25 results on '"Óscar Miranda-Domínguez"'
Search Results
2. Functional maturation in visual pathways predicts attention to the eyes in infant rhesus macaques: Effects of social status
- Author
-
Aiden Ford, Zsofia A. Kovacs-Balint, Arick Wang, Eric Feczko, Eric Earl, Óscar Miranda-Domínguez, Longchuan Li, Martin Styner, Damien Fair, Warren Jones, Jocelyne Bachevalier, and Mar M. Sánchez
- Subjects
Nonhuman primate ,Infant development ,Social attention ,Visual object pathway ,Brain-behavior associations ,Resting state fMRI ,Neurophysiology and neuropsychology ,QP351-495 - Abstract
Differences in looking at the eyes of others are one of the earliest behavioral markers for social difficulties in neurodevelopmental disabilities, including autism. However, it is unknown how early visuo-social experiences relate to the maturation of infant brain networks that process visual social stimuli. We investigated functional connectivity (FC) within the ventral visual object pathway as a contributing neural system. Densely sampled, longitudinal eye-tracking and resting state fMRI (rs-fMRI) data were collected from infant rhesus macaques, an important model of human social development, from birth through 6 months of age. Mean trajectories were fit for both datasets and individual trajectories from subjects with both eye-tracking and rs-fMRI data were used to test for brain-behavior relationships. Exploratory findings showed infants with greater increases in FC between left V1 to V3 visual areas have an earlier increase in eye-looking before 2 months. This relationship was moderated by social status such that infants with low social status had a stronger association between left V1 to V3 connectivity and eye-looking than high status infants. Results indicated that maturation of the visual object pathway may provide an important neural substrate supporting adaptive transitions in social visual attention during infancy. more...
- Published
- 2023
- Full Text
- View/download PDF
Catalog
3. Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds
- Author
-
Omid Kardan, Sydney Kaplan, Muriah D. Wheelock, Eric Feczko, Trevor K.M. Day, Óscar Miranda-Domínguez, Dominique Meyer, Adam T. Eggebrecht, Lucille A. Moore, Sooyeon Sung, Taylor A. Chamberlain, Eric Earl, Kathy Snider, Alice Graham, Marc G. Berman, Kamil Uğurbil, Essa Yacoub, Jed T. Elison, Christopher D. Smyser, Damien A. Fair, and Monica D. Rosenberg more...
- Subjects
Functional connectivity ,FMRI ,Reliability ,Development ,Machine learning ,Age prediction ,Neurophysiology and neuropsychology ,QP351-495 - Abstract
Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler’s connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants’ age within ± 3.6 months error and a prediction R2 = .51. To characterize the anatomy of predictive networks, we grouped connections into 11 infant-specific resting-state functional networks defined in a data-driven manner. We found that connections between regions of the same network—i.e. within-network connections—predicted age significantly better than between-network connections. Looking ahead, these findings can help characterize changes in functional brain organization in infancy and toddlerhood and inform work predicting developmental outcome measures in this age range. more...
- Published
- 2022
- Full Text
- View/download PDF
4. Does Cueing Need Attention? A Pilot Study in People with Parkinson's Disease
- Author
-
Carla Silva-Batista, Óscar Miranda-Domínguez, Anjanibhargavi Ragothaman, Damien A. Fair, Alessandra Mantovani, Sam Stuart, John G. Nutt, Fay B. Horak, and Martina Mancini
- Subjects
General Neuroscience - Abstract
We previously showed that both open-loop (beat of a metronome) and closed-loop (phase-dependent tactile feedback) cueing may be similarly effective in reducing Freezing of Gait (FoG), assessed with a quantitative FoG Index, while turning in place in the laboratory in a group of people with Parkinson's disease (PD). Despite the similar changes on the FoG Index, it is not known whether both cueing responses require attentional control, which would explain FoG Index improvement. The mechanisms underlying cueing responses are poorly understood. Here, we tested the hypothesis that the salience network would predict responsiveness (i.e., FoG Index improvement) to open-loop and closed-loop cueing in people with and without FoG of PD, as salience network contributes to tasks requiring attention to external stimuli in healthy adults. Thirteen people with PD with high-quality imaging data were analyzed to characterize relationships between resting-state MRI functional connectivity and responses to cues. The interaction of the salience network and retrosplenial-temporal networks was the best predictor of responsiveness to open-loop cueing, presenting the largest effect size (d = 1.16). The interaction between the salience network and subcortical as well as cingulo-parietal and subcortical networks were the strongest predictors of responsiveness to closed-loop cueing, presenting the largest effect sizes (d = 1.06 and d = 0.84, respectively). Salience network activity was a common predictor of responsiveness to both cueing, which suggests that auditory and proprioceptive stimuli during turning may require some level of cognitive and insular activity, anchored within the salience network, which explain FoG Index improvements in people with PD. more...
- Published
- 2022
5. A Precision Functional Atlas of Network Probabilities and Individual-Specific Network Topography
- Author
-
Robert J.M. Hermosillo, Lucille A. Moore, Eric Fezcko, Ally Dworetsky, Adam Pines, Gregory Conan, Michael A. Mooney, Anita Randolph, Babatunde Adeyemo, Eric Earl, Anders Perrone, Cristian Morales Carrasco, Johnny Uriarte-Lopez, Kathy Snider, Olivia Doyle, Michaela Cordova, Bonnie J. Nagel, Sarah W. Feldstein Ewing, Theodore Satterthwaite, Nico Dosenbach, Caterina Gratton, Steven Petersen, Óscar Miranda-Domínguez, and Damien A. Fair more...
- Abstract
SUMMARYThe brain is organized into a broad set of functional neural networks. These networks and their various characteristics have been described and scrutinized through in vivo resting state functional magnetic resonance imaging (rs-fMRI). While the basic properties of networks are generally similar between healthy individuals, there is vast variability in the precise topography across the population. These individual differences are often lost in population studies due to population averaging which assumes topographical uniformity. We leveraged precision brain mapping methods to establish a new open-source, method-flexible set of precision functional network atlases: the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. Using participants from the Adolescent Brain Cognitive Development (ABCD) study, single subject precision network maps were generated with two supervised network-matching procedures (template matching and non-negative matrix factorization), an overlapping template matching method for identifying integration zones, as well as an unsupervised community detection algorithm (Infomap). From these individualized maps we also generated probabilistic network maps and integration zones for two demographically-matched groups of n∼3000 each. We demonstrate high reproducibility between groups (Pearson’s r >0.999) and between methods (r=0.96), revealing both regions of high invariance and high variability. Compared to using parcellations based on groups averages, the MIDB Precision Brain Atlas allowed us to derive a set of brain regions that are largely invariant in network topography across populations, which provides more reproducible statistical maps of executive function in brain-wide associations. We also explore an example use case for probabilistic maps, highlighting their potential for use in targeted neuromodulation. The MIDB Precision Brain Atlas is expandable to alternative datasets and methods and is provided open-source with an online web interface to encourage the scientific community to experiment with probabilistic atlases and individual-specific topographies to more precisely relate network phenomenon to functional organization of the human brain. more...
- Published
- 2022
- Full Text
- View/download PDF
6. Familial risk for depression moderates neural circuitry in healthy preadolescents to predict adolescent depression symptoms in the Adolescent Brain Cognitive Development (ABCD) Study
- Author
-
Bailey Holt-Gosselin, Taylor J. Keding, Kathryn Rodrigues, Amanda Rueter, Timothy J. Hendrickson, Anders Perrone, Nora Byington, Audrey Houghton, Oscar Miranda-Dominguez, Eric Feczko, Damien A. Fair, Jutta Joormann, and Dylan G. Gee more...
- Subjects
Depression ,Familial risk for depression ,ABCD study ,Resting-state fMRI ,Youth ,Longitudinal study ,Neurophysiology and neuropsychology ,QP351-495 - Abstract
Background: There is an imminent need to identify neural markers during preadolescence that are linked to developing depression during adolescence, especially among youth at elevated familial risk. However, longitudinal studies remain scarce and exhibit mixed findings. Here we aimed to elucidate functional connectivity (FC) patterns among preadolescents that interact with familial depression risk to predict depression two years later. Methods: 9–10 year-olds in the Adolescent Brain Cognitive Development (ABCD) Study were classified as healthy (i.e., no lifetime psychiatric diagnoses) at high familial risk for depression (HR; n=559) or at low familial risk for psychopathology (LR; n=1203). Whole-brain seed-to-voxel resting-state FC patterns with the amygdala, putamen, nucleus accumbens, and caudate were calculated. Multi-level, mixed-effects regression analyses were conducted to test whether FC at ages 9–10 interacted with familial risk to predict depression symptoms at ages 11–12. Results: HR youth demonstrated stronger associations between preadolescent FC and adolescent depression symptoms (ps0.001), primarily among amygdala/striatal FC with visual and sensory/somatomotor networks. Conclusions: Preadolescent amygdala and striatal FC may be useful biomarkers of adolescent-onset depression, particularly for youth with family histories of depression. This research may point to neurobiologically-informed approaches to prevention and intervention for depression in adolescents. more...
- Published
- 2024
- Full Text
- View/download PDF
7. ADHD and attentional control: Impaired segregation of task positive and task negative brain networks
- Author
-
Brian D. Mills, Oscar Miranda-Dominguez, Kathryn L. Mills, Eric Earl, Michaela Cordova, Julia Painter, Sarah L. Karalunas, Joel T. Nigg, and Damien A. Fair
- Subjects
Electronic computers. Computer science ,QA75.5-76.95 - Published
- 2024
- Full Text
- View/download PDF
8. Personalized functional brain network topography is associated with individual differences in youth cognition
- Author
-
Arielle S. Keller, Adam R. Pines, Sheila Shanmugan, Valerie J. Sydnor, Zaixu Cui, Maxwell A. Bertolero, Ran Barzilay, Aaron F. Alexander-Bloch, Nora Byington, Andrew Chen, Gregory M. Conan, Christos Davatzikos, Eric Feczko, Timothy J. Hendrickson, Audrey Houghton, Bart Larsen, Hongming Li, Oscar Miranda-Dominguez, David R. Roalf, Anders Perrone, Alisha Shetty, Russell T. Shinohara, Yong Fan, Damien A. Fair, and Theodore D. Satterthwaite more...
- Subjects
Science - Abstract
Abstract Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain’s functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) that account for interindividual heterogeneity in functional brain network topography in 9–10 year olds from the Adolescent Brain Cognitive Development℠ Study. Across matched discovery (n = 3525) and replication (n = 3447) samples, the total cortical representation of fronto-parietal PFNs positively correlates with general cognition. Cross-validated ridge regressions trained on PFN topography predict cognition in unseen data across domains, with prediction accuracy increasing along the cortex’s sensorimotor-association organizational axis. These results establish that functional network topography heterogeneity is associated with individual differences in cognition before the critical transition into adolescence. more...
- Published
- 2023
- Full Text
- View/download PDF
9. A general exposome factor explains individual differences in functional brain network topography and cognition in youth
- Author
-
Arielle S. Keller, Tyler M. Moore, Audrey Luo, Elina Visoki, Mārtiņš M. Gataviņš, Alisha Shetty, Zaixu Cui, Yong Fan, Eric Feczko, Audrey Houghton, Hongming Li, Allyson P. Mackey, Oscar Miranda-Dominguez, Adam Pines, Russell T. Shinohara, Kevin Y. Sun, Damien A. Fair, Theodore D. Satterthwaite, and Ran Barzilay more...
- Subjects
Cognition ,Functional networks ,Development ,Environment ,Exposome ,Topography ,Neurophysiology and neuropsychology ,QP351-495 - Abstract
Childhood environments are critical in shaping cognitive neurodevelopment. With the increasing availability of large-scale neuroimaging datasets with deep phenotyping of childhood environments, we can now build upon prior studies that have considered relationships between one or a handful of environmental and neuroimaging features at a time. Here, we characterize the combined effects of hundreds of inter-connected and co-occurring features of a child’s environment (“exposome”) and investigate associations with each child’s unique, multidimensional pattern of functional brain network organization (“functional topography”) and cognition. We apply data-driven computational models to measure the exposome and define personalized functional brain networks in pre-registered analyses. Across matched discovery (n=5139, 48.5% female) and replication (n=5137, 47.1% female) samples from the Adolescent Brain Cognitive Development study, the exposome was associated with current (ages 9–10) and future (ages 11–12) cognition. Changes in the exposome were also associated with changes in cognition after accounting for baseline scores. Cross-validated ridge regressions revealed that the exposome is reflected in functional topography and can predict performance across cognitive domains. Importantly, a single measure capturing a child’s exposome could more accurately and parsimoniously predict cognition than a wealth of personalized neuroimaging data, highlighting the importance of children’s complex, multidimensional environments in cognitive neurodevelopment. more...
- Published
- 2024
- Full Text
- View/download PDF
10. Carotenoids improve the development of cerebral cortical networks in formula-fed infant macaques
- Author
-
Oscar Miranda-Dominguez, Julian S. B. Ramirez, A. J. Mitchell, Anders Perrone, Eric Earl, Sam Carpenter, Eric Feczko, Alice Graham, Sookyoung Jeon, Neal J. Cohen, Laurie Renner, Martha Neuringer, Matthew J. Kuchan, John W. Erdman, and Damien Fair more...
- Subjects
Medicine ,Science - Abstract
Abstract Nutrition during the first years of life has a significant impact on brain development. This study characterized differences in brain maturation from birth to 6 months of life in infant macaques fed formulas differing in content of lutein, β-carotene, and other carotenoids using Magnetic Resonance Imaging to measure functional connectivity. We observed differences in functional connectivity based on the interaction of diet, age and brain networks. Post hoc analysis revealed significant diet-specific differences between insular-opercular and somatomotor networks at 2 months of age, dorsal attention and somatomotor at 4 months of age, and within somatomotor and between somatomotor-visual and auditory-dorsal attention networks at 6 months of age. Overall, we found a larger divergence in connectivity from the breastfeeding group in infant macaques fed formula containing no supplemental carotenoids in comparison to those fed formula supplemented with carotenoids. These findings suggest that carotenoid formula supplementation influences functional brain development. more...
- Published
- 2022
- Full Text
- View/download PDF
11. Using synthetic MR images for distortion correction
- Author
-
David F. Montez, Andrew N. Van, Ryland L. Miller, Nicole A. Seider, Scott Marek, Annie Zheng, Dillan J. Newbold, Kristen Scheidter, Eric Feczko, Anders J. Perrone, Oscar Miranda-Dominguez, Eric A. Earl, Benjamin P. Kay, Abhinav K. Jha, Aristeidis Sotiras, Timothy O. Laumann, Deanna J. Greene, Evan M. Gordon, M. Dylan Tisdall, Andre van der Kouwe, Damien A. Fair, and Nico U.F. Dosenbach more...
- Subjects
fMRI ,EPI ,Distortion correction ,Field map ,Registration ,Neurophysiology and neuropsychology ,QP351-495 - Abstract
Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by magnetic field inhomogeneities. Distortion and differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) images makes their alignment a challenge. Typically, field map data are used to correct EPI distortions. Alignments achieved with field maps can vary greatly and depends on the quality of field map data. However, many public datasets lack field map data entirely. Additionally, reliable field map data is often difficult to acquire in high-motion pediatric or developmental cohorts. To address this, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require field map data. Synth combines information from T1w and T2w anatomical images to construct an idealized undistorted synthetic image with similar contrast properties to EPI data. This synthetic image acts as an effective reference for individual-specific distortion correction. Using pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club; HCP: Human Connectome Project) data, we demonstrate that Synth performs comparably to field map distortion correction approaches, and often outperforms them. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information. more...
- Published
- 2023
- Full Text
- View/download PDF
12. Polyneuro risk scores capture widely distributed connectivity patterns of cognition
- Author
-
Nora Byington, Gracie Grimsrud, Michael A. Mooney, Michaela Cordova, Olivia Doyle, Robert J.M. Hermosillo, Eric Earl, Audrey Houghton, Gregory Conan, Timothy J. Hendrickson, Anjanibhargavi Ragothaman, Cristian Morales Carrasco, Amanda Rueter, Anders Perrone, Lucille A. Moore, Alice Graham, Joel T. Nigg, Wesley K. Thompson, Steven M. Nelson, Eric Feczko, Damien A. Fair, and Oscar Miranda-Dominguez more...
- Subjects
Neuroimaging ,MRI ,Reproducibility ,Big data ,BWAS ,PNRS ,Neurophysiology and neuropsychology ,QP351-495 - Abstract
Resting-state functional connectivity (RSFC) is a powerful tool for characterizing brain changes, but it has yet to reliably predict higher-order cognition. This may be attributed to small effect sizes of such brain-behavior relationships, which can lead to underpowered, variable results when utilizing typical sample sizes (N∼25). Inspired by techniques in genomics, we implement the polyneuro risk score (PNRS) framework - the application of multivariate techniques to RSFC data and validation in an independent sample. Utilizing the Adolescent Brain Cognitive Development® cohort split into two datasets, we explore the framework’s ability to reliably capture brain-behavior relationships across 3 cognitive scores – general ability, executive function, learning & memory. The weight and significance of each connection is assessed in the first dataset, and a PNRS is calculated for each participant in the second. Results support the PNRS framework as a suitable methodology to inspect the distribution of connections contributing towards behavior, with explained variance ranging from 1.0 % to 21.4 %. For the outcomes assessed, the framework reveals globally distributed, rather than localized, patterns of predictive connections. Larger samples are likely necessary to systematically identify the specific connections contributing towards complex outcomes. The PNRS framework could be applied translationally to identify neurologically distinct subtypes of neurodevelopmental disorders. more...
- Published
- 2023
- Full Text
- View/download PDF
13. Motor networks, but also non-motor networks predict motor signs in Parkinson’s disease
- Author
-
Anjanibhargavi Ragothaman, Martina Mancini, John G. Nutt, Junping Wang, Damien A. Fair, Fay B. Horak, and Oscar Miranda-Dominguez
- Subjects
Parkinson’s disease ,Resting-state functional connectivity (RsFC) ,Motor networks ,Non-motor networks ,MDS-UPDRS III ,Predictive modeling ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Objective: Investigate the brain functional networks associated with motor impairment in people with Parkinson’s disease (PD). Background: PD is primarily characterized by motor dysfunction. Resting-state functional connectivity (RsFC) offers a unique opportunity to non-invasively characterize brain function. In this study, we hypothesized that the motor dysfunction observed in people with PD involves atypical connectivity not only in motor but also in higher-level attention networks. Understanding the interaction between motor and non-motor RsFC that are related to the motor signs could provide insights into PD pathophysiology. Methods: We used data from 88 people with PD (mean age: 68.2(SD:10), 55 M/33F) coming from 2 cohorts. Motor severity was assessed in practical OFF-medication state, using MDS‐UPDRS Part‐III motor scores (mean: 49 (SD:10)). RsFC was characterized using an atlas of 384 regions that were grouped into 13 functional networks. Associations between RsFC and motor severity were assessed independently for each RsFC using predictive modeling. Results: The top 5 % models that predicted the MDS-UPDRS-III motor scores with effect size >0.5 were the connectivity between (1) the somatomotor and Subcortical-Basal-ganglia, (2) somatomotor and Visual and (3) CinguloOpercular (CiO) and language/Ventral attention (Lan/VeA) network pairs. Discussion: Our findings suggest that, along with motor networks, visual- and attention-related cortical networks are also associated with the motor symptoms of PD. Non-motor networks may be involved indirectly in motor-coordination. When people with PD have deficits in motor networks, more attention may be needed to carry out formerly automatic motor functions, consistent with compensatory mechanisms in parkinsonian movement disorders. more...
- Published
- 2023
- Full Text
- View/download PDF
14. Use of connectotyping on task functional MRI data reveals dynamic network level cross talking during task performance
- Author
-
Valeria Vazquez-Trejo, Binyam Nardos, Bradley L. Schlaggar, Damien A. Fair, and Oscar Miranda-Dominguez
- Subjects
fMRI ,task fMRI ,connectotyping ,functional connectivity ,cognition ,dynamic connectivity ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Task-based functional MRI (fMRI) has greatly improved understanding of brain functioning, enabling the identification of brain areas associated with specific cognitive operations. Traditional analyses are limited to associating activation patterns in particular regions with specific cognitive operation, largely ignoring regional cross-talk or dynamic connectivity, which we propose is crucial for characterization of brain function in the context of task fMRI. We use connectotyping, which efficiently models functional brain connectivity to reveal the progression of temporal brain connectivity patterns in task fMRI. Connectotyping was employed on data from twenty-four participants (12 male, mean age 24.8 years, 2.57 std. dev) who performed a widely spaced event-related fMRI word vs. pseudoword decision task, where stimuli were presented every 20 s. After filtering for movement, we ended up with 15 participants that completed each trial and had enough usable data for our analyses. Connectivity matrices were calculated per participant across time for each stimuli type. A Repeated Measures ANOVA applied on the connectotypes was used to characterize differences across time for words and pseudowords. Our group level analyses found significantly different dynamic connectivity patterns during word vs. pseudoword processing between the Fronto-Parietal and Cingulo-Parietal Systems, areas involved in cognitive task control, memory retrieval, and semantic processing. Our findings support the presence of dynamic changes in functional connectivity during task execution and that such changes can be characterized using connectotyping but not with traditional Pearson’s correlations. more...
- Published
- 2022
- Full Text
- View/download PDF
15. Filtering respiratory motion artifact from resting state fMRI data in infant and toddler populations
- Author
-
Sydney Kaplan, Dominique Meyer, Oscar Miranda-Dominguez, Anders Perrone, Eric Earl, Dimitrios Alexopoulos, Deanna M. Barch, Trevor K.M. Day, Joseph Dust, Adam T. Eggebrecht, Eric Feczko, Omid Kardan, Jeanette K. Kenley, Cynthia E. Rogers, Muriah D. Wheelock, Essa Yacoub, Monica Rosenberg, Jed T. Elison, Damien A. Fair, and Christopher D. Smyser more...
- Subjects
Resting-state fMRI ,Respiratory filtering ,Neurodevelopment ,Neuroimaging, infant ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
The importance of motion correction when processing resting state functional magnetic resonance imaging (rs-fMRI) data is well-established in adult cohorts. This includes adjustments based on self-limited, large amplitude subject head motion, as well as factitious rhythmic motion induced by respiration. In adults, such respiration artifact can be effectively removed by applying a notch filter to the motion trace, resulting in higher amounts of data retained after frame censoring (e.g., “scrubbing”) and more reliable correlation values. Due to the unique physiological and behavioral characteristics of infants and toddlers, rs-fMRI processing pipelines, including methods to identify and remove colored noise due to subject motion, must be appropriately modified to accurately reflect true neuronal signal. These younger cohorts are characterized by higher respiration rates and lower-amplitude head movements than adults; thus, the presence and significance of comparable respiratory artifact and the subsequent necessity of applying similar techniques remain unknown. Herein, we identify and characterize the consistent presence of respiratory artifact in rs-fMRI data collected during natural sleep in infants and toddlers across two independent cohorts (aged 8–24 months) analyzed using different pipelines. We further demonstrate how removing this artifact using an age-specific notch filter allows for both improved data quality and data retention in measured results. Importantly, this work reveals the critical need to identify and address respiratory-driven head motion in fMRI data acquired in young populations through the use of age-specific motion filters as a mechanism to optimize the accuracy of measured results in this population. more...
- Published
- 2022
- Full Text
- View/download PDF
16. Target identification for Transcranial Magnetic Stimulation (TMS) using precision mapping
- Author
-
Amal Aaden, Cristian Morales-Carrasco, Robert Hermosillo, Nora Byington, Eric Feczko, Mo Chen, Christine Conelea, Damien Fair, and Oscar Miranda-Dominguez
- Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Published
- 2021
- Full Text
- View/download PDF
17. Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity
- Author
-
Caterina Gratton, Ally Dworetsky, Rebecca S. Coalson, Babatunde Adeyemo, Timothy O. Laumann, Gagan S. Wig, Tania S. Kong, Gabriele Gratton, Monica Fabiani, Deanna M. Barch, Daniel Tranel, Oscar Miranda-Dominguez, Damien A. Fair, Nico U.F. Dosenbach, Abraham Z. Snyder, Joel S. Perlmutter, Steven E. Petersen, and Meghan C. Campbell more...
- Subjects
fMRI ,Motion ,Artifacts ,Aging ,Functional connectivity ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., ‘motion’ parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (>0.1 Hz, here referred to as ‘HF-motion’), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0–2.5 s) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 to 2.5 s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants. more...
- Published
- 2020
- Full Text
- View/download PDF
18. Correction of respiratory artifacts in MRI head motion estimates
- Author
-
Damien A. Fair, Oscar Miranda-Dominguez, Abraham Z. Snyder, Anders Perrone, Eric A. Earl, Andrew N. Van, Jonathan M. Koller, Eric Feczko, M. Dylan Tisdall, Andre van der Kouwe, Rachel L. Klein, Amy E. Mirro, Jacqueline M. Hampton, Babatunde Adeyemo, Timothy O. Laumann, Caterina Gratton, Deanna J. Greene, Bradley L. Schlaggar, Donald J. Hagler, Jr., Richard Watts, Hugh Garavan, Deanna M. Barch, Joel T. Nigg, Steven E. Petersen, Anders M. Dale, Sarah W. Feldstein-Ewing, Bonnie J. Nagel, and Nico U.F. Dosenbach more...
- Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Head motion represents one of the greatest technical obstacles in magnetic resonance imaging (MRI) of the human brain. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, head motion estimates may be corrupted by artifacts due to magnetic main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and comparison ‘single-shot’ datasets. We show that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with functional MRI quality reductions. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects from motion estimates. Subsequently, we demonstrate that utilizing a band-stop filter improves post-processing fMRI data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package. more...
- Published
- 2020
- Full Text
- View/download PDF
19. Individual differences in functional brain connectivity predict temporal discounting preference in the transition to adolescence
- Author
-
Jeya Anandakumar, Kathryn L. Mills, Eric A. Earl, Lourdes Irwin, Oscar Miranda-Dominguez, Damion V. Demeter, Alexandra Walton-Weston, Sarah Karalunas, Joel Nigg, and Damien A. Fair
- Subjects
Neurophysiology and neuropsychology ,QP351-495 - Abstract
The transition from childhood to adolescence is marked by distinct changes in behavior, including how one values waiting for a large reward compared to receiving an immediate, yet smaller, reward. While previous research has emphasized the relationship between this preference and age, it is also proposed that this behavior is related to circuitry between valuation and cognitive control systems. In this study, we examined how age and intrinsic functional connectivity strength within and between these neural systems relate to changes in discounting behavior across the transition into adolescence. We used mixed-effects modeling and linear regression to assess the contributions of age and connectivity strength in predicting discounting behavior. First, we identified relevant connections in a longitudinal sample of 64 individuals who completed MRI scans and behavioral assessments 2–3 times across ages 7–15 years (137 scans). We then repeated the analysis in a separate, cross-sectional, sample of 84 individuals (7–13 years). Both samples showed an age-related increase in preference for waiting for larger rewards. Connectivity strength within and between valuation and cognitive control systems accounted for further variance not explained by age. These results suggest that individual differences in functionalbrain organization can account for behavioral changes typically associated with age. Keywords: Delay discounting, fMRI, Intrinsic connectivity, Longitudinal, Resting state more...
- Published
- 2018
- Full Text
- View/download PDF
20. Heritability of the human connectome: A connectotyping study
- Author
-
Oscar Miranda-Dominguez, Eric Feczko, David S. Grayson, Hasse Walum, Joel T. Nigg, and Damien A. Fair
- Subjects
Development ,Heritability ,Effective connectivity ,MRI ,Functional connectivity ,Resting-state MRI ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Recent progress in resting-state neuroimaging demonstrates that the brain exhibits highly individualized patterns of functional connectivity—a “connectotype.” How these individualized patterns may be constrained by environment and genetics is unknown. Here we ask whether the connectotype is familial and heritable. Using a novel approach to estimate familiality via a machine-learning framework, we analyzed resting-state fMRI scans from two well-characterized samples of child and adult siblings. First we show that individual connectotypes were reliably identified even several years after the initial scanning timepoint. Familial relationships between participants, such as siblings versus those who are unrelated, were also accurately characterized. The connectotype demonstrated substantial heritability driven by high-order systems including the fronto-parietal, dorsal attention, ventral attention, cingulo-opercular, and default systems. This work suggests that shared genetics and environment contribute toward producing complex, individualized patterns of distributed brain activity, rather than constraining local aspects of function. These insights offer new strategies for characterizing individual aberrations in brain function and evaluating heritability of brain networks. By using machine learning and two independent datasets, this report shows that the brain’s individualized functional connectome or connectotype is familial and heritable. First we expand previous findings showing that by using a model-based approach to characterize functional connectivity, we can reliably identify and track individual brain signatures—a functional “fingerprint” or “connectotype” for the human brain—in both children and adults. Such signatures can also be used to characterize familial and heritable patterns of brain connectivity, even using limited data. Most heritable systems include the fronto-parietal, dorsal attention, ventral attention, cingulo-opercular, and default systems. Our proposed approach offers new strategies for characterizing normative development as well as altered patterns of brain connectivity and assists in characterizing the associations between genetic and epigenetic factors with brain function. more...
- Published
- 2018
- Full Text
- View/download PDF
21. Delineating the Macroscale Areal Organization of the Macaque Cortex In Vivo
- Author
-
Ting Xu, Arnaud Falchier, Elinor L. Sullivan, Gary Linn, Julian S.B. Ramirez, Deborah Ross, Eric Feczko, Alexander Opitz, Jennifer Bagley, Darrick Sturgeon, Eric Earl, Oscar Miranda-Domínguez, Anders Perrone, R. Cameron Craddock, Charles E. Schroeder, Stan Colcombe, Damien A. Fair, and Michael P. Milham more...
- Subjects
Biology (General) ,QH301-705.5 - Abstract
Summary: Complementing long-standing traditions centered on histology, fMRI approaches are rapidly maturing in delineating brain areal organization at the macroscale. The non-human primate (NHP) provides the opportunity to overcome critical barriers in translational research. Here, we establish the data requirements for achieving reproducible and internally valid parcellations in individuals. We demonstrate that functional boundaries serve as a functional fingerprint of the individual animals and can be achieved under anesthesia or awake conditions (rest, naturalistic viewing), though differences between awake and anesthetized states precluded the detection of individual differences across states. Comparison of awake and anesthetized states suggested a more nuanced picture of changes in connectivity for higher-order association areas, as well as visual and motor cortex. These results establish feasibility and data requirements for the generation of reproducible individual-specific parcellations in NHPs, provide insights into the impact of scan state, and motivate efforts toward harmonizing protocols. : Noninvasive fMRI in macaques is an essential tool in translation research. Xu et al. establish the individual functional parcellation of the macaque cortex and demonstrate that brain organization is unique, reproducible, and valid, serving as a fingerprint for an individual macaque. Keywords: macaque, parcellation, cortical areas, gradient, functional connectivity more...
- Published
- 2018
- Full Text
- View/download PDF
22. At risk of being risky: The relationship between 'brain age' under emotional states and risk preference
- Author
-
Marc D. Rudolph, Oscar Miranda-Domínguez, Alexandra O. Cohen, Kaitlyn Breiner, Laurence Steinberg, Richard J. Bonnie, Elizabeth S. Scott, Kim Taylor-Thompson, Jason Chein, Karla C. Fettich, Jennifer A. Richeson, Danielle V. Dellarco, Adriana Galván, B.J. Casey, and Damien A. Fair more...
- Subjects
Neurophysiology and neuropsychology ,QP351-495 - Abstract
Developmental differences regarding decision making are often reported in the absence of emotional stimuli and without context, failing to explain why some individuals are more likely to have a greater inclination toward risk. The current study (N = 212; 10–25y) examined the influence of emotional context on underlying functional brain connectivity over development and its impact on risk preference. Using functional imaging data in a neutral brain-state we first identify the “brain age” of a given individual then validate it with an independent measure of cortical thickness. We then show, on average, that “brain age” across the group during the teen years has the propensity to look younger in emotional contexts. Further, we show this phenotype (i.e. a younger brain age in emotional contexts) relates to a group mean difference in risk perception − a pattern exemplified greatest in young-adults (ages 18–21). The results are suggestive of a specified functional brain phenotype that relates to being at “risk to be risky.” Keywords: Brain age, Emotional state, Risky behavior, Multivariate, Prediction, Pseudo-resting state fMRI more...
- Published
- 2017
- Full Text
- View/download PDF
23. Heterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD
- Author
-
Michaela Cordova, Kiryl Shada, Damion V Demeter, Olivia Doyle, Oscar Miranda-Dominguez, Anders Perrone, Emma Schifsky, Alice Graham, Eric Fombonne, Beth Langhorst, Joel Nigg, Damien A Fair, and Eric Feczko more...
- Subjects
ASD ,ADHD ,Executive function ,Machine learning ,rs-fMRI ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Background: Those with autism spectrum disorder (ASD) and/or attention-deficit-hyperactivity disorder (ADHD) exhibit symptoms of hyperactivity and inattention, causing significant hardships for families and society. A potential mechanism involved in these conditions is atypical executive function (EF). Inconsistent findings highlight that EF features may be shared or distinct across ADHD and ASD. With ADHD and ASD each also being heterogeneous, we hypothesized that there may be nested subgroups across disorders with shared or unique underlying mechanisms. Methods: Participants (N = 130) included adolescents aged 7–16 with ASD (n = 64) and ADHD (n = 66). Typically developing (TD) participants (n = 28) were included for a comparative secondary sub-group analysis. Parents completed the K-SADS and youth completed an extended battery of executive and other cognitive measures. A two stage hybrid machine learning tool called functional random forest (FRF) was applied as a classification approach and then subsequently to subgroup identification. We input 43 EF variables to the classification step, a supervised random forest procedure in which the features estimated either hyperactive or inattentive ADHD symptoms per model. The FRF then produced proximity matrices and identified optimal subgroups via the infomap algorithm (a type of community detection derived from graph theory). Resting state functional connectivity MRI (rs-fMRI) was used to evaluate the neurobiological validity of the resulting subgroups. Results: Both hyperactive (Mean absolute error (MAE) = 0.72, Null model MAE = 0.8826, (t(58) = −4.9, p more...
- Published
- 2020
- Full Text
- View/download PDF
24. Identifying reproducible individual differences in childhood functional brain networks: An ABCD study
- Author
-
Scott Marek, Brenden Tervo-Clemmens, Ashley N. Nielsen, Muriah D. Wheelock, Ryland L. Miller, Timothy O. Laumann, Eric Earl, William W. Foran, Michaela Cordova, Olivia Doyle, Anders Perrone, Oscar Miranda-Dominguez, Eric Feczko, Darrick Sturgeon, Alice Graham, Robert Hermosillo, Kathy Snider, Anthony Galassi, Bonnie J. Nagel, Sarah W. Feldstein Ewing, Adam T. Eggebrecht, Hugh Garavan, Anders M. Dale, Deanna J. Greene, Deanna M. Barch, Damien A. Fair, Beatriz Luna, and Nico U.F. Dosenbach more...
- Subjects
Neurophysiology and neuropsychology ,QP351-495 - Abstract
The 21-site Adolescent Brain Cognitive Development (ABCD) study provides an unparalleled opportunity to characterize functional brain development via resting-state functional connectivity (RSFC) and to quantify relationships between RSFC and behavior. This multi-site data set includes potentially confounding sources of variance, such as differences between data collection sites and/or scanner manufacturers, in addition to those inherent to RSFC (e.g., head motion). The ABCD project provides a framework for characterizing and reproducing RSFC and RSFC-behavior associations, while quantifying the extent to which sources of variability bias RSFC estimates. We quantified RSFC and functional network architecture in 2,188 9-10-year old children from the ABCD study, segregated into demographically-matched discovery (N = 1,166) and replication datasets (N = 1,022). We found RSFC and network architecture to be highly reproducible across children. We did not observe strong effects of site; however, scanner manufacturer effects were large, reproducible, and followed a “short-to-long” association with distance between regions. Accounting for potential confounding variables, we replicated that RSFC between several higher-order networks was related to general cognition. In sum, we provide a framework for how to characterize RSFC-behavior relationships in a rigorous and reproducible manner using the ABCD dataset and other large multi-site projects. Keywords: ABCD, Resting state fMRI, Functional connectivity, Development, Cognitive ability, Reproducibility more...
- Published
- 2019
- Full Text
- View/download PDF
25. Connectotyping: model based fingerprinting of the functional connectome.
- Author
-
Oscar Miranda-Dominguez, Brian D Mills, Samuel D Carpenter, Kathleen A Grant, Christopher D Kroenke, Joel T Nigg, and Damien A Fair
- Subjects
Medicine ,Science - Abstract
A better characterization of how an individual's brain is functionally organized will likely bring dramatic advances to many fields of study. Here we show a model-based approach toward characterizing resting state functional connectivity MRI (rs-fcMRI) that is capable of identifying a so-called "connectotype", or functional fingerprint in individual participants. The approach rests on a simple linear model that proposes the activity of a given brain region can be described by the weighted sum of its functional neighboring regions. The resulting coefficients correspond to a personalized model-based connectivity matrix that is capable of predicting the timeseries of each subject. Importantly, the model itself is subject specific and has the ability to predict an individual at a later date using a limited number of non-sequential frames. While we show that there is a significant amount of shared variance between models across subjects, the model's ability to discriminate an individual is driven by unique connections in higher order control regions in frontal and parietal cortices. Furthermore, we show that the connectotype is present in non-human primates as well, highlighting the translational potential of the approach. more...
- Published
- 2014
- Full Text
- View/download PDF
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.