta-band cost efficiency, a graph theoretical measure of network organization. Synthetic aperture magnetometry was used to localize brain oscillations with high spatial accuracy; results demonstrated sound and sensorimotor modulations of the beta band in temporo-parietal regions and the sensorimotor cortex respectively. High-gamma activity also correlated with sensorimotor processing during the task, with activation of auditory regions following sound stimulation, and activation of the left sensorimotor cortex preceding the button press. High-gamma power in the left frontal cortex was also found to correlate with accuracy. Following practice, sound-induced broad-band power in the left angular gyri increased. Accuracy improved and was found to correlate with increased mutual information (MI) between sensors in temporal-parietal regions in the beta band but not global cost efficiency. Based on these results, we conclude that hours of task practice can induce meso-scale changes such as increased power in relevant brain regions as well as changes in MI that correlate with improved accuracy.
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Sekihara K, Owen JP, Trisno S, Nagarajan SS. Removal of spurious coherence in MEG source-space coherence analysis. IEEE Trans Biomed Eng 2011; 58:3121-9. [PMID: 21824842 DOI: 10.1109/tbme.2011.2162514] [Citation(s) in RCA: 67] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Source-space coherence analysis has become a popular method to estimate functional connectivity based on MEG/EEG. Source-space analysis involves solving the inverse problem, estimating the time courses of specific brain regions, and then examining the coherence between activities at different brain regions. However, source-space coherence analysis can be confounded by spurious coherence caused due to the leakage properties of the inverse algorithm employed. Such spurious coherence is typically manifested as an artifactual large peak around the seed voxel, called seed blur, in the resulting coherence images. This seed blur often obscures important details of brain interactions. This paper proposes the use of the imaginary part of the coherence to remove the spurious coherence caused by the leakage of an imaging algorithm. We present a theoretical analysis that explains how the use of imaginary part can remove this spurious coherence. We then present results from both computer simulations and experiments using resting-state MEG data which demonstrate the validity of our analysis.
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Affiliation(s)
- Kensuke Sekihara
- Department of Systems Design and Engineering, Tokyo Metropolitan University, Tokyo, Japan.
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