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  1. Book ; Online ; E-Book: Advances in resting-state functional MRI

    Chen, Jean / Chang, Catie

    methods, interpretation, and applications

    (Neuroimaging methods and applications series)

    2023  

    Author's details Jean Chen, Catie Chang
    Series title Neuroimaging methods and applications series
    Keywords Electronic books
    Language English
    Size 1 Online-Ressource (xiii, 366 Seiten), Illustrationen, Diagramme
    Publisher Elsevier Academic Press
    Publishing place London
    Publishing country Great Britain
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT030068506
    ISBN 978-0-323-98545-1 ; 9780323916882 ; 0-323-98545-9 ; 0323916880
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: Complex topology meets simple statistics.

    Wang, Shiyu / Chang, Catie

    Nature neuroscience

    2023  Volume 26, Issue 5, Page(s) 732–734

    Language English
    Publishing date 2023-04-24
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1420596-8
    ISSN 1546-1726 ; 1097-6256
    ISSN (online) 1546-1726
    ISSN 1097-6256
    DOI 10.1038/s41593-023-01295-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Dynamic vagal-mediated connectivity of cortical and subcortical central autonomic hubs predicts chronotropic response to submaximal exercise in healthy adults.

    Di Bello, Maria / Chang, Catie / McIntosh, Roger

    Brain and cognition

    2024  Volume 175, Page(s) 106134

    Abstract: Background: Despite accumulation of a substantial body of literature supporting the role of exercise on frontal lobe functioning, relatively less is understood of the interconnectivity of ventromedial prefrontal cortical (vmPFC) regions that underpin ... ...

    Abstract Background: Despite accumulation of a substantial body of literature supporting the role of exercise on frontal lobe functioning, relatively less is understood of the interconnectivity of ventromedial prefrontal cortical (vmPFC) regions that underpin cardio-autonomic regulation predict cardiac chronotropic competence (CC) in response to sub-maximal exercise.
    Methods: Eligibility of 161 adults (mean age = 48.6, SD = 18.3, 68% female) was based upon completion of resting state brain scan and sub-maximal bike test. Sliding window analysis of the resting state signal was conducted over 45-s windows, with 50% overlap, to assess how changes in photoplethysmography-derived HRV relate to vmPFC functional connectivity with the whole brain. CC was assessed based upon heart rate (HR) changes during submaximal exercise (HR change /HRmax (206-0.88 × age) - HRrest).
    Results: During states of elevated HRV the vmPFC showed greater rsFC with an 83-voxel region of the hypothalamus (p < 0.001, uncorrected). Beta estimates of vmPFC connectivity extracted from a 6-mm sphere around this region emerged as the strongest predictor of CC (b = 0.283, p <.001) than age, BMI, and resting HRV F(8,144) = 6.30, p <.001.
    Conclusion: Extensive glutamatergic innervation of the hypothalamus by the vmPFC allows for top-down control of the hypothalamus and its various autonomic efferents which facilitate chronotropic response during sub-maximal exercise.
    MeSH term(s) Adult ; Humans ; Female ; Middle Aged ; Male ; Autonomic Nervous System/physiology ; Brain ; Prefrontal Cortex/physiology ; Frontal Lobe ; Heart Rate/physiology ; Magnetic Resonance Imaging
    Language English
    Publishing date 2024-01-23
    Publishing country United States
    Document type Journal Article
    ZDB-ID 603163-8
    ISSN 1090-2147 ; 0278-2626
    ISSN (online) 1090-2147
    ISSN 0278-2626
    DOI 10.1016/j.bandc.2024.106134
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Editorial: Advancing the measurement, interpretation, and validation of dynamic functional connectivity.

    O'Connor, David / Chang, Catie / Mitsis, Georgios D

    Frontiers in human neuroscience

    2023  Volume 17, Page(s) 1206098

    Language English
    Publishing date 2023-05-11
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2425477-0
    ISSN 1662-5161
    ISSN 1662-5161
    DOI 10.3389/fnhum.2023.1206098
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  5. Article: Multimodal EEG-fMRI: advancing insight into large-scale human brain dynamics.

    Chang, Catie / Chen, Jingyuan E

    Current opinion in biomedical engineering

    2021  Volume 18

    Abstract: Advances in the acquisition and analysis of functional magnetic resonance imaging (fMRI) data are revealing increasingly rich spatiotemporal structure across the human brain. Nonetheless, uncertainty surrounding the origins of fMRI hemodynamic signals, ... ...

    Abstract Advances in the acquisition and analysis of functional magnetic resonance imaging (fMRI) data are revealing increasingly rich spatiotemporal structure across the human brain. Nonetheless, uncertainty surrounding the origins of fMRI hemodynamic signals, and in the link between large-scale fMRI patterns and ongoing functional states, presently limits the neurobiological conclusions one can draw from fMRI alone. Electroencephalography (EEG) provides complementary information about neural electrical activity and state change, and simultaneously acquiring EEG together with fMRI presents unique opportunities for studying large-scale brain activity and gaining more information from fMRI itself. Here, we discuss recent progress in the use of concurrent EEG-fMRI to enrich the investigation of neural and physiological states and clarify the origins of fMRI hemodynamic signals. Throughout, we outline perspectives on future directions and open challenges.
    Language English
    Publishing date 2021-03-15
    Publishing country England
    Document type Journal Article
    ISSN 2468-4511
    ISSN 2468-4511
    DOI 10.1016/j.cobme.2021.100279
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Book ; Online: Leveraging sinusoidal representation networks to predict fMRI signals from EEG

    Li, Yamin / Lou, Ange / Chang, Catie

    2023  

    Abstract: In modern neuroscience, functional magnetic resonance imaging (fMRI) has been a crucial and irreplaceable tool that provides a non-invasive window into the dynamics of whole-brain activity. Nevertheless, fMRI is limited by hemodynamic blurring as well as ...

    Abstract In modern neuroscience, functional magnetic resonance imaging (fMRI) has been a crucial and irreplaceable tool that provides a non-invasive window into the dynamics of whole-brain activity. Nevertheless, fMRI is limited by hemodynamic blurring as well as high cost, immobility, and incompatibility with metal implants. Electroencephalography (EEG) is complementary to fMRI and can directly record the cortical electrical activity at high temporal resolution, but has more limited spatial resolution and is unable to recover information about deep subcortical brain structures. The ability to obtain fMRI information from EEG would enable cost-effective, imaging across a wider set of brain regions. Further, beyond augmenting the capabilities of EEG, cross-modality models would facilitate the interpretation of fMRI signals. However, as both EEG and fMRI are high-dimensional and prone to artifacts, it is currently challenging to model fMRI from EEG. To address this challenge, we propose a novel architecture that can predict fMRI signals directly from multi-channel EEG without explicit feature engineering. Our model achieves this by implementing a Sinusoidal Representation Network (SIREN) to learn frequency information in brain dynamics from EEG, which serves as the input to a subsequent encoder-decoder to effectively reconstruct the fMRI signal from a specific brain region. We evaluate our model using a simultaneous EEG-fMRI dataset with 8 subjects and investigate its potential for predicting subcortical fMRI signals. The present results reveal that our model outperforms a recent state-of-the-art model, and indicates the potential of leveraging periodic activation functions in deep neural networks to model functional neuroimaging data.
    Keywords Electrical Engineering and Systems Science - Signal Processing ; Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Machine Learning
    Subject code 006
    Publishing date 2023-11-05
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning.

    Ward, Simon J / Cao, Tengfei / Zhou, Xiang / Chang, Catie / Weiss, Sharon M

    Biosensors

    2023  Volume 13, Issue 9

    Abstract: We report a versatile platform based on an array of porous silicon (PSi) thin films that can identify analytes based on their physical and chemical properties without the use of specific capture agents. The ability of this system to reproducibly classify, ...

    Abstract We report a versatile platform based on an array of porous silicon (PSi) thin films that can identify analytes based on their physical and chemical properties without the use of specific capture agents. The ability of this system to reproducibly classify, quantify, and discriminate three proteins separately is demonstrated by probing the reflectance of PSi array elements with a unique combination of pore size and buffer pH, and by analyzing the optical signals using machine learning. Protein identification and discrimination are reported over a concentration range of two orders of magnitude. This work represents a significant first step towards a low-cost, simple, versatile, and robust sensor platform that is able to detect biomolecules without the added expense and limitations of using capture agents.
    Language English
    Publishing date 2023-09-09
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662125-3
    ISSN 2079-6374 ; 2079-6374
    ISSN (online) 2079-6374
    ISSN 2079-6374
    DOI 10.3390/bios13090879
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  8. Article ; Online: Dynamic interactions between anterior insula and anterior cingulate cortex link perceptual features and heart rate variability during movie viewing.

    Sonkusare, Saurabh / Wegner, Katharina / Chang, Catie / Dionisio, Sasha / Breakspear, Michael / Cocchi, Luca

    Network neuroscience (Cambridge, Mass.)

    2023  Volume 7, Issue 2, Page(s) 557–577

    Abstract: The dynamic integration of sensory and bodily signals is central to adaptive behaviour. Although the anterior cingulate cortex (ACC) and the anterior insular cortex (AIC) play key roles in this process, their context-dependent dynamic interactions remain ...

    Abstract The dynamic integration of sensory and bodily signals is central to adaptive behaviour. Although the anterior cingulate cortex (ACC) and the anterior insular cortex (AIC) play key roles in this process, their context-dependent dynamic interactions remain unclear. Here, we studied the spectral features and interplay of these two brain regions using high-fidelity intracranial-EEG recordings from five patients (ACC: 13 contacts, AIC: 14 contacts) acquired during movie viewing with validation analyses performed on an independent resting intracranial-EEG dataset. ACC and AIC both showed a power peak and positive functional connectivity in the gamma (30-35 Hz) frequency while this power peak was absent in the resting data. We then used a neurobiologically informed computational model investigating dynamic effective connectivity asking how it linked to the movie's perceptual (visual, audio) features and the viewer's heart rate variability (HRV). Exteroceptive features related to effective connectivity of ACC highlighting its crucial role in processing ongoing sensory information. AIC connectivity was related to HRV and audio emphasising its core role in dynamically linking sensory and bodily signals. Our findings provide new evidence for complementary, yet dissociable, roles of neural dynamics between the ACC and the AIC in supporting brain-body interactions during an emotional experience.
    Language English
    Publishing date 2023-06-30
    Publishing country United States
    Document type Journal Article
    ISSN 2472-1751
    ISSN (online) 2472-1751
    DOI 10.1162/netn_a_00295
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  9. Article ; Online: Structural disconnection relates to functional changes after temporal lobe epilepsy surgery.

    Sainburg, Lucas E / Janson, Andrew P / Johnson, Graham W / Jiang, Jasmine W / Rogers, Baxter P / Chang, Catie / Englot, Dario J / Morgan, Victoria L

    Brain : a journal of neurology

    2024  Volume 146, Issue 9, Page(s) 3913–3922

    Abstract: Epilepsy surgery consists of surgical resection of the epileptic focus and is recommended for patients with drug-resistant focal epilepsy. However, focal brain lesions can lead to effects in distant brain regions. Similarly, the focal resection in ... ...

    Abstract Epilepsy surgery consists of surgical resection of the epileptic focus and is recommended for patients with drug-resistant focal epilepsy. However, focal brain lesions can lead to effects in distant brain regions. Similarly, the focal resection in temporal lobe epilepsy surgery has been shown to lead to functional changes distant from the resection. Here we hypothesize that there are changes in brain function caused by temporal lobe epilepsy surgery in regions distant from the resection that are due to their structural disconnection from the resected epileptic focus. Therefore, the goal of this study was to localize changes in brain function caused by temporal lobe epilepsy surgery and relate them to the disconnection from the resected epileptic focus. This study takes advantage of the unique opportunity that epilepsy surgery provides to investigate the effects of focal disconnections on brain function in humans, which has implications in epilepsy and broader neuroscience. Changes in brain function from pre- to post-epilepsy surgery were quantified in a group of temporal lobe epilepsy patients (n = 36) using a measure of resting state functional MRI activity fluctuations. We identified regions with significant functional MRI changes that had high structural connectivity to the resected region in healthy controls (n = 96) and patients based on diffusion MRI. The structural disconnection from the resected epileptic focus was then estimated using presurgical diffusion MRI and related to the functional MRI changes from pre- to post-surgery in these regions. Functional MRI activity fluctuations increased from pre- to post-surgery in temporal lobe epilepsy in the two regions most highly structurally connected to the resected epileptic focus in healthy controls and patients-the thalamus and the fusiform gyrus ipsilateral to the side of surgery (PFWE < 0.05). Broader surgeries led to larger functional MRI changes in the thalamus than more selective surgeries (P < 0.05), but no other clinical variables were related to functional MRI changes in either the thalamus or fusiform. The magnitude of the functional MRI changes in both the thalamus and fusiform increased with a higher estimated structural disconnection from the resected epileptic focus when controlling for the type of surgery (P < 0.05). These results suggest that the structural disconnection from the resected epileptic focus may contribute to the functional changes seen after epilepsy surgery. Broadly, this study provides a novel link between focal disconnections in the structural brain network and downstream effects on function in distant brain regions.
    MeSH term(s) Humans ; Epilepsy, Temporal Lobe/diagnostic imaging ; Epilepsy, Temporal Lobe/surgery ; Epilepsy, Temporal Lobe/pathology ; Brain/diagnostic imaging ; Brain/surgery ; Brain/pathology ; Magnetic Resonance Imaging ; Diffusion Magnetic Resonance Imaging ; Temporal Lobe/pathology ; Drug Resistant Epilepsy/diagnostic imaging ; Drug Resistant Epilepsy/surgery ; Drug Resistant Epilepsy/pathology
    Language English
    Publishing date 2024-04-04
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 80072-7
    ISSN 1460-2156 ; 0006-8950
    ISSN (online) 1460-2156
    ISSN 0006-8950
    DOI 10.1093/brain/awad117
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  10. Article ; Online: Analysis of stimulus-induced brain dynamics during naturalistic paradigms.

    Simony, Erez / Chang, Catie

    NeuroImage

    2019  Volume 216, Page(s) 116461

    Abstract: Naturalistic stimuli offer promising avenues for investigating brain function across the rich, realistic spectrum of human experiences. Functional magnetic resonance imaging (fMRI) studies of brain activity during naturalistic paradigms have provided new ...

    Abstract Naturalistic stimuli offer promising avenues for investigating brain function across the rich, realistic spectrum of human experiences. Functional magnetic resonance imaging (fMRI) studies of brain activity during naturalistic paradigms have provided new information about dynamic neural processing in ecologically valid contexts. Yet, the complex, uncontrolled nature of such stimuli -- and the resulting mixture of neuronal and physiological responses embedded within the fMRI signals -- present challenges with respect to data analysis and interpretation. In this brief commentary, we discuss methods and open challenges in naturalistic fMRI investigations, with a focus on extracting and interpreting stimulus-induced fMRI signals.
    MeSH term(s) Brain/diagnostic imaging ; Brain/physiology ; Brain Mapping/methods ; Humans ; Magnetic Resonance Imaging/methods ; Photic Stimulation/methods
    Language English
    Publishing date 2019-12-13
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 1147767-2
    ISSN 1095-9572 ; 1053-8119
    ISSN (online) 1095-9572
    ISSN 1053-8119
    DOI 10.1016/j.neuroimage.2019.116461
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