scholarly journals Assessing uncertainty in connective field estimations from resting state fMRI activity

2020 ◽  
Author(s):  
Azzurra Invernizzi ◽  
Nicolas Gravel ◽  
Koen V. Haak ◽  
Remco J. Renken ◽  
Frans W. Cornelissen
Keyword(s):  
Visual Field ◽  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Fmri Data ◽  
List Type ◽  
Spatial Integration ◽  
Cortical Areas ◽  
Local Functional ◽  
Visual Cortical

AbstractConnective Field (CF) modeling estimates the local spatial integration between signals in distinct cortical visual field areas. As we have shown previously using 7T data, CF can reveal the visuotopic organization of visual cortical areas even when applied to BOLD activity recorded in the absence of external stimulation. This indicates that CF modeling can be used to evaluate cortical processing in participants in which the visual input may be compromised. Furthermore, by using Bayesian CF modelling it is possible to estimate the co-variability of the parameter estimates and therefore, apply CF modeling to single cases. However, no previous studies evaluated the (Bayesian) CF model using 3T resting-state fMRI data, although this is important since 3T scanners are much more abundant and more often used in clinical research than 7T ones. In this study, we investigate whether it is possible to obtain meaningful CF estimates from 3T resting state (RS) fMRI data. To do so, we applied the standard and Bayesian CF modeling approaches on two RS scans interleaved by the acquisition of visual stimulation in 12 healthy participants.Our results show that both approaches reveal good agreement between RS- and visual field (VF)-based maps. Moreover, the 3T observations were similar to those previously reported at 7T. In addition, to quantify the uncertainty associated with each estimate in both RS and VF data, we applied our Bayesian CF framework to provide the underlying marginal distribution of the CF parameters. Finally, we show how an additional CF parameter, beta, can be used as a data-driven threshold on the RS data to further improve CF estimates. We conclude that Bayesian CF modeling can characterize local functional connectivity between visual cortical areas from RS data at 3T. In particular, we expect the ability to assess parameter uncertainty in individual participants will be important for future clinical studies.HighlightsLocal functional connectivity between visual cortical areas can be estimated from RS-fMRI data at 3T using both standard CF and Bayesian CF modelling.Bayesian CF modelling quantifies the model uncertainty associated with each CF parameter on RS and VF data, important in particular for future studies on clinical populations.3T observations were qualitatively similar to those previously reported at 7T.

scholarly journals Assessing Uncertainty and Reliability of Connective Field Estimations From Resting State fMRI Activity at 3T

2021 ◽  
Vol 15 ◽  
Author(s):  
Azzurra Invernizzi ◽  
Nicolas Gravel ◽  
Koen V. Haak ◽  
Remco J. Renken ◽  
Frans W. Cornelissen
Keyword(s):  
Visual Field ◽  
Resting State ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Parameter Estimates ◽  
Spatial Integration ◽  
External Stimulation ◽  
Cortical Areas ◽  
Local Functional ◽  
Visual Cortical

Connective Field (CF) modeling estimates the local spatial integration between signals in distinct cortical visual field areas. As we have shown previously using 7T data, CF can reveal the visuotopic organization of visual cortical areas even when applied to BOLD activity recorded in the absence of external stimulation. This indicates that CF modeling can be used to evaluate cortical processing in participants in which the visual input may be compromised. Furthermore, by using Bayesian CF modeling it is possible to estimate the co-variability of the parameter estimates and therefore, apply CF modeling to single cases. However, no previous studies evaluated the (Bayesian) CF model using 3T resting-state fMRI data. This is important since 3T scanners are much more abundant and more often used in clinical research compared to 7T scanners. Therefore in this study, we investigate whether it is possible to obtain meaningful CF estimates from 3T resting state (RS) fMRI data. To do so, we applied the standard and Bayesian CF modeling approaches on two RS scans, which were separated by the acquisition of visual field mapping data in 12 healthy participants. Our results show good agreement between RS- and visual field (VF)- based maps using either the standard or Bayesian CF approach. In addition to quantify the uncertainty associated with each estimate in both RS and VF data, we applied our Bayesian CF framework to provide the underlying marginal distribution of the CF parameters. Finally, we show how an additional CF parameter, beta, can be used as a data-driven threshold on the RS data to further improve CF estimates. We conclude that Bayesian CF modeling can characterize local functional connectivity between visual cortical areas from RS data at 3T. Moreover, observations obtained using 3T scanners were qualitatively similar to those reported for 7T. In particular, we expect the ability to assess parameter uncertainty in individual participants will be important for future clinical studies.

scholarly journals Model testing for distinctive functional connectivity gradients with resting-state fMRI data

2018 ◽  
Author(s):  
Jonathan F. O’Rawe ◽  
Jaime S. Ide ◽  
Hoi-Chung Leung
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Organization ◽  
Region Of Interest ◽  
Resting State Fmri ◽  
Model Testing ◽  
Fmri Data ◽  
Extensive Literature ◽  
Topographic Organization ◽  
Lateral Organization

AbstractIn accordance with the concept of topographic organization of neuroanatomical structures, there is an increased interest in estimating and delineating continuous changes in the functional connectivity patterns across neighboring voxels within a region of interest using resting-state fMRI data. Fundamental to this functional connectivity gradient analysis is the assumption that the functional organization is stable and uniform across the region of interest. To evaluate this assumption, we developed a model testing procedure to arbitrate between overlapping, shifted, or different topographic connectivity gradients across subdivisions of a structure. We tested the procedure using the striatum, a subcortical structure consisting of the caudate nucleus and putamen, in which an extensive literature, primarily from rodents and non-human primates, suggest to have a shared topographic organization of a single diagonal gradient. We found, across multiple resting state fMRI data samples of different spatial resolutions in humans, and one macaque resting state fMRI data sample, that the models with different functional connectivity gradients across the caudate and putamen was the preferred model. The model selection procedure was validated in control conditions of checkerboard subdivisions, demonstrating the expected overlapping gradient. More specifically, while we replicated the diagonal organization of the functional connectivity gradients in both the caudate and putamen, our analysis also revealed a medial-lateral organization within the caudate. Not surprisingly, performing the same analysis assuming a unitary gradient obfuscates the medial-lateral organization of the caudate, producing only a diagonal gradient. These findings demonstrate the importance of testing basic assumptions and evaluating interpretations across species. The significance of differential topographic gradients across the putamen and caudate and the medial-lateral gradient of the caudate in humans should be tested in future studies.

scholarly journals Evaluating the sensitivity of functional connectivity measures to motion artifact in resting-state fMRI data

2020 ◽  
Author(s):  
Arun S. Mahadevan ◽  
Ursula A. Tooley ◽  
Maxwell A. Bertolero ◽  
Allyson P. Mackey ◽  
Danielle S. Bassett
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Partial Correlation ◽  
Motion Artifact ◽  
Resting State Fmri ◽  
Alternative Methods ◽  
Fmri Data ◽  
Retest Reliability ◽  
Human Connectome Project ◽  
Test Retest Reliability

AbstractFunctional connectivity (FC) networks are typically inferred from resting-state fMRI data using the Pearson correlation between BOLD time series from pairs of brain regions. However, alternative methods of estimating functional connectivity have not been systematically tested for their sensitivity or robustness to head motion artifact. Here, we evaluate the sensitivity of six different functional connectivity measures to motion artifact using resting-state data from the Human Connectome Project. We report that FC estimated using full correlation has a relatively high residual distance-dependent relationship with motion compared to partial correlation, coherence and information theory-based measures, even after implementing rigorous methods for motion artifact mitigation. This disadvantage of full correlation, however, may be offset by higher test-retest reliability and system identifiability. FC estimated by partial correlation offers the best of both worlds, with low sensitivity to motion artifact and intermediate system identifiability, with the caveat of low test-retest reliability. We highlight spatial differences in the sub-networks affected by motion with different FC metrics. Further, we report that intra-network edges in the default mode and retrosplenial temporal sub-networks are highly correlated with motion in all FC methods. Our findings indicate that the method of estimating functional connectivity is an important consideration in resting-state fMRI studies and must be chosen carefully based on the parameters of the study.

scholarly journals Impact of anaesthesia on static and dynamic functional connectivity in mice

2021 ◽  
Author(s):  
Tomokazu Tsurugizawa ◽  
Daisuke Yoshimaru
Keyword(s):  
Functional Connectivity ◽  
Functional Mri ◽  
Resting State ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Network ◽  
List Type ◽  
Thalamic Nuclei ◽  
Dynamic Functional Connectivity ◽  
Subcortical Regions

AbstractA few studies have compared the static functional connectivity between awake and anaesthetized states in rodents by resting-state fMRI. However, impact of anaesthesia on static and dynamic fluctuations in functional connectivity has not been fully understood. Here, we developed a resting-state fMRI protocol to perform awake and anaesthetized functional MRI in the same mice. Static functional connectivity showed a widespread decrease under anaesthesia, such as when under isoflurane or a mixture of isoflurane and medetomidine. Several interhemispheric connections were key connections for anaesthetized condition from awake. Dynamic functional connectivity demonstrates the shift from frequent broad connections across the cortex, the hypothalamus, and the auditory-visual cortex to frequent local connections within the cortex only. Fractional amplitude of low frequency fluctuation in the thalamic nuclei decreased under both anaesthesia. These results indicate that typical anaesthetics for functional MRI alters the spatiotemporal profile of the dynamic brain network in subcortical regions, including the thalamic nuclei and limbic system.HighlightsResting-state fMRI was compared between awake and anaesthetized in the same mice.Anaesthesia induced a widespread decrease of static functional connectivity.Anaesthesia strengthened local connections within the cortex.fALFF in the thalamus was decreased by anaesthesia.

scholarly journals Single-Case Neuropsychological Assessment of a Patient with a Posterior Parietal Lesion Using Behavioral Testing and Resting-State fMRI

2021 ◽  
Vol 05 (03) ◽  
pp. 1-1
Author(s):  
Elisa Martín-Arévalo ◽  
◽  
Carole Guedj ◽  
François Cotton ◽  
Gilles Rode ◽  
...  
Keyword(s):  
Visual Field ◽  
Functional Connectivity ◽  
Resting State ◽  
Left Visual Field ◽  
Single Case ◽  
Visual Fields ◽  
Resting State Fmri ◽  
Occipital Area ◽  
Posterior Parietal ◽  
The Right

This study integrated functional connectivity measures using resting-state fMRI and behavioral data from a single-case observation of patient (PER) one year after right-hemispheric hemorrhage in the intraparietal sulcus and superior parietal lobule (IPS/SPL). PER showed no sign of clinical neglect. Her behavioral performance in the visuo-manual pointing task and in the letter discrimination task under conditions of endogenous and exogenous attentional cueing was compared between the left (affected) and right (unaffected/control) peripheral visual fields. The resting-state fMRI demonstrated an imbalance between the right and left hemispheric frontoparietal functional connectivity within the dorsal attentional and motor networks. Although the frontal and occipital cortices were not structurally damaged, specific fronto-occipital functional connectivity was imbalanced, which was strongly associated with the behavioral changes. First, the activity in the right frontal eye field showed weaker correlations with the activity in the right inferior occipital area compared to the correlation with the activity in the left inferior occipital area. This imbalanced fronto-occipital functional connectivity was accompanied by a specific impairment in endogenous covert attention in the left visual field. Second, the activity within M1 in both hemispheres showed weaker correlations with the activity of the right cuneus compared to the correlation with the activity in the left cuneus. The imbalanced fronto-occipital functional connectivity was associated with the impairment of the reaching movement of the left and right hands towards the left visual field (optic ataxia). Altogether, our results showed that a lesion to the posterior parietal cortex affects the relationship between distal regions underlying the sensorimotor and attentional abilities

scholarly journals Whole brain mapping of somatosensory responses in awake marmosets investigated with ultra-high-field fMRI

2020 ◽  
Vol 124 (6) ◽  
pp. 1900-1913
Author(s):  
Justine C. Cléry ◽  
Yuki Hori ◽  
David J. Schaeffer ◽  
Joseph S. Gati ◽  
J. Andrew Pruszynski ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Mapping ◽  
Resting State ◽  
High Field ◽  
Body Representation ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Ultra High Field ◽  
Somatosensory Stimulation ◽  
Somatosensory Responses

We used somatosensory stimulation combined with functional MRI (fMRI) in awake marmosets to reveal the topographic body representation in areas S1, S2, thalamus, and putamen. We showed the existence of a body representation organization within the thalamus and the cingulate cortex by computing functional connectivity maps from seeds defined in S1/S2 using resting-state fMRI data. This noninvasive approach will be essential for chronic studies by guiding invasive recording and manipulation techniques.

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