High spatial correlation in brain connectivity between micturition and resting states within bladder-related networks using 7 T MRI in multiple sclerosis women with voiding dysfunction

Abstract Background Several studies have reported brain activations and functional connectivity (FC) during micturition using functional magnetic resonance imaging (fMRI) and concurrent urodynamics (UDS) testing. However, due to the invasive nature of UDS procedure, non-invasive resting-state fMRI is being explored as a potential alternative. The purpose of this study is to evaluate the feasibility of utilizing resting states as a non-invasive alternative for investigating the bladder-related networks in the brain. Methods We quantitatively compared FC in brain regions belonging to the bladder-related network during the following states: ‘strong desire to void’, ‘voiding initiation (or attempt at voiding initiation)’, and ‘voiding (or continued attempt of voiding)’ with FC during rest in nine multiple sclerosis women with voiding dysfunction using fMRI data acquired at 7 T and 3 T. Results The inter-subject correlation analysis showed that voiding (or continued attempt of voiding) is achieved through similar network connections in all subjects. The task-based bladder-related network closely resembles the resting-state intrinsic network only during voiding (or continued attempt of voiding) process but not at other states. Conclusion Resting states fMRI can be potentially utilized to accurately reflect the voiding (or continued attempt of voiding) network. Concurrent UDS testing is still necessary for studying the effects of strong desire to void and initiation of voiding (or attempt at initiation of voiding).

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Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

10.1101/2021.02.08.430334 ◽

2021 ◽

Author(s):

Takashi Nakano ◽

Masahiro Takamura ◽

Haruki Nishimura ◽

Maro Machizawa ◽

Naho Ichikawa ◽

...

Keyword(s):

Resting State ◽

Brain Connectivity ◽

Brain Activity ◽

Resting State Fmri ◽

Brain Regions ◽

Posterior Cingulate Cortex ◽

Fmri Data ◽

Independent Test ◽

The Individual ◽

The Brain

AbstractNeurofeedback (NF) aptitude, which refers to an individual’s ability to change its brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical NF applications. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude independent of NF-targeting brain regions. We combined the data in fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect the resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Next we validated the prediction model using independent test data from another site. The result showed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting NF aptitude may be involved in the attentional mode-orientation modulation system’s characteristics in task-free resting-state brain activity.

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Graph Ricci Curvatures Reveal Disease-related Changes in Autism Spectrum Disorder

10.1101/2021.11.28.470231 ◽

2021 ◽

Author(s):

Pavithra Elumalai ◽

Yasharth Yadav ◽

Nitin Williams ◽

Emil Saucan ◽

Jürgen Jost ◽

...

Keyword(s):

Autism Spectrum Disorder ◽

Resting State ◽

Neurodevelopmental Disorders ◽

Data Exchange ◽

Meta Analysis ◽

Resting State Fmri ◽

Brain Regions ◽

Autism Spectrum ◽

Spectrum Disorder ◽

The Brain

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders that pose a significant global health burden. Measures from graph theory have been used to characterise ASD-related changes in resting-state fMRI functional connectivity networks (FCNs), but recently developed geometry-inspired measures have not been applied so far. In this study, we applied geometry-inspired graph Ricci curvatures to investigate ASD-related changes in resting-state fMRI FCNs. To do this, we applied Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and healthy controls (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We performed these comparisons at the brain-wide level as well as at the level of individual brain regions, and further, determined the behavioral relevance of region-specific differences with Neurosynth meta-analysis decoding. We found brain-wide ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures. For Forman-Ricci curvature, these differences were distributed across 83 of the 200 brain regions studied, and concentrated within the Default Mode, Somatomotor and Ventral Attention Network. Meta-analysis decoding identified the brain regions showing curvature differences as involved in social cognition, memory, language and movement. Notably, comparison with results from previous non-invasive stimulation (TMS/tDCS) experiments revealed that the set of brain regions showing curvature differences overlapped with the set of brain regions whose stimulation resulted in positive cognitive or behavioural outcomes in ASD patients. These results underscore the utility of geometry-inspired graph Ricci curvatures in characterising disease-related changes in ASD, and possibly, other neurodevelopmental disorders.

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Resting state functional magnetic resonance imaging processing techniques in stroke studies

Reviews in the Neurosciences ◽

10.1515/revneuro-2016-0052 ◽

2016 ◽

Vol 27 (8) ◽

pp. 871-885 ◽

Cited By ~ 7

Author(s):

Golrokh Mirzaei ◽

Hojjat Adeli

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Functional Magnetic Resonance Imaging ◽

Resting State ◽

Brain Connectivity ◽

Functional Magnetic Resonance ◽

Resonance Imaging ◽

Stroke Patients ◽

Processing Techniques ◽

The Brain

AbstractIn recent years, there has been considerable research interest in the study of brain connectivity using the resting state functional magnetic resonance imaging (rsfMRI). Studies have explored the brain networks and connection between different brain regions. These studies have revealed interesting new findings about the brain mapping as well as important new insights in the overall organization of functional communication in the brain network. In this paper, after a general discussion of brain networks and connectivity imaging, the brain connectivity and resting state networks are described with a focus on rsfMRI imaging in stroke studies. Then, techniques for preprocessing of the rsfMRI for stroke patients are reviewed, followed by brain connectivity processing techniques. Recent research on brain connectivity using rsfMRI is reviewed with an emphasis on stroke studies. The authors hope this paper generates further interest in this emerging area of computational neuroscience with potential applications in rehabilitation of stroke patients.

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Effective brain connectivity estimation between active brain regions in autism using the dual Kalman-based method

Biomedical Engineering / Biomedizinische Technik ◽

10.1515/bmt-2019-0062 ◽

2020 ◽

Vol 65 (1) ◽

pp. 23-32

Author(s):

Mehdi Rajabioun ◽

Ali Motie Nasrabadi ◽

Mohammad Bagher Shamsollahi ◽

Robert Coben

Keyword(s):

Resting State ◽

Brain Connectivity ◽

Effective Connectivity ◽

Estimation Error ◽

Brain Regions ◽

Estimation Methods ◽

Estimation Errors ◽

Normal Children ◽

Brain Functions ◽

The Brain

AbstractBrain connectivity estimation is a useful method to study brain functions and diagnose neuroscience disorders. Effective connectivity is a subdivision of brain connectivity which discusses the causal relationship between different parts of the brain. In this study, a dual Kalman-based method is used for effective connectivity estimation. Because of connectivity changes in autism, the method is applied to autistic signals for effective connectivity estimation. For method validation, the dual Kalman based method is compared with other connectivity estimation methods by estimation error and the dual Kalman-based method gives acceptable results with less estimation errors. Then, connectivities between active brain regions of autistic and normal children in the resting state are estimated and compared. In this simulation, the brain is divided into eight regions and the connectivity between regions and within them is calculated. It can be concluded from the results that in the resting state condition the effective connectivity of active regions is decreased between regions and is increased within each region in autistic children. In another result, by averaging the connectivity between the extracted active sources of each region, the connectivity between the left and right of the central part is more than that in other regions and the connectivity in the occipital part is less than that in others.

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Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI

Brain Sciences ◽

10.3390/brainsci12010066 ◽

2021 ◽

Vol 12 (1) ◽

pp. 66

Author(s):

Lan Yang ◽

Jing Wei ◽

Ying Li ◽

Bin Wang ◽

Hao Guo ◽

...

Keyword(s):

Resting State ◽

Resting State Fmri ◽

Resting State Networks ◽

Functional Magnetic Resonance ◽

Intra Class Correlation ◽

Retest Reliability ◽

Brain Signals ◽

Human Connectome Project ◽

Test Retest Reliability ◽

The Brain

In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals.

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Resting-State fMRI in MS: General Concepts and Brief Overview of Its Application

BioMed Research International ◽

10.1155/2015/212693 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 19

Author(s):

Emilia Sbardella ◽

Nikolaos Petsas ◽

Francesca Tona ◽

Patrizia Pantano

Keyword(s):

Multiple Sclerosis ◽

Resting State ◽

Brain Function ◽

Region Of Interest ◽

Resting State Fmri ◽

Research Field ◽

Clinical Impairment ◽

The Central Nervous System ◽

Brain Functional Connectivity ◽

The Brain

Brain functional connectivity (FC) is defined as the coherence in the activity between cerebral areas under a task or in the resting-state (RS). By applying functional magnetic resonance imaging (fMRI), RS FC shows several patterns which define RS brain networks (RSNs) involved in specific functions, because brain function is known to depend not only on the activity within individual regions, but also on the functional interaction of different areas across the whole brain. Region-of-interest analysis and independent component analysis are the two most commonly applied methods for RS investigation. Multiple sclerosis (MS) is characterized by multiple lesions mainly affecting the white matter, determining both structural and functional disconnection between various areas of the central nervous system. The study of RS FC in MS is mainly aimed at understanding alterations in the intrinsic functional architecture of the brain and their role in disease progression and clinical impairment. In this paper, we will examine the results obtained by the application of RS fMRI in different multiple sclerosis (MS) phenotypes and the correlations of FC changes with clinical features in this pathology. The knowledge of RS FC changes may represent a substantial step forward in the MS research field, both for clinical and therapeutic purposes.

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Social cognition in Multiple Sclerosis is associated to changes in brain connectivity: A resting-state fMRI study

Multiple Sclerosis and Related Disorders ◽

10.1016/j.msard.2020.102333 ◽

2020 ◽

Vol 45 ◽

pp. 102333

Author(s):

Tomas P. Labbe ◽

Mariana Zurita ◽

Cristian Montalba ◽

Ethel L. Ciampi ◽

Juan P. Cruz ◽

...

Keyword(s):

Multiple Sclerosis ◽

Social Cognition ◽

Resting State ◽

Brain Connectivity ◽

Resting State Fmri ◽

Fmri Study

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Brain connectivity at different time-scales measured with EEG

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2005.1649 ◽

2005 ◽

Vol 360 (1457) ◽

pp. 1015-1024 ◽

Cited By ~ 91

Author(s):

T Koenig ◽

D Studer ◽

D Hubl ◽

L Melie ◽

W.K Strik

Keyword(s):

Frequency Domain ◽

Brain Connectivity ◽

Time Domain Analysis ◽

Domain Analysis ◽

Brain Regions ◽

Frequency Domain Analysis ◽

Functional Magnetic Resonance ◽

Eeg Signals ◽

Electroencephalogram Eeg ◽

The Brain

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

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Functional MRI

10.1093/med/9780190297763.001.0001 ◽

2018 ◽

Keyword(s):

Functional Mri ◽

Resting State ◽

Brain Activity ◽

Low Frequency ◽

Resting State Fmri ◽

Blood Oxygen Level Dependent ◽

Brain Regions ◽

Functional Brain Imaging ◽

Fmri Signal ◽

The Brain

Functional MRI with BOLD (Blood Oxygen Level Dependent) imaging is one of the commonly used modalities for studying brain function in neuroscience. The underlying source of the BOLD fMRI signal is the variation in oxyhemoglobin to deoxyhemoglobin ratio at the site of neuronal activity in the brain. fMRI is mostly used to map out the location and intensity of brain activity that correlate with mental activities. In recent years, a new approach to fMRI was developed that is called resting-state fMRI. The fMRI signal from this method does not require the brain to perform any goal-directed task; it is acquired with the subject at rest. It was discovered that there are low-frequency fluctuations in the fMRI signal in the brain at rest. The signals originate from spatially distinct functionally related brain regions but exhibit coherent time-synchronous fluctuations. Several of the networks have been identified and are called resting-state networks. These networks represent the strength of the functional connectivity between distinct functionally related brain regions and have been used as imaging markers of various neurological and psychiatric diseases. Resting-state fMRI is also ideally suited for functional brain imaging in disorders of consciousness and in subjects under anesthesia. This book provides a review of the basic principles of fMRI (signal sources, acquisition methods, and data analysis) and its potential clinical applications.

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Therapeutic effects of non-invasive, individualized, transcranial neuromodulation treatment for voiding dysfunction in multiple sclerosis patients: study protocol for a pilot clinical trial

Pilot and Feasibility Studies ◽

10.1186/s40814-021-00825-z ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Khue Tran ◽

Zhaoyue Shi ◽

Christof Karmonik ◽

Blessy John ◽

Hamida Rajab ◽

...

Keyword(s):

Multiple Sclerosis ◽

Clinical Trial ◽

Urinary Tract ◽

Functional Mri ◽

Lower Urinary Tract ◽

Voiding Dysfunction ◽

Therapeutic Effects ◽

Non Invasive ◽

The Brain ◽

Lower Urinary

Abstract Background Voiding dysfunction (VD) is a common neurogenic lower urinary tract dysfunction (NLUTD) in multiple sclerosis (MS) patients. Currently, the only effective management for VD and urinary retention in MS patients is catheterization, prompting us to look for novel therapeutic options beyond the bladder, such as the brain. Transcranial rotating permanent magnet stimulator (TRPMS) is a non-invasive, portable, multifocal neuromodulator that simultaneously modulates multiple cortical regions, enhancing or attenuating strengths of functional connections between these regions. The objective of this pilot clinical trial is to evaluate the feasibility of a TRPMS trial to address lower urinary tract symptoms in MS patients, through investigating the therapeutic effects of TRPMS in modulating brain regions during voiding initiation and mitigating VD in female MS individuals. Methods Ten adult female MS patients with VD (defined as having %post-void residual/bladder capacity (%PVR/BC) ≥ 40% or Liverpool nomogram percentile < 10%) will be recruited for this study. Concurrent urodynamic and functional MRI evaluation with a bladder filling/emptying task repeated three to four times will be performed at baseline and post-treatment. Predetermined regions of interest and their blood-oxygen-level-dependent (BOLD) activation at voiding initiation will be identified on each patient’s baseline anatomical and functional MRI scan, corresponding to the microstimulators placement on their individualized TRPMS treatment cap to either stimulate or inhibit these regions. Patients will receive 10 40-min treatment sessions. Non-instrumented uroflow and validated questionnaires will also be collected at baseline and post-treatment to evaluate clinical improvement. Discussion Despite the crucial role of the central nervous system in urinary control and its sensitivity to MS, there has been no treatment for urinary dysfunction targeting the brain centers that are involved in proper bladder function. This trial, to our knowledge, will be the first of its kind in humans to consider non-invasive and individualized cortical modulation for treating VD in MS patients. Results from this study will provide a better understanding of the brain control of neurogenic bladders and lay the foundation for a potential alternative therapy for VD in MS patients and other NLUTD in a larger neurogenic population in the future. Trial registration This trial is registered at ClinicalTrials.Gov (NCT03574610, 2 July 2018.) and Houston Methodist Research Institute IRB (PRO00019329)

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