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3. Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy

Author

Park, B.-y., Larivière, S., Rodríguez-Cruces, R., Royer, J., Tavakol, S., Wang, Y., Caciagli, L., Caligiuri, M.E., Gambardella, A., Concha, L., Keller, S.S., Cendes, F., Alvim, M.K.M., Yasuda, C., Bonilha, L., Gleichgerrcht, E., Focke, N.K., Kreilkamp, B.A.K., Domin, M., Podewils, F. von, Langner, S., Rummel, C., Rebsamen, M., Wiest, R., Martin, P., Kotikalapudi, R., Bender, B., O’Brien, T.J., Law, M., Sinclair, B., Vivash, L., Kwan, P., Desmond, P.M., Malpas, C.B., Lui, E., Alhusaini, S., Doherty, C.P., Cavalleri, G.L., Delanty, N., Kälviäinen, R., Jackson, G.D., Kowalczyk, M., Mascalchi, M., Semmelroch, M., Thomas, R.H., Soltanian-Zadeh, H., Davoodi-Bojd, E., Zhang, J., Lenge, M., Guerrini, R., Bartolini, E., Hamandi, K., Foley, S., Weber, B., Depondt, C., Absil, J., Carr, S.J.A., Abela, E., Richardson, M.P., Devinsky, O., Severino, M., Striano, P., Parodi, C., Tortora, D., Hatton, S.N., Vos, S.B., Duncan, J.S., Galovic, M., Whelan, C.D., Bargalló, N., Pariente, J., Conde-Blanco, E., Vaudano, A.E., Tondelli, M., Meletti, S., Kong, X.Z., Francks, C., Fisher, S.E., Caldairou, B., Ryten, M., Labate, A., Sisodiya, S.M., Thompson, P.M., McDonald, C.R., Bernasconi, A., Bernasconi, N., Bernhardt, B.C., Park, B.-y., Larivière, S., Rodríguez-Cruces, R., Royer, J., Tavakol, S., Wang, Y., Caciagli, L., Caligiuri, M.E., Gambardella, A., Concha, L., Keller, S.S., Cendes, F., Alvim, M.K.M., Yasuda, C., Bonilha, L., Gleichgerrcht, E., Focke, N.K., Kreilkamp, B.A.K., Domin, M., Podewils, F. von, Langner, S., Rummel, C., Rebsamen, M., Wiest, R., Martin, P., Kotikalapudi, R., Bender, B., O’Brien, T.J., Law, M., Sinclair, B., Vivash, L., Kwan, P., Desmond, P.M., Malpas, C.B., Lui, E., Alhusaini, S., Doherty, C.P., Cavalleri, G.L., Delanty, N., Kälviäinen, R., Jackson, G.D., Kowalczyk, M., Mascalchi, M., Semmelroch, M., Thomas, R.H., Soltanian-Zadeh, H., Davoodi-Bojd, E., Zhang, J., Lenge, M., Guerrini, R., Bartolini, E., Hamandi, K., Foley, S., Weber, B., Depondt, C., Absil, J., Carr, S.J.A., Abela, E., Richardson, M.P., Devinsky, O., Severino, M., Striano, P., Parodi, C., Tortora, D., Hatton, S.N., Vos, S.B., Duncan, J.S., Galovic, M., Whelan, C.D., Bargalló, N., Pariente, J., Conde-Blanco, E., Vaudano, A.E., Tondelli, M., Meletti, S., Kong, X.Z., Francks, C., Fisher, S.E., Caldairou, B., Ryten, M., Labate, A., Sisodiya, S.M., Thompson, P.M., McDonald, C.R., Bernasconi, A., Bernasconi, N., and Bernhardt, B.C.

Abstract

Contains fulltext : 252489.pdf (Publisher’s version ) (Open Access)

Published
2022

4. Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy

Author

Park, B-Y, Lariviere, S, Rodriguez-Cruces, R, Royer, J, Tavakol, S, Wang, Y, Caciagli, L, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Alvim, MKM, Yasuda, C, Bonilha, L, Gleichgerrcht, E, Focke, NK, Kreilkamp, BAK, Domin, M, von Podewils, F, Langner, S, Rummel, C, Rebsamen, M, Wiest, R, Martin, P, Kotikalapudi, R, Bender, B, O'Brien, TJ, Law, M, Sinclair, B, Vivash, L, Kwan, P, Desmond, PM, Malpas, CB, Lui, E, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Lenge, M, Guerrini, R, Bartolini, E, Hamandi, K, Foley, S, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Parodi, C, Tortora, D, Hatton, SN, Vos, SB, Duncan, JS, Galovic, M, Whelan, CD, Bargallo, N, Pariente, J, Conde-Blanco, E, Vaudano, AE, Tondelli, M, Meletti, S, Kong, X-Z, Francks, C, Fisher, SE, Caldairou, B, Ryten, M, Labate, A, Sisodiya, SM, Thompson, PM, McDonald, CR, Bernasconi, A, Bernasconi, N, Bernhardt, BC, Park, B-Y, Lariviere, S, Rodriguez-Cruces, R, Royer, J, Tavakol, S, Wang, Y, Caciagli, L, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Alvim, MKM, Yasuda, C, Bonilha, L, Gleichgerrcht, E, Focke, NK, Kreilkamp, BAK, Domin, M, von Podewils, F, Langner, S, Rummel, C, Rebsamen, M, Wiest, R, Martin, P, Kotikalapudi, R, Bender, B, O'Brien, TJ, Law, M, Sinclair, B, Vivash, L, Kwan, P, Desmond, PM, Malpas, CB, Lui, E, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Lenge, M, Guerrini, R, Bartolini, E, Hamandi, K, Foley, S, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Parodi, C, Tortora, D, Hatton, SN, Vos, SB, Duncan, JS, Galovic, M, Whelan, CD, Bargallo, N, Pariente, J, Conde-Blanco, E, Vaudano, AE, Tondelli, M, Meletti, S, Kong, X-Z, Francks, C, Fisher, SE, Caldairou, B, Ryten, M, Labate, A, Sisodiya, SM, Thompson, PM, McDonald, CR, Bernasconi, A, Bernasconi, N, and Bernhardt, BC

Abstract

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine ou

Published
2022

5. The ENIGMA-Epilepsy working group: Mapping disease from large data sets

Author

Sisodiya, SM, Whelan, CD, Hatton, SN, Huynh, K, Altmann, A, Ryten, M, Vezzani, A, Caligiuri, ME, Labate, A, Gambardella, A, Ives-Deliperi, V, Meletti, S, Munsell, BC, Bonilha, L, Tondelli, M, Rebsamen, M, Rummel, C, Vaudano, AE, Wiest, R, Balachandra, AR, Bargallo, N, Bartolini, E, Bernasconi, A, Bernasconi, N, Bernhardt, B, Caldairou, B, Carr, SJA, Cavalleri, GL, Cendes, F, Concha, L, Desmond, PM, Domin, M, Duncan, JS, Focke, NK, Guerrini, R, Hamandi, K, Jackson, GD, Jahanshad, N, Kalviainen, R, Keller, SS, Kochunov, P, Kowalczyk, MA, Kreilkamp, BAK, Kwan, P, Lariviere, S, Lenge, M, Lopez, SM, Martin, P, Mascalchi, M, Moreira, JCV, Morita-Sherman, ME, Pardoe, HR, Pariente, JC, Raviteja, K, Rocha, CS, Rodriguez-Cruces, R, Seeck, M, Semmelroch, MKHG, Sinclair, B, Soltanian-Zadeh, H, Stein, DJ, Striano, P, Taylor, PN, Thomas, RH, Thomopoulos, SI, Velakoulis, D, Vivash, L, Weber, B, Yasuda, CL, Zhang, J, Thompson, PM, McDonald, CR, Sisodiya, SM, Whelan, CD, Hatton, SN, Huynh, K, Altmann, A, Ryten, M, Vezzani, A, Caligiuri, ME, Labate, A, Gambardella, A, Ives-Deliperi, V, Meletti, S, Munsell, BC, Bonilha, L, Tondelli, M, Rebsamen, M, Rummel, C, Vaudano, AE, Wiest, R, Balachandra, AR, Bargallo, N, Bartolini, E, Bernasconi, A, Bernasconi, N, Bernhardt, B, Caldairou, B, Carr, SJA, Cavalleri, GL, Cendes, F, Concha, L, Desmond, PM, Domin, M, Duncan, JS, Focke, NK, Guerrini, R, Hamandi, K, Jackson, GD, Jahanshad, N, Kalviainen, R, Keller, SS, Kochunov, P, Kowalczyk, MA, Kreilkamp, BAK, Kwan, P, Lariviere, S, Lenge, M, Lopez, SM, Martin, P, Mascalchi, M, Moreira, JCV, Morita-Sherman, ME, Pardoe, HR, Pariente, JC, Raviteja, K, Rocha, CS, Rodriguez-Cruces, R, Seeck, M, Semmelroch, MKHG, Sinclair, B, Soltanian-Zadeh, H, Stein, DJ, Striano, P, Taylor, PN, Thomas, RH, Thomopoulos, SI, Velakoulis, D, Vivash, L, Weber, B, Yasuda, CL, Zhang, J, Thompson, PM, and McDonald, CR

Abstract

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.

Published
2022

6. Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression

Author

Lariviere, S, Royer, J, Rodriguez-Cruces, R, Paquola, C, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Yasuda, CL, Bonilha, L, Gleichgerrcht, E, Focke, NK, Domin, M, von Podewills, F, Langner, S, Rummel, C, Wiest, R, Martin, P, Kotikalapudi, R, O'Brien, TJ, Sinclair, B, Vivash, L, Desmond, PM, Lui, E, Vaudano, AE, Meletti, S, Tondelli, M, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Winston, GP, Griffin, A, Singh, A, Tiwari, VK, Kreilkamp, BAK, Lenge, M, Guerrini, R, Hamandi, K, Foley, S, Ruber, T, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Tortora, D, Kaestner, E, Hatton, SN, Vos, SB, Caciagli, L, Duncan, JS, Whelan, CD, Thompson, PM, Sisodiya, SM, Bernasconi, A, Labate, A, McDonald, CR, Bernasconi, N, Bernhardt, BC, Lariviere, S, Royer, J, Rodriguez-Cruces, R, Paquola, C, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Yasuda, CL, Bonilha, L, Gleichgerrcht, E, Focke, NK, Domin, M, von Podewills, F, Langner, S, Rummel, C, Wiest, R, Martin, P, Kotikalapudi, R, O'Brien, TJ, Sinclair, B, Vivash, L, Desmond, PM, Lui, E, Vaudano, AE, Meletti, S, Tondelli, M, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Winston, GP, Griffin, A, Singh, A, Tiwari, VK, Kreilkamp, BAK, Lenge, M, Guerrini, R, Hamandi, K, Foley, S, Ruber, T, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Tortora, D, Kaestner, E, Hatton, SN, Vos, SB, Caciagli, L, Duncan, JS, Whelan, CD, Thompson, PM, Sisodiya, SM, Bernasconi, A, Labate, A, McDonald, CR, Bernasconi, N, and Bernhardt, BC

Abstract

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

Published
2022

8. Contributors

Author

Bhatia, K., primary, Bonilha, L., additional, Brosch, T., additional, Caballero, J., additional, Davatzikos, C., additional, De Craene, M., additional, Dewan, M., additional, Dong, A., additional, Du, L., additional, Duchateau, N., additional, Eavani, H., additional, Frangi, A., additional, Fridriksson, J., additional, Gao, Y., additional, Gaonkar, B., additional, Ge, T., additional, He, T., additional, Huang, J., additional, Honnorat, N., additional, Jian, B., additional, Jiang, X., additional, Keller, S., additional, Kong, R., additional, Li, Y., additional, Liu, M., additional, Liu, T., additional, Min, R., additional, Munsell, B.C., additional, Peng, Z., additional, Piella, G., additional, Rueckert, D., additional, Sabuncu, M.R., additional, Schaefer, A., additional, Shen, D., additional, Shen, L., additional, Smoller, J.W., additional, Sotiras, A., additional, Styner, M., additional, Tam, R., additional, Tang, L.Y.W., additional, Thomas Yeo, B.T., additional, Thompson, P., additional, Tong, T., additional, Varol, E., additional, Wang, J., additional, Weber, B., additional, Wu, G., additional, Xing, F., additional, Xue, Z., additional, Yan, J., additional, Yang, L., additional, Yang, T., additional, Yao, X., additional, Ye, J., additional, Yoo, Y., additional, Zhan, Y., additional, Zhang, D., additional, Zhang, S., additional, Zhang, X., additional, Zhou, X.S., additional, and Zhu, D., additional

Published
2016
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10. Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Author

Gleichgerrcht, E, Munsell, BC, Alhusaini, S, Alvim, MKM, Bargallo, N, Bender, B, Bernasconi, A, Bernasconi, N, Bernhardt, B, Blackmon, K, Caligiuri, ME, Cendes, F, Concha, L, Desmond, PM, Devinsky, O, Doherty, CP, Domin, M, Duncan, JS, Focke, NK, Gambardella, A, Gong, B, Guerrini, R, Hatton, SN, Kalviainen, R, Keller, SS, Kochunov, P, Kotikalapudi, R, Kreilkamp, BAK, Labate, A, Langner, S, Lariviere, S, Lenge, M, Lui, E, Martin, P, Mascalchi, M, Meletti, S, O'Brien, TJ, Pardoe, HR, Pariente, JC, Rao, JX, Richardson, MP, Rodriguez-Cruces, R, Ruber, T, Sinclair, B, Soltanian-Zadeh, H, Stein, DJ, Striano, P, Taylor, PN, Thomas, RH, Vaudano, AE, Vivash, L, von Podewills, F, Vos, SB, Weber, B, Yao, Y, Yasuda, CL, Zhang, J, Thompson, PM, Sisodiya, SM, McDonald, CR, Bonilha, L, Gleichgerrcht, E, Munsell, BC, Alhusaini, S, Alvim, MKM, Bargallo, N, Bender, B, Bernasconi, A, Bernasconi, N, Bernhardt, B, Blackmon, K, Caligiuri, ME, Cendes, F, Concha, L, Desmond, PM, Devinsky, O, Doherty, CP, Domin, M, Duncan, JS, Focke, NK, Gambardella, A, Gong, B, Guerrini, R, Hatton, SN, Kalviainen, R, Keller, SS, Kochunov, P, Kotikalapudi, R, Kreilkamp, BAK, Labate, A, Langner, S, Lariviere, S, Lenge, M, Lui, E, Martin, P, Mascalchi, M, Meletti, S, O'Brien, TJ, Pardoe, HR, Pariente, JC, Rao, JX, Richardson, MP, Rodriguez-Cruces, R, Ruber, T, Sinclair, B, Soltanian-Zadeh, H, Stein, DJ, Striano, P, Taylor, PN, Thomas, RH, Vaudano, AE, Vivash, L, von Podewills, F, Vos, SB, Weber, B, Yao, Y, Yasuda, CL, Zhang, J, Thompson, PM, Sisodiya, SM, McDonald, CR, and Bonilha, L

Abstract

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with ("lesional") and without ("non-lesional") radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68-75%) compared to models to lateralize the side of TLE (56-73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67-75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68-76%) than models that stratified non-lesional patients (53-62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.

Published
2021

15. Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study

Author

Lariviere, S, Rodriguez-Cruces, R, Royer, J, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Yasuda, C, Bonilha, L, Gleichgerrcht, E, Focke, NK, Domin, M, von Podewills, F, Langner, S, Rummel, C, Wiest, R, Martin, P, Kotikalapudi, R, O'Brien, TJ, Sinclair, B, Vivash, L, Desmond, PM, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Lenge, M, Guerrini, R, Bartolini, E, Hamandi, K, Foley, S, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Tortora, D, Hatton, SN, Vos, SB, Duncan, JS, Whelan, CD, Thompson, PM, Sisodiya, SM, Bernasconi, A, Labate, A, McDonald, CR, Bernasconi, N, Bernhardt, BC, Lariviere, S, Rodriguez-Cruces, R, Royer, J, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Yasuda, C, Bonilha, L, Gleichgerrcht, E, Focke, NK, Domin, M, von Podewills, F, Langner, S, Rummel, C, Wiest, R, Martin, P, Kotikalapudi, R, O'Brien, TJ, Sinclair, B, Vivash, L, Desmond, PM, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Lenge, M, Guerrini, R, Bartolini, E, Hamandi, K, Foley, S, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Tortora, D, Hatton, SN, Vos, SB, Duncan, JS, Whelan, CD, Thompson, PM, Sisodiya, SM, Bernasconi, A, Labate, A, McDonald, CR, Bernasconi, N, and Bernhardt, BC

Abstract

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.

Published
2020

16. Temporal lobe regions essential for preserved picture naming after left temporal epilepsy surgery.

Author

Binder, JR, Tong, J-Q, Pillay, SB, Conant, LL, Humphries, CJ, Raghavan, M, Mueller, WM, Busch, RM, Allen, L, Gross, WL, Anderson, CT, Carlson, CE, Lowe, MJ, Langfitt, JT, Tivarus, ME, Drane, DL, Loring, DW, Jacobs, M, Morgan, VL, Allendorfer, JB, Szaflarski, JP, Bonilha, L, Bookheimer, S, Grabowski, T, Vannest, J, Swanson, SJ, fMRI in Anterior Temporal Epilepsy Surgery (FATES) study, Binder, JR, Tong, J-Q, Pillay, SB, Conant, LL, Humphries, CJ, Raghavan, M, Mueller, WM, Busch, RM, Allen, L, Gross, WL, Anderson, CT, Carlson, CE, Lowe, MJ, Langfitt, JT, Tivarus, ME, Drane, DL, Loring, DW, Jacobs, M, Morgan, VL, Allendorfer, JB, Szaflarski, JP, Bonilha, L, Bookheimer, S, Grabowski, T, Vannest, J, Swanson, SJ, and fMRI in Anterior Temporal Epilepsy Surgery (FATES) study

Abstract

OBJECTIVE: To define left temporal lobe regions where surgical resection produces a persistent postoperative decline in naming visual objects. METHODS: Pre- and postoperative brain magnetic resonance imaging data and picture naming (Boston Naming Test) scores were obtained prospectively from 59 people with drug-resistant left temporal lobe epilepsy. All patients had left hemisphere language dominance at baseline and underwent surgical resection or ablation in the left temporal lobe. Postoperative naming assessment occurred approximately 7 months after surgery. Surgical lesions were mapped to a standard template, and the relationship between presence or absence of a lesion and the degree of naming decline was tested at each template voxel while controlling for effects of overall lesion size. RESULTS: Patients declined by an average of 15% in their naming score, with wide variation across individuals. Decline was significantly related to damage in a cluster of voxels in the ventral temporal lobe, located mainly in the fusiform gyrus approximately 4-6 cm posterior to the temporal tip. Extent of damage to this region explained roughly 50% of the variance in outcome. Picture naming decline was not related to hippocampal or temporal pole damage. SIGNIFICANCE: The results provide the first statistical map relating lesion location in left temporal lobe epilepsy surgery to picture naming decline, and they support previous observations of transient naming deficits from electrical stimulation in the basal temporal cortex. The critical lesion is relatively posterior and could be avoided in many patients undergoing left temporal lobe surgery for intractable epilepsy.

Published
2020

19. Medial temporal lobe atrophy in patients with refractory temporal lobe epilepsy

Author

Bonilha, L., Kobayashi, E., Rorden, C., Cendes, F., and Li, L.M.

Subjects
Temporal lobes -- Abnormalities -- Injuries, Atrophy -- Diagnosis -- Causes of, Epilepsy -- Abnormalities -- Diagnosis, Health, Psychology and mental health, Diagnosis, Injuries, Abnormalities, Causes of
Abstract

J Neurol Neurosurg Psychiatry 2003;74:1627-1630 Objective: The objective of this study was to assess the volumes of medial temporal lobe structures using high resolution magnetic resonance images from patients with [...]

Published
2003

25. Neuroimaging and connectomics of drug-resistant epilepsy at multiple scales: From focal lesions to macroscale networks

Author

Tavakol, S, Royer, J, Lowe, AJ, Bonilha, L, Tracy, JI, Jackson, GD, Duncan, JS, Bernasconi, A, Bernasconi, N, Bernhardt, BC, Tavakol, S, Royer, J, Lowe, AJ, Bonilha, L, Tracy, JI, Jackson, GD, Duncan, JS, Bernasconi, A, Bernasconi, N, and Bernhardt, BC

Abstract

Epilepsy is among the most common chronic neurologic disorders, with 30%-40% of patients having seizures despite antiepileptic drug treatment. The advent of brain imaging and network analyses has greatly improved the understanding of this condition. In particular, developments in magnetic resonance imaging (MRI) have provided measures for the noninvasive characterization and detection of lesions causing epilepsy. MRI techniques can probe structural and functional connectivity, and network analyses have shaped our understanding of whole-brain anomalies associated with focal epilepsies. This review considers the progress made by neuroimaging and connectomics in the study of drug-resistant epilepsies due to focal substrates, particularly temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal lobe epilepsies associated with malformations of cortical development. In these disorders, there is evidence of widespread disturbances of structural and functional connectivity that may contribute to the clinical and cognitive prognosis of individual patients. It is hoped that studying the interplay between macroscale network anomalies and lesional profiles will improve our understanding of focal epilepsies and assist treatment choices.

Published
2019

26. Pre-articulatory electrical activity associated with correct naming in individuals with aphasia

Author

Singh, T., Phillip, L., Behroozmand, R., Gleichgerrcht, E., Piai, V., Fridriksson, J., Bonilha, L., Singh, T., Phillip, L., Behroozmand, R., Gleichgerrcht, E., Piai, V., Fridriksson, J., and Bonilha, L.

Abstract

Contains fulltext : 184160.pdf (publisher's version ) (Closed access), Picture naming is a language task that involves multiple neural networks and is used to probe aphasia-induced language deficits. The pattern of neural activation seen in healthy individuals during picture naming is disrupted in individuals with aphasia, but the time-course of the disruption remains unclear. Specifically, it remains unclear which anatomical and temporal aspects of neural processing are necessary for correct naming. Here, we tested two individuals with stroke induced aphasia, and compared the differences in the event-related potentials (ERPs) and current sources when they made correct vs. erroneous responses during picture naming. The pre-articulatory ERP activity was significantly different between the two responses. Current source analysis revealed that the ability to recruit left temporal and frontal areas within a 300-550 ms time window after stimulus onset contributed to correct responses. These results suggest that targeted neuromodulation in these areas could lead to better treatment outcomes in patients with aphasia.

Published
2018

30. Damage to left anterior temporal cortex predicts impairment of complex syntactic processing: A lesion‐symptom mapping study

Author

Magnusdottir, S., Fillmore, P., den Ouden, D.B., Hjaltason, H., Rorden, C., Kjartansson, O., Bonilha, L., and Fridriksson, J.

Subjects
Adult, Aged, 80 and over, Male, Brain Mapping, Language Disorders, Language Tests, Auditory Perceptual Disorders, Iceland, Linguistics, Middle Aged, Magnetic Resonance Imaging, Temporal Lobe, Stroke, Diffusion Magnetic Resonance Imaging, Parietal Lobe, Humans, Female, Occipital Lobe, Comprehension, Research Articles, Psychomotor Performance, Aged
Abstract

Sentence processing problems form a common consequence of left‐hemisphere brain injury, in some patients to such an extent that their pattern of language performance is characterized as “agrammatic”. However, the location of left‐hemisphere damage that causes such problems remains controversial. It has been suggested that the critical site for syntactic processing is Broca's area of the frontal cortex or, alternatively, that a more widely distributed network is responsible for syntactic processing. The aim of this study was to identify brain regions that are required for successful sentence processing. Voxel‐based lesion‐symptom mapping (VLSM) was used to identify brain regions where injury predicted impaired sentence processing in 50 native speakers of Icelandic with left‐hemisphere stroke. Sentence processing was assessed by having individuals identify which picture corresponded to a verbally presented sentence. The VLSM analysis revealed that impaired sentence processing was best predicted by damage to a large left‐hemisphere temporo‐parieto‐occipital area. This is likely due to the multimodal nature of the sentence processing task, which involves auditory and visual analysis, as well as lexical and syntactic processing. Specifically impaired processing of noncanonical sentence types, when compared with canonical sentence processing, was associated with damage to the left‐hemisphere anterior superior and middle temporal gyri and the temporal pole. Anterior temporal cortex, therefore, appears to play a crucial role in syntactic processing, and patients with brain damage to this area are more likely to present with receptive agrammatism than patients in which anterior temporal cortex is spared. Hum Brain Mapp 34:2715–2723, 2013. © 2012 Wiley Periodicals, Inc.

Published
2012

35. Hippocampal tissue of patients with refractory temporal lobe epilepsy is associated with astrocyte activation, inflammation, and altered expression of channels and receptors

Author

Das, A., primary, Wallace, G.C., additional, Holmes, C., additional, McDowell, M.L., additional, Smith, J.A., additional, Marshall, J.D., additional, Bonilha, L., additional, Edwards, J.C., additional, Glazier, S.S., additional, Ray, S.K., additional, and Banik, N.L., additional

Published
2012
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50. Antiepileptic drugs: a study of 1028 cases registered by the Sao Paulo Intoxication Control Center

Author

Bonilha, L., Collares, C.F., do Amaral, D.A., Dantas Barcia, S., de Almeida Oliveira, A.M.A., and Li, L.M.

Abstract

Purpose:To illustrate the profile of the cases of intoxications by antiepileptic drugs (AEDs) registered within a large urban area during the period of 1 year.Methods:A cross-sectional observational study was performed in the Intoxication Control Center of the Sao Paulo City Hospital. We evaluated 6535 medical consults of intoxication cases involving prescription and over-the-counter drugs in 2001. We selected and analyzed the cases involving AEDs. Statistical analysis was performed in order to evaluate the frequency of different drug types and the circumstance of drug exposure.Results:The most frequently observed AEDs were phenobarbital, carbamazepine, diazepam, and clonazepam. The frequency of intoxication cases among different age groups did not significantly differ according to the drug type. The circumstances involving AEDs intoxication were analogous to the circumstances of the cases of intoxication involving all other medications (p>0.05).Conclusions:There are a large number of intoxications involving AEDs. Imposing a restriction access to AEDs can be deleterious to patients that depend on AEDs, however, a strict program of AEDs distribution should be considered to reduce the cases of AED intoxication.

Published
2005
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