Christine Law

All Publications

• Differential encoding of noxious heat and self-reported pain along corticospinal networks: a simultaneous spinal cord-brain fMRI study. bioRxiv : the preprint server for biology Pfyffer, D., Wang, Y., Kaptan, M., Fundaun, J., Dildine, T. C., Oliva, V., Indriolo, T., Skare, S., Sprenger, T., Lee, P. K., Truong, M., Weber, K. A., Glover, G. H., Law, C. S., Mackey, S. 2025

  Abstract

  Chronic pain poses a substantial public health burden. Elucidating how the healthy central nervous system (CNS) differentially encodes objective stimulus intensity and subjective experiences of pain perception may offer key insights into the central mechanisms contributing to chronic pain. Functional MRI (fMRI) combined with controlled noxious stimulation provides a powerful means to explore neural representations of nociception and pain perception. Here, we applied noxious heat at three intensities (46 °C, 47 °C, 48 °C, 8 trials each randomized) to the right forearm of 28 healthy women during simultaneous spinal cord-brain fMRI to investigate how distributed corticospinal activity and connectivity encode stimulus intensity and subjective pain. Activity increased with stimulus temperature across regions involved in pain processing-including somatosensory, motor, prefrontal, insular, and subcortical areas-as well as in the ipsilateral dorsal and ventral spinal cord. Spinal-brain functional connectivity was observed between the right dorsal horn and pain-related brain regions such as primary and secondary somatosensory cortex, insula, anterior cingulate cortex, thalamus, and periaqueductal gray, and was positively associated with individual pain ratings. Using representational similarity analysis (RSA), we found that multivoxel activation patterns in the brain and spinal cord, as well as corticospinal connectivity patterns, reliably tracked stimulus temperature, while only subsets of cortical regions (e.g., insula, sensorimotor, and frontal cortices) encoded subjective pain. Notably, spinal cord representations were primarily organized by stimulus temperature rather than perceived pain intensity. These findings demonstrate that simultaneous spinal cord-brain fMRI combined with multivariate modeling can identify sensory and perceptual components of nociceptive processing across the neuroaxis. Such approaches advance mechanistic understanding of pain and may inform the development of CNS-based biomarkers for chronic pain assessment and intervention.

  View details for DOI 10.1101/2025.10.24.684476

  View details for PubMedID 41280069

  View details for PubMedCentralID PMC12633297

• Mapping hand function with simultaneous brain-spinal cord functional MRI. Imaging neuroscience (Cambridge, Mass.) Oliva, V., Bédard, S., Kaptan, M., Pfyffer, D., Chy, B., Aufrichtig, S., Berhe, N., Chaudhari, A. S., Tharin, S., Hu, S. S., Ratliff, J., Smith, Z. A., Smith, A. C., Glover, G. H., Mackey, S., Law, C. S., Weber Ii, K. A. 2025; 3

  Abstract

  Hand motor control depends on intricate brain-spinal cord interactions that regulate muscle activity. Hand function can be disrupted by injury to the brain, spinal cord, and peripheral nerves leading to weakness and impaired coordination. Functional MRI (fMRI) can map motor-related neural activity and potentially characterize the mechanisms underlying hand weakness and diminished coordination. Although brain motor control has been extensively studied, spinal cord mechanisms remain less explored. Here we use simultaneous brain-spinal cord fMRI to map neural activity related to hand strength and dexterity across the central nervous system using force matching and finger tapping tasks. We performed simultaneous brain-spinal cord fMRI in 28 right-handed healthy volunteers (age: 40.0 ± 13.8 years, 14 females, 14 males) using a 3T GE scanner. Participants performed a force-matching task at 10%, 20%, and 30% of maximum voluntary contraction. For the finger tapping task, participants completed button presses for three task levels: single-digit response with the second digit only, single-digit response with all digits in a sequential order, and single-digit response with all digits in a random order. Brain and spinal cord images were processed separately and assessed both activations and deactivations. Region of interest (ROI) analyses were also conducted to explore localized changes in activation across the task levels. Both tasks elicited activation in motor and sensory regions of the brain and spinal cord, with graded responses in the left primary motor (M1), left primary sensory (S1) cortex, and right spinal cord gray matter across task levels. Deactivation of the right M1 and S1 was also present for both tasks. Deactivation of the left spinal cord gray matter that scaled with task level was seen in the force matching task. The ROI analysis findings complemented the group level activity maps. Our study provides a detailed map of brain-spinal cord interactions in hand function, revealing graded neural activation and deactivation patterns across motor and sensory regions. Right M1 deactivation is likely evidence of interhemispheric inhibition that restricts extraneous motor output during unilateral tasks. For force matching, the deactivation of the left ventral and dorsal horns of the spinal cord provides the first evidence that the inhibition of motor areas during a unilateral motor task extends to the spinal cord. Whether this inhibition results from direct descending modulation from the brain or interneuronal inhibition in the spinal cord remains to be interrogated. These findings expand our understanding of central motor control mechanisms and could inform rehabilitation strategies for individuals with motor impairments. This approach may offer a foundation for studying motor dysfunction in conditions such as stroke, spinal cord injury, and neurodegenerative diseases.

  View details for DOI 10.1162/IMAG.a.159

  View details for PubMedID 41064375

  View details for PubMedCentralID PMC12501243

• EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data. Imaging neuroscience (Cambridge, Mass.) Banerjee, R., Kaptan, M., Tinnermann, A., Khatibi, A., Dabbagh, A., Büchel, C., Kündig, C. W., Law, C. S., Pfyffer, D., Lythgoe, D. J., Tsivaka, D., Van De Ville, D., Eippert, F., Muhammad, F., Glover, G. H., David, G., Haynes, G., Haaker, J., Brooks, J. C., Finsterbusch, J., Martucci, K. T., Hemmerling, K. J., Mobarak-Abadi, M., Hoggarth, M. A., Howard, M. A., Bright, M. G., Kinany, N., Kowalczyk, O. S., Freund, P., Barry, R. L., Mackey, S., Vahdat, S., Schading, S., McMahon, S. B., Parish, T., Marchand-Pauvert, V., Chen, Y., Smith, Z. A., Weber Ii, K. A., De Leener, B., Cohen-Adad, J. 2025; 3

  Abstract

  Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.1 and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared with other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.

  View details for DOI 10.1162/IMAG.a.98

  View details for PubMedID 40937159

  View details for PubMedCentralID PMC12421696

• Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study. Imaging neuroscience (Cambridge, Mass.) Labounek, R., Bondy, M. T., Paulson, A. L., Bédard, S., Abramovic, M., Alonso-Ortiz, E., Atcheson, N. T., Barlow, L. R., Barry, R. L., Barth, M., Battiston, M., Büchel, C., Budde, M. D., Callot, V., Combes, A., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostál, M., Doyon, J., Dvorak, A. V., Eippert, F., Epperson, K. R., Epperson, K. S., Freund, P., Finsterbusch, J., Foias, A., Fratini, M., Fukunaga, I., Wheeler-Kingshott, C. A., Germani, G., Gilbert, G., Giove, F., Grussu, F., Hagiwara, A., Henry, P. G., Horák, T., Hori, M., Joers, J. M., Kamiya, K., Karbasforoushan, H., Keřkovský, M., Khatibi, A., Kim, J. W., Kinany, N., Kitzler, H., Kolind, S., Kong, Y., Kudlička, P., Kuntke, P., Kurniawan, N. D., Kusmia, S., Laganà, M. M., Laule, C., Law, C. S., Leutritz, T., Liu, Y., Llufriu, S., Mackey, S., Martin, A. R., Martinez-Heras, E., Mattera, L., O'Grady, K. P., Papinutto, N., Papp, D., Pareto, D., Parrish, T. B., Pichiecchio, A., Prados, F., Rovira, À., Ruitenberg, M. J., Samson, R. S., Savini, G., Seif, M., Seifert, A. C., Smith, A. K., Smith, S. A., Smith, Z. A., Solana, E., Suzuki, Y., Tackley, G. W., Tinnermann, A., Valošek, J., Van De Ville, D., Yiannakas, M. C., Weber Ii, K. A., Weiskopf, N., Wise, R. G., Wyss, P. O., Xu, J., Cohen-Adad, J., Lenglet, C., Nestrašil, I. 2025; 3

  Abstract

  Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e., height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1 ± 6.6 years old, 125 females). We show that body height correlates with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44 ≤ r ≤ 0.62). Intracranial volume (ICV) correlates with body height (r = 0.46) and the brain volumes and CSA-WM (0.37 ≤ r ≤ 0.77). In comparison, age correlates with cortical GM volume, precentral GM volume, and cortical thickness (-0.21 ≥ r ≥ -0.27). Body weight correlates with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20 ≥ r ≥ -0.23). Body weight further correlates with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r = -0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlates with brain volumes (0.39 ≤ r ≤ 0.64), and with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22 ≥ r ≥ -0.25). Linear mixture of age, sex, or sex and age, explained 2 ± 2%, 24 ± 10%, or 26 ± 10%, of data variance in brain volumetry and SC CSA. The amount of explained variance increased to 33 ± 11%, 41 ± 17%, or 46 ± 17%, when body height, ICV, or body height and ICV were added into the mixture model. In females, the explained variances halved suggesting another unidentified biological factor(s) determining females' central nervous system (CNS) morphology. In conclusion, body size and ICV are significant biological variables. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure; and body size and ICV should be considered as covariates in statistical analyses. Normalization of different brain regions with ICV diminishes their correlations with body size, but simultaneously amplifies ICV-related variance (r = 0.72 ± 0.07) and suppresses volume variance of the different brain regions (r = 0.12 ± 0.19) in the normalized measurements.

  View details for DOI 10.1162/imag_a_00559

  View details for PubMedID 40800833

  View details for PubMedCentralID PMC12319740

• Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study IMAGING NEUROSCIENCE Labounek, R., Bondy, M. T., Paulson, A. L., Bedard, S., Abramovic, M., Alonso-Ortiz, E., Atcheson, N. T., Barlow, L. R., Barry, R. L., Barth, M., Battiston, M., Buechel, C., Budde, M. D., Callot, V., Combes, A., De Leener, B., Descoteaux, M., de Sousa, P., Dostal, M., Doyon, J., Dvorak, A. V., Eippert, F., Epperson, K. R., Epperson, K. S., Freund, P., Finsterbusch, J., Foias, A., Fratini, M., Fukunaga, I., Wheeler-Kingshott, C., Germani, G., Gilbert, G., Giove, F., Grussu, F., Hagiwara, A., Henry, P., Horak, T., Hori, M., Joers, J. M., Kamiya, K., Karbasforoushan, H., Kerkovsky, M., Khatibi, A., Kim, J., Kinany, N., Kitzler, H., Kolind, S., Kong, Y., Kudlicka, P., Kuntke, P., Kurniawan, N. D., Kusmia, S., Lagana, M., Laule, C., Law, C. S. W., Leutritz, T., Liu, Y., Llufriu, S., Mackey, S., Martin, A. R., Martinez-Heras, E., Mattera, L., O'Grady, K. P., Papinutto, N., Papp, D., Pareto, D., Parrish, T. B., Pichiecchio, A., Prados, F., Rovira, A., Ruitenberg, M. J., Samson, R. S., Savini, G., Seif, M., Seifert, A. C., Smith, A. K., Smith, S. A., Smith, Z. A., Solana, E., Suzuki, Y., Tackley, G. W., Tinnermann, A., Valosek, J., Van De Ville, D., Yiannakas, M. C., Weber II, K. A., Weiskopf, N., Wise, R. G., Wyss, P. O., Xu, J., Cohen-Adad, J., Lenglet, C., Nestrasil, I. 2025; 3

  View details for DOI 10.1162/imag_a_00559

  View details for Web of Science ID 001524785200002

• Assessing Functional Connectivity Between Brain and Spinal Cord During Thermal Pain Kaptan, M., Pfyffer, D., Law, C. S. W., Weber, K. A., Glover, G., Mackey, S. CHURCHILL LIVINGSTONE. 2025: 110

  View details for DOI 10.1016/j.jpain.2025.105158

  View details for Web of Science ID 001504694300168

• Brain and Spinal Cord Correlates of Deficient Endogenous Pain Modulation in Fibromyalgia Identified by Corticospinal Functional Magnetic Resonance Imaging Pfyffer, D., Kaptan, M., Law, C. S. W., Weber II, K. A., Oliva, V., Bedard, S., Indriolo, T., Maronesy, T., Glover, G. H., Mackey, S. CHURCHILL LIVINGSTONE. 2025

  View details for DOI 10.1016/j.jpain.2025.105157

  View details for Web of Science ID 001504694300010

• EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data. bioRxiv : the preprint server for biology Banerjee, R., Kaptan, M., Tinnermann, A., Khatibi, A., Dabbagh, A., Kündig, C. W., Law, C. S., Pfyffer, D., Lythgoe, D. J., Tsivaka, D., Ville, D. V., Eippert, F., Muhammad, F., Glover, G. H., David, G., Haynes, G., Haaker, J., Brooks, J. C., Finsterbusch, J., Martucci, K. T., Hemmerling, K. J., Mobarak-Abadi, M., Hoggarth, M. A., Howard, M. A., Bright, M. G., Kinany, N., Kowalczyk, O. S., Freund, P., Barry, R. L., Mackey, S., Vahdat, S., Schading, S., McMahon, S. B., Parish, T., Marchand-Pauvert, V., Chen, Y., Smith, Z. A., Weber, K. A., Leener, B. D., Cohen-Adad, J. 2025

  Abstract

  Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.0, and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared to other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.

  View details for DOI 10.1101/2025.01.07.631402

  View details for PubMedID 39829895

  View details for PubMedCentralID PMC11741348

• Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study. bioRxiv : the preprint server for biology Labounek, R., Bondy, M. T., Paulson, A. L., Bédard, S., Abramovic, M., Alonso-Ortiz, E., Atcheson, N. T., Barlow, L. R., Barry, R. L., Barth, M., Battiston, M., Büchel, C., Budde, M. D., Callot, V., Combes, A., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostál, M., Doyon, J., Dvorak, A. V., Eippert, F., Epperson, K. R., Epperson, K. S., Freund, P., Finsterbusch, J., Foias, A., Fratini, M., Fukunaga, I., Gandini Wheeler-Kingshott, C. A., Germani, G., Gilbert, G., Giove, F., Grussu, F., Hagiwara, A., Henry, P. G., Horák, T., Hori, M., Joers, J. M., Kamiya, K., Karbasforoushan, H., Keřkovský, M., Khatibi, A., Kim, J. W., Kinany, N., Kitzler, H., Kolind, S., Kong, Y., Kudlička, P., Kuntke, P., Kurniawan, N. D., Kusmia, S., Laganà, M. M., Laule, C., Law, C. S., Leutritz, T., Liu, Y., Llufriu, S., Mackey, S., Martin, A. R., Martinez-Heras, E., Mattera, L., O'Grady, K. P., Papinutto, N., Papp, D., Pareto, D., Parrish, T. B., Pichiecchio, A., Prados, F., Rovira, À., Ruitenberg, M. J., Samson, R. S., Savini, G., Seif, M., Seifert, A. C., Smith, A. K., Smith, S. A., Smith, Z. A., Solana, E., Suzuki, Y., Tackley, G. W., Tinnermann, A., Valošek, J., Van De Ville, D., Yiannakas, M. C., Weber, K. A., Weiskopf, N., Wise, R. G., Wyss, P. O., Xu, J., Cohen-Adad, J., Lenglet, C., Nestrašil, I. 2024

  Abstract

  Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

  View details for DOI 10.1101/2024.04.29.591421

  View details for PubMedID 38746371

  View details for PubMedCentralID PMC11092490

• Exploring Neuronal Underpinnings of Emotional Regulation of Pain in Fibromyalgia Patients Kaptan, M., Pfyffer, D., Law, C. S. W., Oliva, V., Weber, K., Glover, G., Mackey, S. CHURCHILL LIVINGSTONE. 2024: 47

  View details for Web of Science ID 001282167300210

• Imaging Corticospinal Correlates of Aberrant Pain Processing and Modulation in Fibromyalgia Using Combined Brain-Spinal Cord Functional Magnetic Resonance Imaging Pfyffer, D., Kaptan, M., Law, C. S. W., Weber, K. A., Oliva, V., Bedard, S., Maronesy, T., Glover, G. H., Mackey, S. CHURCHILL LIVINGSTONE. 2024: 47-48

  View details for Web of Science ID 001282167300214

• Investigating the Associations between Lumbar Paraspinal Muscle Health and Age, BMI, Sex, Physical Activity and Back Pain using an Automated Computer-Vision Model: A UK Biobank Study. The spine journal : official journal of the North American Spine Society Wesselink, E. O., Pool-Goudzwaard, A., De Leener, B., Law, C., Fenyo, M. B., Ello, G. M., Coppieters, M. W., Elliott, J. M., Mackey, S., Weber, K. A. 2024

  Abstract

  BACKGROUND CONTEXT: The role of lumbar paraspinal muscle health in back pain (BP) is not straightforward. Challenges in this field have included the lack of tools and large, heterogenous datasets to interrogate the association between muscle health and BP. Computer-vision models have been transformative in this space, enabling the automated quantification of muscle health and the processing of large datasets.PURPOSE: To investigate the associations between lumbar paraspinal muscle health and age, sex, BMI, physical activity, and BP in a large, heterogenous dataset using an automated computer-vision model.DESIGN: Cross-sectional Study PATIENT SAMPLE: Participants from the UK Biobank with abdominal Dixon fat-water MRI (N=9,564) were included (41.8% women; mean (SD) 63.5 (7.6) years; BMI: 26.4 (4.1) kg/m2) of whom 6,953 reported no pain, 930 acute BP, and 1,681 chronic BP.OUTCOME MEASURES: Intramuscular fat (IMF) and average cross-sectional area (aCSA) were automatically derived using a computer-vision model for the left and right lumbar multifidus (LM), erector spinae (ES), and psoas major (PM) from the L1 to L5 vertebral levels.METHODS: Two-tailed partial Pearson correlations were generated for each muscle to assess the relationships between the muscle measures (IMF and aCSA) and age (controlling for BMI, sex, and physical activity), BMI (controlling for age, sex, and physical activity), and physical activity (controlling for age, sex, and BMI). One-way ANCOVA was used to identify sex differences in IMF and aCSA for each muscle while controlling for age, BMI, and physical activity. Similarly, one-way ANCOVA was used to identify between-group differences (no pain, acute BP, and chronic BP) for each muscle and along the superior-inferior expanse of the lumbar spine while controlling for age, BMI, sex, and physical activity (alpha=0.05).RESULTS: Females had higher IMF (LM mean difference (MD)=11.1%, ES MD=10.2%, PM MD=0.3%, p<0.001) and lower aCSA (LM MD=47.6 mm2, ES MD=350.0 mm2, PM MD=321.5 mm2, p<0.001) for all muscles. Higher age was associated with higher IMF and lower aCSA for all muscles (r≥0.232, p<0.001) except for LM and aCSA (r≤0.013, p≥0.267). Higher BMI was associated with higher IMF and aCSA for all muscles (r≥0.174, p<0.001). Higher physical activity was associated with lower IMF and higher aCSA for all muscles (r≥0.036, p≤0.002) except for LM and aCSA (r≤0.010, p≥0.405). People with chronic BP had higher IMF and lower aCSA than people with no pain (IMF MD≤1.6%, aCSA MD≤27.4 mm2, p<0.001) and higher IMF compared to acute BP (IMF MD≤1.1%, p<0.001). The differences between people with BP and people with no pain were not spatially localized to the inferior lumbar levels but broadly distributed across the lumbar spine.CONCLUSIONS: Paraspinal muscle health is associated with age, BMI, sex, and physical activity with the exception of the association between LM aCSA and age and physical activity. People with BP (chronic > acute) have higher IMF and lower aCSA than people reporting no pain. The differences were not localized but broadly distributed across the lumbar spine. When interpreting measures of paraspinal muscle health in the research or clinical setting, the associations with age, BMI, sex, and physical activity should be considered.

  View details for DOI 10.1016/j.spinee.2024.02.013

  View details for PubMedID 38417587

• Recent developments and future avenues for human corticospinal neuroimaging. Frontiers in human neuroscience Kaptan, M., Pfyffer, D., Konstantopoulos, C. G., Law, C. S., Weber Ii, K. A., Glover, G. H., Mackey, S. 2024; 18: 1339881

  Abstract

  Non-invasive neuroimaging serves as a valuable tool for investigating the mechanisms within the central nervous system (CNS) related to somatosensory and motor processing, emotions, memory, cognition, and other functions. Despite the extensive use of brain imaging, spinal cord imaging has received relatively less attention, regardless of its potential to study peripheral communications with the brain and the descending corticospinal systems. To comprehensively understand the neural mechanisms underlying human sensory and motor functions, particularly in pathological conditions, simultaneous examination of neuronal activity in both the brain and spinal cord becomes imperative. Although technically demanding in terms of data acquisition and analysis, a growing but limited number of studies have successfully utilized specialized acquisition protocols for corticospinal imaging. These studies have effectively assessed sensorimotor, autonomic, and interneuronal signaling within the spinal cord, revealing interactions with cortical processes in the brain. In this mini-review, we aim to examine the expanding body of literature that employs cutting-edge corticospinal imaging to investigate the flow of sensorimotor information between the brain and spinal cord. Additionally, we will provide a concise overview of recent advancements in functional magnetic resonance imaging (fMRI) techniques. Furthermore, we will discuss potential future perspectives aimed at enhancing our comprehension of large-scale neuronal networks in the CNS and their disruptions in clinical disorders. This collective knowledge will aid in refining combined corticospinal fMRI methodologies, leading to the development of clinically relevant biomarkers for conditions affecting sensorimotor processing in the CNS.

  View details for DOI 10.3389/fnhum.2024.1339881

  View details for PubMedID 38332933

  View details for PubMedCentralID PMC10850311

• AMMA: Adaptive Multimodal Assistants Through Automated State Tracking and User Model-Directed Guidance Planning Yang, J., Qiu, L., Corona-Moreno, E., Shi, L., Bui, H., Lam, M. S., Landay, J. A., IEEE Comp Soc IEEE COMPUTER SOC. 2024: 892-902

  View details for DOI 10.1109/VR58804.2024.00108

  View details for Web of Science ID 001212781000083

• Exploring Corticospinal Functional Connectome Using Resting-State Functional Magnetic Resonance Imaging Kaptan, M., Law, C. S. W., Weber, K., Pfyffer, D., Zhang, X., Maronesy, T., Glover, G., Mackey, S. CHURCHILL LIVINGSTONE. 2023: 17-18

  View details for Web of Science ID 000995432100047

• Imaging Noxious Thermal Intensity Encoding Along The Neuraxis Using Simultaneous Spinal Cord-Brain Functional Magnetic Resonance Imaging Pfyffer, D., Law, C. S. W., Weber, K. A., Kaptan, M., Maronesy, T., Glover, G. H., Mackey, S. CHURCHILL LIVINGSTONE. 2023: 76

  View details for Web of Science ID 000995432100203

• Self-reported physical function is strongly related to pain behavior and pain interference and weakly related to physical capacity in people with chronic low back pain. Musculoskeletal science & practice Karayannis, N. V., Smuck, M., Law, C., Mackey, S. C., Gross, J. J., Darnall, B. D., Hush, J. 2023: 102721

  Abstract

  BACKGROUND: Inclusion of self-reported and capacity-based measures may help to further elucidate the interactive link between how people think and move.OBJECTIVE: To characterize the relationship between self-reported factors of physical function and pain with objective physical capacity measures.DESIGN: Cross-sectional study of 328 adults with chronic low back pain (CLBP).METHOD: Spearman correlations assessed the relationship between pairs of measures. Multiple linear regression models assessed the association between self-reported measures of physical function and the grouping of physical capacity measures. Self-reported measures included Roland Morris Disability Questionnaire (RMDQ), PROMIS Physical Function, Pain Behavior, and Pain Interference; Fear-Avoidance Beliefs Questionnaire (FABQ), Pain Catastrophizing Scale (PCS), and Chronic Pain Acceptance Questionnaire (CPAQ). Capacity measures included walking speed and endurance, lower extremity functional strength, lumbopelvic range of motion, and trunk endurance.RESULTS: PROMIS Physical Function was directly and weakly correlated with walking speed (rho=0.26, 2-min walk) and inversely and weakly correlated with lower extremity strength (rho=-0.29, 5x sit-to-stand). RMDQ was not correlated with any of the capacity-based measures. PROMIS Physical Function was inversely and moderately correlated with Pain Interference (rho=-0.48) and Pain Behavior (rho=-0.43), PCS (rho=-0.36), and FABQ (rho=-0.31). The RMDQ was strongly correlated with PROMIS Physical Function (rho=-0.56), Pain Behavior (rho=0.51) and Pain Interference (rho=0.49); and moderately correlated with PCS (rho=0.37) and FABQ (rho=0.33). PROMIS Physical Function and RMDQ were not correlated with CPAQ. Lower scores on PROMIS Physical Function were weakly associated with lower measures of lower extremity strength (-0.30, 95% CI: -0.51 to -0.09, p=0.005). Higher scores on RMDQ were also weakly associated with lower measures of lower extremity strength (0.26, 95% CI: 0.11 to 0.41, p=0.001).CONCLUSIONS: A strong association emerged between self-reported limitations in physical function, pain behavior, and pain interference. A weak association emerged between self-reported physical function and lower extremity strength.

  View details for DOI 10.1016/j.msksp.2023.102721

  View details for PubMedID 36759316

• Confounds in neuroimaging: A clear case of sex as a confound in brain-based prediction. Frontiers in neurology Weber, K. A., Teplin, Z. M., Wager, T. D., Law, C. S., Prabhakar, N. K., Ashar, Y. K., Gilam, G., Banerjee, S., Delp, S. L., Glover, G. H., Hastie, T. J., Mackey, S. 2022; 13: 960760

  Abstract

  Muscle weakness is common in many neurological, neuromuscular, and musculoskeletal conditions. Muscle size only partially explains muscle strength as adaptions within the nervous system also contribute to strength. Brain-based biomarkers of neuromuscular function could provide diagnostic, prognostic, and predictive value in treating these disorders. Therefore, we sought to characterize and quantify the brain's contribution to strength by developing multimodal MRI pipelines to predict grip strength. However, the prediction of strength was not straightforward, and we present a case of sex being a clear confound in brain decoding analyses. While each MRI modality-structural MRI (i.e., gray matter morphometry), diffusion MRI (i.e., white matter fractional anisotropy), resting state functional MRI (i.e., functional connectivity), and task-evoked functional MRI (i.e., left or right hand motor task activation)-and a multimodal prediction pipeline demonstrated significant predictive power for strength (R 2 = 0.108-0.536, p ≤ 0.001), after correcting for sex, the predictive power was substantially reduced (R 2 = -0.038-0.075). Next, we flipped the analysis and demonstrated that each MRI modality and a multimodal prediction pipeline could significantly predict sex (accuracy = 68.0%-93.3%, AUC = 0.780-0.982, p < 0.001). However, correcting the brain features for strength reduced the accuracy for predicting sex (accuracy = 57.3%-69.3%, AUC = 0.615-0.780). Here we demonstrate the effects of sex-correlated confounds in brain-based predictive models across multiple brain MRI modalities for both regression and classification models. We discuss implications of confounds in predictive modeling and the development of brain-based MRI biomarkers, as well as possible strategies to overcome these barriers.

  View details for DOI 10.3389/fneur.2022.960760

  View details for PubMedID 36601297

  View details for PubMedCentralID PMC9806266

• Mindfulness-Based Stress Reduction, Cognitive Behavioral Therapy, and Acupuncture in Chronic Low Back Pain: Protocol for Two Linked Randomized Controlled Trials. JMIR research protocols Mackey, S., Gilam, G., Darnall, B., Goldin, P., Kong, J., Law, C., Heirich, M., Karayannis, N., Kao, M., Tian, L., Manber, R., Gross, J. 2022; 11 (9): e37823

  Abstract

  BACKGROUND: Nonpharmacologic mind-body therapies have demonstrated efficacy in low back pain. However, the mechanisms underlying these therapies remain to be fully elucidated.OBJECTIVE: In response to these knowledge gaps, the Stanford Center for Low Back Pain-a collaborative, National Institutes of Health P01-funded, multidisciplinary research center-was established to investigate the common and distinct biobehavioral mechanisms of three mind-body therapies for chronic low back pain: cognitive behavioral therapy (CBT) that is used to treat pain, mindfulness-based stress reduction (MBSR), and electroacupuncture. Here, we describe the design and implementation of the center structure and the associated randomized controlled trials for characterizing the mechanisms of chronic low back pain treatments.METHODS: The multidisciplinary center is running two randomized controlled trials that share common resources for recruitment, enrollment, study execution, and data acquisition. We expect to recruit over 300 chronic low back pain participants across two projects and across different treatment arms within each project. The first project will examine pain-CBT compared with MBSR and a wait-list control group. The second project will examine real versus sham electroacupuncture. We will use behavioral, psychophysical, physical measure, and neuroimaging techniques to characterize the central pain modulatory and emotion regulatory systems in chronic low back pain at baseline and longitudinally. We will characterize how these interventions impact these systems, characterize the longitudinal treatment effects, and identify predictors of treatment efficacy.RESULTS: Participant recruitment began on March 17, 2015, and will end in March 2023. Recruitment was halted in March 2020 due to COVID-19 and resumed in December 2021.CONCLUSIONS: This center uses a comprehensive approach to study chronic low back pain. Findings are expected to significantly advance our understanding in (1) the baseline and longitudinal mechanisms of chronic low back pain, (2) the common and distinctive mechanisms of three mind-body therapies, and (3) predictors of treatment response, thereby informing future delivery of nonpharmacologic chronic low back pain treatments.TRIAL REGISTRATION: ClinicalTrials.gov NCT02503475; https://clinicaltrials.gov/ct2/show/NCT02503475.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37823.

  View details for DOI 10.2196/37823

  View details for PubMedID 36166279

• Response to Scholkmann Commentary: "Effect of Wearing a Face Mask on fMRI BOLD Contrast". NeuroImage Law, C. S., Lan, P. S., Glover, G. H. 2021: 118773

  View details for DOI 10.1016/j.neuroimage.2021.118773

  View details for PubMedID 34864152

• Prediction of Cognitive Function with Multimodal Brain MRI Weber, K., Wager, T. D., Rosen, A., Ashar, Y. K., Law, C. S., Gilam, G., Upadhyayula, P. A., Zhu, S., Banerjee, S., Glover, G. H., Hastie, T. J., Mackey, S. WILEY. 2021: S42

  View details for Web of Science ID 000704705300063

• Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers. Scientific data Cohen-Adad, J., Alonso-Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., Barry, R. L., Barth, M., Battiston, M., Buchel, C., Budde, M., Callot, V., Combes, A. J., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostal, M., Doyon, J., Dvorak, A., Eippert, F., Epperson, K. R., Epperson, K. S., Freund, P., Finsterbusch, J., Foias, A., Fratini, M., Fukunaga, I., Gandini Wheeler-Kingshott, C. A., Germani, G., Gilbert, G., Giove, F., Gros, C., Grussu, F., Hagiwara, A., Henry, P., Horak, T., Hori, M., Joers, J., Kamiya, K., Karbasforoushan, H., Kerkovsky, M., Khatibi, A., Kim, J., Kinany, N., Kitzler, H. H., Kolind, S., Kong, Y., Kudlicka, P., Kuntke, P., Kurniawan, N. D., Kusmia, S., Labounek, R., Lagana, M. M., Laule, C., Law, C. S., Lenglet, C., Leutritz, T., Liu, Y., Llufriu, S., Mackey, S., Martinez-Heras, E., Mattera, L., Nestrasil, I., O'Grady, K. P., Papinutto, N., Papp, D., Pareto, D., Parrish, T. B., Pichiecchio, A., Prados, F., Rovira, A., Ruitenberg, M. J., Samson, R. S., Savini, G., Seif, M., Seifert, A. C., Smith, A. K., Smith, S. A., Smith, Z. A., Solana, E., Suzuki, Y., Tackley, G., Tinnermann, A., Valosek, J., Van De Ville, D., Yiannakas, M. C., Weber Ii, K. A., Weiskopf, N., Wise, R. G., Wyss, P. O., Xu, J. 2021; 8 (1): 242

  View details for DOI 10.1038/s41597-021-01026-2

  View details for PubMedID 34508107

• THE TEMPORAL RELATIONSHIP BETWEEN NEGATIVE AFFECT AND SLEEP BRUXISM IN PATIENTS WITH CHRONIC BACK PAIN Hettie, G., You, D. S., Ziadni, M., Kong, J., Law, C., Gross, J., Manber, R., Darnall, B. D., Mackey, S. OXFORD UNIV PRESS INC. 2021: S478

  View details for Web of Science ID 000648922701161

• Effect of Wearing a Face Mask on fMRI BOLD Contrast. NeuroImage Law, C. S., Lan, P. S., Glover, G. H. 2021: 117752

  Abstract

  International spread of the coronavirus SARS-CoV-2 has prompted many MRI scanning facilities to require scan subjects to wear a facial covering ("mask") during scanning as a precaution against transmission of the virus. Because wearing a mask mixes expired air with the subject's inspired air stream, the concentration of inspired carbon dioxide [CO2] is elevated, resulting in mild hypercapnia. Changes in the inspired gas mixture have been demonstrated to alter R2*-weighted Blood Oxygen Dependent (BOLD) contrast. In this study, we investigate a potential for face masking to alter BOLD contrast during a sensory-motor task designed to activate visual, auditory, and sensorimotor cortices in 8 subjects. We utilize a nasal cannula to supply air to the subject wearing a surgical mask in on-off blocks of 90s to displace expired CO2, while the subject performs the sensory-motor task. While only a small fraction (2.5%) of the sensory-motor task activation is related to nasal air modulation, a 30.0% change in gray matter BOLD signal baseline is found due to air modulation. Repeating the scan with mask removed produces a small subject-specific bias in BOLD baseline signal from nasal air supply, which may be due to cognitive influence of airflow or cannula-induced hypoxia. Measurements with capnography demonstrate wearing a mask induces an average increase in ETCO2 of 7.4%. Altogether, these results demonstrate that wearing a face mask during gradient-echo fMRI can alter BOLD baseline signal but minimally affects task activation.

  View details for DOI 10.1016/j.neuroimage.2021.117752

  View details for PubMedID 33460795

• Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers. Scientific data Cohen-Adad, J., Alonso-Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., Barry, R. L., Barth, M., Battiston, M., Büchel, C., Budde, M., Callot, V., Combes, A. J., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostál, M., Doyon, J., Dvorak, A., Eippert, F., Epperson, K. R., Epperson, K. S., Freund, P., Finsterbusch, J., Foias, A., Fratini, M., Fukunaga, I., Gandini Wheeler-Kingshott, C. A., Germani, G., Gilbert, G., Giove, F., Gros, C., Grussu, F., Hagiwara, A., Henry, P. G., Horák, T., Hori, M., Joers, J., Kamiya, K., Karbasforoushan, H., Keřkovský, M., Khatibi, A., Kim, J. W., Kinany, N., Kitzler, H. H., Kolind, S., Kong, Y., Kudlička, P., Kuntke, P., Kurniawan, N. D., Kusmia, S., Labounek, R., Laganà, M. M., Laule, C., Law, C. S., Lenglet, C., Leutritz, T., Liu, Y., Llufriu, S., Mackey, S., Martinez-Heras, E., Mattera, L., Nestrasil, I., O'Grady, K. P., Papinutto, N., Papp, D., Pareto, D., Parrish, T. B., Pichiecchio, A., Prados, F., Rovira, À., Ruitenberg, M. J., Samson, R. S., Savini, G., Seif, M., Seifert, A. C., Smith, A. K., Smith, S. A., Smith, Z. A., Solana, E., Suzuki, Y., Tackley, G., Tinnermann, A., Valošek, J., Van De Ville, D., Yiannakas, M. C., Weber Ii, K. A., Weiskopf, N., Wise, R. G., Wyss, P. O., Xu, J. 2021; 8 (1): 219

  Abstract

  In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/ . The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.

  View details for DOI 10.1038/s41597-021-00941-8

  View details for PubMedID 34400655

• Quantification of cerebral blood volume changes caused by visual stimulation at 3 T using DANTE-prepared dual-echo EPI. Magnetic resonance in medicine Li, L., Law, C., Marrett, S., Chai, Y., Huber, L., Jezzard, P., Bandettini, P. 2021

  Abstract

  We investigate the influence of moving blood-attenuation effects when using "delay alternating with nutation for tailored excitation" (DANTE) pulses in conjunction with blood oxygen level dependent (BOLD) of functional MRI (fMRI) at 3 T. Based on the effects of including DANTE pulses, we propose quantification of cerebral blood volume (CBV) changes following functional stimulation.Eighteen volunteers in total underwent fMRI scans at 3 T. Seven volunteers were scanned to investigate the effects of DANTE pulses on the fMRI signal. CBV changes in response to visual stimulation were quantified in 11 volunteers using a DANTE-prepared dual-echo EPI sequence.The inflow effects from flowing blood in arteries and draining vein effects from flowing blood in large veins can be suppressed by use of a DANTE preparation module. Using DANTE-prepared dual-echo EPI, we quantitatively measured intravascular-weighted microvascular CBV changes of 25.4%, 29.8%, and 32.6% evoked by 1, 5, and 10 Hz visual stimulation, respectively. The extravascular fraction (∆S/S)extra at TE = 30 ms in total BOLD signal was determined to be 64.8 ± 3.4%, which is in line with previous extravascular component estimation at 3 T. Results show that the microvascular CBV changes are linearly dependent on total BOLD changes at TE = 30 ms with a slope of 0.113, and this relation is independent of stimulation frequency and subject.The DANTE preparation pulses can be incorporated into a standard EPI fMRI sequence for the purpose of minimizing inflow effects and reducing draining veins effects in large vessels. Additionally, the DANTE-prepared dual-echo EPI sequence is a promising fast imaging tool for quantification of intravascular-weighted CBV change in the microvascular space at 3 T.

  View details for DOI 10.1002/mrm.29099

  View details for PubMedID 34817081

• Generic acquisition protocol for quantitative MRI of the spinal cord. Nature protocols Cohen-Adad, J., Alonso-Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., Barry, R. L., Barth, M., Battiston, M., Büchel, C., Budde, M., Callot, V., Combes, A. J., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostál, M., Doyon, J., Dvorak, A., Eippert, F., Epperson, K. R., Epperson, K. S., Freund, P., Finsterbusch, J., Foias, A., Fratini, M., Fukunaga, I., Wheeler-Kingshott, C. A., Germani, G., Gilbert, G., Giove, F., Gros, C., Grussu, F., Hagiwara, A., Henry, P. G., Horák, T., Hori, M., Joers, J., Kamiya, K., Karbasforoushan, H., Keřkovský, M., Khatibi, A., Kim, J. W., Kinany, N., Kitzler, H., Kolind, S., Kong, Y., Kudlička, P., Kuntke, P., Kurniawan, N. D., Kusmia, S., Labounek, R., Laganà, M. M., Laule, C., Law, C. S., Lenglet, C., Leutritz, T., Liu, Y., Llufriu, S., Mackey, S., Martinez-Heras, E., Mattera, L., Nestrasil, I., O'Grady, K. P., Papinutto, N., Papp, D., Pareto, D., Parrish, T. B., Pichiecchio, A., Prados, F., Rovira, À., Ruitenberg, M. J., Samson, R. S., Savini, G., Seif, M., Seifert, A. C., Smith, A. K., Smith, S. A., Smith, Z. A., Solana, E., Suzuki, Y., Tackley, G., Tinnermann, A., Valošek, J., Van De Ville, D., Yiannakas, M. C., Weber, K. A., Weiskopf, N., Wise, R. G., Wyss, P. O., Xu, J. 2021

  Abstract

  Quantitative spinal cord (SC) magnetic resonance imaging (MRI) presents many challenges, including a lack of standardized imaging protocols. Here we present a prospectively harmonized quantitative MRI protocol, which we refer to as the spine generic protocol, for users of 3T MRI systems from the three main manufacturers: GE, Philips and Siemens. The protocol provides guidance for assessing SC macrostructural and microstructural integrity: T1-weighted and T2-weighted imaging for SC cross-sectional area computation, multi-echo gradient echo for gray matter cross-sectional area, and magnetization transfer and diffusion weighted imaging for assessing white matter microstructure. In a companion paper from the same authors, the spine generic protocol was used to acquire data across 42 centers in 260 healthy subjects. The key details of the spine generic protocol are also available in an open-access document that can be found at https://github.com/spine-generic/protocols . The protocol will serve as a starting point for researchers and clinicians implementing new SC imaging initiatives so that, in the future, inclusion of the SC in neuroimaging protocols will be more common. The protocol could be implemented by any trained MR technician or by a researcher/clinician familiar with MRI acquisition.

  View details for DOI 10.1038/s41596-021-00588-0

  View details for PubMedID 34400839

• Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers. Scientific data Cohen-Adad, J., Alonso-Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., Barry, R. L., Barth, M., Battiston, M., Büchel, C., Budde, M., Callot, V., Combes, A. J., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostál, M., Doyon, J., Dvorak, A., Eippert, F., Epperson, K. R., Epperson, K. S., Freund, P., Finsterbusch, J., Foias, A., Fratini, M., Fukunaga, I., Gandini Wheeler-Kingshott, C. A., Germani, G., Gilbert, G., Giove, F., Gros, C., Grussu, F., Hagiwara, A., Henry, P. G., Horák, T., Hori, M., Joers, J., Kamiya, K., Karbasforoushan, H., Keřkovský, M., Khatibi, A., Kim, J. W., Kinany, N., Kitzler, H. H., Kolind, S., Kong, Y., Kudlička, P., Kuntke, P., Kurniawan, N. D., Kusmia, S., Labounek, R., Laganà, M. M., Laule, C., Law, C. S., Lenglet, C., Leutritz, T., Liu, Y., Llufriu, S., Mackey, S., Martinez-Heras, E., Mattera, L., Nestrasil, I., O'Grady, K. P., Papinutto, N., Papp, D., Pareto, D., Parrish, T. B., Pichiecchio, A., Prados, F., Rovira, À., Ruitenberg, M. J., Samson, R. S., Savini, G., Seif, M., Seifert, A. C., Smith, A. K., Smith, S. A., Smith, Z. A., Solana, E., Suzuki, Y., Tackley, G., Tinnermann, A., Valošek, J., Van De Ville, D., Yiannakas, M. C., Weber Ii, K. A., Weiskopf, N., Wise, R. G., Wyss, P. O., Xu, J. 2021; 8 (1): 251

  View details for DOI 10.1038/s41597-021-01044-0

  View details for PubMedID 34556662

• Association between temporal summation and conditioned pain modulation in chronic low back pain: baseline results from 2 clinical trials. Pain reports Kong, J. T., You, D. S., Law, C. S., Darnall, B. D., Gross, J. J., Manber, R., Mackey, S. 2021; 6 (4): e975

  Abstract

  Temporal summation (TS) and conditioned pain modulation (CPM) represent different aspects of central pain processing. Their relationship and differential performance within distinct body locations are not well understood.To examine the association between TS and CPM in chronic low back pain and the influence of testing location on this relationship.We analyzed baseline data from 2 clinical trials on participants with chronic low back pain (n = 264; 47.3% female; mean age = 41 years, SD = 12; mean pain = 5.3/10, SD = 1.4). Measures used included questionnaires assessing pain and negative affect, phasic thermal TS at the hand (thenar) and the lower back (lumbar), followed by CPM that included a thermal testing stimulus (Heat-6, the temperature where pain rating is 6/10) and a cold-pressor conditioning stimulus. Nonparametric, proportional odds logistic regression was used to model thenar, and separately, lumbar TS, using CPM, Heat-6, negative affect, and demographics.Our models revealed a small association (βs = 0.17, P = 0.01) between reduced CPM and heightened TS at both testing sites, regardless of demographics or negative affect.Results suggest a modest association between TS and CPM, irrespective of anatomical testing location, demographics, and negative affect. These findings will help improve the methodology and interpretation of TS and CPM measurement in clinical pain populations.

  View details for DOI 10.1097/PR9.0000000000000975

  View details for PubMedID 34901679

  View details for PubMedCentralID PMC8660006

• Brain Strength: Multi-Modal Brain MRI Predicts Grip Strength Weber, K. A., Wager, T. D., Upadhyayula, P. A., Law, C. S., Ashar, Y. K., Prabhakar, N. K., Zhu, S., Gilam, G., Banerjee, S., Delp, S. L., Glover, G. H., Hastie, T. J., Mackey, S. WILEY. 2020: S223–S224

  View details for Web of Science ID 000572509100411

• Assessing the Spatial Distribution of Cervical Spinal Cord Activity during Tactile Stimulation of the Upper Extremity in Humans with Functional Magnetic Resonance Imaging. NeuroImage Weber, K. A., Chen, Y., Paliwal, M., Law, C. S., Hopkins, B. S., Mackey, S., Dhaher, Y., Parrish, T. B., Smith, Z. A. 2020: 116905

  Abstract

  Dermatomal maps are a mainstay of clinical practice and provide information on the spatial distribution of the cutaneous innervation of spinal nerves. Dermatomal deficits can help isolate the level of spinal nerve root involvement in spinal conditions and guide clinicians in diagnosis and treatment. Dermatomal maps, however, have limitations, and the spatial distribution of spinal cord sensory activity in humans remains to be quantitatively assessed. Here we used spinal cord functional MRI to map and quantitatively compare the spatial distribution of sensory spinal cord activity during tactile stimulation of the left and right lateral shoulders (i.e. C5 dermatome) and dorsal third digits of the hands (i.e., C7 dermatome) in healthy humans (n = 24, age = 36.0 ± 11.8 years). Based on the central sites for processing of innocuous tactile sensory information, we hypothesized that the activity would be localized more to the ipsilateral dorsal spinal cord with the lateral shoulder stimulation activity being localized more superiorly than the dorsal third digit. The findings demonstrate lateralization of the activity with the left- and right-sided stimuli having more activation in the ipsilateral hemicord. Contradictory to our hypotheses, the activity for both stimulation sites was spread across the dorsal and ventral hemicords and did not demonstrate a clear superior-inferior localization. Instead, the activity for both stimuli had a broader than expected distribution, extending across the C5, C6, and C7 spinal cord segments. We highlight the complexity of the human spinal cord neuroanatomy and several sources of variability that may explain the observed patterns of activity. While the findings were not completely consistent with our a priori hypotheses, this study provides a foundation for continued work and is an important step towards developing normative quantitative spinal cord measures of sensory function, which may become useful objective MRI-based biomarkers of neurological injury and improve the management of spinal disorders.

  View details for DOI 10.1016/j.neuroimage.2020.116905

  View details for PubMedID 32387628

• Resting State Functional Connectivity Machine Learning Classification of Chronic Back Pain Weber, K. A., Law, C. S., Asher, Y. K., Martucci, K. T., Gilam, G., Lewis, B., Narayan, S., Hastie, T., Wager, T. D., Mackey, S. WILEY. 2019: S266

  View details for Web of Science ID 000488891800418

• Dynamic per slice shimming for simultaneous brain and spinal cord fMRI MAGNETIC RESONANCE IN MEDICINE Islam, H., Law, C. S. W., Weber, K. A., Mackey, S. C., Glover, G. H. 2019; 81 (2): 825–38

  View details for DOI 10.1002/mrm.27388

  View details for Web of Science ID 000462086300010

• Central mechanisms of real and sham electroacupuncture in the treatment of chronic low back pain: study protocol for a randomized, placebo-controlled clinical trial. Trials Kong, J., MacIsaac, B., Cogan, R., Ng, A., Law, C. S., Helms, J., Schnyer, R., Karayannis, N. V., Kao, M., Tian, L., Darnall, B. D., Gross, J. J., Mackey, S., Manber, R. 2018; 19 (1): 685

  Abstract

  BACKGROUND: Chronic low back pain (CLBP) is the most common chronic pain condition and is often resistant to conventional treatments. Acupuncture is a popular alternative for treating CLBP but its mechanisms of action remain poorly understood. Evidence suggests that pain regulatory mechanisms (particularly the ascending and secondarily the descending pain modulatory pathways) and psychological mechanisms (e.g., expectations, pain catastrophizing and self-efficacy) may be involved in the pathogenesis of CLBP and its response to treatments. We will examine these mechanisms in the treatment of CLBP by electroacupuncture (EA).METHODS: We present the aims and methods of a placebo-controlled, participant-blinded and assessor-blinded mechanistic study. Adult patients with CLBP will be randomized to receiving 16 sessions of real (active) or sham (placebo) EA over the course of 8weeks. The primary pain regulatory measure for which the study was powered is temporal summation (TS), which approximates ascending pain facilitation. Conditioned pain modulation (CPM), representing a descending pain modulatory pathway, will be our secondary pain regulatory measure. The primary psychological measure is expectations of benefit, and the secondary psychological measures are pain catastrophizing and self-efficacy in managing pain. Main clinical outcomes are back pain bothersomeness on a 0-100 visual analog scale (primary), Roland Morris Disability Questionnaire (secondary), and relevant items from the National Institutes of Health (NIH) Patient-Reported Outcome Measures Information System (secondary). We hypothesize that compared to sham, real EA will lead to greater reduction in TS after 8 treatment sessions (4weeks); and that reduction in TS (and secondarily, increase in CPM) after 8 treatment sessions will mediate reduction in back pain bothersomeness from baseline to week 10 (clinical response) to EA. We also hypothesize that the three psychological factors are moderators of clinical response. With 100 treatment completers, the study is designed to have 80% power to detect a medium-sized between-group effect (d=0.5) on temporal summation.DISCUSSION: To the best of our knowledge, this is the first appropriately powered, placebo-controlled clinical trial evaluating mechanisms of EA in the treatment of CLBP.TRIAL REGISTRATION: ClinicalTrials.gov, NCT02503475 . Registered on 15 July 15 2015. Retrospectively registered.

  View details for PubMedID 30541586

• Central mechanisms of real and sham electroacupuncture in the treatment of chronic low back pain: study protocol for a randomized, placebo-controlled clinical trial TRIALS Kong, J., MacIsaac, B., Cogan, R., Ng, A., Law, C., Helms, J., Schnyer, R., Karayannis, N., Kao, M., Tian, L., Darnall, B. D., Gross, J. J., Mackey, S., Manber, R. 2018; 19

  View details for DOI 10.1186/s13063-018-3044-2

  View details for Web of Science ID 000453069900001

• Technical note: can resting state functional MRI assist in routine clinical diagnosis? BJR case reports Harman, P., Law, C., Pardhan, S., Lin, Z. H., Johnson, M., Walter, S., Fassbender, K., Aspinall, R., Grunwald, I. Q. 2018; 4 (4): 20180030

  Abstract

  Despite some differences in clinical presentation, it is often difficult to differentiate between dementia with Lewy bodies (DLB), clinical Alzheimer's dementia (AD) and Parkinson's disease dementia. However, differentiation can be crucial, especially as patients with DLB characteristically have a hypersensitivity to most antiemetic and neuroleptic drugs as they affect the cholinergic and dopaminergic system, potentially leading to life-threatening catatonia, loss of cognitive function and muscle rigidity. The aim of this study is to evaluate if resting state (RS) functional MRI (fMRI) can be used in routine practice on a 1.5 T scanner to differentiate between AD and DLB on an individual basis. We age- and gender-matched a known DLB patient with an AD patient and a human control (HC). Individual independent component analysis was carried out. Region of interest seeds were chosen from the midcingulate and insula regions. Functional connectivity from insula to midcingulate and within the midcingulate network (part of the Salience network) was lower in DLB than AD or HC. RS-fMRI on a 1.5 T scanner, in a routine clinical setting, detected abnormal functional connectivity patterns and allowed differentiation of DLB and AD in a routine clinical setting. This is the first evaluation of RS-fMRI in a routine clinical setting. It shows that incorporating RS-fMRI into the clinical scanning protocol can assist in early diagnosis and likely assist in monitoring the natural history of the disease or disease modifying treatments.

  View details for DOI 10.1259/bjrcr.20180030

  View details for PubMedID 30931142

  View details for PubMedCentralID PMC6438408

• Dynamic per slice Shimming for Simultaneous Brain and Spinal Cord fMRI. Magnetic resonance in medicine Islam, H., Law, C. S., Weber, K. A., Mackey, S. C., Glover, G. H. 2018

  Abstract

  PURPOSE: Simultaneous brain and spinal cord functional MRI is emerging as a new tool to study the central nervous system but is challenging. Poor B0 homogeneity and small size of the spinal cord are principal obstacles to this nascent technology. Here we extend a dynamic shimming approach, first posed by Finsterbusch, by shimming per slice for both the brain and spinal cord.METHODS: We shim dynamically by a simple and fast optimization of linear field gradients and frequency offset separately for each slice in order to minimize off-resonance for both the brain and spinal cord. Simultaneous acquisition of brain and spinal cord fMRI is achieved with high spatial resolution in the spinal cord by means of an echo-planar RF pulse for reduced FOV. Brain slice acquisition is full FOV.RESULTS: T2*-weighted images of brain and spinal cord are acquired with high clarity and minimal observable image artifacts. Fist-clenching fMRI experiments reveal task-consistent activation in motor cortices, cerebellum, and C6-T1 spinal segments.CONCLUSIONS: High quality functional results are obtained for a sensory-motor task. Consistent activation in both the brain and spinal cord is observed at individual levels, not only at group level. Because reduced FOV excitation is applicable to any spinal cord section, future continuation of these methods holds great potential.

  View details for PubMedID 30284730

• Technical note: can resting state functional MRI assist in routine clinical diagnosis? BJR CASE REPORTS Harman, P., Law, C., Pardhan, S., Lin, Z., Johnson, M., Walter, S., Fassbender, K., Aspinall, R., Grunwald, I. Q. 2018; 4 (4)

  View details for DOI 10.1259/bjrcr.20180030

  View details for Web of Science ID 000449524400012

• Interleaved Spiral-In/Out With Application to Functional MRI (fMRI) MAGNETIC RESONANCE IN MEDICINE Law, C. S., Glover, G. H. 2009; 62 (3): 829-834

  Abstract

  The conventional spiral-in/out trajectory samples k-space sufficiently in the spiral-in path and sufficiently in the spiral-out path to enable creation of separate images. We propose an "interleaved spiral-in/out" trajectory comprising a spiral-in path that gathers one half of the k-space data, and a complimentary spiral-out path that gathers the other half. The readout duration is thereby reduced by approximately half, offering two distinct advantages: reduction of signal dropout due to susceptibility-induced field gradients (at the expense of signal-to-noise ratio [SNR]), and the ability to achieve higher spatial resolution when the readout duration is identical to the conventional method. Two reconstruction methods are described; both involve temporal filtering to remove aliasing artifacts. Empirically, interleaved spiral-in/out images are free from false activation resulting from signal pileup around the air/tissue interface, which is common in the conventional spiral-out method. Comparisons with conventional methods using a hyperoxia stimulus reveal greater frontal-orbital activation volumes but a slight reduction of overall activation in other brain regions.

  View details for DOI 10.1002/mrm.22056

  View details for Web of Science ID 000269404900033

  View details for PubMedID 19449373

  View details for PubMedCentralID PMC2763441

• Sliding-Window Sensitivity Encoding (SENSE) Calibration for Reducing Noise in Functional MRI (fMRI) MAGNETIC RESONANCE IN MEDICINE Law, C. S., Liu, C., Glover, G. H. 2008; 60 (5): 1090-1103

  Abstract

  Functional magnetic resonance imaging (fMRI) at high magnetic field with parallel imaging (PI) has become increasingly popular for high-resolution imaging. We present a method of self-calibrated PI-fMRI in which sensitivity profiles are calculated using a sliding window of fully sampled multishot imaging data. We show that by updating these sensitivity profiles in a sliding fashion, thermal noise is reduced in the reconstructed image time series. This is accomplished by retaining thermal noise in the sensitivity profiles; no spatial smoothing is performed. These noisy profiles actually provide a closer match to those required for thermal noise-free reconstruction than conventional sensitivity map generation. Our proposed technique is especially applicable for acquiring high-spatial-resolution images, where thermal noise exceeds physiological noise. With conventional sensitivity calculation, PI-fMRI sensitivity is preserved only when using a voxel size large enough such that physiological noise predominates. With small voxel size, our technique reveals activation from visual stimulation where conventional sensitivity calculation techniques falter. Our technique enhances fMRI detection, especially when higher spatial resolution is desired.

  View details for DOI 10.1002/mrm.21701

  View details for PubMedID 18956461

• Spiral-in/out BOLD fMRI for increased SNR and reduced susceptibility artifacts MAGNETIC RESONANCE IN MEDICINE Glover, G. H., Law, C. S. 2001; 46 (3): 515-522

  Abstract

  BOLD fMRI is hampered by dropout of signal in the orbitofrontal and parietal brain regions due to magnetic field gradients near air-tissue interfaces. This work reports the use of spiral-in trajectories that begin at the edge of k-space and end at the origin, and spiral in/out trajectories in which a spiral-in readout is followed by a conventional spiral-out trajectory. The spiral-in trajectory reduces the dropout and increases the BOLD contrast. The spiral-in and spiral-out images can be combined in several ways to simultaneously achieve increased signal-to-noise ratio (SNR) and reduced dropout artifacts. Activation experiments employing an olfaction task demonstrate significantly increased activation volumes due to reduced dropout, and overall increased SNR in all regions.

  View details for Web of Science ID 000170740300016

  View details for PubMedID 11550244