Publications
Publications
Publication Policy
DABI users agree not to reference results of any analysis shown in the DABI site in scientific or research publications.
Preliminary analysis results shown in DABI are intended solely to stimulate knowledge of and interest in the datasets in the DABI federation. Data analyses are subject to the following constraints:
1. DABI does not provide details of the methods used to run analyses. It is not possible to report analysis results when the analysis methods are hidden.
2. No attempt has been made to correct for confounding variables. There may be and likely are factors which bias the analysis results shown on the site. These can only be identified by working directly with those who have collected the data.
3. A complete and proper understanding of the data collected by DABI providers can only be ascertained by working with them when performing an analysis. DABI aims to connect researchers with its data providers to foster new collaboration.
If DABI users are granted access to data and wish to publish results of analysis performed on the data, they must cite the Data Provider (per the agreed upon conditions) and include the following in their acknowledgements: “Data used to perform this analysis was accessed from the Data Archive for the BRAIN Initiative with support from the National Institutes of Health under Award Number R24MH114796.”
Publications Using DABI
1. Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity.
Bush, Alan, et al., Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity., bioRxiv, 2023; 2023-02.
10.1101/2023.02.08.527719
2. Data Archive for the BRAIN Initiative (DABI)
Duncan, D., Garner, R., Brinkerhoff, S., Walker, H. C., Pouratian, N., Toga, A. W., Data Archive for the BRAIN Initiative (DABI), Scientific Data, 2023; 10(1), 83.
10.1038/s41597-023-01972-z
3. Epidural stimulation of the cervical spinal cord for post-stroke upper-limb paresis
Powell, M. P., Verma, N., Sorensen, E., Carranza, E., Boos, A., Fields, D. P., Capogrosso, M., Epidural stimulation of the cervical spinal cord for post-stroke upper-limb paresis, Nature Medicine, 2023; 1-11.
10.1038/s41591-022-02202-6
4. Non-linear Embedding Methods for Identifying Similar Brain Activity in 1 Million iEEG Records Captured From 256 RNS System Patients
Desai, S. A., Tcheng, T., Morrell, M., Non-linear Embedding Methods for Identifying Similar Brain Activity in 1 Million iEEG Records Captured From 256 RNS System Patients, Frontiers in Big Data, 2022; 5.
10.3389/fdata.2022.840508
5. The spectrum of data sharing policies in neuroimaging data repositories
Jwa, A. S., Poldrack, R. A., The spectrum of data sharing policies in neuroimaging data repositories, Human Brain Mapping, 2022; 43(8), 2707-2721.
10.1002/hbm.25803
6. Flexible, Scalable, High Channel Count Stereo-Electrode for Recording in the Human Brain
Lee, Keundong, et al., Flexible, Scalable, High Channel Count Stereo-Electrode for Recording in the Human Brain, bioRxiv, 2022; 11.
10.1101/2022.11.08.515705
7. Cortical and STN spectral changes during limb movements in PD patients with and without dystonia
Nakhmani, A., Joseph, W., Zachary, T., Lloyd, J., Gonzalez, C. L., Wade, M. H., Walker, H. C., Cortical and STN spectral changes during limb movements in PD patients with and without dystonia, , 2022;
10.1101/2022.01.04.22268757
8. Local anatomy, stimulation site, and time alter directional deep brain stimulation impedances
Olson, J. W., Gonzalez, C. L., Brinkerhoff, S., Boolos, M., Wade, M. H., Hurt, C. P., Walker, H. C., Local anatomy, stimulation site, and time alter directional deep brain stimulation impedances, Frontiers in Human Neuroscience, 2022; 16.
10.3389%2Ffnhum.2022.958703
9. Cortical and subthalamic nucleus spectral changes during limb movements in Parkinson's disease patients with and without dystonia
Olson, J. W., Nakhmani, A., Irwin, Z. T., Edwards, L. J., Gonzalez, C. L., Wade, M. H., Walker, H. C., Cortical and subthalamic nucleus spectral changes during limb movements in Parkinson's disease patients with and without dystonia, Movement Disorders, 2022; 37(8), 1683-1692.
10.1002/mds.29057
10. Cortical and STN spectral changes during limb movements in PD patients with and without dystonia
Olson, J. W., Nakhmani, A., Irwin, Z. T., Edwards, L. J., Gonzalez, C. L., Wade, M. H., Walker, H. C., Cortical and STN spectral changes during limb movements in PD patients with and without dystonia, medRxiv, 2022; 2022-01.
10.1101/2022.01.04.22268757
11. Constructing 2D maps of human spinal cord activity and isolating the functional midline with high-density microelectrode arrays
Russman, S. M., Cleary, D. R., Tchoe, Y., Bourhis, A. M., Stedelin, B., Martin, J., Dayeh, S. A., Constructing 2D maps of human spinal cord activity and isolating the functional midline with high-density microelectrode arrays, Science translational medicine, 2022; 14(664).
10.1126/scitranslmed.abq4744
12. Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics
Tchoe, Y., Bourhis, A. M., Cleary, D. R., Stedelin, B., Lee, J., Tonsfeldt, K. J., Dayeh, S. A., Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics, Science translational medicine, 2022; 14(628).
10.1126/scitranslmed.abj1441
13. Dataset of human intracranial recordings during famous landmark identification
Dataset of human intracranial recordings during famous landmark identification, Scientific data, 2022; 9(1), 28.
10.1038/s41597-022-01125-8
14. Differential Cortical Network Engagement During States of Un/Consciousness in Humans
Zelmann, R., Paulk, A., Tian, F., Balanza, G., Peralta, J. D., Crocker, B., Cash, S., Differential Cortical Network Engagement During States of Un/Consciousness in Humans, , 2022; .
10.21203/rs.3.rs-2006868/v3
15. The role of large-scale data infrastructure in developing next-generation deep brain stimulation therapies
Chen, W., Kirkby, L., Kotzev, M., Song, P., Gilron, R. E., Pepin, B., The role of large-scale data infrastructure in developing next-generation deep brain stimulation therapies, Frontiers in Human Neuroscience, 2021; 15, 717401.
10.3389/fnhum.2021.717401
16. COVID-19 data sharing and collaboration
Duncan, D., COVID-19 data sharing and collaboration, Communications in Information and Systems, 2021; 21(3).
10.4310/CIS.2021.v21.n3.a1
17. Long-term ecological assessment of intracranial electrophysiology synchronized to behavioral markers in obsessive-compulsive disorder
Provenza, N. R., Sheth, S. A., Dastin-van Rijn, E. M., Mathura, R. K., Ding, Y., Vogt, G. S., Borton, D. A., Long-term ecological assessment of intracranial electrophysiology synchronized to behavioral markers in obsessive-compulsive disorder, Nature Medicine, 2021; 27(12), 2154-2164.
10.1038/s41591-021-01550-z
18. The neurodata without borders ecosystem for neurophysiological data science
Rübel, O., Tritt, A., Ly, R., Dichter, B. K., Ghosh, S., Niu, L., Bouchard, K. E., The neurodata without borders ecosystem for neurophysiological data science, Elife, 2021; 11.
10.1101/2021.03.13.435173
19. Musical hallucinations in chronic pain: the anterior cingulate cortex regulates internally generated percepts
Schmitgen, A., Saal, J., Sankaran, N., Desai, M., Joseph, I., Starr, P., Shirvalkar, P., Musical hallucinations in chronic pain: the anterior cingulate cortex regulates internally generated percepts, Frontiers in Neurology, 2021; 12, 669172.
10.3389/fneur.2021.669172
20. Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation
Sendi MSE, Waters AC, Tiruvadi V, et al., Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation, Transl Psychiatry, 2021; 11(1):1-7.
10.1038/s41398-021-01669-0
21. Diet modulates brain network stability, a biomarker for brain aging, in young adults
Mujica-Parodi LR, Amgalan A, Sultan SF, et al., Diet modulates brain network stability, a biomarker for brain aging, in young adults, Proc Natl Acad Sci U.S.A, 2020; 117(11):6170-6177.
10.1073/pnas.1913042117
22. RAVE: Comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data
Magnotti JF, Wang Z, Beauchamp MS, et al., RAVE: Comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data, NeuroImage, 2020; 223:117341.
10.1016/j.neuroimage.2020.117341
23. The Role of Large-Scale Data Infrastructure in Developing Next-Generation Deep Brain Stimulation Therapies
Chen W, Kirkby L, Kotzev M, Song P, Gilron R, Pepin B, et al., The Role of Large-Scale Data Infrastructure in Developing Next-Generation Deep Brain Stimulation Therapies, Front Hum Neurosci, 2021; 2021;15:717401.
10.3389/fnhum.2021.717401
24. Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics
Tchoe Y, Bourhis AM, Cleary DR, et al., Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics, Sci Transl Med, 2022; 14(628):eabj1441.
10.1126/scitranslmed.abj1441
25. Cortical and STN spectral changes during limb movements in PD patients with and without dystonia
Nakhmani A, Olson JW, Irwin ZTF, et al., Cortical and STN spectral changes during limb movements in PD patients with and without dystonia, medRxiv, 2022; 2022.01.04.22268757.
10.1101/2022.01.04.22268757
26. The Neurodata Without Borders ecosystem for neurophysiological data science
Rübel O, Tritt A, Ly R, et al., The Neurodata Without Borders ecosystem for neurophysiological data science, bioRxiv. Published online, 2021; 2021.03.13.435173.
10.1101/2021.03.13.435173
27. Younger, but not older, brains are poised at a critical point of functional activity
Weistuch C, Mujica-Parodi LR, Amgalan A, et al., Younger, but not older, brains are poised at a critical point of functional activity, bioRxiv. Published online, 2020; 2020.04.17.047233.
10.1101/2020.04.17.047233
28. Metabolism modulates network synchrony in the aging brain
Weistuch C, Mujica-Parodi LR, Amgalan A, et al., Metabolism modulates network synchrony in the aging brain, bioRxiv. Published online, 2020; 2020.04.17.047233.
10.1101/2020.04.17.047233
29. Long-term ecological assessment of intracranial electrophysiology synchronized to behavioral markers in obsessive-compulsive disorder
Provenza NR, Sheth SA, Dastin-van Rijn EM, et al., Long-term ecological assessment of intracranial electrophysiology synchronized to behavioral markers in obsessive-compulsive disorder, Nat Med, 2021; 27(12):2154-2164.
10.1038/s41591-021-01550-z
30. Musical Hallucinations in Chronic Pain: The Anterior Cingulate Cortex Regulates Internally Generated Percepts
Mujica-Parodi LR, Amgalan A, Sultan SF, et al., Musical Hallucinations in Chronic Pain: The Anterior Cingulate Cortex Regulates Internally Generated Percepts, Proc Natl Acad Sci U.S.A, 2020; 117(11):6170-6177.
10.1073/pnas.1913042117
31. Bridging the Brain and Data Sciences
Van Horn JD, Bridging the Brain and Data Sciences, Proc Natl Acad Sci U.S.A, 2021; 9(3):153-187.
10.1089/big.2020.0065
32. Dataset of human intracranial recordings during famous landmark identification
Woolnough O, Kadipasaoglu CM, Conner CR, et al., Dataset of human intracranial recordings during famous landmark identification, Sci Data, 2022; 9(1):28.
10.1038/s41597-022-01125-8
33. The spectrum of data sharing policies in neuroimaging data repositories
Jwa AS, Poldrack RA, The spectrum of data sharing policies in neuroimaging data repositories, Hum Brain Mapp, 2022; Published online.
10.1002/hbm.25803
34. Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity.
Bush, Alan, et al., Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity., bioRxiv, 2023; 2023-02.
10.1101/2023.02.08.527719
35. Data Archive for the BRAIN Initiative (DABI)
Duncan, D., Garner, R., Brinkerhoff, S., Walker, H. C., Pouratian, N., Toga, A. W., Data Archive for the BRAIN Initiative (DABI), Scientific Data, 2023; 10(1), 83.
10.1038/s41597-023-01972-z
36. Epidural stimulation of the cervical spinal cord for post-stroke upper-limb paresis
Powell, M. P., Verma, N., Sorensen, E., Carranza, E., Boos, A., Fields, D. P., Capogrosso, M., Epidural stimulation of the cervical spinal cord for post-stroke upper-limb paresis, Nature Medicine, 2023; 1-11.
10.1038/s41591-022-02202-6
37. Non-linear Embedding Methods for Identifying Similar Brain Activity in 1 Million iEEG Records Captured From 256 RNS System Patients
Desai, S. A., Tcheng, T., Morrell, M., Non-linear Embedding Methods for Identifying Similar Brain Activity in 1 Million iEEG Records Captured From 256 RNS System Patients, Frontiers in Big Data, 2022; 5.
10.3389/fdata.2022.840508
38. The spectrum of data sharing policies in neuroimaging data repositories
Jwa, A. S., Poldrack, R. A., The spectrum of data sharing policies in neuroimaging data repositories, Human Brain Mapping, 2022; 43(8), 2707-2721.
10.1002/hbm.25803
39. Flexible, Scalable, High Channel Count Stereo-Electrode for Recording in the Human Brain
Lee, Keundong, et al., Flexible, Scalable, High Channel Count Stereo-Electrode for Recording in the Human Brain, bioRxiv, 2022; 11.
10.1101/2022.11.08.515705
40. Cortical and STN spectral changes during limb movements in PD patients with and without dystonia
Nakhmani, A., Joseph, W., Zachary, T., Lloyd, J., Gonzalez, C. L., Wade, M. H., Walker, H. C., Cortical and STN spectral changes during limb movements in PD patients with and without dystonia, , 2022;
10.1101/2022.01.04.22268757
41. Local anatomy, stimulation site, and time alter directional deep brain stimulation impedances
Olson, J. W., Gonzalez, C. L., Brinkerhoff, S., Boolos, M., Wade, M. H., Hurt, C. P., Walker, H. C., Local anatomy, stimulation site, and time alter directional deep brain stimulation impedances, Frontiers in Human Neuroscience, 2022; 16.
10.3389%2Ffnhum.2022.958703
42. Cortical and subthalamic nucleus spectral changes during limb movements in Parkinson's disease patients with and without dystonia
Olson, J. W., Nakhmani, A., Irwin, Z. T., Edwards, L. J., Gonzalez, C. L., Wade, M. H., Walker, H. C., Cortical and subthalamic nucleus spectral changes during limb movements in Parkinson's disease patients with and without dystonia, Movement Disorders, 2022; 37(8), 1683-1692.
10.1002/mds.29057
43. Cortical and STN spectral changes during limb movements in PD patients with and without dystonia
Olson, J. W., Nakhmani, A., Irwin, Z. T., Edwards, L. J., Gonzalez, C. L., Wade, M. H., Walker, H. C., Cortical and STN spectral changes during limb movements in PD patients with and without dystonia, medRxiv, 2022; 2022-01.
10.1101/2022.01.04.22268757
44. Constructing 2D maps of human spinal cord activity and isolating the functional midline with high-density microelectrode arrays
Russman, S. M., Cleary, D. R., Tchoe, Y., Bourhis, A. M., Stedelin, B., Martin, J., Dayeh, S. A., Constructing 2D maps of human spinal cord activity and isolating the functional midline with high-density microelectrode arrays, Science translational medicine, 2022; 14(664).
10.1126/scitranslmed.abq4744
45. Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics
Tchoe, Y., Bourhis, A. M., Cleary, D. R., Stedelin, B., Lee, J., Tonsfeldt, K. J., Dayeh, S. A., Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics, Science translational medicine, 2022; 14(628).
10.1126/scitranslmed.abj1441
46. Dataset of human intracranial recordings during famous landmark identification
Dataset of human intracranial recordings during famous landmark identification, Scientific data, 2022; 9(1), 28.
10.1038/s41597-022-01125-8
47. Differential Cortical Network Engagement During States of Un/Consciousness in Humans
Zelmann, R., Paulk, A., Tian, F., Balanza, G., Peralta, J. D., Crocker, B., Cash, S., Differential Cortical Network Engagement During States of Un/Consciousness in Humans, , 2022; .
10.21203/rs.3.rs-2006868/v3
48. The role of large-scale data infrastructure in developing next-generation deep brain stimulation therapies
Chen, W., Kirkby, L., Kotzev, M., Song, P., Gilron, R. E., Pepin, B., The role of large-scale data infrastructure in developing next-generation deep brain stimulation therapies, Frontiers in Human Neuroscience, 2021; 15, 717401.
10.3389/fnhum.2021.717401
49. COVID-19 data sharing and collaboration
Duncan, D., COVID-19 data sharing and collaboration, Communications in Information and Systems, 2021; 21(3).
10.4310/CIS.2021.v21.n3.a1
50. Long-term ecological assessment of intracranial electrophysiology synchronized to behavioral markers in obsessive-compulsive disorder
Provenza, N. R., Sheth, S. A., Dastin-van Rijn, E. M., Mathura, R. K., Ding, Y., Vogt, G. S., Borton, D. A., Long-term ecological assessment of intracranial electrophysiology synchronized to behavioral markers in obsessive-compulsive disorder, Nature Medicine, 2021; 27(12), 2154-2164.
10.1038/s41591-021-01550-z
51. The neurodata without borders ecosystem for neurophysiological data science
Rübel, O., Tritt, A., Ly, R., Dichter, B. K., Ghosh, S., Niu, L., Bouchard, K. E., The neurodata without borders ecosystem for neurophysiological data science, Elife, 2021; 11.
10.1101/2021.03.13.435173
52. Musical hallucinations in chronic pain: the anterior cingulate cortex regulates internally generated percepts
Schmitgen, A., Saal, J., Sankaran, N., Desai, M., Joseph, I., Starr, P., Shirvalkar, P., Musical hallucinations in chronic pain: the anterior cingulate cortex regulates internally generated percepts, Frontiers in Neurology, 2021; 12, 669172.
10.3389/fneur.2021.669172
53. Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation
Sendi MSE, Waters AC, Tiruvadi V, et al., Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation, Transl Psychiatry, 2021; 11(1):1-7.
10.1038/s41398-021-01669-0
54. Bridging the Brain and Data Sciences
Van Horn JD, Bridging the Brain and Data Sciences, Proc Natl Acad Sci U.S.A, 2021; 9(3):153-187.
10.1089/big.2020.0065
55. Metabolism modulates network synchrony in the aging brain
Weistuch C, Mujica-Parodi LR, Amgalan A, et al., Metabolism modulates network synchrony in the aging brain, bioRxiv. Published online, 2020; 2020.04.17.047233.
10.1101/2020.04.17.047233
56. Pseudonymisation of neuroimages and data protection: increasing access to data while retaining scientific utility
Eke, D., Aasebø, I. E., Akintoye, S., Knight, W., Karakasidis, A., Mikulan, E., ... & Zehl, L. (2021). Pseudonymisation of neuroimages and data protection: increasing access to data while retaining scientific utility. Neuroimage: Reports, 1(4), 100053.
10.1016/j.ynirp.2021.100045
57. RAVE: Comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data
Magnotti JF, Wang Z, Beauchamp MS, et al., RAVE: Comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data, NeuroImage, 2020; 223:117341.
10.1016/j.neuroimage.2020.117341
58. Diet modulates brain network stability, a biomarker for brain aging, in young adults
Mujica-Parodi LR, Amgalan A, Sultan SF, et al., Diet modulates brain network stability, a biomarker for brain aging, in young adults, Proc Natl Acad Sci U.S.A, 2020; 117(11):6170-6177.
10.1073/pnas.1913042117
59. Younger, but not older, brains are poised at a critical point of functional activity
Weistuch C, Mujica-Parodi LR, Amgalan A, et al., Younger, but not older, brains are poised at a critical point of functional activity, bioRxiv. Published online, 2020; 2020.04.17.047233.
10.1101/2020.04.17.047233
60. A comparison of neuroelectrophysiology databases
Subash, Priyanka, et al. “A comparison of neuroelectrophysiology databases.” Scientific Data 10.1 (2023): 719.
10.1038/s41597-023-02614-0
61. Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes
Soper, Daniel J., et al. “Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes.” Plos one 18.7 (2023): e0287921.
10.1371/journal.pone.0287921
62. Cingulate dynamics track depression recovery with deep brain stimulation
Alagapan, Sankaraleengam, et al. “Cingulate dynamics track depression recovery with deep brain stimulation.” Nature(2023): 1-9.
10.1038/s41586-023-06541-3
63. Expert and deep learning model identification of iEEG seizures and seizure onset times
Desai, Sharanya Arcot, et al. “Expert and deep learning model identification of iEEG seizures and seizure onset times.” Frontiers in Neuroscience 17 (2023).
10.3389/fnins.2023.1156838