Abstracts and studies

This abstracts and studies hub offers an opportunity to review some shortlisted studies by condition, and a more comprehensive list in the Book of Abstracts

Shortlisted studies by condition

This is by no means a comprehensive list. These news items are selected only for information purposes for our professional audience, and MEGIN assumes no responsibility for their content. MEGIN does not endorse any applications or treatments mentioned.

Oncology

Concussion/TBI

Alzheimers

Autism

Epilepsy

Book of Abstracts

Oncology

Alzheimers

Epilepsy

Autism

Concussion/TBI

Book of Abstracts

Huang et al. (2016). High-resolution MEG source imaging approach to acurately localize Broca’s area in patients with brain tumor or epilepsy. Clinical Neurophysiology, Vol.127, No.5.

MEG in Oncology/Radiation Oncology

Belgers, V., Numan, T., Kulik, S. D., Hillebrand, A., de Witt Hamer, P. C., Geurts, J. J. G., Reijneveld, J. C., Wesseling, P., Klein, M., Derks, J., & Douw, L. (2020). Postoperative oscillatory brain activity as an add-on prognostic marker in diffuse glioma. Journal of Neuro-Oncology, 147(1), 49–58.

Numan, T., Kulik, S. D., Moraal, B., Reijneveld, J. C., Stam, C. J., de Witt Hamer, P. C., Derks, J., Bruynzeel, A. M. E., van Linde, M. E., Wesseling, P., Kouwenhoven, M. C. M., Klein, M., Würdinger, T., Barkhof, F., Geurts, J. J. G., Hillebrand, A., & Douw, L. (2021). Non-invasively measured brain activity and radiological progression in diffuse glioma. Scientific Reports, 11, Article 18990.

Lee, A. T., Faltermeier, C., Morshed, R. A., Young, J. S., Kakaizada, S., Valdivia, C., Findlay, A. M., Tarapore, P. E., Nagarajan, S. S., Hervey-Jumper, S. L., & Berger, M. S. (2020). The impact of high functional connectivity network hub resection on language task performance in adult low- and high-grade glioma. Journal of Neurosurgery, 134(4), 1102–1112.

Samuel, N., Harmsen, I. E., Ding, M. Y. R., Sarica, C., Vetkas, A., Wong, C., Lawton, V., Yang, A., Rowland, N. C., Kalia, S. K., Valiante, T., Wennberg, R., Zadeh, G., Kongkham, P., Kalyvas, A., & Lozano, A. M. (2023). Investigation of neurophysiologic and functional connectivity changes following glioma resection using magnetoencephalography. Neuro-Oncology Advances, 5(1), vdad091.

Bulubas, L., Sardesh, N., Traut, T., Findlay, A., Mizuiri, D., Honma, S. M., Krieg, S. M., Berger, M. S., Nagarajan, S. S., & Tarapore, P. E. (2020). Motor cortical network plasticity in patients with recurrent brain tumors. Frontiers in Human Neuroscience, 14, 118.

MEG in Oncology/Radiation Oncology

Belgers, V., Numan, T., Kulik, S. D., Hillebrand, A., de Witt Hamer, P. C., Geurts, J. J. G., Reijneveld, J. C., Wesseling, P., Klein, M., Derks, J., & Douw, L. (2020). Postoperative oscillatory brain activity as an add-on prognostic marker in diffuse glioma. Journal of Neuro-Oncology, 147(1), 49–58.

Numan, T., Kulik, S. D., Moraal, B., Reijneveld, J. C., Stam, C. J., de Witt Hamer, P. C., Derks, J., Bruynzeel, A. M. E., van Linde, M. E., Wesseling, P., Kouwenhoven, M. C. M., Klein, M., Würdinger, T., Barkhof, F., Geurts, J. J. G., Hillebrand, A., & Douw, L. (2021). Non-invasively measured brain activity and radiological progression in diffuse glioma. Scientific Reports, 11, Article 18990.

Lee, A. T., Faltermeier, C., Morshed, R. A., Young, J. S., Kakaizada, S., Valdivia, C., Findlay, A. M., Tarapore, P. E., Nagarajan, S. S., Hervey-Jumper, S. L., & Berger, M. S. (2020). The impact of high functional connectivity network hub resection on language task performance in adult low- and high-grade glioma. Journal of Neurosurgery, 134(4), 1102–1112.

Samuel, N., Harmsen, I. E., Ding, M. Y. R., Sarica, C., Vetkas, A., Wong, C., Lawton, V., Yang, A., Rowland, N. C., Kalia, S. K., Valiante, T., Wennberg, R., Zadeh, G., Kongkham, P., Kalyvas, A., & Lozano, A. M. (2023). Investigation of neurophysiologic and functional connectivity changes following glioma resection using magnetoencephalography. Neuro-Oncology Advances, 5(1), vdad091.

Bulubas, L., Sardesh, N., Traut, T., Findlay, A., Mizuiri, D., Honma, S. M., Krieg, S. M., Berger, M. S., Nagarajan, S. S., & Tarapore, P. E. (2020). Motor cortical network plasticity in patients with recurrent brain tumors. Frontiers in Human Neuroscience, 14, 118.

Huang et al. (2016). High-resolution MEG source imaging approach to acurately localize Broca’s area in patients with brain tumor or epilepsy. Clinical Neurophysiology, Vol.127, No.5.

MEG in Concussion/TBI

Huang, M.-X., Huang, C. W., Harrington, D. L., Nichols, S., Robb-Swan, A., Angeles-Quinto, A., Le, L., Rimmele, C., Drake, A., Song, T., Huang, J. W., Clifford, R., Ji, Z., Cheng, C.-K., Lerman, I., Yurgil, K. A., Lee, R. R., Baker, D. G. (2020). Marked increases in resting-state MEG gamma-band activity in combat-related mild traumatic brain injury. Cerebral Cortex, Volume 30, Issue 1, January 2020, Pages 283–295

Zhang, J., Safar, K., Emami, Z., Ibrahim, G. M., Scratch, S. E., da Costa, L., & Dunkley, B. T. (2020). Local and large-scale beta oscillatory dysfunction in males with mild traumatic brain injury. Journal of Neurophysiology, 125(2), 491–505.

Antonakakis, M., Dimitriadis, S. I., Zervakis, M., Papanicolaou, A. C., & Zouridakis, G. (2020). Aberrant whole-brain transitions and dynamics of spontaneous network microstates in mild traumatic brain injury. Frontiers in Computational Neuroscience, 13, 90.

Safar, K., Zhang, J., Emami, Z., Gharehgazlou, A., Ibrahim, G., & Dunkley, B. T. (2021). Mild traumatic brain injury is associated with dysregulated neural network functioning in children and adolescents. Brain Communications, 3(2), fcab044.

Huang, M.-X., Angeles-Quinto, A., Robb-Swan, A., De-la-Garza, B. G., Huang, C. W., Cheng, C.-K., Hesselink, J. R., Bigler, E. D., Wilde, E. A., Vaida, F., Troyer, E. A., & Max, J. E. (2022). Assessing pediatric mild traumatic brain injury and its recovery using resting-state magnetoencephalography source magnitude imaging and machine learning. Journal of Neurotrauma, Vol. 40, No. 11-12.

MEG in Alzheimers

Gouw, A. A., Hillebrand, A., Schoonhoven, D. N., Demuru, M., Ris, P., Scheltens, P., & Stam, C. J. (2021). Routine magnetoencephalography in memory clinic patients: A machine learning approach. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring. 13(1), e12227.

Cope, T. E., Rittman, T., Borchert, R. J., Jones, P. S., Vatansever, D., Allinson, K. S. J., Passamonti, L., & Rowe, J. B. (2022). Causal evidence for the multiple demand network in change detection: A study of patients with focal brain lesions. The Journal of Neuroscience, 42 (15) 3197-3215

Vaghari, D., Hughes, L. E., Bruna, R., Koelewijn, L., Woolrich, M. W., Luo, Q., & Henson, R. N. (2022). A multi-site, multi-participant magnetoencephalography resting-state dataset to study dementia: The BioFIND dataset. NeuroImage, Volume 258, 119344.

Giovannetti, A., Susi, G., Casti, P., Mencattini, A., Pusil, S., Eugenia Lopez, M., Di Natale, C., Martinelli, E. (2021) Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography. Neural Comput & Applic 33, 14651–14667.

Vossel K., Ranasinghe KG., Beagle AJ., et al. Effect of Levetiracetam on Cognition in Patients With Alzheimer Disease With and Without Epileptiform Activity: A Randomized Clinical Trial. JAMA Neurol. 2021;78(11):1345–1354. doi:10.1001/jamaneurol.2021.3310

MEG in Alzheimers

Gouw, A. A., Hillebrand, A., Schoonhoven, D. N., Demuru, M., Ris, P., Scheltens, P., & Stam, C. J. (2021). Routine magnetoencephalography in memory clinic patients: A machine learning approach. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring. 13(1), e12227.

Cope, T. E., Rittman, T., Borchert, R. J., Jones, P. S., Vatansever, D., Allinson, K. S. J., Passamonti, L., & Rowe, J. B. (2022). Causal evidence for the multiple demand network in change detection: A study of patients with focal brain lesions. The Journal of Neuroscience, 42 (15) 3197-3215

Vaghari, D., Hughes, L. E., Bruna, R., Koelewijn, L., Woolrich, M. W., Luo, Q., & Henson, R. N. (2022). A multi-site, multi-participant magnetoencephalography resting-state dataset to study dementia: The BioFIND dataset. NeuroImage, Volume 258, 119344.

Giovannetti, A., Susi, G., Casti, P., Mencattini, A., Pusil, S., Eugenia Lopez, M., Di Natale, C., Martinelli, E. (2021) Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography. Neural Comput & Applic 33, 14651–14667.

Vossel K., Ranasinghe KG., Beagle AJ., et al. Effect of Levetiracetam on Cognition in Patients With Alzheimer Disease With and Without Epileptiform Activity: A Randomized Clinical Trial. JAMA Neurol. 2021;78(11):1345–1354. doi:10.1001/jamaneurol.2021.3310

MEG in Autism

Seymour, R.A., Rippon, G., Gooding-Williams, G., Sowman, P.F., Kessler, K. (2020). Reduced auditory steady state responses in autism spectrum disorder. Molecular Autism 11, 56.

Manyukhina, V.O., Prokofyev, A.O., Galuta, I.A., Goiaeva, D.E., Obukhova, T.S., Schneiderman, J.F., Altukhov, D.I., Stroganova, T.A., Orekhova, E.V. Globally elevated excitation–inhibition ratio in children with autism spectrum disorder and below-average intelligence. Molecular Autism 13, 20 (2022).

Matsuzaki, J., Ku, M., Dipiero, M., Chiang, T., Saby, J., Blaskey, L., Kuschner, E.S., Kim, M., Berman, J.I., Bloy, L., Chen., Y, Dell, J., Liu, S., Brodkin, E.S., Embick, D., Roberts, T.P.L. (2020). Delayed Auditory Evoked Responses in Autism Spectrum Disorder across the Life Span. Dev Neurosci, 41 (3-4): 223–233.

Rotschafer, S.E. (2021) Auditory Discrimination in Autism Spectrum Disorder. Front. Neurosci. 15:651209.

Gaetz, W., Rhodes, E., Bloy, L., Blaskey, L., Jackel, C.R., Brodkin, E.S., Waldman, A., Embick, D., Hall, S., Roberts, T.P.L. (2020). Evaluating motor cortical oscillations and age-related change in autism spectrum disorder, NeuroImage, Volume 207, 116349.

Ono, Y., Kudoh, K., Ikeda, T., Takahashi, T., Yoshimura, Y., Minabe, Y. and Kikuchi, M. (2020). Auditory steady-state response at 20 Hz and 40 Hz in young typically developing children and children with autism spectrum disorder. Psychiatry Clin. Neurosci., 74: 354-361.

MEG in Epilepsy

Corona, L., Tamilia, E., Perry, M.S., Madsen, J.R., Bolton, J., Stone, S.S.D., Stufflebeam, S.M., Pearl, P.L., Papadelis, C. (2023). Non-invasive mapping of epileptogenic networks predicts surgical outcome. Brain, Volume 146, Issue 5, Pages 1916–1931.

Tripathi M., Kaur K., Ramanujam B., Viswanathan, V., Bharti, K., Singh, G., Singh, V., Garg, A., Sekhar Bal, C., Tripathi, M., Chand Sharma, M., Pandey, R., Dash, D., Mandal, P., Sarat Chandra, P. (2021) Diagnostic added value of interictal magnetic source imaging in presurgical evaluation of persons with epilepsy: A prospective blinded study. Eur J Neurol. 28: 2940-2951.

Tamilia, E., Matarrese, M.A.G., Ntolkeras, G., Grant, P.E., Madsen, J.R., Stufflebeam, S.M., Pearl, P.L. and Papadelis, C. (2021). Noninvasive Mapping of Ripple Onset Predicts Outcome in Epilepsy Surgery. Ann Neurol, 89: 911-925.

Yin, C., Zhang, X., Xiang, J., Chen, Z., Li, X., Wu, S., Lv, P., Wang, Y. (2020). Altered effective connectivity network in patients with insular epilepsy: A high-frequency oscillations magnetoencephalography study. Clinical Neurophysiology, Volume 131, Issue 2, Pages 377-384.

Cao, M., Galvis, D., Vogrin, S.J., Woods, W.P., Vogrin, S., Wang, F., Woldman, W., Terry, J.R., Peterson, A., Plummer, C., Cook, M.J. (2022) Virtual intracranial EEG signals reconstructed from MEG with potential for epilepsy surgery. Nat Commun 13, 994.

MEG in Epilepsy

Corona, L., Tamilia, E., Perry, M.S., Madsen, J.R., Bolton, J., Stone, S.S.D., Stufflebeam, S.M., Pearl, P.L., Papadelis, C. (2023). Non-invasive mapping of epileptogenic networks predicts surgical outcome. Brain, Volume 146, Issue 5, Pages 1916–1931.

Tripathi M., Kaur K., Ramanujam B., Viswanathan, V., Bharti, K., Singh, G., Singh, V., Garg, A., Sekhar Bal, C., Tripathi, M., Chand Sharma, M., Pandey, R., Dash, D., Mandal, P., Sarat Chandra, P. (2021) Diagnostic added value of interictal magnetic source imaging in presurgical evaluation of persons with epilepsy: A prospective blinded study. Eur J Neurol. 28: 2940-2951.

Tamilia, E., Matarrese, M.A.G., Ntolkeras, G., Grant, P.E., Madsen, J.R., Stufflebeam, S.M., Pearl, P.L. and Papadelis, C. (2021). Noninvasive Mapping of Ripple Onset Predicts Outcome in Epilepsy Surgery. Ann Neurol, 89: 911-925.

Yin, C., Zhang, X., Xiang, J., Chen, Z., Li, X., Wu, S., Lv, P., Wang, Y. (2020). Altered effective connectivity network in patients with insular epilepsy: A high-frequency oscillations magnetoencephalography study. Clinical Neurophysiology, Volume 131, Issue 2, Pages 377-384.

Cao, M., Galvis, D., Vogrin, S.J., Woods, W.P., Vogrin, S., Wang, F., Woldman, W., Terry, J.R., Peterson, A., Plummer, C., Cook, M.J. (2022) Virtual intracranial EEG signals reconstructed from MEG with potential for epilepsy surgery. Nat Commun 13, 994.

MEGIN Book of Abstracts – MEG Studies 2020 – 2022

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