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