Academic Appointments

All Publications

  • Why experimental variation in neuroimaging should be embraced. Nature communications Kiar, G., Mumford, J. A., Xu, T., Vogelstein, J. T., Glatard, T., Milham, M. P. 2024; 15 (1): 9411

    Abstract

    In a perfect world, scientists would develop analyses that are guaranteed to reveal the ground truth of a research question. In reality, there are countless viable workflows that produce distinct, often conflicting, results. Although reproducibility places a necessary bound on the validity of results, it is not sufficient for claiming underlying validity, eventual utility, or generalizability. In this work we focus on how embracing variability in data analysis can improve the generalizability of results. We contextualize how design decisions in brain imaging can be made to capture variation, highlight examples, and discuss how variability capture may improve the quality of results.

    View details for DOI 10.1038/s41467-024-53743-y

    View details for PubMedID 39482294

    View details for PubMedCentralID 6041980

  • Predicting Task Activation Maps from Resting-State Functional Connectivity using Deep Learning. bioRxiv : the preprint server for biology Madsen, S. J., Uddin, L. Q., Mumford, J. A., Barch, D. M., Fair, D. A., Gotlib, I. H., Poldrack, R. A., Kuceyeski, A., Saggar, M. 2024

    Abstract

    Recent work has shown that deep learning is a powerful tool for predicting brain activation patterns evoked through various tasks using resting state features. We replicate and improve upon this recent work to introduce two models, BrainSERF and BrainSurfGCN, that perform at least as well as the state-of-the-art while greatly reducing memory and computational footprints. Our performance analysis observed that low predictability was associated with a possible lack of task engagement derived from behavioral performance. Furthermore, a deficiency in model performance was also observed for closely matched task contrasts, likely due to high individual variability confirmed by low test-retest reliability. Overall, we successfully replicate recently developed deep learning architecture and provide scalable models for further research.

    View details for DOI 10.1101/2024.09.10.612309

    View details for PubMedID 39314460

    View details for PubMedCentralID PMC11419026

  • Cognitive tasks, anatomical MRI, and functional MRI data evaluating the construct of self-regulation. Scientific data Bissett, P. G., Eisenberg, I. W., Shim, S., Rios, J. A., Jones, H. M., Hagen, M. P., Enkavi, A. Z., Li, J. K., Mumford, J. A., MacKinnon, D. P., Marsch, L. A., Poldrack, R. A. 2024; 11 (1): 809

    Abstract

    We describe the following shared data from N = 103 healthy adults who completed a broad set of cognitive tasks, surveys, and neuroimaging measurements to examine the construct of self-regulation. The neuroimaging acquisition involved task-based fMRI, resting state fMRI, and structural MRI. Each subject completed the following ten tasks in the scanner across two 90-minute scanning sessions: attention network test (ANT), cued task switching, Columbia card task, dot pattern expectancy (DPX), delay discounting, simple and motor selective stop signal, Stroop, a towers task, and a set of survey questions. The dataset is shared openly through the OpenNeuro project, and the dataset is formatted according to the Brain Imaging Data Structure (BIDS) standard.

    View details for DOI 10.1038/s41597-024-03636-y

    View details for PubMedID 39033226

    View details for PubMedCentralID 3041102

  • Impact of analytic decisions on test-retest reliability of individual and group estimates in functional magnetic resonance imaging: a multiverse analysis using the monetary incentive delay task. bioRxiv : the preprint server for biology Demidenko, M. I., Mumford, J. A., Poldrack, R. A. 2024

    Abstract

    Empirical studies reporting low test-retest reliability of individual blood oxygen-level dependent (BOLD) signal estimates in functional magnetic resonance imaging (fMRI) data have resurrected interest among cognitive neuroscientists in methods that may improve reliability in fMRI. Over the last decade, several individual studies have reported that modeling decisions, such as smoothing, motion correction and contrast selection, may improve estimates of test-retest reliability of BOLD signal estimates. However, it remains an empirical question whether certain analytic decisions consistently improve individual and group level reliability estimates in an fMRI task across multiple large, independent samples. This study used three independent samples (Ns: 60, 81, 120) that collected the same task (Monetary Incentive Delay task) across two runs and two sessions to evaluate the effects of analytic decisions on the individual (intraclass correlation coefficient [ICC(3,1)]) and group (Jaccard/Spearman rho) reliability estimates of BOLD activity of task fMRI data. The analytic decisions in this study vary across four categories: smoothing kernel (five options), motion correction (four options), task parameterizing (three options) and task contrasts (four options), totaling 240 different pipeline permutations. Across all 240 pipelines, the median ICC estimates are consistently low, with a maximum median ICC estimate of .44 - .55 across the three samples. The analytic decisions with the greatest impact on the median ICC and group similarity estimates are the Implicit Baseline contrast, Cue Model parameterization and a larger smoothing kernel. Using an Implicit Baseline in a contrast condition meaningfully increased group similarity and ICC estimates as compared to using the Neutral cue. This effect was largest for the Cue Model parameterization, however, improvements in reliability came at the cost of interpretability. This study illustrates that estimates of reliability in the MID task are consistently low and variable at small samples, and a higher test-retest reliability may not always improve interpretability of the estimated BOLD signal.

    View details for DOI 10.1101/2024.03.19.585755

    View details for PubMedID 38562804

    View details for PubMedCentralID PMC10983911

  • A multi-sample evaluation of the measurement structure and function of the modified monetary incentive delay task in adolescents. Developmental cognitive neuroscience Demidenko, M. I., Mumford, J. A., Ram, N., Poldrack, R. A. 2023; 65: 101337

    Abstract

    Interpreting the neural response elicited during task functional magnetic resonance imaging (fMRI) remains a challenge in neurodevelopmental research. The monetary incentive delay (MID) task is an fMRI reward processing task that is extensively used in the literature. However, modern psychometric tools have not been used to evaluate measurement properties of the MID task fMRI data. The current study uses data for a similar task design across three adolescent samples (N=346 [Agemean 12.0; 44 % Female]; N=97 [19.3; 58 %]; N=112 [20.2; 38 %]) to evaluate multiple measurement properties of fMRI responses on the MID task. Confirmatory factor analysis (CFA) is used to evaluate an a priori theoretical model for the task and its measurement invariance across three samples. Exploratory factor analysis (EFA) is used to identify the data-driven measurement structure across the samples. CFA results suggest that the a priori model is a poor representation of these MID task fMRI data. Across the samples, the data-driven EFA models consistently identify a six-to-seven factor structure with run and bilateral brain region factors. This factor structure is moderately-to-highly congruent across the samples. Altogether, these findings demonstrate a need to evaluate theoretical frameworks for popular fMRI task designs to improve our understanding and interpretation of brain-behavior associations.

    View details for DOI 10.1016/j.dcn.2023.101337

    View details for PubMedID 38160517

  • The response time paradox in functional magnetic resonance imaging analyses. Nature human behaviour Mumford, J. A., Bissett, P. G., Jones, H. M., Shim, S., Rios, J. A., Poldrack, R. A. 2023

    Abstract

    Response times (RTs) are often the main signal of interest in cognitive psychology but are often ignored in functional MRI (fMRI) analyses. In fMRI analysis the intensity of the signal serves as a proxy for the intensity of local neuronal activity, but changes in either the intensity or the duration of neuronal activity can yield identical fMRI signals. Therefore, if RTs are ignored and pair with neuronal durations, fMRI results claiming intensity differences may be confounded by RTs. We show how ignoring RTs goes beyond this confound, where longer RTs are paired with larger activation estimates, to lesser-known issues where RTs become confounds in group-level analyses and, surprisingly, how the RT confound can induce other artificial group-level associations with variables that are not related to the condition contrast or RTs. We propose a new time-series model to address these issues and encourage increasing focus on what the widespread RT-based signal represents.

    View details for DOI 10.1038/s41562-023-01760-0

    View details for PubMedID 37996498

    View details for PubMedCentralID 2622763

  • Cognitive tasks, anatomical MRI, and functional MRI data evaluating the construct of self-regulation. bioRxiv : the preprint server for biology Bissett, P. G., Eisenberg, I. W., Shim, S., Rios, J. A., Jones, H. M., Hagen, M. P., Enkavi, A. Z., Li, J. K., Mumford, J. A., MacKinnon, D. P., Marsch, L. A., Poldrack, R. A. 2023

    Abstract

    We describe the following shared data from N=103 healthy adults who completed a broad set cognitive tasks, surveys, and neuroimaging measurements to examine the construct of self-regulation. The neuroimaging acquisition involved task-based fMRI, resting fMRI, and structural MRI. Each subject completed the following ten tasks in the scanner across two 90-minute scanning sessions: attention network test (ANT), cued task switching, Columbia card task, dot pattern expectancy (DPX), delay discounting, simple and motor selective stop signal, Stroop, a towers task, and a set of survey questions. Subjects also completed resting state scans. The dataset is shared openly through the OpenNeuro project, and the dataset is formatted according to the Brain Imaging Data Structure (BIDS) standard.

    View details for DOI 10.1101/2023.09.27.559869

    View details for PubMedID 37808748

    View details for PubMedCentralID PMC10557703

  • A dual-task approach to inform the taxonomy of inhibition-related processes. Journal of experimental psychology. Human perception and performance Bissett, P. G., Jones, H. M., Hagen, M. P., Bui, T. T., Li, J. K., Rios, J. A., Mumford, J. A., Shine, J. M., Poldrack, R. A. 2022

    Abstract

    Response inhibition is key to controlled behavior and is commonly investigated with the stop-signal paradigm. The authors investigated how response inhibition is situated within a taxonomy of control processes by combining multiple forms of control within dual tasks. Response inhibition, as measured by stop-signal reaction time (SSRT), was impaired when combined with shape matching, but not the flanker task, and when combined with cued task switching, but not predictable task switching, suggesting that response inhibition may be weakly or variably impaired when combined with selective attention and set shifting demands, respectively. Response inhibition was also consistently impaired when combined with the N-back or directed forgetting tasks, putative measures of working memory. Impairments of response inhibition by other control demands appeared to be primarily driven by task context, as SSRT slowing was similar for trials where control demands were either high (e.g., task switch) or low (e.g., task stay). These results demonstrate that response inhibition processes are often impaired in the context of other control demands, even on trials where direct engagement of those other control processes is not required. This suggests a taxonomy of control in which response inhibition overlaps with related control processes, especially working memory. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

    View details for DOI 10.1037/xhp0001073

    View details for PubMedID 36548061

  • Neural Signatures of Pain Modulation in Short-Term and Long-Term Mindfulness Training: A Randomized Active-Control Trial. The American journal of psychiatry Wielgosz, J., Kral, T. R., Perlman, D. M., Mumford, J. A., Wager, T. D., Davidson, R. J. 2022: appiajp21020145

    Abstract

    Mindfulness-based interventions are widely used to target pain, yet their neural mechanisms of action are insufficiently understood. The authors studied neural and subjective pain response in a randomized active-control trial of mindfulness-based stress reduction (MBSR) alongside long-term meditation practitioners.Healthy participants (N=115) underwent functional neuroimaging during a thermal acute pain task before and after random assignment to MBSR (N=28), an active control condition (health enhancement program [HEP]) (N=32), or a waiting list control condition (N=31). Long-term meditators (N=30) completed the same neuroimaging paradigm. Pain response was measured via self-reported intensity and unpleasantness, and neurally via two multivoxel machine-learning-derived signatures: the neurologic pain signature (NPS), emphasizing nociceptive pain processing, and the stimulus intensity independent pain signature-1 (SIIPS1), emphasizing stimulus-independent neuromodulatory processes.The MBSR group showed a significant decrease in NPS response relative to the HEP group (Cohen's d=-0.43) and from pre- to postintervention assessment (d=-0.47). The MBSR group showed small, marginal decreases in NPS relative to the waiting list group (d=-0.36), and in SIIPS1 relative to both groups (HEP group, d=-0.37; waiting list group, d=-0.37). In subjective unpleasantness, the MBSR and HEP groups also showed modest significant reductions compared with the waiting list group (d=-0.45 and d=-0.55). Long-term meditators reported significantly lower pain than nonmeditators but did not differ in neural response. Within the long-term meditator group, cumulative practice during intensive retreat was significantly associated with reduced SIIPS1 (r=-0.65), whereas daily practice was not.Mindfulness training showed associations with pain reduction that implicate differing neural pathways depending on extent and context of practice. Use of neural pain signatures in randomized trials offers promise for guiding the application of mindfulness interventions to pain treatment.

    View details for DOI 10.1176/appi.ajp.21020145

    View details for PubMedID 35899379

  • Relating psychiatric symptoms and self-regulation during the COVID-19 crisis. Translational psychiatry Vaghi, M. M., Hagen, M. P., Jones, H. M., Mumford, J. A., Bissett, P. G., Poldrack, R. A. 2022; 12 (1): 271

    Abstract

    Disruptions of self-regulation are a hallmark of numerous psychiatric disorders. Here, we examine the relationship between transdiagnostic dimensions of psychopathology and changes in self-regulation in the early phase of the COVID-19 pandemic. We used a data-driven approach on a large number of cognitive tasks and self-reported surveys in training datasets. Then, we derived measures of self-regulation and psychiatric functioning in an independent population sample (N=102) tested both before and after the onset of the COVID-19 pandemic, when the restrictions in place represented a threat to mental health and forced people to flexibly adjust to modifications of daily routines. We found independent relationships between transdiagnostic dimensions of psychopathology and longitudinal alterations in specific domains of self-regulation defined using a diffusion decision model. Compared to the period preceding the onset of the pandemic, a symptom dimension related to anxiety and depression was characterized by a more cautious behavior, indexed by the need to accumulate more evidence before making a decision. Instead, social withdrawal related to faster non-decision processes. Self-reported measures of self-regulation predicted variance in psychiatric symptoms both concurrently and prospectively, revealing the psychological dimensions relevant for separate transdiagnostic dimensions of psychiatry, but tasks did not. Taken together, our results are suggestive of potential cognitive vulnerabilities in the domain of self-regulation in people with underlying psychiatric difficulties in face of real-life stressors. More generally, they also suggest that the study of cognition needs to take into account the dynamic nature of real-world events as well as within-subject variability over time.

    View details for DOI 10.1038/s41398-022-02030-9

    View details for PubMedID 35820995

  • The Impact of Mindfulness Training on Police Officer Stress, Mental Health, and Salivary Cortisol Levels. Frontiers in psychology Grupe, D. W., Stoller, J. L., Alonso, C., McGehee, C., Smith, C., Mumford, J. A., Rosenkranz, M. A., Davidson, R. J. 2021; 12: 720753

    Abstract

    Unaddressed occupational stress and trauma contribute to elevated rates of mental illness and suicide in policing, and to violent and aggressive behavior that disproportionately impacts communities of color. Emerging evidence suggests mindfulness training with police may reduce stress and aggression and improve mental health, but there is limited evidence for changes in biological outcomes or the lasting benefits of mindfulness training. We conducted a randomized controlled trial (RCT) of 114 police officers from three Midwestern U.S. law enforcement agencies. We assessed stress-related physical and mental health symptoms, blood-based inflammatory markers, and hair and salivary cortisol. Participants were then randomized to an 8-week mindfulness intervention or waitlist control (WLC), and the same assessments were repeated post-intervention and at 3-month follow-up. Relative to waitlist control, the mindfulness group had greater improvements in psychological distress, mental health symptoms, and sleep quality post-training, gains that were maintained at 3-month follow-up. Intervention participants also had a significantly lower cortisol awakening response (CAR) at 3-month follow-up relative to waitlist control. Contrary to hypotheses, there were no intervention effects on hair cortisol, diurnal cortisol slope, or inflammatory markers. In summary, an 8-week mindfulness intervention for police officers led to self-reported improvements in distress, mental health, and sleep, and a lower CAR. These benefits persisted (or emerged) at 3-month follow-up, suggesting that this training may buffer against the long-term consequences of chronic stress. Future research should assess the persistence of these benefits over a longer period while expanding the scope of outcomes to consider the broader community of mindfulness training for police. Clinical Trial Registration: ClinicalTrials.gov#NCT03488875.

    View details for DOI 10.3389/fpsyg.2021.720753

    View details for PubMedID 34539521

  • Variability in the analysis of a single neuroimaging dataset by many teams. Nature Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R. A., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., Benoit, R. G., Berkers, R. M., Bhanji, J. P., Biswal, B. B., Bobadilla-Suarez, S., Bortolini, T., Bottenhorn, K. L., Bowring, A., Braem, S., Brooks, H. R., Brudner, E. G., Calderon, C. B., Camilleri, J. A., Castrellon, J. J., Cecchetti, L., Cieslik, E. C., Cole, Z. J., Collignon, O., Cox, R. W., Cunningham, W. A., Czoschke, S., Dadi, K., Davis, C. P., Luca, A. D., Delgado, M. R., Demetriou, L., Dennison, J. B., Di, X., Dickie, E. W., Dobryakova, E., Donnat, C. L., Dukart, J., Duncan, N. W., Durnez, J., Eed, A., Eickhoff, S. B., Erhart, A., Fontanesi, L., Fricke, G. M., Fu, S., Galván, A., Gau, R., Genon, S., Glatard, T., Glerean, E., Goeman, J. J., Golowin, S. A., González-García, C., Gorgolewski, K. J., Grady, C. L., Green, M. A., Guassi Moreira, J. F., Guest, O., Hakimi, S., Hamilton, J. P., Hancock, R., Handjaras, G., Harry, B. B., Hawco, C., Herholz, P., Herman, G., Heunis, S., Hoffstaedter, F., Hogeveen, J., Holmes, S., Hu, C. P., Huettel, S. A., Hughes, M. E., Iacovella, V., Iordan, A. D., Isager, P. M., Isik, A. I., Jahn, A., Johnson, M. R., Johnstone, T., Joseph, M. J., Juliano, A. C., Kable, J. W., Kassinopoulos, M., Koba, C., Kong, X. Z., Koscik, T. R., Kucukboyaci, N. E., Kuhl, B. A., Kupek, S., Laird, A. R., Lamm, C., Langner, R., Lauharatanahirun, N., Lee, H., Lee, S., Leemans, A., Leo, A., Lesage, E., Li, F., Li, M. Y., Lim, P. C., Lintz, E. N., Liphardt, S. W., Losecaat Vermeer, A. B., Love, B. C., Mack, M. L., Malpica, N., Marins, T., Maumet, C., McDonald, K., McGuire, J. T., Melero, H., Méndez Leal, A. S., Meyer, B., Meyer, K. N., Mihai, G., Mitsis, G. D., Moll, J., Nielson, D. M., Nilsonne, G., Notter, M. P., Olivetti, E., Onicas, A. I., Papale, P., Patil, K. R., Peelle, J. E., Pérez, A., Pischedda, D., Poline, J. B., Prystauka, Y., Ray, S., Reuter-Lorenz, P. A., Reynolds, R. C., Ricciardi, E., Rieck, J. R., Rodriguez-Thompson, A. M., Romyn, A., Salo, T., Samanez-Larkin, G. R., Sanz-Morales, E., Schlichting, M. L., Schultz, D. H., Shen, Q., Sheridan, M. A., Silvers, J. A., Skagerlund, K., Smith, A., Smith, D. V., Sokol-Hessner, P., Steinkamp, S. R., Tashjian, S. M., Thirion, B., Thorp, J. N., Tinghög, G., Tisdall, L., Tompson, S. H., Toro-Serey, C., Torre Tresols, J. J., Tozzi, L., Truong, V., Turella, L., van 't Veer, A. E., Verguts, T., Vettel, J. M., Vijayarajah, S., Vo, K., Wall, M. B., Weeda, W. D., Weis, S., White, D. J., Wisniewski, D., Xifra-Porxas, A., Yearling, E. A., Yoon, S., Yuan, R., Yuen, K. S., Zhang, L., Zhang, X., Zosky, J. E., Nichols, T. E., Poldrack, R. A., Schonberg, T. 2020; 582 (7810): 84-88

    Abstract

    Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

    View details for DOI 10.1038/s41586-020-2314-9

    View details for PubMedID 32483374

  • Variability in the analysis of a single neuroimaging dataset by many teams NATURE Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., Benoit, R. G., Berkers, R. J., Bhanji, J. P., Biswal, B. B., Bobadilla-Suarez, S., Bortolini, T., Bottenhorn, K. L., Bowring, A., Braem, S., Brooks, H. R., Brudner, E. G., Calderon, C. B., Camilleri, J. A., Castrellon, J. J., Cecchetti, L., Cieslik, E. C., Cole, Z. J., Collignon, O., Cox, R. W., Cunningham, W. A., Czoschke, S., Dadi, K., Davis, C. P., Luca, A., Delgado, M. R., Demetriou, L., Dennison, J. B., Di, X., Dickie, E. W., Dobryakova, E., Donnat, C. L., Dukart, J., Duncan, N. W., Durnez, J., Eed, A., Eickhoff, S. B., Erhart, A., Fontanesi, L., Fricke, G., Fu, S., Galvan, A., Gau, R., Genon, S., Glatard, T., Glerean, E., Goeman, J. J., Golowin, S. E., Gonzalez-Garcia, C., Gorgolewski, K. J., Grady, C. L., Green, M. A., Guassi Moreira, J. F., Guest, O., Hakimi, S., Hamilton, J., Hancock, R., Handjaras, G., Harry, B. B., Hawco, C., Herholz, P., Herman, G., Heunis, S., Hoffstaedter, F., Hogeveen, J., Holmes, S., Hu, C., Huettel, S. A., Hughes, M. E., Iacovella, V., Iordan, A. D., Isager, P. M., Isik, A. I., Jahn, A., Johnson, M. R., Johnstone, T., Joseph, M. E., Juliano, A. C., Kable, J. W., Kassinopoulos, M., Koba, C., Kong, X., Koscik, T. R., Kucukboyaci, N., Kuhl, B. A., Kupek, S., Laird, A. R., Lamm, C., Langner, R., Lauharatanahirun, N., Lee, H., Lee, S., Leemans, A., Leo, A., Lesage, E., Li, F., Li, M. C., Lim, P., Lintz, E. N., Liphardt, S. W., Losecaat Vermeer, A. B., Love, B. C., Mack, M. L., Malpica, N., Marins, T., Maumet, C., McDonald, K., McGuire, J. T., Melero, H., Mendez Leal, A. S., Meyer, B., Meyer, K. N., Mihai, G., Mitsis, G. D., Moll, J., Nielson, D. M., Nilsonne, G., Notter, M. P., Olivetti, E., Onicas, A. I., Papale, P., Patil, K. R., Peelle, J. E., Perez, A., Pischedda, D., Poline, J., Prystauka, Y., Ray, S., Reuter-Lorenz, P. A., Reynolds, R. C., Ricciardi, E., Rieck, J. R., Rodriguez-Thompson, A. M., Romyn, A., Salo, T., Samanez-Larkin, G. R., Sanz-Morales, E., Schlichting, M. L., Schultz, D. H., Shen, Q., Sheridan, M. A., Silvers, J. A., Skagerlund, K., Smith, A., Smith, D. V., Sokol-Hessner, P., Steinkamp, S. R., Tashjian, S. M., Thirion, B., Thorp, J. N., Tinghog, G., Tisdall, L., Tompson, S. H., Toro-Serey, C., Torre Tresols, J., Tozzi, L., Truong, V., Turella, L., van 't Veer, A. E., Verguts, T., Vettel, J. M., Vijayarajah, S., Vo, K., Wall, M. B., Weeda, W. D., Weis, S., White, D. J., Wisniewski, D., Xifra-Porxas, A., Yearling, E. A., Yoon, S., Yuan, R., Yuen, K. L., Zhang, L., Zhang, X., Zosky, J. E., Nichols, T. E., Poldrack, R. A., Schonberg, T. 2020

    View details for DOI 10.1038/s41586-020-2314-9

    View details for Web of Science ID 000535225300001

  • Neural correlates of state-based decision-making in younger and older adults NEUROIMAGE Worthy, D. A., Davis, T., Gorlick, M. A., Cooper, J. A., Bakkour, A., Mumford, J. A., Poldrack, R. A., Maddox, W. T. 2016; 130: 13-23

    Abstract

    Older and younger adults performed a state-based decision-making task while undergoing functional MRI (fMRI). We proposed that younger adults would be more prone to base their decisions on expected value comparisons, but that older adults would be more reactive decision-makers who would act in response to recent changes in rewards or states, rather than on a comparison of expected values. To test this we regressed BOLD activation on two measures from a sophisticated reinforcement learning (RL) model. A value-based regressor was computed by subtracting the immediate value of the selected alternative from its long-term value. The other regressor was a state-change uncertainty signal that served as a proxy for whether the participant's state improved or declined, relative to the previous trial. Younger adults' activation was modulated by the value-based regressor in ventral striatal and medial PFC regions implicated in reinforcement learning. Older adults' activation was modulated by state-change uncertainty signals in right dorsolateral PFC, and activation in this region was associated with improved performance in the task. This suggests that older adults may depart from standard expected-value based strategies and recruit lateral PFC regions to engage in reactive decision-making strategies.

    View details for DOI 10.1016/j.neuroimage.2015.12.004

    View details for Web of Science ID 000372745600002

    View details for PubMedCentralID PMC4808466

  • Long-term neural and physiological phenotyping of a single human NATURE COMMUNICATIONS Poldrack, R. A., Laumann, T. O., Koyejo, O., Gregory, B., Hover, A., Chen, M., Gorgolewski, K. J., Luci, J., Joo, S. J., Boyd, R. L., Hunicke-Smith, S., Simpson, Z. B., Caven, T., Sochat, V., Shine, J. M., Gordon, E., Snyder, A. Z., Adeyemo, B., Petersen, S. E., Glahn, D. C., McKay, D. R., Curran, J. E., Goering, H. H., Carless, M. A., Blangero, J., Dougherty, R., Leemans, A., Handwerker, D. A., Frick, L., Marcotte, E. M., Mumford, J. A. 2015; 6

    Abstract

    Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders.

    View details for DOI 10.1038/ncomms9885

    View details for Web of Science ID 000367577400002

    View details for PubMedCentralID PMC4682164

  • Functional System and Areal Organization of a Highly Sampled Individual Human Brain NEURON Laumann, T. O., Gordon, E. M., Adeyemo, B., Snyder, A. Z., Joo, S. J., Chen, M., Gilmore, A. W., McDermott, K. B., Nelson, S. M., Dosenbach, N. U., Schlaggar, B. L., Mumford, J. A., Poldrack, R. A., Petersen, S. E. 2015; 87 (3): 657-670

    Abstract

    Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activations. Highly convergent correlation network estimates can be derived from this parcellation if sufficient data are collected-considerably more than typically acquired. Notably, within-subject correlation variability across sessions exhibited a heterogeneous distribution across the cortex concentrated in visual and somato-motor regions, distinct from the pattern of intersubject variability. Further, although the individual's systems-level organization is broadly similar to the group, it demonstrates distinct topological features. These results provide a foundation for studies of individual differences in cortical organization and function, especially for special or rare individuals. VIDEO ABSTRACT.

    View details for DOI 10.1016/j.neuron.2015.06.037

    View details for Web of Science ID 000361145000016

    View details for PubMedID 26212711

  • Orthogonalization of Regressors in fMRI Models PLOS ONE Mumford, J. A., Poline, J., Poldrack, R. A. 2015; 10 (4)

    Abstract

    The occurrence of collinearity in fMRI-based GLMs (general linear models) may reduce power or produce unreliable parameter estimates. It is commonly believed that orthogonalizing collinear regressors in the model will solve this problem, and some software packages apply automatic orthogonalization. However, the effects of orthogonalization on the interpretation of the resulting parameter estimates is widely unappreciated or misunderstood. Here we discuss the nature and causes of collinearity in fMRI models, with a focus on the appropriate uses of orthogonalization. Special attention is given to how the two popular fMRI data analysis software packages, SPM and FSL, handle orthogonalization, and pitfalls that may be encountered in their usage. Strategies are discussed for reducing collinearity in fMRI designs and addressing their effects when they occur.

    View details for DOI 10.1371/journal.pone.0126255

    View details for Web of Science ID 000353659400093

    View details for PubMedID 25919488

    View details for PubMedCentralID PMC4412813

  • If all your friends jumped off a bridge: The effect of others' actions on engagement in and recommendation of risky behaviors. Journal of experimental psychology. General Helfinstein, S. M., Mumford, J. A., Poldrack, R. A. 2015; 144 (1): 12-17

    Abstract

    There is a large gap between the types of risky behavior we recommend to others and those we engage in ourselves. In this study, we hypothesized that a source of this gap is greater reliance on information about others' behavior when deciding whether to take a risk oneself than when deciding whether to recommend it to others. To test this hypothesis, we asked participants either to report their willingness to engage in a series of risky behaviors themselves; their willingness to recommend those behaviors to a loved one; or, how good of an idea it would be for either them or a loved one to engage in the behaviors. We then asked them to evaluate those behaviors on criteria related to the expected utility of the risk (benefits, costs, and likelihood of costs), and on engagement in the activity by people they knew. We found that, after accounting for effects of perceived benefit, cost, and likelihood of cost, perceptions of others' behavior had a dramatically larger impact on participants' willingness to engage in a risk than on their willingness to recommend the risk or their prescriptive evaluation of the risk. These findings indicate that the influence of others' choices on risk-taking behavior is large, direct, cannot be explained by an economic utility model of risky decision-making, and goes against one's own better judgment. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

    View details for DOI 10.1037/xge0000043

    View details for PubMedID 25485604

  • What do differences between multi-voxel and univariate analysis mean? How subject-, voxel-, and trial-level variance impact fMRI analysis NEUROIMAGE Davis, T., LaRocque, K. F., Mumford, J. A., Norman, K. A., Wagner, A. D., Poldrack, R. A. 2014; 97: 271-283

    Abstract

    Multi-voxel pattern analysis (MVPA) has led to major changes in how fMRI data are analyzed and interpreted. Many studies now report both MVPA results and results from standard univariate voxel-wise analysis, often with the goal of drawing different conclusions from each. Because MVPA results can be sensitive to latent multidimensional representations and processes whereas univariate voxel-wise analysis cannot, one conclusion that is often drawn when MVPA and univariate results differ is that the activation patterns underlying MVPA results contain a multidimensional code. In the current study, we conducted simulations to formally test this assumption. Our findings reveal that MVPA tests are sensitive to the magnitude of voxel-level variability in the effect of a condition within subjects, even when the same linear relationship is coded in all voxels. We also find that MVPA is insensitive to subject-level variability in mean activation across an ROI, which is the primary variance component of interest in many standard univariate tests. Together, these results illustrate that differences between MVPA and univariate tests do not afford conclusions about the nature or dimensionality of the neural code. Instead, targeted tests of the informational content and/or dimensionality of activation patterns are critical for drawing strong conclusions about the representational codes that are indicated by significant MVPA results.

    View details for DOI 10.1016/j.neuroimage.2014.04.037

    View details for Web of Science ID 000337988700028

    View details for PubMedCentralID PMC4115449

  • Functional imaging of sleep vertex sharp transients CLINICAL NEUROPHYSIOLOGY Stern, J. M., Caporro, M., Haneef, Z., Yeh, H. J., Buttinelli, C., Lenartowicz, A., Mumford, J. A., Parvizi, J., Poldrack, R. A. 2011; 122 (7): 1382-1386

    Abstract

    The vertex sharp transient (VST) is an electroencephalographic (EEG) discharge that is an early marker of non-REM sleep. It has been recognized since the beginning of sleep physiology research, but its source and function remain mostly unexplained. We investigated VST generation using functional MRI (fMRI).Simultaneous EEG and fMRI were recorded from seven individuals in drowsiness and light sleep. VST occurrences on EEG were modeled with fMRI using an impulse function convolved with a hemodynamic response function to identify cerebral regions correlating to the VSTs. A resulting statistical image was thresholded at Z>2.3.Two hundred VSTs were identified. Significantly increased signal was present bilaterally in medial central, lateral precentral, posterior superior temporal, and medial occipital cortex. No regions of decreased signal were present.The regions are consistent with electrophysiologic evidence from animal models and functional imaging of human sleep, but the results are specific to VSTs. The regions principally encompass the primary sensorimotor cortical regions for vision, hearing, and touch.The results depict a network comprising the presumed VST generator and its associated regions. The associated regions functional similarity for primary sensation suggests a role for VSTs in sensory experience during sleep.

    View details for DOI 10.1016/j.clinph.2010.12.049

    View details for Web of Science ID 000291102300017

    View details for PubMedID 21310653

    View details for PubMedCentralID PMC3105179