scholarly journals Dissociating tinnitus patients from healthy controls using resting-state cyclicity analysis and clustering

2019 ◽  
Vol 3 (1) ◽  
pp. 67-89 ◽  
Author(s):  
Benjamin J. Zimmerman ◽  
Ivan Abraham ◽  
Sara A. Schmidt ◽  
Yuliy Baryshnikov ◽  
Fatima T. Husain
Keyword(s):  
Resting State ◽  
Classification Accuracy ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Fmri Data ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Physiological Models ◽  
Analysis Stability

Chronic tinnitus is a common and sometimes debilitating condition that lacks scientific consensus on physiological models of how the condition arises as well as any known cure. In this study, we applied a novel cyclicity analysis, which studies patterns of leader-follower relationships between two signals, to resting-state functional magnetic resonance imaging (rs-fMRI) data of brain regions acquired from subjects with and without tinnitus. Using the output from the cyclicity analysis, we were able to differentiate between these two groups with 58–67% accuracy by using a partial least squares discriminant analysis. Stability testing yielded a 70% classification accuracy for identifying individual subjects’ data across sessions 1 week apart. Additional analysis revealed that the pairs of brain regions that contributed most to the dissociation between tinnitus and controls were those connected to the amygdala. In the controls, there were consistent temporal patterns across frontal, parietal, and limbic regions and amygdalar activity, whereas in tinnitus subjects, this pattern was much more variable. Our findings demonstrate a proof-of-principle for the use of cyclicity analysis of rs-fMRI data to better understand functional brain connectivity and to use it as a tool for the differentiation of patients and controls who may differ on specific traits.

scholarly journals Resting-State Functional Magnetic Resonance Imaging Connectivity Between Semantic and Phonological Regions of Interest May Inform Language Targets in Aphasia

2020 ◽  
Vol 63 (9) ◽  
pp. 3051-3067
Author(s):  
Amy E. Ramage ◽  
Semra Aytur ◽  
Kirrie J. Ballard
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Brain Regions ◽  
Regions Of Interest ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Language Performance

Purpose Brain imaging has provided puzzle pieces in the understanding of language. In neurologically healthy populations, the structure of certain brain regions is associated with particular language functions (e.g., semantics, phonology). In studies on focal brain damage, certain brain regions or connections are considered sufficient or necessary for a given language function. However, few of these account for the effects of lesioned tissue on the “functional” dynamics of the brain for language processing. Here, functional connectivity (FC) among semantic–phonological regions of interest (ROIs) is assessed to fill a gap in our understanding about the neural substrates of impaired language and whether connectivity strength can predict language performance on a clinical tool in individuals with aphasia. Method Clinical assessment of language, using the Western Aphasia Battery–Revised, and resting-state functional magnetic resonance imaging data were obtained for 30 individuals with chronic aphasia secondary to left-hemisphere stroke and 18 age-matched healthy controls. FC between bilateral ROIs was contrasted by group and used to predict Western Aphasia Battery–Revised scores. Results Network coherence was observed in healthy controls and participants with stroke. The left–right premotor cortex connection was stronger in healthy controls, as reported by New et al. (2015) in the same data set. FC of (a) connections between temporal regions, in the left hemisphere and bilaterally, predicted lexical–semantic processing for auditory comprehension and (b) ipsilateral connections between temporal and frontal regions in both hemispheres predicted access to semantic–phonological representations and processing for verbal production. Conclusions Network connectivity of brain regions associated with semantic–phonological processing is predictive of language performance in poststroke aphasia. The most predictive connections involved right-hemisphere ROIs—particularly those for which structural adaptions are known to associate with recovered word retrieval performance. Predictions may be made, based on these findings, about which connections have potential as targets for neuroplastic functional changes with intervention in aphasia. Supplemental Material https://doi.org/10.23641/asha.12735785

Reduced connectivity of the auditory cortex in patients with auditory hallucinations: a resting state functional magnetic resonance imaging study

2009 ◽  
Vol 40 (7) ◽  
pp. 1149-1158 ◽  
Author(s):  
M. Gavrilescu ◽  
S. Rossell ◽  
G. W. Stuart ◽  
T. L. Shea ◽  
H. Innes-Brown ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Connectivity ◽  
Resting State ◽  
Auditory Hallucinations ◽  
Fmri Data ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Interhemispheric Connectivity

BackgroundPrevious research has reported auditory processing deficits that are specific to schizophrenia patients with a history of auditory hallucinations (AH). One explanation for these findings is that there are abnormalities in the interhemispheric connectivity of auditory cortex pathways in AH patients; as yet this explanation has not been experimentally investigated. We assessed the interhemispheric connectivity of both primary (A1) and secondary (A2) auditory cortices in n=13 AH patients, n=13 schizophrenia patients without auditory hallucinations (non-AH) and n=16 healthy controls using functional connectivity measures from functional magnetic resonance imaging (fMRI) data.MethodFunctional connectivity was estimated from resting state fMRI data using regions of interest defined for each participant based on functional activation maps in response to passive listening to words. Additionally, stimulus-induced responses were regressed out of the stimulus data and the functional connectivity was estimated for the same regions to investigate the reliability of the estimates.ResultsAH patients had significantly reduced interhemispheric connectivity in both A1 and A2 when compared with non-AH patients and healthy controls. The latter two groups did not show any differences in functional connectivity. Further, this pattern of findings was similar across the two datasets, indicating the reliability of our estimates.ConclusionsThese data have identified a trait deficit specific to AH patients. Since this deficit was characterized within both A1 and A2 it is expected to result in the disruption of multiple auditory functions, for example, the integration of basic auditory information between hemispheres (via A1) and higher-order language processing abilities (via A2).

scholarly journals Globally conditioned Granger causality in brain–brain and brain–heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study

2016 ◽  
Vol 374 (2067) ◽  
pp. 20150185 ◽  
Author(s):  
Andrea Duggento ◽  
Marta Bianciardi ◽  
Luca Passamonti ◽  
Lawrence L. Wald ◽  
Maria Guerrisi ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Resting State ◽  
High Field ◽  
Brain Activity ◽  
Brain Regions ◽  
Sympathovagal Balance ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Ultra High Field ◽  
Conditioned Approach

The causal, directed interactions between brain regions at rest (brain–brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain–heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain–brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain–brain and brain–heart interactions reflecting central modulation of ANS outflow.

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

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.

Resting state functional magnetic resonance imaging processing techniques in stroke studies

2016 ◽  
Vol 27 (8) ◽  
pp. 871-885 ◽  
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.

scholarly journals Effect of Subanesthetic Ketamine on Intrinsic Functional Brain Connectivity

2012 ◽  
Vol 117 (4) ◽  
pp. 868-877 ◽  
Author(s):  
Marieke Niesters ◽  
Najmeh Khalili-Mahani ◽  
Christian Martini ◽  
Leon Aarts ◽  
Joop van Gerven ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Anterior Cingulate Cortex ◽  
Resting State ◽  
Brain Connectivity ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging

Background The influence of psychoactive drugs on the central nervous system has been investigated with positron emission tomography and task-related functional magnetic resonance imaging. However, it is not known how these drugs affect the intrinsic large-scale interactions of the brain (resting-state functional magnetic resonance imaging connectivity). In this study, the effect of low-dose S(+)-ketamine on intrinsic brain connectivity was investigated. Methods Twelve healthy, male volunteers received a 2-h intravenous S(+)-ketamine infusion (first hour 20 mg/70 kg, second hour 40 mg/70 kg). Before, during, and after S(+)-ketamine administration, resting-state brain connectivity was measured. In addition, heat pain tests were performed between imaging sessions to determine ketamine-induced analgesia. A mixed-effects general linear model was used to determine drug and pain effects on resting-state brain connectivity. Results Ketamine increased the connectivity most importantly in the cerebellum and visual cortex in relation to the medial visual network. A decrease in connectivity was observed in the auditory and somatosensory network in relation to regions responsible for pain sensing and the affective processing of pain, which included the amygdala, insula, and anterior cingulate cortex. Connectivity variations related to fluctuations in pain scores were observed in the anterior cingulate cortex, insula, orbitofrontal cortex, and the brainstem, regions involved in descending inhibition of pain. Conclusions Changes in connectivity were observed in the areas that explain ketamine's pharmacodynamic profile with respect to analgesia and psychedelic and other side effects. In addition, pain and ketamine changed brain connectivity in areas involved in endogenous pain modulation.

Depression is associated with disconnection of neurotransmitter-related nuclei in multiple sclerosis

2020 ◽  
pp. 135245852094821
Author(s):  
Matteo Martino ◽  
Paola Magioncalda ◽  
Mohamed Mounir El Mendili ◽  
Amgad Droby ◽  
Swetha Paduri ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Resting State ◽  
Depressive Symptomatology ◽  
Healthy Controls ◽  
Diffusion Weighted Mri ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Functional Connections ◽  
Brainstem Nuclei ◽  
And Diffusion

Background: Depression is frequently associated with multiple sclerosis (MS). However, the biological background underlying such association is poorly understood. Objective: Investigating the functional connections of neurotransmitter-related brainstem nuclei, along with their relationship with white matter (WM) microstructure, in MS patients with depressive symptomatology (MS-D) and without depressive symptomatology (MS-nD). Methods: Combined resting-state functional magnetic resonance imaging (fMRI) and diffusion-weighted MRI (dMRI) study on 50 MS patients, including 19 MS-D and 31 MS-nD patients, along with 37 healthy controls (HC). Main analyses performed are (1) comparison between groups of raphe nuclei (RN)-related functional connectivity (FC); (2) correlation between RN-related FC and whole brain dMRI-derived fractional anisotropy (FA) map; and (3) comparison between groups of FA in the RN-related WM area. Results: (1) RN-related FC was reduced in MS-D when compared to MS-nD and HC; (2) RN-related FC positively correlated with FA in a WM cluster mainly encompassing thalamic/basal ganglia regions, including the fornix; and (3) FA in such WM area was reduced in MS-D. Conclusion: Depressive symptomatology in MS is specifically associated to a functional disconnection of neurotransmitter-related nuclei, which in turn may be traced to a distinct spatial pattern of WM alterations mainly involving the limbic network.

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