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5. Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks

Author

Neudorfer, Clemens, Butenko, Konstantin, Oxenford, Simon, Rajamani, Nanditha, Achtzehn, Johannes, Goede, Lukas, Hollunder, Barbara, Ríos, Ana Sofía, Hart, Lauren, Tasserie, Jordy, Fernando, Kavisha B., Nguyen, T. A. Khoa, Al-Fatly, Bassam, Vissani, Matteo, Fox, Michael, Richardson, R. Mark, van Rienen, Ursula, Kühn, Andrea A., Husch, Andreas D., Opri, Enrico, Dembek, Till, Li, Ningfei, and Horn, Andreas

Published
2023
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7. Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease

Author

Adams, Sarah, Allegri, Ricardo, Araki, Aki, Barthelemy, Nicolas, Bateman, Randall, Bechara, Jacob, Benzinger, Tammie, Berman, Sarah, Bodge, Courtney, Brandon, Susan, Brooks, William (Bill), Brosch, Jared, Buck, Jill, Buckles, Virginia, Carter, Kathleen, Cash, Lisa, Chen, Charlie, Chhatwal, Jasmeer, Mendez, Patricio Chrem, Chua, Jasmin, Chui, Helena, Courtney, Laura, Cruchaga, Carlos, Day, Gregory S, DeLaCruz, Chrismary, Denner, Darcy, Diffenbacher, Anna, Dincer, Aylin, Donahue, Tamara, Douglas, Jane, Duong, Duc, Egido, Noelia, Esposito, Bianca, Fagan, Anne, Farlow, Marty, Feldman, Becca, Fitzpatrick, Colleen, Flores, Shaney, Fox, Nick, Franklin, Erin, Joseph-Mathurin, Nelly, Fujii, Hisako, Gardener, Samantha, Ghetti, Bernardino, Goate, Alison, Goldberg, Sarah, Goldman, Jill, Gonzalez, Alyssa, Gordon, Brian, Gräber-Sultan, Susanne, Graff-Radford, Neill, Graham, Morgan, Gray, Julia, Gremminger, Emily, Grilo, Miguel, Groves, Alex, Haass, Christian, Häsler, Lisa, Hassenstab, Jason, Hellm, Cortaiga, Herries, Elizabeth, Hoechst-Swisher, Laura, Hofmann, Anna, Holtzman, David, Hornbeck, Russ, Igor, Yakushev, Ihara, Ryoko, Ikeuchi, Takeshi, Ikonomovic, Snezana, Ishii, Kenji, Jack, Clifford, Jerome, Gina, Johnson, Erik, Jucker, Mathias, Karch, Celeste, Käser, Stephan, Kasuga, Kensaku, Keefe, Sarah, Klunk, William, Koeppe, Robert, Koudelis, Deb, Kuder-Buletta, Elke, Laske, Christoph, Levey, Allan, Levin, Johannes, Li, Yan, Lopez, Oscar, Marsh, Jacob, Martins, Ralph, Mason, Neal Scott, Masters, Colin, Mawuenyega, Kwasi, McCullough, Austin, McDade, Eric, Mejia, Arlene, Morenas-Rodriguez, Estrella, Morris, John, Mountz, James, Mummery, Cath, Nadkarni, N eelesh, Nagamatsu, Akemi, Neimeyer, Katie, Niimi, Yoshiki, Noble, James, Norton, Joanne, Nuscher, Brigitte, Obermüller, Ulricke, O'Connor, Antoinette, Patira, Riddhi, Perrin, Richard, Ping, Lingyan, Preische, Oliver, Renton, Alan, Ringman, John, Salloway, Stephen, Schofield, Peter, Senda, Michio, Seyfried, Nicholas T, Shady, Kristine, Shimada, Hiroyuki, Sigurdson, Wendy, Smith, Jennifer, Smith, Lori, Snitz, Beth, Sohrabi, Hamid, Stephens, Sochenda, Taddei, Kevin, Thompson, Sarah, Vöglein, Jonathan, Wang, Peter, Wang, Qing, Weamer, Elise, Xiong, Chengjie, Xu, Jinbin, Xu, Xiong, Millar, Peter R., Luckett, Patrick H., Gordon, Brian A., Benzinger, Tammie L.S., Schindler, Suzanne E., Fagan, Anne M., Bateman, Randall J., Lee, Jae-Hong, Mori, Hiroshi, Salloway, Stephen P, Yakushev, Igor, Morris, John C., and Ances, Beau M.

Published
2022
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11. Combining brain perturbation and neuroimaging in non-human primates

Author

Klink, P. Christiaan, Aubry, Jean-François, Ferrera, Vincent P., Fox, Andrew S., Froudist-Walsh, Sean, Jarraya, Béchir, Konofagou, Elisa E., Krauzlis, Richard J., Messinger, Adam, Mitchell, Anna S., Ortiz-Rios, Michael, Oya, Hiroyuki, Roberts, Angela C., Roe, Anna Wang, Rushworth, Matthew F.S., Sallet, Jérôme, Schmid, Michael Christoph, Schroeder, Charles E., Tasserie, Jordy, Tsao, Doris Y., Uhrig, Lynn, Vanduffel, Wim, Wilke, Melanie, Kagan, Igor, and Petkov, Christopher I.

Published
2021
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16. Functional imaging of the developing brain with wearable high-density diffuse optical tomography: A new benchmark for infant neuroimaging outside the scanner environment

Author

Frijia, Elisabetta Maria, Billing, Addison, Lloyd-Fox, Sarah, Vidal Rosas, Ernesto, Collins-Jones, Liam, Crespo-Llado, Maria Magdalena, Amadó, Marta Perapoch, Austin, Topun, Edwards, Andrea, Dunne, Luke, Smith, Greg, Nixon-Hill, Reuben, Powell, Samuel, Everdell, Nicholas L., and Cooper, Robert J.

Published
2021
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17. Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease

Author

Peter R. Millar, Patrick H. Luckett, Brian A. Gordon, Tammie L.S. Benzinger, Suzanne E. Schindler, Anne M. Fagan, Carlos Cruchaga, Randall J. Bateman, Ricardo Allegri, Mathias Jucker, Jae-Hong Lee, Hiroshi Mori, Stephen P Salloway, Igor Yakushev, John C. Morris, Beau M. Ances, Sarah Adams, MS, Ricardo Allegri, PhD, Aki Araki, Nicolas Barthelemy, PhD, Randall Bateman, MD, Jacob Bechara, BS, Tammie Benzinger, MD, PhD, Sarah Berman, MD, PhD, Courtney Bodge, PhD, Susan Brandon, BS, William (Bill) Brooks, MBBS,MPH, Jared Brosch, MD, PhD, Jill Buck, BSN, Virginia Buckles, PhD, Kathleen Carter, PhD, Lisa Cash, BFA, Charlie Chen, BA, Jasmeer Chhatwal, MD,PhD, Patricio Chrem Mendez, MD, Jasmin Chua, BS, Helena Chui, MD, Laura Courtney, BS, Carlos Cruchaga, PhD, Gregory S Day, MD, Chrismary DeLaCruz, BA, Darcy Denner, PhD, Anna Diffenbacher, MS, Aylin Dincer, BS, Tamara Donahue, MS, Jane Douglas, MPh, Duc Duong, BS, Noelia Egido, BS, Bianca Esposito, BS, Anne Fagan, PhD, Marty Farlow, MD, Becca Feldman, BS,BA, Colleen Fitzpatrick, MS, Shaney Flores, BS, Nick Fox, MD, Erin Franklin, MS, Nelly Joseph-Mathurin, PhD, Hisako Fujii, PhD, Samantha Gardener, PhD, Bernardino Ghetti, MD, Alison Goate, PhD, Sarah Goldberg, MS,LPC,NCC, Jill Goldman, MS,MPhil,CGC, Alyssa Gonzalez, BS, Brian Gordon, PhD, Susanne Gräber-Sultan, PhD, Neill Graff-Radford, MD, Morgan Graham, BA, Julia Gray, MS, Emily Gremminger, BA, Miguel Grilo, MD, Alex Groves, Christian Haass, PhD, Lisa Häsler, MSc, Jason Hassenstab, PhD, Cortaiga Hellm, BA, Elizabeth Herries, BA, Laura Hoechst-Swisher, MS, Anna Hofmann, MD, Anna Hofmann, David Holtzman, MD, Russ Hornbeck, MSCS, MPM, Yakushev Igor, MD, Ryoko Ihara, MD, Takeshi Ikeuchi, MD, Snezana Ikonomovic, MD, Kenji Ishii, MD, Clifford Jack, MD, Gina Jerome, MS, Erik Johnson, MD, PHD, Mathias Jucker, PhD, Celeste Karch, PhD, Stephan Käser, PHD, Kensaku Kasuga, MD, Sarah Keefe, BS, William Klunk, MD, PHD, Robert Koeppe, PHD, Deb Koudelis, MHS,RN, Elke Kuder-Buletta, RN, Christoph Laske, PhD, Allan Levey, MD, PHD, Johannes Levin, MD, Yan Li, PHD, Oscar Lopez, MD, MD, Jacob Marsh, BA, Ralph Martins, PhD, Neal Scott Mason, PhD, Colin Masters, MD, Kwasi Mawuenyega, PhD, Austin McCullough, PhD Candidate, Eric McDade, DO, Arlene Mejia, MD, Estrella Morenas-Rodriguez, MD, PhD, John Morris, MD, James Mountz, MD, Cath Mummery, PhD, N eelesh Nadkarni, MD, PhD, Akemi Nagamatsu, RN, Katie Neimeyer, MS, Yoshiki Niimi, MD, James Noble, MD, Joanne Norton, MSN, RN, PMHCNS-BC, Brigitte Nuscher, Ulricke Obermüller, Antoinette O'Connor, MRCPI, Riddhi Patira, MD, Richard Perrin, MD, PhD, Lingyan Ping, PhD, Oliver Preische, MD, Alan Renton, PhD, John Ringman, MD, Stephen Salloway, MD, Peter Schofield, PhD, Michio Senda, MD, PhD, Nicholas T Seyfried, D.Phil, Kristine Shady, BA, BS, Hiroyuki Shimada, MD, PhD, Wendy Sigurdson, RN, Jennifer Smith, PhD, Lori Smith, PA-C, Beth Snitz, PhD, Hamid Sohrabi, PhD, Sochenda Stephens, BS, CCRP, Kevin Taddei, BS, Sarah Thompson, PA-C, Jonathan Vöglein, MD, Peter Wang, PhD, Qing Wang, PhD, Elise Weamer, MPH, Chengjie Xiong, PhD, Jinbin Xu, PhD, and Xiong Xu, BS, MS

Subjects
Brain aging, Alzheimer disease, Resting-state functional connectivity, fMRI, Machine learning, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

“Brain-predicted age” quantifies apparent brain age compared to normative neuroimaging trajectories. Advanced brain-predicted age has been well established in symptomatic Alzheimer disease (AD), but is underexplored in preclinical AD. Prior brain-predicted age studies have typically used structural MRI, but resting-state functional connectivity (FC) remains underexplored. Our model predicted age from FC in 391 cognitively normal, amyloid-negative controls (ages 18–89). We applied the trained model to 145 amyloid-negative, 151 preclinical AD, and 156 symptomatic AD participants to test group differences. The model accurately predicted age in the training set. FC-predicted brain age gaps (FC-BAG) were significantly older in symptomatic AD and significantly younger in preclinical AD compared to controls. There was minimal correspondence between networks predictive of age and AD. Elevated FC-BAG may reflect network disruption during symptomatic AD. Reduced FC-BAG in preclinical AD was opposite to the expected direction, and may reflect a biphasic response to preclinical AD pathology or may be driven by inconsistency between age-related vs. AD-related networks. Overall, FC-predicted brain age may be a sensitive AD biomarker.

Published
2022
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18. Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults

Author

Shengwen Deng, Crystal G. Franklin, Michael O'Boyle, Wei Zhang, Betty L. Heyl, Paul A. Jerabek, Hanzhang Lu, and Peter T. Fox

Subjects
Voxel-Based Physiology, Metabolism, Brain, Hemodynamics, PET, fMRI, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Voxel-based physiological (VBP) variables derived from blood oxygen level dependent (BOLD) fMRI time-course variations include: amplitude of low frequency fluctuations (ALFF), fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity (ReHo). Although these BOLD-derived variables can detect between-group (e.g. disease vs control) spatial pattern differences, physiological interpretations are not well established. The primary objective of this study was to quantify spatial correspondences between BOLD VBP variables and PET measurements of cerebral metabolic rate and hemodynamics, being well-validated physiological standards. To this end, quantitative, whole-brain PET images of metabolic rate of glucose (MRGlu; 18FDG) and oxygen (MRO2; 15OO), blood flow (BF; H215O) and blood volume (BV; C15O) were obtained in 16 healthy controls. In the same subjects, BOLD time-courses were obtained for computation of ALFF, fALFF and ReHo images. PET variables were compared pair-wise with BOLD variables. In group-averaged, across-region analyses, ALFF corresponded significantly only with BV (R = 0.64; p < 0.0001). fALFF corresponded most strongly with MRGlu (R = 0.79; p < 0.0001), but also significantly (p < 0.0001) with MRO2 (R = 0.68), BF (R = 0.68) and BV (R=0.68). ReHo performed similarly to fALFF, with significant strong correspondence (p < 0.0001) with MRGlu (R = 0.78), MRO2 (R = 0.54), and, but less strongly with BF (R = 0.50) and BV (R=0.50). Mutual information analyses further clarified these physiological interpretations. When conditioned by BV, ALFF retained no significant MRGlu, MRO2 or BF information. When conditioned by MRGlu, fALFF and ReHo retained no significant MRO2, BF or BV information. Of concern, however, the strength of PET-BOLD correspondences varied markedly by brain region, which calls for future investigation on physiological interpretations at a regional and per-subject basis.

Published
2022
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22. Clinical applications of magnetic resonance imaging based functional and structural connectivity

Author

Chengyuan Wu, Francisca Ferreira, Michael Fox, Noam Harel, Jona Hattangadi-Gluth, Andreas Horn, Saad Jbabdi, Joshua Kahan, Ashwini Oswal, Sameer A. Sheth, Yanmei Tie, Vejay Vakharia, Ludvic Zrinzo, and Harith Akram

Subjects
Connectome, Connectomics, Structural connectivity, Tractography, Functional connectivity, Clinical applications, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Published
2021
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26. The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint

Author

Almeida, Maria Rosario, Anderl-Straub, Sarah, Andersson, Christin, Antonell, Anna, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Luisa, Binetti, Giuliano, Black, Sandra, Bocchetta, Martina, Borrego-Ecija, Sergi, Bras, Jose, Bruffaerts, Rose, Caroppo, Paola, Cash, David, Castelo-Branco, Miguel, Convery, Rhian, Cope, Thomas, de Arriba, María, Di Fede, Giuseppe, Díaz, Zigor, Dick, Katrina M., Duro, Diana, Fenoglio, Chiara, Ferreira, Carlos, Ferreira, Catarina B., Flanagan, Toby, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gabilondo, Alazne, Gauthier, Serge, Ghidoni, Roberta, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Jiskoot, Lize, Karnath, Hans-Otto, Keren, Ron, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Nacmias, Benedetta, Neason, Mollie, Nicholas, Jennifer, Öijerstedt, Linn, Olives, Jaume, Panman, Jessica, Papma, Janne, Patzig, Maximilian, Pievani, Michela, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rittman, Tim, Rogaeva, Ekaterina, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Scarpini, Elio, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Tábuas-Pereira, Miguel, Tainta, Mikel, Tang-Wai, David, Thomas, David L., Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Vandamme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Zetterberg, Henrik, Zulaica, Miren, Premi, Enrico, Calhoun, Vince D., Diano, Matteo, Gazzina, Stefano, Cosseddu, Maura, Alberici, Antonella, Archetti, Silvana, Paternicò, Donata, Gasparotti, Roberto, van Swieten, John, Galimberti, Daniela, Sanchez-Valle, Raquel, Laforce, Robert, Jr., Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James, Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, de Mendonça, Alexandre, Santana, Isabel, Butler, Chris, Ducharme, Simon, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Frisoni, Giovanni, Cappa, Stefano, Sorbi, Sandro, Padovani, Alessandro, Rohrer, Jonathan D., and Borroni, Barbara

Published
2019
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27. Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort

Author

Andersson, Christin, Archetti, Silvana, Arighi, Andrea, Benussi, Luisa, Black, Sandra, Cosseddu, Maura, Fallstrm, Marie, Ferreira, Carlos, Fenoglio, Chiara, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gazzina, Stefano, Ghidoni, Roberta, Grisoli, Marina, Jelic, Vesna, Jiskoot, Lize, Keren, Ron, Lombardi, Gemma, Maruta, Carolina, Meeter, Lieke, van Minkelen, Rick, Nacmias, Benedetta, ijerstedt, Linn, Padovani, Alessandro, Panman, Jessica, Pievani, Michela, Polito, Cristina, Premi, Enrico, Prioni, Sara, Rademakers, Rosa, Redaelli, Veronica, Rogaeva, Ekaterina, Rossi, Giacomina, Rossor, Martin, Scarpini, Elio, Tang-Wai, David, Tartaglia, Carmela, Thonberg, Hakan, Tiraboschi, Pietro, Verdelho, Ana, Warren, Jason, Cury, Claire, Durrleman, Stanley, Cash, David M., Lorenzi, Marco, Nicholas, Jennifer M., Bocchetta, Martina, van Swieten, John C., Borroni, Barbara, Galimberti, Daniela, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B., Graff, Caroline, Tagliavini, Fabrizio, Frisoni, Giovanni B., Laforce, Robert, Jr., Finger, Elizabeth, de Mendonça, Alexandre, Sorbi, Sandro, Ourselin, Sebastien, Rohrer, Jonathan D., and Modat, Marc

Published
2019
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35. ERP markers are associated with neurodevelopmental outcomes in 1–5 month old infants in rural Africa and the UK

Author

Laura Katus, Luke Mason, Bosiljka Milosavljevic, Samantha McCann, Maria Rozhko, Sophie E. Moore, Clare E. Elwell, Sarah Lloyd-Fox, Michelle de Haan, Saikou Drammeh, Ebrima Mbye, Ebou Touray, Mohammed Ceesay, Buba Jobarteh, Momodou K. Darboe, Topun Austin, and Andrew Prentice

Subjects
Neurodevelopment, Global health, Infants, Event related potentials, Novelty detection, Habituation, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Introduction: Infants and children in low- and middle-income countries are frequently exposed to a range of poverty-related risk factors, increasing their likelihood of poor neurodevelopmental outcomes. There is a need for culturally objective markers, which can be used to study infants from birth, thereby enabling early identification and ultimately intervention during a critical time of neurodevelopment. Method: In this paper, we investigate developmental changes in auditory event related potentials (ERP) associated with habituation and novelty detection in infants between 1 and 5 months living in the United Kingdom and The Gambia, West Africa. Previous research reports that whereas newborns’ ERP responses are increased when presented with stimuli of higher intensity, this sensory driven response decreases over the first few months of life, giving rise to a cognitively driven, novelty-based response. Anthropometric measures were obtained concurrently with the ERP measures at 1 and 5 months of age. Neurodevelopmental outcome was measured using the Mullen Scales of Early Learning (MSEL) at 5 months of age. Results: The described developmental change was observed in the UK cohort, who exhibited an intensity-based response at 1 month and a novelty-based response at 5 months of age. This change was accompanied by greater habituation to stimulus intensity at 5 compared to 1 month. In the Gambian cohort we did not see a change from an intensity-to a novelty-based response, and no change in habituation to stimulus intensity across the two age points. The degree of change from an intensity towards a novelty-based response was further found to be associated with MSEL scores at 5 months of infant age, whereas infants’ growth between 1 and 5 months was not. Discussion: Our study highlights the utility of ERP-based markers to study young infants in rural Africa. By implementing a well-established paradigm in a previously understudied population we have demonstrated its use as a culturally objective tool to better understand early learning in diverse settings world-wide. Results offer insight into the neurodevelopmental processes underpinning early neurocognitive development, which may in the future contribute to early identification of infants at heightened risk of adverse neurodevelopmental outcome.

Published
2020
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36. Combining fMRI during resting state and an attention bias task in children

Author

Anita Harrewijn, Rany Abend, Julia Linke, Melissa A. Brotman, Nathan A. Fox, Ellen Leibenluft, Anderson M. Winkler, and Daniel S. Pine

Subjects
Attention bias, Functional connectivity, fMRI, Resting state, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Neuroimaging studies typically focus on either resting state or task-based fMRI data. Prior research has shown that similarity in functional connectivity between rest and cognitive tasks, interpreted as reconfiguration efficiency, is related to task performance and IQ. Here, we extend this approach from adults to children, and from cognitive tasks to a threat-based attention task. The goal of the current study was to examine whether similarity in functional connectivity during rest and an attention bias task relates to threat bias, IQ, anxiety symptoms, and social reticence. fMRI was measured during resting state and during the dot-probe task in 41 children (M = 13.44, SD = 0.70). Functional connectivity during rest and dot-probe was positively correlated, suggesting that functional hierarchies in the brain are stable. Similarity in functional connectivity between rest and the dot-probe task only related to threat bias (puncorr

Published
2020
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43. Development of the error-monitoring system from ages 9–35: Unique insight provided by MRI-constrained source localization of EEG

Author

George A. Buzzell, John E. Richards, Lauren K. White, Tyson V. Barker, Daniel S. Pine, and Nathan A. Fox

Subjects
Error-monitoring, ERN, Source-localization, Development, Adolescence, Posterior cingulate, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

The ability to self-detect errors and dynamically adapt behavior is a cornerstone of higher-level cognition, requiring coordinated activity from a network of neural regions. However, disagreement exists over how the error-monitoring system develops throughout adolescence and early adulthood. The present report leveraged MRI-constrained EEG source localization to detail typical development of the error-monitoring system in a sample of 9–35 year-olds (n = 43). Participants performed a flanker task while high-density EEG was recorded; structural MRIs were also acquired for all participants. Analysis of the scalp-recorded EEG data revealed a frontocentral negativity (error-related negativity; ERN) immediately following errors for all participants, although the topography of the ERN varied with age. Source localization of the ERN time range revealed maximal activity within the posterior cingulate cortex (PCC) for all ages, consistent with recent evidence that the PCC provides a substantial contribution to the scalp-recorded ERN. Activity within a network of brain regions, including dorsal anterior cingulate, PCC, and parietal cortex, was predictive of improved performance following errors, regardless of age. However, additional activity within insula, orbitofrontal cortex and inferior frontal gyrus linearly increased with age. Together, these data suggest that the core error-monitoring system is online by early adolescence and remains relatively stable into adulthood. However, additional brain regions become embedded within this core network with age. These results serve as a model of typical development of the error-monitoring system from early adolescence into adulthood.

Published
2017
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44. Multifocal tDCS targeting the resting state motor network increases cortical excitability beyond traditional tDCS targeting unilateral motor cortex

Author

D.B. Fischer, P.J. Fried, G. Ruffini, O. Ripolles, R. Salvador, J. Banus, W.T. Ketchabaw, E. Santarnecchi, A. Pascual-Leone, and M.D. Fox

Subjects
FMRI, Resting state, Functional connectivity, Transcranial direct current stimulation, Network stimulation, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Scientists and clinicians have traditionally targeted single brain regions with stimulation to modulate brain function and disease. However, brain regions do not operate in isolation, but interact with other regions through networks. As such, stimulation of one region may impact and be impacted by other regions in its network. Here we test whether the effects of brain stimulation can be enhanced by simultaneously targeting a region and its network, identified with resting state functional connectivity MRI. Fifteen healthy participants received two types of transcranial direct current stimulation (tDCS): a traditional two-electrode montage targeting a single brain region (left primary motor cortex [M1]) and a novel eight-electrode montage targeting this region and its associated resting state network. As a control, 8 participants also received multifocal tDCS mismatched to this network. Network-targeted tDCS more than doubled the increase in left M1 excitability over time compared to traditional tDCS and the multifocal control. Modeling studies suggest these results are unlikely to be due to tDCS effects on left M1 itself, however it is impossible to completely exclude this possibility. It also remains unclear whether multifocal tDCS targeting a network selectively modulates this network and which regions within the network are most responsible for observed effects. Despite these limitations, network-targeted tDCS appears to be a promising approach for enhancing tDCS effects beyond traditional stimulation targeting a single brain region. Future work is needed to test whether these results extend to other resting state networks and enhance behavioral or therapeutic effects.

Published
2017
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48. Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease

Author

Millar, Peter R., primary, Luckett, Patrick H., additional, Gordon, Brian A., additional, Benzinger, Tammie L.S., additional, Schindler, Suzanne E., additional, Fagan, Anne M., additional, Cruchaga, Carlos, additional, Bateman, Randall J., additional, Allegri, Ricardo, additional, Jucker, Mathias, additional, Lee, Jae-Hong, additional, Mori, Hiroshi, additional, Salloway, Stephen P, additional, Yakushev, Igor, additional, Morris, John C., additional, Ances, Beau M., additional, Adams, Sarah, additional, Araki, Aki, additional, Barthelemy, Nicolas, additional, Bateman, Randall, additional, Bechara, Jacob, additional, Benzinger, Tammie, additional, Berman, Sarah, additional, Bodge, Courtney, additional, Brandon, Susan, additional, Brooks, William (Bill), additional, Brosch, Jared, additional, Buck, Jill, additional, Buckles, Virginia, additional, Carter, Kathleen, additional, Cash, Lisa, additional, Chen, Charlie, additional, Chhatwal, Jasmeer, additional, Mendez, Patricio Chrem, additional, Chua, Jasmin, additional, Chui, Helena, additional, Courtney, Laura, additional, Day, Gregory S, additional, DeLaCruz, Chrismary, additional, Denner, Darcy, additional, Diffenbacher, Anna, additional, Dincer, Aylin, additional, Donahue, Tamara, additional, Douglas, Jane, additional, Duong, Duc, additional, Egido, Noelia, additional, Esposito, Bianca, additional, Fagan, Anne, additional, Farlow, Marty, additional, Feldman, Becca, additional, Fitzpatrick, Colleen, additional, Flores, Shaney, additional, Fox, Nick, additional, Franklin, Erin, additional, Joseph-Mathurin, Nelly, additional, Fujii, Hisako, additional, Gardener, Samantha, additional, Ghetti, Bernardino, additional, Goate, Alison, additional, Goldberg, Sarah, additional, Goldman, Jill, additional, Gonzalez, Alyssa, additional, Gordon, Brian, additional, Gräber-Sultan, Susanne, additional, Graff-Radford, Neill, additional, Graham, Morgan, additional, Gray, Julia, additional, Gremminger, Emily, additional, Grilo, Miguel, additional, Groves, Alex, additional, Haass, Christian, additional, Häsler, Lisa, additional, Hassenstab, Jason, additional, Hellm, Cortaiga, additional, Herries, Elizabeth, additional, Hoechst-Swisher, Laura, additional, Hofmann, Anna, additional, Holtzman, David, additional, Hornbeck, Russ, additional, Igor, Yakushev, additional, Ihara, Ryoko, additional, Ikeuchi, Takeshi, additional, Ikonomovic, Snezana, additional, Ishii, Kenji, additional, Jack, Clifford, additional, Jerome, Gina, additional, Johnson, Erik, additional, Karch, Celeste, additional, Käser, Stephan, additional, Kasuga, Kensaku, additional, Keefe, Sarah, additional, Klunk, William, additional, Koeppe, Robert, additional, Koudelis, Deb, additional, Kuder-Buletta, Elke, additional, Laske, Christoph, additional, Levey, Allan, additional, Levin, Johannes, additional, Li, Yan, additional, Lopez, Oscar, additional, Marsh, Jacob, additional, Martins, Ralph, additional, Mason, Neal Scott, additional, Masters, Colin, additional, Mawuenyega, Kwasi, additional, McCullough, Austin, additional, McDade, Eric, additional, Mejia, Arlene, additional, Morenas-Rodriguez, Estrella, additional, Morris, John, additional, Mountz, James, additional, Mummery, Cath, additional, Nadkarni, N eelesh, additional, Nagamatsu, Akemi, additional, Neimeyer, Katie, additional, Niimi, Yoshiki, additional, Noble, James, additional, Norton, Joanne, additional, Nuscher, Brigitte, additional, Obermüller, Ulricke, additional, O'Connor, Antoinette, additional, Patira, Riddhi, additional, Perrin, Richard, additional, Ping, Lingyan, additional, Preische, Oliver, additional, Renton, Alan, additional, Ringman, John, additional, Salloway, Stephen, additional, Schofield, Peter, additional, Senda, Michio, additional, Seyfried, Nicholas T, additional, Shady, Kristine, additional, Shimada, Hiroyuki, additional, Sigurdson, Wendy, additional, Smith, Jennifer, additional, Smith, Lori, additional, Snitz, Beth, additional, Sohrabi, Hamid, additional, Stephens, Sochenda, additional, Taddei, Kevin, additional, Thompson, Sarah, additional, Vöglein, Jonathan, additional, Wang, Peter, additional, Wang, Qing, additional, Weamer, Elise, additional, Xiong, Chengjie, additional, Xu, Jinbin, additional, and Xu, Xiong, additional

Published
2022
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49. Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA–DTI working group

Author

Jahanshad, Neda, Kochunov, Peter V., Sprooten, Emma, Mandl, René C., Nichols, Thomas E., Almasy, Laura, Blangero, John, Brouwer, Rachel M., Curran, Joanne E., de Zubicaray, Greig I., Duggirala, Ravi, Fox, Peter T., Hong, L. Elliot, Landman, Bennett A., Martin, Nicholas G., McMahon, Katie L., Medland, Sarah E., Mitchell, Braxton D., Olvera, Rene L., Peterson, Charles P., Starr, John M., Sussmann, Jessika E., Toga, Arthur W., Wardlaw, Joanna M., Wright, Margaret J., Hulshoff Pol, Hilleke E., Bastin, Mark E., McIntosh, Andrew M., Deary, Ian J., Thompson, Paul M., and Glahn, David C.

Published
2013
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