scholarly journals A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Krzysztof J Gorgolewski ◽  
Natacha Mendes ◽  
Domenica Wilfling ◽  
Elisabeth Wladimirow ◽  
Claudine J Gauthier ◽  
...  
Keyword(s):  
High Resolution ◽  
Resting State ◽  
Resting State Fmri ◽  
7 Tesla ◽  
Physiological Measures

scholarly journals A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures

2014 ◽  
Author(s):  
Krzysztof Jacek Gorgolewski ◽  
Natacha Mendes ◽  
Domenica Wilfling ◽  
Elisabeth Wladimirow ◽  
Claudine J. Gauthier ◽  
...  
Keyword(s):  
High Spatial Resolution ◽  
Resting State Fmri ◽  
7 Tesla ◽  
Physiological Changes ◽  
Physiological Measures ◽  
Affective States ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Experimental Protocol ◽  
Brain Scans

Here we present a test-retest dataset of functional magnetic resonance imaging (fMRI) data acquired at rest. 22 participants were scanned during two sessions spaced one week apart. Each session includes two 1.5 mm isotropic whole-brain scans and one 0.75 mm isotropic scan of the prefrontal cortex, giving a total of six timepoints. Additionally, the dataset includes measures of mood, sustained attention, blood pressure, respiration, pulse, and the content of self-generated thoughts (mind wandering). This data enables the investigation of sources of both intra- and inter-session variability not only limited to physiological changes, but also including alterations in cognitive and affective states, at high spatial resolution. The dataset is accompanied by a detailed experimental protocol and source code of all stimuli used.

scholarly journals Functional connectome of brainstem nuclei involved in autonomic, limbic, pain and sensory processing in living humans from 7 Tesla resting state fMRI

2021 ◽  
Author(s):  
Simone Cauzzo ◽  
KAVITA SINGH ◽  
Matthew Matthew Stauder ◽  
Maria Guadalupe Garcia-Gomar ◽  
Nicola Vanello ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Sensory Function ◽  
3 Tesla ◽  
7 Tesla ◽  
Reticular Nucleus ◽  
Isotropic Resolution ◽  
Functional Connectome ◽  
Brainstem Nuclei

Despite remarkable advances in mapping the functional connectivity of the cortex, the functional connectivity of subcortical regions is understudied in living humans. This is the case for brainstem nuclei that control vital processes, such as autonomic, limbic, nociceptive and sensory functions. This is because of the lack of precise brainstem nuclei localization, of adequate sensitivity and resolution in the deepest brain regions, as well as of optimized processing for the brainstem. To close the gap between the cortex and the brainstem, on 20 healthy subjects, we computed a correlation based functional connectome of 15 brainstem nuclei involved in autonomic, limbic, nociceptive, and sensory function (superior and inferior colliculi, ventral tegmental area parabrachial pigmented nucleus complex, microcellular tegmental nucleus prabigeminal nucleus complex, lateral and medial parabrachial nuclei, vestibular and superior olivary complex, superior and inferior medullary reticular formation, viscerosensory motor nucleus, raphe magnus, pallidus, and obscurus, and parvicellular reticular nucleus alpha part) with the rest of the brain. Specifically, we exploited 1.1mm isotropic resolution 7 Tesla resting state fMRI, ad hoc coregistration and physiological noise correction strategies, and a recently developed probabilistic template of brainstem nuclei. Further, we used 2.5mm isotropic resolution resting state fMRI data acquired on a 3 Tesla scanner to assess the translatability of our results to conventional datasets. We report highly consistent correlation coefficients across subjects, confirming available literature on autonomic, limbic, nociceptive and sensory pathways, as well as high interconnectivity within the central autonomic network and the vestibular network. Interestingly, our results showed evidence of vestibulo autonomic interactions in line with previous work. Comparison of 7 Tesla and 3 Tesla findings showed high translatability of results to conventional settings for brainstem cortical connectivity and good yet weaker translatability for brainstem brainstem connectivity. The brainstem functional connectome might bring new insight in the understanding of autonomic, limbic, nociceptive and sensory function in health and disease.

scholarly journals Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI

2021 ◽  
Author(s):  
kavita singh ◽  
Simone Cauzzo ◽  
Maria Guadalupe Garcia-Gomar ◽  
Matthew Stauder ◽  
Nicola Vanello ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Resting State ◽  
Resting State Fmri ◽  
3 Tesla ◽  
7 Tesla ◽  
Resting State Functional Connectivity ◽  
Functional Connectome ◽  
Brainstem Nuclei ◽  
The Brain

Brainstem nuclei play a pivotal role in many functions, such as arousal and motor control. Nevertheless, the connectivity of arousal and motor brainstem nuclei is understudied in living humans due to the limited sensitivity and spatial resolution of conventional imaging, and to the lack of atlases of these deep tiny regions of the brain. For a holistic comprehension of sleep, arousal and associated motor processes, we investigated in 20 healthy subjects the resting-state functional connectivity of 18 arousal and motor brainstem nuclei in living humans. To do so, we used high spatial-resolution 7 Tesla resting-state fMRI, as well as a recently developed in-vivo probabilistic atlas of these nuclei in stereotactic space. Further, we verified the translatability of our brainstem connectome approach to conventional (e.g. 3 Tesla) fMRI. Arousal brainstem nuclei displayed high interconnectivity, as well as connectivity to the thalamus, hypothalamus, basal forebrain and frontal cortex, in line with animal studies and as expected for arousal regions. Motor brainstem nuclei showed expected connectivity to the cerebellum, basal ganglia and motor cortex, as well as high interconnectivity. Comparison of 3 Tesla to 7 Tesla connectivity results indicated good translatability of our brainstem connectome approach to conventional fMRI, especially for cortical and subcortical (non-brainstem) targets and to a lesser extent for brainstem targets. The functional connectome of 18 arousal and motor brainstem nuclei with the rest of the brain might provide a better understanding of arousal, sleep and accompanying motor function in living humans in health and disease.

Whole brain, high resolution spin-echo resting state fMRI using PINS multiplexing at 7T

NeuroImage ◽  
2012 ◽  
Vol 62 (3) ◽  
pp. 1939-1946 ◽  
Author(s):  
Peter J. Koopmans ◽  
Rasim Boyacioğlu ◽  
Markus Barth ◽  
David G. Norris
Keyword(s):  
High Resolution ◽  
Resting State ◽  
Spin Echo ◽  
Resting State Fmri ◽  
Whole Brain

scholarly journals Improved 7 Tesla resting-state fMRI connectivity measurements by cluster-based modeling of respiratory volume and heart rate effects

NeuroImage ◽  
2017 ◽  
Vol 153 ◽  
pp. 262-272 ◽  
Author(s):  
Joana Pinto ◽  
Sandro Nunes ◽  
Marta Bianciardi ◽  
Afonso Dias ◽  
L. Miguel Silveira ◽  
...  
Keyword(s):  
Heart Rate ◽  
Resting State ◽  
Resting State Fmri ◽  
7 Tesla ◽  
Respiratory Volume ◽  
Rate Effects

scholarly journals Understanding the Effect of Left Prefrontal Stimulation on Positive Symptoms of Schizophrenia: A Dynamic Causal Modeling Study of Ultra-high field (7-Tesla) Resting-state fMRI

2020 ◽  
Author(s):  
Roberto Limongi ◽  
Michael Mackinley ◽  
Kara Dempster ◽  
Ali R. Khan ◽  
Joseph S. Gati ◽  
...  
Keyword(s):  
Resting State ◽  
High Field ◽  
Negative Symptoms ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
7 Tesla ◽  
Positive Symptoms ◽  
Dynamic Causal Modeling ◽  
Ultra High Field ◽  
Inhibitory Tone

AbstractRepetitive transcranial magnetic stimulation (rTMS), when applied to left dorsolateral prefrontal cortex (LDLPFC), reduces negative symptoms of schizophrenia, but has no effect on positive symptoms. In a small number of cases, it appears to worsen the severity of positive symptoms. It has been hypothesized that high frequency rTMS of the LDLPFC might increase the dopaminergic neurotransmission by driving the activity of the left striatum in the basal ganglia (LSTR)—increasing striatal dopaminergic activity. This hypothesis relies on the assumption that either the frontal-striatal connection or the intrinsic frontal and/or striatal connections covary with the severity of positive symptoms. The current work aimed to evaluate this assumption by studying the association between positive and negative symptoms severity and the effective connectivity within the frontal and striatal network using dynamic causal modeling (DCM) of ultra-high field (7 Tesla) resting state fMRI in a sample of 19 first episode psychosis (FEP) subjects. We found that of all core symptoms of schizophrenia, only delusions are strongly associated with the fronto striatal circuitry. Stronger intrinsic inhibitory tone of LDLPFC and LSTR, as well as a pronounced backward inhibition of the LDLPFC on the LSTR related to the severity of delusions. We interpret that an increase in striatal dopaminergic tone that underlies delusional symptoms, is likely associated with increased prefrontal inhibitory tone, strengthening the frontostriatal ‘brake’. Furthermore, based on our model, we propose that lessening of positive symptoms could be achieved by means of continuous theta-burst or low frequency (1Hz) rTMS of the prefrontal area.

scholarly journals T52. ABERRANT SENSORY PRECISION IN FIRST-EPISODE PSYCHOSIS: A 7-TESLA RESTING-STATE FMRI AND STROOP-TASK STUDY

2019 ◽  
Vol 45 (Supplement_2) ◽  
pp. S223-S224
Author(s):  
Roberto Limongi ◽  
Peter Jeon ◽  
Kara Dempster ◽  
Michael Mackinley ◽  
Jean Theberge ◽  
...  
Keyword(s):  
Stroop Task ◽  
Resting State ◽  
Resting State Fmri ◽  
First Episode Psychosis ◽  
7 Tesla ◽  
First Episode ◽  
Episode Psychosis

scholarly journals Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI

NeuroImage ◽  
2022 ◽  
pp. 118865
Author(s):  
Kavita Singh ◽  
Simone Cauzzo ◽  
María Guadalupe García-Gomar ◽  
Matthew Stauder ◽  
Nicola Vanello ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
7 Tesla ◽  
Functional Connectome ◽  
Brainstem Nuclei

scholarly journals GP.04 Network connectivity following a single unprovoked seizure using 7 Tesla resting-state fMRI

2017 ◽  
Vol 44 (S2) ◽  
pp. S8-S8
Author(s):  
KM Ikeda ◽  
SM Mirsattari ◽  
AR Khan ◽  
I Johnsrude ◽  
JG Burneo ◽  
...  
Keyword(s):  
Functional Mri ◽  
Resting State ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Brain Network ◽  
Clustering Coefficient ◽  
7 Tesla ◽  
Unprovoked Seizure ◽  
Whole Brain ◽  
Network Function

Background: Predicting epilepsy following a first seizure is difficult. Network abnormalities are observed in patients with epilepsy using resting-state functional MRI (rs-fMRI), which worsen with duration of epilepsy. We use rs-fMRI to identify network abnormalities in patients after a first seizure that can be used as a biomarker to predict development of epilepsy. Methods: Patients after a single, unprovoked seizure and age/sex matched healthy controls underwent 7 Tesla structural and resting-state functional MRI. Data were analyzed using graph theory measures. Patients were followed for development of epilepsy. Results: Nine patients and nine control subjects were analyzed. There were no differences in baseline characteristics. No patients developed epilepsy (average follow-up 3 months). No differences between groups occurred on a whole-brain network level. At a 20% threshold, significant differences occurred in the default mode network (DMN). Patients demonstrated an increased local efficiency (p=0.02) and clustering coefficient (p=0.04), and decreased path length (p=0.02) and betweenness centrality (p=0.02). Conclusions: No whole-brain network changes occur after a single unprovoked seizure. No patient has developed epilepsy suggesting this group does not have network alterations after a single seizure. In the DMN, the alterations noted indicate increased segregation of network function.

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