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Xu J, Luo Y, Zhang J, Zhong L, Liu H, Weng A, Yang Z, Zhang Y, Ou Z, Yan Z, Cheng Q, Fan X, Zhang X, Zhang W, Hu Q, Liang D, Peng K, Liu G. Progressive thalamic nuclear atrophy in blepharospasm and blepharospasm-oromandibular dystonia. Brain Commun 2024; 6:fcae117. [PMID: 38638150 PMCID: PMC11025674 DOI: 10.1093/braincomms/fcae117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/21/2024] [Accepted: 04/05/2024] [Indexed: 04/20/2024] Open
Abstract
The thalamus is considered a key region in the neuromechanisms of blepharospasm. However, previous studies considered it as a single, homogeneous structure, disregarding potentially useful information about distinct thalamic nuclei. Herein, we aimed to examine (i) whether grey matter volume differs across thalamic subregions/nuclei in patients with blepharospasm and blepharospasm-oromandibular dystonia; (ii) causal relationships among abnormal thalamic nuclei; and (iii) whether these abnormal features can be used as neuroimaging biomarkers to distinguish patients with blepharospasm from blepharospasm-oromandibular dystonia and those with dystonia from healthy controls. Structural MRI data were collected from 56 patients with blepharospasm, 20 with blepharospasm-oromandibular dystonia and 58 healthy controls. Differences in thalamic nuclei volumes between groups and their relationships to clinical information were analysed in patients with dystonia. Granger causality analysis was employed to explore the causal effects among abnormal thalamic nuclei. Support vector machines were used to test whether these abnormal features could distinguish patients with different forms of dystonia and those with dystonia from healthy controls. Compared with healthy controls, patients with blepharospasm exhibited reduced grey matter volume in the lateral geniculate and pulvinar inferior nuclei, whereas those with blepharospasm-oromandibular dystonia showed decreased grey matter volume in the ventral anterior and ventral lateral anterior nuclei. Atrophy in the pulvinar inferior nucleus in blepharospasm patients and in the ventral lateral anterior nucleus in blepharospasm-oromandibular dystonia patients was negatively correlated with clinical severity and disease duration, respectively. The proposed machine learning scheme yielded a high accuracy in distinguishing blepharospasm patients from healthy controls (accuracy: 0.89), blepharospasm-oromandibular dystonia patients from healthy controls (accuracy: 0.82) and blepharospasm from blepharospasm-oromandibular dystonia patients (accuracy: 0.94). Most importantly, Granger causality analysis revealed that a progressive driving pathway from pulvinar inferior nuclear atrophy extends to lateral geniculate nuclear atrophy and then to ventral lateral anterior nuclear atrophy with increasing clinical severity in patients with blepharospasm. These findings suggest that the pulvinar inferior nucleus in the thalamus is the focal origin of blepharospasm, extending to pulvinar inferior nuclear atrophy and subsequently extending to the ventral lateral anterior nucleus causing involuntary lower facial and masticatory movements known as blepharospasm-oromandibular dystonia. Moreover, our results also provide potential targets for neuromodulation especially deep brain stimulation in patients with blepharospasm and blepharospasm-oromandibular dystonia.
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Affiliation(s)
- Jinping Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yuhan Luo
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
| | - Jiana Zhang
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
| | - Linchang Zhong
- Department of Medical Imaging, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
| | - Huiming Liu
- Department of Medical Imaging, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
| | - Ai Weng
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
| | - Zhengkun Yang
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
| | - Yue Zhang
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
| | - Zilin Ou
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
| | - Zhicong Yan
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
| | - Qinxiu Cheng
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Xinxin Fan
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Xiaodong Zhang
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Weixi Zhang
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
| | - Qingmao Hu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Dong Liang
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Kangqiang Peng
- Department of Medical Imaging, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
| | - Gang Liu
- Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou 510080, China
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Telesford QK, Gonzalez-Moreira E, Xu T, Tian Y, Colcombe SJ, Cloud J, Russ BE, Falchier A, Nentwich M, Madsen J, Parra LC, Schroeder CE, Milham MP, Franco AR. An open-access dataset of naturalistic viewing using simultaneous EEG-fMRI. Sci Data 2023; 10:554. [PMID: 37612297 PMCID: PMC10447527 DOI: 10.1038/s41597-023-02458-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 08/09/2023] [Indexed: 08/25/2023] Open
Abstract
In this work, we present a dataset that combines functional magnetic imaging (fMRI) and electroencephalography (EEG) to use as a resource for understanding human brain function in these two imaging modalities. The dataset can also be used for optimizing preprocessing methods for simultaneously collected imaging data. The dataset includes simultaneously collected recordings from 22 individuals (ages: 23-51) across various visual and naturalistic stimuli. In addition, physiological, eye tracking, electrocardiography, and cognitive and behavioral data were collected along with this neuroimaging data. Visual tasks include a flickering checkerboard collected outside and inside the MRI scanner (EEG-only) and simultaneous EEG-fMRI recordings. Simultaneous recordings include rest, the visual paradigm Inscapes, and several short video movies representing naturalistic stimuli. Raw and preprocessed data are openly available to download. We present this dataset as part of an effort to provide open-access data to increase the opportunity for discoveries and understanding of the human brain and evaluate the correlation between electrical brain activity and blood oxygen level-dependent (BOLD) signals.
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Affiliation(s)
- Qawi K Telesford
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Eduardo Gonzalez-Moreira
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Yiwen Tian
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Stanley J Colcombe
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Jessica Cloud
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Brian E Russ
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Arnaud Falchier
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Maximilian Nentwich
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Jens Madsen
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Lucas C Parra
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Charles E Schroeder
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Departments of Psychiatry and Neurology, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Michael P Milham
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Alexandre R Franco
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA.
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA.
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Chai Y, Handwerker DA, Marrett S, Gonzalez-Castillo J, Merriam EP, Hall A, Molfese PJ, Bandettini PA. Visual temporal frequency preference shows a distinct cortical architecture using fMRI. Neuroimage 2019; 197:13-23. [PMID: 31015027 DOI: 10.1016/j.neuroimage.2019.04.048] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Revised: 03/27/2019] [Accepted: 04/17/2019] [Indexed: 12/30/2022] Open
Abstract
Studies of visual temporal frequency preference typically examine frequencies under 20 Hz and measure local activity to evaluate the sensitivity of different cortical areas to variations in temporal frequencies. Most of these studies have not attempted to map preferred temporal frequency within and across visual areas, nor have they explored in detail, stimuli at gamma frequency, which recent research suggests may have potential clinical utility. In this study, we address this gap by using functional magnetic resonance imaging (fMRI) to measure response to flickering visual stimuli varying in frequency from 1 to 40 Hz. We apply stimulation in both a block design to examine task response and a steady-state design to examine functional connectivity. We observed distinct activation patterns between 1 Hz and 40 Hz stimuli. We also found that the correlation between medial thalamus and visual cortex was modulated by the temporal frequency. The modulation functions and tuned frequencies are different for the visual activity and thalamo-visual correlations. Using both fMRI activity and connectivity measurements, we show evidence for a temporal frequency specific organization across the human visual system.
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Affiliation(s)
- Yuhui Chai
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
| | - Daniel A Handwerker
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Sean Marrett
- Functional MRI Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Javier Gonzalez-Castillo
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Elisha P Merriam
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Andrew Hall
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Peter J Molfese
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA; Functional MRI Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
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Erdogdu E, Kurt E, Duru AD, Uslu A, Başar-Eroğlu C, Demiralp T. Measurement of cognitive dynamics during video watching through event-related potentials (ERPs) and oscillations (EROs). Cogn Neurodyn 2019; 13:503-512. [PMID: 31741687 DOI: 10.1007/s11571-019-09544-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 05/15/2019] [Accepted: 06/11/2019] [Indexed: 11/24/2022] Open
Abstract
Event-related potentials (ERPs) and oscillations (EROs) are reliable measures of cognition, but they require time-locked electroencephalographic (EEG) data to repetitive triggers that are not available in continuous sensory input streams. However, such real-life-like stimulation by videos or virtual-reality environments may serve as powerful means of creating specific cognitive or affective states and help to investigate dysfunctions in psychiatric and neurological disorders more efficiently. This study aims to develop a method to generate ERPs and EROs during watching videos. Repeated luminance changes were introduced on short video segments, while EEGs of 10 subjects were recorded. The ERP/EROs time-locked to these distortions were analyzed in time and time-frequency domains and tested for their cognitive significance through a long term memory test that included frames from the watched videos. For each subject, ERPs and EROs corresponding to video segments of recalled images with 25% shortest and 25% longest reaction times were compared. ERPs produced by transient luminance changes displayed statistically significant fluctuations both in time and time-frequency domains. Statistical analyses showed that a positivity around 450 ms, a negativity around 500 ms and delta and theta EROs correlated with memory performance. Few studies mixed video streams with simultaneous ERP/ERO experiments with discrete task-relevant or passively presented auditory or somatosensory stimuli, while the present study, by obtaining ERPs and EROs to task-irrelevant events in the same sensory modality as that of the continuous sensory input, produces minimal interference with the main focus of attention on the video stream.
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Affiliation(s)
- Emel Erdogdu
- 1Institute of Psychology and Cognition Research, University of Bremen, 28359 Bremen, Germany.,2Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, 34093 Çapa, Istanbul, Turkey
| | - Elif Kurt
- 2Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, 34093 Çapa, Istanbul, Turkey.,3Aziz Sancar Institute of Experimental Medicine, Department of Neuroscience, Istanbul University, 34093 Çapa, Istanbul, Turkey
| | - Adil Deniz Duru
- 4Department of Physical Education and Sports Teaching, Faculty of Sport Sciences, Marmara University, 34815 Beykoz, Istanbul, Turkey
| | - Atilla Uslu
- 5Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, 34093 Çapa, Istanbul, Turkey
| | - Canan Başar-Eroğlu
- 1Institute of Psychology and Cognition Research, University of Bremen, 28359 Bremen, Germany.,6Department of Psychology, Faculty of Arts and Sciences, Izmir University of Economics, 35330 Balçova, Izmir, Turkey
| | - Tamer Demiralp
- 2Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, 34093 Çapa, Istanbul, Turkey.,5Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, 34093 Çapa, Istanbul, Turkey
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Distinguishing Hemodynamics from Function in the Human LGN Using a Temporal Response Model. Vision (Basel) 2019; 3:vision3020027. [PMID: 31735828 PMCID: PMC6802784 DOI: 10.3390/vision3020027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 05/03/2019] [Accepted: 06/04/2019] [Indexed: 11/17/2022] Open
Abstract
We developed a temporal population receptive field model to differentiate the neural and hemodynamic response functions (HRF) in the human lateral geniculate nucleus (LGN). The HRF in the human LGN is dominated by the richly vascularized hilum, a structure that serves as a point of entry for blood vessels entering the LGN and supplying the substrates of central vision. The location of the hilum along the ventral surface of the LGN and the resulting gradient in the amplitude of the HRF across the extent of the LGN have made it difficult to segment the human LGN into its more interesting magnocellular and parvocellular regions that represent two distinct visual processing streams. Here, we show that an intrinsic clustering of the LGN responses to a variety of visual inputs reveals the hilum, and further, that this clustering is dominated by the amplitude of the HRF. We introduced a temporal population receptive field model that includes separate sustained and transient temporal impulse response functions that vary on a much short timescale than the HRF. When we account for the HRF amplitude, we demonstrate that this temporal response model is able to functionally segregate the residual responses according to their temporal properties.
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Brown A, Corner M, Crewther DP, Crewther SG. Human Flicker Fusion Correlates With Physiological Measures of Magnocellular Neural Efficiency. Front Hum Neurosci 2018; 12:176. [PMID: 29867406 PMCID: PMC5960665 DOI: 10.3389/fnhum.2018.00176] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 04/13/2018] [Indexed: 12/22/2022] Open
Abstract
The rapidity with which the visual system can recover from stimulation in order to respond again has important implications for efficiently processing environmental stimuli in real time. To date, there has been little integration of the human psychophysical and physiological research underlying the neural mechanisms contributing to temporal limits on human visual perception. Hence, we investigated the relationship between achromatic flicker fusion frequency and temporal analysis of the magnocellular (M) and parvocellular (P) contributions to the achromatic non-linear multifocal Visual Evoked Potential (mfVEP) responses recorded from occipital scalp (Oz). It was hypothesized, on the basis of higher temporal cut-off frequencies reported for primate M vs. P neurons, that sinusoidal flicker fusion frequencies would negatively correlate with the amplitude of M- but not P-generated non-linearities of the mfVEP. This hypothesis was borne out in 72 typically developing young adults using a four-way forced choice sinusoidal flicker fusion task: amplitudes of all non-linearities that demonstrated a clear M-generated component correlated negatively with flicker thresholds. The strongest of these correlations were demonstrated by the main M non-linearity component (K2.1N70−P100) for both high contrast (r = −0.415, n = 64, p < 0.0005) and low contrast (r = −0.345 n = 63, p < 0.002) conditions, indicating that higher achromatic flicker fusion threshold is linked to a more efficient (smaller second order kernels) M system. None of the peaks related to P activity showed significant correlations. These results establish flicker thresholds as a functional correlate of M-pathway function as can be observed in the non-linear analysis of mfVEP.
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Affiliation(s)
- Alyse Brown
- School of Psychological Science and Public Health, La Trobe University, Melbourne, VIC, Australia
| | - Molly Corner
- School of Psychological Science and Public Health, La Trobe University, Melbourne, VIC, Australia
| | - David P Crewther
- Centre for Human Psychopharmacology, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Sheila G Crewther
- School of Psychological Science and Public Health, La Trobe University, Melbourne, VIC, Australia
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Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role. Prog Neurobiol 2017. [DOI: 10.1016/j.pneurobio.2017.06.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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